From an immunologist perspective, sharks are an important group of jawed cartilaginous fishes and survey of the public database revealed a great gap in availability of large-scale sequence data for the group of Chondrichthyans the elasmobranchs. In an attempt to bridge this deficit we generated the transcriptome from the spleen and kidney tissues (a total of 1,606,172 transcripts) of the shark, Chiloscyllium griseum using the Illumina HiSeq2000 platform. With a cut off of > = 300 bp and an expression value of >1RPKM we used 43,385 transcripts for BLASTX analysis which revealed 17,548 transcripts matching to the NCBI nr database with an E-value of < = 10?5 and similarity score of 40%. The longest transcript was 16,974 bases with matched to HECT domain containing E3 ubiqutin protein ligase. MEGAN4 annotation pipeline revealed immune and signalling pathways including cell adhesion molecules, cytokine-cytokine receptor interaction, T-cell receptor signalling pathway and chemokine signaling pathway to be highly expressed in spleen, while different metabolism pathways such as amino acid metabolism, carbohydrate metabolism, lipid metabolism and xenobiotic biodegradation were highly expressed in kidney. Few of the candidate genes were selected to analyze their expression levels in various tissues by real-time PCR and also localization of a receptor by in-situ PCR to validate the prediction. We also predicted the domains structures of some of the identified pattern recognition receptors, their phylogenetic relationship with lower and higher vertebrates and the complete downstream signaling mediators of classical dsRNA signaling pathway. The generated transcriptome will be a valuable resource to further genetic and genomic research in elasmobranchs.
References
[1]
Carroll RL (1988) Vertebrate paleontology and Evolution. Freeman, New York.
[2]
Inoue J, Donoghue PC, Yang Z (2010) The impact of the representation of fossil calibrations on Bayesian estimation of species divergence times. SystBiol 59: 74–89. doi: 10.1093/sysbio/syp078
[3]
Putnam NH, Butts T, Ferrier DE, Furlong RF, Hellsten U, et al. (2008) The amphioxus genome and the evolution of the chordate karyotype. Nature 453(7198): 1064–1071. doi: 10.1038/nature06967
[4]
Mattingly C, Parton A, Dowell L, Rafferty J, Barnes D (2004) Cell and molecular biology of marine elasmobranchs: Squalusacanthias and Raja erinacea. Zebrafish 1: 111–120. doi: 10.1089/zeb.2004.1.111
[5]
Hazon N, Wells A, Pillans RD, Good JP, Gary AW, et al. (2003) Urea based osmoregulation and endocrine control in elasmobranch fish with special reference to euryhalinity. Comp. Biochem. Physiol., Part B Biochem. Mol. Biol. 136: 685–700. doi: 10.1016/s1096-4959(03)00280-x
[6]
Litman GW, Anderson MK, Rast JP (1999) Evolution of antigen binding receptors. Annual review of immunology 17(1): 109–147. doi: 10.1146/annurev.immunol.17.1.109
[7]
Flajnik MF and Rumfelt LL (2000) The immune system of cartilaginous fish. In Origin and Evolution of the Vertebrate Immune System 249–270. Springer Berlin Heidelberg.
[8]
Litman GW, Rast JP, Fugmann SD (2010) The origins of vertebrate adaptive immunity. Nature Reviews Immunology 10(8): 543–553. doi: 10.1038/nri2807
[9]
Vera JC, Wheat CW, Fescemyer HW, Frilander MJ, Crawford DL, et al. (2008) Rapid transcriptome characterization for a non-model organism using 454 pyrosequencing. Molecular Ecology 17: 1636–1647. doi: 10.1111/j.1365-294x.2008.03666.x
[10]
Collins LJ, Biggs PJ, Voelckel C, Joly S (2008) An approach to transcriptome analysis of non-model organisms using short-read sequences. Genome Inform 21: 3–14. doi: 10.1142/9781848163324_0001
[11]
Morozova O, Marra MA (2008) Applications of next-generation sequencing technologies in functional genomics. Genomics 92(5): 255–264. doi: 10.1016/j.ygeno.2008.07.001
[12]
Morozova O, Hirst M, Marra MA (2009) Applications of new sequencing technologies for transcriptome analysis. Annual review of genomics and human genetics 10: 135–151. doi: 10.1146/annurev-genom-082908-145957
[13]
Wheat CW, Vogel H (2011) Transcriptome sequencing goals, assembly, and assessment. In Molecular Methods for Evolutionary Genetics 129–144. Humana Press.
[14]
Feldmeyer B, Wheat CW, Krezdorn N, Rotter B, Pfenninger M (2011) Short read Illumina data for the de novo assembly of a non-model snail species transcriptome (Radix balthica, Basommatophora, Pulmonata), and a comparison of assembler performance. BMC genomics, 12(1): , 317.
[15]
Zhang J, Jiang Y, Sun F, Zhang Y, Wang R, et al. (2012) Genomic Resources for Functional Genomics in Aquaculture Species, In: Functional Genomics in Aquaculture (eds M. Saroglia and Z. (. Liu), Wiley-Blackwell, Oxford, UK.
[16]
Ge G, Xiao P, Zhang Y, Yang L (2011) The first insight into the tissue specific taxus transcriptome via Illumina second generation sequencing. PLoSOne 6(6): e21220. doi: 10.1371/journal.pone.0021220
[17]
Hertzano R, Elkon R, Kurima K, Morrisson A, Chan SL, et al. (2011) Cell Type–Specific Transcriptome Analysis Reveals a Major Role for Zeb1 and miR-200b in Mouse Inner Ear Morphogenesis. PLoS genetics 7(9): e1002309. doi: 10.1371/journal.pgen.1002309
[18]
Surget-Groba Y, Montoya-Burgos JI (2010) Optimization of de novo transcriptome assembly from next-generation sequencing data. Genome Research 20(10): 1432–1440. doi: 10.1101/gr.103846.109
[19]
Chen M, Zou M, Yang L, He S (2012) Basal Jawed Vertebrate Phylogenomics Using Transcriptomic Data from Solexa Sequencing. PloS one 7(4): e36256. doi: 10.1371/journal.pone.0036256
[20]
Wang W, Li CY, Ge CT, Lei L, Gao YL, et al. (2013) De-novo characterization of the soft-shelled turtle Pelodiscussinensis transcriptome using Illumina RNA-Seq technology. Journal of Zhejiang University. Science B14(1): 58. doi: 10.1631/jzus.b1200219
[21]
Takechi M, Takeuchi M, Ota KG, Nishimura O, Mochii M, et al. (2011) Overview of the transcriptome profiles identified in hagfish, shark, and bichir: current issues arising from some nonmodel vertebrate taxa. J ExpZool B MolDevEvol 316: 526–546. doi: 10.1002/jez.b.21427
[22]
Li R, Yu C, Li Y, Lam YW, Yiu SM, et al. (2009) SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25: 1966–1967. doi: 10.1093/bioinformatics/btp336
[23]
Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10: R25. doi: 10.1186/gb-2009-10-3-r25
[24]
Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5: 621–628. doi: 10.1038/nmeth.1226
[25]
Gish W, States DJ (1993) Identification of protein coding regions by database similarity search. Nat Genet 3: 266–272. doi: 10.1038/ng0393-266
[26]
Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, et al. (2009) BLAST+: architecture and applications. BMC Bioinformatics 10: 421. doi: 10.1186/1471-2105-10-421
[27]
Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M (2012) KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 40: D109–114. doi: 10.1093/nar/gkr988
[28]
Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC (2011) Integrative analysis of environmental sequences using MEGAN4. Genome Res 21: 1552–1560. doi: 10.1101/gr.120618.111
[29]
Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11: R106. doi: 10.1186/gb-2010-11-10-r106
[30]
Tamura K, Peterson D, Peterson N, Stecher G, Nei M, et al. (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular biology and evolution 28(10): 2731–2739. doi: 10.1093/molbev/msr121
[31]
Anandhakumar C, Lavanya V, Pradheepa G, Tirumurugaan KG, Raj GD, et al. (2012) Expression profile of toll-like receptor 2 mRNA in selected tissues of shark (Chiloscyllium sp.). Fish & shellfish immunology 33(5): 1174–1182. doi: 10.1016/j.fsi.2012.09.007
[32]
Nykjaer A, Dragun D, Walther D, Vorum H, Jacobsen C, et al. (1999) An Endocytic Pathway Essential for Renal Uptake and Activation of the Steroid 25-(OH) Vitamin D3. Cell 96(4): 507–515. doi: 10.1016/s0092-8674(00)80655-8
[33]
Venkatesh B, Lee AP, Ravi V, Maurya AK, Lian MM, et al. (2014) Elephant shark genome provides unique insights into gnathostome evolution. Nature 505: 174–179. doi: 10.1038/nature12826
[34]
Tirumurugaan KG, Dhanasekaran S, Raj GD, Raja A, Kumanan K, et al. (2010) Differential expression of toll-like receptor mRNA in selected tissues of goat (Capra hircus). Vet Immunol Immunopathol 133: 296–301. doi: 10.1016/j.vetimm.2009.08.015
[35]
Swathi A, Raj GD, Raja A, Tirumurugaan KG (2013) Homology modeling and structural comparison of leucine rich repeats of toll like receptors 1–10 of ruminants. JMolModel 1-12; DOI 10.1007/s00894-013-1871-3.
[36]
Phelan PE, Mellon MT, Kim CH (2005) Functional characterization of full-length TLR3, IRAK-4, and TRAF6 in zebrafish (Danio rerio). Molecular immunology 42(9): 1057–1071. doi: 10.1016/j.molimm.2004.11.005
[37]
Rodriguez MF, Wiens GD, Purcell MK, Palti Y (2005) Characterization of Toll-like receptor 3 gene in rainbow trout (Oncorhynchus mykiss). Immunogenetics 57(7): 510–519. doi: 10.1007/s00251-005-0013-1
[38]
Baoprasertkul P, Peatman E, Somridhivej B, Liu Z (2006) Toll-like receptor 3 and TICAM genes in catfish: species-specific expression profiles following infection with Edwardsiella ictaluri. Immunogenetics 58(10): 817–830. doi: 10.1007/s00251-006-0144-z
[39]
Tsuboi N, Yoshikai Y, Matsuo S, Kikuchi T, Iwami K, et al. (2002) Roles of toll-like receptors in C-C chemokine production by renal tubular epithelial cells. J Immunol 169(4): 2026–2033. doi: 10.4049/jimmunol.169.4.2026
[40]
Mogensen TH (2009) Pathogen recognition and inflammatory signaling in innate immune defenses. Clinical microbiology reviews 22(2): 240–273. doi: 10.1128/cmr.00046-08
[41]
Benkert P, Biasini M, Schwede T (2011) Towards the estimation of the absolute quality of individual protein structure models. Bioinformatics (Oxford, England) 27(3): 343–350. doi: 10.1093/bioinformatics/btq662