Finding genes in Schistosoma japonicum: annotating novel genomes with help of extrinsic evidence
Author(s) -
Broňa Brejová,
Tomáš Vinař,
Yangyi Chen,
Shengyue Wang,
Guoping Zhao,
Daniel G. Brown,
Ming Li,
Yan Zhou
Publication year - 2009
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkp052
Subject(s) - biology , genome , annotation , gene , caenorhabditis elegans , schistosoma japonicum , computational biology , gene annotation , gene prediction , genetics , genome project , zoology , helminths , schistosomiasis
We have developed a novel method for estimating the parameters of hidden Markov models for gene finding in newly sequenced species. Our approach does not rely on curated training data sets, but instead uses extrinsic evidence (including paired- end ditags that have not been used in gene finding previously) and iterative training. This new method is particularly suitable for annotation of species with large evolutionary distance to the closest annotated species. We have used our approach to produce an initial annotation of more than 16000 genes in the newly sequenced Schistosoma japonicum draft genome. We established the high quality of our pre- dictions by comparison to full-length cDNAs (with- drawn from the extrinsic evidence) and to CEGMA core genes. We also evaluated the effectiveness of the new training procedure on Caenorhabditis ele- gans genome. ExonHunter and the newest para- metric files for S. japonicum genome are available for download at www.bioinformatics.uwaterloo.ca/ downloads/exonhunter
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