Literature DB >> 21856932

Cellular effects and epistasis among three determinants of adaptation in experimental populations of Saccharomyces cerevisiae.

Lucas S Parreiras1, Linda M Kohn, James B Anderson.   

Abstract

Epistatic interactions in which the phenotypic effect of an allele is conditional on its genetic background have been shown to play a central part in various evolutionary processes. In a previous study (J. B. Anderson et al., Curr. Biol. 20:1383-1388, 2010; J. R. Dettman, C. Sirjusingh, L. M. Kohn, and J. B. Anderson, Nature 447:585-588, 2007), beginning with a common ancestor, we identified three determinants of fitness as mutant alleles (each designated with the letter "e") that arose in replicate Saccharomyces cerevisiae populations propagated in two different environments, a low-glucose and a high-salt environment. In a low-glucose environment, MDS3e and MKT1e interacted positively to confer a fitness advantage. Also, PMA1e from a high-salt environment interacted negatively with MKT1e in a low-glucose environment, an example of a Dobzhansky-Muller incompatibility that confers reproductive isolation. Here we showed that the negative interaction between PMA1e and MKT1e is mediated by alterations in intracellular pH, while the positive interaction between MDS3e and MKT1e is mediated by changes in gene expression affecting glucose transporter genes. We specifically addressed the evolutionary significance of the positive interaction by showing that the presence of the MDS3 mutation is a necessary condition for the spread and fixation of the new mutations at the identical site in MKT1. The expected mutations in MKT1 rose to high frequencies in two of three experimental populations carrying MDS3e but not in any of three populations carrying the ancestral allele. These data show how positive and negative epistasis can contribute to adaptation and reproductive isolation.

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Year:  2011        PMID: 21856932      PMCID: PMC3187067          DOI: 10.1128/EC.05083-11

Source DB:  PubMed          Journal:  Eukaryot Cell        ISSN: 1535-9786


  39 in total

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Journal:  Genetics       Date:  2002-12       Impact factor: 4.562

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  5 in total

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Authors:  Linda M Kohn; James B Anderson
Journal:  Eukaryot Cell       Date:  2014-07-11

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Authors:  Larissa Melo do Nascimento; Monica Terrao; Kevin Kamanyi Marucha; Bin Liu; Franziska Egler; Christine Clayton
Journal:  J Biol Chem       Date:  2020-06-12       Impact factor: 5.157

3.  Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome biogenesis.

Authors:  Basel Abu-Jamous; Rui Fa; David J Roberts; Asoke K Nandi
Journal:  BMC Bioinformatics       Date:  2014-09-29       Impact factor: 3.169

4.  The Genetic Basis of Mutation Rate Variation in Yeast.

Authors:  Liangke Gou; Joshua S Bloom; Leonid Kruglyak
Journal:  Genetics       Date:  2018-11-30       Impact factor: 4.562

5.  Trypanosome MKT1 and the RNA-binding protein ZC3H11: interactions and potential roles in post-transcriptional regulatory networks.

Authors:  Aditi Singh; Igor Minia; Dorothea Droll; Abeer Fadda; Christine Clayton; Esteban Erben
Journal:  Nucleic Acids Res       Date:  2014-01-26       Impact factor: 16.971

  5 in total

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