Unknown

Dataset Information

0

Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data.


ABSTRACT: 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.

SUBMITTER: Rawat V 

PROVIDER: S-EPMC4575116 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

altmetric image

Publications

Improving the Annotation of Arabidopsis lyrata Using RNA-Seq Data.

Rawat Vimal V   Abdelsamad Ahmed A   Pietzenuk Björn B   Seymour Danelle K DK   Koenig Daniel D   Weigel Detlef D   Pecinka Ales A   Schneeberger Korbinian K  

PloS one 20150918 9


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  ...[more]

Similar Datasets

2016-05-17 | GSE81496 | GEO
2016-05-17 | E-GEOD-81496 | biostudies-arrayexpress
| PRJNA321818 | ENA
| S-EPMC6596894 | biostudies-literature
| S-EPMC4985025 | biostudies-literature
| S-EPMC4952227 | biostudies-literature
| S-EPMC3650863 | biostudies-literature
| S-EPMC7235421 | biostudies-literature
| S-EPMC6505119 | biostudies-literature
| S-EPMC4739097 | biostudies-literature