Figures
Abstract
To study crab immunogenetics of individuals, newly hatched Eriocheir sinensis larvae were stimulated with a mixture of three pathogen strains (Gram-positive bacteria Micrococcus luteus, Gram-negative bacteria Vibrio alginolyticus and fungi Pichia pastoris; 108 cfu·mL-1). A total of 44,767,566 Illumina clean reads corresponding to 4.52 Gb nucleotides were generated and assembled into 100,252 unigenes (average length: 1,042 bp; range: 201-19,357 bp). 17,097 (26.09%) of 65,535 non-redundant unigenes were annotated in NCBI non-redundant protein (Nr) database. Moreover, 23,188 (35.38%) unigenes were assigned to three Gene Ontology (GO) categories, 15,071 (23.00%) to twenty-six Clusters of orthologous Groups (COG) and 8,574 (13.08%) to six Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, respectively. Numerous genes were further identified to be associated with multiple immune pathways, including Toll, immune deficiency (IMD), janus kinase (JAK)-signal transducers and activators of transcription (STAT) and mitogen-activated protein kinase (MAPK) pathways. Some of them, such as tumor necrosis factor receptor associated factor 6 (TRAF6), fibroblast growth factor (FGF), protein-tyrosine phosphatase (PTP), JNK-interacting protein 1 (JIP1), were first identified in E. sinensis. TRAF6 was even first discovered in crabs. Additionally, 49,555 single nucleotide polymorphisms (SNPs) were developed from over 13,309 unigenes. This is the first transcriptome report of whole bodies of E. sinensis larvae after immune challenge. Data generated here not only provide detail information to identify novel genes in genome reference-free E. sinensis, but also facilitate our understanding on host immunity and defense mechanism of the crab at whole transcriptome level.
Citation: Cui Z, Li X, Liu Y, Song C, Hui M, Shi G, et al. (2013) Transcriptome Profiling Analysis on Whole Bodies of Microbial Challenged Eriocheir sinensis Larvae for Immune Gene Identification and SNP Development. PLoS ONE 8(12): e82156. https://doi.org/10.1371/journal.pone.0082156
Editor: Dongsheng Zhou, Beijing Institute of Microbiology and Epidemiology, China
Received: August 3, 2013; Accepted: October 21, 2013; Published: December 4, 2013
Copyright: © 2013 Cui et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was supported by the Chinese National ‘863’ Project (number 2012AA10A409) and the National Natural Science Foundation of China (41276165). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Chinese mitten crab Eriocheir sinensis, belonging to Grapsidae family of decapod crustaceans, is a catadromous species with a lifetime about two years. The crab has one reproductive season and dies shortly after reproduction [1]. After being hatched, E. sinensis larvae normally experience several developmental processes, including five typical Zoea-stages (Zoea I-V) and a Megalopa-stage [2]. Culture of E. sinensis under facility condition has started since 1980s [3] and constitutes a prospective freshwater fishery industry. It then produces tons of crabs as common food every year in China. Also, E. sinensis is easily to be artificially propagated and transported over long distance, which may make the species as a model organism in aquaculture studies. However, with development of intensive culture, various diseases like tremor disease (TD) and black gill syndrome (BGS) frequently occur and seriously threaten E. sinensis stocks. In particular, larvae of the species suffer from diseases more often than adult crabs. High mortalities of larvae can be easily caused by infection with microorganisms of Vibrio, Micrococcus and Fungus [4]. It is compulsory to obtain comprehensive knowledge about immune system of the crab.
Analysis of expressed sequence tags (ESTs) from cDNA library by Sanger sequencing method is proved to be useful for gene identification and expression profiling analysis. Several EST analyses of haemocytes and hepatopancreas from healthy E. sinensis are performed and numerous immune related sequences are consequently obtained [3,5,6]. They supply basic data for development of functional genes and molecular markers to increase disease resistance of crabs. Some immune genes are also cloned and characterized from haemocytes (haemolymph) of E. sinensis, such as crustin [7], antioxidative protein [8-10], antilipopolysaccharide factor (ALF) [11-13], prophenoloxidase (proPO) [14], serine proteinase (SP) and serine proteinase homologous (SPH) [15,16]. However, due to the limitation of traditional sequencing method and the tissues used for analysis, immune information of E. sinensis is still scattered and inadequate.
Newly-developed high-throughput sequencing technologies, such as Roche/454, Solexa/Illumina and ABI/SOLiD, furnish the opportunity to produce large numbers of sequence data in non-model organisms [17]. They provide a convenient and high-effective solution for de novo assembly of genome reference-free species [18]. Roche 454 pyrosequencing is a primary approach to yield transcriptomic resources and discover important genes [19-22]. However, application of this technique can be hindered by its high cost. Comparing with 454, Illumina and SOLiD provide ultra-short reads, but they are up to 30 times less expensive and produce much more sequence reads [23,24]. In recent years, Illumina method has been widely used in transcriptome analyses of various species [23,25-29]. Studies on transcriptomes from whole bodies of larvae are performed in different invertebrates, such as Litopenaeus vannamei [28], Musca domestica [30], Galleria mellonella [31] and Apis cerana cerana [32]. These reports establish fundamental data to develop extensive genomic and transcriptomic resources for invertebrate larvae.
Previously, we have identified numerous immune-related genes from transcriptome of microbial challenged E. sinensis hepatopancreas [33]. It provides a basis for functional classification and gene characterization of mitten crab. In the present study, whole bodies of E. sinensis larvae were challenged by a mixture of three pathogen strains (Gram-positive bacteria Micrococcus luteus, Gram-negative bacteria Vibrio alginolyticus and fungi Pichia pastoris). These pathogens represented three different types of major microbes that infected the crab and brought about serious diseases in aquaculture. The experimental analysis was expected to completely reveal sequence information, especially the important immune genes of challenged E. sinensis, which could be valuable to study crab immunogenetics and enhance crab resistance to various microorganisms. Besides, SNPs that were ready for marker development were identified in this study. The investigation might provide useful information for future studies on genetics and immunity of E. sinensis and other economic crustaceans.
Materials and Methods
Ethic statement
All animal treatments of the study were strictly carried out according to the Guide for Care and Use of Laboratory Animals by Chinese Association for Laboratory Animal Sciences (No. 2011-2).
Preparation of experimental crabs
Healthy berried female mitten crabs were obtained from a farm in Panjin, China and cultured in aerated seawater at 18±1 °C. During whole period of the experiment, all crabs were fed with clam meat once daily at night. Egg incubation and larval hatching were carried out using the same method with Sui et al [34]. In brief, berried crabs were incubated until larvae were hatched and newly hatched larvae were immediately challenged with microorganisms.
Three pathogen strains (Gram-negative bacteria Vibrio alginolyticus, Gram-positive bacteria Micrococcus luteus and fungi Pichia pastoris) were mixed and suspended in 0.1 mol/L PBS (pH 7.0) with the final pathogen concentration of 108 cfu·mL-1. Lots of small newly hatched larvae were too hard to be directly injected into the body. It might also influence crab responses by physical stimulation as well. To overcome these shortcomings, hundreds of zoea larvae were cultured in seawater containing 100 μL the mixture of pathogens. At 1h post-challenge, whole bodies of all the treated larvae were collected with mesh grid and pooled as one sample for RNA isolation and transcriptome analysis. They were immediately placed in liquid nitrogen until use.
cDNA preparation, transcriptome sequencing and assembly
Total RNA was extracted using Trizol Reagent (Invitrogen). RNA quality and concentration were determined by 1% agarose gel electrophoresis and a NanoDrop spectrophotometer. Polyadenylated mRNA was purified from total RNA using oligo(dT) magnetic beads and Oligotex mRNA Kits (Qiagen). They were fragmented by treating with heat and divalent cations before cDNA synthesis. The cDNA was reverse transcribed with random hexamer primers, end repaired by DNA polymerase and adapter ligated with T4 DNA ligase, according to Illumina manufacturer’s protocol.
Ligated products were PCR-amplified and sequenced from both 5' and 3' ends on an Illumina HiSeq 2000 platform. Raw data of Illumina sequencing were obtained after base calling and stored in fastq format. Cleaning steps of the raw reads were as follows: (1) trimming adapter sequences; (2) removing the reads that contain ambiguous ‘N’ nucleotides over 10%; (3) filtering the reads with more than 50% bases having a quality score lower than 5. All subsequent analyses were based on the remaining clean reads.
De novo assembly of full-length transcripts (Figure 1) was performed with Trinity software (http://trinityrnaseq.sf.net), referring to the strategy of Grabherr et al [35]. In general, Trinity was combined of three independent software modules: Inchworm, Chrysalis and Butterfly. It segmented sequence data to many individual de Bruijn graphs (each represented transcriptional complexity for a given gene) and processed every graph independently to extract full-length splicing isoforms and to output transcripts from paralogous genes (Figure 1). The k-mer value was set to 25 during this period. If a component had more than one transcript, the longest one was selected to represent assembled component in order to eliminate redundancy. To assess coverage of this transcriptome data, the assembled unigene dataset was compared with EST dataset that was available from NCBI Genbank (http://www.ncbi.nlm.nih.gov/nucest/?term=Eriocheir sinensis) using Blast program with an E-value threshold of 1E-5.
(a) Inchworm assembles RNA-seq data by searching for paths in a k-mer graph, generating linear contigs with each k-mer presents only once in the contigs. (b) Chrysalis clusters contigs if they share at least one k−1-mer and if reads span the junction between contigs, and then constructs individual de Bruijn graphs from each cluster. (c) Butterfly takes each de Bruijn graph from Chrysalis, followed by trimming spurious edges and compacting linear paths. It then traces the graph with reads and pairs, ultimately reporting linear sequence for each splice form and teasing paralogous transcript apart.
Bioinformatics analysis and functional annotation
After being compared with NCBI EST dataset, transcriptomic dataset was analyzed using an established approach. Briefly, assembled unigenes were annotated using Blastx algorithm (E-value cut off: < 10-10) with public sequences in NCBI non-redundant protein (Nr), non-redundant nucleotide (Nt) databases (http://www.ncbi.nlm.nih.gov/), and UniProtKB/Swiss-Prot sequence database (http://www.ebi.ac.uk/uniprot/). Gene encoding protein domains were identified by searching against Protein Family (Pfam) database (http://pfam.janelia.org/) by means of hmmpfam program. Moreover, Gene Ontology (GO) (http://www.geneontology.org/) categorization was done with Blast2go program and WEGO software. Clusters of Orthologous Groups (COG) (http://www.ncbi.nlm.nih.gov/COG/) based analysis was then conducted to predict gene functions according to the known orthologous products. Using Enzyme Commission (EC) terms, biochemical pathway information was collected by downloading relevant maps from Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/). Both COG and KEGG classifications were also performed using Blast algorithm.
Gene discovery and SNP identification
Functional genes and molecular markers were deep investigated using the transcriptome data from all the zoea larvae. Presence and absence of immune relevant molecules were manually identified based on matched sequences in public databases [33]. For putative SNP detection, sequencing reads were mapped onto assembled unigenes with SOAPsnp software. Various parameters such as base quality score and read depth were optimized to identify final set of potential SNPs. Base quality score of ≥20 were set to assess the quality of reads at positions for SNP detection. Under the criteria of read depth of four and the minimum variant frequency of two, variations compared to the consensus sequence were counted as SNPs. Furthermore, they were considered statistically significant at a false discovery rate (FDR)/tested p-value <0.1.
Results
Transcriptome sequencing and assembly
Illumina sequencing-received raw data were deposited in NCBI short read archive database (accession number: SRA068379). Totally 46,099,408 raw reads were obtained from whole bodies of microbial challenged E. sinensis larvae (Table 1). After eliminating adapters, ambiguous nucleotides and low-quality sequences, 44,767,566 clean reads remained and they accumulated to be 4.52 Gb with a GC percentage of 47.00% (Table 1). Remaining clean reads were then assembled into 100,252 unigenes with a N50 length of 2,095 bp and an average size of 1,042 bp (Table 1). Assembled unigenes ranged from 201 bp to 19,357 bp and about half of them (51,156, 51.03%) were 200-500 bp in length (Figure 2). After elimination of repetition and short-length sequences, 65,535 non-redundant unigenes were selected for further analysis.
| Summary statistics | Number | |
|---|---|---|
| Total raw reads | 46,099,408 | |
| Total clean reads | 44,767,566 | |
| Total clean base pairs (Gb) | 4.52 | |
| Average length of clean reads (bp) | 100.97 | |
| GC percentage (%) | 47.00 | |
| Q20 percentage (%) | 97.70 | |
| Total number of unigenes | 100,252 | |
| Min-Max length of unigenes (bp) | 201-19,357 | |
| Average length of unigenes (bp) | 1,042 | |
| N50 of unigenes (bp) | 2,095 | |
| N90 of unigenes (bp) | 372 | |
Table 1. Overview of E. sinensis larvae transcriptome sequencing and assembly.
The x-axis indicates unigene size and the y-axis indicates number of unigenes of each size.
To evaluate coverage and abundance of this transcriptome data, assembled unigenes were compared against known EST sequences of E. sinensis. A total of 16,987 ESTs were downloaded from NCBI Genebank, of which 87.07% (14,790) were matched to transcriptome unigenes. However, only 9.49% (6,216 of 65,535) unigenes could be matched to NCBI ESTs (Table 2).
Unigene annotation
To estimate putative functions of them, non-redundant unigenes were subjected to public databases for Blast analysis. Approximately 17,097 unigenes, which took up a proportion of 26.09%, showed significant blast hits against known sequences in Nr database (Figure 3). E-value distribution of matched sequences revealed that almost half of them (49.92%, 8,534) had an E-value from 1E-10 to 1E-50, while 10.24% (1,751) with the E-value to be zero (Figure 4A). Moreover, 26.28% (4,493) of them had a 500 to 1,000 score during the alignment with other sequences in Nr database, while 24.20% (4,138) had a larger score than 1,000 (Figure 4B). Apart from matched unigenes, the other 48,438 unigenes had no blast hits with any protein sequences in Nr database.
(A) E-value distribution of annotated unigenes; (B) Score distribution of annotated unigenes.
In addition, 4,819 (7.35%) unigenes were annotated in Nt database and 14,481 (22.10%) in Swiss-Prot database (Figure 3). Unigenes were then tested by querying against Pfam database for homologous domains and motifs. The query results indicated that 21,603 (32.96%) unigenes encoded similar protein domains to other sequences, while encoding domains of the other 43,932 (67.04%) unigenes were not found in any sequences or any species (Figure 3).
Functional classification
Assembled non-redundant unigenes were also subjected to GO, COG and KEGG databases for blast searching. Summary statistics of them were shown in Figure 3.
GO is an international standardized gene functional classification system to comprehensively describe characteristics of different genes and their products. In this study, 23,188 unigenes were categorized by GO analysis (Figure 3). Second-level GO terms were applied to classify unigenes in terms of their involvement in three main categories (biological process, cellular component and molecular function) and each unigene was assigned at least one GO term. Twenty-six functional subcategories were grouped to biological process, among which ‘cellular process’ (23.31%) and ‘metabolic process’ (20.44%) contained the highest number of unigenes (Figure 5A). Seven subcategories were assigned into cellular component, of which ‘cell’ (29.88%) and ‘cell part’ (29.88%) were most dominant (Figure 5B). Seventeen subcategories were classified into molecular function category, among which the largest subcategory was ‘binding’ (41.59%) and ‘catalytic activity’ (30.00%) (Figure 5C).
(A) Biological process; (B) Cellular component; (C) Molecular function. Each annotated sequence is assigned at least one GO term. All data are presented on the basis of GO second level terms. Numbers refer to percentage of assigned unigenes in each category.
COG database is a database in which orthologous gene products are classified. To further evaluate the completeness of our transcriptome library and the effectiveness of the annotation process, annotation of COG were selected and 15,071 unigenes were clustered in different processes (Figure 3). Five largest of the 26 COG categories were ‘signal transduction mechanisms’ (3,035), ‘general function prediction only’ (2,661), ‘post-translational modification, protein turnover, chaperon’ (1,221), ‘cytoskeleton’ (1,157) and ‘transcription’ (1083), while the three smallest clusters were ‘coenzyme metabolism’ (98), ‘cell’ (25) and ‘unnamed protein’ (22) (Figure 6).
KEGG pathway-based analysis facilitated systematical study on complicated metabolic pathways and biological behaviors of functional molecules. Thousands of unigenes were consequently classified into specific pathways (Table 3), among which most fell into ‘human diseases’ (2,880) and ‘metabolism’ (2,451), followed by ‘organism system’ (2,084), ‘genetic information processing’ (1,762) and ‘cellular processes’ (1,244), while least were assigned to ‘environmental information processing’ (1,033). Predominant subcategories of all the pathways were ‘infectious diseases’ (1205), ‘signal transduction’ (807) and ‘translation’ (753).
| KEGG category | KEGG subcategory | No. of unigenes |
|---|---|---|
| Metabolism | Amino acid metabolism | 346 |
| Biosynthesis of other secondary metabolites | 38 | |
| Carbohydrate metabolism | 455 | |
| Energy metabolism | 229 | |
| Glycan biosynthesis and metabolism | 307 | |
| Lipid metabolism | 352 | |
| Metabolism of cofactors and vitamins | 151 | |
| Metabolism of other amino acids | 125 | |
| Metabolism of terpenoids and polyketides | 43 | |
| Nucleotide metabolism | 282 | |
| Xenobiotics biodegradation and metabolism | 123 | |
| Genetic information processing | Folding | 496 |
| Replication and repair | 284 | |
| Transcription | 229 | |
| Translation | 753 | |
| Environmental information processing | Membrane transport | 39 |
| Signal transduction | 807 | |
| Signaling molecules and interaction | 187 | |
| Cellular processes | Cell communication | 264 |
| Cell growth and death | 379 | |
| Cell motility | 99 | |
| Transport and catabolism | 502 | |
| Organismal systems | Circulatory System | 91 |
| Development | 105 | |
| Digestive System | 334 | |
| Endocrine System | 354 | |
| Environmental Adaptation | 36 | |
| Excretory System | 128 | |
| Immune System | 408 | |
| Nervous System | 548 | |
| Sensory System | 80 | |
| Human diseases | Cancers | 689 |
| Cardiovascular diseases | 133 | |
| Endocrine and metabolic diseases | 20 | |
| Immune diseases | 72 | |
| Infectious diseases | 1,205 | |
| Neurodegenerative diseases | 484 | |
| Substance dependence | 277 |
Table 3. KEGG assignment of non-redundant unigenes for E. sinensis larvae transcriptome.
Annotation of immune-relevant genes and pathways
Using the transcriptome data as references, immune relevant genes, metabolic and signaling pathways were analyzed to gain deep insight into immune system of the crab. As shown in Figure 6, 3,292 unigenes were classified into COG categories of ‘signal transduction mechanisms’ and ‘defense mechanisms’. About 1,402 unigenes were highly enriched in KEGG subcategories of ‘immune system’, ‘signal transduction’ and ‘signaling molecules and interaction’ (Table 3). These results indicated considerable immune and transduction-related genes that were associated with various known metabolic or pathways. Lots of functional molecules involved in multiple immune pathways were then analyzed.
Well-studied signaling pathways involved in innate immunity are Toll pathway and IMD pathway, which actively participate in anti-bacterial processes. In the study, we found many key components of the two pathways, referring to the knowledge in Drosophila melanogaster, shrimps and other relative species [36-38]. Members of Toll pathway were mainly composed of Toll receptor, Spatzle and the corresponding adaptors such as myeloid differentiation factor 88 (Myd88), Pelle, tumor necrosis factor receptor associated factor 6 (TRAF6), Cactus and Dorsal/ Dorsal-related immunity factor (Dif) (Figure 7, Table S1). Key adaptor proteins of IMD pathway included transforming growth factor beta–activated kinase dTAK1, inhibitor of nuclear factor kappa-B kinase (IKK), Dredd/Caspase and the related nuclear transcription factor Relish (Figure 7, Table S2). Via Toll and IMD pathways, these molecules may induce the expression of their downstream effectors, antimicrobial peptide (AMP) genes [36].
Putative Toll and IMD pathways of E. sinensis were constructed based on the knowledge in Drosophila, shrimps and other species. Purple square indicated proteins that were identified in microbial challenged E. sinensis larvae; and orange circle, not identified. Most interactions have to be confirmed experimentally.
Different members of Jak-Stat pathway and MAPK pathway were detected based on reference information of KEGG mapping. Major effectors involved in Jak-Stat pathway were cytokines, cytokine-receptors (CytokineR), JAK and STAT (Figure 8, Table S3). Their downstream regulatory molecules such as cytokine inducible SH2-containing protein (CIS), suppressor of cytokine signaling (SOCS), SH2-containing phosphatase, tyrosine-protein phosphatase non-receptor type 6 (SHP1), protein inhibitor of activated STAT (PIAS) and signal transducing adaptor molecule (STAM) were also detected (Table S3). In MAPK pathway, protein kinases could be grouped into three main families, including extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK) and p38/stress-activated protein kinase (p38/SAPK) (Figure 9, Table S4). We also found many other key members of the conserved protease cascades like MAPK kinase kinase kinase, MAPK kinase kinase/MEKK, MAPK kinase/MKK, and the activated transcription factors like p53, nuclear factor kappa-B (NF-κB), MAX protein and cyclic AMP-dependent transcription factor (ATF2) (Table S4). They may also play pivotal roles in many biological responses of mitten crab through putative Jak-Stat and MAPK pathways.
Putative JAK-STAT pathway of E. sinensis was constructed based on KEGG mapping. Purple square indicated proteins that were identified in microbial challenged E. sinensis larvae; and orange circle, not identified. Most interactions have to be confirmed experimentally.
Putative MAPK pathway of E. sinensis was constructed based on KEGG mapping. Purple square indicated proteins that were identified in microbial challenged E. sinensis larvae; and orange circle, not identified. Most interactions have to be confirmed experimentally.
SNP markers
Putative SNPs were screened following specific criteria according to base quality score, read depth and minor allele frequency (see Materials and Methods). With these criteria, 49,555 putative SNPs were identified from 13,039 assembled unigenes (Table 4), which were identified with the FDR/p-value of 0.1. Average frequency of the SNPs was one SNP for every 244 bp (or 0.41 SNP per 100 bp). The number of SNPs per unigene was highly variable from one to fifty-three. Among all unigenes with identified SNPs, up to 40.56% contained only one SNP (Figure 10A). About 56.12% unigenes were detected with two to fifteen SNPs per unigene, while only a few (3.31%) had more than 15 (Figure 10A). 32,085 of all the putative SNPs were transversions (Tv) and 17,470 were transitions (Ts), with a mean ratio (Tv:Ts) of 1.84:1.00 across the transcriptome (Figure 10B). A/G substitutions were frequent and accounted for 18.73% of all SNPs (Figure 10B).
| Description | Number |
|---|---|
| Unigenes with SNPs | 13,309 |
| Total SNPs | 49,555 |
| Transitions | 14,470 |
| Transversions | 32,085 |
| bp/SNP | 244 |
| Average depth in SNP position (min-max) | 614.60 (11-22276) |
Table 4. Summary description of putative SNPs identified from E. sinensis larvae transcriptome.
(A) Number of SNPs distributed per unigene; (B) Classification of different substitution types of SNPs.
To analyze sequence variants of immune genes, 176 candidate SNPs from 38 unigenes were found to be involved with the four mentioned immune pathways (Table 5). The number of SNPs in every unigene ranged from one to 46 and most unigenes had only one SNP. Among all the 38 unigenes, Spatzle was found to contain largest number of SNPs, followed by cell division control protein 42/Ras-related C3 botulinum toxin substrate 1(cdc42/Rac), growth factor receptor-binding protein 2 (GRB2) and tumor protein P53 (Table 5).
| Gene category | Unigene component | No. of SNPs |
|---|---|---|
| Spatzle | comp33625_c0 | 14 |
| comp37644_c0 | 46 | |
| Toll | comp44024_c0 | 1 |
| comp45455_c0 | 3 | |
| Pelle | comp35625_c0 | 3 |
| Relish | comp43492_c2 | 4 |
| comp43492_c3 | 6 | |
| Jak | comp42519_c2 | 4 |
| Cyclin D | comp42339_c0 | 2 |
| PI3K | comp419368_c0 | 1 |
| Akt | comp43162_c2 | 1 |
| CBP | comp45257_c2 | 1 |
| SOCS | comp29409_c0 | 1 |
| Spred | comp42402_c2 | 6 |
| CACN | comp40211_c0 | 1 |
| comp42200_c0 | 5 | |
| EGFR | comp45184_c1 | 1 |
| FGFR | comp39916_c0 | 1 |
| GRB2 | comp41990_c6 | 16 |
| Ras | comp43121_c0 | 1 |
| p120GAP | comp41773_c0 | 1 |
| NF1 | comp45632_c0 | 7 |
| comp45632_c1 | 2 | |
| ERK | comp36917_c0 | 4 |
| PTP | comp27866_c0 | 1 |
| MKP | comp36734_c1 | 1 |
| STMN1 | comp42386_c1 | 1 |
| RSK2 | comp43663_c1 | 1 |
| PPP3C | comp33500_c0 | 1 |
| FASL | comp44048_c0 | 1 |
| DAXX | comp37820_c0 | 1 |
| ECSIT | comp42144_c1 | 3 |
| cdc42/Rac | comp103709_c0 | 17 |
| comp39531_c0 | 1 | |
| MKK4 | comp38478_c0 | 1 |
| P53 | comp44289_c7 | 10 |
| comp45072_c0 | 2 | |
| ATF2 | comp44533_c0 | 3 |
Table 5. List of 176 SNPs in 38 immune pathway-related unigenes.
Discussion
Knowledge of genetic information is essential for aquaculture management and sustainable development of crustacean fisheries. However, only genome of Daphnia pulex is sequenced in Crustacea [39]. Lack of fully sequenced genome not only limits genetic resources of crustacean, but also hampers researches on gene expression and the regulations. Fortunately, with development of EST method and high-throughput sequencing technology, some genes have been revealed from transcriptome analyses of the important crustaceans like E. sinensis. In this study, whole bodies of E. sinensis larvae after microbial challenge are used for the first time to analyze E. sinensis transcriptome and discover immune functional genes.
Previous transcriptome studies of E. sinensis have been performed from single organ and tissue of the crab [3,5,33,40-43]. Differently, our study covers all tissues of E. sinensis larvae and contains fuller transcriptional genes of the organism. It largely enriches transcriptional sources of mitten crab. Transcriptome data is known to be the completed RNA transcripts in a cell. Characterization of transcriptome is important to explain functional complexity of genome and to understand cell activities like growth, development, disease and immune response [44]. Therefore, our report offers a general view on gene background and immune system of the crab.
In detail, many ESTs are obtained from tissues like testis, haemocyte and hepatopancreas of E. sinensis by Sanger sequencing approach [3,5,40] and they all have been submitted to NCBI. Our analysis shows that only 12.93% NCBI ESTs could not be matched to transcriptome unigenes of E. sinensis larvae, while up to 90.51% unigenes could not matched to NCBI ESTs of E. sinensis. It implies deep coverage of E. sinensis larval transcriptome and supplies considerable gene resources of the crab. In comparison, 60.1% NCBI ESTs from muscle, blood, hepatopancreas and other organs of L. vannamei are matched to transcriptome unigenes in L. vannamei larvae, whereas 85.8% of larvae unigenes are not matched to NCBI ESTs [28]. Our results are similar with the report of L. vannamei and greatly enrich transcriptional data of important economic crustaceans. Additionally, Pfam searching of protein homologous domain/motif shows many genes without blast hits in any species. It will be helpful to explore new sequences and study on them, such as molecular characterization, sequence structure analysis, expression pattern analysis and biological activity test.
The research shows that infection with various microbes, including Gram-positive bacteria Micrococcus luteus, Gram-negative bacteria Vibrio alginolyticus and fungi Pichia pastoris, can help to acquire abundant information of immune genes. A considerable amount of genes relating to Toll, IMD, JAK-STAT and MAPK pathways are fully and systematically characterized in our study. Most genes are also detected in infected Fenneropenaeus chinensis pleopod and E. sinensis hepatopancreas [29,33]. Those pathways and genes play important roles in signal transduction, immune defense and other responses [33]. Hence, the study serves a good idea to identify functional genes and understand host immunity mechanism in crustacean at whole transcriptome level.
Comparing with previous transcriptome data of E. sinensis [33], several molecules like TRAF6, fibroblast growth factor (FGF), protein tyrosine phosphatase (PTP) and JNK-interacting protein 1 (JIP1) are first found of existence in this study. TRAF6 is even detected in crab for the first time. It is the only molecule of TRAF family that functions as signal transducer for tumor necrosis factor receptor (TNFR) and interleukin-1 receptor (IL-1R)/Toll-like receptor (TLR) families [45]. It is also reported to be important in antibacterial and antiviral responses through immune pathways [45,46]. As expected, we find that expression of TRAF6 is involved in both Toll and MAPK signaling pathways of E. sinensis larvae. Moreover, the molecule is recently characterized to be a new STAT3 interactor and negatively regulate activation of JAK-STAT signaling pathway [47]. All the findings imply that TRAF6 has crucial and complicated role in immune system. In addition, several molecules like Tube, IMD and Dredd were not found in this transcriptome analysis. Fortunately, researches reveal that deep sequencing (such as de novo sequencing and resequencing) of the genome offers another strategy to find candidate functional genes [48,49]. With development of genome sequencing in crab, we may make further efforts to identify those genes.
In this analysis, although high data output is produced, only a few unigenes have blast hits in public databases. Sequences that are not definitively annotated possibly represent genes of unknown functions in E. sinensis. Alternatively, it may be because of the complicated gene background of Eriocheir species or other crustaceans and their limited sequence information. Besides, there might be some differences on gene sequences of the crab and other animal species. Considering these, it is quite common that many unigenes cannot be matched. With more crab genetic information being studied and high-throughput sequencing data being applied, sequences obtained in the study will be further annotated and characterized.
Potential genes and pathways are also annotated in other larval transcriptome researches of arthropod species, including G. mellonella [32], Bactrocera dorsalis [50] and Spodoptera exigua [51]. The pathways are quite similar in different arthropods, which finally activate expression of AMPs and other proteins through interacting with NF-κB factors. Combing these similar reports in arthropod, annotated information is worthy of in-depth characterizing, which will facilitate researches on genetics, gene expression and regulation of whole bodies of their larvae.
Another important application of high-throughput sequencing technology is to identify genetic variants. It has been well established and demonstrated using Illumina technique to detect SNP mutations [52-54]. Our large-scale sequencing effort reveals lots of SNPs in E. sinensis larval transcriptome sequences. In the analysis, SNP types of A/G and C/T are quite common and SNP densities vary among different genes. It may be partly due to the relative functional importance of individual genes and the effects of selection [55]. Discovery of 49,555 SNPs, especially the 13,039 SNPs from immune pathway related genes, will therefore provide a valuable resource of candidate markers for future selective breeding of E. sinensis.
Many SNPs are also derived in other crustacean species with EST sequences through traditional sequencing method [54,56]. Both of the EST-SNP and high-throughput sequencing-derived SNP may lead to different alterations in amino acids and promote marker development of cultured crustaceans. However, total number of SNPs yielded in this study are much more than that of EST-derived SNPs in other crustacean studies [54,56]. It suggests high efficiency of high-throughput transcriptome analysis to gain SNP markers. In addition, our study is consistent with the report of catfish transcriptome that most unigenes had only one SNP [52]. It shows that most common genes have the same SNP density. However, Spatzle gene is found with largest number of SNPs in this study. Previous researches implies that Spatzle plays crucial role in recognizing pathogen associated molecular patterns and activating Toll receptor to initiate Toll pathway [57,58]. Application of these SNPs in Spatzle may be of great value in regulating signal transduction and antibacterial response of the crab.
Conclusion
High-throughput sequencing technology offers a powerful approach to analyze gene expression and SNP markers in genome reference-free organisms. Using Illumina platform and de novo assembly technique, we have derived a dataset from whole bodies of E. sinensis larvae after microbial challenge. This data comprised 44,767,566 clean reads and 100,252 assembled unigenes. Enormous functional genes are detected to be related with multiple immune pathways, including Toll, IMD, JAK-STAT and MAPK pathways. Some important genes, including TRAF6, FGF, PTP and JIP1, are identified in E. sinensis for the first time. Particularly, TRAF6 is even first found of existence in crabs. 49,555 putative SNPs are also identified from the transcriptome data, which are useful to marker assisted selection of new strains in E. sinensis. Collectively, this is the first transcriptome report of microbial challenged E. sinensis larvae and it will provide valuable data to research immune mechanism and molecular biological of the crab.
Supporting Information
Table S1.
Putative immune genes involved in Toll pathway of E. sinensis larvae.
https://doi.org/10.1371/journal.pone.0082156.s001
(DOC)
Table S2.
Putative immune genes involved in IMD pathway of E. sinensis larvae.
https://doi.org/10.1371/journal.pone.0082156.s002
(DOC)
Table S3.
Putative immune genes involved in JAK-STAT pathway of E. sinensis larvae.
https://doi.org/10.1371/journal.pone.0082156.s003
(DOC)
Table S4.
Putative immune genes involved in MAPK pathway of E. sinensis larvae.
https://doi.org/10.1371/journal.pone.0082156.s004
(DOC)
Acknowledgments
We thank Beijing Novogene Bioinformatics Technology Co., Ltd. (Beijing, China) for Illumina transcriptome sequencing and primitive data analysis.
Author Contributions
Conceived and designed the experiments: ZC. Performed the experiments: XL Y. Liu CS GS DL Y. Li. Analyzed the data: XL CS. Wrote the manuscript: ZC XL MH.
References
- 1. Rudnick DA, Hieb K, Grimmer KF, Resh VH (2003) Patterns and processes of biological invasion: The Chinese mitten crab in San Francisco Bay. Basic and Applied Ecology 4: 249-262. doi:https://doi.org/10.1078/1439-1791-00152.
- 2. Montu M, Anger K, deBakker C (1996) Larval development of the Chinese mitten crab Eriocheir sinensis H Milne-Edwards (Decapoda：Grapsidae) reared in the laboratory. Helgolander Meeresuntersuchungen 50: 223-252. doi:https://doi.org/10.1007/BF02367153.
- 3. Jiang H, Yin Y, Zhang X, Hu S, Wang Q (2009) Chasing relationships between nutrition and reproduction: A comparative transcriptome analysis of hepatopancreas and testis from Eriocheir sinensis. Comp Biochem Physiol Part D Genomics Proteomics 4: 227-234. doi:https://doi.org/10.1016/j.cbd.2009.05.001. PubMed: 20403758.
- 4. Zheng Y, Fang H (1998) Technique for Prevention and Treatment of Common Disease in Seed —rearing of River Crab. Shandong Fisheries 15: 31-34.
- 5. Jiang H, Cai YM, Chen LQ, Zhang XW, Hu SN et al. (2009) Functional annotation and analysis of expressed sequence tags from the hepatopancreas of mitten crab (Eriocheir sinensis). Mar Biotechnol (NY) 11: 317-326. doi:https://doi.org/10.1007/s10126-008-9146-1. PubMed: 18815839.
- 6. Zhao D, Song S, Wang Q, Zhang X, Hu S et al. (2009) Discovery of immune-related genes in Chinese mitten crab (Eriocheir sinensis) by expressed sequence tag analysis of haemocytes. Aquaculture 287: 297-303. doi:https://doi.org/10.1016/j.aquaculture.2008.10.050.
- 7. Mu C, Zheng P, Zhao J, Wang L, Qiu L et al. (2011) A novel type III crustin (CrusEs2) identified from Chinese mitten crab Eriocheir sinensis. Fish and Shellfish Immunol 31: 142-147.
- 8. Mu C, Zhao J, Wang L, Song L, Song X et al. (2009) A thioredoxin with antioxidant activity identified from Eriocheir sinensis. Fish Shellfish Immunol 26: 716-723. doi:https://doi.org/10.1016/j.fsi.2009.02.024. PubMed: 19269333.
- 9. Mu C, Zhao J, Wang L, Song L, Zhang H et al. (2009) Molecular cloning and characterization of peroxiredoxin 6 from Chinese mitten crab Eriocheir sinensis. Fish Shellfish Immunol 26: 821-827. PubMed: 18992822.
- 10. Meng Q, Du J, Yao W, Xiu Y, Li Y et al. (2011) An extracellular copper/zinc superoxide dismutase (ecCuZnSOD) from Chinese mitten crab, Eriocheir sinensis and its relationship with Spiroplasma eriocheiris. Aquaculture 320: 56-61. doi:https://doi.org/10.1016/j.aquaculture.2011.08.014.
- 11. Li C, Zhao J, Song L, Mu C, Zhang H et al. (2008) Molecular cloning, genomic organization and functional analysis of an anti-lipopolysaccharide factor from Chinese mitten crab Eriocheir sinensis. Dev Comp Immunol 32: 784-794. doi:https://doi.org/10.1016/j.dci.2007.11.008. PubMed: 18206230.
- 12. Zhang Y, Wang L, Wang L, Yang J, Gai Y et al. (2010) The second anti-lipopolysaccharide factor (EsALF-2) with antimicrobial activity from Eriocheir sinensis. Dev Comp Immunol 34: 945-952. doi:https://doi.org/10.1016/j.dci.2010.04.002. PubMed: 20416335.
- 13. Wang L, Zhang Y, Wang L, Yang J, Zhou Z et al. (2011) A new anti-lipopolysaccharide factor (EsALF-3) from Eriocheir sinensis with antimicrobial activity. African Journal of Biotechnology 10: 17678-17689.
- 14. Gai Y, Zhao J, Song L, Li C, Zheng P et al. (2008) A prophenoloxidase from the Chinese mitten crab Eriocheir sinensis: Gene cloning, expression and activity analysis. Fish and Shellfish Immunology 24: 156-167.
- 15. Gai Y, Qiu L, Wang L, Song L, Mu C et al. (2009) A clip domain serine protease (cSP) from the Chinese mitten crab Eriocheir sinensis: cDNA characterization and mRNA expression. Fish and Shellfish Immunol 27: 670-677.
- 16. Qin C, Chen L, Qin JG, Zhao D, Zhang H et al. (2010) Characterization of a serine proteinase homologous (SPH) in Chinese mitten crab Eriocheir sinensis. Dev Comp Immunol 34: 14-18. doi:https://doi.org/10.1016/j.dci.2009.08.006. PubMed: 19720078.
- 17. Ekblom R, Galindo J (2011) Applications of next generation sequencing in molecular ecology of non-model organisms. Heredity (Edinb) 107: 1-15. doi:https://doi.org/10.1038/hdy.2010.152. PubMed: 21139633.
- 18. Cahais V, Gayral P, Tsagkogeorga G, Melo-Ferreira J, Ballenghien M et al. (2012) Reference-free transcriptome assembly in non-model animals from next-generation sequencing data. Mol Ecol Resour 12: 834-845. doi:https://doi.org/10.1111/j.1755-0998.2012.03148.x. PubMed: 22540679.
- 19. Pereiro P, Balseiro P, Romero A, Dios S, Forn-Cuni G et al. (2012) High-Throughput Sequence Analysis of Turbot (Scophthalmus maximus) Transcriptome Using 454-Pyrosequencing for the Discovery of Antiviral Immune Genes. PLOS ONE 7: e35369. doi:https://doi.org/10.1371/journal.pone.0035369. PubMed: 22629298.
- 20. Zhang Y, Zhang S, Han S, Li X, Qi L (2012) Transcriptome profiling and in silico analysis of somatic embryos in Japanese larch (Larix leptolepis). Plant Cell Rep 31: 1637-1657. doi:https://doi.org/10.1007/s00299-012-1277-1. PubMed: 22622308.
- 21. Sun L, Chen M, Yang H, Wang T, Liu B et al. (2011) Large scale gene expression profiling during intestine and body wall regeneration in the sea cucumber Apostichopus japonicus. Comp Biochem Physiol Part D Genomics Proteomics 6: 195-205. doi:https://doi.org/10.1016/j.cbd.2011.03.002. PubMed: 21501978.
- 22. Zhang F, Guo H, Zheng H, Zhou T, Zhou Y et al. (2010) Massively parallel pyrosequencing-based transcriptome analyses of small brown planthopper (Laodelphax striatellus), a vector insect transmitting rice stripe virus (RSV). BMC Genomics 11: 303. doi:https://doi.org/10.1186/1471-2164-11-303. PubMed: 20462456.
- 23. Gavery MR, Roberts SB (2012) Characterizing short read sequencing for gene discovery and RNA-Seq analysis in Crassostrea gigas. Comp Biochem Physiol Part D Genomics Proteomics 7: 94-99. doi:https://doi.org/10.1016/j.cbd.2011.12.003. PubMed: 22244882.
- 24. Shendure J, Ji H (2008) Next-generation DNA sequencing. Nat Biotechnol 26: 1135-1145. doi:https://doi.org/10.1038/nbt1486. PubMed: 18846087.
- 25. Sun X, Zhou S, Meng F, Liu S (2012) De novo assembly and characterization of the garlic (Allium sativum) bud transcriptome by Illumina sequencing. Plant Cell Rep 31: 1823-1828. doi:https://doi.org/10.1007/s00299-012-1295-z. PubMed: 22684307.
- 26. Robinson N, Sahoo PK, Baranski M, Mahapatra KD, Saha JN et al. (2012) Expressed Sequences and Polymorphisms in Rohu Carp (Labeo rohita, Hamilton) Revealed by mRNA-seq. Mar Biotechnol (NY) 14: 620–633. doi:https://doi.org/10.1007/s10126-012-9433-8. PubMed: 22298294.
- 27. Hsu JC, Chien TY, Hu CC, Chen MJ, Wu WJ et al. (2012) Discovery of Genes Related to Insecticide Resistance in Bactrocera dorsalis by Functional Genomic Analysis of a De Novo Assembled Transcriptome. PLOS ONE 7: e40950. doi:https://doi.org/10.1371/journal.pone.0040950. PubMed: 22879883.
- 28. Li C, Weng S, Chen Y, Yu X, Lu L et al. (2012) Analysis of Litopenaeus vannamei Transcriptome using the Next-Generation DNA Sequencing. Technique - PLOS ONE 7: e47442. doi:https://doi.org/10.1371/journal.pone.0047442.
- 29. Li S, Zhang X, Sun Z, Li F, Xiang J (2013) Transcriptome Analysis on Chinese Shrimp Fenneropenaeus chinensis during WSSV Acute. Infection - PLOS ONE 8: e58627. doi:https://doi.org/10.1371/journal.pone.0058627.
- 30. Liu F, Tang T, Sun L, Jose Priya TA (2012) Transcriptomic analysis of the housefly (Musca domestica) larva using massively parallel pyrosequencing. Mol Biol Rep 39: 1927-1934. doi:https://doi.org/10.1007/s11033-011-0939-3. PubMed: 21643958.
- 31. Vogel H, Altincicek B, Glöckner G, Vilcinskas A (2011) A comprehensive transcriptome and immune-gene repertoire of the lepidopteran model host Galleria mellonella. BMC Genomics 12: 308. doi:https://doi.org/10.1186/1471-2164-12-308. PubMed: 21663692.
- 32. Wang ZL, Liu TT, Huang ZY, Wu XB, Yan WY et al. (2012) Transcriptome Analysis of the Asian Honey Bee Apis cerana cerana. PLOS ONE 7: e47954. doi:https://doi.org/10.1371/journal.pone.0047954. PubMed: 23112877.
- 33. Li X, Cui Z, Liu Y, Song C, Shi G (2013) Transcriptome analysis and discovery of genes involved in immune pathways from hepatopancreas of microbial challenged mitten crab Eriocheir sinensis. PLOS ONE 8: e68233. doi:https://doi.org/10.1371/journal.pone.0068233. PubMed: 23874555.
- 34. Sui L, Cai J, Sun H, Wille M, Bossier P (2012) Effect of poly-beta-hydroxybutyrate on Chinese mitten crab, Eriocheir sinensis, larvae challenged with pathogenic Vibrio anguillarum. J Fish Dis 35: 359-364. doi:https://doi.org/10.1111/j.1365-2761.2012.01351.x. PubMed: 22417317.
- 35. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA et al. (2011) Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol 29: 644-652. doi:https://doi.org/10.1038/nbt.1883. PubMed: 21572440.
- 36. Akira S, Uematsu S, Takeuchi O (2006) Pathogen Recognition and Innate Immunity. Cell 124: 783-801. doi:https://doi.org/10.1016/j.cell.2006.02.015. PubMed: 16497588.
- 37. Wang PH, Gu ZH, Wan DH, Zhang MY, Weng SP et al. (2011) The Shrimp NF-κB Pathway Is Activated by White Spot Syndrome Virus (WSSV) 449 to Facilitate the Expression of WSSV069 (ie1), WSSV303 and WSSV371. PLOS ONE 6(9): e24773. doi:https://doi.org/10.1371/journal.pone.0024773. PubMed: 21931849.
- 38. Li F, Yan H, Wang D, Priya TA, Li S et al. (2009) Identification of a novel relish homolog in Chinese shrimp Fenneropenaeus chinensis and its function in regulating the transcription of antimicrobial peptides. Dev Comp Immunol 33: 1093-1101. doi:https://doi.org/10.1016/j.dci.2009.06.001. PubMed: 19520110.
- 39. Colbourne JK, Pfrender ME, Gilbert D, Thomas WK, Tucker A et al. (2011) The ecoresponsive genome of Daphnia pulex. Science 331: 555-561. doi:https://doi.org/10.1126/science.1197761. PubMed: 21292972.
- 40. Zhang W, Wan H, Jiang H, Zhao Y, Zhang X et al. (2011) A transcriptome analysis of mitten crab testes (Eriocheir sinensis). Genet Mol Biol 34: 136-141. doi:https://doi.org/10.1590/S1415-47572010005000099. PubMed: 21637557.
- 41. He L, Wang Q, Jin X, Wang Y, Chen L et al. (2012) Transcriptome profiling of testis during sexual maturation stages in Eriocheir sinensis using Illumina sequencing. PLOS ONE 7: e33735. doi:https://doi.org/10.1371/journal.pone.0033735. PubMed: 22442720.
- 42. Ou J, Meng Q, Li Y, Xiu Y, Du J et al. (2012) Identification and comparative analysis of the Eriocheir sinensis microRNA transcriptome response to Spiroplasma eriocheiris infection using a deep sequencing approach. Fish Shellfish Immunol 32: 345-352. PubMed: 22166732.
- 43. He L, Jiang H, Cao D, Liu L, Hu S et al. (2013) Comparative Transcriptome Analysis of the Accessory Sex Gland and Testis from the Chinese Mitten Crab (Eriocheir sinensis). PLOS ONE 8(1): e53915. doi:https://doi.org/10.1371/journal.pone.0053915. PubMed: 23342039.
- 44. Xiang LX, He D, Dong WR, Zhang YW, Shao JZ (2010) Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish. BMC Genomics 11: 472. doi:https://doi.org/10.1186/1471-2164-11-472. PubMed: 20707909.
- 45. Yuan S, Liu T, Huang S, Wu T, Huang L et al. (2009) Genomic and functional uniqueness of the TNF receptor-associated factor gene family in amphioxus, the basal chordate. J Immunol 183: 4560-4568. doi:https://doi.org/10.4049/jimmunol.0901537. PubMed: 19752230.
- 46. Wang PH, Wan DH, Gu ZH, Deng XX, Weng SP et al. (2011) Litopenaeus vannamei tumor necrosis factor receptor-associated factor 6 (TRAF6) responds to Vibrio alginolyticus and white spot syndrome virus (WSSV) infection and activates antimicrobial peptide genes. Dev Comp Immunol 35: 105-114. doi:https://doi.org/10.1016/j.dci.2010.08.013. PubMed: 20816892.
- 47. Wei J, Yuan Y, Jin C, Chen H, Leng L et al. (2012) The ubiquitin ligase TRAF6 negatively regulates the JAK-STAT signaling pathway by binding to STAT3 and mediating its ubiquitination. PLOS ONE 7: e49567. doi:https://doi.org/10.1371/journal.pone.0049567. PubMed: 23185365.
- 48. Kurokawa S, Kabayama J, Hwang SD, Nho SW, Hikima J et al. (2013) Comparative Genome Analysis of Fish and Human Isolates of Mycobacterium marinum. Mar Biotechnol (NY) 15: 596-605. doi:https://doi.org/10.1007/s10126-013-9511-6. PubMed: 23728847.
- 49. Deák T, Kupi T, Oláh R, Lakatos L, Kemény L et al. (2013) Candidate plant gene homologues in grapevine involved in Agrobacterium transformation. Central European. Journal of Biology 8: 1001-1009.
- 50. Zheng W, Peng T, He W, Zhang H (2012) High-Throughput Sequencing to Reveal Genes Involved in Reproduction and Development in Bactrocera dorsalis (Diptera_ Tephritidae). PLOS ONE 7: e36463. doi:https://doi.org/10.1371/journal.pone.0036463. PubMed: 22570719.
- 51. Pascual L, Jakubowska AK, Blanca JM, Cañizares J, Ferré J et al. (2012) The transcriptome of Spodoptera exigua larvae exposed to different types of microbes. Insect Biochem Mol Biol 42: 557-570. doi:https://doi.org/10.1016/j.ibmb.2012.04.003. PubMed: 22564783.
- 52. Liu S, Zhou Z, Lu J, Sun F, Wang S et al. (2011) Generation of genome-scale gene-associated SNPs in catfish for the construction of a high-density SNP array. BMC Genomics 12: 53. doi:https://doi.org/10.1186/1471-2164-12-53. PubMed: 21255432.
- 53. Lu T, Lu G, Fan D, Zhu C, Li W et al. (2010) Function annotation of the rice transcriptome at single-nucleotide resolution by RNA-seq. Genome Res 20: 1238-1249. doi:https://doi.org/10.1101/gr.106120.110. PubMed: 20627892.
- 54. Sze SH, Dunham JP, Carey B, Chang PL, Li F et al. (2012) A de novo transcriptome assembly of Lucilia sericata (Diptera: Calliphoridae) with predicted alternative splices, single nucleotide polymorphisms and transcript expression estimates. Insect Mol Biol 21: 205-221. doi:https://doi.org/10.1111/j.1365-2583.2011.01127.x. PubMed: 22283785.
- 55. Jung H, Lyons RE, Dinh H, Hurwood DA, McWilliam S et al. (2011) Transcriptomics of a Giant Freshwater Prawn (Macrobrachium rosenbergii): De Novo Assembly, Annotation and Marker Discovery. PLOS ONE 6: e27938. doi:https://doi.org/10.1371/journal.pone.0027938. PubMed: 22174756.
- 56. Liu C, Wang X, Xiang J, Li F (2012) EST-derived SNP discovery and selective pressure analysis in Pacific white shrimp (Litopenaeus vannamei). Chinese Journal of Oceanology and Limnology 30: 713-723. doi:https://doi.org/10.1007/s00343-012-1252-2.
- 57. Zheng LP, Hou L, Yu M, Li X, Zou XY (2012) Cloning and the expression pattern of Spa¨tzle gene during embryonic development and bacterial challenge in Artemia sinica. Mol Biol Rep 39: 6035–6042. doi:https://doi.org/10.1007/s11033-011-1417-7. PubMed: 22203485.
- 58. Wang PH, Liang JP, Gu ZH, Wan DH, Weng SP et al. (2012) Molecular cloning, characterization and expression analysis of two novel Tolls (LvToll2 and LvToll3) and three putative Spatzle-like Toll ligands (LvSpz1-3) from Litopenaeus vannamei. Dev Comp Immunol 36: 359-371. doi:https://doi.org/10.1016/j.dci.2011.07.007. PubMed: 21827783.