iGEMS : an integrated model for identification of alternative exon usage events
Sood, S., Szkop, K. J., Nakhuda, A., Gallagher, I. J., Murie, C., Brogan, R. J., Kaprio, J., Kainulainen, H., Atherton, P. J., Kujala, U., Gustafsson, T., Larsson, O., & Timmons, J. A. (2016). iGEMS : an integrated model for identification of alternative exon usage events. Nucleic Acids Research, 44(11), Article e109. https://doi.org/10.1093/nar/gkw263
Julkaistu sarjassa
Nucleic Acids ResearchTekijät
Päivämäärä
2016Tekijänoikeudet
© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an open access article distributed under the terms of the Creative Commons Attribution License.
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 identi-
fied 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 identi-
fication 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.
...
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