Ontogenomic study of the relationship between number of gene splice variants and GO categorization

Ari B. Kahn, Barry R. Zeeberg, Michael C. Ryan, D. Curtis Jamison, David M. Rockoff, Yves Pommier, John N. Weinstein

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Motivation: Splice variation plays important roles in evolution and cancer. Different splice variants of a gene may be characteristic of particular cellular processes, subcellular locations or organs. Although several genomic projects have identified splice variants, there have been no large-scale computational studies of the relationship between number of splice variants and biological function. The Gene Ontology (GO) and tools for leveraging GO, such as GoMiner, now make such a study feasible. Results: We partitioned genes into two groups: those with numbers of splice variants ≤b and >b (b=1,..., 10). Then we used GoMiner to determine whether any GO categories are enriched in genes with particular numbers of splice variants. Since there was no a priori 'appropriate' partition boundary, we studied those 'robust' categories whose enrichment did not depend on the selection of a particular partition boundary. Furthermore, because the distribution of splice variant number was a snapshot taken at a particular point in time, we confirmed that those observations were stable across successive builds of GenBank. A small number of categories were found for genes in the lower partitions. A larger number of categories were found for genes in the higher partitions. Those categories were largely associated with cell death and signal transduction. Apoptotic genes tended to have a large repertoire of splice variants, and genes with splice variants exhibited a distinctive 'apoptotic island' in clustered image maps (CIMs).

Original languageEnglish (US)
Article numberbtq335
Pages (from-to)1945-1949
Number of pages5
JournalBioinformatics
Volume26
Issue number16
DOIs
StatePublished - Jul 8 2010

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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