A high quality Arabidopsis transcriptome for accurate transcript-level analysis of alternative splicing

Runxuan Zhang(James Hutton Institute), Cristiane P. G. Calixto(University of Dundee), Yamile Márquez(Max Perutz Labs), Peter Venhuizen(Max Perutz Labs), Nikoleta A. Τzioutziou(University of Dundee), Wenbin Guo(James Hutton Institute), Mark Spensley(University of Toronto), Juan Carlos Entizne(University of Dundee), Dominika Lewandowska(James Hutton Institute), Sara ten Have(University of Dundee), Nicolas Frei dit Frey(Centre National de la Recherche Scientifique), Heribert Hirt(Centre National de la Recherche Scientifique), Allan B. James(University of Glasgow), Hugh G. Nimmo(University of Glasgow), Andrea Barta(Max Perutz Labs), Maria Kalyna(BOKU University), John W. Brown(James Hutton Institute)
Nucleic Acids Research
April 5, 2017
Cited by 320Open Access
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Abstract

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.


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