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Detection of differentially expressed alternative transcripts using conventional microarrays : with application to diffuse large B-cell lymphoma

University of British Columbia

Alternative splicing, alternative transcript initiation, and alternative 3’ polyadenylation are the main molecular mechanisms which allow for a single gene to give rise to multiple, biologically distinct, alternative mRNA transcripts. Prior studies have observed that alternatively expressed transcripts can be detected using conventional gene expression microarrays by identifying inconsistent expression patterns of probesets interrogating the same gene. However, conventional microarrays have been disregarded as a potential platform for detecting differentially expressed alternative transcripts between two groups of samples. We have developed a novel algorithm, called DISCO (DIscordancy SCOre), for detecting differentially expressed alternative transcripts between two groups of samples that is designed to work on conventional microarrays. Using a published dataset with RT-PCR validated results, we demonstrated DISCO’s ability to accurately discriminate between true positive and true negative events. Using an internal cohort of 36 conventional microarrays with matched RNA-Seq libraries and an external cohort of 200 conventional microarrays of diffuse large B-cell lymphoma samples, dichotomized into the two main subtypes, we showed that DISCO has superior performance over an existing method. Gene enrichment analysis performed on the top 165 DISCO candidate genes, from the comparison of the two main subtypes, showed an enrichment for the molecular terms “alternative splicing” and “splice variants”. Among the top ranked genes with differentially expressed transcripts, between the two main subtypes, included FOXP1 (a previously reported finding), and PHF19, which to the best of our knowledge has not yet been reported. With DISCO, conventional microarrays can now be analyzed to detect for differentially expressed transcripts which these microarrays were not originally designed for. To the best of our knowledge, this is the first study to assess the concordancy between conventional microarrays and RNA-Seq predictions for differentially expressed transcripts. The concordancy between these two platforms indicate that the extensive repository of conventional microarrays may serve as a powerful supplement, potentially acting as a first line discovery platform, to RNA-Seq data.

Text

2011-12-23

Attribution-NonCommercial-ShareAlike 3.0 Unported

http://hdl.handle.net/2429/39846

Bioinformatics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-sa/3.0/