Enhancing Structural Annotation of Yeast Genomes with RNA-Seq Data

Abstract

The number of fully sequenced genomes of yeasts is dramatically increasing but both structural and functional annotation quality are usually neglected, as most frequently based on automatic annotation transfer tools from reference genomes. RNA sequencing technologies offer the possibility to better characterize yeast transcriptomes and to correct or improve the prediction of mRNA, ncRNA, or miscellaneous RNA. We describe a computational approach to enhance structural annotation of yeast genomes based on RNA-Seq data exploitation. The proposed pipeline is primarily based on read mapping with TopHat2. Mapping outputs are then used for various applications such as: (1) validation of exon–exon junctions of predicted transcripts, (2) definition of new transcribed features, (3) prediction of 3' UTR, and (4) identification of extra features absent from the genome assembly. We strongly encourage curators to proceed to a manual validation and editing of the reference genome. Releasing genomes with high-quality annotation is an important issue, as they will be considered as references for further predictions.