BMC Genomics (May 2018)

The aquatic animals’ transcriptome resource for comparative functional analysis

  • Chih-Hung Chou,
  • Hsi-Yuan Huang,
  • Wei-Chih Huang,
  • Sheng-Da Hsu,
  • Chung-Der Hsiao,
  • Chia-Yu Liu,
  • Yu-Hung Chen,
  • Yu-Chen Liu,
  • Wei-Yun Huang,
  • Meng-Lin Lee,
  • Yi-Chang Chen,
  • Hsien-Da Huang

DOI
https://doi.org/10.1186/s12864-018-4463-x
Journal volume & issue
Vol. 19, no. S2
pp. 161 – 170

Abstract

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Abstract Background Aquatic animals have great economic and ecological importance. Among them, non-model organisms have been studied regarding eco-toxicity, stress biology, and environmental adaptation. Due to recent advances in next-generation sequencing techniques, large amounts of RNA-seq data for aquatic animals are publicly available. However, currently there is no comprehensive resource exist for the analysis, unification, and integration of these datasets. This study utilizes computational approaches to build a new resource of transcriptomic maps for aquatic animals. This aquatic animal transcriptome map database dbATM provides de novo assembly of transcriptome, gene annotation and comparative analysis of more than twenty aquatic organisms without draft genome. Results To improve the assembly quality, three computational tools (Trinity, Oases and SOAPdenovo-Trans) were employed to enhance individual transcriptome assembly, and CAP3 and CD-HIT-EST software were then used to merge these three assembled transcriptomes. In addition, functional annotation analysis provides valuable clues to gene characteristics, including full-length transcript coding regions, conserved domains, gene ontology and KEGG pathways. Furthermore, all aquatic animal genes are essential for comparative genomics tasks such as constructing homologous gene groups and blast databases and phylogenetic analysis. Conclusion In conclusion, we establish a resource for non model organism aquatic animals, which is great economic and ecological importance and provide transcriptomic information including functional annotation and comparative transcriptome analysis. The database is now publically accessible through the URL http://dbATM.mbc.nctu.edu.tw/.