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The aquatic animals' transcriptome resource for comparative functional analysis.

Chih-Hung Chou1,2, Hsi-Yuan Huang1,2, Wei-Chih Huang1,2

  • 1Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.

BMC Genomics
|May 17, 2018
PubMed
Summary

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This summary is machine-generated.

A new database, dbATM, offers integrated transcriptomic data for over twenty non-model aquatic animals. This resource facilitates eco-toxicity and adaptation studies by providing de novo assembly, gene annotation, and comparative genomics analyses.

Area of Science:

  • Marine Biology
  • Genomics
  • Bioinformatics

Background:

  • Aquatic animals hold significant economic and ecological value.
  • Non-model aquatic organisms are crucial for understanding eco-toxicity, stress biology, and environmental adaptation.
  • Advances in next-generation sequencing have generated vast amounts of public RNA-seq data for aquatic species.

Purpose of the Study:

  • To develop a comprehensive database for analyzing, unifying, and integrating transcriptomic datasets of aquatic animals.
  • To create a valuable resource for non-model aquatic organisms lacking draft genomes.

Main Methods:

  • Utilized computational approaches for de novo transcriptome assembly.
  • Employed Trinity, Oases, and SOAPdenovo-Trans for enhanced assembly, followed by CAP3 and CD-HIT-EST for merging.

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  • Performed functional annotation, including gene ontology and KEGG pathway analysis.

    • Main Results:

    • Developed dbATM, a database providing de novo transcriptome assembly, gene annotation, and comparative analysis for over twenty aquatic organisms.
    • Functional annotation revealed gene characteristics like full-length coding regions and conserved domains.
    • Generated essential comparative genomics resources, including homologous gene groups, BLAST databases, and phylogenetic analysis tools.

    Conclusions:

    • Established dbATM, a public resource for transcriptomic information of non-model aquatic animals.
    • The database supports functional annotation and comparative transcriptome analysis.
    • dbATM is accessible at http://dbATM.mbc.nctu.edu.tw/.