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Genome‐wide characterization of differential transcript usage in Arabidopsis thaliana
Author(s) -
Vaneechoutte Dries,
Estrada April R.,
Lin YingChen,
Loraine Ann E.,
Vandepoele Klaas
Publication year - 2017
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.13746
Subject(s) - biology , gene , alternative splicing , genetics , arabidopsis , computational biology , transcriptome , arabidopsis thaliana , rna seq , rna splicing , genome , gene isoform , gene expression , rna , mutant
Summary Alternative splicing and the usage of alternate transcription start‐ or stop sites allows a single gene to produce multiple transcript isoforms. Most plant genes express certain isoforms at a significantly higher level than others, but under specific conditions this expression dominance can change, resulting in a different set of dominant isoforms. These events of differential transcript usage ( DTU ) have been observed for thousands of Arabidopsis thaliana , Zea mays and Vitis vinifera genes, and have been linked to development and stress response. However, neither the characteristics of these genes, nor the implications of DTU on their protein coding sequences or functions, are currently well understood. Here we present a dataset of isoform dominance and DTU for all genes in the At RTD 2 reference transcriptome based on a protocol that was benchmarked on simulated data and validated through comparison with a published reverse transciptase‐polymerase chain reaction panel. We report DTU events for 8148 genes across 206 public RNA ‐Seq samples, and find that protein sequences are affected in 22% of the cases. The observed DTU events show high consistency across replicates, and reveal reproducible patterns in response to treatment and development. We also demonstrate that genes with different evolutionary ages, expression breadths and functions show large differences in the frequency at which they undergo DTU , and in the effect that these events have on their protein sequences. Finally, we showcase how the generated dataset can be used to explore DTU events for genes of interest or to find genes with specific DTU in samples of interest.