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Cell-to-cell stochastic variation in gene expression is a complex genetic trait.

Ansel J, Bottin H, Rodriguez-Beltran C, Damon C, Nagarajan M, Fehrmann S, François J, Yvert G - PLoS Genet. (2008)

Bottom Line: We found that noise was highly heritable and placed under a complex genetic control.Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background.The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits.

View Article: PubMed Central - PubMed

Affiliation: Université de Lyon, Lyon, France.

ABSTRACT
The genetic control of common traits is rarely deterministic, with many genes contributing only to the chance of developing a given phenotype. This incomplete penetrance is poorly understood and is usually attributed to interactions between genes or interactions between genes and environmental conditions. Because many traits such as cancer can emerge from rare events happening in one or very few cells, we speculate an alternative and complementary possibility where some genotypes could facilitate these events by increasing stochastic cell-to-cell variations (or 'noise'). As a very first step towards investigating this possibility, we studied how natural genetic variation influences the level of noise in the expression of a single gene using the yeast S. cerevisiae as a model system. Reproducible differences in noise were observed between divergent genetic backgrounds. We found that noise was highly heritable and placed under a complex genetic control. Scanning the genome, we mapped three Quantitative Trait Loci (QTL) of noise, one locus being explained by an increase in noise when transcriptional elongation was impaired. Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background. The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits.

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Related in: MedlinePlus

Strain-to-strain variation and complex genetic segregation of noise.A) Five representative flow-cytometry experiments on strains GY51, GY43, GY44, GY53 and GY445 derived from S288c, FL200, CEN.PK, RM11-1a and Y9J_1 respectively, each showing the distribution of PMET17-GFP expression levels in 15,000 individual cells (events) after two hours of moderate induction. Raw fluorescent values were corrected for cell size and granularity as described in Materials and Methods. Mean expression levels were similar between strains, while variances differed. B) Boxplot representation of flow-cytometry experiments repeated n times in the same conditions as in A), showing reproducible noise differences between genetic backgrounds. C–D) Genetic segregation of PMET17-GFP noise in a cross between S288c and RM11-1a backgrounds. Colored dots in C) represent independent flow-cytometry experiments performed on strain GY51 (red) or strain GY53 (blue). Each open circle represents the average values of three experiments performed on one S288c×RM11-1a segregant. The distribution of noise values in these segregants is shown in D), with the average noise of GY51 and GY53 represented as red and blue crosses, respectively. The arrow points to segregant GY157 displaying extremely high noise. E–F) Genetic segregation of PMET17-GFP noise in a cross between FL200 and CEN.PK backgrounds. Representation is similar as in C) and D), with repeated experiments on strain GY43 and GY44 shown in green and magenta, respectively. One flow-cytometry experiment was performed on each segregant obtained by crossing GY43 and GY44 (open circles). All segregants analyzed possessed the ura3-52 mutation of GY44, and their differences must therefore result from allelic variations residing in other genes.
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pgen-1000049-g001: Strain-to-strain variation and complex genetic segregation of noise.A) Five representative flow-cytometry experiments on strains GY51, GY43, GY44, GY53 and GY445 derived from S288c, FL200, CEN.PK, RM11-1a and Y9J_1 respectively, each showing the distribution of PMET17-GFP expression levels in 15,000 individual cells (events) after two hours of moderate induction. Raw fluorescent values were corrected for cell size and granularity as described in Materials and Methods. Mean expression levels were similar between strains, while variances differed. B) Boxplot representation of flow-cytometry experiments repeated n times in the same conditions as in A), showing reproducible noise differences between genetic backgrounds. C–D) Genetic segregation of PMET17-GFP noise in a cross between S288c and RM11-1a backgrounds. Colored dots in C) represent independent flow-cytometry experiments performed on strain GY51 (red) or strain GY53 (blue). Each open circle represents the average values of three experiments performed on one S288c×RM11-1a segregant. The distribution of noise values in these segregants is shown in D), with the average noise of GY51 and GY53 represented as red and blue crosses, respectively. The arrow points to segregant GY157 displaying extremely high noise. E–F) Genetic segregation of PMET17-GFP noise in a cross between FL200 and CEN.PK backgrounds. Representation is similar as in C) and D), with repeated experiments on strain GY43 and GY44 shown in green and magenta, respectively. One flow-cytometry experiment was performed on each segregant obtained by crossing GY43 and GY44 (open circles). All segregants analyzed possessed the ura3-52 mutation of GY44, and their differences must therefore result from allelic variations residing in other genes.

Mentions: To investigate the natural genetic diversity of noise in the expression of a representative gene, we integrated in the genome of five distant S. cerevisiae strains a reporter construct where the green fluorescent protein (GFP) was regulated by the inducible promoter of the MET17 (YLR303W) gene. The strains used were three unrelated laboratory strains (S288c, FL200 and CEN.PK), a wine strain from California (RM11-1a), and a wine strain from Japan (Y9J_1). In each case the construct was integrated at the same HIS3 chromosomal locus. We then quantified the level of expression in individual living cells by flow cytometry. Figure 1A shows representative experiments where 15,000 cells were recorded for each background after two hours of moderate induction. We found that although mean induction was similar between backgrounds, the variance of gene expression level differed. This observation was reproduced when the experiments were repeated at various dates (Figure 1B). This suggested the presence of genetic variation that might control noise without necessarily affecting mean expression of the cell population. To see if the difference in noise between S288c and RM11-1a was specific to the chromosomal environment of the HIS3 locus, we integrated the same reporter system at the LYS2 locus located on another chromosome (Figure S1). Noise and mean expression values were comparable to the results obtained when targeting HIS3, showing that the difference in noise between the two strains could not be accounted for by differences at the integration locus only.


Cell-to-cell stochastic variation in gene expression is a complex genetic trait.

Ansel J, Bottin H, Rodriguez-Beltran C, Damon C, Nagarajan M, Fehrmann S, François J, Yvert G - PLoS Genet. (2008)

Strain-to-strain variation and complex genetic segregation of noise.A) Five representative flow-cytometry experiments on strains GY51, GY43, GY44, GY53 and GY445 derived from S288c, FL200, CEN.PK, RM11-1a and Y9J_1 respectively, each showing the distribution of PMET17-GFP expression levels in 15,000 individual cells (events) after two hours of moderate induction. Raw fluorescent values were corrected for cell size and granularity as described in Materials and Methods. Mean expression levels were similar between strains, while variances differed. B) Boxplot representation of flow-cytometry experiments repeated n times in the same conditions as in A), showing reproducible noise differences between genetic backgrounds. C–D) Genetic segregation of PMET17-GFP noise in a cross between S288c and RM11-1a backgrounds. Colored dots in C) represent independent flow-cytometry experiments performed on strain GY51 (red) or strain GY53 (blue). Each open circle represents the average values of three experiments performed on one S288c×RM11-1a segregant. The distribution of noise values in these segregants is shown in D), with the average noise of GY51 and GY53 represented as red and blue crosses, respectively. The arrow points to segregant GY157 displaying extremely high noise. E–F) Genetic segregation of PMET17-GFP noise in a cross between FL200 and CEN.PK backgrounds. Representation is similar as in C) and D), with repeated experiments on strain GY43 and GY44 shown in green and magenta, respectively. One flow-cytometry experiment was performed on each segregant obtained by crossing GY43 and GY44 (open circles). All segregants analyzed possessed the ura3-52 mutation of GY44, and their differences must therefore result from allelic variations residing in other genes.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2289839&req=5

pgen-1000049-g001: Strain-to-strain variation and complex genetic segregation of noise.A) Five representative flow-cytometry experiments on strains GY51, GY43, GY44, GY53 and GY445 derived from S288c, FL200, CEN.PK, RM11-1a and Y9J_1 respectively, each showing the distribution of PMET17-GFP expression levels in 15,000 individual cells (events) after two hours of moderate induction. Raw fluorescent values were corrected for cell size and granularity as described in Materials and Methods. Mean expression levels were similar between strains, while variances differed. B) Boxplot representation of flow-cytometry experiments repeated n times in the same conditions as in A), showing reproducible noise differences between genetic backgrounds. C–D) Genetic segregation of PMET17-GFP noise in a cross between S288c and RM11-1a backgrounds. Colored dots in C) represent independent flow-cytometry experiments performed on strain GY51 (red) or strain GY53 (blue). Each open circle represents the average values of three experiments performed on one S288c×RM11-1a segregant. The distribution of noise values in these segregants is shown in D), with the average noise of GY51 and GY53 represented as red and blue crosses, respectively. The arrow points to segregant GY157 displaying extremely high noise. E–F) Genetic segregation of PMET17-GFP noise in a cross between FL200 and CEN.PK backgrounds. Representation is similar as in C) and D), with repeated experiments on strain GY43 and GY44 shown in green and magenta, respectively. One flow-cytometry experiment was performed on each segregant obtained by crossing GY43 and GY44 (open circles). All segregants analyzed possessed the ura3-52 mutation of GY44, and their differences must therefore result from allelic variations residing in other genes.
Mentions: To investigate the natural genetic diversity of noise in the expression of a representative gene, we integrated in the genome of five distant S. cerevisiae strains a reporter construct where the green fluorescent protein (GFP) was regulated by the inducible promoter of the MET17 (YLR303W) gene. The strains used were three unrelated laboratory strains (S288c, FL200 and CEN.PK), a wine strain from California (RM11-1a), and a wine strain from Japan (Y9J_1). In each case the construct was integrated at the same HIS3 chromosomal locus. We then quantified the level of expression in individual living cells by flow cytometry. Figure 1A shows representative experiments where 15,000 cells were recorded for each background after two hours of moderate induction. We found that although mean induction was similar between backgrounds, the variance of gene expression level differed. This observation was reproduced when the experiments were repeated at various dates (Figure 1B). This suggested the presence of genetic variation that might control noise without necessarily affecting mean expression of the cell population. To see if the difference in noise between S288c and RM11-1a was specific to the chromosomal environment of the HIS3 locus, we integrated the same reporter system at the LYS2 locus located on another chromosome (Figure S1). Noise and mean expression values were comparable to the results obtained when targeting HIS3, showing that the difference in noise between the two strains could not be accounted for by differences at the integration locus only.

Bottom Line: We found that noise was highly heritable and placed under a complex genetic control.Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background.The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits.

View Article: PubMed Central - PubMed

Affiliation: Université de Lyon, Lyon, France.

ABSTRACT
The genetic control of common traits is rarely deterministic, with many genes contributing only to the chance of developing a given phenotype. This incomplete penetrance is poorly understood and is usually attributed to interactions between genes or interactions between genes and environmental conditions. Because many traits such as cancer can emerge from rare events happening in one or very few cells, we speculate an alternative and complementary possibility where some genotypes could facilitate these events by increasing stochastic cell-to-cell variations (or 'noise'). As a very first step towards investigating this possibility, we studied how natural genetic variation influences the level of noise in the expression of a single gene using the yeast S. cerevisiae as a model system. Reproducible differences in noise were observed between divergent genetic backgrounds. We found that noise was highly heritable and placed under a complex genetic control. Scanning the genome, we mapped three Quantitative Trait Loci (QTL) of noise, one locus being explained by an increase in noise when transcriptional elongation was impaired. Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background. The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits.

Show MeSH
Related in: MedlinePlus