The Dynamics of Adaptation to Stress from Standing Genetic Variation and de novo Mutations.

Adaptation from standing genetic variation is an important process underlying evolution in natural populations, but we rarely get the opportunity to observe the dynamics of fitness and genomic changes in real time. Here, we used experimental evolution and Pool-Seq to track the phenotypic and genomic changes of genetically diverse asexual populations of the yeast Saccharomyces cerevisiae in four environments with different fitness costs. We found that populations rapidly and in parallel increased in fitness in stressful environments. In contrast, allele frequencies showed a range of trajectories, with some populations fixing all their ancestral variation in <30 generations and others maintaining diversity across hundreds of generations. We detected parallelism at the genomic level (involving genes, pathways, and aneuploidies) within and between environments, with idiosyncratic changes recurring in the environments with higher stress. In particular, we observed a tendency of becoming haploid-like in one environment, whereas the populations of another environment showed low overall parallelism driven by standing genetic variation despite high selective pressure. This work highlights the interplay between standing genetic variation and the influx of de novo mutations in populations adapting to a range of selective pressures with different underlying trait architectures, advancing our understanding of the constraints and drivers of adaptation.

Hybridization Outcomes Have Strong Genomic and Environmental Contingencies.

AbstractExtreme F2 phenotypes known as transgressive segregants can cause increased or decreased fitness in hybrids beyond the ranges seen in parental populations. Despite the usefulness of transgression for plant and animal breeding and its potential role in hybrid speciation, the genetic mechanisms and predictors of transgressive segregation remain largely untested. We generated seven hybrid crosses between five widely divergent Saccharomyces yeast species and measured the fitness of the parents and their viable F1 and F2 hybrids in seven stressful environments. We found that on average 16.6% of all replicate F2 hybrids had higher fitness than both parents. Against our predictions, transgression frequency was not a function of parental genetic and phenotypic distances across test environments. Within environments, some relationships were significant, but not in the predicted direction; for example, genetic distance was negatively related to transgression in ethanol and hydrogen peroxide. Significant effects of hybrid cross, test environment, and cross × environment interactions suggest that the amount of transgression produced in a hybrid cross is highly context specific and that outcomes of hybridization differ even among crosses made from the same two parents. If the goal is to reliably predict hybrid fitness and forecast the evolutionary potential of admixed populations, we need more efforts to identify patterns beyond the idiosyncrasies caused by specific genomic or environmental contexts.

GPD1 and ADH3 Natural Variants Underlie Glycerol Yield Differences in Wine Fermentation.

Glycerol is one of the most important by-products of alcohol fermentation, and depending on its concentration it can contribute to wine flavor intensity and aroma volatility. Here, we evaluated the potential of utilizing the natural genetic variation of non-coding regions in budding yeast to identify allelic variants that could modulate glycerol phenotype during wine fermentation. For this we utilized four Saccharomyces cerevisiae strains (WE - Wine/European, SA - Sake, NA - North American, and WA - West African), which were previously profiled for genome-wide Allele Specific Expression (ASE) levels. The glycerol yields under Synthetic Wine Must (SWM) fermentations differed significantly between strains; WA produced the highest glycerol yields while SA produced the lowest yields. Subsequently, from our ASE database, we identified two candidate genes involved in alcoholic fermentation pathways, ADH3 and GPD1, exhibiting significant expression differences between strains. A reciprocal hemizygosity assay demonstrated that hemizygotes expressing GPD1WA , GPD1SA , ADH3WA and ADH3SA alleles had significantly greater glycerol yields compared to GPD1WE and ADH3WE . We further analyzed the gene expression profiles for each GPD1 variant under SWM, demonstrating that the expression of GPD1WE occurred earlier and was greater compared to the other alleles. This result indicates that the level, timing, and condition of expression differ between regulatory regions in the various genetic backgrounds. Furthermore, promoter allele swapping demonstrated that these allele expression patterns were transposable across genetic backgrounds; however, glycerol yields did not differ between wild type and modified strains, suggesting a strong trans effect on GPD1 gene expression. In this line, Gpd1 protein levels in parental strains, particularly Gpd1pWE, did not necessarily correlate with gene expression differences, but rather with glycerol yield where low Gpd1pWE levels were detected. This suggests that GPD1WE is influenced by recessive negative post-transcriptional regulation which is absent in the other genetic backgrounds. This dissection of regulatory mechanisms in GPD1 allelic variants demonstrates the potential to exploit natural alleles to improve glycerol production in wine fermentation and highlights the difficulties of trait improvement due to alternative trans-regulation and gene-gene interactions in the different genetic background.

QTL mapping of volatile compound production in Saccharomyces cerevisiae during alcoholic fermentation.

BACKGROUND: The volatile metabolites produced by Saccharomyces cerevisiae during alcoholic fermentation, which are mainly esters, higher alcohols and organic acids, play a vital role in the quality and perception of fermented beverages, such as wine. Although the metabolic pathways and genes behind yeast fermentative aroma formation are well described, little is known about the genetic mechanisms underlying variations between strains in the production of these aroma compounds. To increase our knowledge about the links between genetic variation and volatile production, we performed quantitative trait locus (QTL) mapping using 130 F2-meiotic segregants from two S. cerevisiae wine strains. The segregants were individually genotyped by next-generation sequencing and separately phenotyped during wine fermentation. RESULTS: Using different QTL mapping strategies, we were able to identify 65 QTLs in the genome, including 55 that influence the formation of 30 volatile secondary metabolites, 14 with an effect on sugar consumption and central carbon metabolite production, and 7 influencing fermentation parameters. For ethyl lactate, ethyl octanoate and propanol formation, we discovered 2 interacting QTLs each. Within 9 of the detected regions, we validated the contribution of 13 genes in the observed phenotypic variation by reciprocal hemizygosity analysis. These genes are involved in nitrogen uptake and metabolism (AGP1, ALP1, ILV6, LEU9), central carbon metabolism (HXT3, MAE1), fatty acid synthesis (FAS1) and regulation (AGP2, IXR1, NRG1, RGS2, RGT1, SIR2) and explain variations in the production of characteristic sensorial esters (e.g., 2-phenylethyl acetate, 2-metyhlpropyl acetate and ethyl hexanoate), higher alcohols and fatty acids. CONCLUSIONS: The detection of QTLs and their interactions emphasizes the complexity of yeast fermentative aroma formation. The validation of underlying allelic variants increases knowledge about genetic variation impacting metabolic pathways that lead to the synthesis of sensorial important compounds. As a result, this work lays the foundation for tailoring S. cerevisiae strains with optimized volatile metabolite production for fermented beverages and other biotechnological applications.

Adaptability of the Saccharomyces cerevisiae yeasts to wine fermentation conditions relies on their strong ability to consume nitrogen.

Saccharomyces cerevisiae strains are genetically diverse, largely as a result of human efforts to develop strains specifically adapted to various fermentation processes. These adaptive pressures from various ecological niches have generated behavioral differences among these strains, particularly in terms of their nitrogen consumption capacities. In this work, we characterize this phenotype by the specific quantity of nitrogen consumed under oenological fermentation conditions using a new approach. Indeed, unlike previous studies, our experiments were conducted in an environment containing excess nitrogen, eliminating the nitrogen limitation/starvation factor that is generally observed in fermentation processes. Using these conditions, we evaluated differences in the nitrogen consumption capacities for a set of five strains from diverse origins. The strains presented extremely different phenotypes and variations in their capacities to take up nitrogen from a wine fermentation environment. These variations reflect the differences in the nitrogen uptake capacities between wine and non-wine strains. Finally, the strains differed in their ability to adapt to the nitrogen composition of the environment, leading to variations in the cellular stress states, fermentation performances and the activity of the nitrogen sensing signaling pathway.

Identification of Nitrogen Consumption Genetic Variants in Yeast Through QTL Mapping and Bulk Segregant RNA-Seq Analyses.

Saccharomyces cerevisiae is responsible for wine must fermentation. In this process, nitrogen represents a limiting nutrient and its scarcity results in important economic losses for the wine industry. Yeast isolates use different strategies to grow in poor nitrogen environments and their genomic plasticity enables adaptation to multiple habitats through improvements in nitrogen consumption. Here, we used a highly recombinant S. cerevisiae multi-parent population (SGRP-4X) derived from the intercross of four parental strains of different origins to identify new genetic variants responsible for nitrogen consumption differences during wine fermentation. Analysis of 165 fully sequenced F12 segregants allowed us to map 26 QTL in narrow intervals for 14 amino acid sources and ammonium, the majority of which represent genomic regions previously unmapped for these traits. To complement this strategy, we performed Bulk segregant RNA-seq (BSR-seq) analysis in segregants exhibiting extremely high and low ammonium consumption levels. This identified several QTL overlapping differentially expressed genes and refined the gene candidate search. Based on these approaches, we were able to validate ARO1, PDC1, CPS1, ASI2, LYP1, and ALP1 allelic variants underlying nitrogen consumption differences between strains, providing evidence of many genes with small phenotypic effects. Altogether, these variants significantly shape yeast nitrogen consumption with important implications for evolution, ecological, and quantitative genomics.

Responses of Saccharomyces cerevisiae to nitrogen starvation in wine alcoholic fermentation.

Nitrogen is an important nutrient in alcoholic fermentation because its starvation affects both fermentation kinetics and the formation of yeast metabolites. In most alcoholic fermentations, yeasts have to ferment in nitrogen-starved conditions, which requires modifications of cell functions to maintain a high sugar flux and enable cell survival for long periods in stressful conditions. In this review, we present an overview of our current understanding of the responses of the wine yeast Saccharomyces cerevisiae to variations of nitrogen availability. Adaptation to nitrogen starvation involves changes in the activity of signaling pathways such as target of rapamycin (TOR) and nitrogen catabolite repression (NCR), which are important for the remodeling of gene expression and the establishment of stress responses. Upon starvation, protein degradation pathways involving autophagy and the proteasome play a major role in nitrogen recycling and the adjustment of cellular activity. Recent progress in the understanding of the role of these mechanisms should enable advances in fermentation management and the design of novel targets for the selection or improvement of yeast strains.

A genetic approach of wine yeast fermentation capacity in nitrogen-starvation reveals the key role of nitrogen signaling.

BACKGROUND: In conditions of nitrogen limitation, Saccharomyces cerevisiae strains differ in their fermentation capacities, due to differences in their nitrogen requirements. The mechanisms ensuring the maintenance of glycolytic flux in these conditions are unknown. We investigated the genetic basis of these differences, by studying quantitative trait loci (QTL) in a population of 133 individuals from the F2 segregant population generated from a cross between two strains with different nitrogen requirements for efficient fermentation. RESULTS: By comparing two bulks of segregants with low and high nitrogen requirements, we detected four regions making a quantitative contribution to these traits. We identified four polymorphic genes, in three of these four regions, for which involvement in the phenotype was validated by hemizygote comparison. The functions of the four validated genes, GCN1, MDS3, ARG81 and BIO3, relate to key roles in nitrogen metabolism and signaling, helping to maintain fermentation performance. CONCLUSIONS: This study reveals that differences in nitrogen requirement between yeast strains results from a complex allelic combination. The identification of three genes involved in sensing and signaling nitrogen and specially one from the TOR pathway as affecting nitrogen requirements suggests a role for this pathway in regulating the fermentation rate in starvation through unknown mechanisms linking nitrogen signaling to glycolytic flux.

Assessing the mechanisms responsible for differences between nitrogen requirements of saccharomyces cerevisiae wine yeasts in alcoholic fermentation.

Nitrogen is an essential nutrient for Saccharomyces cerevisiae wine yeasts during alcoholic fermentation, and its abundance determines the fermentation rate and duration. The capacity to ferment under conditions of nitrogen deficiency differs between yeasts. A characterization of the nitrogen requirements of a set of 23 strains revealed large differences in their fermentative performances under nitrogen deficiency, and these differences reflect the nitrogen requirements of the strains. We selected and compared two groups of strains, one with low nitrogen requirements (LNRs) and the other with high nitrogen requirements (HNRs). A comparison of various physiological traits indicated that the differences are not related to the ability to store nitrogen or the protein content. No differences in protein synthesis activity were detected between strains with different nitrogen requirements. Transcriptomic analysis revealed expression patterns specific to each of the two groups of strains, with an overexpression of stress genes in HNR strains and a stronger expression of biosynthetic genes in LNR strains. Our data suggest that differences in glycolytic flux may originate from variations in nitrogen sensing and signaling under conditions of starvation.

Identification of precursor transcripts for 6 novel miRNAs expands the diversity on the genomic organisation and expression of miRNA genes in rice.

BACKGROUND: The plant miRNAs represent an important class of endogenous small RNAs that guide cleavage of an mRNA target or repress its translation to control development and adaptation to stresses. MiRNAs are nuclear-encoded genes transcribed by RNA polymerase II, producing a primary precursor that is subsequently processed by DCL1 an RNase III Dicer-like protein. In rice hundreds of miRNAs have been described or predicted, but little is known on their genes and precursors which are important criteria to distinguish them from siRNAs. Here we develop a combination of experimental approaches to detect novel miRNAs in rice, identify their precursor transcripts and genes and predict or validate their mRNA targets. RESULTS: We produced four cDNA libraries from small RNA fractions extracted from distinct rice tissues. By in silico analysis we selected 6 potential novel miRNAs, and confirmed that their expression requires OsDCL1. We predicted their targets and used 5'RACE to validate cleavage for three of them, targeting a PPR, an SPX domain protein and a GT-like transcription factor respectively. In addition, we identified precursor transcripts for the 6 miRNAs expressed in rice, showing that these precursors can be efficiently processed using a transient expression assay in transfected Nicotiana benthamiana leaves. Most interestingly, we describe two precursors producing tandem miRNAs, but in distinct arrays. We focus on one of them encoding osa-miR159a.2, a novel miRNA produced from the same stem-loop structure encoding the conserved osa-miR159a.1. We show that this dual osa-miR159a.2-osa-miR159a.1 structure is conserved in distant rice species and maize. Finally we show that the predicted mRNA target of osa-miR159a.2 encoding a GT-like transcription factor is cleaved in vivo at the expected site. CONCLUSION: The combination of approaches developed here identified six novel miRNAs expressed in rice which can be clearly distinguished from siRNAs. Importantly, we show that two miRNAs can be produced from a single precursor, either from tandem stem-loops or tandemly arrayed in a single stem-loop. This suggests that processing of these precursors could be an important regulatory step to produce one or more functional miRNAs in plants and perhaps coordinate cleavage of distinct targets in the same plant tissue.