Natural gene expression variation studies in yeast

Thompson, Dawn; Cubillos, Francisco A.

doi:10.1002/yea.3210

Cited by 18 publications

(14 citation statements)

References 148 publications

(238 reference statements)

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“…However, if we focus on just one genotype, regardless of URA3 sol or URA3 agg , we obtain higher noise when uracil is added. This is consistent with the current view that the maximum population variance is achieved under conditions with no selection (Thompson & Cubillos, ). Interestingly, the cell‐to‐cell variation in protein abundance is higher in the deposits compared to the cytosol for URA3 agg irrespective of whether Ura3p is essential non‐essential or toxic (Fig C).…”

Section: Resultssupporting

confidence: 92%

The fitness cost and benefit of phase‐separated protein deposits

Groot

Torrent

Ravarani

et al. 2019

Molecular Systems Biology

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Phase separation of soluble proteins into insoluble deposits is associated with numerous diseases. However, protein deposits can also function as membrane‐less compartments for many cellular processes. What are the fitness costs and benefits of forming such deposits in different conditions? Using a model protein that phase‐separates into deposits, we distinguish and quantify the fitness contribution due to the loss or gain of protein function and deposit formation in yeast. The environmental condition and the cellular demand for the protein function emerge as key determinants of fitness. Protein deposit formation can influence cell‐to‐cell variation in free protein abundance between individuals of a cell population (i.e., gene expression noise). This results in variable manifestation of protein function and a continuous range of phenotypes in a cell population, favoring survival of some individuals in certain environments. Thus, protein deposit formation by phase separation might be a mechanism to sense protein concentration in cells and to generate phenotypic variability. The selectable phenotypic variability, previously described for prions, could be a general property of proteins that can form phase‐separated assemblies and may influence cell fitness.

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Section: Resultssupporting

confidence: 92%

The fitness cost and benefit of phase‐separated protein deposits

Groot

Torrent

Ravarani

et al. 2019

Molecular Systems Biology

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“…There is also a positive association between galactose metabolism ability and the flower/Ipomoea isolation environment and a negative association between galactose metabolism ability and tree or insect frass isolation environments [54]. While gene gain and loss in budding yeasts may play an important role in ecological adaptation, variation in gene expression is also a likely contributor [55][56][57]. The recent publication of 332 budding yeast genomes and the identification of translational selection on codon usage in a majority of these species provide a unique opportunity to test for differences in GAL gene expression-inferred from optimal codon usage-across ecological niches inferred from recorded isolation environments [54,[58][59][60].…”

Section: Introductionmentioning

confidence: 99%

Signatures of optimal codon usage predict metabolic ecology in budding yeasts

LaBella

Opulente

Steenwyk

et al. 2020

Preprint

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Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically-relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the thiamine biosynthesis and GAL pathways. As a result, optimal codon usage in thiamine biosynthesis genes is also associated with dairy ecological niches in Saccharomycetaceae, which may reflect competition with co-occurring microbes for extracellular thiamine. This work highlights the potential of codon optimization as a tool for gaining insights into the metabolic ecology of microbial eukaryotes. Doing so may be especially illuminating for studying fungal dark matter—species that have yet to be cultured in the lab or have only been identified by genomic material.

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“…Thus, non-invasive nor mutagenic strategies represent an alternative where variants of interest are selected from standing natural genetic variation ( Cubillos, 2016 ). S. cerevisiae strains are genotypically and phenotypically highly variable, and thus are an ideal model for studying trait improvement ( Thompson and Cubillos, 2017 ; Peter et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

“…Although, these regions explain a substantial fraction of the natural phenotypic variation between individuals, a wide set of variants across eukaryotes are located within non-coding regions and finely modulate gene expression and ultimately phenotypes ( Wray, 2007 ). In this context, non-coding regions have been less explored in yeast and could be useful for genetic breeding and industrial applications via the modulation of gene regulation and expression ( Thompson and Cubillos, 2017 ). Previous expression profiles of S. cerevisiae isolates obtained from different ecological niches have demonstrated that the genetic control of expression is well-defined ( Fay et al, 2004 ; Kvitek et al, 2008 ; Ehrenreich et al, 2009 ; Zhu et al, 2009 ; Fraser et al, 2010 ; Cubillos et al, 2012 ).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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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.

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Natural gene expression variation studies in yeast

Cited by 18 publications

References 148 publications

The fitness cost and benefit of phase‐separated protein deposits

The fitness cost and benefit of phase‐separated protein deposits

Signatures of optimal codon usage predict metabolic ecology in budding yeasts

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

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