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      Exploring whole-genome duplicate gene retention with complex genetic interaction analysis

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          Abstract

          Whole-genome duplication has played a central role in the genome evolution of many organisms, including the human genome. Most duplicated genes are eliminated, and factors that influence the retention of persisting duplicates remain poorly understood. We describe a systematic complex genetic interaction analysis with yeast paralogs derived from the whole-genome duplication event. Mapping of digenic interactions for a deletion mutant of each paralog, and of trigenic interactions for the double mutant, provides insight into their roles and a quantitative measure of their functional redundancy. Trigenic interaction analysis distinguishes two classes of paralogs: a more functionally divergent subset and another that retained more functional overlap. Gene feature analysis and modeling suggest that evolutionary trajectories of duplicated genes are dictated by combined functional and structural entanglement factors.

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          The genetic landscape of a cell.

          M. Costanzo, A. Baryshnikova, J. Bellay … (2010)
          A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
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            A global genetic interaction network maps a wiring diagram of cellular function.

            M. Costanzo, B. VanderSluis, E. Koch … (2016)
            We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.
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              Dosage sensitivity and the evolution of gene families in yeast.

              Balázs Papp, Csaba Pál, Laurence D. Hurst (2003)
              According to what we term the balance hypothesis, an imbalance in the concentration of the subcomponents of a protein-protein complex can be deleterious. If so, there are two consequences: first, both underexpression and overexpression of protein complex subunits should lower fitness, and second, the accuracy of transcriptional co-regulation of subunits should reflect the deleterious consequences of imbalance. Here we show that all these predictions are upheld in yeast (Saccharomyces cerevisiae). This supports the hypothesis that dominance is a by-product of physiology and metabolism rather than the result of selection to mask the deleterious effects of mutations. Beyond this, single-gene duplication of protein subunits is expected to be harmful, as this, too, leads to imbalance. As then expected, we find that members of large gene families are rarely involved in complexes. The balance hypothesis therefore provides a single theoretical framework for understanding components both of dominance and of gene family size.
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                Author and article information

                Journal
                Title: Science
                Abbreviated Title: Science
                Publisher: American Association for the Advancement of Science (AAAS)
                ISSN (Print): 0036-8075
                ISSN (Electronic): 1095-9203
                Publication date Created: June 25 2020
                Publication date Created: June 26 2020
                Publication date (Electronic): June 25 2020
                Publication date (Print): June 26 2020
                Volume: 368
                Issue: 6498
                Page: eaaz5667
                Affiliations
                [1 ]Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
                [2 ]Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
                [3 ]Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
                [4 ]Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada.
                [5 ]Center for Analysis of Evolution and Function, University of Toronto, Toronto, Ontario, Canada.
                [6 ]Zentrum für Molekulare Biologie der Universität Heidelberg (ZMBH), DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany.
                [7 ]Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA.
                [8 ]Cell Morphogenesis and Signal Transduction, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
                [9 ]Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.
                Article
                DOI: 10.1126/science.aaz5667
                PMC ID: 7539174
                PubMed ID: 32586993
                SO-VID: fdfda29f-6b21-4857-b3c8-697f07f78f0a
                Copyright © © 2020
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                http://www.sciencemag.org/about/science-licenses-journal-article-reuse

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