Different trajectories of polyploidization shape the genomic landscape of the Brettanomyces bruxellensis yeast species.

Polyploidization events are observed across the tree of life and occur in many fungi, plant, and animal species. During evolution, polyploidy is thought to be an important source of speciation and tumorigenesis. However, the origin of polyploid populations is not always clear, and little is known about the precise nature and structure of their complex genome. Using a long-read sequencing strategy, we sequenced 71 strains from the Brettanomyces bruxellensis yeast species, which is found in anthropized environments (e.g., beer, contaminant of wine, kombucha, and ethanol production) and characterized by several polyploid subpopulations. To reconstruct the polyploid genomes, we phased them by using different strategies and found that each subpopulation had a unique polyploidization history with distinct trajectories. The polyploid genomes contain either genetically closely related (with a genetic divergence <1%) or diverged copies (>3%), indicating auto- as well as allopolyploidization events. These latest events have occurred independently with a specific and unique donor in each of the polyploid subpopulations and exclude the known Brettanomyces sister species as possible donors. Finally, loss of heterozygosity events has shaped the structure of these polyploid genomes and underline their dynamics. Overall, our study highlights the multiplicity of the trajectories leading to polyploid genomes within the same species.

nPhase: an accurate and contiguous phasing method for polyploids.

While genome sequencing and assembly are now routine, we do not have a full, precise picture of polyploid genomes. No existing polyploid phasing method provides accurate and contiguous haplotype predictions. We developed nPhase, a ploidy agnostic tool that leverages long reads and accurate short reads to solve alignment-based phasing for samples of unspecified ploidy ( https://github.com/OmarOakheart/nPhase ). nPhase is validated by tests on simulated and real polyploids. nPhase obtains on average over 95% accuracy and a contiguous 1.25 haplotigs per haplotype to cover more than 90% of each chromosome (heterozygosity rate ≥ 0.5%). nPhase allows population genomics and hybrid studies of polyploids.

Flor Yeasts Rewire the Central Carbon Metabolism During Wine Alcoholic Fermentation.

The identification of natural allelic variations controlling quantitative traits could contribute to decipher metabolic adaptation mechanisms within different populations of the same species. Such variations could result from human-mediated selection pressures and participate to the domestication. In this study, the genetic causes of the phenotypic variability of the central carbon metabolism of Saccharomyces cerevisiae were investigated in the context of the enological fermentation. The genetic determinism of this trait was found out by a quantitative trait loci (QTL) mapping approach using the offspring of two strains belonging to the wine genetic group of the species. A total of 14 QTL were identified from which 8 were validated down to the gene level by genetic engineering. The allelic frequencies of the validated genes within 403 enological strains showed that most of the validated QTL had allelic variations involving flor yeast specific alleles. Those alleles were brought in the offspring by one parental strain that contains introgressions from the flor yeast genetic group. The causative genes identified are functionally linked to quantitative proteomic variations that would explain divergent metabolic features of wine and flor yeasts involving the tricarboxylic acid cycle (TCA), the glyoxylate shunt and the homeostasis of proton and redox cofactors. Overall, this work led to the identification of genetic factors that are hallmarks of adaptive divergence between flor yeast and wine yeast in the wine biotope. These results also reveal that introgressions originated from intraspecific hybridization events promoted phenotypic variability of carbon metabolism observed in wine strains.

Extensive impact of low-frequency variants on the phenotypic landscape at population-scale.

Genome-wide association studies (GWAS) allow to dissect complex traits and map genetic variants, which often explain relatively little of the heritability. One potential reason is the preponderance of undetected low-frequency variants. To increase their allele frequency and assess their phenotypic impact in a population, we generated a diallel panel of 3025 yeast hybrids, derived from pairwise crosses between natural isolates and examined a large number of traits. Parental versus hybrid regression analysis showed that while most phenotypic variance is explained by additivity, a third is governed by non-additive effects, with complete dominance having a key role. By performing GWAS on the diallel panel, we found that associated variants with low frequency in the initial population are overrepresented and explain a fraction of the phenotypic variance as well as an effect size similar to common variants. Overall, we highlighted the relevance of low-frequency variants on the phenotypic variation.