Exploiting single-molecule transcript sequencing for eukaryotic gene prediction
Posted on 2015-09-02 - 05:00
Abstract We develop a method to predict and validate gene models using PacBio single-molecule, real-time (SMRT) cDNA reads. Ninety-eight percent of full-insert SMRT reads span complete open reading frames. Gene model validation using SMRT reads is developed as automated process. Optimized training and prediction settings and mRNA-seq noise reduction of assisting Illumina reads results in increased gene prediction sensitivity and precision. Additionally, we present an improved gene set for sugar beet (Beta vulgaris) and the first genome-wide gene set for spinach (Spinacia oleracea). The workflow and guidelines are a valuable resource to obtain comprehensive gene sets for newly sequenced genomes of non-model eukaryotes.
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Minoche, André; Dohm, Juliane; Schneider, Jessica; Holtgräwe, Daniela; Viehöver, Prisca; Montfort, Magda; et al. (2016). Exploiting single-molecule transcript sequencing for eukaryotic gene prediction. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.3619019.v1
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AUTHORS (9)
AM
André Minoche
JD
Juliane Dohm
JS
Jessica Schneider
DH
Daniela Holtgräwe
PV
Prisca Viehöver
MM
Magda Montfort
TR
Thomas Rosleff Sörensen
BW
Bernd Weisshaar
HH
Heinz Himmelbauer