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Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data

Gene model annotations are important community resources that ensure comparability and reproducibility of analyses and are typically the first step for functional annotation of genomic regions. Without up-to-date genome annotations, genome sequences cannot be used to maximum advantage. It is therefo...

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Autores principales: Rawat, Vimal, Abdelsamad, Ahmed, Pietzenuk, Björn, Seymour, Danelle K., Koenig, Daniel, Weigel, Detlef, Pecinka, Ales, Schneeberger, Korbinian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575116/
https://www.ncbi.nlm.nih.gov/pubmed/26382944
http://dx.doi.org/10.1371/journal.pone.0137391
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author Rawat, Vimal
Abdelsamad, Ahmed
Pietzenuk, Björn
Seymour, Danelle K.
Koenig, Daniel
Weigel, Detlef
Pecinka, Ales
Schneeberger, Korbinian
author_facet Rawat, Vimal
Abdelsamad, Ahmed
Pietzenuk, Björn
Seymour, Danelle K.
Koenig, Daniel
Weigel, Detlef
Pecinka, Ales
Schneeberger, Korbinian
author_sort Rawat, Vimal
collection PubMed
description Gene model annotations are important community resources that ensure comparability and reproducibility of analyses and are typically the first step for functional annotation of genomic regions. Without up-to-date genome annotations, genome sequences cannot be used to maximum advantage. It is therefore essential to regularly update gene annotations by integrating the latest information to guarantee that reference annotations can remain a common basis for various types of analyses. Here, we report an improvement of the Arabidopsis lyrata gene annotation using extensive RNA-seq data. This new annotation consists of 31,132 protein coding gene models in addition to 2,089 genes with high similarity to transposable elements. Overall, ~87% of the gene models are corroborated by evidence of expression and 2,235 of these models feature multiple transcripts. Our updated gene annotation corrects hundreds of incorrectly split or merged gene models in the original annotation, and as a result the identification of alternative splicing events and differential isoform usage are vastly improved.
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spelling pubmed-45751162015-09-25 Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data Rawat, Vimal Abdelsamad, Ahmed Pietzenuk, Björn Seymour, Danelle K. Koenig, Daniel Weigel, Detlef Pecinka, Ales Schneeberger, Korbinian PLoS One Research Article Gene model annotations are important community resources that ensure comparability and reproducibility of analyses and are typically the first step for functional annotation of genomic regions. Without up-to-date genome annotations, genome sequences cannot be used to maximum advantage. It is therefore essential to regularly update gene annotations by integrating the latest information to guarantee that reference annotations can remain a common basis for various types of analyses. Here, we report an improvement of the Arabidopsis lyrata gene annotation using extensive RNA-seq data. This new annotation consists of 31,132 protein coding gene models in addition to 2,089 genes with high similarity to transposable elements. Overall, ~87% of the gene models are corroborated by evidence of expression and 2,235 of these models feature multiple transcripts. Our updated gene annotation corrects hundreds of incorrectly split or merged gene models in the original annotation, and as a result the identification of alternative splicing events and differential isoform usage are vastly improved. Public Library of Science 2015-09-18 /pmc/articles/PMC4575116/ /pubmed/26382944 http://dx.doi.org/10.1371/journal.pone.0137391 Text en © 2015 Rawat et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Rawat, Vimal
Abdelsamad, Ahmed
Pietzenuk, Björn
Seymour, Danelle K.
Koenig, Daniel
Weigel, Detlef
Pecinka, Ales
Schneeberger, Korbinian
Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data
title Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data
title_full Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data
title_fullStr Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data
title_full_unstemmed Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data
title_short Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data
title_sort improving the annotation of arabidopsis lyrata using rna-seq data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575116/
https://www.ncbi.nlm.nih.gov/pubmed/26382944
http://dx.doi.org/10.1371/journal.pone.0137391
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