Journal
NUCLEIC ACIDS RESEARCH
Volume 45, Issue 9, Pages 5061-5073Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkx267
Keywords
-
Categories
Funding
- Biotechnology and Biological Sciences Research Council (BBSRC) [BB/K013661/1, BB/K006568/1, BB/K006835/1]
- Scottish Government Rural and Environment Science and Analytical Services division (RESAS)
- Austrian Science Fund (FWF) [P26333, DK W1207]
- LABEX Saclay Plant Sciences
- BBSRC EASTBIO PhD studentships
- European Alternative Splicing Network of Excellence (EURASNET) [LSHG-CT-2005-518238]
- University of Dundee
- BBSRC [BB/K006568/1, BB/K013661/1, BB/K006835/1, 1785562] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [1785562, BB/K013661/1, BB/K006835/1, BB/K006568/1] Funding Source: researchfish
- Austrian Science Fund (FWF) [P26333, W1207] Funding Source: Austrian Science Fund (FWF)
Ask authors/readers for more resources
Alternative splicing generates multiple transcript and protein isoforms from the same gene and thus is important in gene expression regulation. To date, RNA-sequencing (RNA-seq) is the standard method for quantifying changes in alternative splicing on a genome-wide scale. Understanding the current limitations of RNA-seq is crucial for reliable analysis and the lack of high quality, comprehensive transcriptomes for most species, including model organisms such as Arabidopsis, is a major constraint in accurate quantification of transcript isoforms. To address this, we designed a novel pipeline with stringent filters and assembled a comprehensive Reference Transcript Dataset for Arabidopsis (AtRTD2) containing 82,190 non-redundant transcripts from 34 212 genes. Extensive experimental validation showed that AtRTD2 and its modified version, AtRTD2-QUASI, for use in Quantification of Alternatively Spliced Isoforms, outperform other available transcriptomes in RNA-seq analysis. This strategy can be implemented in other species to build a pipeline for transcript-level expression and alternative splicing analyses.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available