Big data toolkit to mine the dark genome for precision medicine

Big Data tools for identifying new gene functions.

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Traditionally, gene function has been elucidated through experimental approaches, including the evaluation of the phenotypic consequences of gain- or loss-of-function (G/LOF) mutations or by genetic linkage or association studies. In any case, most research endeavors have been given to just a small part of the genes, dismissing the larger “dark genome.” This blocks our comprehension of the underlying mechanisms of complex traits and infections, which is fundamental for the progression of precise medication.

As most of the studies are gene-oriented and primarily influenced by prior knowledge; thus, many potentially important genes are ignored.

In a new study by the EPFL, scientists address the issue of the “dark genome” by developing novel approaches based on systems genetics. Scientists have developed big data tools to identify new gene functions.

To come up with this new approach, scientists collected large-scale gene-expression datasets containing more than 300,000 samples from six different species. The samples were then used to develop the toolkit dubbed ‘GeneBridge’ to identify potential gene functions.

For testing, scientists used the toolkit to identify hundreds of thousands of novel functions of genes, many of which have been verified by Auwerx’s group as well as by other research groups.

Johan Auwerx, whose lab at EPFL led the study, along with colleagues from the University of Lausanne and University of Tennessee, said, “We have deposited GeneBridge and its seven billion data points on systems-genetics.org along with the already existing 300 million data points. This resource will undoubtedly improve our knowledge of the ‘dark genome’ and promote the development of precision medicine.”

The study is published in Genome Research 21.

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