An atlas of tissue-specific conserved coexpression for functional annotation and disease gene prediction

Ferdinando Di Cunto (1) , Rosario Michael Piro (1) , Ugo Ala (1) , Ivan Molineris (1) , Elena Grassi (1) , Chiara Bracco (1) , Gianpaolo Perego (1) , Paolo Provero (1)

1 Genetics, Biology and Biochemistry, Molecular Biotechnology Centre

Gene coexpression relationships that are phylogenetically conserved between human and mouse have been shown to provide important clues about gene function that can be efficiently used to identify promising candidate genes for human hereditary disorders. In the past, such approaches have considered mostly generic gene expression profiles that cover multiple tissues and organs. The individual genes of multicellular organisms, however, can participate in different transcriptional programs, operating at scales as different as single cell types, tissues, organs, body regions or the entire organism. Therefore, the systematic analysis of tissue-specific coexpression could be, in principle, a very powerful strategy to dissect those functional relationships among genes that emerge only in particular tissues or organs. In this report, we show that, in fact, conserved coexpression as determined from tissue-specific and condition-specific datasets can predict many functional relationships that are not detected by analyzing heterogeneous microarray datasets. More importantly, we find that, when combined with disease networks, the simultaneous use of both generic (multi-tissue) and tissue-specific conserved coexpression allows a more efficient prediction of human disease genes than the use of generic conserved coexpression alone. Using this strategy, we were able to identify high-probability candidates for 238 orphan disease loci. We provide the proof of concept that this combined use of generic and tissue-specific conserved coexpression can be very useful to prioritize the mutational candidates obtained from deep-sequencing projects, even in the case of genetic disorders as heterogeneous as X-linked mental retardation.

Mots clés: Bioinformatics; Disease gene prediction; Functional prediction

Ferdinando Di Cunto, Rosario Michael Piro, Ugo Ala, Ivan Molineris, Elena Grassi, et al.. An atlas of tissue-specific conserved coexpression for functional annotation and disease gene prediction. European Journal of Human Genetics, 2011, ⟨10.1038/ejhg.2011.96⟩. ⟨hal-00649447⟩