Journal
GENOME BIOLOGY
Volume 21, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s13059-020-02071-7
Keywords
scRNA-seq; Alternative polyadenylation; mRNA isoforms; Differential transcript use
Funding
- National Health and Medical Research Council of Australia (NHMRC) [APP1118576, 1074386]
- Australian Research Council (ARC) Special Research Initiative in Stem Cell Science [SR110001002]
- Foundation Leducq Transatlantic Networks of Excellence in Cardiovascular Research [15 CVD 03, 13 CVD 01]
- New South Wales Government Department of Health
- Career Development Fellowship by the National Health and Medical Research Council [1105271]
- National Heart Foundation of Australia [100848]
- HKU-USydney Strategic Partnership Fund
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High-throughput single-cell RNA-seq (scRNA-seq) is a powerful tool for studying gene expression in single cells. Most current scRNA-seq bioinformatics tools focus on analysing overall expression levels, largely ignoring alternative mRNA isoform expression. We present a computational pipeline, Sierra, that readily detects differential transcript usage from data generated by commonly used polyA-captured scRNA-seq technology. We validate Sierra by comparing cardiac scRNA-seq cell types to bulk RNA-seq of matched populations, finding significant overlap in differential transcripts. Sierra detects differential transcript usage across human peripheral blood mononuclear cells and the Tabula Muris, and 3(')UTR shortening in cardiac fibroblasts. Sierra is available at.
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