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Mutation severity spectrum of rare alleles in the human genome is predictive of disease type

Jimin Pei, Lisa Kinch, Nick V. Grishin
doi: https://doi.org/10.1101/835462
Jimin Pei
1Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA
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Lisa Kinch
1Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA
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Nick V. Grishin
1Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA
2Departments of Biophysics and Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA
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  • For correspondence: grishin@chop.swmed.edu
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Abstract

The human genome harbors a variety of genetic variations. Single-nucleotide changes that alter amino acids in protein-coding regions are one of the major causes of human phenotypic variation and diseases. These single-amino acid variations (SAVs) are routinely found in whole genome and exome sequencing. Evaluating the functional impact of such genomic alterations is crucial for diagnosis of genetic disorders. We developed DeepSAV, a deep-learning convolutional neural network to differentiate disease-causing and benign SAVs based on a variety of protein sequence, structural and functional properties. Our method outperforms most stand-alone programs and has similar predictive power as some of the best available. We transformed DeepSAV scores of rare SAVs observed in the general population into a mutation severity measure of protein-coding genes. This measure reflects a gene’s tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. Genes implicated in cancer, autism, and viral interaction are found by this measure as intolerant to mutations, while genes associated with a number of other diseases are scored as tolerant. Among known disease-associated genes, those that are mutation-intolerant are likely to function in development and signal transduction pathways, while those that are mutation-tolerant tend to encode metabolic and mitochondrial proteins.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 10, 2019.
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Mutation severity spectrum of rare alleles in the human genome is predictive of disease type
Jimin Pei, Lisa Kinch, Nick V. Grishin
bioRxiv 835462; doi: https://doi.org/10.1101/835462
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Mutation severity spectrum of rare alleles in the human genome is predictive of disease type
Jimin Pei, Lisa Kinch, Nick V. Grishin
bioRxiv 835462; doi: https://doi.org/10.1101/835462

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