Welcome to the UPF Digital Repository

Exploiting single-molecule transcript sequencing for eukaryotic gene prediction

Show simple item record

dc.contributor.author Minoche, André E.
dc.contributor.author Dohm, Juliane C.
dc.contributor.author Schneider, Jessica
dc.contributor.author Holtgräwe, Daniela
dc.contributor.author Viehöver, Prisca
dc.contributor.author Montfort, Magda
dc.contributor.author Sörensen, Thomas Rosleff
dc.contributor.author Weisshaar, Bernd
dc.contributor.author Himmelbauer, Heinz
dc.date.accessioned 2015-11-12T14:10:47Z
dc.date.available 2015-11-12T14:10:47Z
dc.date.issued 2015
dc.identifier.citation Minoche AE, Dohm JC, Schneider J, Holtgräwe D, Viehöver P, Montfort M et al. Exploiting single-molecule transcript sequencing for eukaryotic gene prediction. Genome biology. 2015;16:184. DOI: 10.1186/s13059-015-0729-7
dc.identifier.issn 1474-7596
dc.identifier.uri http://hdl.handle.net/10230/25069
dc.description.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.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher BioMed Central
dc.relation.ispartof Genome biology. 2015;16:184
dc.rights © 2015 Minoche et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject.other Genòmica
dc.subject.other RNA missatger
dc.title Exploiting single-molecule transcript sequencing for eukaryotic gene prediction
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1186/s13059-015-0729-7
dc.subject.keyword Single-molecule real-time sequencing
dc.subject.keyword Eukaryotic gene prediction
dc.subject.keyword mRNA-seq
dc.subject.keyword Caryophyllales
dc.subject.keyword Sugar beet
dc.subject.keyword Spinach
dc.subject.keyword Non-model species
dc.subject.keyword Genome annotation
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account

Statistics

In collaboration with Compliant to Partaking