**Morphostatic Speciation within the Dagger Nematode** *Xiphinema hispanum-***Complex Species (Nematoda: Longidoridae)**

**Antonio Archidona-Yuste 1,\* , Ruihang Cai 2,3, Carolina Cantalapiedra-Navarrete <sup>2</sup> , José A. Carreira <sup>4</sup> , Ana Rey <sup>5</sup> , Benjamín Viñegla <sup>4</sup> , Gracia Liébanas <sup>4</sup> , Juan E. Palomares-Rius <sup>2</sup> and Pablo Castillo <sup>2</sup>**


http://zoobank.org:pub:6D60BC11-B301-42EF-9301-6E42A8E93B9C Received: 23 October 2020; Accepted: 23 November 2020; Published: 26 November 2020

**Abstract:** Dagger nematodes of the genus *Xiphinema* include a remarkable group of invertebrates of the phylum Nematoda comprising ectoparasitic animals of many wild and cultivated plants. Damage is caused by direct feeding on root cells and by vectoring nepoviruses that cause diseases on several crops. Precise identification of *Xiphinema* species is critical for launching appropriate control measures. We deciphered the cryptic diversity of the *Xiphinema hispanum*-species complex applying integrative taxonomical approaches that allowed us to verify a paradigmatic example of the morphostatic speciation and the description of a new species, *Xiphinema malaka* sp. nov. Detailed morphological, morphometrical, multivariate and genetic studies were carried out, and mitochondrial and nuclear haploweb analyses were used for species delimitation of this group. The new species belongs to morphospecies Group 5 from the *Xiphinema* non*americanum*-group species. *D2-D3*, *ITS1*, partial *18S*, and partial *coxI* regions were used for inferring the phylogenetic relationships of *X. malaka* sp. nov. with other species within the genus *Xiphinema*. Molecular analyses showed a clear species differentiation not paralleled in morphology and morphometry, reflecting a clear morphostatic speciation. These results support the hypothesis that the biodiversity of dagger nematodes in southern Europe is greater than previously assumed.

**Keywords:** Bayesian inference; cryptic species; *coxI*; *D2-D3* expansion domains of *28S* rRNA-gene; integrative taxonomy; principal component analysis

#### **1. Introduction**

Plant-parasitic nematodes (PPN) are characterized by the presence of a stylet used for root tissue penetration, comprise about 15% of the total number of nematode species currently known, of which over 4100 species have been identified as PPN [1,2]. Annual crop losses caused by PPN are estimated to be about 8–15% of total crop production worldwide [3,4]. Accurate identification of PPN is essential for the selection of appropriate control measures against plant pathogenic species, as well as for a reliable method allowing distinction between species under quarantine or regulatory strategies and a better understanding of their implications in pest control and soil ecology [5,6]. PPN species have been defined historically based on morphological characteristics [7,8]. However, the adoption of molecular techniques in nematode taxonomy has revealed unexpected genetic diversity within species throughout the phylum Nematoda [9]. This has been especially accurate for the family Longidoridae, a large group of ectoparasitic nematodes feeding from the root tip zone to the hairy root region, and characterized by a substantial intra and interspecific homogeneity of the morphometric characters used for species discrimination [1,6,10,11]. Use of molecular data in species identification of dagger and needle nematodes over the last three decades has indicated that many widespread species actually comprise multiple genetically divergent and morphologically similar cryptic species [6,11–13]. Complexes of cryptic species often result from nonecological speciation in which diversification is not accompanied by apparent ecological or morphological separation in traditional quantitative traits [14].

The genus *Xiphinema* is one of the most diversified group species of longidorid nematodes with more than 280 valid species [5,6,11,15]. The ecological and phytopathological importance of this group of nematodes lies in its wide range of host plants and cosmopolitan distribution [5,11], but some species of this genus are vectors of several important plant viruses (genus *Nepovirus*, family Comoviridae) that cause significant damage to a wide range of crops [10,16]. Considering the great diversity of this group, the genus *Xiphinema* was divided into two different species groups [5,17,18]: (i) the *Xiphinema americanum*-group comprising a complex of about 60 species [15,17]; and (ii) the *Xiphinema* non*americanum*-group which comprises a complex of more than 220 species [5,6,19]. Later, this group was divided into eight morphospecies groups for helping identification [18]. However, some cryptic species and species complexes within *Xiphinema* have been recently revealed based on integrative taxonomical approaches, including morphometric multivariate methods, genetic analyses based on ribosomal and mitochondrial DNA (rDNA and mtDNA, respectively) and species delimitation (haplonet tools) [6,11,20,21]. A paradigmatic example of these species complexes comprises the *Xiphinema hispanum*-complex, *viz*. didelphic *Xiphinema* species from the Iberian Peninsula characterized by a rounded tail in females with or without an inconspicuous bulge projecting slightly ventrally and a uterus showing spiniform structures [22]. The cryptic diversity of this species complex has been deciphered by our team over the last ten years applying integrative taxonomical approaches that allowed us to verify these species as valid, and the recent description of a new species, *X. subbaetense* [11,20]. Recent studies on this species complex clearly separated three species (*X. adenohystherum*, *X. hispanum* and *X. subbaetense*) revealing high levels of genetic diversity within them that showed little morphological differentiation [11]. In new nematode surveys carried out in natural areas in the provinces of Málaga and Almería, Andalusia, southern Spain, we have detected nine unidentified *Xiphinema* isolates resembling *X. hispanum*-complex morphology. Detailed morphological and morphometrical observations using light microscopy indicated that these isolates appeared undistinguishable from *X. hispanum* complex species, a fact which prompted us to undertake comprehensive multivariate and genetic analyses, compared with previous reported data, to decipher this taxonomic conundrum.

Morphostatic evolution can be defined as genetic modifications, and even complete speciation events, which are not reflected in morphology, often being a result of nonadaptive radiation marked by the rapid proliferation of species without ecological differentiation [23,24]. Although no data have yet been specifically mentioned in Nematoda, morphostatic evolution seems not to be a rare phenomenon in longidorids based on the numerous complexes and cryptic species documented [6,11–13,15,20,25]. In Longidoridae, it is very common that molecular divergences among species are not reflected in morphological or morphometric traits, which conforms a morphostatic model of evolution with numerous cryptic species within this group [6,11,13,15,20,21,25,26].

In this context, we investigated (1) the existence of a new cryptic species within the *X. hispanum*-complex confirming a morphostatic speciation in this group using an integrative species delineation approach

based on multivariate morphometric analysis and haplonet mitochondrial and nuclear haploweb tools; (2) a new species of the genus *Xiphinema* (*Xiphinema malaka* sp. nov.) described through integrative methods based on the combination of morphological, morphometric and molecular data; and (3) phylogenetic analyses based on *D2-D3* expansion domains of the *28S* rRNA gene, *ITS1*, the partial *18S* rRNA gene, and the partial mitochondrial *coxI* gene sequences to clarify the relationships of the new *Xiphinema* species. haploweb tools; (2) a new species of the genus *Xiphinema* (*Xiphinema malaka* sp. nov.) described through integrative methods based on the combination of morphological, morphometric and molecular data; and (3) phylogenetic analyses based on *D2-D3* expansion domains of the *28S* rRNA gene, *ITS1*, the partial *18S* rRNA gene, and the partial mitochondrial *coxI* gene sequences to clarify the relationships of the new *Xiphinema* species.

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#### **2. Results 2. Results**

Species boundaries within the *Xiphinema* complex included in this research (Figure 1) were based on the integrative application of morphological, morphometric and molecular methods to unravel potential cryptic species diversity (Table 1). Species delimitation was carried out using two independent approaches based on morphometric (multivariate analysis) and molecular data using ribosomal and mitochondrial sequences (haplonet). Multivariate morphometric and haplonet methods were performed on the nine studied isolates including previous isolates from the *X. hispanum*-complex to verify species identifications. The integration of this procedure with the analysis of nematode morphology allowed us to verify *Xiphinema malaka* sp. nov. as a valid new species within the *X. hispanum* cryptic complex. Additionally, we maintained a consensus approach for the different species delimitation methods, including concordant results in phylogenetic trees inferred from nuclear and mitochondrial markers and/or different morphological or morphometric characteristics. Species boundaries within the *Xiphinema* complex included in this research (Figure 1) were based on the integrative application of morphological, morphometric and molecular methods to unravel potential cryptic species diversity (Table 1). Species delimitation was carried out using two independent approaches based on morphometric (multivariate analysis) and molecular data using ribosomal and mitochondrial sequences (haplonet). Multivariate morphometric and haplonet methods were performed on the nine studied isolates including previous isolates from the *X. hispanum*-complex to verify species identifications. The integration of this procedure with the analysis of nematode morphology allowed us to verify *Xiphinema malaka* sp. nov. as a valid new species within the *X. hispanum* cryptic complex. Additionally, we maintained a consensus approach for the different species delimitation methods, including concordant results in phylogenetic trees inferred from nuclear and mitochondrial markers and/or different morphological or morphometric characteristics.

**Figure 1.** Geographic distribution of *Xiphinema hispanum*-complex species and locations of sampling sites of which the recovered isolates of the new species were characterized morphometrically and **Figure 1.** Geographic distribution of *Xiphinema hispanum*-complex species and locations of sampling sites of which the recovered isolates of the new species were characterized morphometrically and molecularly. Arrow indicates the location of Andalusia in the Iberian Peninsula.

molecularly. Arrow indicates the location of Andalusia in the Iberian Peninsula.


**Table 1.** Isolates sampled for *Xiphinema malaka* sp. nov. from several localities of Málaga and Almería provinces (Southern Spain), and *Xiphinema adenohystherum* sequences used in this study.




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#### *2.1. Multivariate Morphometric Analysis*

In principal component analysis (PCA), the first three components (sum of squares (SS) loadings>1) accounted for 65.1% of the total variance in the morphometric characteristics of the *X. hispanum-*complex (Table 2). The eigenvalues for each character were used to interpret the biological meaning of the factors. First, the principal component 1 (PC1) was mainly dominated by a stylet with a high positive correlation (eigenvalue = 0.523). PC2 was mainly dominated by high negative correlation for the vulva position (eigenvalue = −0.547) as well as a high positive correlation for the a ratio (eigenvalue = 0.482) (Table 2). This component was, therefore, related with the overall nematode size and shape. Finally, PC3 was mainly dominated by the highest positive correlation found for the c' ratio and lower, but also high, positive correlation for the hyaline region length (eigenvalues = 0.774 and 0.458, respectively). This component was then related with tail shape. Overall, these results suggest that all of the extracted PCs were related to the overall size and shape of nematode isolates. The results of the PCA were represented graphically in Cartesian plots in which isolates of the *X. hispanum-*complex were projected on the plane of the *x*- and *y*-axes, respectively, as pairwise combinations of components 1 to 3 (Figure 2). In the graphic representation of the *X. hispanum-*complex, and with the exception of *X. adenohystherum*, we observed that the specimens of all species were projected showing an expanded distribution along the plane for all the projected combinations of the components. One reason might be the wide morphometric variation detected in these species (Tables 3 and 4) [6,11]. As a consequence, we did not detect a clear separation amongst species within the *X. hispanum-*complex, all the specimens being projected at random for all the projected combinations. These patterns suggest a clear example of morphostatic speciation within the *X. hispanum-*complex. However, it should be noted that when projected on the plane of the combinations of PC1-2 and PC2-3, almost all specimens of *X. malaka* sp. nov. and *X. subbaetense* were separated among them (Figure 2). This graphical separation was shown by the projection of PC2 (dominated by the V and a ratios). This graphical separation is due to the variation found in the ratio a among these species, as pointed out below. A minimum spanning tree (MST) superimposed on the plot of the first three principal components showed the same patterns observed with PCA, that is, not clear separation amongst species within the *X. hispanum*-complex (Figure 2).


**Table 2.** Eigenvectors and SS loadings of factors derived from nematode morphometric characters for *Xiphinema hispanum-*complex (*Xiphinema malaka* sp. nov., *Xiphinema adenohystherum*, *Xiphinema hispanum*, *Xiphinema subbaetense*).

<sup>a</sup> Based on 41 female specimens of *Xiphinema malaka* sp. nov. from seven isolate samples, 25 female specimens of *Xiphinema subbaetense* from two isolate samples, eight female specimens of *Xiphinema adenohystherum* from a isolate sample, and 11 female specimens of *Xiphinema hispanum* from a isolate sample. Values of morphometric variables 1 to 3 (eigenvector > 0.458) are underlined. All isolates were molecularly identified and located at southern Spain. The c' ratio was excluded by the multicollinearity test and then, it was not included in the multivariate analysis for the *Xiphinema hispanum*-complex; <sup>b</sup> Morphological and diagnostic characters according to Jairajpuri and Ahmad [7] with some inclusions. a = body length/maximum body width; c' = tail length/body width at anus; d = anterior to guiding ring/body diam. at lip region; d' = body diameter at guiding ring/body diameter at lip region; Oa-gr = Oral aperture-guiding ring distance; V = (distance from anterior end to vulva/body length) × 100.

vulva/body length) × 100.

with some inclusions. a = body length/maximum body width; c' = tail length/body width at anus; d

**Figure 2.** Principal component analysis on morphometric characters to characterize *Xiphinema hispanum*complex with a superimposed minimum spanning tree (based on Euclidean distance).


**Table 3.** Morphometrics of paratypes for *Xiphinema malaka* sp. nov. from maritime pine (*Pinus pinaster* Aiton) at Canillas de Albaida (Málaga province) southern Spain <sup>a</sup> .

<sup>a</sup> Measurements are in <sup>µ</sup>m and in the form: mean <sup>±</sup> standard deviation (range); <sup>b</sup> <sup>a</sup> <sup>=</sup> body length/maximum body width; b = body length/pharyngeal length; c = body length/tail length; c' = tail length/body width at anus; d = anterior to guiding ring/body diam. at lip region; d'= body diam. at guiding ring/body diam. at lip region; V = (distance from anterior end to vulva/body length) × 100; J = hyaline tail region length; G1 = (anterior genital branch length/body length) × 100; G2 = (posterior genital branch length/body length) × 100.

#### *2.2. Mitochondrial Haplonet and Nuclear Haploweb Networks*

Species delimitation using haplonet methods in *X. hispanum-*complex species contained 75 sequences (35 sequences from *X. malaka* sp. nov., four sequences from *X. adenohystherum*, 13 sequences from *X. hispanum*, and 23 sequences from *X. subbaetense*) with 13, 3, 4, and 3 different haplotypes and several heterozygous individuals, respectively (Table 1, Figure 3A). The TCS haplotype analysis inferred from the *D2-D3* region showed four well-differentiated haplogroups corresponding to four different main lineages (*X. adenohystherum*, *X. hispanum*, *X. malaka* sp. nov., and *X. subbaetense*) (Figure 3A). *Xiphinema malaka* sp. nov. comprised a higher diversity in Mountain Almijara (SA, with nine haplotypes) than that detected in Mountain Nieves (SN 2 haplotypes), one haplotype in Tabernas, and one haplotype (Hm3) jointly detected in SA and SN (Figure 3A).



.




 Measurements are in µm and in the form: mean ± standard deviation (range); b a = body length/maximum body width; b = body length/pharyngeal length; c = body length/tail length; c' = tail length/body width at anus; d = anterior to guiding ring/body diam. at lip region; d'= body diam. at guiding ring/body diam. at lip region; V = (distance from anterior end to vulva/body length) × 100; J = hyaline tail region length; G1 = (anterior genital branch length/body length) × 100; G2 = (posterior genital branch length/body length) × 100.

*2.3. Molecular Characterization* 

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**Figure 3.** (**A**). Construction of *D2-D3* haploweb of *Xiphinema malaka* sp. nov. (**B**). *coxI* haplonet of *Xiphinema malaka* sp. nov. Coloured circles represent haplotypes and their diameter are proportional to the number of individuals sharing the same haplotype. Black short lines on the branches indicate the number of mutated positions in the alignment that separate each haplotype. Co-occurring haplotypes are enclosed in black dashes. (**C**). Phylogenetic relationships within the genus *Xiphinema*. Bayesian 50% majority rule consensus tree as inferred from D2 and D3 expansion domains of *28S* rRNA sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G) +. Posterior probabilities more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. Some branches were collapsed for improving readability of *Xiphinema* species. Abbreviations: Ha = *X. adenohystherum* haplotypes; Hh = *X. hispanum* haplotypes; Hm = *X. malaka* sp. nov. haplotypes; Hs = *X. subbaetense* haplotypes; Hzs = *X. subbaetense* heterozygous specimens. SA = Mountain of Almijara and Tejeda; SN = Mountain of Nieves. **Figure 3.** (**A**). Construction of *D2-D3* haploweb of *Xiphinema malaka* sp. nov. (**B**). *coxI* haplonet of *Xiphinema malaka* sp. nov. Coloured circles represent haplotypes and their diameter are proportional to the number of individuals sharing the same haplotype. Black short lines on the branches indicate the number of mutated positions in the alignment that separate each haplotype. Co-occurring haplotypes are enclosed in black dashes. (**C**). Phylogenetic relationships within the genus *Xiphinema*. Bayesian 50% majority rule consensus tree as inferred from D2 and D3 expansion domains of *28S* rRNA sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G) +. Posterior probabilities more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. Some branches were collapsed for improving readability of *Xiphinema* species. Abbreviations: Ha = *X. adenohystherum* haplotypes; Hh = *X. hispanum* haplotypes; Hm = *X. malaka* sp. nov. haplotypes; Hs = *X. subbaetense* haplotypes; Hzs = *X. subbaetense* heterozygous specimens. SA = Mountain of Almijara and Tejeda; SN = Mountain of Nieves.

The amplification of *D2-D3* expansion domains of *28S* rRNA, *ITS1* rRNA, the partial *18S* rRNA, and partial *coxI* genes, yielded single fragments of ~900 bp, 1100 bp, 1800 bp, and 500 bp, respectively, based on gel electrophoresis. *D2-D3* for *X. malaka* sp. nov. (MT584052–MT584085) showed a low

However, in *coxI* haplonet (Figure 3B), six different haplotypes of *X. malaka* sp. nov. were detected, three in SN and three in SA. One from SA shared the same haplotype with the Tabernas isolate, and this haplotype kept a far molecular distance with the other two haplotypes from SA. It was worth noting that the number of *D2-D3* haplotypes of *X. malaka* sp. nov. was higher than *coxI* haplotypes (13 vs. 6), but there were more mutations between these *coxI* haplotypes than *D2-D3* haplotypes (Figure 3A,B). Besides, *X. subbaetense* also comprised more haplotypes in the *D2-D3* haplonet than the *coxI* haplonet (11 vs. 2); the situation of *X. hispanum*, *X. adenohystherum* were the same as previously described by Cai et al. [11].

#### *2.3. Molecular Characterization*

The amplification of *D2-D3* expansion domains of *28S* rRNA, *ITS1* rRNA, the partial *18S* rRNA, and partial *coxI* genes, yielded single fragments of ~900 bp, 1100 bp, 1800 bp, and 500 bp, respectively, based on gel electrophoresis. *D2-D3* for *X. malaka* sp. nov. (MT584052–MT584085) showed a low intraspecific variability with 1–7 different nucleotides and 0 indels (99% similarity). The molecular diversity of this marker within SA (1–7 nucleotides, 0 indels) and SN (2–3 nucleotides, 0 indels) isolates was similar among them and differed from the closest related species, *X. hispanum* (KX244905, MT039125–MT039134) by 20–21 different nucleotides and 1–2 indels (97% similarity), *X. subbaetense* (MT039104–MT039124) by 22–25 different nucleotides and 2–3 indels (97% similarity), and from *X. adenohystherum* (KC567164, KX244898, GU725075, KX244897) by 29–42 different nucleotides and 3 indels (96% similarity).

The *ITS1* region for *X. malaka* sp. nov. showed an intraspecific variability with 26–39 different nucleotides and 4–10 indels (96%–98% similarity). The molecular diversity of this marker within SA (18–24 nucleotides, 1–4 indels) and SN (26–29 nucleotides, 4 indels) isolates was also similar among them. *ITS1* for *X. malaka* sp. nov. (MT584088-MT584099) differed from the closest related species, *X. subbaetense*(MT026293–MT026295) by 132–136 different nucleotides and 28–29 indels (88% similarity), *X. hispanum* (GU725061) by 84–142 different nucleotides and 22–38 indels (87–90% similarity), and from *X. adenohystherum* (GU725063, MT584100–MT584102) by 133–139 different nucleotides and 40–45 indels (87–88% similarity).

For the *18S* rRNA, two new identical sequences for *X. malaka* sp. nov. (MT584086–MT584087) were obtained in this study and both of them showed very high similarity values with other accessions from *Xiphinema* spp. deposited in GenBank, being 98–99% similar. From the closet related species they differed by 1–2 nucleotides and 0 indels from *X. subbaetense* (MT039135–MT039140), *X. adenohystherum* (GU725084) by two nucleotides different and 0 indels, and *X. hispanum* (GU725083) by one nucleotide different and 0 indels. Finally, thirteen new *coxI* sequences for *X. malaka* sp. nov. (MT580263–MT580274) were deposited in GenBank in this study. This gene showed an intraspecific variability with 3–48 different nucleotides and 0 indels (88–99% similarity). The molecular diversity of this marker within SA (0–2 nucleotides, 0 indels) and SN (0–9 nucleotides, 0 indels) isolates was similar among them. *coxI* for *X. malaka* sp. nov. (MT580263–MT580274) differed from the closest related species, *X. subbaetense* (MT040280–MT010300) by 59–66 different nucleotides and 0 indels (82% similarity), *X. hispanum* (KY816614, MT040301-MT040305) by 51–78 different nucleotides and no indels (78–81% similarity), and from *X. adenohystherum* (KY816588–KY816592) by 58–65 different nucleotides and no indels (82–85% similarity).

#### *2.4. Phylogenetic Relationships*

Phylogenetic relationships among *Xiphinema* species inferred from analyses of *D2-D3* expansion domains of *28S* rRNA, *ITS1*, the partial *18S* rRNA and the partial *coxI* mtDNA gene sequences using BI are shown in Figures 3C, 4, 5 and 6, respectively. The phylogenetic trees generated with the nuclear and mitochondrial markers included 136, 49, 65 and 95 sequences with 747, 1106, 1547 and 372 positions in length, respectively (Figures 3C, 4, 5 and 6). The *D2-D3* tree of *Xiphinema* spp. showed a well-supported clade (PP = 1.00), including 10 species from morphospecies Groups 5 and 6, seven of

them belonging to morphospecies Group 5 and three to Group 6, all of them reported from the Iberian peninsula, and included *X. malaka* sp. nov. (MT584052–MT584085). All other clades followed the same pattern as previous studies. *Xiphinema malaka* sp. nov. was phylogenetically related with *X. hispanum*, *X. celtiense* and *X. cohni* in a moderately supported clade (PP = 0.88), but clearly separate from all of them (Figure 3C). *Plants* **2020**, *9*, x FOR PEER REVIEW 11 of 30 Finally, the phylogenetic relationships of *Xiphinema* species inferred from analysis of partial *coxI* gene sequences showed several clades that were not well defined (Figure 6). *Xiphinema malaka* sp. nov. (MT580263-MT580274) was phylogenetically related to *X. hispanum*-complex species in a low

supported clade (PP = 0.65), but clearly separate from all of them (Figure 6).

**Figure 4.** Phylogenetic relationships of *Xiphinema malaka* sp. nov. within the genus *Xiphinema*. Bayesian 50% majority-rule consensus trees as inferred from *ITS1* sequence alignments under transition model with a proportion of invariable sites and a rate of variation across sites (TIM2 + I + G). Posterior probabilities more than 70% are given for appropriate clades. Newly obtained sequences in this study are in bold letters, and each colour is associated with each species of the complex. **Figure 4.** Phylogenetic relationships of *Xiphinema malaka* sp. nov. within the genus *Xiphinema*. Bayesian 50% majority-rule consensus trees as inferred from *ITS1* sequence alignments under transition model with a proportion of invariable sites and a rate of variation across sites (TIM2 + I + G). Posterior probabilities more than 70% are given for appropriate clades. Newly obtained sequences in this study are in bold letters, and each colour is associated with each species of the complex.

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**Figure 5.** Phylogenetic relationships of *Xiphinema malaka* sp. nov. within the genus *Xiphinema*. Bayesian 50% majority-rule consensus trees as inferred from *18S* sequence alignments under the GTR + I + G model. Posterior probabilities more than 70% are given for appropriate clades. Newly obtained sequences in this study are in bold letters. **Figure 5.** Phylogenetic relationships of *Xiphinema malaka* sp. nov. within the genus *Xiphinema*. Bayesian 50% majority-rule consensus trees as inferred from *18S* sequence alignments under the GTR + I + G model. Posterior probabilities more than 70% are given for appropriate clades. Newly obtained sequences in this study are in bold letters.

Difficulties were experienced with alignment of the ITS1 sequences due to scarce similarity. Thus, only related sequences were used for phylogeny. The 50% majority rule consensus *ITS1* BI tree showed several clades low to moderately supported (Figure 4). *Xiphinema malaka* sp. nov. was phylogenetically related to *X. adenohystherum* and *X. iznajarense* in a moderately supported clade (PP = 0.92), but clearly separate from all of them (Figure 4).

The 50% majority rule consensus *18S* rRNA gene BI tree showed several major clades (Figure 5). Phylogenetic inferences based on *18S* suggest that *X. malaka* sp. nov. was related to other species of the *X. hispanum*-complex in a moderately supported clade (PP = 0.91), together with other species such as *X. barense*, *X. celtiense*, *X. cohni*, *X. gersoni*, *X. iznajarense*, *X. mengibarense*, and *X. sphaerocephalum* (Figure 5).

Finally, the phylogenetic relationships of *Xiphinema* species inferred from analysis of partial *coxI* gene sequences showed several clades that were not well defined (Figure 6). *Xiphinema malaka* sp. nov. (MT580263-MT580274) was phylogenetically related to *X. hispanum*-complex species in a low supported clade (PP = 0.65), but clearly separate from all of them (Figure 6).

**Figure 6.** Phylogenetic relationships of *Xiphinema malaka* sp. nov. within the genus *Xiphinema*. Bayesian 50% majority-rule consensus trees as inferred from cytochrome c oxidase subunit I (*coxI*) mtDNA gene sequence alignments under the GTR + I + G model. Posterior probabilities more than 70% are given for appropriate clades. Newly obtained sequences in this study are in bold letters, and each colour is associated with each species of the complex. **Figure 6.** Phylogenetic relationships of *Xiphinema malaka* sp. nov. within the genus *Xiphinema*. Bayesian 50% majority-rule consensus trees as inferred from cytochrome c oxidase subunit I (*coxI*) mtDNA gene sequence alignments under the GTR + I + G model. Posterior probabilities more than 70% are given for appropriate clades. Newly obtained sequences in this study are in bold letters, and each colour is associated with each species of the complex.

#### *2.5. Morphology and Morphometry of Xiphinema malaka* sp. *nov*

#### *Xiphinema malaka* **sp. nov.**

http://zoobank.org/urn:lsid:zoobank.org:act: BDBF964D-71E8-4E4F-B61C-50C5A7C51083 (Figures 7–10, Tables 3 and 4)

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**Figure 7.** Line drawings of holotype for *Xiphinema malaka* sp. nov. (**A**), pharyngeal region; (**B**), detail of lip region; (**C**,**D)**, female tails; (**E**), detail of uterine pseudo Z-differentiation.; (**F**), tail of first-stage juvenile (J1); (**G**), male tail. **Figure 7.** Line drawings of holotype for *Xiphinema malaka* sp. nov. (**A**), pharyngeal region; (**B**), detail of lip region; (**C**,**D)**, female tails; (**E**), detail of uterine pseudo Z-differentiation.; (**F**), tail of first-stage juvenile (J1); (**G**), male tail.

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**Figure 8.** Light photomicrographs of *Xiphinema malaka* sp. nov. females holotype and paratypes: (**A**), anterior region holotype; (**B**,**C**) anterior regions paratypes; (**D**), detail of odontophore and guiding ring in holotype; (**E**), vulval region; (**F**–**H**), detail of female genital track showing Z-differentiation in holotype; (**I**), tail region of holotype; (**J**–**N**), tail region in paratypes; (**O**), detail of first-stage anterior region; (**P**–**S**), tail region of 1st, 2nd, 3rd and 4th stage juveniles. Abbreviations: a = anus; af = amphidial fovea; cb = crystalloid bodies; fl = odontophore flanges; gr = guiding ring; odp = odontophore; odt = odontostyle; psZ = pseudo-Z organ; rodt = replacement odontostyle; sp = spine; v = vulva. Scale bars: 20 μm. **Figure 8.** Light photomicrographs of *Xiphinema malaka* sp. nov. females holotype and paratypes: (**A**), anterior region holotype; (**B**,**C**) anterior regions paratypes; (**D**), detail of odontophore and guiding ring in holotype; (**E**), vulval region; (**F**–**H**), detail of female genital track showing Z-differentiation in holotype; (**I**), tail region of holotype; (**J**–**N**), tail region in paratypes; (**O**), detail of first-stage anterior region; (**P**–**S**), tail region of 1st, 2nd, 3rd and 4th stage juveniles. Abbreviations: a = anus; af = amphidial fovea; cb = crystalloid bodies; fl = odontophore flanges; gr = guiding ring; odp = odontophore; odt = odontostyle; psZ = pseudo-Z organ; rodt = replacement odontostyle; sp = spine; v = vulva. Scale bars: 20 µm.

*Plants* **2020**, *9*, x FOR PEER REVIEW 23 of 30

**Figure 9.** Light photomicrographs of *Xiphinema malaka* sp. nov. male: (**A**), posterior region; (**B**), detail of tail showing spicules. Abbreviations: a = anus; ads = adanal supplements; sp = spicules; vs = ventromedian supplements. Scale bars: 20 μm. **Figure 9.** Light photomicrographs of *Xiphinema malaka* sp. nov. male: (**A**), posterior region; (**B**), detail of tail showing spicules. Abbreviations: a = anus; ads = adanal supplements; sp = spicules; vs = ventromedian supplements. Scale bars: 20 µm.

#### 2.5.1. Material Examined

*Holotype.* Adult female was found in the rhizosphere of maritime pine (*Pinus pinaster* Aiton) at 1312 m a.s.l. from Canillas de Albaida, Málaga province, Spain (GPS: 36◦52021.8100 N; 3◦55041.0000 W) collected by A. Archidona-Yuste on 12 December 2019; mounted in pure glycerin and deposited in the nematode collection at Institute for Sustainable Agriculture (IAS) of Spanish National Research Council (CSIC), Córdoba, Spain (Slide number X-SA3-02).

*Paratypes.* Female and juvenile paratypes were collected from the same soil sample as the holotype (Table 3); mounted in pure glycerin and deposited in the Institute for Sustainable Agriculture (IAS) of the Spanish National Research Council (CSIC), Córdoba, Spain (Slide numbers X-SA3-03–X-SA3-08); one female at Istituto per la Protezione delle Piante (IPP) of Consiglio Nazionale delle Ricerche (C.N.R.), Sezione di Bari, Bari, Italy (X-SA3-011); one female at the USDA Nematode Collection (T-7474p).

*Plants* **2020**, *9*, x FOR PEER REVIEW 24 of 30

**Figure 10.** Relationship of body length to length of functional and replacement odontostyle (Ost and rOst, respectively) length in all developmental stages from first-stage juveniles (J1) to mature females of *Xiphinema malaka* sp. nov. **Figure 10.** Relationship of body length to length of functional and replacement odontostyle (Ost and rOst, respectively) length in all developmental stages from first-stage juveniles (J1) to mature females of *Xiphinema malaka* sp. nov.

**3. Discussion**  The primary objective of this study was to decipher the cryptic diversity of the *X. hispanum*complex by applying an integrative taxonomical approaches on several new unidentified *Xiphinema* isolates from Málaga and Almería provinces (southern Spain), appearing morphologically and morphometrically indistinguishable from this species complex. Multivariate morphometric analyses *Additional material examined.* Additional nematode isolates were studied and characterized from the rhizosphere of maritime pine, black pine, cork oak and yellow broom at several localities at Málaga and Almería provinces (Table 4). Morphometric measurements were taken for 62 individuals, 40 females, one male and 21 juveniles from J1 to J4 from several localities in Málaga province, Tables 3 and 4. Unfortunately, the scarce nematode isolate detected in the isolte of Tabernas (Almería) did not allow us to take measurements of adult females.

proved to be useful tools for species delimitation within the genera *Longidorus* and *Xiphinema* [11,15,19,28]. These data support that *X. hispanum*-complex species comprise a model example of *Type locality*. Canillas de Albaida, Málaga province, Spain (GPS: 36◦52021.81" N; 3◦55041.00" W); 1254 m above sea level (a.s.l.) collected by A. Archidona-Yuste on 12 December 2019.

morphostatic speciation (genetic modifications not reflected in morphology and morphometry) [23,24], since independent approaches based on molecular analyses using ribosomal and *Etymology.* The species epithet refers to the Phoenician word Malaka, the name of the province of Málaga where the species was found in several localities.

mitochondrial sequences (haploweb and haplonet) revealed high levels of genetic diversity within

#### these species complexes which clearly separated *X. malaka* sp. nov. from all other *X. hispanum*-2.5.2. Diagnosis. *Xiphinema malaka* sp. nov.

complex species. These results, as well as those from previous studies, may suggest that *X. hispanum*complex species comprises a *Xiphinema* endemic lineage, with members morphologically and morphometrically very similar, that have diversified in the Iberian peninsula, since no other records on these species have been reported outside this area [20,22,29]. Phylogenetic analyses based on three rDNA molecular markers (*D2–D3* expansion domains of *28S* rRNA gene, *ITS1* region and the partial *18S* rRNA) resulted in a general consensus of species phylogenetic positions for the majority of them, and were generally congruent with those given by previous phylogenetic analysis [6,11,19,30–33]. The results of this research support our hypothesis that biodiversity of Longidoridae in southern Spain is still not fully clarified and needs additional sampling efforts given the significant gaps in soil nematode biodiversity regarding the large number of undescribed species [34,35] and the hypothesis suggesting the Iberian Peninsula as a possible center of speciation for some groups of the family Longidoridae [6,15,36]. The recognition of this extraordinary cryptic diversity has a direct bearing on estimates of global nematode biodiversity and concepts of nematode biogeography. Regional endemicity in plant-parasitic nematodes has seldom been recognized and cosmopolitan distributions Belongs to morphospecies Group 5 from the *Xiphinema* non*americanum*-group species [18]. It is characterized by a moderate long body (3.5–4.9 mm), assuming a J-shaped when heat-relaxed; lip region hemispherical, separate from the body contour by a depression, 14.0–15.0 µm wide; a relatively long odontostyle 131.0–148.5 µm; vulva located at 47.1–53.8% of body length; female reproductive system didelphic-amphidelphic having both branches about equally developed, pseudo Z-differentiation containing numerous small granular bodies, uterus tripartite with small crystalloid bodies and spines in low number and presence of prominent wrinkles in the uterine wall that may be confused with spiniform structures; female tail short convex-conoid on both sides, and bearing 3 caudal pores, ending in a rounded and broad terminus with a very small bulge at the end in some specimens; c' ratio (0.9–1.0); male rare one individual out of 75 females. Four developmental juvenile stages were identified, the 1st-stage juvenile with tail elongate-conoid with characteristic subdigitate rounded terminus (c' ratio 3.2–3.8). According to the polytomous key of Loof & Luc [18] and matrix codes sorted by Archidona-Yuste et al. [19], codes for the new species are (codes in parentheses are exceptions): A4-B23-C6-D6-E65-F4(5)-G3-H2-I3-J6-K2-L1. The DNA sequences of

in nematodes, like other microscopic organisms, are reportedly common [37,38].

*D2-D3* expansion domains of *28S*, ITS1 rRNA, *18S* rRNA, and partial *coxI* were deposited in GenBank under the accession numbers MT584052-MT584085, MT584088-MT584099, MT584086-MT584087 and MT580263-MT580274, respectively.

#### 2.5.3. Description

*Female.* Body cylindrical, slightly tapering towards anterior end in a J-shape when heat relaxed. Cuticle with fine transverse striae visible in tail region, 3.2 ± 0.3 (3.0–3.5) µm thick at mid body but thicker just posterior to anus. Lateral chord 13.2 ± 2.5 (11.5–16.0) µm wide, occupying ca. 25% of corresponding body diam. Lip region hemispherical, slightly offset from body contour by a depression, 14.6 ± 0.4 (14.0–15.0) µm wide and 6.5 ± 0.6 (6.0–7.5) µm high. Odontostyle moderately long, 1.7–1.9 times longer than odontophore, the latter with well-developed flanges (13.0–15.5 µm wide). Guiding ring and guiding sheath variable in length depending on degree of protraction/retraction of stylet. Pharynx composed by a slender narrow flexible part 335–582 µm long, and a posterior muscular, cylindrical and expanded part with three nuclei. Terminal pharyngeal bulb variable in length, 112.0–149.0 µm long and 24.0–31.0 µm wide. Glandularium 110.0–129.0 µm long. Dorsal gland nucleus (DN) located at beginning of basal bulb (8.5–14.3%), ventrosublateral gland nuclei (SVN) situated *ca* halfway along bulb (52.3–67.9%) (position of gland nuclei calculated as described by Loof & Coomans [27]). Cardia conoid-rounded and variable in length, 12.0–15.0 µm long. Intestine simple, prerectum variable in size 471–516 µm long. Rectum 32.0–40.0 µm long ending in anus as a small rounded slit. Reproductive system didelphic-amphidelphic with two equally developed branches. Each branch composed of a short ovary 47–78 µm long, a reflexed oviduct 93–104 µm long with well-developed pars dilatata oviductus, a sphincter, a well-developed pars dilatata uteri, and a 254–286 µm long uterus with pseudo-Z differentiation containing numerous small granular bodies with small crystalloid bodies (6.0–12.5 µm long) and spines in low number, and presence of prominent wrinkles in the uterine wall that may be confused with spiniform structures (Figures 7 and 8); a 35.5–47.0 µm long vagina perpendicular to body axis (having 28–32% corresponding body diam. ingrowth), ovejector well-developed 36.5–50.0 µm wide, pars distalis vaginae 16.8 ± 2.4 (13.0–19.5) µm long, and pars proximalis vaginae 24.3 ± 2.4 (20.5–27.5) µm long and 26.3 ± 1.0 (21.5–29.5) µm wide, and vulva as a transverse slit. Tail short, convex-conoid on both sides, and bearing three caudal pores, ending in a rounded and broad terminus, with a very small bulge at the end in some specimens (Figure 8).

*Male.* Extremely rare, only one male individual out of 75 female specimens was found in one sample near the type locality. Morphologically similar to female except for genital system and secondary sexual features. Male genital tract diorchic with testes containing multiple rows of different stages of spermatogonia. Tail short, convex-conoid with a broadly rounded terminus and thickened outer cuticular layer. Adanal supplements paired, preceded anteriorly by a row of five irregularly spaced ventromedians supplements. Spicules paired, dorylaimoid, moderately long and slightly curved ventrally, approximately 2.5 times longer than tail length; lateral guiding pieces more or less straight or with curved proximal end.

*Juveniles.* Four developmental juvenile stages were detected and distinguished by relative body length, odontostyle and replacement odontostyle length. The 1st-stage juveniles were characterized by the replacement odontostyle inserted into odontophore base (Figure 8). In all other stages, the replacement odontostyle was posterior to the flanges of odontophore in its resting position. The correlation between body length, replacement and functional odontostyle of the type population is given in Figure 10. Lip region in all juvenile stages looks similar to that in females. Other morphological characters similar to female, except for their size and immature sexual characteristics (developing genital primordium 16.0–87.0 µm long). The first-stage juvenile was characterized by a tail elongate-conoid with characteristic subdigitate rounded terminus (c' ratio 3.2–3.8). Tail of other developmental stages becoming progressively shorter and wider after each moult (Figure 8).

#### 2.5.4. Remarks

According to the polytomous key by Loof & Luc [18] and matrix codes sorted by Archidona-Yuste et al. [6]: A (type of female genital apparatus), C (tail shape), D (c' ratio), E (vulva position), F (body length), and G (total stylet length) (in this order of main features), *X. malaka* sp. nov. is closely related to *X. subbaetense* Cai, Archidona-Yuste, Cantalapiedra-Navarrete, Palomares Rius & Castillo [11], *X. hispanum* Lamberti, Castillo, Gomez-Barcina & Agostinelli [22], *X. adenohystherum* Lamberti, Castillo, Gomez-Barcina & Agostinelli [22], *X. cohni* Lamberti, Castillo, Gomez-Barcina & Agostinelli [22], and *X. sphaerocephalum* Lamberti, Castillo, Gomez-Barcina & Agostinelli [22].

*Xiphinema malaka* sp. nov. is morphometrically almost undistinguishable from *X. subbaetense* and *X. hispanum*, from the former can only be differentiated in females by a higher a ratio (65.6–99.8 vs. 49.0–70.0), a shorter odontophore (75.0–88.0 vs. 82.0–96.5 µm), narrower lip region (14.0–15.5 vs. 15.5–18.5 µm), higher c' ratio in J1 (3.2–3.8 vs. 2.6–3.1, 2.7–3.1, respectively), and presence of male (very rare vs. absent) [11,20]. Morphologically can be differentiated from *X. subbaetense* and *X. hispanum* in pseudo-Z differentiation containing numerous small granular bodies vs. 4–5 granular bodies. It can be differentiated from *X. adenohystherum* by slightly shorter odontostyle (131.0–149.0 vs. 143.0–152.0 µm), longer tail (26.0–47.0 vs. 29.0–35.0 µm), and slightly higher a ratio (65.6–96.5 vs. 65.2–73.3). It can be differentiated from *X. sphaerocephalum* by its shorter odontostyle (131.0–149.0 vs. 143.5–168.0 µm), and shorter oral aperture-guiding ring distance (96.0–135.0 vs. 126.0–162.0 µm). Finally, *X. malaka* sp. nov. can be differentiated from *X. cohni* by its shorter odontostyle (131.0–149.0 vs. 149–174 µm), shorter oral aperture-guiding ring distance (96.0–135.0 vs. 137.0–161.0 µm), and higher c ratio (97.3–178.6 vs. 82.6–115.2). Nevertheless, it can be clearly separated by specific *28S* rRNA, ITS1 rRNA and *coxI* sequences.

#### **3. Discussion**

The primary objective of this study was to decipher the cryptic diversity of the *X. hispanum*-complex by applying an integrative taxonomical approaches on several new unidentified *Xiphinema* isolates from Málaga and Almería provinces (southern Spain), appearing morphologically and morphometrically indistinguishable from this species complex. Multivariate morphometric analyses proved to be useful tools for species delimitation within the genera *Longidorus* and *Xiphinema* [11,15,19,28]. These data support that *X. hispanum*-complex species comprise a model example of morphostatic speciation (genetic modifications not reflected in morphology and morphometry) [23,24], since independent approaches based on molecular analyses using ribosomal and mitochondrial sequences (haploweb and haplonet) revealed high levels of genetic diversity within these species complexes which clearly separated *X. malaka* sp. nov. from all other *X. hispanum*-complex species. These results, as well as those from previous studies, may suggest that *X. hispanum*-complex species comprises a *Xiphinema* endemic lineage, with members morphologically and morphometrically very similar, that have diversified in the Iberian peninsula, since no other records on these species have been reported outside this area [20,22,29].

Phylogenetic analyses based on three rDNA molecular markers (*D2–D3* expansion domains of *28S* rRNA gene, *ITS1* region and the partial *18S* rRNA) resulted in a general consensus of species phylogenetic positions for the majority of them, and were generally congruent with those given by previous phylogenetic analysis [6,11,19,30–33].

The results of this research support our hypothesis that biodiversity of Longidoridae in southern Spain is still not fully clarified and needs additional sampling efforts given the significant gaps in soil nematode biodiversity regarding the large number of undescribed species [34,35] and the hypothesis suggesting the Iberian Peninsula as a possible center of speciation for some groups of the family Longidoridae [6,15,36]. The recognition of this extraordinary cryptic diversity has a direct bearing on estimates of global nematode biodiversity and concepts of nematode biogeography. Regional endemicity in plant-parasitic nematodes has seldom been recognized and cosmopolitan distributions in nematodes, like other microscopic organisms, are reportedly common [37,38].

In summary, the present study confirmed the extraordinary cryptic diversity of *X. hispanum*-complex species in Andalusia and comprises a paradigmatic example of morphostatic speciation of dagger nematodes in southern Spain, which can be a potential explanation of the unusual high biodiversity within Longidoridae, considering Andalusia as a hot spot of biodiversity. However, additional similar intensive taxonomic studies are needed in other areas which can confirm this statement.

#### **4. Materials and Methods**

#### *4.1. Nematode Isolates and Morphological Studies*

No specific permits were required for the indicated fieldwork studies. The soil samples were obtained in public areas, forests and other natural areas and did not involve any endangered species or those protected in Spain, nor were the sites protected in any way.

A total of 62 individuals including 41 adults and 21 juvenile specimens from several localities in Málaga and Almería provinces (southern Spain) were used for morphological analyses (Table 1, Figure 1). Nematodes were surveyed during spring season in 2019 in natural ecosystems in Andalusia, southern Spain (Table 1). Soil samples were collected for nematode analysis with a shovel randomly selecting four to five cores at each point, and considering the upper 5–50 cm depth of soil that was close to the active plant root at each sampling spot. Nematodes were extracted from a 500-cm<sup>3</sup> sub-sample of soil by centrifugal flotation [39] and a modification of Cobb's decanting and sieving [40] methods. For morphometric studies, *Xiphinema* specimens were killed and fixed by a hot solution of 4% formalin + 1% glycerol, then processed in pure glycerin [41] as modified by De Grisse [42].

Specimens for light microscopy were killed by hot fixative using a solution of 4% formaldehyde+1% propionic acid and embedded in pure glycerine using Seinhorst's [41] method. The morphometric study of each nematode isolate included morphology-based diagnostic features in *Xiphinema* (i.e., de Man body ratios), lip region width, amphid shape, oral aperture-guiding-ring, odontostyle and odontophore length and female tail shape [7]. For line drawings of the new species, light micrographs were imported to CorelDraw ver. X7 and redrawn. The light micrographs and measurements of each nematode isolate, including important diagnostic characteristics (i.e., de Man indices, body length, odontostyle length, lip region, tail shape, amphid shape and oral aperture-guiding ring; [7]) were performed using a Leica DM6 (Wetzlar, Germany) compound microscope with a Leica DFC7000 T digital camera. For the line drawings of the new species, CorelDraw software version X7 (Corel Corporation, London, UK) was used to redraw according to the selected light micrographs.

#### *4.2. DNA Extraction, Polymerase Chain Reaction (PCR) and Sequencing*

For molecular analyses, in order to ensure the selected nematodes for extracting DNA were from the same species, two live nematodes from each sample were temporary mounted in a drop of 1M NaCl containing glass beads (to avoid nematode crushing/damaging specimens) to ensure specimens conformed to the unidentified isolates of *Xiphinema*. Thus, 34 individuals collected from several sampling points in Andalusia were molecularly analyzed (Table 1). All necessary morphological and morphometric data, by taking pictures and measurements using the above camera-equipped microscope, were recorded. This was followed by DNA extraction from a single specimen and polymerase chain reaction (PCR) cycle conditions as previously described [6,15]. Several sets of primers were used for PCR. A partial region of the *28S* rRNA gene including the expansion domains D2 and D3 (*D2-D3*) was amplified by using the primers D2A (50 -ACAAGTACCGTGAGGGAAAGTTG-30 ) and D3B (50 -TCGGAAGGAACCAGCTACTA-30 ) [43]. The Internal Transcribed Spacer region 1 (*ITS1*) separating the *18S* rRNA gene from the 5.8S rRNA gene was amplified using forward primer *18S* (50 -TTGATTACGTCCCTGCCCTTT-30 ) [44] and reverse primer rDNA1 5.8S (50 -ACGAGCCGAGTGATCCACCG-30 ) [45]. A partial sequence of the *18S* rRNA gene (*18S*) was amplified as previously described [46] using primers 988F (50 -CTCAAAGATTAAGCCATGC-30 ), 1912R (50 -TTTACGGTCAGAACTAGGG-30 ), 1813F (50 -CTGCGTGAGAGGTGAAAT-30 ), and 2426R

(50 -GCTACCTTGTTACGACTTTT -30 . Finally, the portion of the cytochrome c oxidase subunit I gene (*coxI*) was amplified using the primers COIF (50 -GATTTTTTGGKCATCCWGARG-30 ) and COIR (50 -CWACATAATAAGTATCATG-30 ) [47]. The newly obtained sequences were deposited in the GenBank database under accession numbers indicated in Table 1 and on the phylogenetic trees.

PCR cycle conditions were one cycle of 94 ◦C for two min, followed by 35 cycles of 94 ◦C for 30 s, annealing temperature of 55 ◦C for 45 s, 72 ◦C for three min, and finally one cycle of 72 ◦C for 10 min. PCR products were purified after amplification using ExoSAP-IT (Affimetrix, USB products, High Wycombe, UK), quantified using a Nanodrop spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA) and used for direct sequencing in both directions using the primers noted above. The resulting products were purified and run on a DNA multicapillary sequencer (Model 3130XL genetic analyser; Applied Biosystems, Foster City, CA, USA), using the BigDye Terminator Sequencing Kit v.3.1 (Applied Biosystems, Foster City, CA, USA), at the Stab Vida sequencing facilities (Caparica, Portugal). The newly obtained sequences were submitted to the GenBank database under accession numbers indicated in Table 1 and on the phylogenetic trees.

#### *4.3. Species Delimitation via Multivariate Morphometric Analysis and Haplotype Networks Construction*

The nine new *Xiphinema* isolates detected in this study were included in the *X. hispanum*-complex species group given the close relationships morphologically with *X. hispanum* as outlined above. An iterative analysis of morphometric and molecular data using two independent strategies of species delimitation was utilized to asses described and undescribed specimens and to determine species boundaries within this species complex.

Species delineation using morphometry was conducted with principal component analysis (PCA) in order to estimate the degree of association among species within the *X. hispanum*-complex [48]. PCA was based upon the following morphological characters: L (body length), the ratios a, c, c', d, d', V, odontostyle and odontophore length, lip region width and hyaline region length (Table 2) [6,7,13]. Prior to the statistical analysis, diagnostic characters were tested for collinearity [49]. We used the collinearity test based on the values of the variance inflation factor (VIF) method that iteratively excludes numeric covariates showing VIF values > 10 as suggested by Montgomery and Peck [50]. PCA was performed by a decomposition of the data matrix amongst isolates using the principal function implemented in the package psych [51]. Orthogonal varimax raw rotation was used to estimate the factor loadings. Only factors with sum of squares (SS) loadings > 1 were extracted. Finally, a minimum spanning tree (MST) based on the Euclidean distance was superimposed on the scatter plot of the *X. malaka* sp. nov.-specimens complex against the PCA axes. MST was performed using the ComputeMST function implemented in the package emstreeR [52]. All statistical analyses were performed using the R v. 3.5.1 freeware [53].

In order to detect distinct phylogenetic groups possibly representing separate species, haplotype networks (briefly, haplonet) were constructed to each of the two separate datasets, i.e., the *D2-D3* and *coxI*. Alignments were converted to the NEXUS format using DnaSP V.6 [54]; TCS networks [55] were applied in the program PopART V.1.7 [56]. Illustrations of networks were prepared using the program Adobe illustrator to add connecting curves between the haplotypes found co-occurring in heterozygous individuals [57].

#### *4.4. Phylogenetic Analysis*

Sequenced genetic markers in the present study (after discarding primer sequences and ambiguously aligned regions), and several *Xiphinema* spp. sequences obtained of GenBank, were used for phylogenetic reconstruction (Table 1). Outgroup taxa for each dataset were selected based on previous published studies [6,11,30,45,58]. Multiple sequence alignments of the newly obtained and published sequences were made using the FFT-NS-2 algorithm of MAFFT v. 7.450 [59]. Sequence alignments were visualized using BioEdit [60] and edited by Gblocks ver. 0.91b [61] in the Castresana Laboratory server (http://molevol.cmima.csic.es/castresana/Gblocks\_server.html) using

options for a less stringent selection (minimum number of sequences for a conserved or a flanking position: 50% of the number of sequences + 1; maximum number of contiguous no conserved positions: 8; minimum length of a block: 5; allowed gap positions: with half).

Phylogenetic analyses of the sequence data sets were based on Bayesian inference (BI) using MRBAYES 3.2.7a [62]. The best-fit model of DNA evolution was calculated with the Akaike information criterion (AIC) of JMODELTEST v. 2.1.7 [63]. The best-fit model, the base frequency, the proportion of invariable sites and the gamma distribution shape parameters and substitution rates in the AIC were then used in phylogenetic analyses. BI analyses were performed under a general time reversible, with a proportion of invariable sites and a rate of variation across sites (GTR + I + G) model for *D2-D3*, the partial *18S* rRNA, and the partial *coxI* gene, and under a transition model with a proportion of invariable sites and a rate of variation across sites (TIM2 +I + G). These BI analyses were run separately per dataset with four chains for 2 <sup>×</sup> <sup>10</sup><sup>6</sup> generations. The Markov chains were sampled at intervals of 100 generations. Two runs were conducted for each analysis. After discarding burn-in samples of 30% and evaluating convergence, the remaining samples were retained for more in-depth analyses. The topologies were used to generate a 50% majority-rule consensus tree. Posterior probabilities (PP) were given on appropriate clades. Trees from all analyses were visualized using FigTree software version v.1.42 [64].

**Author Contributions:** Conceptualization, A.A.-Y., R.C., C.C.-N., J.A.C., A.R., B.V., G.L., J.E.P.-R. and P.C., methodology, A.A.-Y., R.C., C.C.-N., J.A.C., A.R., G.L., J.E.P.-R. and P.C., software, A.A.Y., R.C., J.E.P.-R. and P.C., analysis, A.A.Y., R.C., J.E.P.-R. and P.C., resources, J.A.C., A.R., G.L. and P.C., writing, A.A.-Y., R.C., C.C.-N., J.A.C., A.R., G.L., J.E.P.-R. and P.C. All authors contributed to the final discussion data, and read and approved the final manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by Spanish Ministry of Science, Innovation and Universities, grant number RTI2018-095345-B-C21, LITHOFOR ("Modulating role of LITHOlogy in the response of Mediterranean FORest ecosystems to climate change: growth, edaphological processes and future predictions") and the Humboldt Research Fellowship for Postdoctoral Researchers awarded for the first author.

**Acknowledgments:** We would like to thanks J. Martin Barbarroja and G. León Ropero (IAS-CSIC) for their excellent technical assistance in surveys and management of soil samples, and further anonymous reviewers and editors for their effort in reviewing the manuscript and helping improve this study. The first author is a recipient of Humboldt Research Fellowship for Postdoctoral Researchers at Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany. The second author acknowledges the China Scholarship Council (CSC) for financial support. The sixth author acknowledges Spanish Ministry of Economy and Competitiveness for the "Ramon y Cajal" Fellowship RYC-2017-22228.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


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## *Article* **Global Distribution of the Reniform Nematode Genus** *Rotylenchulus* **with the Synonymy of** *Rotylenchulus macrosoma* **with** *Rotylenchulus borealis*

**Juan E. Palomares-Rius <sup>1</sup> , Ilenia Clavero-Camacho <sup>1</sup> , Antonio Archidona-Yuste <sup>2</sup> , Carolina Cantalapiedra-Navarrete <sup>1</sup> , Guillermo León-Ropero <sup>1</sup> , Sigal Braun Miyara <sup>3</sup> , Gerrit Karssen 4,5 and Pablo Castillo 1,\***


**Abstract:** Reniform nematodes of the genus *Rotylenchulus* are semi-endoparasites of numerous herbaceous and woody plant roots that occur largely in regions with temperate, subtropical, and tropical climates. In this study, we compared 12 populations of *Rotylenchulus borealis* and 16 populations of *Rotylenchulus macrosoma*, including paratypes deposited in nematode collections, confirming that morphological characters between both nematode species do not support their separation. In addition, analysis of molecular markers using nuclear ribosomal DNA (*28S*, *ITS1*) and mitochondrial DNA (*coxI*) genes, as well as phylogenetic approaches, confirmed the synonymy of *R. macrosoma* with *R. borealis*. This study also demonstrated that *R. borealis* (= *macrosoma*) from Israel has two distinct rRNA gene types in the genome, specifically the two types of *D2-D3* (A and B). We provide a global geographical distribution of the genus *Rotylenchulus*. The two major pathogenic species (*Rotylenchulus reniformis* and *Rotylenchulus parvus*) showed their close relationship with warmer areas with high annual mean temperature, maximum temperature of the warmest month, and minimum temperature of the coldest month. The present study confirms the extraordinary morphological and molecular diversity of *R. borealis* in Europe, Africa, and the Middle East and comprises a paradigmatic example of remarkable flexibility of ecological requirements within reniform nematodes.

**Keywords:** Bayesian inference; cytochrome c oxidase subunit 1; distribution; *D2-D3* expansion domains of *28S* rRNA gene; *ITS1*; phylogeny

#### **1. Introduction**

Reniform nematodes of the genus *Rotylenchulus* are an economically important polyphagous group of highly adapted obligate plant parasites that parasitize numerous plants and crops usually associated with temperate, subtropical, and tropical climates [1]. The genus *Rotylenchulus* Linford and Oliveira [2] comprise 11 valid species; some of them are distributed worldwide, whereas others have shown a limited distribution [1,3,4]. This genus has been reported in 77 countries of Africa, Asia, Europe, North and South America, and Australia [1,3,4]. The influence of future global climate change could shorten the life cycle of these nematodes and may expand the distribution of well-adapted species to

**Citation:** Palomares-Rius, J.E.; Clavero-Camacho, I.; Archidona-Yuste, A.; Cantalapiedra-Navarrete, C.; León-Ropero, G.; Braun Miyara, S.; Karssen, G.; Castillo, P. Global Distribution of the Reniform Nematode Genus *Rotylenchulus* with the Synonymy of *Rotylenchulus macrosoma* with *Rotylenchulus borealis*. *Plants* **2021**, *10*, 7. https://dx.doi.org/10.3390/plants 10010007

Received: 24 November 2020 Accepted: 21 December 2020 Published: 23 December 2020

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**Copyright:** © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).

drought conditions [5,6]. However, other factors such as the low population density in soil, no apparent harvest losses in some crops, or the difficulties for an accurate identification for some *Rotylenchulus* species could thwart their precise geographical distribution. For these reasons, *Rotylenchulus* spp. could be regarded as a "neglected pathogen", but also as a potentially dangerous pathogen in the future because of new ecological conditions predicted in global climate change scenarios [7]. Consequently, an updating of the global distribution of this group of nematodes allowed us to know the climatic conditions adapted to each species, which are essential to predict the response of this genus to climate change [8,9].

*Rotylenchulus* spp. show high intraspecific variability of some morphological diagnostic features in immature females (the developmental stage usually employed for species identification) [3], and for this reason, it is necessary to use molecular markers for precise species identification. In this regard, the use of rRNA markers is challenging due to the previously noted presence of several gene copies that are not well homogenized in the genome, and for this reason, several different amplicon sizes and associated sequences can be observed [4]. A prominent example of this high intraspecific variability was established in the study on several populations of *Rotylenchulus macrosoma* by Dasgupta et al. [10] and *R. borealis* by Loof and Oostenbrink [11].

In 1952, Oostenbrink found a population of reniform-shaped nematode in a soil sample from Arnhem (The Netherlands). Subsequent examination and comparison with published descriptions showed that the new nematode represented an undescribed species, proposed as *Rotylenchulus borealis* Loof & Oostenbrink [11], referring to its occurrence in northern countries, since the other species of the genus were mainly known from the tropical and subtropical regions [11]. Some years later, Dasgupta et al. [10] revised the genus *Rotylenchulus* and described a new species from olive in Hulda, Israel, closely related to *R. borealis*, named *Rotylenchulus macrosoma* (original spelling *macrosomus). R. macrosoma* differed from the former by its larger body length of immature females and males (0.52–0.64 mm, 0.50–0.68 mm vs. 0.37–0.46 mm, 0.40–0.49 mm in *R. borealis*, respectively), larger female stylet (18–22 vs. 13–16 µm in *R. borealis*), and longer hyaline portion of immature female tail (h = 13–18 vs. 9–13 µm in *R. borealis*). These limited differences between both species have been confirmed by posterior morphometrics of several African populations studied by Germani [12], as well as the recent *R. macrosoma* populations studied from Europe [3,9].

In 2003, Castillo et al. [13] detected a population of reniform nematodes infecting the roots of wild olive trees (*Olea europea* L. ssp. *sylvestris*) on a sandy soil in Cádiz province, southern Spain, which was identified as *R. macrosoma*. Morphometric of the Spanish population agreed with the original description of *R. macrosoma*, except for a shorter stylet length (15–18 *vs*. 18–22 µm), which was considered as an intraspecific variability. Later on, in 2016, Van den Berg et al. [3] provided morphological and molecular characterization of 6 out of 11 presently known species of *Rotylenchulus*, including three Spanish populations (two and one from Cádiz and Seville provinces, respectively) of *R. macrosoma*, which formed a separate and well-supported clade within phylogenetic trees of *D2-D3* expansion segments of *28S* rRNA, *ITS*, and *hsp90* genes [3]. This study also reported high levels of intraspecific and intra-individual variations of rRNA with two or more distinct types of rRNA genes, namely, type A and B [3]. These phylogenetic relationships were confirmed by posterior studies on additional new reports of *R. macrosoma* populations from several European countries including the Czech Republic, France, Germany, Greece, Hungary, Italy, Portugal, Romania, Serbia, and Spain [4,9]. In a recent study on the integrative characterization of plant-parasitic nematodes of potato in Rwanda, Niragire [14] provided morphological and molecular data of a population of *R. macrosoma* from Burera (North Rwanda), but no sequences were deposited in the National Center for Biotechnology Information (NCBI) database. Molecular data available for *R. borealis* is a *28S* rRNA sequence obtained from a Belgian population (MK558206) and the mentioned sequence for Burera clustered together with the Spanish *R. macrosoma* populations [14]. However, this Belgian population (Oudenaarde, Belgium) of *R. borealis* was not mentioned in the

associated paper with the NCBI sequence and no morphological data were available alongside it [15]. This sequence has a 99.45% identity with *R. macrosoma*-KT003748 from Spain. Recently, Qing et al. [16] studied the rRNA variation (intragenomic polymorphism) across 30 terrestrial nematode species and sequenced *28S* and *ITS1* from a population of *R. macrosoma* in Israel, which clustered together in the same clade with *R. macrosoma* populations from Spain and Crete (Greece) and clearly separated from other *Rotylenchulus* spp. Finally, in the last months, one new *28S* rRNA sequence of *R. borealis* from New Delhi, India, was deposited on the NCBI database, MT775429 (95% identity with *R. macrosoma* KT003748 from Spain and 94% identity with *R. borealis* MK558206 from Belgium). All these concerns prompted us to carry out an integrative taxonomic analysis of *R. borealis* from the Netherlands in order to confirm the validity of these species or their synonymization with *R. macrosoma*.

The objectives of this study were (1) to morphometrically and molecularly characterize several populations of *R. macrosoma* from Europe and a population of *R. borealis* from the Netherlands, as well as paratypes of both species deposited in Nematode Collections, and to compare them with previous records; (2) to study the phylogenetic relationships of the European and Dutch populations of *R. macrosoma* and *R. borealis* and compare them with available sequenced populations of these species to establish their validity; and (3) to provide a clear view of the global distribution and the current climatic conditions that affect the distribution of species within the genus *Rotylenchulus.*

#### **2. Results**

#### *2.1. Morphometric Comparison of Paratypes and Several Populations of Rotylenchulus Borealis and Rotylenchulus Macrosoma*

We detected similar morphological traits in the comparison of 12 populations of *R. borealis* and 16 populations of *R. macrosoma* (Figure 1, Tables 1–8), but ordinary morphometric differences among both species grouped within the three main diagnostic characters of immature females originally used for separating both species (namely, body length, stylet length, and hyaline tail region length) (Figure 2), being the major differences in the original species descriptions. Our data indicated that mean body length of all 12 populations of *R. borealis* was 401.7 µm, whereas the mean for 16 populations of *R. macrosoma* was 483.0 µm. Similarly, stylet and hyaline tail region lengths were 14.25 µm, 7.8 µm vs. 17.28 µm, 12.5 µm, respectively (Tables 2–8). No differences were detected between the paratype immature females and males of *R. borealis* and the original description, as well as the new studied population from Huissen, Betuwe region (close to the type locality), the Netherlands (Table 2). However, of the two paratype immature females of *R. macrosoma* examined from Wageningen Nematode Collection (WANECO) and United States Department of Agriculture (USDA) nematode collections, both specimens showed a stylet length slightly lower than 18.0 µm (Table 5), and representing a lower measure to that provided in the type population from olive at Hulda, Israel, and quite close to several European populations, such as Spanish populations from Jerez and Huévar del Aljarafe, Cretan populations from Petrokefali and Limnes, or the Rwandan population from Burera. Nevertheless, immature female body and hyaline tail region lengths were similar to those provided in the original description.

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**Figure 1.** Comparative morphology among paratype specimens of *Rotylenchulus borealis* from the Netherlands (**a**–**f**), paratype specimens of *Rotylenchulus macrosoma* from Israel (**g**–**l**), and a population of *Rotylenchulus macrosoma* from Hungary (**m**–**t**). (**a**,**g**) slides deposited in Wageningen Nematode Collection (WANECO) and United States Department of Agriculture (USDA) nematode collections; (**b**–**d**,**m**,**o**,**q**) mature females; (**e**, **h**–**j**,**n**,**p**,**r**) immature females; (**f**,**k**,**l**,**n**,**s**,**t**) = males. Abbreviations: a = anus; dgo = dorsal gland opening; V = vulva. Scale bars: (**b**–**d**,**h**,**k**,**m**–**o**) 100 μm; (**e**,**f**) 50 μm; (**i**,**j**,**l**,**p**,**q**,**s**,**t**) 20 μm; (**r**) 10 μm. **Figure 1.** Comparative morphology among paratype specimens of *Rotylenchulus borealis* from the Netherlands (**a**–**f**), paratype specimens of *Rotylenchulus macrosoma* from Israel (**g**–**l**), and a population of *Rotylenchulus macrosoma* from Hungary (**m**–**t**). (**a**,**g**) slides deposited in Wageningen Nematode Collection (WANECO) and United States Department of Agriculture (USDA) nematode collections; (**b**–**d**,**m**,**o**,**q**) mature females; (**e**, **h**–**j**,**n**,**p**,**r**) immature females; (**f**,**k**,**l**,**n**,**s**,**t**) = males. Abbreviations: a = anus; dgo = dorsal gland opening; V = vulva. Scale bars: (**b**–**d**,**h**,**k**,**m**–**o**) 100 µm; (**e**,**f**) 50 µm; (**i**,**j**,**l**,**p**,**q**,**s**,**t**) 20 µm; (**r**) 10 µm.

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**Table 1.** Populations sampled for *Rotylenchulus* spp. from two localities in the Netherlands and Israel used in this study. *Plants* **2021**, *10*, x FOR PEER REVIEW 5 of 22

> (-) Not obtained or not performed. (-) Not obtained or not performed.

**Figure 2.** Range (minimum and maximum) comparative key diagnostic measures of immature females (body, stylet, and hyaline female tail lengths) for separating among *R. borealis* and *R. macrosoma* populations in decreasing chronological order of publication. **Figure 2.** Range (minimum and maximum) comparative key diagnostic measures of immature females (body, stylet, and hyaline female tail lengths) for separating among *R. borealis* and *R. macrosoma* populations in decreasing chronological order of publication.

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**Table 2.** Measurements of immature females and males of *Rotylenchulus borealis* from type locality in the Netherlands and several localities in Africa. All measurements are in micrometers and in the form mean ± SD (range).




**Table 4.** Measurements of immature females and males of *Rotylenchulus borealis* from several localities in Africa and the Slovak Republic. All measurements are in micrometers and in the form mean ± SD (range).


**Table 5.** Measurements of immature females and males of *Rotylenchulus borealis (= R. macrosoma)* from type locality in Israel and several localities in Spain. All measurements are in micrometers and in the form mean ± SD (range).


**Table 6.** Measurements of immature females and males of *Rotylenchulus borealis (= R. macrosoma)* from cultivated olive in Spain and Crete, Greece. All measurements are in micrometers and in the form mean ± SD (range).


h = hyaline tail region length; o = (DGO/stylet length) × 100; V = (distance from anterior end to vulva/body length) × 100.



**Table 8.** Measurements of immature females and males of *Rotylenchulus borealis (= R. macrosoma)* from corn and wheat from several localities in Europe. All measurements are in micrometers and in the form mean ± SD (range).


h = hyaline tail region length; o = (DGO/stylet length) × 100; V = (distance from anterior end to vulva/body length) × 100.

#### *2.2. Molecular Characterisation and Phylogenetic Analysis of Rotylenchulus Borealis and Rotylenchulus Macrosoma Populations*

The amplification of *D2-D3* expansion domains of *28S* rRNA, *ITS1* rRNA, and *coxI* genes of *R. borealis* and *R. macrosoma* populations yielded single fragments of ≈900 bp, 1100 bp, and 450 bp, respectively, on the basis of gel electrophoresis and, in the case of the Israel population, from cloning of the PCR product. Sixteen new sequences from the *D2-D3* of *28S* rRNA gene and eight new sequences from ITS1 rRNA gene were obtained in this study (7 and 9, and 4 and 4, from the Netherlands and Israel, respectively). Four new *coxI* sequences from the Netherlands were deposited in GenBank; however, due to lack of material, it was not possible to obtain *coxI* sequences from Israel. Type B-D2D3 sequence of *R. macrosoma* from Israel was obtained for the first time in this study (MW173975). *D2-D3* for *R. borealis* (MW173970-MW173976) showed a low intraspecific variability with 1–5 different nucleotides and 0 indels (99% similarity). Similarly, intraspecific variability for *D2-D3* in *R. macrosoma* from Israel was slightly higher, with 6–17 different nucleotides and 0–2 indels (97–99% similarity). The molecular diversity of this marker between *R. borealis* (MW173970-MW173976) from the Netherlands and *R. macrosoma* (MW173977- MW173985) from Israel populations was also low, with 5–22 different nucleotides and 0–2 indels (96–99% similarity). *D2-D3* sequences of *R. macrosoma* from Israel (MW173977- MW173985) differed in 0–10 nucleotides and 0 indels (99% similarity) when compared with sequences of *R. macrosoma* deposited in the NCBI database from Spain, Belgium, Serbia, Romania, Hungary, and Portugal, and with *Rotylenchulus* sp. 191\_7 (MK558208) and *R. borealis* (MT775429) from Ethiopia and New Delhi in 32, 44 bp, 0, 1 indels (95%, 94% similarity), respectively. Similarly, *D2-D3* sequences of *R. borealis* from the Netherlands (MW173970-MW173976) differed in 14–21 nucleotides and 0 indels (97–98% similarity) when compared with sequences of *R. macrosoma* deposited in the NCBI database from Spain, Belgium, Serbia, Romania, Hungary, and Portugal, and with *Rotylenchulus* sp. 191\_7 (MK558208) and *R. borealis* (MT775429) from Ethiopia and New Delhi in 41, 39 bp, 0 indels (94%, 94% similarity), respectively.

The *ITS1* region showed a low intraspecific variability for *R. borealis* (MW174239- MW174242) from the Netherlands, with 0–6 different nucleotides and 0–1 indels (98–100% similarity). Similarly, intraspecific variability for*ITS1* in *R. macrosoma* from Israel (MW174243- MW174246) was low, with 0–11 different nucleotides and 0–4 indels (98–100% similarity). The molecular diversity of this marker between *R. borealis* from the Netherlands (MW174239- MW174242) and *R. macrosoma* from Israel (MW174243-MW174246) populations was also low, with 0–24 different nucleotides and 0–12 indels (95–100% similarity). *ITS1* sequences of *R. macrosoma* from Israel (MW174243-MW174246) differed in 19–32 nucleotides and 1–8 indels (94–96% similarity) when compared with sequences of *R. macrosoma* deposited in the NCBI database from Spain and Greece, and with *Rotylenchulus reniformis* (KF999979) from Japan in 92 bp, 26 indels (86% similarity). Similarly, *ITS1* sequences of *R. borealis* from the Netherlands (MW174239-MW174242) differed in 13–42 nucleotides and 1–11 indels (94–98% similarity) when compared with sequences of *R. macrosoma* deposited in the NCBI database from Spain and Greece, and with *R. reniformis* (KP018567) from China in 137 bp, 54 indels (83% similarity).

The partial *coxI* gene for *R. borealis* from the Netherlands (MW182432-MW182435) showed a low intraspecific variability with 0–8 different nucleotides and 0 indels (98–100% similarity). These sequences differed in 0–47 nucleotides and 0 indels (89–100% similarity) with sequences of *R. macrosoma* deposited in the NCBI database from Spain, Serbia, Romania, Hungary, and Greece, and with *Rotylenchulus parvus* (MK558211) from Tanzania in 64 bp, 4 indels (85% similarity). All molecular markers suggest that populations of *R. borealis* from the Netherlands and *R. macrosoma* from Israel are conspecific.

Phylogenetic relationships among *Rotylenchulus* species inferred from analyses of *D2-D3* expansion domains of *28S* rRNA, *ITS1*, and partial *coxI* gene sequences using Bayesian inference (BI) are shown in Figures 3–5, respectively. The phylogenetic trees

generated with the two nuclear and the mitochondrial markers included 123, 77, and 38 sequences, with 704, 888, and 355 positions in length, respectively (Figures 3–5). *D2-D3* tree of *Rotylenchulus* spp. showed two moderately supported clades including *R. borealis* type A and type B sequences (posterior probabilities (PP) = 0.87, 0.93, respectively), including *R. reniformis*, *Rotylenchulus macrodoratus*, and *Rotylenchulus macrosomoides* (Figure 3). All sequences of *R. borealis* from the Netherlands (MW173970-MW173976) and Belgium (MK558206), as well as those of *R. borealis* (= *R. macrosoma*) from Israel and all the sequences from Spain, Serbia, Romania, Hungary, and Greece deposited in the NCBI database clustered together in a highly supported clade (PP = 1.00) and were well separated (PP = 1.00) from *28S* of *R. borealis* (MT775429) from New Delhi (Figure 3). *Plants* **2021**, *10*, x FOR PEER REVIEW 12 of 22

**Figure 3.** Phylogenetic relationships within the genus *Rotylenchulus*. Bayesian 50% majority rule consensus tree as inferred from D2 and D3 expansion domains of 28S rRNA sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. Some branches were collapsed for improving readability of *Rotylenchulus* species. \*\*\* Sequence that needs to be revised under integrative taxonomical approaches. **Figure 3.** Phylogenetic relationships within the genus *Rotylenchulus*. Bayesian 50% majority rule consensus tree as inferred from D2 and D3 expansion domains of 28S rRNA sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. Some branches were collapsed for improving readability of *Rotylenchulus* species. \*\*\* Sequence that needs to be revised under integrative taxonomical approaches.

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**Figure 4.** Phylogenetic relationships within the genus *Rotylenchulus*. Bayesian 50% majority rule consensus tree as inferred from *ITS1* rRNA sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. **Figure 4.** Phylogenetic relationships within the genus *Rotylenchulus*. Bayesian 50% majority rule consensus tree as inferred from *ITS1* rRNA sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. **Figure 4.** Phylogenetic relationships within the genus *Rotylenchulus*. Bayesian 50% majority rule consensus tree as inferred from *ITS1* rRNA sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site.

from *coxI* mitochondrial DNA (mtDNA) sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. The 50% majority rule consensus *ITS1* BI tree also showed two clades, one moder-**Figure 5.** Phylogenetic relationships within the genus *Rotylenchulus*. Bayesian 50% majority rule consensus tree as inferred from *coxI* mitochondrial DNA (mtDNA) sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. **Figure 5.** Phylogenetic relationships within the genus *Rotylenchulus*. Bayesian 50% majority rule consensus tree as inferred from *coxI* mitochondrial DNA (mtDNA) sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gamma-shaped distribution (GTR + I + G). Posterior probabilities of more than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site.

ately and the other well supported including *R. borealis* type A and type B sequences (PP

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The 50% majority rule consensus *ITS1* BI tree also showed two clades, one moderately and the other well supported including *R. borealis* type A and type B sequences (PP = 0.95, 1.00, respectively), including *R. reniformis*, *R. parvus*, *Rotylenchulus sacchari*, and *Rotylenchulus clavicaudatus* (Figure 4). All sequences of *R. borealis* from the Netherlands (MW174239-MW174242) and those of *R. borealis* (= *macrosoma*) from Israel and all the sequences from Spain and Greece deposited in the NCBI database clustered together in a highly supported clade (PP = 1.00).

Finally, the phylogenetic relationships of *Rotylenchulus* species inferred from analysis of partial *coxI* gene sequences showed several clades that were well defined (Figure 5). All sequences of *R. borealis* from the Netherlands (MW182432-MW182435) and sequences from several European countries (Germany, Greece, Hungary, Italy, Portugal, Romania, Serbia, and Spain) deposited in the NCBI database clustered together in a highly supported clade (PP = 1.00).

#### *2.3. Global Distribution Rotylenchulus spp.*

We detected that the genus *Rotylenchulus* exhibited a worldwide distribution across a wide variety of environments and climatic zones (Figure 6). We found that *Rotylenchulus* spp. are widely distributed in warm temperature (−3 ◦C < annual mean temperature < +18 ◦C) and arid (annual precipitation < 300 mm) climate zones, with seven different species for both types, and to a lesser extent in equatorial (annual mean temperature ≥ +18 ◦C) and snow (mean temperature of the coldest month ≤ −3 ◦C) climate zones, with four and one species, respectively (Figure 6). We did not detect species in the polar (mean temperature of the warmest month < +10 ◦C) climate zone (Figure 6). It should be noted that highest diversity of species, although less frequently found, seems to be in the southern part of Africa with mainly warm temperate and arid climatic zones (Figure 6). The species distribution observed in this study revealed that the genus *Rotylenchulus* is adapted to heterogeneous climatic conditions, with an annual mean temperature of 19.14 ◦C, but ranging from 8.36 to 28.58 ◦C, and a mean annual precipitation of 1026.97 mm, but ranging from 1 to 3583.00 mm. This suggests that the occurrence of *Rotylenchulus* species in areas with extremely low values in annual precipitation (i.e., desert lands in Egypt and Iraq; Figure 6) could be due to the establishment of an irrigation regime in agricultural ecosystems. Only four species were reported more than three times in literature review, i.e., *R. borealis* (= *R. macrosoma*), *R. macrodoratus*, *R. parvus*, and *R. reniformis* (Figure 6). The most widely distributed species was *R. reniformis*, followed by *R. parvus*, both reported in all continents except Antarctica (Africa, North and South America, Asia, Australia, and Europe), and *R. borealis* in Africa, Europe, and Middle East Asia (Figure 6). Bioclimatic variables (BIOCLIM) based on temperature (annual mean temperature (BIO1), maximum temperature of warmest month (BIO5), and minimum temperature of coldest month (BIO6)) showed significantly different temperature conditions on the distribution of these most common species (Figure 7). The two major pathogenic species (*R. reniformis* and *R. parvus*) were mainly distributed in tropical, temperate, and arid climates, showing their close relationship with warmer areas with high annual mean temperature, max temperature of the warmest month, and minimum temperature of the coldest month, ranging from 9.55 to 21.11 ◦C, 24.00 to 3583.00 mm and 14.79 to 26.99 ◦C, 1.00 to 1773.00 mm, respectively (Figures 6 and 7). *Rotylenchulus macrodoratus* showed a distribution in temperate climate with annual mean temperature and precipitation ranging from 12.32 to 19.23 ◦C and 526.00 to 1013.00 mm, respectively (Figure 7). The climatic plasticity of *R. borealis* is remarkable in relationship with annual mean temperature and precipitation, ranging from 8.36 to 28.58 ◦C and 160.00 to 1998.00 mm, respectively (Figure 7). *Rotylenchulus borealis* (= *R. macrosoma*) showed statistically significant differences in lower annual mean temperature, max temperature of the warmest month, and min temperature of the coldest month in comparison to *R. parvus* and *R. reniformis* (Figure 7). However, only *R. reniformis* showed statistically significant differences in higher annual precipitation in comparison to the other studied species (Figure 7). Other bioclimatic variables are shown in Figure S1.

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**Figure 6.** World map distribution of *Rotylenchulus* species across different climate conditions. Climatic zones based on type of vegetation [19]. In the species list, the number in brackets indicates the locations cited for each species. **Figure 6.** World map distribution of *Rotylenchulus* species across different climate conditions. Climatic zones based on type of vegetation [19]. In the species list, the number in brackets indicates the locations cited for each species. **Figure 6.** World map distribution of *Rotylenchulus* species across different climate conditions. Climatic zones based on type of vegetation [19]. In the species list, the number in brackets indicates the locations cited for each species.

**Figure 7.** Annual mean temperature, annual precipitation, maximum temperature of warmest month, and minimum temperature of coldest month for *Rotylenchulus* species with ≥ 3 reports (each single dot correspond to a species report). The different lowercase letters indicate the differences in each bioclimatic variable between species. They were tested using ANOVA with a level of significance of *p* < 0.05. **Figure 7.** Annual mean temperature, annual precipitation, maximum temperature of warmest month, and minimum temperature of coldest month for *Rotylenchulus* species with ≥ 3 reports (each single dot correspond to a species report). The different lowercase letters indicate the differences in each bioclimatic variable between species. They were tested using ANOVA with a level of significance of *p* < 0.05. **Figure 7.** Annual mean temperature, annual precipitation, maximum temperature of warmest month, and minimum temperature of coldest month for *Rotylenchulus* species with ≥ 3 reports (each single dot correspond to a species report). The different lowercase letters indicate the differences in each bioclimatic variable between species. They were tested using ANOVA with a level of significance of *p* < 0.05.

#### **3. Discussion**

The primary objective of this study was to decipher the intraspecific diversity of *R. borealis* and *R. macrosoma* by applying integrative taxonomical approaches on several new unidentified *Rotylenchulus* populations from Europe, appearing morphological and morphometrically undistinguishable. Additionally, we aimed to provide new insights into the global distribution and climatic requirements of the genus *Rotylenchulus*.

The resemblance between the mature females of *R. borealis* and *R. macrosoma*, as well as the general similarity between these two species also in their male and immature female forms, host preferences, and host tissue reactions was emphasized by Cohn and Mordechai [18] studying a topotype population of *R. macrosoma* from olive under growth chamber conditions. Our morphometric studies in this research support that both species do not have major differences in basic morphology or in morphometric informative characters such as immature female body length, stylet length, tail hyaline region, and spicules morphology and morphometry, showing a remarkable example of a close phylogenetic relationship of both species. The results on our new measurements on *R. macrosoma* immature female paratype specimens from WANECO and USDA nematode collections suggest that the range in stylet length could probably be shorter than that provided in the original description [10], but unfortunately no other paratypes could be studied. The morphometric comparison of an important number of populations from *R. borealis* and *R. macrosoma* exhibited morphometric variation normally expected among populations of the same *Rotylenchulus* species. The higher values in all of the three main distinguishing morphometric characters between both species were detected in Israel, Crete, and a Spanish population from Huévar del Aljarafe (southern Spain), but these differences do not justify the separation in two different species [3,4,9,10].

In the present study, in which sequence data obtained from *28S* and *ITS1* rRNA genes and *coxI* mitochondrial DNA (mtDNA) gene was analyzed, specimens from populations identified as representing *R. borealis* and *R. macrosoma* from the Netherlands and several European countries, including Israel, respectively, clustered together as a single group. This grouping was well supported by the high bootstrap values in the phylogenetic analysis, thereby supporting the synonymization of *R. macrosoma* with *R. borealis*, as already emphasized by Cohn and Mordechai [18].

Phylogenetic analyses based on three molecular markers (*D2-D3* expansion domains of *28S* rRNA gene, *ITS1* region, and the partial *coxI* mtDNA) resulted in a general consensus of species phylogenetic positions clustering *R. borealis* population from the Netherlands with *R. macrosoma* from Israel, together with all other *R. macrosoma* populations previously reported in several European countries. These phylogenetic analyses were congruent with those given by previous studies [3,4,9,16,20], and phylogeny of the *28S* rRNA and ITS regions confirm that *R. borealis* population from the Netherlands is conspecific with *R. macrosoma* from Israel and all other populations from Europe. Our results on *28S* rRNA phylogeny also suggest that *R. borealis* (MT775429) from New Delhi could not be considered conspecific with *R. borealis* and needs to be revised under integrative taxonomical approaches for confirming its specific status. The genus *Rotylenchulus* has rRNA genes that exhibit high levels of intraspecific and intra-individual variation [3,9,16]. However, they seem functional through the reconstruction of secondary structure models and mutation mapping using *R. reniformis* sequences [3]. Qing et al. [16] suggested that these different sequences are paralogs located in different rRNA clusters or chromosomes and that these tandem arrays may still be expanding in number.

Longer stylet specimens do not seem to be associated with differences in molecular markers (as some Andalusian populations with longer stylet were molecularly associated with other species with shorter stylets) (Figures 3–5). Other characters (body length and hyaline tail region length), as shown in Figure 2, seem to be very variable for African populations of *R. borealis*. Palomares-Rius et al. [4], in a broad molecular study of *R. borealis* (*= R. macrosoma*), also studied the molecular species separation, with the results showing incongruent results for species separation between Cretan and other European populations for *R. borealis* (*= R. macrosoma*), even with the relatively high molecular differences between both population groups. In our case, the new population of *R. borealis* found in the Netherlands in this study, and the sequence deposited in GenBank from Belgium (MK558206), had an even lower molecular similarity with other former *R. macrosoma* populations from Crete, Greece, fully supporting our idea of conspecificity.

Thus, the morphological and morphometric results of both species groups, together with the high molecular similarity among ribosomal and mitochondrial genes of both species groups, do not support the validity of *R. macrosoma* as a separate species and give sufficient basis for the synonymization of *R. macrosoma* n. syn. with *R. borealis*. Since the description of *R. borealis* was in 1962 and that of *R. macrosoma* in 1968, the name *R. borealis* has priority over *R. macrosoma*; thus, *R. macrosoma* is proposed here as a junior synonym of the former.

Climate is a critical environmental determinant of the distribution of plant-parasitic nematodes and a key driver of their reproduction and survival [21]. Temperature, moisture, and availability of host plants are three of the most important factors governing the distribution, spread, and symptom development in plants from plant-parasitic nematodes [21,22], including reniform nematodes. The wide distribution of *Rotylenchulus* species likely resulted from an exceptionally wide host range, as well as their ability to survive extended periods in a dehydrated state [1]. Anhydrobiotic *Rotylenchulus* forms have been documented dispersing long distances in dust storms [23]; however, human dispersion through agriculture activities need also to be considered [4]. The influence of annual precipitation on *Rotylenchulus* spp. distribution suggests that this factor may be not as important as expected. However, the majority of the recorded points have crops with irrigation, and this could change the natural precipitation conditions and importance for these species. In particular, the widespread presence of *R. borealis* in localities at higher latitude in Northern Europe and lower latitude in several central African countries indicated and adaptation to heterogeneous climatic conditions and probably survival strategies for colder and warmer winters and humid to dry soil conditions. Similarly, the cosmopolitan distribution of *R. parvus* can be related to the wide range of temperature reproduction (20 to 35 ◦C) and survival (4 to 35 ◦C), as suggested by Dasgupta and Raski [24]. Climate change could expand *R. borealis* to upper latitudes as climate will warm and this will fulfil the ecological requirements of this species, one of the most adapted to lower temperatures among the four most distributed species (*R. borealis*, *R. macrodoratus*, *R. parvus*, and *R. reniformis*). Interestingly, the major diversity of the genus is from sub-Saharan Africa, with the exception of *R. macrodoratus* (Mediterranean distribution) and *R. leptus* (Arabian Peninsula). Siddiqi [25] proposed the idea about the origin of this genus in the Afrotropical (Ethiopian) zoogeographical region, comprising Africa (south of the Sahara); the southern part of the Arabian Peninsula; and various islands, including Madagascar. This idea was reinforced with phylogenetic analysis [3]. However, only three species (*R. borealis*, *R. parvus*, and *R. reniformis*) have been able to colonize different continents with wide ecological requirements, as was shown in this research. Additionally, to these ecological requirements for species distribution, other factors such as survival in anhydrobiotic stage or resting eggs could help with the dispersal of this species to other agricultural areas in the world.

In summary, the present study confirmed the synonymy of *R. macrosoma* with *R. borealis*, and thus the genus comprises 10 valid species. Our data also demonstrate the extraordinary morphological and molecular diversity of *R. borealis* in Europe, Africa, and the Middle East and comprise a paradigmatic example of remarkable flexibility of climatic requirements within reniform nematodes. Nevertheless, despite frequent surveys in different continents of the world, the number of sites studied is still low. Therefore, further surveys are still needed in unsampled geographical areas and climatic conditions, both in plantations and indigenous forests with the aim to identify additional *Rotylenchulus* species.

#### **4. Materials and Methods**

#### *4.1. Nematode Populations and Morphometric Studies*

One of the authors (G. Karssen) visited the type locality of *R. borealis*, and the place reported in the original description was lost, i.e., was filled up by new building of houses. Nevertheless, this author detected a new population of *R. borealis* in another location close near the type locality, at Huissen, Betuwe region, the Netherlands. This new population, together with mounted paratypes from of *R. macrosoma* and *R. borealis* from the nematode collections Wageningen Nematode Collection (WANECO; slides WT106, WT107, WT110, WT111, and #1025 NT and #1026 NT) and USDA Nematode Collection kindly provided by Dr. Z. A. Handoo (slides T-594p and T-595p), were used for morphological studies.

In addition, some new European reports recently detected and associated with corn and wheat [4] were measured in order to carry out a morphometric comparison with all the measured populations of both species (Tables 2–8). All these populations were compared with the morphometry of all previously studied populations of both species, including a total of 12 populations of *R. borealis* and 16 populations of *R. macrosoma*.

Nematodes were extracted from 500 cm<sup>3</sup> of soil by centrifugal flotation [26] method. For morphometric studies, *Rotylenchulus* specimens were killed and fixed by a hot solution of 4% formalin + 1% glycerol, then processed in pure glycerin [27], as modified by De Grisse [28]. The light micrographs and measurements of each nematode population including important diagnostic characteristics (i.e., de Man indices, body length, stylet length, lip region, tail length, etc.) were performed using a Leica DM6 compound microscope with a Leica DFC7000 T digital camera. Nematodes were identified at the species level using an integrative approach combining molecular and morphological techniques to achieve efficient and accurate identification [4,9]. For each nematode population, key diagnostic characters were determined, including body length, stylet length, a ratio (body length/maximum body width), c' ratio (tail length/body width at anus), V ratio ((distance from anterior end to vulva/body length) × 100), and o ratio ((distance from stylet base to dorsal pharyngeal opening/body length) × 100) [9], and the sequencing of specific DNA fragments (described below) confirmed the identity of the nematode species for each population.

#### *4.2. DNA Extraction, PCR, and Sequencing*

For molecular analyses, in order to ensure that the selected nematodes for extracting DNA are from the same species, we temporary mounted 2 live nematodes from each sample in a drop of 1M NaCl containing glass beads (to avoid nematode crushing/damaging specimens) to ensure specimens conformed to the unidentified populations of *Rotylenchulus*. All necessary morphological and morphometric data by taking pictures and measurements using the above camera-equipped microscope were recorded. This was followed by DNA extraction from a single specimen and polymerase chain reaction (PCR) cycle conditions, as previously described [4,9]. PCR and sequencing of the Dutch population was performed at the Institute for Sustainable Agriculture, Spanish National Research Council (IAS-CSIC) facility, whereas for the Israeli population at Agricultural Research organization (ARO)-Volcani Center, Israel. Several sets of primers were used for PCR. A partial region of the *28S* rRNA gene including the expansion domains D2 and D3 (*D2-D3*) was amplified by using the primers D2A (50 -ACAAGTACCGTGAGGGAAAGTTG-30 ) and D3B (50 -TCGGAAGGAACCAGCTACTA-30 ) [29]. The internal transcribed spacer region (*ITS*) was amplified using forward primer TW81 (50 -GTTTCCGTAGGTGAACCTGC-30 ) and reverse primer AB28 (50 -ATATGCTTAAGTTCAGCGGGT -30 ) [30]. The *coxI* gene was amplified using the primers JB3 (50 -TTTTTTGGGCATCCTGAGGTTTAT-30 ) and JB5 (50 -AGCACCTAAACTTAAAACATAATGAAAATG-30 ) [31]. The PCR cycling conditions for the *28S* rRNA primers were as follows: 94 ◦C for 2 min, followed by 35 cycles of 94 ◦C for 30 s, an annealing temperature of 55 ◦C for 45 s, and 72 ◦C for 1 min, and 1 final cycle of 72 ◦C for 10 min. The PCR cycling for *coxI* primers was as follows: 95 ◦C for 15 min, 39 cycles at 94 ◦C for 30 s, 53 ◦C for 30 s, and 68 ◦C for 1 min, followed by a final extension

at 72 ◦C for 7 min. PCR volumes were adapted to 25 µL for each reaction, and primer concentrations were as described in De Ley et al. [29] and Bowles et al. [31]. We used 5x HOT FIREpol Blend Master Mix (Solis Biodyne, Tartu, Estonia) in all PCR reactions. The PCR products were purified after amplification using ExoSAP-IT (Affimetrix, USB products, Kandel, Germany) and used for direct sequencing in both directions with the corresponding primers. Israeli amplification products were cloned before sequencing using pGEM-T easy vector systems (Promega). The resulting products were purified and run in a DNA multicapillary sequencer (Model 3130XL Genetic Analyzer; Applied Biosystems, Foster City, CA, USA), using the BigDye Terminator Sequencing Kit v.3.1 (Applied Biosystems) at the Stab Vida sequencing facility (Caparica, Portugal). The sequence chromatograms of the 2 markers (*coxI* and *D2-D3* expansion segments of *28S* rRNA) were analyzed using DNASTAR LASERGENE SeqMan v. 7.1.0. Basic local alignment search tool (BLAST) at the National Center for Biotechnology Information (NCBI) was used to confirm the species identity of the DNA sequences obtained in this study [32]. The newly obtained sequences were deposited in the GenBank database under accession numbers indicated on the phylogenetic trees and in Table 1.

#### *4.3. Phylogenetic Analysis*

Sequenced genetic markers in the present study (after discarding primer sequences and ambiguously aligned regions) and several *Rotylenchulus* spp. sequences obtained from GenBank were used for phylogenetic reconstruction (Table 1). Outgroup taxa for each dataset were selected on the basis of previous published studies [3,4,9]. Multiple sequence alignments of the newly obtained and published sequences were made using the Fast Fourier transform-normalized similarity matrix (FFT-NS-2) algorithm of MAFFT v. 7.450 [33]. Sequence alignments were visualized using BioEdit [34] and edited by Gblocks ver. 0.91b [35] in Castresana Laboratory server (http://molevol.cmima.csic.es/castresana/ Gblocks\_server.html) using options for a less stringent selection (minimum number of sequences for a conserved or a flanking position: 50% of the number of sequences + 1; maximum number of contiguous no conserved positions: 8; minimum length of a block: 5; allowed gap positions: with half).

Phylogenetic analyses of the sequence datasets were based on Bayesian inference (BI) using MRBAYES 3.2.7a [36]. The best-fit model of DNA evolution was calculated with the Akaike information criterion (AIC) of JMODELTEST v. 2.1.7 [37]. The best-fit model, the base frequency, the proportion of invariable sites, and the gamma distribution shape parameters and substitution rates in the AIC were then used in phylogenetic analyses. BI analyses were performed under a general time reversible, with a proportion of invariable sites and a rate of variation across sites (GTR + I + G) model for *D2-D3*, *ITS1* rRNA, and the partial *coxI* gene. These BI analyses were run separately per dataset with 4 chains for <sup>2</sup> <sup>×</sup> <sup>10</sup><sup>6</sup> generations. The Markov chains were sampled at intervals of 100 generations. Two runs were conducted for each analysis. After discarding burn-in samples of 30% and evaluating convergence, we retained the remaining samples for more in-depth analyses. The topologies were used to generate a 50% majority-rule consensus tree. Posterior probabilities (PP) were given on appropriate clades. Trees from all analyses were visualized using FigTree software version v.1.42 [38].

#### *4.4. Data Collection of Global Distribution of Rotylenchulus spp. and Statistical Analysis*

The species distribution data of *Rotylenchulus* spp. were exhaustively compiled from the national and regional nematofauna records worldwide from databases (Google Scholar, Web of Sciences, Scopus, and PubMed) and specialized literature (nematological and phytopathological journals) during the period 2020–1940. We selected only those articles satisfying one the following criteria for this review: (1) contained geographical information about the presence and/or abundance of reniform nematodes (*Rotylenchulus* spp.); (2) contained data on their taxonomy, morphology, molecular identification, ecology, pathogenicity, and provided localities of each population. Articles lacking information about geographic

coordinates were cross-checked using Quantum GIS v. 3.12.0 [39]. Nevertheless, since *R. reniformis* has been associated with hundreds of crops and native plants in many regions of the world (on the four aforementioned databases we found 9640, 1377, 446, and 189 studies, respectively), only selected reports concerning geographical information were selected, and duplicity of reported localities were not included.

We used bioclimatic predictors (BIOCLIM) based on temperature and precipitation [40] to detect environmental conditions associated with the global distribution of *Rotylenchulus* spp. and to compare the climate spaces for the different species. Additionally, we plotted the global distribution *Rotylenchulus* spp. across climate zones on the basis of the type of vegetation [19]. Only species with more than 3 reported populations were plotted in order to assess the range of climatic variables for each species. Species with type locality only or occasional records were omitted.

The analysis on the bioclimatic variables for *Rotylenchulus* spp. with more than 3 reported populations was concentrated in 18 variables: BIO1 (Annual mean temperature), BIO2 [Mean Diurnal Range (Mean of monthly (max temp-min temp)], BIO3 [Isothermality, (BIO2/BIO7) \* 100], BIO4 [Temperature seasonality, (standard deviation \* 100)], BIO5 (maximum temperature of the warmest month), BIO6 (minimum temperature of the coldest month), BIO7 [temperature annual range (BIO5-BIO6)], BIO9 (mean temperature of driest quarter), BIO10 (mean temperature of the warmest quarter), BIO 15 (precipitation seasonality, coefficient of variation), and BIO18 (precipitation of the warmest quarter). To detect the influence on *Rotylenchulus* spp. of the different bioclimatic variables, we used one-way ANOVA among species conducted using the R v. 3.5.1 freeware [41]

**Supplementary Materials:** The following material is available online at https://www.mdpi.com/22 23-7747/10/1/7/s1. Figure S1. BIOCLIM variables for *Rotylenchulus* species with ≥ 3 reports. BIO3 [Isothermality, (BIO2/BIO7) \* 100], BIO4 [Temperature seasonality, (SD \* 100)], BIO7 [Temperature annual range (BIO5-BIO6)], BIO9 (mean temperature of driest quarter), BIO10 (mean temperature of the warmest quarter), BIO 15 [precipitation seasonality (CV)], BIO17 (precipitation of driest quarter), and BIO18 (precipitation of the warmest quarter).

**Author Contributions:** Conceptualization, J.E.P.-R., I.C.-C., A.A.-Y., G.L.-R., C.C.-N., S.B.M., G.K., and P.C.; methodology, J.E.P.-R., I.C.-C., A.A.-Y., G.L.-R., C.C.-N., S.B.M., G.K., and P.C.; software, J.E.P.-R., I.C.-C., A.A.-Y., G.L.-R., C.C.-N., and P.C.; analysis, J.E.P.-R., I.C.-C., A.A.-Y., G.L.-R., C.C.-N., and P.C.; resources, J.E.P.-R. and P.C.; writing, J.E.P.-R., I.C.-C., A.A.-Y., C.C.-N., S.B.M., G.K., and P.C. All authors contributed to the final discussion data, and read and approved the final manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by grant RTI2018-095925-A-100 from Ministerio de Ciencia, Innovación y Universidades, Spain, grant 201740E042 "Análisis de diversidad molecular, barcoding, y relaciones filogenéticas de nematodos fitoparásitos en cultivos mediterráneos" from the Spanish National Research Council (C.S.I.C.), and by the Humboldt Research Fellowship for Postdoctoral Researchers awarded to the third author (A.A.-Y.).

**Data Availability Statement:** The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

**Acknowledgments:** We would like to thank J. Martin Barbarroja (IAS-CSIC) for their excellent technical assistance in surveys and management of soil samples, as well as further anonymous reviewers and editors for their effort in reviewing the manuscript and helping improve this study. This research is part of the PhD project of the second author. The second author is a recipient of a contract from Ministry of Science and Innovation for Predoctoral Researchers in Spain, PRE2019-090206. The third author is a recipient of the Humboldt Research Fellowship for Postdoctoral Researchers at the Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

#### **References**


### *Review* **Optimizing Sampling and Extraction Methods for Plant-Parasitic and Entomopathogenic Nematodes**

**Mahfouz M. M. Abd-Elgawad**

National Research Center, Plant Pathology Department, Agricultural and Biological Research Division, El-behooth St., Dokki 12622, Egypt; mahfouzian2000@yahoo.com

**Abstract:** Plant-parasitic and entomopathogenic nematodes (PPNs and EPNs) are key groups in crop production systems. This study aims at optimizing nematode sampling and extraction methods to benefit integrated pest management (IPM) through (a) management of PPNs and (b) use of EPNs. The impacts of these methods on PPNs and EPNs to achieve cost-effective and efficient IPM programs are presented. The common misuses of sampling and extraction methods are discussed. Professionals engaged in IPM should consider sampling the reliability level in the light of the intended goal, location, crop value, susceptibility, nematode species, and available funds. Logical sampling methodology should be expanded to integrate various factors that can recover extra EPN isolates with differential pathogenicity. It should seek for the best EPN-host matching. Merits of repeated baiting for EPN extraction from soil and sieving for PPN recovery from suspensions are presented. Their extraction values may be modelled to quantify the efficiency of nematode separation. The use of proper indices of dispersion to enhance the biocontrol potential of EPNs or save costs in nematicidal applications is ideally compatible with IPM programs. Selecting an extraction method may sometimes require further tests to find the best extraction method of the existing fauna and/or flora. Cons and pros of modern sampling and extraction techniques are highlighted.

**Keywords:** index of dispersion; IPM; modelling; molecular approaches; sampling and extraction

#### **1. Introduction**

Plant-parasitic and entomopathogenic nematodes (PPNs and EPNs) represent two key groups as damaging [1] and beneficial [2] organisms, respectively in crop production systems. Their sampling and extraction methods should be optimized to benefit integrated pest management (IPM) through (a) management of PPNs and (b) use of EPNs. Addressing both groups might be a little tricky but the soil is their original habitat. They have a few sampling and extraction issues related to assessing their populations, distribution patterns, and interactions with many other factors within the context of IPM.

#### **2. Sampling Goal and Conceived Scenario**

As sampling pertains importantly to every aspect of nematode study and management, its significance and drawbacks will cover all related scopes. Sampling of PPNs is basically intended to detect, identify, and estimate their population densities in soil or plant tissues. Its timing, pattern, intensity, tool, and the associated material sampled, all depend on the desired goal, carefully conceived scenario to avoid problems and allocated funds. For example, heavily nematode-infected plants may consequently possess too small a root system to support many PPNs, whereas samples from nearby less infected plants may harbor more nematodes for relatively large root system. Soil samples preferably obtained from the rhizosphere are often used to count PPN number per unit (either volume in cm<sup>3</sup> or weight in g, but it is quite better in this case to express nematode number per g of feeder roots in the same volume of soil. This is especially important to avoid discrepancy of PPN population densities relative to plant damage. Clearly, this issue will result in a

**Citation:** Abd-Elgawad, M.M.M. Optimizing Sampling and Extraction Methods for Plant-Parasitic and Entomopathogenic Nematodes. *Plants* **2021**, *10*, 629. https://doi.org/ 10.3390/plants10040629

Academic Editors: Zafar Handoo and Mihail Kantor

Received: 3 February 2021 Accepted: 1 March 2021 Published: 26 March 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

false correlation between nematode population levels and plant growth parameters/yields based on using either volume or weight unit, not both.

Sampling may also be utilized in a survey, advisory service, research, or relating population level to specific biological/ecological factor(s) or production practices. Plant root, instead of soil samples, may sometimes be good alternatives. Even one individual of any root-knot nematode (RKN) *Meloidogyne* species in a root sample of a highly susceptible crop, may call for PPN control measure, be it (regulatory, cultural, and sanitary methods, nematicide, rotation, resistant variety); e.g., according to the number of RKN-galls, more than one of these control methods may be properly used in IPM [1,3]. This applies for most species/varieties of solanaceous (tomato, eggplant, potato, pepper) and cucurbitaceous (melon, watermelon, squash, pumpkin, zucchini, cucumber) crops. For advisory service, soil and roots should be sampled for PPNs at planting or pre-planting of annual crops.

Sampling to relate the nematode population level to specific biological/ecological factor(s) or production practices can effectively contribute in IPM. It can monitor population level and impact of any biological control agent (BCA) for its further development. It can also detect harmful organisms to prevent their suppression of any beneficial invertebrate [4] in IPM. In such cases, sampling may be done just at the planting and harvest times. However, more informative sampling times may be better. It would preferably fit different growth stages of the plant. This enables pest control operators to know whether prevalence of natural or introduced BCA gradually or rapidly decline with each stage. This approach clearly addresses IPM for both PPNs and EPNs. It may monitor BCAs (e.g., EPNs against insect pests or fungi/bacteria against PPNs) for different IPM programs.

#### **3. Ecological Considerations and Concepts**

It is well known that there is inherited sampling error, but the most accurate samples should be obtained from locations and at times when population size is greatest in general [5,6]. Inaccuracy of assessing nematode population level is known as sampling error. Precision/reliability is the probability of getting a specified degree of sampling accuracy. Both should be considered for sound IPM. Sampling reliability is used either in terms of the standard error to mean ratio (*E*) or the ratio of the half-width of the confidence interval to the mean (*D*) of the samples [7,8]. The reliability level acceptable as a basis for PPN control in IPM decisions may vary due to the location, crop, nematode species, and available fund or personnel.

Sampling should be done to get accurate data on the pest's ecology for effective IPM. Its design and timing should also enable us to grasp BCA ecology and biology as well as host-BCA interactions. Edaphic and crop factors (e.g., soil properties, cultivar susceptibility, nematode-economic threshold, planting, harvest times, and previous crops), and climatic factors (rainfall, temperature, humidity, solar efficacy) may add better perception for the used IPM strategy. These variables can reveal the positive or negative role of a specific production practice in IPM. Generally, pesticide usage, tillage, crop rotation, and fallow periods can adversely disrupt BCA populations [9]. Biological control of PPNs using an introduced BCA may not be as effective in various settings as that of indigenous BCA due to ecological validity. Soil moisture and texture [10], salinity [11], mulching [12], and pH [13] were also found to modulate EPN populations directly or indirectly by influencing their hosts or enemies [4].

Though often used, random soil samples suffer from the possibility that samples may chance to target an unimportant range of biotic and edaphic factors. So, most soil nematodes and related organisms remain unsampled. In contrast, stratified random sampling can upgrade efficiency to assess population densities and related factors if variations in a stratum are obviously less than that among strata. So, dividing the strata should be based on factors known to the farmer; e.g., difference in soil characteristics, productivity of previous crops, or susceptibility of these crop varieties to PPN-infection. Stratified random sampling may not only offer better estimate of PPN population levels but can also lower pest-control cost via IPM of individual or uniform strata. Regular zigzag

patterns with dimensions smaller than the nematode foci can adequately sample PPNs and offer proper weight to the larger, non-infested area as nematodes mostly have clumped distribution [7]. Such patterns can more accurately assess the population density than random sampling especially when more sampling points are taken across plant rows than within rows [5].

Nematode extraction should consider the related settings and nematode genera. For example, extraction of nematode cysts (genera Heterodera and Globodera) may differ from that used for *Meloidogyne* spp. [6,14]. Proper extraction techniques should best fit the existing organisms (e.g., protozoa, fungi, bacteria, invertebrate predators, omnivores, and microarthropods) as the extraction efficiency varies among species. Sucrose centrifugation is the most efficient method for microarthropod extraction. It is) used [15] as a model to study nematodes and their natural enemies such as collembolan and acari mites. Such techniques as species-specific primers and probes in quantitative polymerase chain reaction (qPCR) assessment, colony culture to count colony forming units per unit of root weight, sucrose centrifugation, Baermann funnel, sieving, or baiting with EPN-susceptible host may vary in the extraction efficiency [6,14,16].

Various factors can share in cost-effective and efficient IPM programs. Cost can be reduced via more efficient sampling procedures. A common mistake is to assume that there is always a linear relation between sampling cost and sample size. The variation due to laboratory procedures in the sampling and extraction methodology are mostly unknown and may even exceed field variation that requires more samples. One would rather improve methods instead of reducing samples. A big gap in the accuracy and precision of nematode counts resulting from inter-laboratory proficiency tests was reported [17]. The reasons may be the different custom-made equipment, laboratory-specific adaptations, and/or relative operator's experience. Manufacturers of sampling and extraction tools should continuously contact the related stakeholder for tools' fine-tuning and upgrading. The tests should further be expanded to evaluate and fix the quality of the laboratories' own methods especially in developing countries. This will help to gain insights into possible trends and potential refinements. Mechanized sampling could improve the accuracy and precision, but it requires well-qualified operator on the mechanical sampling equipment (e.g., operate the tractor in a sound and safe manner, sound review for the map of sampled area and handling of the samples, bags, and bag holder).

#### **4. Sampling Tools**

Conventional soil samplers [14] such as augers to obtain cores are often used in developed countries while an ordinary spade, bladed shovel, or hand trowel is frequently used in developing countries. The use of these variable samplers for similar IPM programs may lead to erratic results. The difference in volume/area of the sampling units may influence the obtained distribution patterns of the pest or BCA [18]. Though acceptable, they lack in the standardization of the used sampler which may falsely contribute to the value of the same index of nematode dispersion used (Table 1). Even sampling for similar objectives is taken with cores that may differ in diameters (e.g., 17, 18, 20, and 25 mm) from one trial to another. This may lead to inconsistent results and misinterpretation of data. For instance, sampling the same site with two concentric circles (as core or unit area) might unexpectedly reveal different spatial patterns of the same population. These patterns (Figure 1) are so different that the nematode counts would require log (for aggregated distribution) or square root (for random distribution) data transformations to equalize experimental treatment variances; a pre-requisite to use parametric statistical methods such as analysis of variance, regression, and correlation [19]. Moreover, adopting a standardized sampler can grant sound comparison between different trials and expand analysis of individual trials for perfection of the conclusions. For vertical distribution, deep-rooted crops require deeper sampling (e.g., grape; 60 cm depth) than shallow-rooted ones (e.g., squash; 20 cm depth) but generally a depth of 30 cm can target the nematodes in the zone of their highest density. A standard core of 2 cm diameter with adjustable

depths may be suggested unless it stifles an innovation or experimental goal. Notably, this suggestion avoids other drawbacks because characteristics of a distribution pattern are often dependent on the "standard" scale over which it is processed. Manufacturers and suppliers of such tools would preferably consult pest control operators to standardize their products for better IPM.

**Table 1.** Comparison of index of aggregation (Ia)\* values of five studies on entomopathogenic nematode [EPN] distributions using different sampling approaches in various regions.


I<sup>a</sup> = the observed value of distance to regularity/the mean randomized value [25]; qPCR: quantitative polymerase chain reaction.

**Figure 1.** Two quadrat sizes are represented by concentric circles. The inner circle represents random nematode distribution around plant main root and the outer circle represents clumped nematode distribution around lateral fibrous roots as well.

#### **5. Addressing Nematode Distribution Patterns**

These patterns, revealed by sound sampling, can enable pest control operators to: (1) choose plant material that best fit to specific locations, (2) leverage variable rate methods for the used nematicides, and (3) characterize relationships between organisms in space and time for careful IPM. Stuart and Gaugler [25] stressed that nematode clumped distribution can have great ramifications at the community levels by changing the dynamics of parasitism, predation, and competition. Such spatial (horizontal or vertical) and temporal distributions may be compared with one or more of the relevant biotic and physical forces for better development of IPM. Moreover, definite models [26–28] (4) can serve in the nematode-count transformation to fulfill accurate treatment comparisons.

However, samples often become costly to offer these merits of distribution patterns. So, a trade-off between objectivity and cost is necessary. For convenience, recent trends offer different accuracy levels for the same sample size and tactic to meet affordability. Iteration was also used to further improve optimum sample size [29]. Increasing the cost by

increasing the number of cores or samples, or both, should be weighed against the benefit it provides via accuracy and reliability [30]. Collecting more small cores, though costly, offers a more accurate mean estimate than an equivalent amount of soil collected as fewer large cores [5]. Moreover, collecting numbers of cores/sub-samples from a targeted area before mixing into a composite sample to homogenize variance of nematode counts may reduce costs though it introduces another potential source of statistical variability. A modification is to take subsample(s) from the composite sample to estimate the population density and/or the numbers of BCA/endospores associated with the nematodes per sample to reduce costs.

#### **6. Indices of Nematode Dispersion**

We should cautiously suggest type and number of these indices to fit the goal of the work. For instance, contrary to Taylor's Power law (TPL) [31], Spatial Analysis by Distance Indices (SADIE) has geographic coordinates. [32] reviewed geostatistical models as another group that can apply sample values and locations simultaneously to depict spatial patterns and estimate values at unsampled locations. Yet, this group does not offer tests to assess the statistical significance of the patterns but SADIE software can determine the statistical probability level of spatial association between organisms or the same organism at different times [33]. So, these indices can complement each other to show more aspects of the distribution patterns. Gorny et al. [34] manipulated two indices to set sound sampling protocols and determined specific sites for nematicide usage. Moreover, Wu et al. [23] used SADIE to prove regulation of EPNs by a natural enemy. Therefore, the use of such indices to enhance biocontrol potential or to save costs in nematicidal applications is ideally compatible with IPM.

Conceivably, nematode spatial patterns are more representative in samples taken far apart which will be more impacted by various microhabitats than samples taken close to each other. This concept could be backed by using both semivariogram and SADIE analyses together to better grasp PPN and/or EPN spatial patterns and spatiotemporal dynamics [34,35]. To facilitate its use, SADIE program in terms of its major indices and graphical displays were recently reviewed [36]. It was integrated with other methods to study soil food webs in citrus orchards in order to develop new biocontrol approach that can serve in IPM [32,37].

Complementary methods [38,39] can optimally detect spatial heterogeneity when clusters are situated on elongated or square domains and near to the edges of the surveyed sites. They can reveal clusters with small radius and in sample size smaller than that of SADIE as well as adjust for the absolute location or the magnitude of the counts.

#### **7. Other Examples to Optimize EPN Sampling and Extraction**

A main challenge facing the use of EPN is to broaden the EPN species/strain library in order to provide suitable matches of nematodes to target pests. This will certainly optimize their benefits as biocontrol agents. The wide variation of EPN sampling makes results from a definite case-study difficult to generalize. Nevertheless, it is quite evident that the percentage of samples positive for EPN in many typical surveys worldwide are relatively low; <35% [12,40]. There is a dire need to increase it to likely offer new strains and upgrade EPN-host matching. So, novel sampling concepts to get EPN with high recovery frequency value and differential pathogenicity should be further sought. One such recent concept relies on combining four factors. The factors are favorable sampling method, time, site targeting, and use of multiple extraction technique. This combination could recover EPN from the seven surveyed groves and from 61.7% soil samples [24]. On the contrary, only one EPN-positive out of 593 soil samples was detected also in Egypt [41]. However, they used random sampling and single baiting cycle. Moreover, the EPN isolates recovered via rational sampling showed so variable pathogenicity to the strawberry white grub, *Temnorhynchus baal* [42]. Using such criteria or other new concepts to optimize EPN sampling and recovery frequency value should be further tested and expanded.

Another example is the invasive mole crickets as major pests of pastures, turf, and vegetables in the Caribbean Basin where *Steinernema scapterisci* is the only EPN species utilized efficiently as classical biocontrol strategy. It is used against the mole crickets [43]. Classical biocontrol should be expanded via directing sampling and extraction techniques to isolate BCA from environments where the organisms will presumably have had to develop the desired trait [44].

Specifically, the extraction technique using multiple *Galleria*-baiting cycles proved more effective than a single cycle in several studies [25,28,45]. Moreover, stressing by crowding, abiotic/biotic factors in soil, or presence under other suboptimal conditions may prevent or delay the nematode activity for infection [46,47]. Optimizing conditions for infection may gradually revert the EPN activity to infect the baiting insect in a consecutive cycle. Repeated extraction via baiting cycles can usually provide optimal conditions and longer time, for such a revision. Hence, it allows for differential pathogenicity of EPN too. A common technique is to keep the soil samples at about 23 ◦C in suitable cups with 4 last instar *Galleria mellonella* larvae as baits per cup in each cycle. Soil is sometimes watered to remain almost at field capacity during the extraction cycles. Each cup is inspected twice weekly in the first 3–4 weeks but once thereafter. Each cycle ends by inspecting the cups to: *i*) isolate insect cadavers with symptoms of EPN infection. These cadavers are transferred to White traps [48] to fulfill Koch's postulates, and/or *ii*) discard the other dead insects. A new following cycle begins with replacing the infected cadavers/dead insects by new living *G*. *mellonella* larvae. Suspect cadavers that failed to produce EPN-infective juveniles (IJs) are considered negative. The first cycle may be repeated 5–10 times [25,28] depending on the magnitude of EPN-positive samples. Other modifications to improve the baiting method are possible. They may include screening for EPN by using the target insect pest species; e.g., citrus root weevil, *Diaprepes abbreviatus* [49] or pecan weevil, *Curculio caryae* [50], as baits to achieve adequate EPN-host matching. Moreover, two model insect species/baiting at different temperatures to increase and diversify the recovery of EPN were tried [50,51]. These trends to find ecologically adaptable and effective BCAs should not be limited to a specific region or pest. Biocontrol components can strengthen IPM programs by using indigenous, or to a less degree introduced, EPN against the target 'baiting' pest or via setting the best EPN-host matching.

#### **8. Other Sampling and Extraction Methods**

EPNs in soil may be detected directly under binocular microscope via dissecting or enzymatic hydrolysis of the EPN-infected-cadavers or indirectly by scoring the cadavers per sample. Other methods of extracting EPNs from soil or their host insects [16,52] and PPNs from soil or plant tissues [5–7,14] were reviewed. Pest control operators must consider their relative merits and demerits for perfection of IPM. For instance, sieving and centrifugation using a sucrose gradient may directly extract and quantify dead and live EPN-IJs and PPNs from soil samples. The method may recover a larger proportion of EPNs in soil than insect baiting. It is less biased due to differential pathogenicity among EPNs extracted via the baiting method. However, it is rarely used to recover EPNs as it is more labor-intensive and require taxonomic expertise for the recovered nematodes [16]. Baermann funnel method and its modifications can extract only live nematodes. Selecting a method may sometimes require further tests to find the most efficient extraction method of the existing fauna and flora related to IPM [15].

#### **9. Quantifying Extraction Efficiency of EPNs with a Model Used for PPNs**

Nematode extraction via sieving, mostly favored for PPNs. or insect baiting, often used for EPNs, is based on physical (aperture sizes of the sieves) or biological (susceptibility of the baiting insects) background, respectively. So, it is exciting to find out their extraction efficiency herein via modeling. To test efficiency of sieving processes, the PPN suspension is poured through a stack of like sieves, and the recovery on each sieve is assessed. So, the cumulative recovery is related to number of times sieved. [53] related the number of

sieving to percentage recovery of PPNs in the formula: Percentage recovery = 100 (1 − *a x* ) where *a* is proportion of total number of PPNs present of a given length which pass through the sieve, and *x* is number of times sieved. The equation is used herein for EPN extraction too where *a* is the proportional loss at each *Galleria*-baiting cycle, and *x* is the number of repetitions (baiting cycles). The raw data of two EPN surveys were applied to the formula where 6 [28] or 10 [24] *Galleria*-baiting cycles produced positive samples (Figure 2). Herein, the practical % recovery of EPNs vs. theoretical corresponding values were 79% vs. 99% and 74.3% vs. 98.3% for % recovery of EPNs from mango [28] and citrus [24] orchards, respectively (Figure 2). This formula may offer approximate quantification of separation efficiency during the extraction processes. It allows consideration of the benefit to be gained by devoting more time and resources into the used EPN separation techniques [14,54] for IPM.

**Figure 2.** Calculated relationships between number of *Galleria*-baiting cycles and percentage recovery of entomopathogenic nematodes-infected insects for surveys of mango and citrus orchards.

#### **10. Molecular vs. Traditional Sampling and Extraction Technology**

Limitations of traditional sampling and extraction methods are apparent. Notwithstanding the utility of a series of extractions using the above-mentioned methods to significantly enhance the PPN- and EPN-separation efficiency, they do not provide a full recovery rate [6,45]. Moreover, not all EPN species can be isolated using just one insect bait species [55]. The most common *Galleria*-baiting method can hamper the laboratory maintenance of certain EPN species (e.g., *Steinernema kraussei*).

Sampling and extraction of biochemicals are relatively newer approaches. Relevant assays [6,16] may extract proteins or isozymes from the nematodes (e.g., for identification) or from their hosts (e.g., for measuring enzyme activity of a host species/cultivar related to its compatible or incompatible reaction to nematode infection). These accurate assays may designate PPN susceptible or resistant plant cultivars and assess the contribution of BCAs in priming the plant against PPNs [56]. Extraction of isozymes has enabled the study of species diversity, frequency, and abundance to study the nature conservancy and biodiversity. Moreover, new isozyme phenotypes may be detected particularly in conserved areas that may thrive our grasping of biogeography and ecology of key species such as RKNs [57]. Moreover, sampling methods to detect and measure volatiles in the soil atmosphere in situ can enable the study of chemical cues that are critical to communicate across various trophic levels of different organisms. Hence, they can assist in grasping the IPM scenario in the soil [32]. However, reliable results can often be obtained with nematodes at a specific developmental stage.

In contrast, DNA-based diagnostics do not rely on the express products of the genome and are independent of environmental influence or developmental stage [6]. Significant gains in sampling and extraction of nematodes and their related organisms are in progress due to introducing the polymerase chain reaction (PCR) and relevant techniques [6,19,58]. The relationship between the EPN numbers in soil samples extracted by conventional techniques and the numbers recovered via qPCR approaches could be established by [59] as a base to count EPN via the molecular technique. The novel set of primers and probes integrated with the qPCR systems could then optimize a protocol for extracting nematodes and DNA from soil samples. The protocol can detect even one EPN added to a nematode community [60]. This method could detect and quantify soil-inhabiting organisms (EPNs and their related nematophagous fungi, ectoparasitic bacteria, and competitor free-living nematodes) in Florida citrus groves and examine the EPN soil food web in various ecological settings [16]. Campos-Herrera et al. [61] used qPCR to reveal sympatric distributions of EPN species and detected their low numbers in samples where the insect baiting method failed.

These molecular tools were integrated with appropriate models, e.g., indices of dispersion, in order to: (1) clarify soil food webs that modulate the rates of a herbivore-disease complex [37], (2) prove regulation of EPNs by a natural enemy where manipulating a soil property (pH) can enhance biocontrol of an insect pest [4], and (3) examine geospatial relationships between native EPN and the fungus *Fusarium solani* in citrus habitats [23]. Such gains can enable us to better conceptualize biological control potential of pests and pathogens within sound IPM context.

New molecular methods are still in the pipeline or are of limited geographic scale. Using species-specific primer-probe combinations and the high throughput sequencing [62] to characterize nematode communities and their natural enemies in soil are often used in developed countries. These methods are generally costly and require a variety of reagents and equipment of medium-high technology levels that are rarely produced in developing countries. Their cost issue will exacerbate if the local currency has gone a drastic exchange rate. A current limitation is that qPCR will identify and quantify only those organisms for which the molecular toolkits are employed. It does not reveal the presence of those species not screened for, or species for which the qPCR was not developed. Therefore, in areas where EPN diversity is not well known, the insect-bait method is done to isolate new and/or unexpected species [16]. The insect-baiting can detect new species and provide their activity (ability to kill) data.

The primer/probe combination is designed to be specific for a single species, but discovery of closely related species in the sampled area might increase the likelihood of cross-amplification. So, optimizing the approach in a new system is recommended. It requires great skill in molecular biology. If not, contradictory results may be due to imperfectly carried out tests. Moreover, contamination of the used reagents may indicate false positives for some EPN species. In this case, re-sampling and repeating the tests will be required and increase the costs. Finally, qPCR and insect-baiting may or may not agree. The qPCR method indicated high numbers of IJs, but no insects were infected when the same soil was baited [63]. So, more studies are needed to trust the merits and demerits of each technique (qPCR and insect-bait).

In parallel to EPN, adequate methods for DNA extraction from the PPNs and related BCA are going ahead. For instance, techniques using beacon probe qPCR to detect, quantify, and surveil PPN antagonists in samples are applied. Regaieg et al. [64] used this technique to evaluate capability of the fungus *Verticillium leptobactrum* to colonize RKN-egg masses. Its accurate quantification of the *V. leptobactrum* DNA over the egg masses can help in unraveling the complexity of the soil ecology that has many biological and physical factors. These methods can identify pathogens such as PPNs and discriminate resident microbial populations and cells or propagules which form the released BCA [65]. Isolation of BCAs and genomic DNA extraction from the organisms are described elsewhere [66]. The methods are ideally used collectively; combining morphology, biochemical, and molecular attributes of the organism. This strategy is necessary to strengthen diagnose, define species boundaries, and offer a comprehensive database for BCA and PPN species that can serve IPM programs [57]. Multiplex PCR can detect one or several species in a nematode mixture by a single PCR test, thus decreasing diagnostic time and costs. Cautious must be exercised in this technique for identifying several nematode targets in one assay. It is limited by the available primer pairs that can be used in a reaction and the number of bands that can be identified without giving false-positive results [6]. It requires precise optimization of the reaction conditions for the primer sets used simultaneously in the test.

In conclusion, advances in IPM programs related to nematology can be achieved via optimizing sampling and extraction methods. Solving their related issues via perseverance will lead to gain more experience and refine current methods. The price of related devices on which new technologies are based usually drops rapidly after a short marketing time. So, it is expected that decreasing costs for sequence analyses will allow its wider application for diagnostics and quantification of nematodes and related organisms. This optimism will serve IPM programs concerning nematodes in many ways such as unravelling the complexity of nematode interactions in soil and characterizing their food webs, taxonomy, and best EPN-host matching.

**Funding:** This research was funded by STDF, US-Egyptian project cycle 17 grant number 172 and The NRC in-house project No. 12050105 entitled Pesticide alternatives against soil-borne pathogens and pests attacking economically important solanaceous crops. funded by The National Research Centre.

**Acknowledgments:** This article is supported in part by the US-Egypt Project cycle 17 (no. 172) entitled "Preparing and evaluating IPM tactics for increasing strawberry and citrus production." The study was also supported in part by the NRC In-house project No. 12050105 entitled "Pesticide alternatives against soil-borne pathogens and pests attacking economically important solanaceous crops". The author thanks Larry Duncan and Zafar Handoo for their valuable comments on the manuscript.

**Conflicts of Interest:** The author declares no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


### *Review* **Taxonomy, Morphological and Molecular Identification of the Potato Cyst Nematodes,** *Globodera pallida* **and** *G. rostochiensis*

**John Wainer \* and Quang Dinh**

Agriculture Victoria Research, Department of Jobs, Precincts and Regions, Bundoora, VIC 3086, Australia; quang.dinh@agriculture.vic.gov.au

**\*** Correspondence: john.wainer@agriculture.vic.gov.au

**Abstract:** The scope of this paper is limited to the taxonomy, detection, and reliable morphological and molecular identification of the potato cyst nematodes (PCN) *Globodera pallida* and *G. rostochiensis*. It describes the nomenclature, hosts, life cycle, pathotypes, and symptoms of the two species. It also provides detailed instructions for soil sampling and extraction of cysts from soil. The primary focus of the paper is the presentation of accurate and effective methods to identify the two principal PCN species.

**Keywords:** PCN; potato cyst nematode; *Globodera*; taxonomy; detection; morphology; molecular identification; PCR

#### **1. Introduction**

Potato cyst nematodes (PCN) are damaging soilborne quarantine pests of potato and other solanaceous crops worldwide [1,2]. The two most damaging species, *G. pallida* (Stone, 1973) Behrens, 1975, the pale or white cyst nematode, and *G. rostochiensis* (Wollenweber, 1923) Behrens, 1975, the golden cyst nematode, have proved to be highly adaptive at exploiting new environments, being passively transported, undetected across borders, in intimate association with tubers of their major host, the potato. *Globodera* species feeding on potato also include *G. ellingtonae*, restricted to Chile, Argentina, and two states in northwest USA [3–5] and *G. leptonepia* (Cobb and Taylor, 1953) Skarbilovich, 1959 found only once in a ship-borne consignment of potatoes [6,7].

Potato cyst nematodes are obligate sedentary endoparasites that can cause stunting of plants, reduce yields, and sometimes lead to complete crop failure. PCN causes losses of 9% of total potato production in Europe and can cause total losses in other parts of the world when no control strategies are employed [8]. When PCN populations are high in the field, potato yields can be less than the tonnage per unit area of the planted seed [9,10]. PCN presents formidable problems to farmers, advisors, and policy makers due to their small size and cryptic nature within large volumes of soil, their extreme specialization and intimate association with their host, and their adaptation for long-term survival in the soil in the absence of a suitable host. In fact, PCN is recognized throughout the temperate regions of the world as one of the most difficult crop pests to control [11].

As internationally recognized plant-quarantine organisms, efficient sampling and detection methods of PCN are critical to the effective management of these pests in both emergency response and on-going control situations [12–15]. Cysts are the dead remnants of female nematodes and contain hundreds of eggs; they can survive in soil without a host for 20 years or more [16]. *Globodera rostochiensis* and *G. pallida* are closely related species and difficult to be distinguished from each other solely based on morphology. The European and Mediterranean Plant Protection Organization has published a diagnostic protocol for the two species [17].

**Citation:** Wainer, J.; Dinh, Q. Taxonomy, Morphological and Molecular Identification of the Potato Cyst Nematodes, *Globodera pallida* and *G. rostochiensis*. *Plants* **2021**, *10*, 184. https://doi.org/10.3390/ plants10010184

Received: 25 December 2020 Accepted: 15 January 2021 Published: 19 January 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### **2. Nomenclature**

Phylum: Nematoda Diesing, 1861, Order: Rhabditida Chitwood, 1933, Suborder: Tylenchina Chitwood, 1950, Family: Heteroderidae Filip'ev & Schuurmans Stekhoven, 1941, Genus: *Globodera* (Skarbilovich, 1959) Behrens, 1975.

*Globodera pallida* synonyms:

*Heterodera rostochiensis* Wollenweber, 1923 in partim *Heterodera pallida* Stone, 1973 *Heterodera (Globodera) pallida* Stone, 1973 *Globodera pallida* (Stone, 1973) Mulvey and Stone, 1976. *Globodera pallida* common names:

English: PCN, white potato cyst nematode, pale potato cyst nematode; French: nématode blanc de la pomme de terre; Spanish: nemátodo quiste blanco de la papa.

*Globodera rostochiensis* synonyms: *Heterodera rostochiensis* Wollenweber, 1923 *Heterodera schachtii rostochiensis* Wollenweber, 1923 *Heterodera schachtii solani* Zimmermann, 1927 *Heterodera solani* Zimmermann, 1927 *Heterodera* (*Globodera*) *rostochiensis* (Wollenweber, 1923) Skarbilovich, 1959 *Heterodera pseudorostochiensis* Kirjanova, 1963 *Globodera pseudorostochiensis* (Kirjanova, 1963) Mulvey and Stone, 1976 *Globodera rostochiensis* (Wollenweber, 1923) Mulvey and Stone, 1976 *Globodera arenaria* Chizhov, Udalova and Nasonova, 2008. *Globodera rostochiensis* common names:

English: PCN, yellow potato cyst nematode, golden potato cyst nematode, golden nematode, potato root eelworm; French: anguillule a kyste de la pomme de terre, anguillule des racines de la pomme de terre, nématode doré, nématode doré de la pomme de terre; German: kartoffelnematode; Spanish: nemátodo dorado.

#### **3. Hosts**

PCN hosts are restricted to the nightshade family Solanaceae. The most important host is *Solanum tuberosum* (potato) although other agronomic crops such as *Solanum lycopersicum* (tomato) and *Solanum melongena* (eggplant) are also attacked [18]. Up to 90 *Solanum* spp. And their hybrids can be PCN hosts including some weed species. These include *Datura* spp. (devil's trumpets), *Hyoscyamus niger* (henbane), *Nicotiana acuminata* (manyflower tobacco), *Physalis* spp. (husk tomatoes), *Physochlaina orientalis* (oriental physochlaina), *Salpiglossis* sp. (painted tongue), *Capsicum annuum* (chili pepper), and *Jaltomata procumbens* (creeping false holly) [19,20]. For a more complete list of PCN hosts, see [21–24].

Vermiform juveniles and adult PCN cysts can be found either in the soil or attached to roots or tubers, whereas adult males are found exclusively in the soil.

#### **4. Life Cycle**

The PCN cyst is the hardened dead body of a female and protects the eggs within. It is spheroid with a short neck. The female *G. rostochiensis* changes during maturation from white to yellow and then into brown cysts, whereas *G. pallida* changes from creamy white directly to brown. Cysts are highly resistant and long-lived and can be readily spread, mostly in association with soil, by human activities [25].

After infective juvenile nematodes hatch, they can disperse in the soil a distance of about 1 m and infect plants by entering a root near the growing tip. The nematode becomes sedentary, establishing a feeding site by modifying plant cells which then provide nutrients. Infested potato plants have a reduced root system and poor productivity [26]. Plant death can occur [27].

The lifecycle of PCN (Figure 1) can be described as follows:

**Figure 1.** Illustration of the life cycle of *Globodera rostochiensis* (modified after Charles S Papp, Exclusion and Detection, Plant Pest Detection Manual 5:1, California Department of Food and Agriculture, Division of Plant Industry, USA).

A period of 38–48 days (depending on soil temperature) is required for PCN to complete its life cycle [28]. Nematodes reproduce sexually; males are attracted to females by a pheromone sex attractant. Nematodes may mate several times. After mating, each female produces approximately 200–500 eggs [29], dies, and the cuticle of the dead female forms a cyst. Eggs mostly remain dormant within the cyst until receiving a hatching stimulus (i.e., specific chemical released by host plant roots). PCN eggs can remain dormant and viable within the cyst for at least 30 years [16] and are resistant to nematicides [11].

When soil temperatures are warm enough (above 10 ◦C) [30], and hatching stimuli are received [31], second-stage juveniles hatch from the eggs, escape from the cyst, and migrate towards the host plant roots. Egg hatching is stimulated by host root diffusate, but not all eggs hatch (60–80%); by comparison only about 5% will hatch in water. Some eggs do not hatch until subsequent years [2].

Juveniles penetrate roots where they begin to feed. Host plant cells within the root cortex are stimulated to form specialized cells (syncytia) which transfer nutrients to the nematodes. After feeding commences, the juvenile grows and undergoes three more moults to become an adult. Females grow and become round, breaking through the roots and exposing the posterior portion of their body to the external environment.

Male juveniles remain active, feeding on the host plant until maturity, at which time they stop feeding, become vermiform, and seek females [32]. Adult males do not feed. Sex is determined by food supply—more juveniles develop into males under adverse conditions and heavy infestations.

#### **5. Pathotypes**

Pathotypes (or virulence groups) of PCN are characterized by ability to multiply on certain clones and hybrids of *Solanum* spp. Both species of PCN have several pathotypes under several different schemes [1,33–36]. Under the European scheme [35], there are five pathotypes (Ro1–Ro5) for *G. rostochiensis* and three (Pa1–Pa3) for *G. pallida*. A wide range of commercial potato cultivars currently available carry the H1 gene that confers near complete resistance to the Ro1 and Ro4 pathotypes [37] and other genes (e.g., Gro1) confer resistance to all *G. rostochiensis* pathotypes. Although various genes confer a degree of resistance to *G. pallida*, complete resistance is not known, which means that some multiplication of the nematode is possible for most commercial cultivars [38]. The term "pathotype" is now considered too general, as many PCN populations cannot be assigned conclusively to pathotypes [17]. Any population showing signs of a new virulence should be tested as soon as possible.

#### **6. Symptoms**

Symptoms of PCN infestation are not specific and may not be apparent even when crop yield is significantly reduced. At high densities, patches of poor growth can occur in potato crops, sometimes with yellowing, wilting, or necrosis of the foliage. These symptoms may be caused by many other plant pathogens, including other nematodes, and should not be considered proof of PCN presence. If there are clear patches of stunting, plants should be lifted for a visual check for cysts on the roots. This is only possible for a short time at the appropriate stage of the crop; as young females mature into cysts they are easily detached when lifting plants.

When infested plants are lifted carefully, the swollen females or the cysts appear as small bead-like objects attached to the roots and can be easily seen with the naked eye. With severe infestations, cysts may be seen on the surface of tubers or stolons.

A cyst that changes during maturation from white to yellow and then into brown is *G. rostochiensis* while one which changes from creamy white directly to brown is *G. pallida*. Note that this feature can only be used at the appropriate stage of the life cycle: young cysts of both species are white or cream, and mature cysts of both species are brown.

#### **7. Soil Sampling**

Visual symptoms alone cannot be used to identify the presence of PCN in a potato crop. There are two methods available to sample fields for PCN: (1) taking soil samples and processing them in the laboratory; or (2) lifting plants and examining their roots for females or cysts in either the field or laboratory. The latter method has been used to detect low populations, which may have been undetectable by soil sampling [39]. However, plant sampling is extremely labor intensive, and plants are available only during a part of the year or cropping cycle, whereas viable cysts can remain in the soil for many years. Soil samples must be large enough to achieve the required accuracy and sensitivity and must also be derived from many points in the field to ensure that they are representative of the area. Been and Schomaker [40] emphasized the importance of sample point spacing to the probability of detection of PCN cysts in a field. To achieve a 90% average probability of detection, grid sampling at 5 m spacing with 52 g cores (total sample size 6.9 kg/0.33 ha) was recommended as being the best compromise for minimizing sample size and maximizing detection probability, while minimizing time needed to collect and process the samples. This recommendation is based on detecting the minimum abundance of cysts which will cause crop losses, rather than the presence or absence of PCN. The level of sampling depends on the aim: delimiting surveys for biosecurity reasons require a relatively high level of accuracy (i.e., a high probability of detection) whereas routine sampling, for

example of seed potato crops, is generally done at a lower level of accuracy and probability of detection.

#### **8. Cyst Extraction**

*Globodera* spp. Juveniles and adult males can be extracted from soil by general nematode extraction methods such as Whitehead Trays or the more efficient differential flotation [41,42]. An additional cyst extraction on the soil is desirable because a combination of cyst and juvenile or male characteristics is better for identification.

To extract cysts from soil, the commonly used methods are flotation and elutriation. Flotation works on the principle that dried cysts will float. Standard methods include the Fenwick can and Schuiling centrifuge. Elutriation is based on cysts having lower density than soil particles and so can be used for wet soil.

The Fenwick can, as modified by Oostenbrink [19], is the most commonly used instrument for the extraction of cysts from soil samples using the principles of flotation [43,44]. Nematode cysts are relatively light in relation to the inorganic fraction of soil, have a waxy covering, and contain a pocket of air within, so it is possible to separate cysts in the lighter organic fraction of the soil for identification and assessment.

The can tapers toward the top, with a sloping collar around the outside of the rim which collects overflow and directs it towards an outlet. The can has a sloping internal base with a drain plug at its lowest point. Soil is placed at the bottom of the can. Water is then turned on and enters near the bottom of the can. As the can fills, lighter soil particles and cysts flow over the spout and onto sieves from which cysts are "backwashed" after at least 15 min and when the overflow water has become clear.

Soil samples should first be air dried at 37 ◦C for 48 h to ensure consistency of sample weight and to aid floatation of cysts, which improves efficiency of recovery. If relatively free of organic matter, put the sample of soil directly into the Fenwick can or into a funnel on top of the can. The recommended soil sample size for a smaller or standard-sized Fenwick can (height 30 cm, volume 2 L) is 300 g [45,46]. However, Bellvert [47] found that cyst extraction efficiency was stable in their Fenwick can using soil samples from 100 g up to the physical limits of the can (600 g). Collins et al. [48,49] achieved greater average cyst extraction efficiency using large-scale Fenwick cans (height 50 cm, soil sample size 2 kg) than with medium-sized Fenwick cans (87.5% and 76%, respectively) and concluded that a large Fenwick can is an effective tool for extraction of cysts from large soil samples. Fenwick [43] found very efficient cyst extraction from a can 60 cm high with a capacity of 19 L by using a soil sample size of 4.5 kg.

To achieve improved cyst recovery efficiency, very organic soils should be washed through an 850 µm sieve into the can to allow coarse organic material to be excluded. Fill the can with tap water from the inlet at the bottom, washing through the soil as the can fills. The organic matter with the cysts will rise and overflow onto the collar. Place two sieves with apertures of 850 and 250 µm under the collar outlet. The cysts are collected on the 250 µm sieve for further processing, as they are on average about 450 µm in diameter [46].

#### **9. Taxonomic Descriptions**

(After Golden and Ellington [50], Stone [29,51], Subbotin et al. [7]) *Globodera pallida*

Female. Body subspherical with projecting neck bearing head, pharynx corpus, isthmus, and anterior part of pharyngeal glands. White in color, some populations passing, after 4–6 weeks, through a cream stage, turning glossy brown when dead. Labial region with amalgamated lips and one or two prominent annuli, deep irregular annulations present on neck, changing to reticulate pattern of ridges over most of body surface. Head framework weakly developed, hexaradiate. Stylet knobs sloping backward. Very large median pharyngeal bulb, almost circular with large crescentic valve plates. Pharyngeal gland lobe broad, frequently displaced anteriad, three gland nuclei. Prominent excretory pore situated at base of neck. Internal structures in neck region often obscured by hyaline

secretions on cuticle surface. Vulva a transverse slit at posterior end, set in a slight circular depression or vulval basin. Cuticle surface between anus and vulval basin including about 12 parallel ridges with a few cross connections. Subsurface punctations irregularly arranged over much of body surface, may be confused with surface papillae on vulval crescents.

Cyst. White when first visible on root surface, changing to glossy brown with maturity, subspherical with protruding neck. Vulval region intact or fenestrated with single circumfenestrate opening occupying all or part of vulval basin. Abullate, but small darkened or thickened "vulval bodies" sometimes present in vulval region. Anus visible in most specimens, often at apex of a V-shape mark. Cuticular pattern as in female but more accentuated. Subcrystalline layer absent.

Male. Heat-relaxed specimens C- or S-shaped, posterior part twisted 90–180◦ about longitudinal axis. Cuticle with regular annulations and four incisures in lateral field, terminating on tail. Labial region offset, rounded with large oral disc, six irregular lips, six or seven annuli, and heavily sc1erotized hexaradiate framework. Stylet well developed with posteriorly sloping basal knobs and cone forming ca 45% of total stylet. Ellipsoid pharyngeal median bulb with strong crescentic valve plates linked by a narrow isthmus encircled by a broad nerve ring, to a narrow, ventrally situated, pharyngeal gland lobe. Hemizonid two annuli long, situated two or three annuli posterior to excretory pore. One testis, commencing with single cap cell 40–65% of body length from head, terminating in a narrow vas deferens with glandular walls. Cloaca with small raised circular lip containing two stout arcuate spicules terminating distally in uni-pointed tips. Small dorsal gubernaculum without ornamentation, slightly wider in dorsoventral aspect. Tail short with bluntly rounded terminus of variable shape.

Juvenile (J2). Lateral field with four incisures but with three anteriorly and posteriorly, occasionally completely areolated. Cuticle thickened for first seven or eight body annuli. Labial region rounded, slightly offset with four to six annuli. Oral disc surrounded by two lateral lips bearing amphidial apertures, adjacent dorsal and ventral submedial lips often fused. Contour of lips and oral disc sub-rectangular [52]. Heavily sclerotized hexaradiate head framework, dorsal and ventral radii bifurcate at tips in 60% of specimens. Stylet well developed, basal knobs with distinct anterior projection as viewed laterally. Gland lobe extending posteriorly for ca 35% of body length. Excretory pore ca 20% of body length from anterior end. Distinct hemizonid two annuli long, located one annulus anterior to excretory pore; hemizonion five or six annuli posterior to excretory pore. Genital primordium at ca 60% of body length from anterior end. Tail tapering uniformly with a finely rounded point, hyaline region forming about half of tail region.

*Globodera rostochiensis*

Female. Pearly white, subspherical to ovate, with elongate, protruding neck. Color changing from white to yellow to light golden as female matures to cyst stage. Cuticle thick, with superficial, rugose, lace-like pattern, D-layer present, punctations resolved near or beneath surface. Labial region slightly offset, bearing two annuli. Labial framework weakly developed. Stylet fairly strong, straight to slightly curved, with well-developed rounded basal knobs, sloping posteriorly. Median bulb large, nearly spherical, with welldeveloped valve. Pharyngeal glands often obscured but appearing clustered. Excretory pore conspicuous, always at or near base of neck. Vulva terminal, slit of medium length. Vulval area circumfenestrate. No anal fenestration, but anus and vulva both lying in a "vulval basin", anal area not encircled by cuticular rings. Often beneath vulva, generally in a cluster, are vulval bodies of highly variable size and shape, large superficial tubercles clumped near vulva. Vulva ellipsoid in shape, anus shorter than vulva. All eggs retained in body, no egg mass.

Cyst. Yellow when first visible on root surface, eventually turning brown with age, ovate to spherical in shape with protruding neck, circumfenestrate, abullate, without distinct "vulval bodies" commonly seen in white females. Fenestra circular, anus conspicuous at apex of a V-shaped subsurface cuticular mark. Cyst wall pattern basically as in female but often more prominent, especially near mid-body, tending to form wavy lines going

around body. Subcrystalline layer absent. Punctations generally present but variable in intensity and arrangement. Each cyst containing 200–1000 eggs.

Male. Body vermiform, slightly tapering at both anterior and posterior regions. Cuticle with prominent annulation. Labial region slightly offset, hemispherical, with six annuli. Labial framework heavily sclerotized. Stylet strong, with prominent knobs. Anterior and posterior cephalids present. Lateral fields with four equally spaced lines. Median bulb ellipsoidal. Excretory pore ca two annuli posterior to often distinct hemizonid. One testis. Spicules slightly arcuate, tips rounded, not notched. Tail short, variable in length and shape.

Juvenile (J2). Body tapering at both extremities but more at posterior end. Cuticular annulation well defined. Lateral fields with four lines extending for most of body length, outer two lines crenate but without areolation. Labial region slightly offset, bearing 4–6 annuli, considerably wider at base than anteriorly, presenting a rounded, though rather anteriorly flattened, appearance. Labial framework heavily sclerotized. Stylet well developed, with prominent rounded knobs as viewed laterally. Anterior and posterior cephalids present. Valve of median bulb prominent, ellipsoidal. Isthmus and pharyngeal glands typical for the genus. Excretory pore almost adjacent yet slightly posterior to hemizonid. Genital primordium slightly posterior to mid-body, with four cells commonly resolved. Tail tapering to small, rounded terminus. Phasmids generally difficult to see, when visible, located about halfway along tail.

#### **10. Identification**

*Globodera rostochiensis* and *G. pallida* are morphologically and morphometrically very similar [29,51,52]. Therefore, identification of as many stages as possible should be performed using a combination of morphological characters and molecular techniques.

Nematode cysts separated from soil organic matter must first be carefully inspected using moderate power (up to about 25×) of a dissecting microscope to exclude all non-globose cysts, including those of *Cactodera*, *Betulodera*, *Dolichodera*, *Heterodera*, and *Paradolichodera*.

Any remaining cysts should be considered as suspect PCN cysts. If the laboratory possesses positive control DNA of both species of PCN, single cyst sub-samples should be tested using the PCR protocol provided in Section 10.3.2.

When positive control DNA is not available, there are two potential courses of action, viz. molecular sequencing using the DNA sequencing protocol or morphological examination using the morphological protocol. Morphological identification of suspected *Globodera* cysts and juvenile nematodes to genus and species levels is difficult and requires an experienced nematologist. When a skilled nematologist is available, it is preferable to utilize both the DNA sequencing and morphological protocols to enhance the level of certainty of identification.

#### *10.1. Morphological Identification to Genus*

An early consideration is how to distinguish cysts of *Globodera* from those of other cyst-forming genera. There is the potential to confuse cysts of *Globodera* with those of the six other genera of the subfamily Heteroderinae, where all females turn into a hard-walled cyst. Cyst shape can be an important character to help distinguish *Globodera* from other genera: globose or spheroid in *Globodera* and generally elongate-ovoid in *Dolichodera* and *Paradolichodera*, and lemon-shaped or pear-shaped in *Betulodera*, *Cactodera*, and *Heterodera*. Occasionally, cysts of *Betulodera* and *Cactodera* tend towards the globose shape, and these specimens can be separated by the presence of a terminal cone, which is a posterior protrusion of the cyst encompassing the anus and vulva and is not present in *Globodera*.

*Punctodera* cysts lack a terminal cone and some species of the genus have globose cysts like *Globodera*, but all can be distinguished from other cyst-forming genera including *Globodera* by the formation of a fenestra in the anal region, of similar shape and size to the vulval fenestra. A fenestra is a terminal region of a cyst where the wall remains very thin and therefore can rupture to permit emergence of juveniles. The vulval slit of *Punctodera* is very short at <5 µm, whereas it is about 9 or 10 µm for *G. rostochiensis* [29,50] and about 11.5 µm for *G. pallida* [52]. In cysts of *Globodera*, the anus is at the apex of a conspicuous V-shaped subsurface cuticular mark not seen in *Punctodera*. Additionally, all members of the genus *Punctodera* are parasites of monocotyledonous plants.

Adult female root knot nematodes (*Meloidogyne* sp., family Meloidogynidae), like *Globodera* are swollen and sedentary plant root feeders, and can be distinguished from *Globodera* by their lack of cuticle thickening and pigmentation as a persistent container for the eggs, i.e., a cyst. The perineum of swollen adult female *Meloidogyne* retains its annulation in the form of fingerprint-like whorls, whereas this annulation is lost in *Globodera*. Unlike *Globodera*, female *Meloidogyne* create an egg-mass, which is a collection of extruded eggs embedded within a secreted gelatinous matrix. In addition, females of *Meloidogyne*, but not *Globodera*, are gall-inciting.

Second-stage juvenile specimens of *Globodera* are more robust than their *Meloidogyne* counterparts. The more conspicuous stylet is longer and thicker, and the tail terminus is hyaline (transparent), whereas it is non-hyaline in *Meloidogyne*. The phasmids (paired postanal lateral chemoreceptor sensory organs) of *Meloidogyne* are small and pore-like, whereas they are larger and lens-like in *Globodera*.

Male *Globodera* lack the distinctive lateral amphidial cheeks (outer part of the lateral lip of the head, adjacent the opening of the amphid sense organ) of *Meloidogyne*; they also have a long, slender esophageal isthmus in contrast to the very short, broad isthmus of *Meloidogyne*.

To identify suspected *Globodera* nematodes to genus level, refer to the key in Table 1. Additionally, to identify cysts within the family Heteroderidae, the keys of Hesling [53], Mulvey and Golden [54], Golden [55], Baldwin and Mundo-Ocampo [56], Brzeski [57], Wouts and Baldwin [58], Siddiqi [59], or Subbotin et al. [7] based on cyst form including characteristics of the vulva-anus region, should be consulted.

**Table 1.** Simplified dichotomous morphological key to genus *Globodera*.


#### *10.2. Morphological Identification to Species*

Once all other genera are excluded and it is confirmed that cysts belong to the genus *Globodera*, the following procedure should be followed.

Use a combination of cyst and second-stage juvenile (J2) characteristics if possible. Both stages are normally present in most soil samples infested with PCN, but juveniles will not be extracted by the flotation methods that rely on dried cysts floating to the top of a column of water. Alternatively, to obtain larvae, a cyst can be broken open in a droplet of water on a microscope slide to release the contained eggs. During the process the delicate shells of some eggs will inevitably be broken, enabling the larvae to escape and unfold ready for identification. The most reliable characteristics for identification of second-stage juveniles (J2) within the genus *Globodera* are stylet length, stylet knob width, and stylet knob shape. In *G. pallida*, J2 stylet knobs are distinctly anteriorly directed to flattened anteriorly, and the mean J2 stylet length is >23 µm, whereas in *G. rostochiensis* J2 stylet knobs are rounded to flattened anteriorly, and the mean J2 stylet length is <23 µm (Figure 2).

**Figure 2.** Stylets of second-stage juveniles of *G. pallida* (diagrams (**A**,**B**)) and *G. rostochiensis* (diagrams (**C**,**D**)) (after Stone [52]).

Cysts should be observed under a dissecting microscope directly on the filter paper used to catch the cysts during the extraction process, at low to moderate magnification (up to about 25×). For species identification, a 40× objective on a compound microscope is adequate to examine the perineal region after the cyst wall has been mounted on a slide. There are no clear differences in size, shape, or color of mature cysts of *G. rostochiensis* and *G. pallida*; the most important cyst differences can be obtained from examination of the perineal area, i.e., number of cuticular ridges between vulval basin and anus (Figure 3), and Granek's ratio (see Section 10.2.2), the distance from the anus to the nearest edge of the vulval basin divided by vulval basin diameter [60]. However, in some cases cuticular ridges are not visible or are very difficult to count, so Granek's ratio is considered a more reliable diagnostic tool, and when combined with the important second-stage juvenile measurements, a species diagnosis can be made. Confirmation with molecular techniques is also recommended.

A key to species of *Globodera* is presented in Table 2. Further keys to species can be found in Mulvey [61,62], Hesling [53], Wouts [63], Golden [55], Wouts and Baldwin [58], Subbotin et al. [7], and EPPO [17].

**Figure 3.** Vulval-anal ridge patterns for *G. pallida* and *G. rostochiensis* (after Stone [52]).

**Table 2.** Dichotomous morphological key to species of the genus *Globodera*. (after Subbotin et al. [7] and EPPO [17], with the addition of *G. agulhasensis* [64] and *G. sandveldensis* [65]).


<sup>1</sup> DGO = distance from anterior end to orifice of dorsal gland opening. <sup>2</sup> gubernaculum = grooved cuticular structure which guides the spicule or intromittent organ.

Three other *Globodera* species could cause confusion during identification of potato cyst nematodes: *G. achilleae* (Golden and Klindic, 1973) Behrens, 1975, *G. artemisiae* (Eroshenko and Kazachenko, 1972) Behrens, 1975, and *G. tabacum sensu lato*. None are parasitic on potato, although the *G. tabacum* species complex (*G. tabacum tabacum* (Lownsbery and Lownsbery, 1954) Skarbilovich, 1959; *G. tabacum solanacearum* (Miller and Gray, 1972) Behrens, 1975, and *G. tabacum virginiae* (Miller and Gray, 1972) Behrens, 1975) parasitizes *Nicotiana tabacum* (tobacco) and some other solanaceous plants (but not potato). To help resolve species determination, Table 3 shows morphometric and morphological comparisons between PCN and *G. achilleae*, *G. artemisiae* and *G. tabacum*. See also Baldwin and Mundo-Ocampo [56], Brzeski [57], Wouts and Baldwin [58], and Subbotin et al. [7,66] for more detailed information on other members of the Heteroderinae.

**Table 3.** Mean and range (in parentheses) values of some essential characters of *Globodera rostochiensis*, *G. pallida*, *G. tabacum (tabacum)*, *G. achilleae*, and *G. artemisiae,* as given in Baldwin and Mundo-Ocampo [56], Brzeski [57], Fleming and Powers [67], Manduric et al. [68], and Dobosz et al. [69].


10.2.1. Microscope Slide-Mounting of Cyst Wall


**Figure 4.** Puncture cyst wall to release pressure.

**Figure 5.** Cut across base of cyst to retain vulval and anal region.

**Figure 6.** Make two more cuts to the excised section of cyst wall.

**Figure 7.** Light microscope image of cuticle surface of perineal region of potato cyst nematode (PCN) (*G. rostochiensis*) cyst laid flat on glass microscope slide.

10.2.2. Taking Measurements for Granek's Ratio


#### *10.3. Molecular Identification*

For potato growers to attain phytosanitary certification, and for a country's authorities to maintain official control of PCN, molecular techniques are often the preferred choice for regular routine soil testing. When new introductions are suspected, the identification of *G. pallida* and *G. rostochiensis* should combine molecular and morphological methods.

#### 10.3.1. DNA Extraction from PCN Cysts

Cysts collected from soil can be washed/soaked in deionized water or briefly washed in 70% ethanol to avoid possible fungal/bacterial contamination.

The following DNA extraction method works with cysts that contain larvae or unhatched eggs; it does not work with empty cysts.

Material/equipment:


Operation manual of DNA extraction KIT Cat Nos 69504/69506, Protocol for Purification of Total DNA from Animal Tissues (Spin-Column Protocol)

Quader et al. [70] Method:


10.3.2. Multiplex PCR for the Identification of Species of PCN

Material/equipment:


Bulman and Marshal [71] White et al. [72] PCR primer sequences: ITS5 50 -CGCGCGGATCCGGAAGTAAAAGTCGTAACAAGG-30 PIr3 50 -AGCGCAGACATGCCGCAA-30 PIp4, 50 -ACAACAGCAATCGTCGAG-30 ITS26 50 -TATATGGATCCATATGCTTAAGTTCAGCGGGT-30

Primer ITS5 is used in combination with primer PITSr3 in a specific PCR to detect *G. rostochiensis* only. Primer ITS5 is used in combination with primer PITSp4 in a specific PCR to detect *G. pallida* only. Primer ITS5 is used in combination with PITSr3 and PITSp4 to detect both species from a mixed population.

Primers ITS5 and ITS26 should amplify both *G. pallida* and *G. rostochiensis*. These primers are used in a housekeeping nematode PCR to check the quality of DNA extracts. The PCR ensures that DNA is present or that there are no inhibitors in the DNA extracts that retard the activity of the DNA polymerase.

DNA barcoding based on the 18S rDNA gene and the internal transcribed spacer ITS1 region of rDNA (ITS) has been determined as suitable for species identification in *Globodera*. Bulman and Marshall [71] designed the PCR-based *G. pallida*-specific primer PITSp4 and *G. rostochiensis*-specific primer PITSr3 to be used in conjunction with the universal ITS5 primer. These can be used singly or in a multiplex PCR. Alternatively, the universal ITS5 and ITS26 primer pair can be used to amplify the barcoding region, and the resultant product sequenced and compared with verified reference sequences on the NCBS GenBank database.

Method:


PCR cycles:



**Table 4.** Master mix of specific PCRs for both PCN species identification in one reaction (multiplex PCR).

\* PITSr3 for *G. rostochiensis* and PITSp4 for *G. pallida*.

**Table 5.** Master mix of housekeeping PCRs for both PCN species.


**Table 6.** PCR cycles for PCN species detection.


Gel run and photograph:


PCR product sizes:


#### 10.3.3. DNA Sequencing

For confirmation, the PCR products of the reactions using primers ITS5 and ITS26 for single cysts should be sequenced.

Sequencing reactions using BigDye™ Terminator v3.1 Cycle Sequencing Kit (Table 7) can be done in the laboratory using PCR products cleaned up by QIAquick PCR Purification Kit. Either cleaned PCR products or sequencing reaction products can be sent to Sanger sequencing services, e.g., Macrogen or Micromon, along with the primers to obtain forward and reverse sequences. Forward and reverse sequences of each sample should be de novo assembled and edited/corrected using a suitable computer program, e.g., Geneious. The consensus sequence should be subjected to a database search, e.g., GenBank or private sequence libraries, and phylogenetic analysis. Sequences should be compared with those in GenBank for accession numbers EF622513–EF622532 for *G. rostochiensis* and HQ260426–8, FJ212165 for *G. pallida*. For a match to be positive, the sequence must have a similarity of greater than 99% with these GenBank sequences.

**Table 7.** Sequencing reaction mix.


#### 10.3.4. Genotyping

It is possible to compare the genetic differentiation of PCN populations using polymorphic microsatellite DNA markers. DNA can be screened after extracting it from single larvae dissected from cysts. For methodology of this genotyping, see Boucher et al. [73], Alenda et al. [74], and Blacket et al. [75].

There have been many phylogenetic analyses of species within the genus *Globodera* (e.g., [5,73,76–86]). A recent study, based on a phylogenetic analysis of gene sequences of three molecular markers (455 ITS rRNA, 219 *COI*, and 164 *cytb*) of 11 valid and 2 undescribed species of *Globodera* [87], found that *Globodera* displayed two main clades in their phylogenetic trees: (i) *Globodera* from South and North America parasitizing plants from Solanaceae; and (ii) *Globodera* from Africa, Europe, Asia, and New Zealand parasitizing plants from Asteraceae and other families. They hypothesized that the split between solanaceous and non-solanaceous lineages occurred roughly 2.9 ± 0.5 Mya (million years ago), divergence dates of the solanaceous *Globodera* lineages started 2.7 ± 0.2 Mya and the nonsolanaceous *Globodera* lineages 1.6 ± 0.3 Mya, and dispersals of *Globodera* to Europe and New Zealand occurred 1.4 ± 0.3 and 0.9 ± 0.2 Mya, respectively.

**Author Contributions:** Conceptualization, J.W.; methodology, J.W. and Q.D.; validation, J.W. and Q.D.; formal analysis, J.W. and Q.D.; investigation, J.W. and Q.D.; resources, J.W and Q.D.; data curation, J.W. and Q.D.; writing—original draft preparation, J.W. and Q.D.; writing—review and editing, J.W.; visualization, J.W.; supervision, J.W.; project administration, J.W.; funding acquisition, J.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** The preparation of this paper was funded by Agriculture Victoria Research, Department of Jobs, Precincts and Regions, State Government of Victoria.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Acknowledgments:** This research received financial support from Plant Health Australia, the Subcommittee of Plant Health Diagnostics and the State Government of Victoria. Dolf De Boer and Jacky Edwards provided valuable suggestions on the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


*Review*
