Genetic Regulation of Phenotypic Plasticity and Canalisation in Yeast Growth

Abstract

The ability of a genotype to show diverse phenotypes in different environments is called phenotypic plasticity. Phenotypic plasticity helps populations to evade extinctions in novel environments, facilitates adaptation and fuels evolution. However, most studies focus on understanding the genetic basis of phenotypic regulation in specific environments. As a result, while it's evolutionary relevance is well established, genetic mechanisms regulating phenotypic plasticity and their overlap with the environment specific regulators is not well understood. Saccharomyces cerevisiae is highly sensitive to the environment, which acts as not just external stimulus but also as signalling cue for this unicellular, sessile organism. We used a previously published dataset of a biparental yeast population grown in 34 diverse environments and mapped genetic loci regulating variation in phenotypic plasticity, plasticity QTL, and compared them with environment-specific QTL. Plasticity QTL is one whose one allele exhibits high plasticity whereas the other shows a relatively canalised behaviour. We mapped phenotypic plasticity using two parameters-environmental variance, an environmental order-independent parameter and reaction norm (slope), an environmental order-dependent parameter. Our results show a partial overlap between pleiotropic QTL and plasticity QTL such that while some plasticity QTL are also pleiotropic, others have a significant effect on phenotypic plasticity without being significant in any environment independently. Furthermore, while some plasticity QTL are revealed only in specific environmental orders, we identify large effect plasticity QTL, which are order-independent such that whatever the order of the environments, one allele is always plastic and the other is canalised. Finally, we show that the environments can be divided into two categories based on the phenotypic diversity of the population within them and the two categories have differential regulators of phenotypic plasticity. Our results highlight the importance of identifying genetic regulators of phenotypic plasticity to comprehensively understand the genotype-phenotype map.

Fig 1. Schematic showing dependence of phenotypic plasticity parameters on the order of the environments.

Genotype A1 and A2 are represented in blue and red colours respectively. Var_E refers to environmental variance whereas ${\displaystyle \sum Slope}$ refers to sum of slopes, as described in Methods. y-axis denotes the phenotype and x-axis denotes discrete environments arranged in different orders. (A) Genotype A1 and A2 have significant differences in multiple environments but are both equally plastic. (B) A1 is plastic and A2 is canalised. (C) and (D) shows the same environments arranged in different orders which have no effect on environmental variance but have different impact on reaction norms or sum of slopes.

Fig 2. Categorisation of environments based on phenotypic variance.

(A) Phenotypic variance of ~1,000 segregants (x-axis) across different environments (y-axis). (B) Phenotypic variance of ~1,000 segregants (y-axis) within each environment (x-axis). Green colour refers to environments with low phenotypic variance (Lv) and pink refers to environments with high phenotypic variance (Hv). The dashed line indicates the median of the distribution. (C) Comparison of phenotypic variance of ~1000 segregants between Hv (y-axis) and Lv (x-axis) environments. A low regression coefficient indicates poor correlation between the two.

Fig 3. QTL mapping of environmental variance in Hv and Lv environments.

(A) LOD score distribution plot of environmental variance across Hv environments. The dashed line represent the LOD cut off of 2.0, permutation P < 0.01. (B) Dot plot of marker at chrV (201,987). (C) Dot plot of marker at chrXIII (46,211). (D) LOD score distribution plot of environmental variance across Lv environments. The dashed line represent the LOD cut off of 2.0, permutation P < 0.01. (E) Dot plot of marker at chrXIV (374,661). Red and blue colours denote BY and RM alleles respectively.

Fig 4. QTL mapping of reaction norms in Hv and Lv environments using allele specific orders.

(A) and (B) show LOD score distribution plots of reaction norms using allele specific order across Hv environments. The dashed line represent the LOD cut off of 4.0 in A and B respectively, permutation P < 0.01. (C) and (D) show LOD score distribution plots of reaction norms using allele specific order across Lv environments. The dashed line represent the LOD cut off of 5.0 in C and D respectively, permutation P < 0.01. Red and blue plots indicated QTL mapping performed by canalising BY and RM alleles, respectively.

Fig 5. Phenotypic plasticity observed within canalised mean effects.

Reaction norms of segregants carrying RM allele of marker chrXIII (45,801) in Hv environments (A), and BY allele of marker chrXIV (364,968) in Lv environments (B). In both the plots, the environments are arranged such that the mean phenotype, denoted by the black line, has the least possible value of sum of slopes. Reaction norms for 10 random segregants have been highlighted as blue, RM, and red, BY in the two plots and reaction norms of other segregants are represented in grey lines.

Fig 6. Comparison of mean and variance of allelic reaction norms.

Comparison of difference in mean and variance of the alleles of peaks identified in 10 different random orders in Hv (A) and Lv (B) environments. x-axis shows the difference between mean value of sum of slopes of alleles for different peaks, BY-RM, and y-axis refers to difference between variance of sum of slopes of alleles, BY-RM. See S3 Table for more details.