Saccharomyces cerevisiae CEN.PK 113-7D is widely used for metabolic engineering and systems biology research in industry and academia. We sequenced, assembled, annotated and analyzed its genome. Single-nucleotide variations (SNV), insertions/deletions (indels) and differences in genome organization compared to the reference strain S. cerevisiae S288C were analyzed. In addition to a few large deletions and duplications, nearly 3000 indels were identified in the CEN.PK113-7D genome relative to S288C. These differences were overrepresented in genes whose functions are related to transcriptional regulation and chromatin remodelling. Some of these variations were caused by unstable tandem repeats, suggesting an innate evolvability of the corresponding genes. Besides a previously characterized mutation in adenylate cyclase, the CEN.PK113-7D genome sequence revealed a significant enrichment of non-synonymous mutations in genes encoding for components of the cAMP signalling pathway. Some phenotypic characteristics of the CEN.PK113-7D strains were explained by the presence of additional specific metabolic genes relative to S288C. In particular, the presence of the BIO1 and BIO6 genes correlated with a biotin prototrophy of CEN.PK113-7D. Furthermore, the copy number, chromosomal location and sequences of the MAL loci were resolved. The assembled sequence reveals that CEN.PK113-7D has a mosaic genome that combines characteristics of laboratory strains and wild-industrial strains.

Lager brewing strains of Saccharomyces pastorianus are natural interspecific hybrids originating from the spontaneous hybridization of Saccharomyces cerevisiae and Saccharomyces eubayanus. Over the past 500 years, S. pastorianus has been domesticated to become one of the most important industrial microorganisms. Production of lager-type beers requires a set of essential phenotypes, including the ability to ferment maltose and maltotriose at low temperature, the production of flavors and aromas, and the ability to flocculate. Understanding of the molecular basis of complex brewing-related phenotypic traits is a prerequisite for rational strain improvement. While genome sequences have been reported, the variability and dynamics of S. pastorianus genomes have not been investigated in detail. Here, using deep sequencing and chromosome copy number analysis, we showed that S. pastorianus strain CBS1483 exhibited extensive aneuploidy. This was confirmed by quantitative PCR and by flow cytometry. As a direct consequence of this aneuploidy, a massive number of sequence variants was identified, leading to at least 1,800 additional protein variants in S. pastorianus CBS1483. Analysis of eight additional S. pastorianus strains revealed that the previously defined group I strains showed comparable karyotypes, while group II strains showed large interstrain karyotypic variability. Comparison of three strains with nearly identical genome sequences revealed substantial chromosome copy number variation, which may contribute to strain-specific phenotypic traits. The observed variability of lager yeast genomes demonstrates that systematic linking of genotype to phenotype requires a three-dimensional genome analysis encompassing physical chromosomal structures, the copy number of individual chromosomes or chromosomal regions, and the allelic variation of copies of individual genes.

Significance The shift from unicellular to multicellular life forms represents a key innovation step in the evolution of life on Earth. However, knowledge on the evolutionary pressures resulting in the selection of multicellular life forms and the underlying molecular mechanisms is far from complete. Our study provides a complete identification of the specific genetic changes by which the unicellular eukaryote S. cerevisiae can acquire a multicellular, fast-sedimenting phenotype. We demonstrated that a minimal evolutionary mechanism encompassed a deregulation of the late step of the cell cycle through mutation in ACE2 followed by whole genome duplication.

Here, we develop and test an algorithm, named Magnolya, that uses a Poisson mixture model for copy number estimation of contigs assembled from sequencing data. We combine this with co-assembly to allow de novo detection of copy number variation (CNV) between two individual genomes, without mapping reads to a reference genome. In co-assembly, multiple sequencing samples are combined, generating a single contig graph with different traversal counts for the nodes and edges between the samples. In the resulting 'coloured' graph, the contigs have integer copy numbers; this negates the need to segment genomic regions based on depth of coverage, as required for mapping-based detection methods. Magnolya is then used to assign integer copy numbers to contigs, after which CNV probabilities are easily inferred. The copy number estimator and CNV detector perform well on simulated data. Application of the algorithms to hybrid yeast genomes showed allotriploid content from different origin in the wine yeast Y12, and extensive CNV in aneuploid brewing yeast genomes. Integer CNV was also accurately detected in a short-term laboratory-evolved yeast strain.