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A high quality Arabidopsis transcriptome for accurate transcript-level analysis of alternative splicing
Runxuan Zhang1, Cristiane P G Calixto2, Yamile Marquez3
1Informatics and Computational Sciences, The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK.
Nucleic Acids Research
|April 13, 2017
Summary
A new pipeline and reference transcript dataset (AtRTD2) improve RNA-sequencing analysis for alternative splicing. This enhances transcript isoform quantification in species lacking comprehensive transcriptomes, like Arabidopsis.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Alternative splicing generates diverse transcript and protein isoforms, crucial for gene expression regulation.
- RNA-sequencing (RNA-seq) is the standard for genome-wide alternative splicing quantification.
- Limited high-quality transcriptomes hinder accurate isoform quantification in many species, including model organisms like Arabidopsis.
Purpose of the Study:
- To develop a robust pipeline and comprehensive reference transcriptome for improved RNA-seq analysis of alternative splicing.
- To address the constraint of incomplete transcriptomes in accurate transcript isoform quantification.
Main Methods:
- Designed a novel bioinformatics pipeline with stringent filtering criteria.
- Assembled a comprehensive Reference Transcript Dataset for Arabidopsis (AtRTD2) comprising 82,190 non-redundant transcripts from 34,212 genes.
- Validated the dataset and pipeline through extensive experimental analysis.
Main Results:
- The developed AtRTD2 dataset and its modified version (AtRTD2-QUASI) significantly outperform existing transcriptomes in RNA-seq analysis.
- Demonstrated enhanced accuracy in quantifying alternatively spliced isoforms.
Conclusions:
- The novel pipeline and AtRTD2 dataset provide a superior resource for transcript-level expression and alternative splicing analyses in Arabidopsis.
- The strategy is adaptable for other species, enabling the creation of similar resources for improved genomic analysis.