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Titel
Exploiting single-molecule transcript sequencing for eukaryotic gene prediction
VerfasserMinoche, André E. ; Dohm, Juliane C. ; Schneider, Jessica ; Holtgräwe, Daniela ; Viehöver, Prisca ; Montfort, Magda ; Rosleff Sörensen, Thomas ; Weisshaar, Bernd ; Himmelbauer, Heinz
Erschienen in
Genome Biology, 2015, Jg. 16,
ErschienenBioMed Central (BMC), 2015
SpracheEnglisch
DokumenttypAufsatz in einer Zeitschrift
Schlagwörter (EN)Eukaryotic gene prediction / Single-molecule real-time sequencing / mRNA-seq / Caryophyllales / Sugar beet / Spinach / Non-model species / Genome annotation
ISSN1474-760X
URNurn:nbn:at:at-ubbw:3-463 Persistent Identifier (URN)
DOIdoi:10.1186/s13059-015-0729-7 
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Exploiting single-molecule transcript sequencing for eukaryotic gene prediction [2.01 mb]
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Zusammenfassung (Englisch)

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.