Editors' ChoiceHuman Genetics

The Virtue of Intolerance

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Science Translational Medicine  11 Sep 2013:
Vol. 5, Issue 202, pp. 202ec151
DOI: 10.1126/scitranslmed.3007487

Coding variants in the human genome are functional candidates for studying the underlying cause of human disease. Exome sequencing has emerged as the go-to approach to systematically catalog such variants, yet it often reveals hundreds of plausible functional variants. The need to identify the subset of truly pathological variants has been a barrier to translational medicine, spurring the development of computational tools to prioritize variants for follow-up studies. A new study by Petrovski and colleagues addresses a complementary question: Can genes be reprioritized as likely causal on the basis of their natural tolerance to developing new mutations? Genes that are subject to evolutionary constraints should purge deleterious coding polymorphisms that occur naturally. New mutations discovered by sequencing within such “intolerant” genes are more likely to be functional and, perhaps, causal.

Using a publicly available catalog of natural variation in the coding genome, based on sequences in >6500 individuals, the authors propose a score to rank degrees of polymorphism from gene to gene. They first demonstrated that genes with high intolerance to natural variation are predictive of genes in the OMIM database that are assigned to a disease. Their score also predicted genes most likely to be essential in humans according to previous work documenting mouse lethal phenotypes. They also showed that different classes of genes associated with various disorders also vary in their intolerance. For example, immune system genes tended to be more tolerant to variation. This is consistent with a model in which diversifying selection acts to maintain diversity, presumably in response to pathogens. Last, the authors showed that their intolerance score helped to enrich for likely casual, new mutations discovered in phenotypic studies of autism, intellectual disability, and epileptic encephalopathies.

The new work merely scratches the surface regarding the potential utility of using large-scale population genetic resources for the interpretation of human genomes. Whereas the hunt for rare, casual mutations underlying human disease will continue to be a challenging prospect, this new approach is certainly a welcome addition to the repertoire of interpretative tools for human genome sequencing data.

S. Petrovski et al., Genic intolerance to functional variation and the interpretation of personal genomes. PLoS Genet. 9, e1003709 (2013). [Full Text]

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