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Transcriptome analysis of head kidney in grass carp and discovery of immune-related genes.
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PMID:  22776770     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: Grass carp (Ctenopharyngodon idella) is one of the most economically important freshwater fish, but its production is often affected by diseases that cause serious economic losses. To date, no good breeding varieties have been obtained using the oriented cultivation technique. The ability to identify disease resistance genes in grass carp is important to cultivate disease-resistant varieties of grass carp.
RESULTS: In this study, we constructed a non-normalized cDNA library of head kidney in grass carp, and, after clustering and assembly, we obtained 3,027 high-quality unigenes. Solexa sequencing was used to generate sequence tags from the transcriptomes of the head kidney in grass carp before and after grass carp reovirus (GCRV) infection. After processing, we obtained 22,144 tags that were differentially expressed by more than 2-fold between the uninfected and infected groups. 679 of the differentially expressed tags (3.1%) mapped to 483 of the unigenes (16.0%). The up-regulated and down-regulated unigenes were annotated using gene ontology terms; 16 were annotated as immune-related and 42 were of unknown function having no matches to any of the sequences in the databases that were used in the similarity searches. Semi-quantitative RT-PCR revealed four unknown unigenes that showed significant responses to the viral infection. Based on domain structure predictions, one of these sequences was found to encode a protein that contained two transmembrane domains and, therefore, may be a transmembrane protein. Here, we proposed that this novel unigene may encode a virus receptor or a protein that mediates the immune signalling pathway at the cell surface.
CONCLUSION: This study enriches the molecular basis data of grass carp and further confirms that, based on fish tissue-specific EST databases, transcriptome analysis is an effective route to discover novel functional genes.
Authors:
Jin Chen; Cai Li; Rong Huang; Fukuan Du; Lanjie Liao; Zuoyan Zhu; Yaping Wang
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2012-07-09
Journal Detail:
Title:  BMC veterinary research     Volume:  8     ISSN:  1746-6148     ISO Abbreviation:  BMC Vet. Res.     Publication Date:  2012  
Date Detail:
Created Date:  2012-11-26     Completed Date:  2013-03-25     Revised Date:  2013-07-12    
Medline Journal Info:
Nlm Unique ID:  101249759     Medline TA:  BMC Vet Res     Country:  England    
Other Details:
Languages:  eng     Pagination:  108     Citation Subset:  IM    
Affiliation:
State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
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MeSH Terms
Descriptor/Qualifier:
Animals
Carps / physiology*
Cloning, Molecular
Expressed Sequence Tags
Gene Expression Regulation / immunology
Gene Library
Head Kidney / metabolism*
Reverse Transcriptase Polymerase Chain Reaction / veterinary
Transcriptome*
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Journal ID (nlm-ta): BMC Vet Res
Journal ID (iso-abbrev): BMC Vet. Res
ISSN: 1746-6148
Publisher: BioMed Central
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Copyright ©2012 Chen et al.; licensee BioMed Central Ltd.
open-access:
Received Day: 12 Month: 2 Year: 2012
Accepted Day: 18 Month: 6 Year: 2012
collection publication date: Year: 2012
Electronic publication date: Day: 9 Month: 7 Year: 2012
Volume: 8First Page: 108 Last Page: 108
PubMed Id: 22776770
ID: 3505460
Publisher Id: 1746-6148-8-108
DOI: 10.1186/1746-6148-8-108

Transcriptome analysis of head kidney in grass carp and discovery of immune-related genes
Jin Chen12 Email: chenjin@ihb.ac.cn
Cai Li12 Email: cai_li.hust@163.com
Rong Huang1 Email: huangrong@ihb.ac.cn
Fukuan Du12 Email: adublg@126.com
Lanjie Liao1 Email: liaolj@ihb.ac.cn
Zuoyan Zhu1 Email: zyzhu@ihb.ac.cn
Yaping Wang1 Email: wangyp.ihb@gmail.com
1State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
2Graduate School of Chinese Academy of Sciences, Beijing, 100039, China

Background

Grass carp (Ctenopharyngodon idella) is one of the most important freshwater fish, with fast growth, low cost of breeding, and delicious meat. It is widely distributed in China's major river systems. Grass carp is a farmed species that is easily affected by diseases induced by viruses and bacteria; this can cause tremendous economic losses. To date, no excellent breeding varieties have been obtained by the oriented cultivation technique. Because of the long breeding cycle (4–5 years), a hybrid breeding strategy is not feasible. Further, because of the lack of understanding of the genetic background of grass carp, no molecular breeding technology has been applied. The discovery of economically important trait-related genes and their functional study may help to establish a molecular breeding technology system in the fish.

ESTs (expressed sequence tags) are partial cDNA sequences obtained after sequencing the ends of random cDNA clones. ESTs were first used in 1991 as an effective new method to discover human genes. Using EST sequences, unknown genomes could be explored at a relatively low cost [1]. With the development of DNA sequencing technology, the cost of sequencing is becoming lower, and the application of large-scale EST sequencing combined with bioinformatics tools for analyzing data is being widely used in different species to find novel genes, for genome annotation, for the identification of gene structure and expression, and in the development of type I molecular markers [2]. In fish, large scale EST sequencing was used in channel catfish (Ictalurus punctatus) [3], common carp (Cyprinus carpio) [4], and zebrafish (Danio rerio) [5].

In recent years, high-throughput data analysis methods have gradually improved and the genomes of many kinds of fishes have been studied. The fishes that have been studied include zebrafish [6] and fugu [7], as model organisms, and the commercial fishes such as Atlantic salmon [8], sea bass [9,10], rainbow trout [11], Atlantic halibut [12], bluefin tuna [13], turbot [14,15], and Senegal sole fish [16]. In contrast, the molecular biology of grass carp is relatively unknown; currently, there are only 6,915 grass carp ESTs in NCBI’s dbEST database. Most functional genomic research on economically important fish is focused mainly on the development of molecular markers, genetic map construction and gene interval mapping, and other basic data accumulation. Research into gene function and its application to breeding is still in the initial stages.

Head kidney is an important immune organ in teleost fish; its role is equivalent to mammalian bone marrow [17]. Head kidney contains a large number of T and B lymphocytes, macrophages and granulocytes that are the basis upon which specific and non-specific immunity is acquired.

In this study, we constructed a non-normalized cDNA library for the head kidney of grass carp and obtained 3,027 unigenes including 221 genes of unknown function. We compared the head kidney expression profiles of grass carp infected with grass carp reovirus (GCRV) with normal controls and obtained 22,144 differential expressed tags. Based on a comparison of the differential expressed tags and potential genes with unknown function in the cDNA library, and by identifying gene expression response to GCRV and predicting protein structure, we discovered a novel immune-related gene. This study provides a method for the discovery of novel genes, and reveals the function and the network regulation mechanism of immune-related genes. The results provide a theoretical foundation for molecular design breeding in grass carp.


Methods
RNA extraction and construction of the cDNA library

Total RNA was extracted from the head kidney of healthy adult grass carp using Trizol reagent (Invitrogen, Carlsbad, CA, USA). The mRNA was isolated using the Oligotex mRNA Kit (QIAGEN, Hilden, Germany). Full length cDNA was synthesized by the CreatorTM SMARTTM cDNA Library Construction Kit (Clontech, CA, USA) following the method described previously [18]. cDNA segments longer than 1 kb were isolated by electrophoresis, then ligated into pDNR-LIB vector (Clontech) and used to transform competent E. coli DH5α cells. After growing the colony for 12 hours on an LB plate containing chloramphenicol, the cDNA library was constructed by selecting mono-clones from the 96-well plate. Ethical approval for the work was obtained from Expert Committee of Biomedical Ethics, Institute of Hydrobiology of the Chinese Academy of Sciences. The Reference number obtained was Y12202-1-303.

DNA sequencing and processing of the EST sequences

10,464 clones were randomly selected from 109 96-well plates. After extracting the recombinant plasmids, 5’ terminal sequencing was performed using the T7 universal primer (T7: 5′-TAATACGACTCACTATAGGG-3′; Tm = 53.2 °C).

An optimal peak chart was obtained by processing the raw sequence data with basecalling. Next, FASTA format sequences (raw ESTs) were obtained by processing the optimal peak chart using the Phrap program [19] with the Q20 standard. We used crossmatch (Smith and Green, unpublished observations) to remove the pDNR-LIB vector sequences and after excluding EST sequences that were less than 100 bp long, we obtained a cleaned EST data set. Clustering of the cleaned ESTs was performed using UIcluster [20]. The UIcluster sequences were assembled using the Phrap program to build a unigene data set for the ESTs from the head kidney of grass carp.

BLAST searches, GO functional classification and KEGG pathway analysis

We used the NCBI BLAST server [21] to identify sequences that were similar to the sequences in the NCBI nucleotide sequence database (Nt), the protein sequence database (Nr) [22] and the Swissprot database [23] using BLASTN, and BLASTX [24]. Using the EST sequence with the highest homology as a guide, we set the threshold E-value to E < 1e-6.

We used the BLASTX search results from the Swissprot database and the Blast2GO tool [25] to assign GO functional classification to the unigene sequences. Blast2GO parameters were set as follows: E-Value-Hit-Filter < 1e-6; annotation cutOff = 55; other parameters remained at the default values.

KAAS [26] was used to assign the unigene ESTs to pathways based on KEGG Orthology (KO) [27]. Unigenes were mapped to the corresponding KEGG pathways using the comparison method of bi-directional best hit.

GCRV infection of grass carp and preparation of RNA sample

The GCRV-873 strain was provided by the Gaobo biotechnology company (Wuhan, China). One-year-old grass carp with an average weight of 180–210 g were intraperitoneally injected with 150–200 μL GCRV, a dosage of approximately 106 TCID50 kg-1 body weight. The injected grass carp were raised in clean tanks at 28°C. Three infected grass carp with typical hemorrhage symptoms (infected group, n = 3) and three uninfected grass carp (healthy control group, n = 3) were selected at 5d after infection for further study. Total RNA was extracted from the head kidney of both groups using Trizol reagent. cDNA was obtained after reverse transcription and used for Solexa sequencing.

Three-month-old grass carp with an average weight of 30–60 g were intraperitoneally injected with 50–80 μL GCRV, a dosage of approximately 106 TCID50 kg-1 body weight; fish in the control group were injected with same amount of saline. The grass carp were raised in clean tanks at 28°C. At 1d, 2d, 3d, 4d, 5d after infection ten GCRV-infected carp were selected for further study (n = 10). Ten uninfected fish were selected from the control group at 0d (n = 10). The whole fish was immediately used for RNA isolation. cDNA was obtained after reverse transcription and used for the detection of gene expression.

Solexa sequencing and expression profile analysis

The NlaIII and MmeI digestion method [28] was used to build a 21-bp cDNA tag library of the two groups (one-year-old), the control group and the GCRV-infected group. The tags in the two libraries end with different Illumina adapter sequences. The raw sequencing read length was 35 bp. The Solexa sequencing was performed by the Beijing Genomics Institute (BGI, Shenzhen, China).

The raw sequence data was processed through basecalling, the adapter and low quality sequences were removed, and cleaned 21-bp tags were obtained. We converted the cleaned tag number into the standard (relative) number of transcripts per million (TPM), and calculated the logarithm of TPM for each of the cleaned tags from the control and GCRV-infected groups. We used a dual limit of P <0.01 and FPR (false positive rate) <0.01, to find cleaned tags with log2Ratio ≥ 1 or log2Ratio ≤ −1 [29]. The selected tags have differential expression levels of more than 2-fold in both groups. We then compared the differential expressed tags with the unigenes from the cDNA library using SeqMap [30]; mismatch was set to 0, and sense and antisense strands were considered in the mapping.

Semi-quantitative RT-PCR and RACE cloning

Total RNA was used to synthesize the first strand cDNA. Upstream and downstream primers (Table 1) were designed based on the unigene sequences. β-actin (primers, β-actin-F and β-actin-R) was used as the internal reference. PCR and electrophoresis was used to detect the change of expression level.

3' and 5' RACE was performed using the BD SMART RACE cDNA Amplification Kit (Clontech) according to the manufacturer’s instructions. Upstream and downstream primers used in the 3' and 5' RACE were designed based on the EST sequences (Table 1). Full length cDNA sequences of each gene were assembled using the 3' and 5' terminal sequences.


Results
Head kidney cDNA library of grass carp

The storage capacity of the original library was 6 × 105, in the form of the E. coli DH5α cells that were stored on the 532 96-well plates in a total of 51,072 clones. One hundred randomly selected clones were used for further study. The PCR test results showed that the size of inserts was between 1–3 kilobases, the library reorganization was 97.85% and the no-load rate was 2.15%.

EST sequence analysis

10,464 EST clones were sequenced, and 10,282 FASTA sequences (raw ESTs) with an average read length of 470 bp were obtained. After removing the vector and sequences less than 100 bp long, 7,918 cleaned ESTs (accession no. JK847435-JK855352) were obtained. After clustering and assembly, we obtained 3,027 unigene EST sequences, 802 (26.5%) of which were contigs and 2,225 (73.5%) of which were singletons; the library redundancy was 61.78%. Most genes in the library exhibited low-level expression, only a small number of genes exhibited high-abundance expression. The number of low expression unigenes, the singletons, was 2,225 (73.5%); the number of medium expression unigenes, those containing 2–5 ESTs was 641 (21.2%); and the number of high expression unigenes, those that contained six or more ESTs, was 161 (5.3%). Only 23 unigenes contained more than 20 ESTs. The average length of the unigenes was 431 bp and 77.33% of the unigenes were 300–500 bp long (Figure 1).

BLAST searches and GO functional classification

The 3,027 unigenes were used as queries in BLAST searches of the NCBI nucleotide and protein sequence databases and the Swissprot database. 2,713 unigenes (89.6%) matched sequences in the nucleotide sequence database, 2,162 unigenes (71.4%) matched sequences in protein sequence database and 1,845 unigenes (61.0%) matched sequences in the Swissprot database. In all, 2,806 unigenes (92.7%) matched sequences in at least one of the three databases; the remaining 221 unigenes (7.3%) were not found (E-value <1e-6) in any of the three databases and may be novel gene sequences.

Using the gene ontology (GO) classification, we successfully assigned functional annotations to 1,323 of the unigene sequences. In the GO biological process ontology, three terms accounted for the largest proportion of unigenes, they were cellular process, metabolic process and biological regulation; in the GO molecular function ontology, the three most commonly occurring terms were binding, catalytic activity and structural molecule activity; and in the GO cellular component ontology, cell, cell part and organelle were the terms that occurred most frequently (Table 2). Of the 1,323 GO-annotated unigenes, 53 were immune system process-related genes (Table 3), 4 were response to virus, and 9 were response to bacterium process-related genes (Tables 4 and 5). Some unigenes were assigned multiple functions. Not all of the unigenes could be mapped to the lower level GO terms.

KEGG pathway analysis

A total of 989 of the 3,027 were assigned a KEGG ontology (KO) annotation; they were mapped to 201 KEGG pathways. Three most frequently occurring KEGG pathways were ribosome, oxidative phosphorylation, and proteasome. 68 unigenes mapped to immune-related pathways including leukocyte transendothelial migration, antigen processing and presentation, chemokine signalling pathway, and T cell receptor signalling pathway (Table 6). We found that 28 unigenes from head kidney in grass carp have been reported to be involved in the following pathways, Toll-like receptor signalling pathway, RIG-I-like receptor signalling pathway and the NOD-like receptor signalling pathway (Table 7).

Expression profiling analysis

By Solexa sequencing, we obtained 7,696,804 and 6,136,889 raw tags from the transcriptomes of head kidney tissue from grass carp before and after GCRV infection, respectively. After removing low quality sequences, adapter sequences and single copy sequence the cleaned tag numbers were 7,188,005 and 5,724,526, respectively. The final numbers of non-redundant distinct tags were 152,826 and 105,653 before and after GCRV infection, respectively. All tags were submitted to SRA at NCBI under the accession no. SRA052520.2. Of the distinct tags, 22,144 were differentially expressed by more than 2-fold between the GCRV-infected and uninfected groups.

These 22,144 differentially expressed tags mapped to 3,027 unigenes using SeqMap [30]. Of the differentially expressed tags, 679 (3.1%) mapped to 483 differentially expressed unigenes (16.0%); 145 of the unigenes were up-regulated genes, 307 were down-regulated genes. The remaining 31 unigenes mapped to tags that exhibited both up and down regulation, and so these unigenes were not included in the statistics. The up- and down-regulated genes were mainly annotated with the GO terms, genetic information processing, metabolism, and cellular processes and 16 unigenes were annotated with the GO term immune-related (Table 8). We found 54 tags that mapped onto 42 of the 221 unknown unigenes. These are potentially infection related novel genes; 15 of them were up-regulated between the GCRV-infected and uninfected groups, and 27 were down-regulated genes (Table 9).

Cloning and expression regulation analysis of the novel genes

Using semi-quantitative RT-PCR, we examined the gene expression changes of the 42 potentially novel unigenes that were detected in the head kidney after viral infection. By comparing the 1, 2, 3, 4, and 5 day post-infection samples and the samples from the control group, we found four unigenes that showed a significant response to the viral infection: cichka_Cluster153 and cichka_Cluster291 were up-regulated in days 1 and 2 post-infection after which their expressions returned to the starting level; cichka_Cluster357 and cichka_Cluster788 were up-regulated in days 1 and 2 post-infection, and the increased expression levels were maintained till day 5 (Figure 2).

The full-length cDNA sequences of these four unigenes were 2,057 bp (cichka_Cluster291, JQ412736), 2,288 bp (cichka_Cluster357, JQ412737), 1,044 bp (cichka_Cluster788, JQ412738) and 1,387 bp (cichka_Cluster153, JQ412739) encoding polypeptides of 586, 322, 142 and 155 amino acids, respectively. BLAST searches revealed that cichka_Cluster291 can encode a protein that is similar to the vertebrate endonuclease domain containing protein, cichka_Cluster357 can encode a protein that is similar to the vertebrate ankyrin repeat domain 10 protein, cichka_Cluster788 can encode a protein that is similar to the CST complex subunit TEN1; for the cichka_Cluster153 encoded protein, no similar sequences were found in the databases that we searched, suggesting that cichka_Cluster153 may represent a novel gene in grass carp. We used the SMART server [31] to predict the domain structure of the 42 novel unigenes and found that 83.02% of them contained the endonuclease domain 1 that is found in proteins that are involved in the apoptosis pathway, and 35.22% contained the ankyrin repeat domain that is present in proteins that are involved in pathways that include the B cell receptor signalling pathway, the T cell receptor signalling pathway, and the apoptosis pathway. The cichka_Cluster788 unigene contained no obvious structural domains; the cichka_Cluster153 encoded protein contained two transmembrane domains and may be a transmembrane protein.


Discussion

Currently, there are about 6,915 sequences of grass carp in the public databases. This situation does not reflect the extremely important breeding position of grass carp. In this study, we built a head kidney non-normalized cDNA library of healthy grass carp and obtained 3,027 unigene EST sequences. This library greatly enriches the available genomic data for grass carp and lays an important foundation for the discovery of novel genes and for their functional investigation.

GO analysis revealed that the annotated unigenes were mainly related to genes involved in basic biological processes such as cellular process (25.5%), metabolic process (19.1%) and biological regulation (10.8%). This functional distribution is similar to the EST distributions reported earlier in the head kidney of zebrafish [32] and sea bass [10].

Of the unigenes that were similar to immune-related genes, 66 unigenes were annotated as associated with the immune process; 53 were related to the immune system process, 4 were annotated as response to virus, and 9 were related to response to bacteria. Among the 989 unigenes that were assigned KO annotations, 68 were mapped to immune-related pathways that included leukocyte transendothelial migration, antigen processing and presentation, chemokine signalling pathway and T cell receptor signalling pathway. By examining the literature, we found that 28 of the unigenes in grass carp head kidney were related to fish genes that were reported to be involved in the Toll-like receptor signalling pathway, the RIG-I-like receptor signalling pathway and the NOD-like receptor signalling pathway. Clearly, head kidney tissue plays an important role in immune processes in fish. EST databases of head kidney tissue are likely to become important resources in which immune-related genes can be identified.

In the 3,027 unigene library of head kidney in grass carp, 7.3% (221) failed to match any of the sequences in the three public databases that were searched. Of the 10 unigenes that were the most highly expressed in grass carp head kidney, 9 were unknown sequences (Table 10). This could be partly because sequence data for fish is still very scarce, and partly because fish head kidney tissue may contain tissue-specific or species-specific genes. EST databases can be important resources for identifying unknown genes in fish [33-35]. In recent years, the fish transcriptome has been used to study the regulation of gene expression. Pardo et al (2008) conducted a comparative study of turbot expression profiles in the main immune tissue before and after pathogen infection to find genes that were related to immune response and disease resistance [36]. Chini et al (2008) carried out a comparative study of reproductive development-related tissues in bluefin tuna using transcriptome research methods to explore the molecular mechanism of gonadal development and maturity split [13]. Indeed, comparative transcriptome analysis can be used, not only to investigate the mechanisms of expression and regulation of known genes, but also as an effective means to find important and novel function-related genes.


Conclusion

We carried out a comparative analysis to find differences in the Solexa expression profiles of head kidney in grass carp before and after infection, and identified 42 unigenes of unknown function that showed differential expression in response to the pathogen. After RT-PCR validation of the cDNA and gene structure analysis, we found a potentially novel immune-related gene. Based on its response to viral infection and the prediction that it might encode a membrane protein, we speculate that this novel gene may encode a virus receptor or a protein that mediates the immune signalling pathway at the cell surface. We intend to further investigate the function of this gene in a future study. Our findings confirm that fish tissue-specific EST databases combined with comparative transcriptome analysis are effective tools that can direct the discovery of novel functional genes.


Competing interests

The authors declare that they have no competing interests.


Authors’ contributions

CJ carried out the experiments and drafted the manuscript. LC and DFK conducted the database searches and bioinformatics analysis. HR and ZZY participated in the study design and in the manuscript preparation. LLJ was involved in the experiments. WYP was overall responsible for the project and finalized the manuscript. All authors read and approved the final manuscript.


Acknowledgements

The research was financially supported by the Innovation Project of the Chinese Academy of Sciences (KSCX2-EW-N-004-3), the National Key Basic Research Program (2009CB118701), and the Autonomous Project of State Key Laboratory of Freshwater Ecology and Biotechnology (2011FBZ18).


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Figures

[Figure ID: F1]
Figure 1 

Length distribution of the assembled EST unigenes. The abscissa indicates the length of the unigenes, the ordinate indicates the number of unigenes.



[Figure ID: F2]
Figure 2 

RT-PCR verification of the novel infection-related genes. M, maker; 0, non-infected tissue; 1, 1 day after infection; 2, 2 days after infection; 3, 3 days after infection; 4, 4 days after infection;5, 5 days after infection; N, the negative control.



Tables
[TableWrap ID: T1] Table 1 

Primers used for semi-quantitative RT-PCR and RACE


Primer Sequence (5′ to 3′) Application
291-F1
ATGTGGGTGATAGTTGGTTTACAAT
Expression study
291-R1
GTAATTTCAGAAGCACAGTTGAGAG
Expression study
357-F1
CTATCGCATGATTGCCTACTCAGACT
Expression study
357-R1
ACAACATTTTCCATCTCAATCTCAG
Expression study
788-F1
GGTCTTAACGGAGAGAAGTGCGA
Expression study
788-R1
GACTCTTCCGGCACGTAACT
Expression study
153-F1
CCAGCATCACAGTGTTCAGGCAG
Expression study
153-R1
AGTGTGTAGTTGTGTTCACCCTCC
Expression study
β-actin-F
CAGATCATGTTTGAGACC
Expression study
β-actin-R
ATTGCCAATGGTGATGAC
Expression study
291-F2
CTCTCAACTGTGCTTCTGAAATTAC
3’ RACE PCR
291-R2
ATTGTAAACCAACTATCACCCACAT
5’ RACE PCR
357-F2
GGTATGATTATGACTAAAGCAGGAC
3’ RACE PCR
357-R2
GTCCTGCTTTAGTCATAATCATACC
5’ RACE PCR
788-F2
AGTTACGTGCCGGAAGAGTC
3’ RACE PCR
788-R2
TCGCACTTCTCTCCGTTAAGAC
5’ RACE PCR
153-F2
GGAGGGTGAACACAACTACACACT
3’ RACE PCR
153-R2 CTGCCTGAACACTGTGATGCTGG 5’ RACE PCR

[TableWrap ID: T2] Table 2 

GO functional classification of the unigene data set


  GO term Number of unigenes %
Biological Process
cellular process
899
68.0
 
metabolic process
672
50.8
 
biological regulation
379
28.6
 
regulation of biological process
356
26.9
 
localization
250
18.9
 
establishment of localization
232
17.5
 
developmental process
135
10.2
 
response to stimulus
126
9.5
 
multicellular organismal process
100
7.6
 
positive regulation of biological process
80
6.0
 
anatomical structure formation
71
5.4
 
negative regulation of biological process
66
5.0
 
immune system process
53
4.0
 
multi-organism process
22
1.7
 
growth
18
1.4
 
biological adhesion
14
1.1
 
locomotion
14
1.1
 
reproduction
14
1.1
 
reproductive process
14
1.1
 
viral reproduction
4
0.3
Cellular Component
cell part
1084
81.9
 
cell
1084
81.9
 
organelle
733
55.4
 
macromolecular complex
402
30.4
 
organelle part
384
29.0
 
membrane-enclosed lumen
140
10.6
 
envelope
80
6.0
 
extracellular region
32
2.4
 
extracellular region part
12
0.9
 
synapse
6
0.5
 
synapse part
4
0.3
Molecular Function
binding
770
58.2
 
catalytic activity
440
33.3
 
structural molecule activity
77
5.8
 
transporter activity
70
5.3
 
transcription regulator activity
46
3.5
 
molecular transducer activity
46
3.5
 
enzyme regulator activity
30
2.3
 
translation regulator activity
29
2.2
 
electron carrier activity
11
0.8
  antioxidant activity 5 0.4

[TableWrap ID: T3] Table 3 

Unigenes annotated with the GO term immune system process


Sequence name Sequence description Hit AC Clustered EST
Cluster1088
fucolectin
Q7SIC1
1
Cluster1225
endoplasmic reticulum aminopeptidase 1
Q9NZ08
1
Cluster1249
transcription factor sp2
Q02086
1
Cluster1357
complement c3
P98093
1
Cluster1410
b-cell lymphoma 6 protein homolog
P41183
1
Cluster1474
matrix metalloproteinase-9
P14780
1
Cluster1562
serine threonine-protein phosphatase subunit
P30153
1
Cluster1638
inosine-5 -monophosphate dehydrogenase 2
Q3SWY3
1
Cluster1667
chemokine-like factor
Q9UBR5
1
Cluster1692
60 kda heat shock mitochondrial
Q5ZL72
1
Cluster1821
transcription elongation factor
Q4KLL0
1
Cluster1865
serine threonine-protein kinase tbk1
Q9WUN2
1
Cluster1872
dedicator of cytokinesis protein 2
Q92608
1
Cluster1891
complement c3
P98093
1
Cluster1908
interferon regulatory factor 4
Q64287
1
Cluster2109
sh2 domain-containing protein 1a
B2RZ59
1
Cluster2173
bisphosphate phosphodiesterase gamma-2
Q8CIH5
1
Cluster2189
ig heavy chain v-iii region cam
P01768
2
Cluster2214
complement c3
P12387
2
Cluster2253
calreticulin
P18418
2
Cluster2255
ap-2 complex subunit sigma-1
P62744
2
Cluster2335
myosin-if
O00160
2
Cluster2337
adenylate kinase mitochondrial
Q1L8L9
2
Cluster2342
40s ribosomal protein s14
P62263
2
Cluster2345
apoptotic chromatin condensation inducer
Q9UKV3
2
Cluster244
MHC I-related gene protein
Q95460
1
Cluster2440
ubiquitin thioesterase otub1
Q96FW1
2
Cluster2466
nf-kappa-b inhibitor alpha
P25963
2
Cluster2474
toll-interacting protein
A2RUW1
2
Cluster2602
moesin
P26038
3
Cluster2612
beta-2-microglobulin
Q04475
3
Cluster265
myosin-9
P14105
1
Cluster2659
proteasome maturation protein
Q3SZV5
3
Cluster2663
apoptotic chromatin condensation inducer
Q9UKV3
3
Cluster2706
cd81 antigen
P35762
3
Cluster2717
complement -binding mitochondrial
Q07021
4
Cluster2828
integrin alpha-l
P24063
6
Cluster2869
moesin
P26038
8
Cluster2872
beta-2-microglobulin
O42197
8
Cluster2877
c-x-c chemokine receptor type 4
P61072
8
Cluster2908
fucolectin
Q7SIC1
12
Cluster311
proteasome subunit beta type-9
Q8UW64
1
Cluster33
inosine-5 -monophosphate dehydrogenase 1
P20839
1
Cluster490
paired box protein pax-5
Q02548
1
Cluster493
nucleosome assembly protein 1-like 1-a
Q4U0Y4
1
Cluster588
cysteine-rich protein 2
Q9DCT8
1
Cluster634
interleukin enhancer-binding factor 2 homolog
Q6NZ06
1
Cluster668
zinc finger e-box-binding homeobox 1
P36197
1
Cluster780
kinase catalytic subunit delta isoform
O35904
1
Cluster789
cd81 antigen
P35762
1
Cluster812
interferon regulatory factor 1
P15314
1
Cluster937
high mobility group protein b3
Q32L31
1
Cluster999 aminoacyl trna synthetase protein Q12904 1

[TableWrap ID: T4] Table 4 

Unigenes annotated with the GO term response to virus


Sequence name Sequence description Hit AC Clustered EST
Cluster2255
ap-2 complex subunit sigma-1
P62744
2
Cluster2287
interferon-induced gtp-binding protein
Q8JH68
2
Cluster2379
40s ribosomal protein s15a
P62244
2
Cluster2877 c-x-c chemokine receptor type 4 P61072 8

[TableWrap ID: T5] Table 5 

Unigenes annotated with the GO term response to bacterium


Sequence name Sequence description Hit AC Clustered EST
Cluster12
histone h2a
P02264
1
Cluster1225
endoplasmic reticulum aminopeptidase 1
Q9NZ08
1
Cluster1269
lysozyme c
P85045
1
Cluster1910
akirin-2
Q25C79
1
Cluster2173
phosphatidylinositol phosphodiesterase gamma-2
Q8CIH5
1
Cluster2335
myosin-if
O00160
2
Cluster2543
histone h1
P06350
2
Cluster2861
histone h1
P06350
7
Cluster566 histone h1 P06350 1

[TableWrap ID: T6] Table 6 

The most represented KEGG pathways in the unigene data set


Pathway Mapping genes Categories
Ribosome
60
Genetic Information Processing
Oxidative phosphorylation
53
Metabolism
Proteasome
32
Genetic Information Processing
Spliceosome
31
Genetic Information Processing
Lysosome
28
Cellular Processes
Purine metabolism
25
Metabolism
Endocytosis
24
Cellular Processes
Regulation of actin cytoskeleton
24
Cellular Processes
Cell cycle
19
Cellular Processes
Leukocyte transendothelial migration
18
Organismal Systems
Pyrimidine metabolism
17
Metabolism
MAPK signalling pathway
17
Environmental Information Processing
Antigen processing and presentation
17
Organismal Systems
Chemokine signalling pathway
17
Organismal Systems
Tight junction
16
Cellular Processes
T cell receptor signalling pathway 16 Organismal Systems

[TableWrap ID: T7] Table 7 

Mapping genes in fish primary non-specific immune pathways


Pathway Mapping genes Containing ESTs
Toll-like receptor signalling pathway
8
16
RIG-I-like receptor signalling pathway
11
20
NOD-like receptor signalling pathway 9 17

[TableWrap ID: T8] Table 8 

Differentially expressed unigenes annotated as immune-related


Sequence name Description log2Ratio (VP/CP) Up-Down
cichka_Cluster2189.seq. Contig1
ig heavy chain v-iii region cam
9.552669098
Up
cichka_Cluster2214.seq. Contig1
complement c3
−1.234417227
Down
cichka_Cluster2335.seq. Contig1
myosin-if
−1.616395009
Down
cichka_Cluster2337.seq. Contig1
adenylate kinase mitochondrial
−2.622261042
Down
cichka_Cluster2612.seq. Contig1
beta-2-microglobulin
14.96510786
Up
cichka_Cluster2717.seq. Contig1
complement -binding mitochondrial
2.831849484
Up
cichka_Cluster2828.seq. Contig1
integrin alpha-l
−3.476196501
Down
cichka_Cluster2872.seq. Contig1
beta-2-microglobulin
−2.257387843
Down
cichka_Cluster2877.seq. Contig1
c-x-c chemokine receptor type 4
−2.941536738
Down
cichka_Cluster2908.seq. Contig1
fucolectin
−3.57091306
Down
cichka_Cluster2379.seq. Contig1
40s ribosomal protein s15a
−2.133495724
Down
cichka_Cluster1269
lysozyme c
−5.60930435
Down
cichka_Cluster634
interleukin enhancer-binding factor 2 homolog
−8.383704292
Down
cichka_Cluster812
interferon regulatory factor 1
2.652601218
Up
cichka_Cluster1474
matrix metalloproteinase-9
−5.851050959
Down
cichka_Cluster1667 chemokine-like factor −8.189824559 Down

[TableWrap ID: T9] Table 9 

Potentially novel differentially expressed unigenes


Sequence name log2 Ratio(VP/CP) Up-Down
cichka_Cluster1
−1.30897451703681
Down
cichka_Cluster1004
−8.18982455888002
Down
cichka_Cluster1074
−4.68008319087111
Down
cichka_Cluster1080
1.5772610962369
Up
cichka_Cluster1095
1.70760741456741
Up
cichka_Cluster1139
−3.01282922395069
Down
cichka_Cluster1321
−1.17687776208408
Down
cichka_Cluster1418
2.57740490960702
Up
cichka_Cluster144
−2.37056287013824
Down
cichka_Cluster1502
−2.69938241135805
Down
cichka_Cluster153
9.00842862207058
Up
cichka_Cluster155
−4.35320513151951
Down
cichka_Cluster1567
−3.23219204494701
Down
cichka_Cluster1689
−1.24599865006401
Down
cichka_Cluster18
−8.55458885167764
Down
cichka_Cluster1830
5.67155018571725
Up
cichka_Cluster1847
−1.8154025874359
Down
cichka_Cluster19
−7.4998458870832
Down
cichka_Cluster1931
1.44222232860508
Up
cichka_Cluster2016
2.84923580318831
Up
cichka_Cluster2063
−3.29278174922784
Down
cichka_Cluster219
8.44708322620965
Up
cichka_Cluster2432.seq. Contig1
−1.12271915825313
Down
cichka_Cluster2506.seq. Contig1
−2.26096007759593
Down
cichka_Cluster2646.seq. Contig1
−8.18982455888002
Down
cichka_Cluster2651.seq. Contig1
−8.32192809488736
Down
cichka_Cluster2765.seq. Contig1
−8.38370429247405
Down
cichka_Cluster291
3.07771266869725
Up
cichka_Cluster2966.seq. Contig1
−5.46317402032312
Down
cichka_Cluster317
−2.29418310440446
Down
cichka_Cluster357
3.48529281620541
Up
cichka_Cluster468
−1.41853954357293
Down
cichka_Cluster482
1.43096228428556
Up
cichka_Cluster559
7.82654848729092
Up
cichka_Cluster613
−1.71345884128158
Down
cichka_Cluster619
−3.62148837674627
Down
cichka_Cluster625
1.46068016483455
Up
cichka_Cluster751
1.83711846346595
Up
cichka_Cluster788
1.13154390971446
Up
cichka_Cluster790
−5.47619650111671
Down
cichka_Cluster837
−2.25442127552909
Down
cichka_Cluster891 −1.33599920243744 Down

[TableWrap ID: T10] Table 10 

Ten most highly expressed unigenes in the head kidney of healthy grass carp


Sequence name ORF length Clustered ESTs Description
Cluster2971
159
1114
Unknown
Cluster2970
267
251
hybrid granulin
Cluster2969
132
166
hypothetical 18 K protein
Cluster2968
282
109
Unknown
Cluster2967
273
123
Unknown
Cluster2966
267
78
hypothetical protein
Cluster2965
132
85
Unknown
Cluster2964
0
83
Unknown
Cluster2963
279
63
Unknown
Cluster2962 108 55 Unknown


Article Categories:
  • Research Article

Keywords: Grass carp, Head kidney, cDNA, EST, Immune-related gene.

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