iGEMS: an integrated model for identification of alternative exon usage events.
DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with (n = 9) or without (n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (∼90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3'UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5-10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.
Division of Genetics and Molecular Medicine, King's College London, WC2R 2LS, London, UK Research Department, XRGenomics Ltd, 35 Kingsland Road, London E2 8AA, UK.
Sanjana
S
Sood
Division of Genetics and Molecular Medicine, King's College London, WC2R 2LS, London, UK Research Department, XRGenomics Ltd, 35 Kingsland Road, London E2 8AA, UK.
Krzysztof J
KJ
Szkop
Division of Genetics and Molecular Medicine, King's College London, WC2R 2LS, London, UK School of Medicine, University of Nottingham, Derby Royal Hospital, Derbyshire, DE22 3DT, UK.
Asif
A
Nakhuda
School of Health Sciences, University of Stirling, Stirling, FK9 4LA, Scotland.
Iain J
IJ
Gallagher
Department of Oncology-Pathology, SciLifeLab, Karolinska Institutet, 171 76 Stockholm, Sweden.
Carl
C
Murie
Research Department, XRGenomics Ltd, 35 Kingsland Road, London E2 8AA, UK.
Robert J
RJ
Brogan
Department of Public Health and the Institute for Molecular Medicine (FIMM), University of Helsinki, FI-00014, Helsinki, Finland National Institute for Health and Welfare, University of Helsinki, FI-00014, Helsinki, Finland.
Jaakko
J
Kaprio
Department of Biology of Physical Activity, University of Jyväskylä, FI-40014, Jyväskylä, Finland.
Heikki
H
Kainulainen
School of Medicine, University of Nottingham, Derby Royal Hospital, Derbyshire, DE22 3DT, UK.
Philip J
PJ
Atherton
Department of Health Sciences, University of Jyväskylä, FI-40014, Jyväskylä, Finland.
Urho M
UM
Kujala
Department of Laboratory Medicine, Division of Clinical Physiology, Karolinska University Hospital, 14186, Huddinge, Sweden.
Thomas
T
Gustafsson
Department of Oncology-Pathology, SciLifeLab, Karolinska Institutet, 171 76 Stockholm, Sweden.
Ola
O
Larsson
Division of Genetics and Molecular Medicine, King's College London, WC2R 2LS, London, UK Research Department, XRGenomics Ltd, 35 Kingsland Road, London E2 8AA, UK Jamie.Timmons@gmail.com.
James A
JA
Timmons
D000328:Adult; D017398:Alternative Splicing; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D005091:Exons; D020869:Gene Expression Profiling / Q000379:methods; D023281:Genomics / Q000379:methods*; D006801:Humans; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis; D059467:Transcriptome