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Article

Identification of Major Brown Planthopper Resistance Genes in Indigenous Thai Upland Rice Germplasm Using Molecular Markers

by
Kittiya Kanngan
1,
Phijittra Umalee
1,
Khanobporn Tangtrakulwanich
1,2,
Rungrote Nilthong
1 and
Somrudee Nilthong
1,2,*
1
School of Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
2
Circular Economy for Waste-Free Thailand Research Center, School of Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(10), 2605; https://doi.org/10.3390/agronomy13102605
Submission received: 9 September 2023 / Revised: 2 October 2023 / Accepted: 10 October 2023 / Published: 13 October 2023
(This article belongs to the Section Crop Breeding and Genetics)
Browse Figures
Versions Notes

Abstract

:
Brown planthopper (BPH) is the most problematic insect in rice cultivation, as it decreases crop yields. In this study, 143 upland rice varieties were genotyped for five essential Bph resistance genes: bph2, Bph3, Bph14, Bph15, and Bph17. The gene frequencies of the five Bph resistance genes varied from 33.57% to 61.54%. The 139 varieties contained one to five Bph resistance genes. Polymorphism information content values ranged from 0.4460 to 0.4984 with an average of 0.4744. Cluster analysis supported the subpopulations identified by STRUCTURE. An analysis of molecular variance analysis identified 7% variance among and 92% variance within subpopulations, indicating a significant gene exchange between the two subpopulations. The evaluation of BPH resistance using the SEM system by IRRI showed that 2 varieties were resistant to BPH, 29 varieties were moderately resistant, and 112 varieties were susceptible. The Bph3, Bph14, and Bph15 genes and BPH resistance showed significant correlation. These findings provide important information regarding BPH-resistant varieties for future use in rice breeding programs.

1. Introduction

Rice (Oryza sativa L.) is one of the most important food crops in the world and serves as a staple food for one-third of the global population, particularly in Asia [1]. Indigenous upland rice varieties are mainly cultivated in upland, hilly slopes, and mountainous areas in northern and northeastern Thailand, as well as in some regions of the south. Indigenous upland rice varieties have been derived from nature through human selection, particularly by the ethnic groups living in those areas for resistance to specific conditions, such as biotic and abiotic stress, which can serve as a valuable genetic resource for future rice breeding programs [2].
The brown planthopper (Nilaparvata lugens; BPH) is the most serious monophagous pest of rice cultivation and is found throughout South, Southeast, and East Asia, as well as the South Pacific Islands and Australia. BPH can damage rice and cause yield loss every year by directly feeding on it, causing hopper burn, and indirectly transmitting diseases such as ragged stunt virus [3] and grassy stunt virus [4]. The damage levels observed ranged from 10% to 100% in irrigated rice, wet-seeded rice, and off-season rice fields. In wetland rice and rained rice fields, the damage levels varied from 5% to 60% [5]. In rice, there are four original biotypes of the BPH population. Biotype 1 is found in East and Southeast Asia [6]. Biotype 2 is a scourge in Vietnam and Indonesia [6]. Biotype 3 was generated in the laboratory, while biotype 4 was discovered in South Asia [7]. Presently, there are additional biotypes beyond the four previously reported biotypes identified in Thailand. Furthermore, several biotypes have been observed in the outbreak area, indicating the existence of multibiotype populations [8]. According to Prakobna et al. [9], a comprehensive study of BPH populations collected from the central region of Thailand identified a total of 31 biotypes. In addition, the presence of biotype 8 in certain rice field areas has been reported, demonstrating its ability to cause damage to all rice varieties, except the weedy rice variety [10]. The adaptability and appearance biotypes of BPH have been described as being induced by a combination of genetic variables and other factors that triggered changes in BPH feeding or oviposition behaviors, such as the microbial symbiosis observed in BPH abdominal fat [11].
Pesticides are the most effective way to control BPH. However, excessive pesticide use can result in environmental problems, including pollution, the destruction of beneficial insects, and the evolution of a BPH resistant to pesticides. Rice resistance is considered the most economical and environmentally friendly approach for BPH management [12]. Rice varieties exhibit distinct resistance mechanisms against BPH, categorized as antixenosis, antibiosis, and tolerance [13]. Antixenosis, also known as non-preference or deterrence, refers to the ability of rice plants to deter BPH feeding or oviposition. It involves physical or chemical traits in the plant that make it less attractive or suitable for BPH, thus reducing their damage. Antibiosis refers to the ability of rice plants to inhibit BPH growth and development. It involves the production of certain chemical compounds or proteins that are toxic to BPH, leading to reduced survival or impaired reproductive capabilities. Tolerance is the ability of rice plants to withstand BPH feeding without experiencing significant yield losses [14]. Antibiosis is the most extensively studied defense mechanism in rice [15].
Since the marker-assisted selection (MAS) method has the potential to develop BPH-resistant varieties and their durability, SSR [16,17], InDel [18,19,20], and SNP [21,22] markers are common molecular markers used to research the genetics of BPH resistance in rice. Currently, more than 43 host plant resistance genes have been identified and are being used in the breeding program [23]. The genes for BPH resistance are located on chromosomes 3, 4, 6, and 12, with the majority being dominant and a few being recessive, such as bph4, bph5, bph7, bph8, bph19, bph25, and bph29 [24]. Furthermore, nine genes have been cloned: Bph6, Bph9, Bph14, Bph17, Bph18, Bph26, Bph29, Bph30 and Bph32 [25]. The genes bph2, Bph3, Bph14, Bph15, and Bph17 have exhibited promising effects in enhancing resistance to BPH and have been extensively researched and widely applied in breeding programs to improve BPH resistance in rice [24,26,27,28,29]. In Thailand, the development of rice resistant varieties begins with the utilization of rice germplasms from IRRI such as W1252, W1256, IR32, IR56, and IR60 varieties [30]. However, the adaptability and biotype changes in BPH enable it to overcome resistance varieties. Jairin [31] reported that certain rice varieties, initially exhibiting resistance to BPH, can become susceptible as a result of biotype variation. Furthermore, no rice varieties in Thailand have exhibited comprehensive resistance against all biotypes of BPH. Consequently, the search for new sources of resistance genes becomes imperative for the breeding program. This study aimed to investigate the distribution of Bph resistance genes in indigenous Thai upland rice germplasm and to identify an alternative and novel valuable genetic resource for Bph resistance genes for use in rice genetics and breeding.

2. Materials and Methods

2.1. Brown Planthopper Population

The mixed biotypes 3, 4, 5, 6, and 7 of the brown planthopper population were originally collected from rice fields in Chaing Rai province, Thailand, by the Chiang Rai Rice Research Center in Phan district, Chiang Rai province, Thailand. To increase the population size, the BPH colonies were maintained on Khao Dawk Mali 105 (KDML105) under greenhouse conditions at Mae Fah Luang University.

2.2. Evaluation of Brown Planthopper Resistance in Upland Rice

Evaluation of plant reaction to BPH infestation was conducted using a completely randomized design (CRD) with three replications of each variety under greenhouse conditions. Seeds of 143 upland rice varieties, along with Rathu Heenati (a resistant variety) and TN1 (a susceptible variety), were planted in a plug tray. At the second-leaf stage, five seedlings per variety were infested with 2nd–3rd instar nymphs at a density of 10 nymphs per seedling. Seven days after infestation, when nearly all TN1 seedlings had died, the damage score on each variety was recorded on a 0–9 scale according to IRRI [32]. The six-scale scoring system is as follows: 0 (no visible damage), 1 (minor damage), 3 (first and second leaves are yellowing), 5 (significant yellowing and stunting), 7 (almost fully wilted but still alive), and 9 (plant has completely died). The interpretation of each variety’s result was based on a standard evaluation system with average ratings of 0.00–3.49, 3.50–5.49, and 3.50–9.00, which were designated as resistant, moderately resistant, and susceptible to BPH, respectively [33].

2.3. Rice Materials and DNA Extraction

Forty-six upland rice varieties were collected from ethnic farmers in Chiang Rai province, Thailand, and the remaining 97 varieties were generously provided by Asst. Prof. Dr. Vaiphot Kanjoo from Phayao University, Thailand (Supplementary Table S1). Rathu heenati was derived from the Phitsanulok Rice Research Center. TN1 was derived from the Pathum Thani Rice Research Center, Thailand. Two to three fresh young leaves of all rice varieties were collected from two-week-old seedlings for genomic DNA extraction. Genomic DNA was extracted using a TIANGEN DNA extraction kit (TIANGEN Biotech (Beijing) Co., Ltd., Beijing, China) following the manufacturer’s protocol. The extracted DNA was quantified using a Nanodrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), and the quality was evaluated by 0.8% agarose gel electrophoresis. The DNA was finally diluted with 1× TE buffer to a concentration of 50 ng/µL and stored at −20 °C for further uses.

2.4. Genotypic Screening of BPH Resistance Genes in Upland Rice

The entire set of 143 indigenous upland rice varieties was genotyped using four SSR markers and one InDel marker, which are associated with the bph2, Bph3, Bph14, Bph15, and Bph17 genes (Table 1). The PCR reaction was carried out in a 20 µL volume using an Eppendorf Mastercycler Nexus Gradient GSX1 Thermal Cycler (Marshall Scientific, LLC, Hampton, NH, USA). The reaction mixture contained 100 ng of genomic DNA, 5 pmol forward and reverse primers, 200 µM dNTPs, 1× PCR buffer, 1.25 mM MgCl2, 1 µL DMSO, and 1 U of Taq polymerase (Thermo Fisher Scientific, Waltham, MA, USA). PCR was performed as follows: 1 cycle at 95 °C for 5 min, 35 cycles of denaturation at 95 °C for 30 s; annealing depending on the markers (Table 1) for 30 s; extension at 72 °C for 30 s and a final extension at 72 °C for 10 min. The amplified products were examined using 4% agarose gel electrophoresis and visualized using a UV-based gel documentation system (Bio-Rad, Feldkirchen, Germany). All PCR assays were performed twice to validate the results.

2.5. Analysis of Genotypic Data and Genetic Diversity

The correlation between genotypes with different Bph resistance genes and plant reaction to BPH infestation was analyzed using a Spearman correlation via the R program. To create a binary matrix for each marker, the unique polymorphic bands of markers were scored based on genotypic characteristics, with a present allele receiving a score of 1 and an absent allele receiving a score of 0. The similarity between genotypes for each variety was estimated from the matrix of binary data using Jaccard’s coefficient. The cluster analysis was conducted using the unweighted pair group method with an arithmetic average (UPGMA) in the R program [39]. The polymorphic information content (PIC) of each marker was calculated using the formula described by Anderson et al. [40]. The formula was as follows: PIC = 1 − ΣjPij2, where Pij is the frequency of the jth allele for the locus summed over all alleles for the locus. The PIC of each marker was then calculated using the following formula:
P I C = ∑ i = 1 n P I C i / n
where n is the number of bands.

2.6. Analysis of Population Structure

The population structure of 143 upland rice varieties was analyzed using the Bayesian Markov Chain Monte Carlo (MCMC) model in STRUCTURE software version 2.3.4 [41] to interpret genetic structure and classify clusters based on five markers associated with five Bph resistance genes. The software was run with different K values to identify the actual subpopulations (K). From K = 1 through K = 10, 10 independent iterations were performed per K. For each run, the burn-in time and the number of Markov Chain Monte Carlo (MCMC) replications were set to 500,000. The mean posterior probability (LnP(D)) for each K value was plotted to identify the plateau of K values, which was then used to calculate the most likely K value with STRUCTURE Harvester software [42]. The number of subpopulations was utilized for analysis of molecular variance (AMOVA) to estimate the total molecular variance within and between subpopulations, fixation index (Fst), and Nm values (haploid number of migrants) using GenAlex version 6.503 software [43].

3. Result

3.1. BPH Resistance Evaluation of Upland Rice

Upland rice varieties were assessed for BPH resistance at seedling stage. Each replicate was infested with 10 mature BPH individuals. The finding indicated that only 2 varieties (1.40%) were resistant to BPH, while 29 varieties (20.28%) were moderately resistant, and 112 varieties (78.32%) were susceptible (Supplementary Table S1).

3.2. Genotypic Diversity of BPH Resistance Genes in Upland Rice

A total of 143 upland rice varieties were genotyped using markers specific to five different Bph genes (bph2, Bph3, Bph14, Bph15, and Bph17). Five varieties, including IR70175-51-2-1-1-2, Lai Chan, Beu Hmeu Mae La, Pi Ai Kor, and Khao Nieow Kla, contained the highest number of five Bph resistance genes. Nineteen varieties (13.29%) had four Bph resistance genes, 48 varieties (33.57%) for three Bph resistance genes, 44 varieties (30.77%) for two Bph resistance genes, and 23 varieties (16.08%) for one Bph resistance gene. However, none of the Bph resistance genes were found in four varieties (2.80%), including Ja Na Toy, Unknown179, Lai San, and Ber Sue Ha. The average gene frequency was found to be 49.79%, ranging from 33.57% (IN76-2) to 62.94% (RM261). The presence of bph2 gene on chromosome 12 was determined by the RM463 marker and 88 (61.54%) varieties were found to carry the bph2 gene. The RM588 and IN76-2 markers were used to amplify the Bph resistance genes Bph3 and Bph14, respectively, which are located on chromosome 3. Sixty-three (44.06%) varieties were found to be positive for a Bph3 resistance allele, while 48 (33.57%) varieties contained the Bph14 resistance allele. PCR screening of the Bph15 and Bph17 genes on chromosome 4 showed that the Bph15 allele was widely distributed in 90 (62.94%) varieties, whereas 67 (46.85%) varieties carried the resistance allele Bph17 (Figure 1). The amplicon bands corresponding to RM463, RM588, IN76-2, RM261, and RM16626 markers are displayed in Figure 2.
The polymorphism information content (PIC) value is used to measure the probability that two randomly chosen alleles from a population are prominent. The PIC values for five markers varied from 0.4460 (IN76-2) to 0.4984 (RM16626) with an average of 0.4744 (Table 1).

3.3. Cluster Analysis

The 143 upland rice varieties were categorized into two distinct major clusters (Cluster I and II) at 28% level of genetic similarity coefficient (Figure 3). Major cluster I, consisting of 100 varieties, was divided into four subclusters: I-A, I-B, I-C, and I-D. Subcluster I-A contained 49 varieties and most of them had Bph15 and Bph3 genes. Subcluster I-B included 20 varieties with primarily Bph15 and Bph17 genes. Subcluster I-C consisted of 25 varieties, most of which predominantly contained four Bph resistance genes, bph2, Bph3, Bph14, and Bph15, while 5 varieties (IR70175-51-2-1-1-2, Lai Chan, Beu Hmeu Mae La, Pi Ai Kor, and Khao Nieow Kla) contained all five Bph resistance genes. The smallest subcluster was I-D, which had only five varieties that mostly contained Bph14 and Bph15 genes. The remaining 44 varieties were included in Cluster II, which was further divided into subcluster II-A and II-B. Subcluster II-A contained 26 varieties having mainly bph2 and Bph17 genes, while 3 varieties, Neaw Doi, Wa La Nee Gu Su, and Mali Namnao, contained only the bph2 gene. Eighteen varieties were found in the subcluster II-B, and most contained only the Bph17 gene. Furthermore, four varieties in subcluster II-B, Ja Nae Nae, Ja Chue Chue, Unknown168, and Khao Lai Pang Kwam Noi, lacked any Bph resistance genes.

3.4. Population Structure and AMOVA Analysis

The K value was used to estimate the number of subpopulations of the upland rice varieties based on the genotypic data. The number of clusters (K) was plotted versus ΔK to determine the optimal K value, which showed a sharp peak at K = 2 (Figure 4a). At all values, LnP(D) continuously increased and gradually increased as K increased (Figure 4b). Based on the optimal K value, the analysis of population structure divided the 143 upland rice varieties into two subpopulations (subpopulation 1 and subpopulation 2). Subpopulation 1 (represented by the red color in Figure 4c) was a small group containing 68 varieties (46.90%), which came from two different provinces: Phayao (66.18%) and Chiang Rai (33.82%). Subpopulation 2 (represented by the green color in Figure 4c) consisted of 77 varieties (53.10%) with 32.67% coming from Chiang Rai province and 67.53% from Phayao province. According to the mean fixation index (Fst), which identified populations among upland rice varieties, subpopulations 1 and 2 had Fst values of 0.2148 and 0.4218, respectively, indicating significant diversity (Fst > 0.15) in both subpopulations (Table 2). Additionally, the expected heterozygosity (He) of subpopulation 1 (0.3620) was higher than that of subpopulation 2 (0.3486), suggesting that subpopulation 1 was more diverse than subpopulation 2 (Table 2). The analysis of population structure also revealed that genetic variation within subpopulations was 92%, while 7% was detected among subpopulations (Table 3).

3.5. Genetic Association of BPH Resistance Genes

The genetic association between Bph resistance genes and the rice’s resistance response was analyzed using Spearman rank correlations. The result showed that only the gene Bph3 was negatively correlated with the rice’s resistance to BPH. The BPH genes Bph14 and Bph15 showed significant correlation with the rice’s resistance to BPH (Table 4).

4. Discussion

BPH has long been recognized as the most detrimental pest to rice, causing a significant negative impact on rice production. The primary control method for BPH is through the use of insecticides, which can cause environmental contamination and contribute to the development of insecticide-resistant BPH populations [44]. The development of BPH-resistant rice varieties has been the most cost-effective and environmentally friendly approach for BPH control. However, BPH-resistant varieties often lose their resistance due to the evolutionary adaptation of BPH [45]. Therefore, the identification of Bph resistance genes in new sources of rice varieties, which can serve as valuable germplasm for the development of resistant varieties, is an ongoing need for breeding programs.
The gene frequency of five major Bph genes ranged from 33.54% to 62.94% in the 143 upland rice varieties. All upland rice varieties were found to contain zero to five Bph genes, similar to the previous reports [46,47]. Furthermore, these selected genes have been extensively studied and widely utilized in breeding programs, particularly in Southeast Asia. Bph3 is well known for its broad-spectrum resistance to all BPH biotypes and has been successfully used to develop elite rice lines that can serve as valuable germplasm sources for rice breeding programs [29]. Rice lines carrying a combination of bph2, Bph3, and Bph17 genes have been reported to exhibit relatively high resistance against the Koshi-2013 BPH population in the studies by Nguyen et al. [26]. Additionally, the introgressed rice varieties that have pyramided Bph14 and Bph15 have demonstrated the most significant effect in conferring resistance to BPH [24,27]. The PIC value is commonly used to measure the information content of a genetic marker [48]. As proposed by Botstein et al. [49], there are three levels of marker informativeness: (1) Highly informative markers have a PIC value greater than 0.5 (PIC > 0.5). (2) Markers with PIC values ranging from 0.25 to 0.50 are considered moderately informative (0.50 > PIC > 0.25). (3) Markers with PIC values less than 0.25 (PIC 0.25) are ineffective [50]. In this study, the PIC values for all markers were less than 0.5, with an average PIC value of 0.4744, suggesting that all the markers were considered moderately informative. Similar results were reported in farmers’ rice varieties collected from Odisha state, India, of which the IN76-2 marker was found to have the lowest PIC value (0.4460), whereas the RM16626 marker had the highest PIC value (0.4984) [51]. However, several factors contribute to improving the average PIC values and genetic diversity, including sample size, breeding behaviors of the species, heterogeneity of the samples and their diverse nature, genotypic techniques, and marker locations [52].
Population among upland rice varieties was recognized by the Fst value. Fst is a value that can be a measure of population diversity based on genetic structure. Mohammadi and Prasanna [53] reported that Fst > 0.25 indicates great differentiation, 0.25 > Fst > 0.15 represents medium differentiation, and Fst 0.05 implies low differentiation. The STRUCTURE results showed that both subpopulations had significant divergence. A low Fst value (0.068) was found between the two subpopulations, indicating low genetic divergence between these two subpopulations. Furthermore, subpopulation 1 exhibited higher expected heterozygosity (He) than subpopulation 2, suggesting greater diversity in subpopulation 1 (Table 2). The diversity among upland rice varieties was also confirmed by AMOVA analysis, which showed that 92% of the variation was found within subpopulations. The rest of the genetic variation (7%) was found among subpopulations. These findings support the Fst values for subpopulations 1 and 2, which were 0.2148 and 0.4218, respectively, indicating significant divergence within each of the two subpopulations of upland rice varieties. Our results are consistent with those of Anant et al. [51], who reported 83% variation within a population and 17% variation among populations of rice in Odisha, India.
Based on plant reaction to BPH infestation, two upland rice varieties, Neaw Doi (one Bph gene) and Seu No Nu (four Bph genes), were found to exhibit resistance to BPH infestation, similar to the Rathu Heenati variety that served as the resistant control. The Rathu Heenati variety has been known for its broad-spectrum and long-lasting resistance against BPH infestation [21] and has often been utilized as a donor variety for the Bph3 gene [24]. Several varieties, such as IR70175-51-2-1-1-2, Lai Chan, Beu Hmeu Mae La, and Khao Nieow Kla, demonstrated susceptibility while containing five resistance genes. Consistent results were found in a study on blast resistance in Indian rice landraces whose specific rice cultivars exhibited susceptibility reactions while possessing 14 or more R genes [42]. This can be explained by the type of alleles present in rice varieties, the use of resistant breeding techniques, the occurrence of mutations in R genes, or the adaptation of pathogen or pests. However, BPHs have evolved measures to escape detection by the rice plant or to inhibit the host response. The emergence of new BPH biotypes poses a significant challenge to breeding programs, and our findings indicate that the Neaw Doi and Seu No Nu varieties have potential as the varieties resistant to BPH biotypes 3, 4, 5, 6 and 7. These varieties can serve as alternative sources for breeding programs focused on the development of rice varieties with enhanced resistance to BPH. Further investigation and characterization of these varieties are warranted to fully understand their potential and incorporate their beneficial traits into breeding programs.
According to the Spearman rank correlations between genotypes of different Bph resistance genes and their resistance to BPH, Bph3 showed effects against BPH infestation. This is congruent with the study results of Liu et al. [54], who observed that the Bph3 gene exhibited highly effective and broad-spectrum resistance to all BPH biotypes. He et al. [55] also induced four Bph resistance genes (Bph3, Bph14, Bph18, and Bph32) into the cultivar Guang 8B and found that the Bph3 gene constituted the most powerful gene. Furthermore, the correlation between Bph14 and Bph15 and the infestation of BPH was found to be statistically significant at the 0.05 level, as indicated in Table 4. These results agree with Xu [56], who discovered moderate susceptibility to BPH in a variety containing the Bph14 gene. Han et al. [12] examined the resistance of rice pyramid lines containing Bph14 and Bph15, as well as two single-gene introgression lines each carrying Bph14 and Bph15. The findings revealed that rice introgression lines carrying only Bph14 or Bph15 displayed a moderate susceptibility, whereas rice pyramid lines containing both Bph14 and Bph15 exhibited strong antibiotic resistance to BPH. This confirmed that multiple genes contribute to BPH resistance in rice and that the pyramiding of two or more genes can improve the resistance. In addition, some markers in this study showed a weak association between Bph resistance genes and rice against BPH. The limited strength of the association between selected molecular markers and BPH resistance can be explained by the inherent genetic complexity of BPH resistance in rice. The manifestation of this intricate characteristic is governed by multiple genes, each gene exerting influence on different aspects such as levels of resistance to BPH, genetic backgrounds, and interactions among genes in plant species [28]. It is well established that BPH resistance genes can confer various mechanisms, including antibiotic, antixenotic, or tolerance mechanisms, to counteract BPH [57]. Previous studies have identified the genes with distinct mechanisms; for instance, genes such as Bph6, Bph9, Bph12, Bph14, Bph15, Bph18, Bph27, Bph33, and Bph36 have been found to confer both antibiosis and antixenosis, whereas Bph1, bph2, Bph3, Bph10, Bph17, Bph20, Bph21, bph25, Bph26, Bph30, and Bph32 have primarily demonstrated antibiosis. In contrast, Bph7 and Bph37 have been reported to exhibit a tolerance effect against BPH [2,19,26,27,28,36,55]. This suggested that the variation in resistance levels may possibly be related to the genetic backgrounds. Moreover, the genetic diversity of BPH populations presents another challenge. BPH has been reported to exhibit geographic variability and rapid evolution in host plants. In subsequent years, new virulent BPH biotypes evolved and have come to dominate the resistance genes [58]. Genetic diversity among BPH populations feeding on resistant rice varieties has been reported to be notably greater than among populations feeding on susceptible varieties [59,60]. As a result, the genetic diversity within BPH populations may also impact the resistance levels in rice plants. Additionally, the marker is somehow randomly correlated with the phenotype during the marker selection process, then when using it in the screening, it will show weak or no association. Consequently, it was observed that two upland rice varieties exhibited resistance to BPH. This finding implies that these particular varieties hold potential as valuable sources of resistance genes for the development of future breeding programs.

5. Conclusions

In this study, BPH resistance was genotyped and phenotyped in 143 upland rice varieties to investigate the relationship between Bph resistance genes and resistance expression. The selected SSR and Indel markers were efficient and sufficiently informative and capable of detecting the presence of Bph resistance genes in upland rice varieties. Based on genetic variation, cluster analysis separated the upland rice varieties into two significant groups. Population structure revealed a significant level of genetic variation among populations. With 92% variance, the AMOVA study confirmed the gene exchange between subpopulation 1 and subpopulation 2. This study has provided valuable information on the BPH resistance of upland rice varieties, particularly New Doi and Seu No Nu, which have been identified as resistant varieties. These varieties can serve as alternate BPH-resistant sources for future rice breeding programs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13102605/s1, Table S1: One hundred and forty-three upland rice varieties.

Author Contributions

Conceptualization, S.N., K.T. and K.K.; Investigation, K.K.; Maintaining BPH colonies, P.U.; Formal analysis, R.N.; Funding acquisition, S.N. and K.T.; Supervision, S.N. and K.T.; Writing—original draft, K.K. and S.N.; Writing—review and editing, S.N. and K.T.; Essentially intellectual contributor in entomological experiment design, K.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the MFU Reinventing University and Mae Fah Luang University Grant 641B01003, Thailand.

Data Availability Statement

The data supporting the findings of this study are available within the article and its Supplementary Tables.

Acknowledgments

We sincerely thank the Chiang Rai Rice Research Center in Phan district, Chiang Rai province, Thailand, for kindly providing brown plant hoppers. We would also like to extend special thanks to Vaiphot Kanjoo from Phayao University, Thailand, for providing 97 upland rice varieties.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The frequency of Bph genes found in upland rice varieties.
Figure 1. The frequency of Bph genes found in upland rice varieties.
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Figure 2. Amplification of Bph genes: (a) RM463 marker; (b) RM588 marker; (c) IN76-2 marker; (d) RM261 marker; (e) RM16626 marker; M—molecular marker.
Figure 2. Amplification of Bph genes: (a) RM463 marker; (b) RM588 marker; (c) IN76-2 marker; (d) RM261 marker; (e) RM16626 marker; M—molecular marker.
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Figure 3. The dendrogram depicting the genetic diversity of 143 upland rice varieties.
Figure 3. The dendrogram depicting the genetic diversity of 143 upland rice varieties.
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Figure 4. Population structure of 143 upland rice varieties: (a) The average log-likelihood of K value against K; (b) The relationship between ΔK and K showing the maximum peak at K = 2; (c) Estimation of population structure of 143 upland rice varieties on K = 2.
Figure 4. Population structure of 143 upland rice varieties: (a) The average log-likelihood of K value against K; (b) The relationship between ΔK and K showing the maximum peak at K = 2; (c) Estimation of population structure of 143 upland rice varieties on K = 2.
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Table 1. Details of SSR and InDel markers tightly linked to the Bph resistance genes.
Table 1. Details of SSR and InDel markers tightly linked to the Bph resistance genes.
GeneMarkerChr.Sequences (5′–3′)Type of MarkerTa (°C)Expected Size (bp)BPH Gene Frequency (%)PICRef.
Resistant AlleleSusceptible Allele
bph2RM46312F: 5′-TTCCCCTCCTTTTATGGTGC-3′SSR5520021061.540.4734[34]
R: 5′-TGTTCTCCTCAGTCACTGCG-3′
Bph3RM5883F: 5′-TCTTGCTGTGCTGTTAGTGTACG-3′SSR589011044.060.4876[35]
R: 5′-GCAGGACATAAATACTAGGCATGG-3′
Bph14IN76-23F: 5′-CTGCTGCTGCTCTCGTATTG-3′InDel60.519018033.540.4460[36]
R: 5′-CAGGGAAGCTCCAAGAACAG-3′
Bph15RM2614F: 5′-CTACTTCTCCCCTTGTGTCG-3′SSR5813012062.940.4665[37]
R: 5′-TGTACCATCGCCAAATCTCC-3′
Bph17RM166264F: 5′-ACATGATTGCTGGCTTGCTTACC-3′SSR5820019046.850.4984[38]
R: 5′-GCCACGCAGTGTTGTTTCAGC-3′
SSR—Simple sequence repeats, InDel—Insertion Deletion, PIC—Polymorphic information content.
Table 2. Population structure results of 143 upland rice varieties for the inferred clusters, fixation index (Fst), expected heterozygosity (He), and number of genotypes determined to subpopulation.
Table 2. Population structure results of 143 upland rice varieties for the inferred clusters, fixation index (Fst), expected heterozygosity (He), and number of genotypes determined to subpopulation.
SubpopulationInferred ClustersMean FstExpected Heterozygosity (He)No. of Genotypes
Subpopulation 10.4820.21480.362068
Subpopulation 20.4650.42180.348677
Table 3. Analysis of Molecular Variance (AMOVA) for the 143 upland rice varieties.
Table 3. Analysis of Molecular Variance (AMOVA) for the 143 upland rice varieties.
SourcedfSSMSEst. VarianceVariance (%)
Among subpopulations114.47914.4790.0857
Among individuals143327.8252.2921.13992
Within individuals1452.0000.0140.0141
Total289344.303 1.238100
Fixation index (Fst)0.068
Nm (Heploid)3.410
df—degrees of freedom, SS—Sums of squares, MS—Means squares.
Table 4. Spearman rank correlation between genotype and the rice’s resistance to BPH of upland rice varieties.
Table 4. Spearman rank correlation between genotype and the rice’s resistance to BPH of upland rice varieties.
bph2Bph3Bph14Bph15Bph17
The rice’s resistance to BPH0.076−0.1760.1840.1850.078
p-value0.3610.034 *0.027 *0.026 *0.352
* correlation is significant at the 0.05 level.
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Kanngan, K.; Umalee, P.; Tangtrakulwanich, K.; Nilthong, R.; Nilthong, S. Identification of Major Brown Planthopper Resistance Genes in Indigenous Thai Upland Rice Germplasm Using Molecular Markers. Agronomy 2023, 13, 2605. https://doi.org/10.3390/agronomy13102605

AMA Style

Kanngan K, Umalee P, Tangtrakulwanich K, Nilthong R, Nilthong S. Identification of Major Brown Planthopper Resistance Genes in Indigenous Thai Upland Rice Germplasm Using Molecular Markers. Agronomy. 2023; 13(10):2605. https://doi.org/10.3390/agronomy13102605

Chicago/Turabian Style

Kanngan, Kittiya, Phijittra Umalee, Khanobporn Tangtrakulwanich, Rungrote Nilthong, and Somrudee Nilthong. 2023. "Identification of Major Brown Planthopper Resistance Genes in Indigenous Thai Upland Rice Germplasm Using Molecular Markers" Agronomy 13, no. 10: 2605. https://doi.org/10.3390/agronomy13102605

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