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      Fermentation innovation through complex hybridization of wild and domesticated yeasts

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          Abstract

          The most common fermented beverage, lager beer, is produced by interspecies hybrids of the brewing yeast Saccharomyces cerevisiae and its wild relative Saccharomyces eubayanus . Lager-brewing yeasts are not the only example of hybrid vigor or heterosis in yeasts, but the full breadth of interspecies hybrids associated with human fermentations has received less attention. Here we present a comprehensive genomic analysis of 122 Saccharomyces hybrids and introgressed strains. These strains arose from hybridization events between two to four species. Hybrids with S. cerevisiae contributions originated from three lineages of domesticated S. cerevisiae , including the major wine-making lineage and two distinct brewing lineages. In contrast, the undomesticated parents of these interspecies hybrids were all from wild Holarctic or European lineages. Most hybrids have inherited a mitochondrial genome from a parent other than S. cerevisiae , which recent functional studies suggest could confer adaptation to colder temperatures. A subset of hybrids associated with crisp flavor profiles, including both lineages of lager-brewing yeasts, have inherited inactivated S. cerevisiae alleles of critical phenolic off-flavor genes and/or lost functional copies from the wild parent through multiple genetic mechanisms. These complex hybrids shed light on the convergent and divergent evolutionary trajectories of interspecies hybrids and their impact on innovation in lager-brewing and other diverse fermentation industries.

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          Most cited references73

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Population genomics of domestic and wild yeasts

            Since the completion of the genome sequence of Saccharomyces cerevisiae in 19961,2, there has been an exponential increase in complete genome sequences accompanied by great advances in our understanding of genome evolution. Although little is known about the natural and life histories of yeasts in the wild, there are an increasing number of studies looking at ecological and geographic distributions3,4, population structure5-8, and sexual versus asexual reproduction9,10. Less well understood at the whole genome level are the evolutionary processes acting within populations and species leading to adaptation to different environments, phenotypic differences and reproductive isolation. Here we present one- to four-fold or more coverage of the genome sequences of over seventy isolates of the baker's yeast, S. cerevisiae, and its closest relative, S. paradoxus. We examine variation in gene content, SNPs, indels, copy numbers and transposable elements. We find that phenotypic variation broadly correlates with global genome-wide phylogenetic relationships. Interestingly, S. paradoxus populations are well delineated along geographic boundaries while the variation among worldwide S. cerevisiae isolates shows less differentiation and is comparable to a single S. paradoxus population. Rather than one or two domestication events leading to the extant baker's yeasts, the population structure of S. cerevisiae consists of a few well-defined geographically isolated lineages and many different mosaics of these lineages, supporting the idea that human influence provided the opportunity for cross-breeding and production of new combinations of pre-existing variation.
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              PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses in R

              Although many computer programs can perform population genetics calculations, they are typically limited in the analyses and data input formats they offer; few applications can process the large data sets produced by whole-genome resequencing projects. Furthermore, there is no coherent framework for the easy integration of new statistics into existing pipelines, hindering the development and application of new population genetics and genomics approaches. Here, we present PopGenome, a population genomics package for the R software environment (a de facto standard for statistical analyses). PopGenome can efficiently process genome-scale data as well as large sets of individual loci. It reads DNA alignments and single-nucleotide polymorphism (SNP) data sets in most common formats, including those used by the HapMap, 1000 human genomes, and 1001 Arabidopsis genomes projects. PopGenome also reads associated annotation files in GFF format, enabling users to easily define regions or classify SNPs based on their annotation; all analyses can also be applied to sliding windows. PopGenome offers a wide range of diverse population genetics analyses, including neutrality tests as well as statistics for population differentiation, linkage disequilibrium, and recombination. PopGenome is linked to Hudson’s MS and Ewing’s MSMS programs to assess statistical significance based on coalescent simulations. PopGenome’s integration in R facilitates effortless and reproducible downstream analyses as well as the production of publication-quality graphics. Developers can easily incorporate new analyses methods into the PopGenome framework. PopGenome and R are freely available from CRAN (http://cran.r-project.org/) for all major operating systems under the GNU General Public License.
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                Author and article information

                Journal
                Nature Ecology & Evolution
                Nat Ecol Evol
                Springer Science and Business Media LLC
                2397-334X
                November 2019
                October 21 2019
                November 2019
                : 3
                : 11
                : 1576-1586
                Article
                10.1038/s41559-019-0998-8
                7295394
                31636426
                38afb345-f630-4a9b-bae3-80c4c7110f0f
                © 2019

                http://www.springer.com/tdm

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