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Genome Res. 2016 May;26(5):670-80. doi: 10.1101/gr.192526.115. Epub 2016 Mar 14.

An extended set of yeast-based functional assays accurately identifies human disease mutations.

Author information

1
Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario M5G 1X5, Canada; Department of Medical Biochemistry and Microbiology, Uppsala University, SE-75123 Uppsala, Sweden;
2
Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario M5G 1X5, Canada;
3
Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada;
4
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA;
5
Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA;
6
Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario M5G 1X5, Canada;
7
Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario M5G 1X5, Canada; Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; Canadian Institute for Advanced Research, Toronto, Ontario, M5G 1Z8, Canada.

Abstract

We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods.

PMID:
26975778
PMCID:
PMC4864455
DOI:
10.1101/gr.192526.115
[Indexed for MEDLINE]
Free PMC Article

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