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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
The genetic basis of variation in clean lineages of Saccharomyces cerevisiae in response to stresses encountered during bioethanol fermentations
PLoS ONE, Volume 9, No. 8, Article e103233, Year 2014
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Description
Saccharomyces cerevisiae is the micro-organism of choice for the conversion of monomeric sugars into bioethanol. Industrial bioethanol fermentations are intrinsically stressful environments for yeast and the adaptive protective response varies between strain backgrounds. With the aim of identifying quantitative trait loci (QTL's) that regulate phenotypic variation, linkage analysis on six F1 crosses from four highly divergent clean lineages of S. cerevisiae was performed. Segregants from each cross were assessed for tolerance to a range of stresses encountered during industrial bioethanol fermentations. Tolerance levels within populations of F1 segregants to stress conditions differed and displayed transgressive variation. Linkage analysis resulted in the identification of QTL's for tolerance to weak acid and osmotic stress. We tested candidate genes within loci identified by QTL using reciprocal hemizygosity analysis to ascertain their contribution to the observed phenotypic variation; this approach validated a gene (COX20) for weak acid stress and a gene (RCK2) for osmotic stress. Hemizygous transformants with a sensitive phenotype carried a COX20 allele from a weak acid sensitive parent with an alteration in its protein coding compared with other S. cerevisiae strains. RCK2 alleles reveal peptide differences between parental strains and the importance of these changes is currently being ascertained. © 2014 Greetham et al.
Authors & Co-Authors
Greetham, Darren
United Kingdom, Nottingham
University of Nottingham
Wimalasena, Tithira T.
United Kingdom, Nottingham
University of Nottingham
Leung, Kay
United Kingdom, Leicester
University of Leicester
Marvin, Marcus E.
United Kingdom, Leicester
University of Leicester
Chandelia, Yogeshwar
United Kingdom, Nottingham
University of Nottingham
Hart, Andrew
United Kingdom, Nottingham
University of Nottingham
Phister, Trevor G.
United Kingdom, Nottingham
University of Nottingham
United States, New York
Pepsico, Inc.
Tucker, Gregory A.
United Kingdom, Nottingham
University of Nottingham
Louis, E.
United Kingdom, Leicester
University of Leicester
Smart, Katherine A.
United Kingdom, Nottingham
University of Nottingham
South Africa, Sandton
Sabmiller Plc
Statistics
Citations: 19
Authors: 10
Affiliations: 4
Identifiers
Doi:
10.1371/journal.pone.0103233
e-ISSN:
19326203
Research Areas
Genetics And Genomics
Study Approach
Quantitative