Abstract
Summary RNA‐sequencing (RNA‐seq) allows global gene expression analysis at the individual transcript level. Accurate quantification of transcript variants generated by alternative splicing (AS) remains a challenge. We have developed a comprehensive, nonredundant Arabidopsis reference transcript dataset (AtRTD) containing over 74 000 transcripts for use with algorithms to quantify AS transcript isoforms in RNA‐seq.The AtRTD was formed by merging transcripts from TAIR10 and novel transcripts identified in an AS discovery project. We have estimated transcript abundance in RNA‐seq data using the transcriptome‐based alignment‐free programmes Sailfish and Salmon and have validated quantification of splicing ratios from RNA‐seq by high resolution reverse transcription polymerase chain reaction (HR RT‐PCR).Good correlations between splicing ratios from RNA‐seq and HR RT‐PCR were obtained demonstrating the accuracy of abundances calculated for individual transcripts in RNA‐seq.The AtRTD is a resource that will have immediate utility in analysing Arabidopsis RNA‐seq data to quantify differential transcript abundance and expression.
Highlights
Alternative splicing (AS) plays a key regulatory role in the growth, development and behaviour of eukaryotic organisms
Accurate quantification of transcript variants generated by alternative splicing (AS) remains a challenge
We have developed a comprehensive, nonredundant Arabidopsis reference transcript dataset (AtRTD) containing over 74 000 transcripts for use with algorithms to quantify AS transcript isoforms in RNA-seq
Summary
Alternative splicing (AS) plays a key regulatory role in the growth, development and behaviour of eukaryotic organisms. RNA-seq permits the genome-wide identification of all transcript isoforms/splicing variants of a gene and the contribution that each transcript makes to expression. As the availability of RNA-seq data grows and AS becomes a routine part of expression analysis, the resolution of gene expression studies will increase and will require accurate methods to quantify transcript isoforms in RNA-seq. A recent study compared different methods of analysing AS in plant RNA-seq data and showed variation in their ability to detect and quantify AS events with the accuracy of annotation having a major effect (Liu et al, 2014)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
