Abstract
Eriocheir sinensis larva normally experiences 11 stages. The reduced abdomen folded beneath the thorax is the most prominent characteristic of morphological alteration from megalopa to juvenile crab. Up to date, the molecular mechanisms of brachyurization remain a mystery. Here, transcriptome library, digital gene expression (DGE) libraries and proteome libraries at two developmental stages [the megalopa stage of E. sinensis (stage M) and the first stage of juvenile crab (stage J1)] of the Chinese mitten crab larva were constructed for RNA sequencing and iTRAQ approaches followed by bioinformatics analysis, respectively. In total, 1106 genes and 871 proteins were differentially expressed between the stage M and stage J1. Moreover, several important pathways were identified, including biosynthesis of secondary metabolites, metabolic pathways, focal adhesion, and some disease pathways. Besides, muscle contraction, oxidative phosphorylation, calcium signaling, PI3K-Akt, DNA replication pathway, and integrin signaling pathway also had important functions in brachyurization process. Furthermore, the components, actin, actin-related protein, collagens, filamin-A/B, laminin, integrins, paxillin, and fibronectin had up-regulated expression levels in M stage compared to J1 stage.
Keywords: Eriocheir sinensis, Brachyurization, Transcriptome, Proteome, Digital gene expression
1. Introduction
The brachyuran decapod crustaceans are characterized by a reduced abdomen folded beneath the cephalothorax, and inserted in a special cavity or between the pereiopods in the early developmental process, called brachyurization metamorphosis [1]. The Chinese mitten crab (Eriocheir sinensis), a brachyuran decapod crab species, is distributed in eastern and northern China. Up to now, the molecular mechanisms of brachyurization development in brachyuran decapods are still unclarified.
The high-throughput sequencing approaches, including Illumina RNA-seq, iTRAQ and digital gene expression (DGE), are newly developed tools for omics perspective at the transcriptomic and posttranslational levels. Transcriptome and DGE can be used to identify candidate genes that regulate the developmental process of brachyurization [2], while proteome may provide strategy to examine specific physiological response at the protein levels [3]. Numerous studies have been performed to identify a certain class of molecules in E. sinensis, such as reproductive and embryo development [4,5,6], immunoreaction [7,8], eyestalk ablation [9], osmoregulation and stress adaption [10], brachyurization and adaptation to benthic lifestyle [2], metamorphosis and nutrition metabolism [11,12], immune-related miRNAs [13], etc. Although brachyurization has become perspicuous and intelligible in morphological changing processes, the molecular mechanisms of brachyurization in brachyuran crabs remain elusive and obscure. Hence, this study aimed to investigate brachyurization-associated genes and proteins in E. sinensis via transcriptome, proteome and DGE analyses.
Here, the unigenes and proteins identified from the larvae of E. sinensis through transcriptome, proteome, and DGE sequencing approaches were analyzed by bioinformatics approaches. Approximately 4 billion high-quality nucleotide sequences were generated by Illumina technology. Overall, 76,112 unigenes were obtained in a single run, and then assembled into 187,504 distinct contiguous sequences. Then, ten DGE libraries were established, and the differences in gene expression patterns between two developmental stages of E. sinensis were compared using a DGE system. Furthermore, the transcriptome sequences, proteome sequences and DGE profiles can be valuable resources for identifying the genes and proteins responsible for brachyurization in E. sinensis.
2. Materials and methods
2.1. Total RNA extraction, cDNA library construction and illumina sequencing and data analysis
RNeasy Mini Kit (Qiagen, Germany) was utilized to isolate total RNA from the whole Chinese mitten crab larvae at two developmental stages (stage M: the megalopa stage; stage J1: the first stage of juvenile crab). Briefly, total RNA was extracted from E. sinensis in accordance with the kit's instructions. mRNA was purified from total mixture RNA using the Oligo (dT) magnetic beads at an equal ratio of stage M and stage J1. Poly(A) mRNA was extracted with OligoTex mRNA mini kit (Qiagen). Then, mRNA was cut into short fragments (100–400 bp) with Fragmentation buffer. After 2% TAE-agarose gel electrophoresis, different fragments (200 ± 25 bp) were chosen and excised for PCR amplification as a template. cDNA was synthetized with SuperScript Double-Stranded cDNA Synthesis kit (Invitrogen, USA). High-throughput sequencing was performed using the Illumina HiSeq™ 2000 at the Beijing Genomics Institute (BGI; Shenzhen, Shenzhen, China).
Raw data were firstly processed by removing low-quality reads, reads containing ploy-N and reads containing adapter via in-house perl scripts. Meanwhile, Q20 (the proportion of bases with a quality score >20), sequence duplication level and GC-content of the clean reads were determined. The downstream analysis was conducted according to the high-quality clean data. Trinity was used to perform transcriptome assembly [14] by default parameter set. The contigs were the longest assembled sequences. To determine contigs from the same transcript and the distance between these contigs, the reads were mapped to the paired-end reads-containing contigs. Finally, the contigs without Ns and ability to extend on both ends were regarded as Unigenes. Gene annotation was performed using the following databases: Nr, Nt, KO/COG, PFAM, KO, GO, and Swiss-Prot.
RSEM was used to estimate gene expression levels [15]. Differential expression analysis was carried out using the DESeq R package v1.10.1 [[16], [17]]. Differential expression was calculated from DGE data by DESeq using a negative binomial distribution-based model. To control false discovery rate (FDR), the obtained P-values were adjusted using the Benjamini and Hochberg's method. Genes (an adjusted P < 0.05) determined by DESeq were defined as differentially expressed genes (DEGs). RT-PCR was employed to examine the expression levels of genes in triplicate specimens.
2.2. Protein isolation, digestion and sequencing
Tissues from stage M and stage J1 (triplicate biological specimens per group) were ground to powder in liquid nitrogen. The methods of protein extraction and digestion were in accordance with the general instruction manual. Briefly, the powder was resuspended in lysis buffer and added with PMSF and EDTA to the final concentrations of 1 and 2 mM, respectively. After mixing, the specimens were added with dithiothreitol (DTT) to a final concentration of 10 mM, followed by sonication at 200 W for 15 min. The extracted proteins were digested with Trypsin Gold at the protein: trypsin ratio of 20:1 for 4 h at 37 °C. After trypsinization, the peptides were dried using a centrifugal vacuum. The peptides were were then labeled using an iTRAQ Reagent 8-plex Kit. Fractionation of the iTRAQ-labeled peptides was conducted by SCX chromatography using a Shimadzu LC-20AB HPLC Pump system. Then, ProteinPilot V4.5 was used for peptide identification according to the paragon parameters. Further filtration was performed based on the unused score to verify the results of ProteinPilot. The peptides with unused score ≥1.3 were selected, in order to ensure a reliability level of over 95%. The filtrated proteins were subjected to further analyses.
2.3. DGE library construction and sequencing
Illumina Gene Expression Sample Prep Kit was utilized to construct the tag library of stage M and stage J1 samples. First, mRNA was extracted from the specimens at the two developmental stages. The cDNA was synthesized as described above. Then, Nla III was used to digest the double-stranded cDNAs to produce a CATG cohesive end. Illumina adapter I containing a Mme I restriction site was ligated to the digested cDNA with Dynabeads. All adapter I-containing cDNAs were purified, followed by digestion with Mme I. To produce a tag library, the adapter I containing 21 bp tags was ligated to the Illumina adapter II. Liner PCR was used to amplify these tag fragments for 15 cycles. Then, the 85-bp amplicons were separated on nucleic acid non-denatured pre-made glue 6% gel to generate single-strand molecules. After anchoring to Solexa sequencing array, these molecules were sequenced using the Illumina platform at BGI (Shenzhen, China).
2.4. De novo assembly and analyses of the transcriptome and proteome
Before assembly, the high-quality clean reads were retrieved by eliminating low-quality reads containing >10% Q20 bases, reads containing >10% ambiguous bases, duplicate sequences and adaptor sequences. Then, the SOAP de novo program [18] was employed for assembly of short reads containing 21 bp K-mers. Smaller K-mers or larger K-mers all were not appropriate. Finally, non-redundant unigenes with the longest length were obtained.
Nr, KEGG pathway, GO, COG and Swiss-Prot databases were used for unigenes and protein alignment with E-value <10−5. Then, the functional annotation and sequence direction of unigenes and proteins were determined based on the analysis of the alignment data. The sequences of unigenes were first aligned with BLASTx, which acquired proteins with the highest sequence similarity to the unigenes along with their protein functional annotation. The function of annotated unigenes was classified by GO and analyzed using the Blast2go software. WEGO software was employed to analyze the distribution of gene functions in a species. All unigenes were subjected to GO annotations analysis. Unigene with higher priority aligned to the databases could enter the next circle. At last, the amino acid and nucleotide (5′-3′) sequences of the coding regions were retrieved. When the unigenes could not be aligned to any database, other data of the amino acid and nucleotide (5′-3′) sequences of the coding regions were obtained through ESTScan.
Genome and transcriptome databases have been widely used for protein identification, especially for tandem mass spectral data. NCBInr, SwissProt and UniProt were used to annotate the proteins. UniProt contains a massive amount of protein sequences and functional data. SwissProt and NCBInr have been recognized as the good annotated databases. However, SwissProt database is non-redundant, and the NCBInr database includes non-identical sequences from GenBank CDS translations.
2.5. Mapping of DGE tags to reference transcriptome databases
All low-quality tags, such as tags with only one copy (sequencing errors), low complexity tags, empty tags (only adaptor sequences) and tags with unknown sequences ‘N’, were eliminated before read mapping to transcriptome databases. For tag mapping, a virtual library was constructed with our transcriptome database. All clean tags were mapped to the library and only one nucleotide mismatch was acceptable. The clean tag mapped to multiple genes was filtered, and the remainder was designed as an unambiguous clean tag. To determine gene expression levels, the number of unambiguous clean tags for each gene was measured and then normalized to the number of transcripts per million clean tags (TPM) [19,20].
2.6. Analyses of differentially expressed genes and proteins
The frequency of tags in each DGE library was determined based on the DGE significance analysis method [21]. The thresholds of FDR<0.001 and log2 ratio>1 were deemed as significant differences in gene expression. Differentially expressed proteins (DEPs) were further quantified by iTRAQ analysis. For GO enrichment analysis, DEGs/DEPs were mapped to the GO database. For pathway enrichment analysis, the DEGs/DEPs were mapped to the KEGG database. The hypergeometric test was used to calculate the enriched P-values [22]. The bonferroni correction's P-value (less than 0.05) and FDR less than 0.01 was chosen as the thresholds for detecting the gene and/or protein sets with significant enrichment in the GO and KEGG analyses, respectively.
3. Results
3.1. The transcriptome assembly and analysis in E. sinensis
The RNA mixtures with J1 and M stages of E. sinensi were sequenced using the Solexa/Illumina RNA-Seq platform. About 58,292,820 raw reads and 51,921,414 clean reads were assembled and analyzed (Table 1).
Table 1.
Summary for the transcriptome of Eriocheir sinensis.
| Data items | Number/length |
|---|---|
| Total number of raw reads | 58,292,820 |
| Total number of clean reads | 51,921,414 |
| Total number of clean nucleotides (nt) | 4,672,927,260 |
| Total number of contigs | 187,504 |
| Mean length of contigs (nt) | 292 |
| Total number of unigenes | 76,112 |
| Mean length of unigenes (nt) | 628 |
In total, 187,504 contigs were assembled with an average size of 292 nt. GC percentage and Q20% were 48.4% and 97.13%, respectively. Moreover, 76,112 unigenes with an average size of 628 nt were identified. BLASTn (cut-off E-value = 10−10) was used to search these cDNA sequences. The results showed that the assembled 30,987 unigenes were highly reliable and covered most of the transcriptome sequences with query coverage of 76.5% and mean identity of 98.5%. All unigenes were deposited in the NCBI Short Read Archive database (accession number SRR16996440/PRJNA782386).
Then, all of these unigenes were annotated to match sequences against the Nr, Swiss-Prot, PFAM, GO and KEGG databases by using BLAST (E-value <10−5) [23,24]. The numbers of best matched unigenes from the BLAST search are demonstrated in Table 2.
Table 2.
Statisticical data for the unigene annotation.
| Annotated database | Number of unigenes | Percentage (%) |
|---|---|---|
| Nr | 19157 | 21.24 |
| Nt | 3370 | 3.73 |
| KO | 8321 | 9.22 |
| SwissProt | 15277 | 16.94 |
| PFAM | 20198 | 22.4 |
| GO | 21185 | 23.49 |
| KOG | 10930 | 12.12 |
| All databases | 1885 | 2.09 |
| At least one database | 26768 | 29.68 |
| Total unigenes | 90161 | 100 |
3.2. Mapping of DGE sequences to the reference transcriptome database
DGE could generate absolute instead of gene expression data and further avoid the limitations of microarray assays [25]. Therefore, the variations in gene expression during brachyurization were analyzed using the DGE method. The significant features of these libraries are demonstrated in Table 3. Each library could generate nearly 6 million raw tags and 5.6–6.1 million clean tags (Table 3) after filtering the low-quality tags.
Table 3.
Statistical data of DGE library sequencing and tag mapping.
| Summary | Es-Ma | Es-J1a | |
|---|---|---|---|
| Raw data | Total | 5,854,677 | 5,966,011 |
| Distinct tags | 244,413 | 229,772 | |
| Clean tags | Total number | 5,686,189 | 5,801,179 |
| Distinct tag number | 94,791 | 85,366 | |
| All tags mapped to genes | Total number | 4,536,136 | 4,987,715 |
| Total % of clean tags | 79.77% | 85.98% | |
| Distinct tag number | 53,940 | 51,854 | |
| Distinct tag % of clean tags | 56.90% | 60.74% | |
| Unambiguous tags mapped to genes | Total number | 4,009,476 | 4,286,175 |
| Total % of clean tags | 70.51% | 73.88% | |
| Distinct tag number | 45,676 | 437,23 | |
| Distinct tag % of clean tags | 48.19% | 51.22% | |
| All tag-mapped genes | Total number | 22,137 | 20,814 |
| Total % of reference genes | 29.08% | 27.35% | |
| Unambiguous tag-mapped genes | Total number | 17,192 | 16,014 |
| Total % of reference genes | 22.59% | 21.04% | |
Es-M: the megalopa stage of E. sinensis; Es-J1: the first stage of juvenile crab.
The DGE tags were mapped to the transcriptome database to elucidate the molecular mechanism during brachyurization development from J1 stage to M stage. Tags mapped to a unique sequence can be used to identify a transcript, which represent the most critical important of DGE library. Approximately 20,814 unique tags in the stage J1 (27.35%) and 22,137 in the stage M (29.08%) were unequivocally identified in our reference transcriptome database (Table 3).
3.3. Analysis for DEGs/DEPs between stage M and stage J1
After mapping the DGE library sequences to the transcriptome sequences, 1106 DEGs between M and J1 stages were identified from the mapped tags (Fig. 1), with 400 up-regulated genes and 706 down-regulated genes (stage J1 vs stage M). As demonstrated in Fig. 2, the expression levels of all candidate genes were detected by real-time quantitative PCR (qPCR), and differential expression patterns are in agreement with the sequencing results of transcriptome.
Fig. 1.
DEGs between M and J1 stages of Eriocheir sinensis. M: the megalopa stage of E. sinensis; J1: the first stage of juvenile crab.
Fig. 2.
The results from real-time quantitative PCR detection. Seven genes were determined by qPCR in triplicate samples. M: the megalopa stage of E. sinensis; J1: the first stage of juvenile crab.
The high-throughput proteomics analysis of E. sinensis resulted in the initial identification of 4300 proteins, of which all were maintained for statistical analysis after quality control steps (Table 4). According to the abundance of the proteins, those with fold-change>1.2 and P < 0.05 were defined as DEPs. Comparative analysis of two samples (Stage J1 vs Stage M) revealed that there were 871 regulated proteins, including 353 up-regulated proteins and 518 down-regulated proteins (Fig. 3).
Table 4.
Overview of the proteomics sequencing results in Eriocheir sinensis.
| Item | Number |
|---|---|
| Total spectra | 270349 |
| Spectra | 52702 |
| Unique spectra | 48539 |
| Peptides | 17207 |
| Unique peptides | 16549 |
| Proteins | 4300 |
Fig. 3.
The fold-change distribution of all proteins. The X-axis represents protein ratio [log (protein ratio), with base = 2]. The protein ratios above and below 0 indicate the up-regulated and down-regulated expression, respectively. Red dots mean the potential DEGs with up-regulation, while green dots mean the potential DEGs with down-regulation. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
The information about the correlation between genes and proteins are shown in Table 5.
Table 5.
The numbers of proteins and genes, and the correlation between them in Eriocheir sinensis.
| Group name | Type | Number of proteins | Number of genes | Number of correlations |
|---|---|---|---|---|
| J1 vs Ma | Identification | 4300 | 14573 | 1703 |
| Quantitation | 3108 | 14573 | 1398 | |
| Differential Expression | 871 | 1106 | 83 |
M: the megalopa stage of E. sinensis; J1: the first stage of juvenile crab.
Combining proteome and transcriptome analyses, the correlation between DEPs/genes was analyzed. Fig. 4 shows the abundance ratios of DEPs/genes.
Fig. 4.
Gene abundance ratio versus protein abundance ratio. X- and Y-axis indicate the expression levels of DEGs/DEPs, respectively.
3.4. GO and KEGG analyses for DEPs and DEGs
The differential expression genes and proteins could be grouped into diverse classes associated with binding (40.05%), catalytic activity (41.94%), cell and cell parts (21.68%, respectively), cellular processes (17.05%), metabolic processes (15.94%), organelle (16.08%) and macromolecular complexes (11.67%) (Fig. 5). The KEGG database was used to obtain more information for predicting the functions, whereby 1140 DEGs/DEPs were classified into 235 KEGG pathways. The top 30 pathways of DEGs/DEPs are displayed in Table 6.
Fig. 5.
GO analysis of DEGs/DEPs. These proteins were classified into diverse group: biological process, molecular function and cellular component.
Table 6.
The top 30 pathways of DEGs/DEPs in Eriocheir sinensis.
| No. | Pathway | The different expressed proteins and genes | Pathway ID |
|---|---|---|---|
| 1 | Metabolic pathways | 291 (25.44%) | ko01100 |
| 2 | Ribosome | 71 (6.21%) | ko03010 |
| 3 | Huntington's disease | 66 (5.77%) | ko05016 |
| 4 | Alzheimer's disease | 63 (5.51%) | ko05010 |
| 5 | Parkinson's disease | 59 (5.16%) | ko05012 |
| 6 | Oxidative phosphorylation | 58 (5.07%) | ko00190 |
| 7 | Protein processing in endoplasmic reticulum | 48 (4.2%) | ko04141 |
| 8 | Phagosome | 47 (4.11%) | ko04145 |
| 9 | Focal adhesion | 45 (3.93%) | ko04510 |
| 10 | Regulation of actin cytoskeleton | 44 (3.85%) | ko04810 |
| 11 | RNA transport | 37 (3.23%) | ko03013 |
| 12 | Tight junction | 36 (3.15%) | ko04530 |
| 13 | Spliceosome | 35 (3.06%) | ko03040 |
| 14 | Pathways in cancer | 35 (3.06%) | ko05200 |
| 15 | Lysosome | 34 (2.97%) | ko04142 |
| 16 | Influenza A | 31 (2.71%) | ko05164 |
| 17 | Valine, leucine and isoleucine degradation | 31 (2.71%) | ko00280 |
| 18 | Pancreatic secretion | 31 (2.71%) | ko04972 |
| 19 | Salmonella infection | 31 (2.71%) | ko05132 |
| 20 | Epstein-Barr virus infection | 30 (2.62%) | ko05169 |
| 21 | Pathogenic Escherichia coli infection | 30 (2.62%) | ko05130 |
| 22 | Cardiac muscle contraction | 29 (2.53%) | ko04260 |
| 23 | Dilated cardiomyopathy | 28 (2.45%) | ko05414 |
| 24 | Proteasome | 28 (2.45%) | ko03050 |
| 25 | Glutathione metabolism | 27 (2.36%) | ko00480 |
| 26 | Hypertrophic cardiomyopathy | 27 (2.36%) | ko05410 |
| 27 | Tuberculosis | 26 (2.27%) | ko05152 |
| 28 | Shigellosis | 26 (2.27%) | ko05131 |
| 29 | Leukocyte transendothelial migration | 25 (2.19%) | ko04670 |
| 30 | Glycolysis/Gluconeogenesis | 25 (2.19%) | ko00010 |
4. Discussion
The larva of E. sinensis experience various developmental stages, including 5 zoeal stages and 1 megalopal stage, followed by the first to third juvenile crab stages [26,27]. The reduced abdomen folded beneath the thorax is the most prominent characteristic of morphological alteration from megalopa to juvenile crab, which is known as brachyurization [28]. Various taxonomical studies have indicated that the brachyuran organization can lead to greater biological functions with wider distribution and better adaptation to the littoral habitats. This organization has a phenotypic plasticity and undergone secondary modifications in response to habit and habitat alterations. To date, paleontological evidence has been proven invaluable to understanding the origins and evolution of brachyurans. However, molecular mechanism of brachyurization in brachyurans remains unknown, even though there are some researches about this question [29,2]. In this work, the transcriptome, proteome and DGE of E. sinensis could significantly enrich the databases and provide better understanding of the mechanism of brachyurization. [30] indicated that various genes in the pathways of oxidative phosphorylation, muscle contraction, calcium signaling, and lipid metabolism were significantly down-regulated in the abdomen of E. sinensis during brachyurization metamorphosis, while DNA replication and PI3K-Akt pathway genes demonstrated up-regulation. These results are also observed in this study.
At the same time, we found that the components of integrin signaling pathway and extracellular matrix also play the important functions in brachyurization metamorphosis. The results of proteome indicated that actin, actin-related protein, collagens, filamin-A/B, laminin, integrins, paxillin, and fibronectin were highly expressed in M stage than in J1 stage. These proteins are the components of the extracellular matrix and involved in integrin signaling pathway. The extracellular matrix can function as an important source for angiogenic, motility, survival and growth factors, which remarkably affects cell biology and development. Furthermore, cell adhesion to the extracellular matrix can trigger intracellular signaling pathways and interact with integrins and other cell surface receptors to modulate cell differentiation, migration, and cell cycle progression [31,32,33,34]. These proteins, as the main components of integrin signaling pathway and extracellular matrix, showed lower expression levels in the stage J1. These findings demonstrate that the brachyurization development may be related with the dysregulation of extracellular matrix or integrin signaling pathway.
In addition, we found that myosin had a high proportion and gene expression in M stage compared to J1 stage. Previous research has indicated that the fates of tail and trunk muscles are mainly influenced by the distributions of adult myoblasts in muscle tissues [35]. The tail absorption can be influenced by cAMP in a direct way [36], which is related to integrin signaling pathway. On the other hand, calcification in crustaceans plays vital roles in forming solid exoskeletons and attenuating physical damage [37]. Compared to the stage M, cuticle protein genes were up-regulated in the stage J1. These data are in agreement with a previous study [2].
Based on the analysis results of DEGs/DEPs between J1 and M stages, most genes and proteins belonged to the metabolite interconversion enzymes, including ligases, isomerases, lyases, hydrolases, transferases, oxidoreductases, translocases, and so on. Most of them participated in metabolic pathways. The results indicated that metabolism was activated in both M and J1 stages. Metabolic enzymes are required to catalyze the nutrients (e.g., carbohydrate, protein and lipid) and even nucleic acid to complete the developmental process of E. sinensis.
5. Conclusion
In summary, this study found that integrin signaling pathway and extracellular matrix remodeling exhibited important functions in brachyurization metamorphosis. In addition, the metabolite interconversion enzymes were activated during the morphological changes from stage M to stage J1. Altogether, our results can help explain the brachyurization patterns of E. sinensis and suggest comparative omics patterns with other brachyuran species.
Contribution statement
PL and KYZ conceived and designed this research. FCJ, YXY and PL conducted the experiments and data analysis. WYL, GMH, FZ, JY and KYZ analyzed and interpreted the data. YXY, FCJ and PL wrote the article. All authors discussed the results and approved the final revision for submission.
Competing interests
The authors declare that they have no competing interests.
Funding
This research was funded by the National Natural Science Foundation of China (31000954), National Key Research and Development Project (No. 2019YFC1605800), Specialized Research Fund for the Doctoral Program of Higher Education of China (20103207120007), Priority Academic Program Development of Jiangsu Higher Education Institutions, and Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (PPZY2015B117).
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