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Article

De Novo Assembly of the Asian Citrus Psyllid Diaphorina citri (Hemiptera: Psyllidae) Transcriptome across Developmental Stages

by
Chunxiao Yang
1,2,3,
Da Ou
2,
Wei Guo
2,
Jing Lü
2,
Changfei Guo
2,
Baoli Qiu
2,* and
Huipeng Pan
2,*
1
State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China
2
Key Laboratory of Bio-Pesticide Innovation and Application of Guangdong Province, South China Agricultural University, Guangzhou 510642, China
3
State Key Laboratory for Biology of Plant Diseases and Insect Pests, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2020, 21(14), 4974; https://doi.org/10.3390/ijms21144974
Submission received: 21 May 2020 / Revised: 9 July 2020 / Accepted: 12 July 2020 / Published: 14 July 2020
(This article belongs to the Section Molecular Biology)
Browse Figures
Versions Notes

Abstract

:
Asian citrus psyllid Diaphorina citri Kuwayama is an important economic pest of citrus, as it transmits Candidatus Liberibacter asiaticus, the causative agent of huanglongbing. In this study, we used RNA-seq to identify novel genes and provide the first high-resolution view of the of D. citri transcriptome throughout development. The transcriptomes of D. citri during eight developmental stages, including the egg, five instars, and male and female adults were sequenced. In total, 115 million clean reads were obtained and assembled into 354,726 unigenes with an average length of 925.65 bp and an N50 length of 1733 bp. Clusters of Orthologous Groups, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses were conducted to functionally annotate the genes. Differential expression analysis highlighted developmental stage-specific expression patterns. Furthermore, two trehalase genes were characterized with lower expression in adults compared to that in the other stages. The RNA interference (RNAi)-mediated suppression of the two trehalase genes resulted in significantly high D. citri mortality. This study enriched the genomic information regarding D. citri. Importantly, these data represent the most comprehensive transcriptomic resource currently available for D. citri and will facilitate functional genomics studies of this notorious pest.

1. Introduction

The Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Psyllidae) is one of the most destructive pests of citrus, due primarily to the fact of its role as the vector of Candidatus Liberibacter asiaticus (CLas) which, worldwide, causes the highly destructive citrus disease huanglongbing (HLB) [1,2]. Huanglongbing is one of the most lethal diseases against citrus and, currently, there is no cure. Diaphorina citri was first described in Taiwan Province in 1907 [3], and the infectious nature of HLB was described in Southern China in 1956 [4]. Large populations of D. citri in HLB-endemic areas often result in high incidences and spread of HLB. Controlling D. citri to reduce its availability as a vector of CLas has been a pivotal global strategy to restrict the spread of HLB. The recent rapid spread of HLB in the Americas has motivated extensive research aimed at improving the understanding of D. citri biology, ecology, and management tactics [5].
Several factors contribute to the status of D. citri as a serious pest species, including adaptation to a wide range of host plants [6], a short life cycle and high fecundity [7], adaptation to growth at a wide range of temperatures [8,9], high dispersal ability [5], and high capacity to evolve resistance to different types of insecticides [5,10,11,12]. Intense use of insecticides has led to the development of high levels of insecticide resistance in D. citri populations [12]. Therefore, the development of novel highly specific and environmentally friendly methods must be considered for controlling this pest.
RNA interference (RNAi) technology is a powerful tool for functional studies that can be used to selectively suppress the expression of target genes both in vitro and in vivo [13,14,15,16,17,18]. RNA interference has been widely explored as an alternative to conventional management methods for controlling insect pests [15,16,17,18]. For example, bacterially expressed double-stranded RNA (dsRNA) from the lesswright (lwr) gene of Henosepilachna vigintioctopunctata was applied to eggplant leaves and caused 88% mortality for the 1st larvae of H. vigintioctopunctata, 66% mortality for the 3rd instar larvae, and 36% mortality to the adults after 10 d, 10 d, and 14 d of application, respectively [15].
The genome of D. citri has been sequenced in recent years (GCA_000475195.1). In addition, transcriptomes of the terminal abdomen and antennae of adult male and female D. citri (SRX1330478–SRX1330481), those of CLas-free and CLas-infected D. citri nymphs and adults (SRX525230, SRX525218, SRX525209, SRX525152), and those encompassing the three main life stages of D. citri (egg, nymph/larva, and adult) have also been sequenced [19]. Diaphorina citri undergoes gradual metamorphosis and, as noted, has three differentiated life stages. The metamorphic changes are accompanied by changes in gene expression. Molecular characterization of D. citri at its various stages of morphogenesis would likely provide important inroads into the identification of novel target sites for pest control. Furthermore, comparison of the developmental transcriptomes of D. citri from the eggs, each of the instars, and adult male and female insects would provide insights into the function of numerous genes and the regulation of different signaling pathways involved during the different developmental stages.
Trehalose is a natural alpha-linked disaccharide formed by an α,α-1,1-glucoside bond between two α-glucose units. Trehalose can be used as an energy source by bacteria, fungi, insects, invertebrates, plants, and a large number of other organisms and plays an important role in stress tolerance [20]. Trehalose is hydrolyzed by the enzyme trehalase into glucose to rapidly provide energy when needed. Trehalase is also the first enzyme in the chitin biosynthesis pathway and significantly influences chitin metabolism by regulating the pathway. Therefore, trehalase has great potential as a target gene for controlling insects using RNAi technology [20,21,22].
In the current study, we attempted to obtain expression data throughout all developmental stages of D. citri by performing comprehensive RNA sequencing. In addition, two trehalase genes were characterized and their functions investigated using RNAi technology. The assembled and annotated transcriptome sequences and gene expression profiles should provide useful information for the identification of genes involved in D. citri development and will facilitate functional genomics studies on this destructive insect species.

2. Results

2.1. Illumina Sequencing and Assembly

To advance our understanding of the molecular mechanisms involved in the developmental changes that occur during D. citri life stages, complementary DNA (cDNA) libraries generated from eggs, 1st instars, 2nd instars, 3rd instars, 4th instars, 5th instars, and male and female adults were sequenced using the Illumina HiSeqTM 2000 sequencing platform. The results were deposited in the Sequence Read Archive (SRA) repository and are available using the following BioProject accession numbers: PRJNA633316, PRJNA634209, and PRJNA633417. The quality statistics of the filtered data are shown in Table S1. A total of 39,787,301 contigs were obtained with a mean length of 58.24 bp and an N50 length of 49 bp. After clustering the contigs with the nucleotide sequences available at the National Center for Biotechnology Information (NCBI), we ultimately obtained 354,726 unigenes with an average length of 925.65 bp and an N50 length of 1733 bp. The unigene length distribution indicated most of the unigenes (52.42%) were concentrated at 200–500 bp lengths (Figure 1).

2.2. Annotation of Predicted Proteins

To annotate the unigenes, we first searched reference sequences using BLASTX against the non-redundant (NR) NCBI protein database using a cut-off E-value of 10−5. The annotation details for each unigene are provided in Table S2, with the matching protein listed was the top hit for each unigene (Table S2). A total of 120,902 of all the annotated unigenes (34.08%) provided a BLAST result. Gene number distribution among the best match top 10 species is shown in Figure 2. A total of 101,114 unigenes were annotated to the 10 top-hit species of insects of which 86,146 annotated genes (approximately 85.20%) were matched to D. citri, the number one top-hit species. The other top-hit species were Zootermopsis nevadensis, Cimex lectularius, Halyomorpha halys, Acyrthosiphon pisum, Diuraphis noxia, Tribolium castaneum, Pediculus humanus corporis, Candidatus Profftella armatura, and Neodiprion lecontei (Figure 2).
A total of 120,902 unigenes were annotated based on four major databases, the NCBI Nr database, SwissProt database, Clusters of Orthologous Groups (COG) database, and Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Table 1) (Figure 3). Among them, 119,683 unigenes were matched in the Nr database including 47,191 unigenes that matched only to this database. In addition, 64,503 unigenes had significant matches in the SwissProt database of which 116 unigenes only matched this database. Moreover, 63,429 unigenes had specific matches in the COG database and 10,121 unigenes had specific matches in the KEGG database, with 507 and 485 unigenes being unique to each database, respectively (Figure 3).

2.3. Functional Annotation Results

The functional classification of D. citri unigenes was predicted by performing Gene Ontology (GO), COG, and KEGG analyses. A total of 33,800 unigenes were assigned to three main categories of GO classification, molecular function (12,876 unigenes), cellular component (8548 unigenes), and biological process (12,376 unigenes). The terms “binding” and “catalytic activity”, “cell part” and “organelle”, and “metabolic process” and “cellular process” were the top two dominant GO terms for each of the three main categories (Figure 4). In total, 58 sub-categories were divided from the primary categories, 23 categories for “biological process,” 18 categories for “cellular component”, and 17 categories for “molecular function.”
For COG functional classification, a total of 71,145 unigenes were annotated to 25 COG categories (Figure 5). Among them, the largest group was the “general function prediction” (9856 genes, 13.85%), followed by the large groups (i.e., >2000 genes), “signal transduction mechanisms” (9776 genes, 13.74%), “transcription” (6216 genes, 8.74%), “posttranslational modification, protein turnover, chaperones” (5522 genes, 7.76%), and “lipid transport and metabolism” (3470 genes, 4.88%).
Diaphorina citri unigene sequences that mapped to reference canonical pathways in the KEGG database were also analyzed. We specifically assigned 31,909 unigene sequences to 44 KEGG pathways. The top three pathways were signal transduction, endocrine system, and translation (Figure 6).

2.4. Differentially Expressed Genes (DEGs)

To identify DEGs among the different developmental stages, the number of clean tags for each gene was calculated. Gene expression variation was analyzed between different stage combinations (Figure 7). The top 20 upregulated and downregulated DEGs expressed genes at each stage are shown in Table S3.

2.5. Developmental Gene Expression of Trehalase 1 and Trehalase 2

Results from the gene expression analysis showed that trehalase 1 was differently expressed across different development stages (F7,16 = 62.363, p < 0.0001). Specifically, the trehalase 1 gene exhibited the highest expression level during the egg stage, while the expression level was lowest in the male and female adults. In addition, expression of trehalase 1 gene was lower in the 5th instar compared to that in the other four instar stages. There was no significant difference in trehalase 1 gene expression among the other development stages (Figure 8A). Similar gene expression profiles were found for the trehalase 2 gene across the different developmental stages (Figure 8B).

2.6. Impact of the silencing of trehalase 1 and trehalase 2 on Gene Expression

After two days of treatment, gene expression of trehalase 1 in instars treated with trehalase1-specific dsRNA (dstrehalase1) was significantly suppressed (F2,6 = 77.681, p < 0.0001). The expression of trehalase 1 was reduced 2.495-fold compared to that of the ddH2O-treated control (Figure 9A). Similarly, gene expression of trehalase 2 in instars treated with trehalase2-specific dsRNA (dstrehalase2) was also significantly suppressed (F2,6 = 24.181, p = 0.001). The expression of trehalase 2 was reduced 2.232 fold compared to that of the ddH2O-treated control (Figure 9B).

2.7. Toxicity of in Vitro Synthesized Dstrehalase1 and Dstrehalase2

Diaphorina citri mortality in the dstrehalase1- and dstrehalase2-treated groups was observed starting on the first day of dsRNA bioassay (Figure 10). Specifically, knockdown of trehalase 1 and trehalase 2 using their respective specific dsRNAs each resulted in significant mortality of D. citri compared to that in the dsGFP-treated and H2O-treated control groups on day 1 (F3,8 = 28.152, p < 0.0001), day 2 (F3,8 = 217.502, p < 0.0001), day 3 (F3,8 = 15.672, p = 0.001), and day 4 (F3,8 = 7.958, p = 0.009) post-treatment (Figure 10). There was no significant difference in D. citri mortality between the dstrehalase1-treated and dstrehalase2-treated groups at any time point.

3. Discussion

In the current study, we compared the transcriptomes of eight developmental stages of D. citri. A better understanding of the molecular mechanisms regulating the life cycles and developmental stages of this important pest may aid in its control by facilitating the development of more sustainable and environmentally friendly interventions. Our results significantly advance the molecular resources available for the study of this and other insect pests and provide a framework to understand changes in gene expression during insect development. We assembled transcriptomes from all eight developmental stages and identified a total of 354,726 unigenes with an average length of 925.65 bp. A total of 120,902 unigenes were annotated using four major databases.
Interestingly, transcriptome sequence analysis revealed that Z. nevadensis, which belong to the order Blattaria, shared the highest similarity with D. citri based on the BLAST annotation. This was in contrast to H. halys, A. pisum, and D. noxia, which like D. citri belong to the order Hemiptera but showed lower best-match percentages. These unexpected results were not likely due to the availability of more sequence resources for Z. nevadensis in the NCBI protein database compared to those for the other organisms, as the number of protein sequences for A. pisum (53,285) was higher than that for Z. nevadensis (49,273). It appears that D. citri may have a closer relationship to Z. nevadensis than to the other Hemipteran insects. The precise relationship among these insect species needs further investigation.
One of the top 10 species regarding distribution of the best match by BLASTX against the Nr database was Ca. Profftella armature. D. citri possesses a specialized organ called a bacteriome, which may harbor the vertically transmitted intracellular mutualists Ca. Carsonella ruddii and Ca. Profftella armature. Carsonella is a typical nutritional symbiont while Profftella is an unprecedented type of toxin-producing defensive symbiont, unusually sharing organelle-like features with nutritional symbionts [23,24]. Furthermore, many strains of D. citri are infected with Wolbachia, which manipulates the reproductive and developmental processes in various arthropod hosts [25]. In our study, Ca. Carsonella ruddii, Ca. Profftella armature, and Wolbachia were each found in the transcriptome, with Profftella having the most abundant transcripts (Table S2). The function of these symbionts in D. citri should be investigated in future studies.
Compared to that of the previous study in which the D. citri transcriptomes of eggs, nymphs, and adults were sequenced with no biological replicate [19], our transcriptome and gene expression profiling data greatly enrich the current D. citri transcriptome database and will benefit research with respect to the identification of novel genes, chemical targets, developmental mechanisms, and sex difference of D. citri. During the developmental stages, most DEGs were Upregulated and downregulated in adults compared to that in eggs. In contrast, the expression of few genes was changed among different larvae stages. Each stage library contained large numbers of genes that showed specific expression and were likely involved in developmental differentiation. This is consistent with other insects that also show their larvae stage development to be tightly regulated by a few key genes, and this regulation is important for developmental differentiation [26,27].
The success of RNAi-based strategies in future pest management will rely on the identification of essential target genes that confer lethal phenotypic effects upon knockdown [28]. Generally, functional genes involved in insect development, metamorphosis, or key metabolic processes may be suitable RNAi targets as part of control strategies of insects [15,16,17,18,29,30,31,32,33]. Previous studies have shown that trehalase plays pivotal roles in various physiological processes, including energy metabolism [34], chitin synthesis during molting [35], and diapause [36]. Recently, trehalases from several insects have been characterized and their biological roles investigated, including those from Nilaparvata lugens [21], Tribolium castaneum [22], and Harmonia axyridis [36]. Suppressing the expression of trehalase can lead to the developmental inhibition and death of the insects [21,22]. In the current study, treating D. citri nymphs with a solution containing dsRNAs specific for trehalase 1 and trehalase 2 genes resulted in a robust RNAi response. When dsRNA is administered by soaking the insect with the solution, the dsRNA can be taken up through spiracles or by cuticle permeation [37]. This is then followed by the spread of the dsRNA/siRNA molecules throughout the body of the insect. The individual insect cells can then take up the dsRNA/siRNA from their nearby environment, thereby inducing the RNAi activity, which is process referred to as environmental RNAi silencing [28]. Ultimately, we found that silencing trehalases induced high mortality in D. citri, which lays the foundation for developing RNAi-based biopesticides aimed at controlling D. citri.
In general, we developed a comprehensive sequence resource of D. citri consisting of a desirable quality. It was built based on preparing and analyzing eight different developmental transcriptomes of D. citri eggs, larvae, and adults. Future analyses of genes related to insect development or death will be useful for pest control. Furthermore, this study enriches the genomic platform of D. citri which should facilitate our understanding of the metamorphosis and development of this important pest insect.

4. Materials and Methods

4.1. Insect Rearing and Sample Preparation

Diaphorina citri adults were collected from Murraya exotica (L.) and reared on host M. exotica in an incubator at 25 ± 0.5 °C, a 16 h light/8 h dark photoperiod and 50% relative humidity. Eight developmental stages of D. citri were sampled, including eggs, 1st instars, 2nd instars, 3rd instars, 4th instars, 5th instars, and male and female adults. Each developmental sample was collected during the first two days of their respective stages. First to fifth instars were discriminated by appearance and body size. All the samples were placed in TRIzol reagent (Invitrogen, Carlsbad, CA, USA), rapidly frozen in liquid nitrogen, and then transferred to −80 °C. All D. citri developmental samples were represented by three biological replicates that were independently processed.

4.2. mRNA Sequencing by ILLUMINA HiSeq

Total RNA was extracted from the D. citri samples using an RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. After quantification of the RNA using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA), a NanoDrop spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA), and 1% agarose gel electrophoresis, the extracted RNA with RNA integrity number (RIN) values >8 was used for generation of cDNA libraries. Next generation sequencing libraries were constructed using a NEBNext® Ultra™ RNA Library Prep Kit for Illumina® according to the manufacturer’s protocol (New England Biolabs, Ipswich, MA, USA). Libraries with different indices were then multiplexed and loaded onto an Illumina HiSeqTM 2000 instrument according to manufacturer’s instructions (Illumina, San Diego, CA, USA). Sequencing was carried out using a 2 × 150 bp paired-end (PE) platform (GENEWIZ, Suzhou, China).

4.3. Functional Annotation Analysis of Sequencing Data

After sequencing, all sequence data were cleaned using Trimmomatic with default parameters [38]. Two approaches were then used for data analysis. For the first approach, expression profiles of each gene at different developmental stages were determined. During this step, both assembly and annotations of D. citri were downloaded from NCBI and used as references. Briefly, the clean data were mapped to the D. citri genome using Hisat2 [39]. Gene values, represented as transcripts per kilobase million (TPM), were then calculated using StringTie [40]. Differentially expressed genes between every two samples were also determined using DESeq with a cutoff for fold change set at > 2 and false discovery rate (FDR) < 0.05 [41]. For the second approach, a transcript dataset of D. citri was constructed. Briefly, all the clean reads were assembled using Trinity [42] and the transcripts generated were clustered by CD-Hit software [43]. Ultimately, transcript datasets of D. citri were constructed using the above approaches. A database consisting of NR, SwissProt, COG, GO, and KEGG gene sequences and related parameters were analyzed using the appropriate software (Table S4).

4.4. Temporal Gene Expression Analysis of Trehalase

RNAs from different developmental stages used for Illumina HiSeq sequencing were used for gene expression analysis. First-strand cDNA was prepared using 1 μg of total RNA and a PrimeScript RT Kit with gDNA Eraser (Perfect Real Time) from TaKaRa (Dalian, China) following the manufacturer’s instructions. The synthesized first-strand cDNA was diluted 10 fold and was immediately used or stored at −20 °C until used.
Real-time reverse transcription polymerase chain reaction (RT-qPCR) was conducted according to the manufacturer’s recommendations using SYBR® Premix Ex Taq™ (Tli RNaseH Plus) purchased from TaKaRa. PCR amplification in 15 μL reactions were performed using the cycling program and PCR system described in our previous study [44]. Briefly, PCR reaction mixtures contained 5.25 μL ddH2O, 7.5 μL 2× SYBR Green MasterMix (Bio-Rad Laboratories, Hercules, CA, USA), 4 μM each specific primer, and 1.0 μL first-strand cDNA template. The RT-qPCR program included an initial denaturation at 95 °C for 3 min followed by 40 cycles of denaturation at 95 °C for 10 s, annealing for 30 s at 55 °C, and extension for 30 s at 72 °C. The gene-specific primers used for the RT-qPCR are listed in Table 2. Relative quantification was calculated using the 2−ΔΔCt method [45] and data were normalized to expression of reference genes GAPDH and EF1α [46]. Three technical replicates were used for each sample.

4.5. dsRNA Synthesis

Specific dsRNA primers containing a T7 promoter sequence at the 5′end targeting trehalase 1 and trehalase 2 were designed using E-RNAi. The sequences of the primers are listed in Table 3. The PCR template and cycling program used were described in our previous study [44]. PCR products were purified using a Universal DNA Purification Kit (TIANGEN, Beijing, China) and used as template with a T7 MEGAscript Kit (Thermo Fisher Scientific) following the manufacturer’s protocol to generate the dsRNA. The primers for dsGFP synthesis were used according to our recent study [16]. Synthesized dsRNAs were purified and suspended in ddH2O and their size and integrity confirmed by 1.5% agarose/TAE gel electrophoresis stained with GoldView I. Concentrations of the purified dsRNAs were determined using a NanoDrop One spectrophotometer (Thermo Fisher Scientific), and the purified dsRNAs were stored at −20 °C until use.

4.6. RNA Interference Assays on D. citri

In our preliminary investigation, the effect of dsRNA on D. citri 2nd instars mortality was determined using dstrehalase concentrations of 10, 25, 50, 75, and 100 ng/μL. We found that D. citri 2nd instars had the highest mortality rates when exposed to 75 ng/μL dstrehalase and the mortality did not increase when the dstrehalase concentration was increased to 100 ng/μL. Therefore, the concentration of dsRNA used in this study was 75 ng/μL. RNA interference assays were conducted according to a recent study [14] with modification. Specifically, D. citri 2nd instars were starved for two hours and then completely soaked with a 4 μL droplet containing 75 ng/μL dsRNA. The dsRNA droplet was removed using a pipette after soaking for approximately 2 min. As controls, additional D. citri 2nd instars were treated with ddH2O or dsGFP. After drying on filter paper, 20 newly emerged D. citri 2nd instars were transferred onto 5 to 7 M. paniculata seedlings of a true leaf stage (tender leaf). The petiole was then fixed in agar at the bottom of a glass cylindrical container (4 cm diameter and 20 cm high), the upper opening of the cylinder was covered with a mesh screen for ventilation, and the agar was covered with a piece of filter paper and cotton to prevent water loss. The feeding chambers were placed incubated at 25 ± 0.5 °C with a 16 h light/8 h dark photoperiod and 50% relative humidity. Each treatment was performed using three biological replicates. Mortality was monitored and recorded for four days.
For analysis of gene suppression caused by the cognate mRNAs, D. citri 2nd instars were treated as noted above. A total of 100 instars were used for each treatment. After two days, 50 living nymphs were collected, flash-frozen in liquid nitrogen, and stored at –80 °C in 1.5 mL centrifuge tubes until processed for total RNA extraction. Each treatment was independently repeated three times. For RT-qPCR analysis, total RNA was extracted, cDNA synthesized, and RT-qPCR amplification performed as described above. Three technical replicates were used for each sample.

4.7. Data Analysis

One-way analysis of variance (ANOVA) was used to detect significant differences in trehalase 1 and trehalase 2 expression levels among different treatments, followed by a Tukey’s multiple range test with p < 0.05 being considered statistically significant. One-way ANOVA was also used to compare mortality rates each day of D. citri treated with H2O, dsGFP, dstrehalase1, and dstrehalase2. Mortality means were compared using Tukey’s tests and again p < 0.05 was considered statistically significant. Proportional data were arcsine square root transformed before analyses. All statistical analyses were performed using SPSS version 21.0 software (SPSS Inc., Chicago, IL, USA).

5. Conclusions

Our data greatly improved our genetic understanding of D. citri and provides a large number of gene sequences for future studies. Our findings also provide comprehensive insight into gene expression profiles across different developmental stages of D. citri. Dietary RNAi toxicity assays demonstrated that trehalase 1 and trehalase 2 may be effective molecular targets for controlling D. citri. However, prior to the practical application of RNAi to control D. citri, further studies are necessary, such as determining an effective delivery system of dsRNA to citrus trees.

Supplementary Materials

Supplementary materials can be found at https://www.mdpi.com/1422-0067/21/14/4974/s1. Table S1. The quality statistics of the filtered sequencing data. Table S2. The Nr annotation information for each unigene. Table S3. The top 20 upregulated and downregulated differential expression genes expressed genes at each stage. The stage on the right for each DEG comparison served as the control. Table S4. Gene function analysis software and parameters.

Author Contributions

Conceptualization, H.P. and C.Y.; methodology, H.P.; validation, D.O., W.G., J.L. and C.G.; formal analysis, H.P.; investigation, C.Y., D.O., W.G., J.L. and C.G.; resources, B.Q.; data curation, D.O., W.G., J.L. and C.G.; writing—original draft preparation, H.P., C.Y.; writing—review and editing, H.P. and C.Y.; supervision, H.P.; funding acquisition, H.P. All authors have read and agreed to the published version of the manuscript

Funding

This research was funded by the State Key Laboratory for Biology of Plant Diseases and Insect Pests (SKLOF201808), the Science and Technology Program of Guangzhou (201804020070), a project supported by GDUPS (2017), and a start-up fund from the South China Agricultural University.

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.

Abbreviations

NrNon-redundant
COGClusters of Orthologous Groups of proteins
GOGene Ontology
KEGGKyoto Encyclopedia of Genes and Genomes
RT-qPCRreverse transcriptase-quantitative polymerase chain reaction

References

  1. Bové, J.M. Huanglongbing: A destructive, newly-emerging, century-old disease of citrus. J. Plant Pathol. 2006, 88, 7–37. [Google Scholar]
  2. Hall, D.G.; Richardson, M.L.; Ammar, E.D.; Halbert, S.E. Asian citrus psyllid, Diaphorina citri, vector of citrus huanglongbing disease. Entomol. Exp. Appl. 2013, 146, 207–223. [Google Scholar] [CrossRef]
  3. Kuwayama, S. Die psylliden Japans. Trans. Sapporo Nat. Hist. Soc. 1908, 2, 149–189. [Google Scholar]
  4. Lin, K.H. Observations on yellow shoot of citrus: Etiological studies of yellow shoot of citrus. Acta Phytopathol. Sin. 1956, 2, 13–42. [Google Scholar]
  5. Grafton-Cardwell, E.E.; Stelinski, L.L.; Stansly, P.A. Biology and management of Asian citrus psyllid, vector of the huanglongbing pathogens. Annu. Rev. Entomol. 2013, 58, 413–432. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Yang, Y.; Huang, M.; Beattie, G.A.; Xia, Y.; Ouyang, G.; Xiong, J. Distribution, biology, ecology and control of the psyllid Diaphorina citri Kuwayama, a major pest of citrus: A status report for China. Int. J. Pest Manag. 2006, 52, 343–352. [Google Scholar] [CrossRef]
  7. Halbert, S.E.; Manjunath, K.L. Asian citrus psyllids (Sternorrhyncha: Psyllidae) and greening disease of citrus: A literature review and assessment of risk in Florida. Fla. Entomol. 2004, 87, 330–353. [Google Scholar] [CrossRef]
  8. Hall, D.G.; Wenninger, E.J.; Hentz, M.G. Temperature studies with the Asian citrus psyllid, Diaphorina citri: Cold hardiness and temperature thresholds for oviposition. J. Insect Sci. 2011, 11, 83. [Google Scholar] [CrossRef] [Green Version]
  9. Liu, Y.H.; Tsai, J.H. Effects of temperature on biology and life table parameters of the Asian citrus psyllid, Diaphorina citri Kuwayama (Homoptera: Psyllidae). Ann. Appl. Biol. 2000, 137, 201–206. [Google Scholar] [CrossRef]
  10. Tiwari, S.; Gondhalekar, A.D.; Mann, R.S.; Scharf, M.E.; Stelinski, L.L. Characterization of five CYP4 genes from Asian citrus psyllid and their expression levels in Candidatus Liberibacter asiaticus-infected and uninfected psyllids. Insect Mol. Biol. 2011, 20, 733–744. [Google Scholar] [CrossRef]
  11. Serikawa, R.H.; Backus, E.A.; Rogers, M.E. Effects of soil-applied imidacloprid on Asian citrus psyllid (Hemiptera: Psyllidae) feeding behavior. J. Econ. Entomol. 2012, 105, 1492–1502. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Boina, D.R.; Bloomquist, J.R. Chemical control of the Asian citrus psyllid and of huanglongbing disease in citrus. Pest Manag. Sci. 2015, 71, 808–823. [Google Scholar] [CrossRef] [PubMed]
  13. Fire, A.; Xu, S.; Montgomery, M.K.; Kostas, S.A.; Driver, S.E.; Mello, C.C. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 1998, 391, 806–811. [Google Scholar] [CrossRef] [PubMed]
  14. Yu, X.; Gowda, S.; Killiny, N. Double-stranded RNA delivery through soaking mediates silencing of the muscle protein 20 and increases mortality to the Asian citrus psyllid, Diaphorina citri. Pest Manag. Sci. 2017, 73, 1846–1853. [Google Scholar] [CrossRef] [PubMed]
  15. Lü, J.; Liu, Z.Q.; Guo, W.; Guo, M.J.; Chen, S.M.; Yang, C.X.; Zhang, Y.J.; Pan, H.P. Oral delivery of dsHvlwr is a feasible method for management of the pest Henosepilachna vigintioctopunctata (Coleoptera: Coccinellidae). Insect Sci. 2020. [Google Scholar] [CrossRef]
  16. Lü, J.; Guo, W.; Chen, S.M.; Guo, M.J.; Qiu, B.L.; Yang, C.X.; Zhang, Y.J.; Pan, H.P. Double-stranded RNAs targeting HvRPS18 and HvRPL13 reveal potential targets for pest management of the 28-spotted ladybeetle, Henosepilachna vigintioctopunctata. Pest Manag. Sci. 2020. [Google Scholar] [CrossRef]
  17. Lü, J.; Guo, M.J.; Chen, S.M.; Noland, J.E.; Guo, W.; Sang, W.; Qi, Y.X.; Qiu, B.L.; Zhang, Y.J.; Yang, C.X.; et al. Double-stranded RNA targeting vATPase B reveals a potential target for pest management of Henosepilachna vigintioctopunctata. Pestic. Biochem. Phys. 2020. [Google Scholar] [CrossRef]
  18. Lü, J.; Liu, Z.Q.; Guo, W.; Guo, M.J.; Chen, S.M.; Li, H.L.; Yang, C.X.; Zhang, Y.J.; Pan, H.P. Feeding delivery of dsHvSnf7 is a promising method for management of the pest Henosepilachna vigintioctopunctata (Coleoptera: Coccinellidae). Insects 2020, 11, 34. [Google Scholar] [CrossRef] [Green Version]
  19. Reese, J.; Christenson, M.K.; Leng, N.; Saha, S.; Cantarel, B.; Lindeberg, M.; Tamborindeguy, C.; MacCarthy, J.; Weaver, D.; Trease, A.J.; et al. Characterization of the Asian citrus psyllid transcriptome. J. Genomics 2014, 2, 54–58. [Google Scholar] [CrossRef]
  20. Zhu, K.Y.; Merzendorfer, H.; Zhang, W.; Zhang, J.; Muthukrishnan, S. Biosynthesis, turnover, and functions of chitin in insects. Annu. Rev. Entomol. 2016, 61, 177–196. [Google Scholar] [CrossRef]
  21. Zhao, L.N.; Yang, M.M.; Shen, Q.D.; Liu, X.J.; Shi, Z.K.; Wang, S.G.; Tang, B. Functional characterization of three trehalase genes regulating the chitin metabolism pathway in rice brown planthopper using RNA interference. Sci. Rep. 2016, 6, 27841. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Tang, B.; Wei, P.; Zhao, L.N.; Shi, Z.K.; Shen, Q.D.; Yang, M.M.; Xie, G.Q.; Wang, S.G. Knockdown of five trehalase genes using RNA interference regulates the gene expression of the chitin biosynthesis pathway in Tribolium castaneum. BMC Biotechnol. 2016, 16, 67. [Google Scholar] [CrossRef] [Green Version]
  23. Yamada, T.; Hamada, M.; Floreancig, P.; Nakabachi, A. Diaphorin, a polyketide synthesized by an intracellular symbiont of the Asian citrus psyllid, is potentially harmful for biological control agents. PLoS ONE 2019, 14, e0216319. [Google Scholar] [CrossRef] [Green Version]
  24. Nakabachi, A.; Malenovský, I.; Gjonov, I.; Hirose, Y. 16S rRNA sequencing detected Profftella, Liberibacter, Wolbachia, and Diplorickettsia from relatives of the Asian citrus psyllid. Microb. Ecol. 2020. [Google Scholar] [CrossRef] [PubMed]
  25. Takano, S.I.; Tuda, M.; Takasu, K.; Furuya, N.; Imamura, Y.; Kim, S.; Tashiro, K.; Iiyama, K.; Tavares, M.; Amaral, A.C. Unique clade of alphaproteobacterial endosymbionts induces complete cytoplasmic incompatibility in the coconut beetle. Proc. Natl. Acad. Sci. USA 2017, 114, 6110–6115. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Wang, X.W.; Luan, J.B.; Li, J.M.; Bao, Y.Y.; Zhang, C.X.; Liu, S.S. De novo characterization of a whitefly transcriptome and analysis of its gene expression during development. BMC Genomics 2010, 11, 400. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Shen, G.M.; Dou, W.; Niu, J.Z.; Jiang, H.B.; Yang, W.J.; Jia, F.X.; Hu, F.; Cong, L.; Wang, J.J. Transcriptome analysis of the oriental fruit fly (Bactrocera dorsalis). PLoS ONE 2011, 6, e29127. [Google Scholar] [CrossRef]
  28. Zhu, K.Y.; Palli, S.R. Mechanisms, Applications, and Challenges of Insect RNA Interference. Annu. Rev. Entomol. 2020, 65, 293–311. [Google Scholar] [CrossRef] [Green Version]
  29. Zhu, F.; Xu, J.; Palli, R.; Ferguson, J.; Palli, S.R. Ingested RNA interference for managing the populations of the Colorado potato beetle, Leptinotarsa decemlineata. Pest Manag. Sci. 2011, 67, 175–182. [Google Scholar] [CrossRef]
  30. Liu, F.Z.; Yang, B.; Zhang, A.H.; Ding, D.R.; Wang, G.R. Plant-mediated RNAi for controlling Apolygus lucorum. Front. Plant Sci. 2019, 10, 64. [Google Scholar] [CrossRef] [Green Version]
  31. Guo, Z.J.; Kang, S.; Zhu, X.; Xia, J.X.; Wu, Q.J.; Wang, S.L.; Xie, W.; Zhang, Y.J. The novel ABC transporter ABCH1 is a potential target for RNAi-based insect pest control and resistance management. Sci. Rep. 2015, 5, 13728. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Vélez, A.M.; Fishilevich, E.; Rangasamy, M.; Khajuria, C.; Mccaskill, D.G.; Pereira, A.E.; Gandra, P.; Frey, M.; Worden, S.E.; Whitlock, S.L.; et al. Control of western corn rootworm via RNAi traits in maize: Lethal and sublethal effects of Sec23 dsRNA. Pest Manag. Sci. 2020, 76, 1500–1512. [Google Scholar] [CrossRef] [Green Version]
  33. Asano, N. Glycosidase inhibitors: Update and perspectives on practical use. Glycobiology 2003, 13, 93R–104R. [Google Scholar] [CrossRef]
  34. Chen, J.; Tang, B.; Chen, H.X.; Yao, Q.; Huang, X.F.; Chen, J.; Zhang, D.W.; Zhang, W.Q. Different functions of the insect soluble and membrane-bound trehalase genes in chitin biosynthesis revealed by RNA interference. PLoS ONE 2010, 5, e10133. [Google Scholar] [CrossRef]
  35. Shukla, E.; Thorat, L.J.; Nath, B.B.; Gaikwad, S.M. Insect trehalase: Physiological significance and potential applications. Glycobiology 2014, 25, 357–367. [Google Scholar] [CrossRef] [Green Version]
  36. Tang, B.; Qin, Z.; Shi, Z.K.; Wang, S.; Guo, X.J.; Wang, S.G.; Zhang, F. Trehalase in Harmonia axyridis (Coleoptera: Coccinellidae): Effects on beetle locomotory activity and the correlation with trehalose metabolism under starvation conditions. Appl. Entomol. Zool. 2014, 49, 255–264. [Google Scholar] [CrossRef]
  37. Whyard, S.; Singh, A.D.; Wong, S. Ingested double-stranded RNAs can act as species-specific insecticides. Insect Biochem. Mol. Biol. 2009, 39, 824–832. [Google Scholar] [CrossRef]
  38. Bolger, A.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [Green Version]
  39. Pertea, M.; Kim, D.; Pertea, G.M.; Leek, J.T.; Salzberg, S.L. Transcript-level expression analysis of RNA-seq experiments with hisat, stringtie and ballgown. Nat. Protoc. 2016, 11, 1650–1667. [Google Scholar] [CrossRef]
  40. Pertea, M.; Pertea, G.M.; Antonescu, C.M.; Chang, T.C.; Mendell, J.T.; Salzberg, S.L. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 2015, 33, 290–295. [Google Scholar] [CrossRef] [Green Version]
  41. Anders, S.; Huber, W. Differential Expression of RNA-Seq Data at the Gene Level-the DESeq Package; European Molecular Biology Laboratory (EMBL): Heidelberg, Germany, 2012. [Google Scholar]
  42. Grabherr, M.G.; Haas, B.J.; Yassour, M.; Levin, J.Z.; Thompson, D.A.; Amit, I.; Adiconis, X.; Fan, L.; Raychowdhury, R.; Zeng, Q.D.; et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 2011, 29, 644–652. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Fu, L.; Niu, B.; Zhu, Z.; Wu, S.; Li, W. CD-HIT: Accelerated for clustering the next-generation sequencing data. Bioinformatics 2012, 28, 3150–3152. [Google Scholar] [CrossRef] [PubMed]
  44. Pan, H.P.; Yang, X.W.; Bidne, K.; Hellmich, R.L.; Siegfried, B.D.; Zhou, X.G. Dietary risk assessment of v-ATPase A dsRNAs on monarch butterfly larvae. Front. Plant Sci. 2017, 8, 242. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  46. Bin, S.; Pu, X.; Shu, B.; Kang, C.; Luo, S.; Tang, Y.; Wu, Z.; Lin, J. Selection of reference genes for optimal normalization of quantitative real-time polymerase chain reaction results for Diaphorina citri adults. J. Econ. Entomol. 2019, 112, 355–363. [Google Scholar] [CrossRef] [Green Version]
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Figure 1. Unigene size distribution. Unigene sizes were calculated, and their relative distribution (%) according to size (bp) are shown.
Figure 1. Unigene size distribution. Unigene sizes were calculated, and their relative distribution (%) according to size (bp) are shown.
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Figure 2. Top 10 species distribution of the BLASTX top hits results. Species distribution of the unigene BLASTX top hits results against the National Center for Biotechnology Information (NCBI) non-redundant protein database using a cutoff E-value of 10−5 and the proportions of each species are shown. Each bar represents a different species.
Figure 2. Top 10 species distribution of the BLASTX top hits results. Species distribution of the unigene BLASTX top hits results against the National Center for Biotechnology Information (NCBI) non-redundant protein database using a cutoff E-value of 10−5 and the proportions of each species are shown. Each bar represents a different species.
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Figure 3. Comparison of unigene annotation in the National Center for Biotechnology Information (NCBI) non-redundant (Nr), SwissProt, Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genome (KEGG) databases.
Figure 3. Comparison of unigene annotation in the National Center for Biotechnology Information (NCBI) non-redundant (Nr), SwissProt, Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genome (KEGG) databases.
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Figure 4. Gene Ontology (GO) functional categories of the unigenes annotated in the current study. Unigenes were annotated to three main categories: molecular function, cellular component, and biological process.
Figure 4. Gene Ontology (GO) functional categories of the unigenes annotated in the current study. Unigenes were annotated to three main categories: molecular function, cellular component, and biological process.
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Figure 5. Clusters of Orthologous Groups (COG) functional categories of the unigenes annotated in the current study. The names of each class definition (A to Y) are provided on the right side of the figure.
Figure 5. Clusters of Orthologous Groups (COG) functional categories of the unigenes annotated in the current study. The names of each class definition (A to Y) are provided on the right side of the figure.
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Figure 6. Kyoto Encyclopedia of Genes and Genome (KEGG) functional categories of the unigenes annotated in the current study. Unigenes were annotated and assigned to six main categories, cellular processes, environmental information processing, genetic information processing, human diseases, metabolism, and organismal systems.
Figure 6. Kyoto Encyclopedia of Genes and Genome (KEGG) functional categories of the unigenes annotated in the current study. Unigenes were annotated and assigned to six main categories, cellular processes, environmental information processing, genetic information processing, human diseases, metabolism, and organismal systems.
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Figure 7. Comparison of differentially expressed gene (DEG) numbers in each. Upregulated (UP) and downregulated (DOWN) unigenes were quantified. The results of 28 comparisons are shown. (A) the comparison of DEGs between egg and other stages; (B) the comparison of DEGs between 1st instar and other stages; (C) the comparison of DEGs between 2nd instar and other stages; (D) the comparison of DEGs between 3rd instar and other stages; (E) the comparison of DEGs between 4th instar and other stages; (F) the comparison of DEGs between 5th instar and other stages; (G) the comparison of DEGs between female and male.
Figure 7. Comparison of differentially expressed gene (DEG) numbers in each. Upregulated (UP) and downregulated (DOWN) unigenes were quantified. The results of 28 comparisons are shown. (A) the comparison of DEGs between egg and other stages; (B) the comparison of DEGs between 1st instar and other stages; (C) the comparison of DEGs between 2nd instar and other stages; (D) the comparison of DEGs between 3rd instar and other stages; (E) the comparison of DEGs between 4th instar and other stages; (F) the comparison of DEGs between 5th instar and other stages; (G) the comparison of DEGs between female and male.
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Figure 8. Expression patterns of trehalase 1 (A) and trehalase 2 (B) in D. citri across different developmental stages. The values shown are means + SE. Different letters indicate significant differences in gene expression across different developmental stages (p < 0.05).
Figure 8. Expression patterns of trehalase 1 (A) and trehalase 2 (B) in D. citri across different developmental stages. The values shown are means + SE. Different letters indicate significant differences in gene expression across different developmental stages (p < 0.05).
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Figure 9. Relative gene expression in D. citri 2nd instars after treatment with specific double-stranded RNA (dsRNA). Trehalase 1 (A) and trehalase 2 (B). The 2nd instars were treated with trehalase1-specific dsRNA (dstrhalase1), trehalase2-specific dsRNA (dstrhalase2), control green fluorescent protein-specific dsRNA (dsGFP), or water (H2O) and the gene expression levels were measured. Values shown are means + SE. Different letters indicate significant differences among treatments (p < 0.05, Tukey’s multiple comparisons test).
Figure 9. Relative gene expression in D. citri 2nd instars after treatment with specific double-stranded RNA (dsRNA). Trehalase 1 (A) and trehalase 2 (B). The 2nd instars were treated with trehalase1-specific dsRNA (dstrhalase1), trehalase2-specific dsRNA (dstrhalase2), control green fluorescent protein-specific dsRNA (dsGFP), or water (H2O) and the gene expression levels were measured. Values shown are means + SE. Different letters indicate significant differences among treatments (p < 0.05, Tukey’s multiple comparisons test).
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Figure 10. Effect of trehalase1-specific double-stranded RNA (dstrehalase1) and trehalase2-specific double-stranded RNA (dstrehalase2) treatment on D. citri 2nd instars mortality. D. citri 2nd instars were treated with dstrehalase1, dstrehalase2, green fluorescent protein-specific dsRNA (dsGFP), or water (H2O) and monitored for mortality. Values shown in the figure are means ± SE. * Indicates statistically significant differences (p < 0.05; ANOVA, Tukey’s multiple comparisons test).
Figure 10. Effect of trehalase1-specific double-stranded RNA (dstrehalase1) and trehalase2-specific double-stranded RNA (dstrehalase2) treatment on D. citri 2nd instars mortality. D. citri 2nd instars were treated with dstrehalase1, dstrehalase2, green fluorescent protein-specific dsRNA (dsGFP), or water (H2O) and monitored for mortality. Values shown in the figure are means ± SE. * Indicates statistically significant differences (p < 0.05; ANOVA, Tukey’s multiple comparisons test).
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Table
Table 1. Statistics of annotation results.
Table 1. Statistics of annotation results.
DatabaseNrSwissProtCOGKEGGTotal
Unigenes119,68364,50363,42910,121120,902
Table
Table 2. Assembly statistics for Diaphorina citri transcriptomes across developmental stages.
Table 2. Assembly statistics for Diaphorina citri transcriptomes across developmental stages.
TypeTotal SequencesGC PercentageN50Max LengthMin LengthAverage LengthTotal Assembled Bases
Contig39,787,30142.54%4919,0672558.242,317,181,757
Unigene354,72639.43%173319,592201925.65328,351,381
Table
Table 3. Primers used in this study.
Table 3. Primers used in this study.
Name of PrimersPrimer Sequences (5′-3′)
dstrehalase1-FTAATACGACTCACTATAGGGGGGCGTGATCGAGAACATAA
dstrehalase1-RTAATACGACTCACTATAGGGGATGAACCACCGACTGGAAA
dstrehalase2-FTAATACGACTCACTATAGGGCTTTGAAGCAGGCAATGAGC
dstrehalase2 -RTAATACGACTCACTATAGGGGCACAATCTGTTGCCGATTT
RT-qPCR-trehalase1-FTTTCCAGTCGGTGGTTCATC
RT-qPCR-trehalase1-RCCACCATTCGCTCAGATAGTT
RT-qPCR-trehalase2-FCGAGCCTTGCTCACCAATAA
RT-qPCR-trehalase2-RCTCGGGTTGGAGGTGAAATC

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MDPI and ACS Style

Yang, C.; Ou, D.; Guo, W.; Lü, J.; Guo, C.; Qiu, B.; Pan, H. De Novo Assembly of the Asian Citrus Psyllid Diaphorina citri (Hemiptera: Psyllidae) Transcriptome across Developmental Stages. Int. J. Mol. Sci. 2020, 21, 4974. https://doi.org/10.3390/ijms21144974

AMA Style

Yang C, Ou D, Guo W, Lü J, Guo C, Qiu B, Pan H. De Novo Assembly of the Asian Citrus Psyllid Diaphorina citri (Hemiptera: Psyllidae) Transcriptome across Developmental Stages. International Journal of Molecular Sciences. 2020; 21(14):4974. https://doi.org/10.3390/ijms21144974

Chicago/Turabian Style

Yang, Chunxiao, Da Ou, Wei Guo, Jing Lü, Changfei Guo, Baoli Qiu, and Huipeng Pan. 2020. "De Novo Assembly of the Asian Citrus Psyllid Diaphorina citri (Hemiptera: Psyllidae) Transcriptome across Developmental Stages" International Journal of Molecular Sciences 21, no. 14: 4974. https://doi.org/10.3390/ijms21144974

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