Abstract
Ethanol tolerance, a polygenic trait of the yeast Saccharomyces cerevisiae, is the primary factor determining industrial bioethanol productivity. Until now, genomic elements affecting ethanol tolerance have been mapped only at low resolution, hindering their identification. Here, we explore the genetic architecture of ethanol tolerance, in the F6 generation of an Advanced Intercrossed Line (AIL) mapping population between two phylogenetically distinct, but phenotypically similar, S. cerevisiae strains (a common laboratory strain and a wild strain isolated from nature). Under ethanol stress, 51 quantitative trait loci (QTLs) affecting growth and 96 QTLs affecting survival, most of them novel, were identified, with high resolution, in some cases to single genes, using a High-Resolution Mapping Package of methodologies that provided high power and high resolution. We confirmed our results experimentally by showing the effects of the novel mapped genes: MOG1, MGS1, and YJR154W. The mapped QTLs explained 34% of phenotypic variation for growth and 72% for survival. High statistical power provided by our analysis allowed detection of many loci with small, but mappable effects, uncovering a novel “quasi-infinitesimal” genetic architecture. These results are striking demonstration of tremendous amounts of hidden genetic variation exposed in crosses between phylogenetically separated strains with similar phenotypes; as opposed to the more common design where strains with distinct phenotypes are crossed. Our findings suggest that ethanol tolerance is under natural evolutionary fitness-selection for an optimum phenotype that would tend to eliminate alleles of large effect. The study provides a platform for development of superior ethanol-tolerant strains using genome editing or selection.
Highlights
The yeast Saccharomyces cerevisiae has long been studied as a model organism for eukaryotic molecular and cellular biology
The key to unlocking the full potential of the yeast model for genetic analysis of quantitative traits was the development in our laboratory (Bahalul et al, 2010) and elsewhere (Parts et al, 2011) of improved ascospore isolation procedures that increased the number of segregants that could be obtained in a yeast cross by orders of magnitude
This was achieved by combining various advanced mapping designs, high-throughput sequencing methods, and statistical procedures—some well-known, others relatively recent into a “High Resolution Mapping Package” (HRMP)
Summary
The yeast Saccharomyces cerevisiae has long been studied as a model organism for eukaryotic molecular and cellular biology. High ethanol concentration endangers the survival of the cells, while under moderate ethanol levels, cells survive but may have very reduced growing ability and fermentation rate. Both aspects of ethanol tolerance, growth, and survival are key factors in ethanol production (Amorim et al, 2011). A previous ethanol tolerance mapping study by Hu et al, 2007, based on the F2 of a cross between two strains that diverged widely in ethanol tolerance, uncovered two QTLs of large and three QTLs of moderate effect on ethanol tolerance, as measured by survival. Of similar design, in which a large-scale QTL mapping experiment was carried out, detected one QTL of large effect for ethanol tolerance as measured by growth (Cubillos et al, 2011)
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