Saccharomyces cerevisiae has been used for millennia in winemaking, but little is known about the selective forces acting on the wine yeast genome. We sequenced the complete genome of the diploid commercial wine yeast EC1118, resulting in an assembly of 31 scaffolds covering 97% of the S288c reference genome. The wine yeast differed strikingly from the other S. cerevisiae isolates in possessing 3 unique large regions, 2 of which were subtelomeric, the other being inserted within an EC1118 chromosome. These regions encompass 34 genes involved in key wine fermentation functions. Phylogeny and synteny analyses showed that 1 of these regions originated from a species closely related to the Saccharomyces genus, whereas the 2 other regions were of non-Saccharomyces origin. We identified Zygosaccharomyces bailii, a major contaminant of wine fermentations, as the donor species for 1 of these 2 regions. Although natural hybridization between Saccharomyces strains has been described, this report provides evidence that gene transfer may occur between Saccharomyces and nonSaccharomyces species. We show that the regions identified are frequent and differentially distributed among S. cerevisiae clades, being found almost exclusively in wine strains, suggesting acquisition through recent transfer events. Overall, these data show that the wine yeast genome is subject to constant remodeling through the contribution of exogenous genes. Our results suggest that these processes are favored by ecologic proximity and are involved in the molecular adaptation of wine yeasts to conditions of high sugar, low nitrogen, and high ethanol concentrations. adaptive evolution ͉ comparative genomics ͉ horizontal gene transfer ͉ introgression ͉ Zygosaccharomyces bailii
Ecosystems across the globe are threatened by climate change and human activities. New rapid survey approaches for monitoring biodiversity would greatly advance assessment and understanding of these threats. Taking advantage of next-generation DNA sequencing, we tested an approach we call metabarcoding: high-throughput and simultaneous taxa identification based on a very short (usually <100 base pairs) but informative DNA fragment. Short DNA fragments allow the use of degraded DNA from environmental samples. All analyses included amplification using plant-specific versatile primers, sequencing and estimation of taxonomic diversity. We tested in three steps whether degraded DNA from dead material in soil has the potential of efficiently assessing biodiversity in different biomes. First, soil DNA from eight boreal plant communities located in two different vegetation types (meadow and heath) was amplified. Plant diversity detected from boreal soil was highly consistent with plant taxonomic and growth form diversity estimated from conventional above-ground surveys. Second, we assessed DNA persistence using samples from formerly cultivated soils in temperate environments. We found that the number of crop DNA sequences retrieved strongly varied with years since last cultivation, and crop sequences were absent from nearby, uncultivated plots. Third, we assessed the universal applicability of DNA metabarcoding using soil samples from tropical environments: a large proportion of species and families from the study site were efficiently recovered. The results open unprecedented opportunities for large-scale DNA-based biodiversity studies across a range of taxonomic groups using standardized metabarcoding approaches.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.