Systematic analysis of complex genetic interactions
Author(s) -
Elena Kuzmin,
Benjamin VanderSluis,
Wen Wang,
Guihong Tan,
Raamesh Deshpande,
Yiqun Chen,
Matej Ušaj,
Attila Balint,
Mojca Mattiazzi Ušaj,
Jolanda van Leeuwen,
Elizabeth N. Koch,
Carles Pons,
Andrius J. Dagilis,
Michael Pryszlak,
Jason Zi Yang Wang,
Julia Hanchard,
Margot Riggi,
Kaicong Xu,
Hamed Heydari,
Bryan-Joseph San Luis,
Ermira Shuteriqi,
Hongwei Zhu,
Nydia van Dyk,
Sara Sharifpoor,
Michael Costanzo,
Robbie Loewith,
Amy A. Caudy,
Daniel I. Bolnick,
Grant W. Brown,
Brenda Andrews,
Charles Boone,
Chad L. Myers
Publication year - 2018
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.aao1729
Subject(s) - biology , genetics , gene , inheritance (genetic algorithm) , mutant , phenotype , epistasis , gene interaction , genetic analysis , mutation , interaction network , computational biology
To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship.
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