Literature DB >> 33563210

Identification of novel genes involved in neutral lipid storage by quantitative trait loci analysis of Saccharomyces cerevisiae.

Uroš Petrovič1,2, Klaus Natter3, Klavdija Pačnik4, Mojca Ogrizović5, Matthias Diepold4, Tobias Eisenberg4,6,7, Mia Žganjar4,8, Gašper Žun5,8, Beti Kužnik5, Cene Gostinčar5,9, Tomaž Curk10.   

Abstract

BACKGROUND: The accumulation of intracellular fat depots is a polygenic trait. Therefore, the extent of lipid storage in the individuals of a species covers a broad range and is determined by many genetic factors. Quantitative trait loci analysis can be used to identify those genetic differences between two strains of the same species that are responsible for the differences in a given phenotype. We used this method and complementary approaches to identify genes in the yeast Saccharomyces cerevisiae that are involved in neutral lipid storage.
RESULTS: We selected two yeast strains, the laboratory strain BY4741 and the wine yeast AWRI1631, with a more than two-fold difference in neutral lipid content. After crossing, sporulation and germination, we used fluorescence activated cell sorting to isolate a subpopulation of cells with the highest neutral lipid content from the pool of segregants. Whole genome sequencing of this subpopulation and of the unsorted pool of segregants implicated several loci that are involved in lipid accumulation. Three of the identified genes, PIG1, PHO23 and RML2, were investigated in more detail. Deletions of these genes and the exchange of the alleles between the two parental strains confirmed that the encoded proteins contribute to neutral lipid storage in S. cerevisiae and that PIG1, PHO23 and RML2 are the major causative genes. Backcrossing of one of the segregants with the parental strains for seven generations revealed additional regions in the genomes of both strains with potential causative genes for the high lipid accumulation phenotype.
CONCLUSIONS: We identified several genes that contribute to the phenotype of lipid accumulation in an allele-specific manner. Surprisingly, no allelic variations of genes with known functions in lipid metabolism were found, indicating that the level of storage lipid accumulation is determined by many cellular processes that are not directly related to lipid metabolism.

Entities:  

Keywords:  QTL analysis; baker’s yeast; lipid droplet; lipid metabolism; natural variation; polygenic trait; steryl esters; triacylglycerol

Mesh:

Substances:

Year:  2021        PMID: 33563210      PMCID: PMC7871550          DOI: 10.1186/s12864-021-07417-4

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


  45 in total

1.  Dual targeting of Osh1p, a yeast homologue of oxysterol-binding protein, to both the Golgi and the nucleus-vacuole junction.

Authors:  T P Levine; S Munro
Journal:  Mol Biol Cell       Date:  2001-06       Impact factor: 4.138

2.  A yeast strain defective in oleic acid utilization has a mutation in the RML2 gene.

Authors:  P J Trotter; R A Hagerman; D R Voelker
Journal:  Biochim Biophys Acta       Date:  1999-05-18

3.  Nutritional requirements of the BY series of Saccharomyces cerevisiae strains for optimum growth.

Authors:  Michael Hanscho; David E Ruckerbauer; Neha Chauhan; Harald F Hofbauer; Stefan Krahulec; Bernd Nidetzky; Sepp D Kohlwein; Juergen Zanghellini; Klaus Natter
Journal:  FEMS Yeast Res       Date:  2012-07-31       Impact factor: 2.796

4.  Revealing the genetic structure of a trait by sequencing a population under selection.

Authors:  Leopold Parts; Francisco A Cubillos; Jonas Warringer; Kanika Jain; Francisco Salinas; Suzannah J Bumpstead; Mikael Molin; Amin Zia; Jared T Simpson; Michael A Quail; Alan Moses; Edward J Louis; Richard Durbin; Gianni Liti
Journal:  Genome Res       Date:  2011-03-21       Impact factor: 9.043

5.  Dissection of genetically complex traits with extremely large pools of yeast segregants.

Authors:  Ian M Ehrenreich; Noorossadat Torabi; Yue Jia; Jonathan Kent; Stephen Martis; Joshua A Shapiro; David Gresham; Amy A Caudy; Leonid Kruglyak
Journal:  Nature       Date:  2010-04-15       Impact factor: 49.962

6.  Genome-wide detection of polymorphisms at nucleotide resolution with a single DNA microarray.

Authors:  David Gresham; Douglas M Ruderfer; Stephen C Pratt; Joseph Schacherer; Maitreya J Dunham; David Botstein; Leonid Kruglyak
Journal:  Science       Date:  2006-03-09       Impact factor: 47.728

7.  ggbio: an R package for extending the grammar of graphics for genomic data.

Authors:  Tengfei Yin; Dianne Cook; Michael Lawrence
Journal:  Genome Biol       Date:  2012-08-31       Impact factor: 13.583

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

Authors:  Matthias Eder; Isabelle Sanchez; Claire Brice; Carole Camarasa; Jean-Luc Legras; Sylvie Dequin
Journal:  BMC Genomics       Date:  2018-03-01       Impact factor: 3.969

Review 9.  Yeast Cells Exposed to Exogenous Palmitoleic Acid Either Adapt to Stress and Survive or Commit to Regulated Liponecrosis and Die.

Authors:  Karamat Mohammad; Paméla Dakik; Younes Medkour; Mélissa McAuley; Darya Mitrofanova; Vladimir I Titorenko
Journal:  Oxid Med Cell Longev       Date:  2018-01-31       Impact factor: 6.543

10.  Uncovering Natural Longevity Alleles from Intercrossed Pools of Aging Fission Yeast Cells.

Authors:  David A Ellis; Ville Mustonen; María Rodríguez-López; Charalampos Rallis; Michał Malecki; Daniel C Jeffares; Jürg Bähler
Journal:  Genetics       Date:  2018-08-02       Impact factor: 4.562

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