Decanalizing thinking on genetic canalization

Abstract

The concept of genetic canalization has had an abiding influence on views of complex-trait evolution. A genetically canalized system has evolved to become less sensitive to the effects of mutation. When a gene product that supports canalization is compromised, the phenotypic impacts of a mutation should be more pronounced. This expected increase in mutational effects not only has important consequences for evolution, but has also motivated strategies to treat disease. However, recent studies demonstrate that, when putative agents of genetic canalization are impaired, systems do not behave as expected. Here, we review the evidence that is used to infer whether particular gene products are agents of genetic canalization. Then we explain how such inferences often succumb to a converse error. We go on to show that several candidate agents of genetic canalization increase the phenotypic impacts of some mutations while decreasing the phenotypic impacts of others. These observations suggest that whether a gene product acts as a 'buffer' (lessening mutational effects) or a 'potentiator' (increasing mutational effects) is not a fixed property of the gene product but instead differs for the different mutations with which it interacts. To investigate features of genetic interactions that might predispose them toward buffering versus potentiation, we explore simulated gene-regulatory networks. Similarly to putative agents of genetic canalization, the gene products in simulated networks also modify the phenotypic effects of mutations in other genes without a strong overall tendency towards lessening or increasing these effects. In sum, these observations call into question whether complex traits have evolved to become less sensitive (i.e., are canalized) to genetic change, and the degree to which trends exist that predict how one genetic change might alter another's impact. We conclude by discussing approaches to address these and other open questions that are brought into focus by re-thinking genetic canalization.

DnaJ chaperones contribute to canalization

“…This result agreed with previous studies in Drosophila that failed to detect phenotypes buffered by Hsp90 (reviewed by Takahashi, ). Such studies led to another hypothesis; that Hsp90 might not be a capacitor but a “genetic modifier” that has many interacting clients and can modify the genetic interaction network when the function is impaired (Geiler‐Samerotte, Sartori, & Siegal, ). A recent study comparing effects of different genetic backgrounds has revealed that there are potentially numerous “genetic modifiers” in a genome (Paaby et al, ; Schell, Mullis, & Ehrenreich, ).…”

Embryonic canalization and its limits—A view from temperature

“…While this study did not test environmental variation, the authors argue that Hsp90 is not a canalization gene. Rather, natural selection preferentially allows cryptic genetic variation to accumulate, which is revealed in the absence of Hsp90 (Geiler‐Samerotte, Sartori, & Siegal, 2019).…”

Genetic buffering and potentiation in metabolism

“…The difference in phenotypic (growth-rate) variation in the presence or absence of an enzyme reveals how it modifies the consequences of flux mutations on fitness. We quantified this difference with a score defined by the change between standard deviations θ = (stdmutant -stdwild-type)/stdwild-type, with θ < 0 indicating that the enzyme works as a potentiator (presence of the enzyme increases variability) and θ > 0 indicating that it acts as a buffer [presence of the enzyme decreases variability, Methods (Geiler-Samerotte et al, 2018;Hermisson and Wagner, 2004)].…”

“…If the variability observed in a specific mutant is bigger than that observed in the wild-type, we say that the corresponding enzyme is a buffer; if smaller, we say that it is a potentiator. We use the relative difference with respect to the wild-type value θ = (STD fit_mutant -STD fit_wild-type)/STD fit_wild-type (Geiler-Samerotte et al, 2018;Hermisson and Wagner, 2004) as score. Different measures that we tested led to comparable results, like the genotype-by-line interaction variance (Richardson et al, 2013) (Table S1).…”

“…Mutation accumulation experiments (Halligan and Keightley, 2009) reduce the strength of selection and thus provide a more accurate sample instead (Geiler-Samerotte et al, 2018).…”