Gene function in mammals can be quickly and reliably predicted using a high-throughput analysis of patterns of RNA expression, according to an article published today in Journal of Biology. This challenges the conventional view that tissue-specificity is the best predictor of function, and could speed up the quest to understand whole genomes, in humans and other mammals, by decades. The authors have made their mouse dataset openly accessible online to the research community.
Tim Hughes and colleagues from the University of Toronto, Canada, looked at the mouse genome using a technique previously only applied to simple organisms such as yeast and the nematode worm C. elegans. In yeast and other simple organisms, the expression of genes with similar functions tends to be coordinately regulated. In these organisms, identifying correlated expression of known and unknown genes can help predicting the function of a novel gene. It has been assumed that this strategy couldnt be applied to mammals, but instead that genes expressed in the same tissue are most likely to have a functional relationship, making tissue-specificity the best indicator of function.
In an experiment that challenges this view, Hughes and colleagues created and analysed a microarray panel of over 40,000 known mouse mRNAs, expressed in 55 tissues. Their results showed that genes from the same Gene Ontology Biological Process (GO-BP) category – which indicates the physiological function of their encoded protein, such as response to temperature or amino acid metabolism - are transcriptionally co-regulated, independent of the tissue in which they are expressed.
Juliette Savin | EurekAlert!
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