• Medientyp: E-Artikel
  • Titel: An extended set of yeast-based functional assays accurately identifies human disease mutations
  • Beteiligte: Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L.; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E.; Vidal, Marc; Andrews, Brenda J.; Boone, Charles; Dolinski, Kara; Roth, Frederick P.
  • Erschienen: Cold Spring Harbor Laboratory, 2016
  • Erschienen in: Genome Research, 26 (2016) 5, Seite 670-680
  • Sprache: Englisch
  • DOI: 10.1101/gr.192526.115
  • ISSN: 1088-9051; 1549-5469
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  • Beschreibung: 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.
  • Zugangsstatus: Freier Zugang