期刊
BRIEFINGS IN BIOINFORMATICS
卷 12, 期 5, 页码 474-484出版社
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbr038
关键词
Chondrichthyes; trained gene prediction; next generation sequencing; genome assembly; orthology
资金
- German Research Foundation (DFG) [KU2669/1-1]
- University of Konstanz
- Konstanz Research School Chemical Biology (KoRS-CB)
- ETH Independent Investigators' Research Award
Recent development of deep sequencing technologies has facilitated de novo genome sequencing projects, now conducted even by individual laboratories. However, this will yield more and more genome sequences that are not well assembled, and will hinder thorough annotation when no closely related reference genome is available. One of the challenging issues is the identification of protein-coding sequences split into multiple unassembled genomic segments, which can confound orthology assignment and various laboratory experiments requiring the identification of individual genes. In this study, using the genome of a cartilaginous fish, Callorhinchus milii, as test case, we performed gene prediction using a model specifically trained for this genome. We implemented an algorithm, designated ESPRIT, to identify possible linkages between multiple protein-coding portions derived from a single genomic locus split into multiple unassembled genomic segments. We developed a validation framework based on an artificially fragmented human genome, improvements between early and recent mouse genome assemblies, comparison with experimentally validated sequences from GenBank, and phylogenetic analyses. Our strategy provided insights into practical solutions for efficient annotation of only partially sequenced (low-coverage) genomes. To our knowledge, our study is the first formulation of a method to link unassembled genomic segments based on proteomes of relatively distantly related species as references.
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