Novel domain combinations in proteins encoded by chimeric transcripts

Milana Frenkel-Morgenstern, Alfonso Valencia

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Motivation: Chimeric RNA transcripts are generated by different mechanisms including pre-mRNA trans-splicing, chromosomal translocations and/or gene fusions. It was shown recently that at least some of chimeric transcripts can be translated into functional chimeric proteins. Results: To gain a better understanding of the design principles underlying chimeric proteins, we have analyzed 7,424 chimeric RNAs from humans. We focused on the specific domains present in these proteins, comparing their permutations with those of known human proteins. Our method uses genomic alignments of the chimeras, identification of the gene-gene junction sites and prediction of the protein domains. We found that chimeras contain complete protein domains significantly more often than in random data sets. Specifically, we show that eight different types of domains are over-represented among all chimeras as well as in those chimeras confirmed by RNA-seq experiments. Moreover, we discovered that some chimeras potentially encode proteins with novel and unique domain combinations. Given the observed prevalence of entire protein domains in chimeras, we predict that certain putative chimeras that lack activation domains may actively compete with their parental proteins, thereby exerting dominant negative effects. More generally, the production of chimeric transcripts enables a combinatorial increase in the number of protein products available, which may disturb the function of parental genes and influence their protein-protein interaction network.

Original languageEnglish
Article numberbts216
Pages (from-to)i67-i74
JournalBioinformatics
Volume28
Issue number12
DOIs
StatePublished - 15 Jun 2012
Externally publishedYes

Bibliographical note

Funding Information:
Funding: Spanish Government grant (CONSOLIDER, CSD2007-00050), BI02007-666855, Open PHACTS (IMI-115191-2) and the NHGRI-NIH ENCODE grant (HG00455-04). Miguel Servet (FIS) to M.F.-M.

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