Biological systems are remarkably evolvable. There are three main explanations for this fact: sex/recombination, modularity, and robustness. In our group, we primarily study robustness.
Robustness promotes evolvability in both sexual and asexual populations, albeit by different mechanisms (Masel & Trotter 2010). In asexual populations, we can picture a population in a space where each genotype is a point, and mutations connect them together. Evolvability is the ability to find genotypes with improved phenotypes. For traits affected by multiple genes, evolvability is driven by the “quality” of the genotypes sampled by mutation, rather than by greater quantity or spread across the genotype space (Rajon & Masel 2013).
With recombination, there are more complex ways than mutation to get from one genotype to another. Alleles that achieve little on their own may become important when recombined with other alleles. These cryptic genetic variants were first studied by Conrad Waddington in his seminal genetic assimilation experiments. When biological systems are robust to the effects of genetic variants, they accumulate through neutral evolutionary processes, and provide a cryptic source for future adaptation.
Preadaptation and pre-adapting selection
Preadaptation means that if you look at adapations with 20/20 hindsight, you can see aspects of the ancestral form that made the adaptation more accessible. This is a natural consequence of the way conditional probability works, in this case the probability conditional on the fact that you are looking at a major adaptation. No foresight is involved.
But while evolution has no foresight as to what will be adaptive, it sometimes does have foresight about what will not be adaptive. For example, lethality is never adaptive. Populations are only partially robust to many perturbations that at higher exposures might be lethal. Low residual levels of selection may act as a form of pre-screening. This removes the most deleterious alleles and leaves the remaining variation pre-enriched for potential adaptations (Masel 2006; Rajon & Masel 2011). This enrichment makes cryptic variants a likely source of future adaptations. We have found evidence that this occurs for stop codon readthrough errors in Saccharomyces cerevisiae (Kosinski & Masel 2020).
More generally, all kinds of errors in gene expression (transcription, translation and folding) in the present provide a preview of mutations in the future. Some gene expression errors lead to catastrophically misfolded proteins, while others are relatively benign. The effects of catastrophic misfolding can be avoided either by evolving global proofreading machinery, or by evolving benign cryptic sequences locally at each of the error-dependent sites (Rajon & Masel 2011). Populations that have evolved the local solution are dramatically more evolvable (Rajon & Masel 2011).
Evolutionary capacitors provide a window into cryptic variants, facilitating their study. Evolutionary capacitors are molecular mechanisms that are able to tap into stocks of cryptic genetic variation. Just as an electronic capacitor stores and releases charge, an evolutionary capacitor stores and releases genetic variation. Examples include the yeast prion [PSI+], regulators of alternative splicing, phase variation and gene conversion. In fact, any complex network can have evolutionary capacitance properties, so capacitance is likely to be widespread.
The main example we study as a model system for evolutionary capacitance is the yeast prion [PSI+]. [PSI+] taps into cryptic stocks of variation beyond stop codons by causing elevated rates of readthrough translation. This can lead to faster adaptation: [PSI+] can lead to faster growth rates in stressful environments (True & Lindquist 2000). Evolutionary capacitors may therefore promote evolvability.
When variation is revealed all at once, most of it is likely to be deleterious, while only a small subset is likely to be adaptive. Selection will act to genetically assimilate this subset. For example, [PSI+] may act as a stopgap mechanism, buying yeast time to find the appropriate stop codon mutation (Giacomelli et al. 2007). Once this has occurred, capacitors such as [PSI+] are reversible, and simply disappear. This leaves the organism with a brand new adaptation but no load of other, deleterious mutations, since these disappear with [PSI+]. This reversibility is one of the factors that make evolutionary capacitance a much more potent promoter of evolvability than elevated mutation rates.
It is one thing for capacitors to promote evolvability, but another for this increased evolvability to itself be the product of natural selection. The evolution of evolvability is difficult, because natural selection acts on present costs, not future benefits. We have constructed stochastic mathematical models that balance the weak constant deleterious effects of capacitance through revealing variation at inappropriate times, the rare strongly advantageous effects of capacitance at times of environmental change, and genetic drift. We found both that evolutionary capacitance is favored by natural selection (Masel 2005; King & Masel 2007; Masel & Griswold 2009; Griswold & Masel 2009; Lancaster et al. 2010) and that this is by far the most likely explanation for how the ability to form [PSI+] evolved in the first place (Masel & Bergman 2003).
Our goal in this work is to understand evolutionary capacitance, and the biology of the [PSI+] prion is our guide, but along the way our theoretical models have had broader application to other related areas of evolutionary theory. These have included phenotypic plasticity, epigenetic inheritance systems, bet-hedging, and the mutational degradation of complex traits.
Facultative sex as an evolutionary capacitor
Saccharomyces mostly reproduce asexually by mitosis. When they occasionally undergo meiosis, it is normally followed by selfing. This converts many heterozygotes into homozygotes, increasing genetic variation that can be selected by subsequent clonal expansion. While this can cause inbreeding depression through recessive deleterious mutations becoming homozygotes, it can also increase the evolvability of that fraction of the population that lacks such mutations (Masel & Lyttle 2011).
Kosinski L. J., Masel J. (2020). Readthrough errors purge deleterious cryptic sequences, facilitating the birth of coding sequences. Molecular Biology and Evolution, 37(6), 1761-1774.
Nelson P., & Masel J. (2018) Evolutionary capacitance emerges spontaneously during adaptation to environmental changes. Cell Reports, 25(1): 249-258.
Xiong K., McEntee J., Porfirio D., Masel J. (2017) Drift barriers to quality control when genes are expressed at different levels. Genetics 205: 397-407.
Trotter, M. V.,Weissman, D. B., Peterson, G., Peck, K., & Masel, J. (2014) Cryptic genetic variation can make "irreducible complexity" a common mode of adaptation. Evolution, 68:3357–3367.
Masel J. (2013) Q&A: Evolutionary capacitance. BMC Biology, 11:103.
Rajon, E., & Masel, J. (2013) Compensatory evolution and the origins of innovations. Genetics, 193(4):1209-20.
Siegal M. L., & Masel J. (2012) Hsp90 depletion goes wild. BMC Biology 10:14 .
Wilson, B. A., & Masel, J. (2011). Putatively noncoding transcripts show extensive association with ribosomes. Genome Biology & Evolution, 3, 1245-1252
Masel, J. & Lyttle, D. N. (2011). The consequences of rare sexual reproduction by means of selfing in an otherwise clonally reproducing species. Theoretical Population Biology, 80(4), 317-322 .
Rajon, E., & Masel, J. (2011). Evolution of molecular error rates and the consequences for evolvability. Proc. Natl. Acad. Sci. USA, 108(3), 1082-7.
Masel, J., & Trotter, M. V. (2010). Robustness and Evolvability. Trends in Genetics, 26(9), 406-414.
Lancaster, A. K., Bardill, J. P., True, H. L., & Masel, J. (2010). The Spontaneous Appearance Rate of the Yeast Prion [PSI+] and Its Implications For the Evolution of the Evolvability Properties of the [PSI+] System. Genetics, 184(2), 393-400.
Masel, J., & Griswold, C. K. (2009). The strength of selection against the yeast prion [PSI+]. Genetics, 181(3), 1057-63.
Masel, J., & Siegal, M. L. (2009). Robustness: mechanisms and consequences. Trends in Genetics.
Griswold, C. K., & Masel, J. (2009). Complex adaptations can drive the evolution of the capacitor [PSI], even with realistic rates of yeast sex. PLoS Genet, 5(6), 1000517.
Giacomelli, M. G., Hancock, A. S., & Masel, J. (2007). The conversion of 3′ UTRs into coding regions. Molecular Biology & Evolution, 24(2), 457-64.
King OD, Masel J. (2007). The evolution of bet-hedging adaptations to rare scenarios. Theoretical Population Biology 72: 560-575.
Masel, J., & Maughan, H. (2007). Mutations leading to loss of sporulation ability in Bacillus subtilis are sufficiently frequent to favor genetic canalization. Genetics, 175(1), 453-7.
Masel, J. (2006). Cryptic genetic variation is enriched for potential adaptations. Genetics, 172(3), 1985-91.
Masel, J. (2005). Evolutionary capacitance may be favored by natural selection. Genetics, 170(3), 1359-71.
Masel, J. (2004). Genetic assimilation can occur in the absence of selection for the assimilating phenotype, suggesting a role for the canalization heuristic. Journal of Evolutionary Biology, 17(5), 1106-10.
Masel, J., & Bergman, A. (2003). The evolution of the evolvability properties of the yeast prion [PSI+]. Evolution, 57(7), 1498-512.