Cell-to-cell stochastic variation in gene expression is a complex genetic trait.
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.
Affiliation: Université de Lyon, Lyon, France.
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.
Related in: MedlinePlus
Mentions: We then sought to map genetic variations underlying noise differences between S288c and RM11-1a, which we did by two methods. Firstly, using the noise values of the 61 segregants from S288cxRM11-1a and their genotypes at 3042 marker positions, we screened the genome for Quantitative Trait Loci (QTL). Two QTL were found (position 79091 on chromosome III and position 449639 on chromosome XIV) at a genome-wide significance of 1% (Figure 2A). Secondly, we introgressed the high-noise phenotype of RM11-1a into the S288c background, and searched for alleles that had been conserved from RM11-1a in the resulting strains (see Materials and Methods). This approach identified a region on chromosome V (from position 116530 to 207819) as a candidate region for conferring high-noise level (Figure 2B). To validate or refute this locus as a QTL, we backcrossed GY157, the S288c×RM11-1a segregant showing highest noise, with an S288c derivative. Fifty five random spores from this cross were analyzed by flow cytometry to quantify their level of HIS3:PMET17-GFP noise. We took advantage of the presence of the ura3Δ0 auxotrophic marker within the region of interest to genotype the 55 spores by plating them on URA-plates. A significant linkage was found between these genotypes and noise levels (Wilcoxon-Mann Whitney test, P = 3.5×10−3) (Figure 3C), which validated the locus as a third QTL. The three QTL identified showed the following characteristics: Firstly, in all three cases, the molecular control of noise involves trans-regulations (a polymorphism in one gene affecting noise level of another gene) because none of the QTL were located at or near the HIS3 integration site nor the MET17 endogenous regulatory region. Secondly, QTL1 and QTL2 but not QTL3 were also in genetic linkage with the mean expression levels of the samples (Figure 3). Consistently, QTL1 was already detected as an expression QTL (eQTL) locus controlling MET17 mRNA levels in a previous study where only mean expression was measured. This indicated that regulatory variation could scale noise levels by acting on mean expression, raising the possibility that other eQTL identified by ‘genetical genomics’ are likely to influence noise as well. Thirdly, and surprisingly, the effects of QTL1 and QTL2 were opposite to the effects expected from the parental difference: alleles from the high-noise background RM11-1a conferred low noise (Figure 3A–B). This was consistent with the transgressive segregation visible on Figure 1C and it supported the presence of additional QTL (such as QTL3) where RM11-1a alleles conferred high noise. Finally, QTL3 effect was extremely low in the panel of S288cxRM11-1a segregants (P = 0.4 from linear regression). From these observations, we conclude that the difference in noise between S288c and RM11-1a backgrounds can not be attributed to one or a few loci but rather results from the cumulative effects of numerous QTL, several of which remain to be identified.