Skip to main content
Log in

Guidelines for RNA-seq projects: applications and opportunities in non-model decapod crustacean species

  • CRUSTACEAN GENOMICS
  • Review Paper
  • Published:
Hydrobiologia Aims and scope Submit manuscript

Abstract

Next-generation sequencing (NGS) has dramatically changed the way biological research is being conducted in the post-genomic era, and they have only been utilized widely over the recent decade for studies of non-model decapod crustacean species, predominantly by sequencing the transcriptome of various tissues across different life stages. Next-generation sequencing can now provide a rapid, cost-effective solution for discovery of genetic markers crucial in many applications that would previously have otherwise taken years to develop. Sequencing of the entire transcriptome (referred to as RNA sequencing; RNA-seq) is one of the most popular NGS tools. RNA-seq studies of non-model species in crustacean taxa, however, have faced some problems, including a lack of “good” experimental study design, a relative paucity of gene annotations, combined with limited knowledge of genomic technologies and analyses. The aim of the current review is to assist crustacean biologists to develop a better appreciation for the applications and scope of RNA-seq analysis, understand the basic requirements for optimal RNA-seq studies and provide an overview of each step, from RNA-seq experimental design to bioinformatics approaches to data analysis. Insights that have resulted from RNA-seq studies across a wide range of non-model decapod species are also summarized.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Abbreviations

P. trituberculatus :

Portunus trituberculatus

S. henanense :

Sinopotamon henanense

P. vannamei :

Penaeus vannamei

P. monodon :

Penaeus monodon

M. japonicus :

Marsupenaeus japonicus

P. virginalis :

Procambarus virginalis or Procambarus fallax forma virginalis

S. olivacea :

Scylla olivacea

S. paramamosain :

Scylla paramamosain

E. sinensis :

Eriocheir sinensis

N. norvegicus :

Nephrops norvegicus

F. merguiensis :

Fenneropenaeus merguiensis

P. clarkii :

Procambrarus clarkii

M. rosenbergii :

Macrobrachium rosenbergii

S. verreauxi :

Sagmariasus verreauxi

N. denticulata :

Neocaridina denticulata

P. hawaiensis :

Parhyale hawaiensis

E. carinicauda :

Exopalaemon carinicauda

M. olfersi :

Macrobrachium olfersi

P. elegans :

Palaemon elegans

P. australiensis :

Paratya australiensis

H. rubra :

Halocaridina rubra

References

  • Amin, S., P. Prentis, E. Gilding & A. Pavasovic, 2014. Assembly and annotation of a non-model gastropod (Nerita melanotragus) transcriptome: a comparison of De novo assemblers. BMC Research Notes 7(1): 488.

    PubMed  PubMed Central  Google Scholar 

  • Anders, S. & W. Huber, 2012. Differential expression of RNA-Seq data at the gene level–the DESeq package. European Molecular Biology Laboratory, Heidelberg.

    Google Scholar 

  • Anders, S., P. T. Pyl & W. Huber, 2015. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics 31(2): 166–169.

    CAS  PubMed  Google Scholar 

  • Anvar, S., L. Khachatryan, M. Vermaat, M. van Galen, I. Pulyakhina, Y. Ariyurek, K. Kraaijeveld, J. den Dunnen & P. de Knijff, 2014. Determining the quality and complexity of next-generation sequencing data without a reference genome. Genome Biology 15(12): 555.

    PubMed  PubMed Central  Google Scholar 

  • Auer, P. L. & R. W. Doerge, 2010. Statistical design and analysis of RNA sequencing data. Genetics 185(2): 405–416.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Aziz, D., V. T. Nguyen, M. L. Rahi, D. A. Hurwood & P. B. Mather, 2017. Identification of genes that potentially affect social dominance hierarchy in adult male giant freshwater prawns (Macrobrachium rosenbergii). Aquaculture 476: 168–184.

    CAS  Google Scholar 

  • Bain, P. A., A. L. Gregg & A. Kumar, 2016. De novo assembly and analysis of changes in the protein-coding transcriptome of the freshwater shrimp Paratya australiensis (Decapoda: Atyidae) in response to acid sulfate drainage water. BMC Genomics 17(1): 890.

    PubMed  PubMed Central  Google Scholar 

  • Baruzzo, G., K. E. Hayer, E. J. Kim, B. Di Camillo, G. A. FitzGerald & G. R. Grant, 2017. Simulation-based comprehensive benchmarking of RNA-seq aligners. Nature Methods 14(2): 135–139.

    CAS  PubMed  Google Scholar 

  • Ben, L., 2010. Aligning Short Sequencing Reads with Bowtie. Current Protocols in Bioinformatics. https://doi.org/10.1002/0471250953.bi1107s32.

    Article  Google Scholar 

  • Bolger, A. M., M. Lohse & B. Usadel, 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btu170.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bray, N. L., H. Pimentel, P. Melsted & L. Pachter, 2016. Near-optimal probabilistic RNA-seq quantification. Nature Biotechnology 34(5): 525–527.

    CAS  PubMed  Google Scholar 

  • Busby, M. A., C. Stewart, C. A. Miller, K. R. Grzeda & G. T. Marth, 2013. Scotty: a web tool for designing RNA-Seq experiments to measure differential gene expression. Bioinformatics 29(5): 656–657.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Camacho, C., G. Coulouris, V. Avagyan, N. Ma, J. Papadopoulos, K. Bealer & T. L. Madden, 2009. BLAST+: architecture and applications. BMC Bioinformatics 10: 421.

    PubMed  PubMed Central  Google Scholar 

  • Cao, J., L. Wu, M. Jin, T. Li, K. Hui & Q. Ren, 2017. Transcriptome profiling of the Macrobrachium rosenbergii lymphoid organ under the white spot syndrome virus challenge. Fish & Shellfish Immunology 67: 27–39.

    CAS  Google Scholar 

  • Cartolano, M., B. Huettel, B. Hartwig, R. Reinhardt & K. Schneeberger, 2016. cDNA library enrichment of full length transcripts for SMRT long read sequencing. PLoS ONE 11(6): e0157779.

    PubMed  PubMed Central  Google Scholar 

  • Catchen, J. M., A. Amores, P. Hohenlohe, W. Cresko & J. H. Postlethwait, 2011. Stacks: building and genotyping loci de novo from short-read sequences. G3: Genes, Genomes. Genetics 1(3): 171–182.

    CAS  Google Scholar 

  • Chakrapani, V., S. K. Patra, S. D. Mohapatra, K. D. Rasal, U. Deshpande, S. Nayak, J. K. Sundaray, P. Jayasankar & H. K. Barman, 2016. Comparative transcriptomic profiling of larvae and post-larvae of Macrobrachium rosenbergii in response to metamorphosis and salinity exposure. Genes & Genomics 38(11): 1061–1076.

    CAS  Google Scholar 

  • Chandler, J. C., J. Aizen, Q. P. Fitzgibbon, A. Elizur & T. Ventura, 2016. Applying the power of transcriptomics: understanding male sexual development in Decapod Crustacea. Integrative and Comparative Biology 56(6): 1144–1156.

    CAS  PubMed  Google Scholar 

  • Chandramohan, R., P. Y. Wu, J. H. Phan & M. D. Wang, 2013. Systematic assessment of RNA-Seq quantification tools using simulated sequence data. ACM Conference on Bioinformatics, Computational Biology and Biomedicine. https://doi.org/10.1145/2506583.2506648.

    Article  Google Scholar 

  • Chang, Z., G. Li, J. Liu, Y. Zhang, C. Ashby, D. Liu, C. Cramer & X. Huang, 2015. Bridger: a new framework for de novo transcriptome assembly using RNA-seq data. Genome Biology 16(1): 30.

    PubMed  PubMed Central  Google Scholar 

  • Chen, S.-Y., F. Deng, X. Jia, C. Li & S.-J. Lai, 2017. A transcriptome atlas of rabbit revealed by PacBio single-molecule long-read sequencing. Scientific Reports 7(1): 7648.

    PubMed  PubMed Central  Google Scholar 

  • Chen, K., E. Li, T. Li, C. Xu, X. Wang, H. Lin, J. G. Qin & L. Chen, 2015. Transcriptome and molecular pathway analysis of the hepatopancreas in the Pacific White Shrimp Litopenaeus vannamei under chronic low-salinity stress. PLoS ONE 10(7): e0131503.

    PubMed  PubMed Central  Google Scholar 

  • Clark, K. F. & S. J. Greenwood, 2016. Next-Generation Sequencing and the crustacean immune system: the need for alternatives in immune gene annotation. Integrative and Comparative Biology 56(6): 1113–1130.

    CAS  PubMed  Google Scholar 

  • Conesa, A., S. Gotz, J. M. Garcia-Gomez, J. Terol, M. Talon & M. Robles, 2005. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21(18): 3674–3676.

    CAS  PubMed  Google Scholar 

  • Conesa, A., P. Madrigal, S. Tarazona, D. Gomez-Cabrero, A. Cervera, A. McPherson, M. W. Szcześniak, D. J. Gaffney, L. L. Elo, X. Zhang & A. Mortazavi, 2016. A survey of best practices for RNA-seq data analysis. Genome Biology 17(1): 13.

    PubMed  PubMed Central  Google Scholar 

  • Cui, Z., X. Li, Y. Liu, C. Song, M. Hui, G. Shi, D. Luo & Y. Li, 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.

    PubMed  PubMed Central  Google Scholar 

  • Das, S. & D. L. Mykles, 2016. A comparison of resources for the annotation of a de novo assembled transcriptome in the molting gland (Y-Organ) of the Blackback Land Crab, Gecarcinus lateralis. Integrative and Comparative Biology 56(6): 1103–1112.

    CAS  PubMed  Google Scholar 

  • Das, S., S. Shyamal & D. S. Durica, 2016. Analysis of annotation and differential expression methods used in RNA-seq Studies in crustacean systems. Integrative and Comparative Biology 56(6): 1067–1079.

    CAS  PubMed  Google Scholar 

  • Dillies, M.-A., A. Rau, J. Aubert, C. Hennequet-Antier, M. Jeanmougin, N. Servant, C. Keime, G. Marot, D. Castel, J. Estelle, G. Guernec, B. Jagla, L. Jouneau, D. Laloë, C. Le Gall, B. Schaëffer, S. Le Crom, M. Guedj & F. Jaffrézic, 2013. A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Briefings in Bioinformatics 14(6): 671–683.

    CAS  PubMed  Google Scholar 

  • Du, Z., Y. Jin & D. Ren, 2016. In-depth comparative transcriptome analysis of intestines of red swamp crayfish, Procambarus clarkii, infected with WSSV. Scientific reports 6: 26780.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Everaert, C., M. Luypaert, J. L. V. Maag, Q. X. Cheng, M. E. Dinger, J. Hellemans & P. Mestdagh, 2017. Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data. Scientific Reports 7: 1559.

    PubMed  PubMed Central  Google Scholar 

  • Ewing, B., L. Hillier, M. C. Wendl & P. Green, 1998. Base-calling of automated sequencer traces using Phred. I. Accuracy assessment. Genome Research 8(3): 175–185.

    CAS  PubMed  Google Scholar 

  • Del Fabbro, C., S. Scalabrin, M. Morgante & F. M. Giorgi, 2013. An extensive evaluation of read trimming effects on Illumina NGS data analysis. PLoS ONE 8(12): e85024.

    PubMed  PubMed Central  Google Scholar 

  • Fang, Z. & X. Cui, 2011. Design and validation issues in RNA-seq experiments. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbr004.

    Article  PubMed  Google Scholar 

  • Feng, J., C. A. Meyer, Q. Wang, J. S. Liu, X. Shirley Liu & Y. Zhang, 2012. GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data. Bioinformatics 28(21): 2782–2788.

    CAS  PubMed  Google Scholar 

  • Finn, R. D., P. Coggill, R. Y. Eberhardt, S. R. Eddy, J. Mistry, A. L. Mitchell, S. C. Potter, M. Punta, M. Qureshi, A. Sangrador-Vegas, G. A. Salazar, J. Tate & A. Bateman, 2016. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Research 44(D1): D279–D285.

    CAS  PubMed  Google Scholar 

  • Finseth, F. R. & R. G. Harrison, 2014. A comparison of Next Generation Sequencing technologies for transcriptome assembly and utility for RNA-Seq in a non-model bird. PLoS ONE 9(10): e108550.

    PubMed  PubMed Central  Google Scholar 

  • Fonseca, N. A., J. Rung, A. Brazma & J. C. Marioni, 2012. Tools for mapping high-throughput sequencing data. Bioinformatics. https://doi.org/10.1093/bioinformatics/bts605.

    Article  PubMed  Google Scholar 

  • Francis, W. R., L. M. Christianson, R. Kiko, M. L. Powers, N. C. Shaner & S. H. Haddock, 2013. A comparison across non-model animals suggests an optimal sequencing depth for de novo transcriptome assembly. BMC Genomics 14(1): 167.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gao, J., X. Wang, Z. Zou, X. Jia, Y. Wang & Z. Zhang, 2014. Transcriptome analysis of the differences in gene expression between testis and ovary in green mud crab (Scylla paramamosain). BMC Genomics 15: 585.

    PubMed  PubMed Central  Google Scholar 

  • Gao, Y., J. Wei, J. Yuan, X. Zhang, F. Li & J. Xiang, 2017. Transcriptome analysis on the exoskeleton formation in early developmetal stages and reconstruction scenario in growth-moulting in Litopenaeus vannamei. Scientific reports 7(1): 1098.

    PubMed  PubMed Central  Google Scholar 

  • Ge, Q., J. Li, J. Wang, J. Li, H. Ge & Q. Zhai, 2017. Transcriptome analysis of the hepatopancreas in Exopalaemon carinicauda infected with an AHPND-causing strain of Vibrio parahaemolyticus. Fish & Shellfish Immunology 67: 620–633.

    CAS  Google Scholar 

  • Ghangal, R., S. Chaudhary, M. Jain, R. S. Purty & P. Chand Sharma, 2013. Optimization of De Novo short read assembly of Seabuckthorn Hippophae rhamnoides L. transcriptome. PLoS ONE 8(8): e72516.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Glenn, T. C., 2011. Field guide to next-generation DNA sequencers. Molecular Ecology Resources 11(5): 759–769.

    CAS  PubMed  Google Scholar 

  • Goodwin, S., J. D. McPherson & W. R. McCombie, 2016. Coming of age: ten years of Next Generation Sequencing technologies. Nature Reviews Genetics 17(6): 333–351.

    CAS  PubMed  Google Scholar 

  • Grabherr, M., B. Haas, M. Yassour, J. Levin, D. Thompson, I. Amit, X. Adiconis, L. Fan, R. Raychowdhury, Q. Zeng, Z. Chen, E. Mauceli, N. Hacohen, A. Gnirke, N. Rhind, F. di Palma, B. Birren, C. Nusbaum, K. Lindblad-Toh, N. Friedman & A. Regev, 2011. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology 29(7): 644–652.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Grant, G. R., M. H. Farkas, A. D. Pizarro, N. F. Lahens, J. Schug, B. P. Brunk, C. J. Stoeckert, J. B. Hogenesch & E. A. Pierce, 2011. Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM). Bioinformatics 27(18): 2518–2528.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Gutekunst, J., R. Andriantsoa, C. Falckenhayn, K. Hanna, W. Stein, J. Rasamy & F. Lyko, 2018. Clonal genome evolution and rapid invasive spread of the marbled crayfish. Nature Ecology & Evolution 2(3): 567–573.

    Google Scholar 

  • Haas, B. J., A. Papanicolaou, M. Yassour, M. Grabherr, P. D. Blood, J. Bowden, M. B. Couger, D. Eccles, B. Li, M. Lieber, M. D. MacManes, M. Ott, J. Orvis, N. Pochet, F. Strozzi, N. Weeks, R. Westerman, T. William, C. N. Dewey, R. Henschel, R. D. LeDuc, N. Friedman & A. Regev, 2013. De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity. Nature Protocols. https://doi.org/10.1038/nprot.2013.084.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hardcastle, T. J. & K. A. Kelly, 2010. BaySeq: empirical Bayesian methods for identifying differential expressions in sequence count data. BMC bioinformatics 11(1): 422.

    PubMed  PubMed Central  Google Scholar 

  • Hatem, A., D. Bozdağ, A. E. Toland & Ü. V. Çatalyürek, 2013. Benchmarking short sequence mapping tools. BMC Bioinformatics 14(1): 184.

    PubMed  PubMed Central  Google Scholar 

  • Havird, J. C., R. T. Mitchell, R. P. Henry & S. R. Santos, 2016. Salinity-induced changes in gene expression from anterior and posterior gills of Callinectes sapidus (Crustacea: Portunidae) with implications for crustacean ecological genomics. Comparative biochemistry and physiology Part D, Genomics & proteomics 19: 34–44.

    CAS  Google Scholar 

  • Havird, J. C. & S. R. Santos, 2016a. Here we are, but where do we go? A systematic review of crustacean transcriptomic studies from 2014–2015. Integrative and Comparative Biology 56(6): 1055–1066.

    PubMed  PubMed Central  Google Scholar 

  • Havird, J. C. & S. R. Santos, 2016b. Developmental Transcriptomics of the Hawaiian Anchialine Shrimp Halocaridina rubra Holthuis, 1963 (Crustacea: Atyidae). Integr Comp Biol 56(6): 1170–1182.

    CAS  PubMed  PubMed Central  Google Scholar 

  • da Huang, W., B. T. Sherman & R. A. Lempicki, 2009. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4(1): 44–57.

    CAS  Google Scholar 

  • Huerta-Cepas, J., D. Szklarczyk, K. Forslund, H. Cook, D. Heller, M. C. Walter, T. Rattei, D. R. Mende, S. Sunagawa & M. Kuhn, 2015. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Research 44(D1): D286–D293.

    PubMed  PubMed Central  Google Scholar 

  • Hui, M., Z. Cui, Y. Liu & C. Song, 2017. Transcriptome profiles of embryos before and after cleavage in Eriocheir sinensis: identification of developmental genes at the earliest stages. Chinese Journal of Oceanology and Limnology 35(4): 770–781.

    CAS  Google Scholar 

  • Jaramillo, M. L., F. Guzman, C. L. Paese, R. Margis, E. M. Nazari, D. Ammar & Y. M. R. Müller, 2016. Exploring developmental gene toolkit and associated pathways in a potential new model crustacean using transcriptomic analysis. Development Genes and Evolution 226(5): 325–337.

    CAS  PubMed  Google Scholar 

  • Jin, S., H. Fu, Q. Zhou, S. Sun, S. Jiang, Y. Xiong, Y. Gong, H. Qiao & W. Zhang, 2013. Transcriptome analysis of androgenic gland for discovery of novel genes from the oriental river prawn, Macrobrachium nipponense, using Illumina Hiseq 2000. PloS one 8(10): e76840.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Jones, P., D. Binns, H.-Y. Chang, M. Fraser, W. Li, C. McAnulla, H. McWilliam, J. Maslen, A. Mitchell, G. Nuka, S. Pesseat, A. F. Quinn, A. Sangrador-Vegas, M. Scheremetjew, S.-Y. Yong, R. Lopez & S. Hunter, 2014. InterProScan 5: genome-scale protein function classification. Bioinformatics 30(9): 1236–1240.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Jung, H., R. E. Lyons, H. Dinh, D. A. Hurwood, S. McWilliam & P. B. Mather, 2011. Transcriptomics of a Giant Freshwater Prawn (Macrobrachium rosenbergii): de novo assembly, annotation and marker discovery. PLoS ONE 6(12): e27938.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Jung, H., B.-H. Yoon, W.-J. Kim, D.-W. Kim, D. Hurwood, R. Lyons, K. Salin, H.-S. Kim, I. Baek, V. Chand & P. Mather, 2016. Optimizing hybrid de novo transcriptome assembly and extending genomic resources for Giant Freshwater Prawns (Macrobrachium rosenbergii): the identification of genes and markers associated with reproduction. International Journal of Molecular Sciences 17(5): 690.

    PubMed Central  Google Scholar 

  • Kanehisa, M. & S. Goto, 2000. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research 28(1): 27–30.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Kao, D., A. G. Lai, E. Stamataki, S. Rosic, N. Konstantinides, E. Jarvis, A. Di Donfrancesco, N. Pouchkina-Stancheva, M. Sémon, M. Grillo, H. Bruce, S. Kumar, I. Siwanowicz, A. Le, A. Lemire, M. B. Eisen, C. Extavour, W. E. Browne, C. Wolff, M. Averof, N. H. Patel, P. Sarkies, A. Pavlopoulos & A. Aboobaker, 2016. The genome of the crustacean Parhyale hawaiensis, a model for animal development, regeneration, immunity and lignocellulose digestion. eLife 5: e20062.

    PubMed  PubMed Central  Google Scholar 

  • Kelley, D. R., M. C. Schatz & S. L. Salzberg, 2010. Quake: quality-aware detection and correction of sequencing errors. Genome Biology 11(11): R116.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Kenny, N. J., Y. W. Sin, X. Shen, Q. Zhe, W. Wang, T. F. Chan, S. S. Tobe, S. M. Shimeld, K. H. Chu & J. H. Hui, 2014. Genomic sequence and experimental tractability of a new decapod shrimp model. Neocaridina denticulata. Marine Drugs 12(3): 1419–1437.

    CAS  PubMed  Google Scholar 

  • Khang, T. F. & C. Y. Lau, 2015. Getting the most out of RNA-seq data analysis. PeerJ 3: e1360.

    PubMed  PubMed Central  Google Scholar 

  • Koboldt, Daniel C., Karyn M. Steinberg, David E. Larson, Richard K. Wilson & E. R. Mardis, 2013. The next-generation sequencing revolution and its impact on genomics. Cell 155(1): 27–38.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Kuo, R. I., E. Tseng, L. Eory, I. R. Paton, A. L. Archibald & D. W. Burt, 2017. Normalized long read RNA sequencing in chicken reveals transcriptome complexity similar to human. BMC Genomics 18(1): 323.

    PubMed  PubMed Central  Google Scholar 

  • Kvam, V. M., P. Liu & Y. Si, 2012. A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data. American Journal of Botany 99(2): 248–256.

    PubMed  Google Scholar 

  • Lahens, N. F., E. Ricciotti, O. Smirnova, E. Toorens, E. J. Kim, G. Baruzzo, K. E. Hayer, T. Ganguly, J. Schug & G. R. Grant, 2017. A comparison of Illumina and Ion Torrent sequencing platforms in the context of differential gene expression. BMC Genomics 18(1): 602.

    PubMed  PubMed Central  Google Scholar 

  • Lam, H. Y. K., M. J. Clark, R. Chen, R. Chen, G. Natsoulis, M. O’Huallachain, F. E. Dewey & L. Habegger, 2012. Performance comparison of whole-genome sequencing platforms. Nature Biotechnology. https://doi.org/10.1038/nbt.2065.

    Article  PubMed  PubMed Central  Google Scholar 

  • Langmead, B. & S. L. Salzberg, 2012. Fast gapped-read alignment with Bowtie 2. Nature Methods 9(4): 357–359.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Langmead, B., C. Trapnell, M. Pop & S. L. Salzberg, 2009. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biology 10(3): R25.

    PubMed  PubMed Central  Google Scholar 

  • Ledergerber, C. & C. Dessimoz, 2011. Base-calling for next-generation sequencing platforms. Briefings in Bioinformatics 12(5): 489–497.

    PubMed  PubMed Central  Google Scholar 

  • Lee, H. K., W. Braynen, K. Keshav & P. Pavlidis, 2005. ErmineJ: tool for functional analysis of gene expression data sets. BMC Bioinformatics 6(1): 269.

    PubMed  PubMed Central  Google Scholar 

  • Levin, J. Z., M. Yassour, X. Adiconis, C. Nusbaum, D. A. Thompson, N. Friedman, A. Gnirke & A. Regev, 2010. Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nature Methods 7(9): 709–715.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Li, Z., Y. Chen, D. Mu, J. Yuan, Y. Shi, H. Zhang, J. Gan, N. Li, X. Hu, B. Liu, B. Yang & W. Fan, 2012. Comparison of the two major classes of assembly algorithms: overlap-layout-consensus and de-Bruijn-graph. Briefings in Functional Genomics 11(1): 25–37.

    PubMed  Google Scholar 

  • Li, B. & C. N. Dewey, 2011. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12: 323.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Li, H. & R. Durbin, 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14): 1754–1760.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Li, H. & N. Homer, 2010. A survey of sequence alignment algorithms for next-generation sequencing. Briefings in Bioinformatics 11(5): 473–483.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Li, B., N. Fillmore, Y. Bai, M. Collins, J. A. Thomson, R. Stewart & C. N. Dewey, 2014. Evaluation of de novo transcriptome assemblies from RNA-Seq data. Genome Biology 15(12): 553. https://doi.org/10.1186/s13059-014-0553-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li, Y., M. Hui, Z. Cui, Y. Liu, C. Song & G. Shi, 2015. Comparative transcriptomic analysis provides insights into the molecular basis of the metamorphosis and nutrition metabolism change from zoeae to megalopae in Eriocheir sinensis. Comparative Biochemistry and Physiology Part D: Genomics and Proteomics 13: 1–9.

    Google Scholar 

  • Li, Y., S. Lai, R. Wang, Y. Zhao, H. Qin, L. Jiang, N. Li, Q. Fu & C. Li, 2017. RNA-Seq analysis of the antioxidant status and immune response of Portunus trituberculatus following aerial exposure. Marine Biotechnology 19(1): 89–101.

    CAS  PubMed  Google Scholar 

  • Li, R., Y. Li, K. Kristiansen & J. Wang, 2008. SOAP: short oligonucleotide alignment program. Bioinformatics 24(5): 713–714.

    CAS  PubMed  Google Scholar 

  • Li, E., S. Wang, C. Li, X. Wang, K. Chen & L. Chen, 2014. Transcriptome sequencing revealed the genes and pathways involved in salinity stress of Chinese mitten crab, Eriocheir sinensis. Physiological Genomics. https://doi.org/10.1152/physiolgenomics.00191.2013.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lister, R., B. D. Gregory & J. R. Ecker, 2009. Next is now: new technologies for sequencing of genomes, transcriptomes, and beyond. Current Opinion in Plant Biology 12(2): 107–118.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Liu, S., G. Chen, H. Xu, W. Zou, W. Yan, Q. Wang, H. Deng, H. Zhang, G. Yu, J. He & S. Weng, 2017. Transcriptome analysis of mud crab (Scylla paramamosain) gills in response to Mud crab reovirus (MCRV). Fish & Shellfish Immunology 60: 545–553.

    CAS  Google Scholar 

  • Liu, Y., M. Hui, Z. Cui, D. Luo, C. Song, Y. Li & L. Liu, 2015. Comparative transcriptome analysis reveals sex-biased gene expression in juvenile Chinese Mitten Crab Eriocheir sinensis. PLoS ONE 10(7): e0133068.

    PubMed  PubMed Central  Google Scholar 

  • Liu, L., Y. Li, S. Li, N. Hu, Y. He, R. Pong, D. Lin, L. Lu & M. Law, 2012. Comparison of next-generation sequencing systems. Journal of Biomedicine and Biotechnology 2012: 11.

    Google Scholar 

  • Liu, Y., J. Zhou & K. P. White, 2014. RNA-seq differential expression studies: more sequence or more replication? Bioinformatics 30(3): 301–304.

    CAS  PubMed  Google Scholar 

  • Lo, C. C. & P. S. Chain, 2014. Rapid evaluation and quality control of next generation sequencing data with FaQCs. BMC bioinformatics 15(1): 366.

    PubMed  PubMed Central  Google Scholar 

  • Love, M. I., W. Huber & S. Anders, 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15(12): 550.

    PubMed  PubMed Central  Google Scholar 

  • Lu, X., J. Kong, S. Luan, P. Dai, X. Meng, B. Cao & K. Luo, 2016. Transcriptome analysis of the hepatopancreas in the Pacific White Shrimp (Litopenaeus vannamei) under acute Ammonia stress. PLoS ONE 11(10): e0164396.

    PubMed  PubMed Central  Google Scholar 

  • Lv, J., P. Liu, B. Gao, Y. Wang, Z. Wang, P. Chen & J. Li, 2014. Transcriptome analysis of the Portunus trituberculatus: de novo assembly, growth-related gene identification and marker discovery. PLoS One 9(4): e94055.

    PubMed  PubMed Central  Google Scholar 

  • Lv, J., P. Liu, Y. Wang, B. Gao, P. Chen & J. Li, 2013. Transcriptome analysis of Portunus trituberculatus in response to salinity stress provides insights into the molecular basis of osmoregulation. PLoS ONE 8(12): e82155.

    PubMed  PubMed Central  Google Scholar 

  • Lv, J., L. Zhang, P. Liu & J. Li, 2017. Transcriptomic variation of eyestalk reveals the genes and biological processes associated with molting in Portunus trituberculatus. PLoS ONE 12(4): e0175315.

    PubMed  PubMed Central  Google Scholar 

  • MacManes, M. D., 2014. On the optimal trimming of high-throughput mRNA sequence data. Frontiers in Genetics 5: 13.

    PubMed  PubMed Central  Google Scholar 

  • Macharia, R. W., F. L. Ombura & E. O. Aroko, 2015. Insects RNA profiling reveals absence of hidden break in 28S Ribosomal RNA molecule of Onion Thrips, Thrips tabaci. Journal of Nucleic Acids 2015: 8.

    Google Scholar 

  • Marguerat, S. & J. Bähler, 2010. RNA-seq: from technology to biology. Cellular and Molecular Life Sciences 67(4): 569–579.

    CAS  PubMed  Google Scholar 

  • Martin, M., 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet journal 17(1): 10–12.

    Google Scholar 

  • McCarthy, S. D., M. M. Dugon & A. M. Power, 2015. ‘Degraded’ RNA profiles in Arthropoda and beyond. PeerJ 3: e1436.

    PubMed  PubMed Central  Google Scholar 

  • Meng, X.-L., P. Liu, F.-L. Jia, J. Li & B.-Q. Gao, 2015. De novo transcriptome analysis of Portunus trituberculatus ovary and testis by RNA-Seq: identification of genes involved in gonadal development. PLoS ONE 10(6): e0128659.

    PubMed  PubMed Central  Google Scholar 

  • Metzker, M. L., 2010. Sequencing technologies—the next generation. Nature Reviews Genetics 11(1): 31–46.

    CAS  PubMed  Google Scholar 

  • Miller, J. R., S. Koren & G. Sutton, 2010. Assembly algorithms for next-generation sequencing data. Genomics 95(6): 315–327.

    CAS  PubMed  Google Scholar 

  • Misner, I., C. Bicep, P. Lopez, S. Halary, E. Bapteste & C. E. Lane, 2013. Sequence comparative analysis using networks: software for evaluating de novo transcript assembly from Next-Generation Sequencing. Molecular Biology and Evolution 30(8): 1975–1986.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Moshtaghi, A., M. L. Rahi, P. B. Mather & D. A. Hurwood, 2017. Understanding the Genomic Basis of Adaptive Response to Variable Osmotic Niches in Freshwater Prawns: a Comparative Intraspecific RNA-Seq Analysis of Macrobrachium australiense. J Hered 108(5): 544–552.

    PubMed  Google Scholar 

  • Moshtaghi, A., M. L. Rahi, V. T. Nguyen, P. B. Mather & D. A. Hurwood, 2016. A transcriptomic scan for potential candidate genes involved in osmoregulation in an obligate freshwater palaemonid prawn (Macrobrachium australiense). PeerJ 4: e2520.

    PubMed  PubMed Central  Google Scholar 

  • Mykles, D. L., K. G. Burnett, D. S. Durica, B. L. Joyce, F. M. McCarthy, C. J. Schmidt & J. H. Stillman, 2016. Resources and recommendations for using transcriptomics to address grand challenges in comparative biology. Integrative and Comparative Biology 56(6): 1183–1191.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mykles, D. L. & J. H. Hui, 2015. Neocaridina denticulata: a decapod crustacean model for Functional Genomics. Integrative and Comparative Biology 55(5): 891–897.

    PubMed  Google Scholar 

  • Nguyen, C., T. G. Nguyen, L. Van Nguyen, H. Q. Pham, T. H. Nguyen, H. T. Pham, H. T. Nguyen, T. T. Ha, T. H. Dau & H. T. Vu, 2016. De novo assembly and transcriptome characterization of major growth-related genes in various tissues of Penaeus monodon. Aquaculture 464: 545–553.

    CAS  Google Scholar 

  • Niedringhaus, T. P., D. Milanova, M. B. Kerby, M. P. Snyder & A. E. Barron, 2011. Landscape of Next-Generation Sequencing technologies. Analytical Chemistry 83(12): 4327–4341.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Olsvik, P. A., B. T. Lunestad, A. L. Agnalt & O. B. Samuelsen, 2017. Impact of teflubenzuron on the rockpool shrimp (Palaemon elegans). Comparative Biochemistry and Physiology Toxicology & Pharmacology 201: 35–43.

    CAS  Google Scholar 

  • Ozsolak, F. & P. M. Milos, 2011. RNA sequencing: advances, challenges and opportunities. Nature Reviews Genetics 12(2): 87–98.

    CAS  PubMed  Google Scholar 

  • Parkhomchuk, D., T. Borodina, V. Amstislavskiy, M. Banaru, L. Hallen, S. Krobitsch, H. Lehrach & A. Soldatov, 2009. Transcriptome analysis by strand-specific sequencing of complementary DNA. Nucleic Acids Research 37(18): e123.

    PubMed  PubMed Central  Google Scholar 

  • Parra, G., K. Bradnam & I. Korf, 2007. CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics 23(9): 1061–1067.

    CAS  PubMed  Google Scholar 

  • Patel, R. K. & M. Jain, 2012. NGS QC Toolkit: a Toolkit for quality control of next generation sequencing data. PLoS ONE 7(2): e30619.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Patro, R., G. Duggal, M. I. Love, R. A. Irizarry & C. Kingsford, 2017. Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods. https://doi.org/10.1038/nmeth.4197.

    Article  PubMed  PubMed Central  Google Scholar 

  • Peng, J., P. Wei, B. Zhang, Y. Zhao, D. Zeng, X. Chen, M. Li & X. Chen, 2015. Gonadal transcriptomic analysis and differentially expressed genes in the testis and ovary of the Pacific white shrimp (Litopenaeus vannamei). BMC Genomics 16: 1006.

    PubMed  PubMed Central  Google Scholar 

  • Powell, D., W. Knibb, N. H. Nguyen & A. Elizur, 2016. Transcriptional profiling of Banana Shrimp Fenneropenaeus merguiensis with differing levels of viral load. Integrative and Comparative Biology. https://doi.org/10.1093/icb/icw029.

    Article  PubMed  Google Scholar 

  • Qiao, H., H. Fu, Y. Xiong, S. Jiang, W. Zhang, S. Sun, S. Jin, Y. Gong, Y. Wang, D. Shan, F. Li & Y. Wu, 2017. Molecular insights into reproduction regulation of female Oriental River prawns Macrobrachium nipponense through comparative transcriptomic analysis. Scientific reports 7(1): 12161.

    PubMed  PubMed Central  Google Scholar 

  • Rahi, M. L., S. Amin, P. B. Mather & D. A. Hurwood, 2017. Candidate genes that have facilitated freshwater adaptation by palaemonid prawns in the genus Macrobrachium: identification and expression validation in a model species (M. koombooloomba). PeerJ 5: 2977.

    Google Scholar 

  • Rajkumar, A. P., P. Qvist, R. Lazarus, F. Lescai, J. Ju, M. Nyegaard, O. Mors, A. D. Børglum, Q. Li & J. H. Christensen, 2015. Experimental validation of methods for differential gene expression analysis and sample pooling in RNA-seq. BMC Genomics 16(1): 548.

    PubMed  PubMed Central  Google Scholar 

  • Rao, R., Y. B. Zhu, T. Alinejad, S. Tiruvayipati, K. L. Thong, J. Wang & S. Bhassu, 2015. RNA-seq analysis of Macrobrachium rosenbergii hepatopancreas in response to Vibrio parahaemolyticus infection. Gut Pathogens 7(1): 1.

    Google Scholar 

  • Ren, Q. & L. Pan, 2014. Digital gene expression analysis in the gills of the swimming crab (Portunus trituberculatus) exposed to elevated ambient ammonia-N. Aquaculture 434: 108–114.

    CAS  Google Scholar 

  • Reuter, Jason A., D. V. Spacek & Michael P. Snyder, 2015. High-throughput sequencing technologies. Molecular Cell 58(4): 586–597.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Roberts, A. & L. Pachter, 2012. Streaming fragment assignment for real-time analysis of sequencing experiments. Nature Methods 10: 71.

    PubMed  PubMed Central  Google Scholar 

  • Robertson, G., J. Schein, R. Chiu, R. Corbett, M. Field, S. D. Jackman, K. Mungall, S. Lee, H. M. Okada, J. Q. Qian, M. Griffith, A. Raymond, N. Thiessen, T. Cezard, Y. S. Butterfield, R. Newsome, S. K. Chan, R. She, R. Varhol, B. Kamoh, A.-L. Prabhu, A. Tam, Y. Zhao, R. A. Moore, M. Hirst, M. A. Marra, S. J. M. Jones, P. A. Hoodless & I. Birol, 2010. De novo assembly and analysis of RNA-seq data. Nature Methods 7(11): 909–912.

    CAS  PubMed  Google Scholar 

  • Robinson, M. D., D. J. McCarthy & G. K. Smyth, 2010. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1): 139–140.

    CAS  PubMed  Google Scholar 

  • Robles, J. A., S. E. Qureshi, S. J. Stephen, S. R. Wilson, C. J. Burden & J. M. Taylor, 2012. Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing. BMC Genomics 13(1): 484.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Rotllant, G., T. V. Nguyen, V. Sbragaglia, L. Rahi, K. J. Dudley, D. Hurwood, T. Ventura, J. B. Company, V. Chand, J. Aguzzi & P. B. Mather, 2017. Sex and tissue specific gene expression patterns identified following de novo transcriptomic analysis of the Norway lobster, Nephrops norvegicus. BMC Genomics 18: 622.

    PubMed  PubMed Central  Google Scholar 

  • Sagi, A., R. Manor & T. Ventura, 2013. Gene silencing in Crustaceans: from basic research to biotechnologies. Genes 4(4): 620.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Sbragaglia, V., F. Lamanna, A. M. Mat, G. Rotllant, S. Joly, V. Ketmaier, H. O. de la Iglesia & J. Aguzzi, 2015. Identification, characterization, and diel pattern of expression of canonical clock genes in Nephrops norvegicus (Crustacea: Decapoda) eyestalk. PLoS ONE 10(11): e0141893.

    PubMed  PubMed Central  Google Scholar 

  • Schadt, E. E., S. Turner & A. Kasarskis, 2010. A window into third-generation sequencing. Human Molecular Genetics 19(R2): R227–R240.

    CAS  PubMed  Google Scholar 

  • Schirmer, M., U. Z. Ijaz, R. D’Amore, N. Hall, W. T. Sloan & C. Quince, 2015. Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform. Nucleic Acids Research 43(6): e37.

    PubMed  PubMed Central  Google Scholar 

  • Schmieder, R. & R. Edwards, 2011. Quality control and preprocessing of metagenomic datasets. Bioinformatics. https://doi.org/10.1093/bioinformatics/btr026.

    Article  PubMed  PubMed Central  Google Scholar 

  • Schulz, M. H., D. R. Zerbino, M. Vingron & E. Birney, 2012. Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinformatics 28(8): 1086–1092.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Schurch, N. J., P. Schofield, M. Gierliński, C. Cole, A. Sherstnev, V. Singh, N. Wrobel, K. Gharbi, G. G. Simpson, T. Owen-Hughes, M. Blaxter & G. J. Barton, 2016. How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? RNA 22(6): 839–851.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Seelenfreund, E., W. A. Robinson, C. M. Amato, A.-C. Tan, J. Kim & S. E. Robinson, 2014. Long term storage of dry versus frozen RNA for next generation molecular studies. PLoS ONE 9(11): e111827.

    PubMed  PubMed Central  Google Scholar 

  • Simão, F. A., R. M. Waterhouse, P. Ioannidis, E. V. Kriventseva & E. M. Zdobnov, 2015. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31(19): 3210–3212.

    PubMed  Google Scholar 

  • Soneson, C. & M. Delorenzi, 2013. A comparison of methods for differential expression analysis of RNA-seq data. BMC Bioinformatics 14(1): 91.

    PubMed  PubMed Central  Google Scholar 

  • Song, L., C. Bian, Y. Luo, L. Wang, X. You, J. Li, Y. Qiu, X. Ma, Z. Zhu, L. Ma, Z. Wang, Y. Lei, J. Qiang, H. Li, J. Yu, A. Wong, J. Xu, Q. Shi & P. Xu, 2016. Draft genome of the Chinese mitten crab. Eriocheir sinensis. GigaScience 5: 5.

    PubMed  Google Scholar 

  • Sookruksawong, S., F. Sun & Z. Liu, 2013. RNA-Seq analysis reveals genes associated with resistance to Taura syndrome virus (TSV) in the Pacific white shrimp Litopenaeus vannamei. Developmental & Comparative Immunology 41(4): 523–533.

    CAS  Google Scholar 

  • Sultan, M., V. Amstislavskiy, T. Risch, M. Schuette, S. Dökel, M. Ralser, D. Balzereit, H. Lehrach & M.-L. Yaspo, 2014. Influence of RNA extraction methods and library selection schemes on RNA-seq data. BMC Genomics 15(1): 675.

    PubMed  PubMed Central  Google Scholar 

  • Sultan, M., S. Dökel, V. Amstislavskiy, D. Wuttig, H. Sültmann, H. Lehrach & M.-L. Yaspo, 2012. A simple strand-specific RNA-Seq library preparation protocol combining the Illumina TruSeq RNA and the dUTP methods. Biochemical and Biophysical Research Communications 422(4): 643–646.

    CAS  PubMed  Google Scholar 

  • Sun, M., Y. Ting Li, Y. Liu, S. Chin Lee & L. Wang, 2016. Transcriptome assembly and expression profiling of molecular responses to cadmium toxicity in hepatopancreas of the freshwater crab Sinopotamon henanense. Scientific Reports 6: 19405.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Surget-Groba, Y. & J. I. Montoya-Burgos, 2010. Optimization of de novo transcriptome assembly from next-generation sequencing data. Genome Research 20(10): 1432–1440.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Tarazona, S., F. García, A. Ferrer, J. Dopazo & A. Conesa, 2012. NOIseq: a RNA-seq differential expression method robust for sequencing depth biases. EMBnet Journal 17: 18–19.

    Google Scholar 

  • Tarazona, S., F. García-Alcalde, J. Dopazo, A. Ferrer & A. Conesa, 2011. Differential expression in RNA-seq: a matter of depth. Genome Research 21(12): 2213–2223.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Teng, M., M. I. Love, C. A. Davis, S. Djebali, A. Dobin, B. R. Graveley, S. Li, C. E. Mason, S. Olson, D. Pervouchine, C. A. Sloan, X. Wei, L. Zhan & R. A. Irizarry, 2016. A benchmark for RNA-seq quantification pipelines. Genome Biology 17(1): 74.

    PubMed  PubMed Central  Google Scholar 

  • Ventura, T., Q. P. Fitzgibbon, S. C. Battaglene & A. Elizur, 2015. Redefining metamorphosis in spiny lobsters: molecular analysis of the phyllosoma to puerulus transition in Sagmariasus verreauxi. Scientific Reports 5: 13537.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ventura, T., R. Manor, E. D. Aflalo, V. Chalifa-Caspi, S. Weil, O. Sharabi & A. Sagi, 2013. Post-embryonic transcriptomes of the prawn Macrobrachium rosenbergii: multigenic succession through metamorphosis. PLoS ONE 8(1): e55322.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Waiho, K., H. Fazhan, M. S. Shahreza, J. H. Z. Moh, S. Noorbaiduri, L. L. Wong, S. Sinnasamy & M. Ikhwanuddin, 2017. Transcriptome analysis and differential gene expression on the testis of orange mud crab, Scylla olivacea, during sexual maturation. PLoS ONE 12(1): e0171095.

    PubMed  PubMed Central  Google Scholar 

  • Wang, L., Z. Feng, X. Wang, X. Wang & X. Zhang, 2010. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics 26(1): 136–138.

    PubMed  Google Scholar 

  • Wang, Z., M. Gerstein & M. Snyder, 2009. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics 10(1): 57–63.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Wang, Y., N. Ghaffari, C. Johnson, U. Braga-Neto, H. Wang, R. Chen & H. Zhou, 2011. Evaluation of the coverage and depth of transcriptome by RNA-Seq in chickens. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-12-S10-S5.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wang, Y., Y. Xiu, K. Bi, J. Ou, W. Gu, W. Wang & Q. Meng, 2017. Integrated analysis of mRNA-seq in the haemocytes of Eriocheir sinensis in response to Spiroplasma eriocheiris infection. Fish Shellfish Immunol 68: 289–298.

    CAS  PubMed  Google Scholar 

  • Wei, J., X. Zhang, Y. Yu, H. Huang, F. Li & J. Xiang, 2014. Comparative transcriptomic characterization of the early development in Pacific white shrimp Litopenaeus vannamei. PLoS ONE 9(9): e106201.

    PubMed  PubMed Central  Google Scholar 

  • Wilhelm, B. T. & J.-R. Landry, 2009. RNA-Seq—quantitative measurement of expression through massively parallel RNA-sequencing. Methods 48(3): 249–257.

    CAS  PubMed  Google Scholar 

  • Winnebeck, E. C., C. D. Millar & G. R. Warman, 2010. Why Does Insect RNA Look Degraded? Journal of Insect Science 10: 159.

    PubMed  PubMed Central  Google Scholar 

  • Wu, T. D. & S. Nacu, 2010. Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 26(7): 873–881.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Wu, A. R., N. F. Neff, T. Kalisky, P. Dalerba, B. Treutlein, M. E. Rothenberg, F. M. Mburu, G. L. Mantalas, S. Sim, M. F. Clarke & S. R. Quake, 2014. Quantitative assessment of single-cell RNA-sequencing methods. Nature Methods 11(1): 41–46.

    CAS  PubMed  Google Scholar 

  • Xie, Y., G. Wu, J. Tang, R. Luo, J. Patterson, S. Liu, W. Huang, G. He, S. Gu, S. Li, X. Zhou, T.-W. Lam, Y. Li, X. Xu, G. K.-S. Wong & J. Wang, 2014. SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads. Bioinformatics. https://doi.org/10.1093/bioinformatics/btu077.

    Article  PubMed  PubMed Central  Google Scholar 

  • Yang, X., D. Liu, F. Liu, J. Wu, J. Zou, X. Xiao, F. Zhao & B. Zhu, 2013. HTQC: a fast quality control toolkit for Illumina sequencing data. BMC bioinformatics 14(1): 33.

    PubMed  PubMed Central  Google Scholar 

  • Yang, C. & H. Wei, 2015. Designing Microarray and RNA-Seq experiments for greater systems biology discovery in modern plant genomics. Molecular Plant 8(2): 196–206.

    CAS  PubMed  Google Scholar 

  • Yu, Y., X. Zhang, J. Yuan, F. Li, X. Chen, Y. Zhao, L. Huang, H. Zheng & J. Xiang, 2015. Genome survey and high-density genetic map construction provide genomic and genetic resources for the Pacific White Shrimp Litopenaeus vannamei. Scientific Reports 5: 15612.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Yuan, J., X. Zhang, C. Liu, Y. Yu, J. Wei, F. Li & J. Xiang, 2017. Genomic resources and comparative analyses of two economical penaeid shrimp species, Marsupenaeus japonicus and Penaeus monodon. Marine Genomics. https://doi.org/10.1016/j.margen.2017.12.006.

    Article  Google Scholar 

  • Zerbino, D. R. & E. Birney, 2008. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Research 18(5): 821–829.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang, Z. H., D. J. Jhaveri, V. M. Marshall, D. C. Bauer, J. Edson, R. K. Narayanan, G. J. Robinson, A. E. Lundberg, P. F. Bartlett, N. R. Wray & Q.-Y. Zhao, 2014. A comparative study of techniques for differential expression analysis on RNA-Seq data. PLoS ONE 9(8): e103207.

    PubMed  PubMed Central  Google Scholar 

  • Zhang, D., F. Wang, S. Dong & Y. Lu, 2016. De novo assembly and transcriptome analysis of osmoregulation in Litopenaeus vannamei under three cultivated conditions with different salinities. Gene 578(2): 185–193.

    CAS  PubMed  Google Scholar 

  • Zhao, Q.-Y., Y. Wang, Y.-M. Kong, D. Luo, X. Li & P. Hao, 2011. Optimizing de novo transcriptome assembly from short-read RNA-Seq data: a comparative study. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-12-S14-S2.

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhao, S., Y. Zhang, W. Gordon, J. Quan, H. Xi, S. Du, D. von Schack & B. Zhang, 2015a. Comparison of stranded and non-stranded RNA-seq transcriptome profiling and investigation of gene overlap. BMC Genomics 16(1): 675.

    PubMed  PubMed Central  Google Scholar 

  • Zhao, Q., L. Pan, Q. Ren & D. Hu, 2015b. Digital gene expression analysis in hemocytes of the white shrimp Litopenaeus vannamei in response to low salinity stress. Fish & Shellfish Immunology 42(2): 400–407.

    CAS  Google Scholar 

  • Zhong, S., J. G. Joung, Y. Zheng, Y. R. Chen, B. Liu, Y. Shao, J. Z. Xiang, Z. Fei & J. J. Giovannoni, 2011. High-throughput illumina strand-specific RNA sequencing library preparation. Cold Spring Harbor Protocols 2011(8): 940–949.

    PubMed  Google Scholar 

  • Zhou, Y. H., K. Xia & F. A. Wright, 2011. A powerful and flexible approach to the analysis of RNA sequence count data. Bioinformatics 27(19): 2672–2678.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The current study was supported through a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme (612296-DeNuGReC). Tuan Viet Nguyen was supported through the Australian Research Council Discovery Project grant awarded to Dr Tomer Ventura (No. DP160103320) and a USC International PhD scholarship. The authors would like to acknowledge the precious help of Professor Abigail Elizur (University of the Sunshine Coast, Australia) and four anonymous reviewers for numerous feedbacks that helped improve the quality of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Tuan Viet Nguyen or Tomer Ventura.

Additional information

Guest editors: Guiomar Rotllant, Ferran Palero, Peter Mather, Heather Bracken-Grissom & Begoña Santos / Crustacean Genomics

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nguyen, T.V., Jung, H., Rotllant, G. et al. Guidelines for RNA-seq projects: applications and opportunities in non-model decapod crustacean species. Hydrobiologia 825, 5–27 (2018). https://doi.org/10.1007/s10750-018-3682-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10750-018-3682-0

Keywords

Navigation