title: Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications.
abstract: BACKGROUND
  The need for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering.
  
  
  RESULTS
  In this work we performed whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between Saccharomyces cerevisiae strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the Saccharomyces Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,596 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being nonsynonymous (e.g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (GAL1, GAL10) and ergosterol biosynthetic pathway (ERG8, ERG9). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function.
  
  
  CONCLUSIONS
  With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at http://www.sysbio.se/cenpk.
authors.affiliation: Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-41296 Gothenburg, Sweden. nielsenj@chalmers.se
authors.forename: José Manuel
authors.initials: JM
authors.lastname: Otero
authors.forename: Wanwipa
authors.initials: W
authors.lastname: Vongsangnak
authors.forename: Mohammad A
authors.initials: MA
authors.lastname: Asadollahi
authors.forename: Roberto
authors.initials: R
authors.lastname: Olivares-Hernandes
authors.forename: Jérôme
authors.initials: J
authors.lastname: Maury
authors.forename: Laurent
authors.initials: L
authors.lastname: Farinelli
authors.forename: Loïc
authors.initials: L
authors.lastname: Barlocher
authors.forename: Magne
authors.initials: M
authors.lastname: Osterås
authors.forename: Michel
authors.initials: M
authors.lastname: Schalk
authors.forename: Anthony
authors.initials: A
authors.lastname: Clark
authors.forename: Jens
authors.initials: J
authors.lastname: Nielsen
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000378:metabolism; D001483:Base Sequence; D015825:Chromosomes, Fungal / Q000235:genetics; D004875:Ergosterol / Q000378:metabolism; D005656:Fungal Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D005690:Galactose / Q000378:metabolism; D020869:Gene Expression Profiling; D015966:Gene Expression Regulation, Fungal; D005818:Genetic Engineering / Q000379:methods*; D016681:Genome, Fungal / Q000235:genetics*; D005838:Genotype; D058977:Molecular Sequence Annotation; D008969:Molecular Sequence Data; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism*; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D000596:Amino Acids; D005656:Fungal Proteins; D005690:Galactose; D004875:Ergosterol