Literature DB >> 27904371

Dominant Epistasis Between Two Quantitative Trait Loci Governing Sporulation Efficiency in Yeast Saccharomyces cerevisiae.

Juraj Bergman1, Petar T Mitrikeski2, Krunoslav Brčić-Kostić1.   

Abstract

Sporulation efficiency in the yeast Saccharomyces cerevisiae is a well-established model for studying quantitative traits. A variety of genes and nucleotides causing different sporulation efficiencies in laboratory, as well as in wild strains, has already been extensively characterised (mainly by reciprocal hemizygosity analysis and nucleotide exchange methods). We applied a different strategy in order to analyze the variation in sporulation efficiency of laboratory yeast strains. Coupling classical quantitative genetic analysis with simulations of phenotypic distributions (a method we call phenotype modelling) enabled us to obtain a detailed picture of the quantitative trait loci (QTLs) relationships underlying the phenotypic variation of this trait. Using this approach, we were able to uncover a dominant epistatic inheritance of loci governing the phenotype. Moreover, a molecular analysis of known causative quantitative trait genes and nucleotides allowed for the detection of novel alleles, potentially responsible for the observed phenotypic variation. Based on the molecular data, we hypothesise that the observed dominant epistatic relationship could be caused by the interaction of multiple quantitative trait nucleotides distributed across a 60--kb QTL region located on chromosome XIV and the RME1 locus on chromosome VII. Furthermore, we propose a model of molecular pathways which possibly underlie the phenotypic variation of this trait.

Entities:  

Keywords:  QTL analysis; budding yeast; phenotype simulation; sporulation inheritance; two-locus epistasis

Year:  2015        PMID: 27904371      PMCID: PMC5079172          DOI: 10.17113/ftb.53.04.15.3998

Source DB:  PubMed          Journal:  Food Technol Biotechnol        ISSN: 1330-9862            Impact factor:   3.918


  38 in total

1.  Quantitative trait loci affecting survival and fertility-related traits in Caenorhabditis elegans show genotype-environment interactions, pleiotropy and epistasis.

Authors:  D R Shook; T E Johnson
Journal:  Genetics       Date:  1999-11       Impact factor: 4.562

2.  Quantitative trait loci mapped to single-nucleotide resolution in yeast.

Authors:  Adam M Deutschbauer; Ronald W Davis
Journal:  Nat Genet       Date:  2005-11-06       Impact factor: 38.330

3.  Genetic model testing and statistical power in population-based association studies of quantitative traits.

Authors:  Guillaume Lettre; Christoph Lange; Joel N Hirschhorn
Journal:  Genet Epidemiol       Date:  2007-05       Impact factor: 2.135

4.  A century after Fisher: time for a new paradigm in quantitative genetics.

Authors:  Ronald M Nelson; Mats E Pettersson; Örjan Carlborg
Journal:  Trends Genet       Date:  2013-10-23       Impact factor: 11.639

5.  Evolution and variation of the yeast (Saccharomyces) genome.

Authors:  R K Mortimer
Journal:  Genome Res       Date:  2000-04       Impact factor: 9.043

6.  Repression and activation domains of RME1p structurally overlap, but differ in genetic requirements.

Authors:  Anna Blumental-Perry; Weishi Li; Giora Simchen; Aaron P Mitchell
Journal:  Mol Biol Cell       Date:  2002-05       Impact factor: 4.138

7.  Two yeast forkhead genes regulate the cell cycle and pseudohyphal growth.

Authors:  G Zhu; P T Spellman; T Volpe; P O Brown; D Botstein; T N Davis; B Futcher
Journal:  Nature       Date:  2000-07-06       Impact factor: 49.962

8.  Epistasis for three grain yield components in rice (Oryza sativa L.).

Authors:  Z Li; S R Pinson; W D Park; A H Paterson; J W Stansel
Journal:  Genetics       Date:  1997-02       Impact factor: 4.562

9.  Meiotic gene conversion mutants in Saccharomyces cerevisiae. I. Isolation and characterization of pms1-1 and pms1-2.

Authors:  M S Williamson; J C Game; S Fogel
Journal:  Genetics       Date:  1985-08       Impact factor: 4.562

10.  Control of meiosis by respiration.

Authors:  Ashwini Jambhekar; Angelika Amon
Journal:  Curr Biol       Date:  2008-07-08       Impact factor: 10.834

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