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Keilwagen, J.* ; Hartung, F.* ; Paulini, M.* ; Twardziok, S.O. ; Grau, J.*

Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi.

BMC Bioinformatics 19:189 (2018)
Publ. Version/Full Text DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Background: Genome annotation is of key importance in many research questions. The identification of protein-coding genes is often based on transcriptome sequencing data, ab-initio or homology-based prediction. Recently, it was demonstrated that intron position conservation improves homology-based gene prediction, and that experimental data improves ab-initio gene prediction. Results: Here, we present an extension of the gene prediction program GeMoMa that utilizes amino acid sequence conservation, intron position conservation and optionally RNA-seq data for homology-based gene prediction. We show on published benchmark data for plants, animals and fungi that GeMoMa performs better than the gene prediction programs BRAKER1, MAKER2, and CodingQuarry, and purely RNA-seq-based pipelines for transcript identification. In addition, we demonstrate that using multiple reference organisms may help to further improve the performance of GeMoMa. Finally, we apply GeMoMa to four nematode species and to the recently published barley reference genome indicating that current annotations of protein-coding genes may be refined using GeMoMa predictions. Conclusions: GeMoMa might be of great utility for annotating newly sequenced genomes but also for finding homologs of a specific gene or gene family. GeMoMa has been published under GNU GPL3 and is freely available at http://www.jstacs.de/index.php/GeMoMa.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Genome Annotation ; Homology-based Gene Prediction ; Rna-seq
ISSN (print) / ISBN 1471-2105
e-ISSN 1471-2105
Journal BMC Bioinformatics
Quellenangaben Volume: 19, Issue: 1, Pages: , Article Number: 189 Supplement: ,
Publisher BioMed Central
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Research Unit Plant Genome and Systems Biology (PGSB)