Mutation and evolution: Conceptual possibilities.

Although random mutation is central to models of evolutionary change, a lack of clarity remains regarding the conceptual possibilities for thinking about the nature and role of mutation in evolution. We distinguish several claims at the intersection of mutation, evolution, and directionality and then characterize a previously unrecognized category: complex conditioned mutation. Empirical evidence in support of this category suggests that the historically famous fluctuation test should be revisited, and new experiments should be undertaken with emerging experimental techniques to facilitate detecting mutation rates within specific loci at an ultra-high, individual base pair resolution.

De novo mutation rates at the single-mutation resolution in a human HBB gene region associated with adaptation and genetic disease.

Although it is known that the mutation rate varies across the genome, previous estimates were based on averaging across various numbers of positions. Here, we describe a method to measure the origination rates of target mutations at target base positions and apply it to a 6-bp region in the human hemoglobin subunit beta (HBB) gene and to the identical, paralogous hemoglobin subunit delta (HBD) region in sperm cells from both African and European donors. The HBB region of interest (ROI) includes the site of the hemoglobin S (HbS) mutation, which protects against malaria, is common in Africa, and has served as a classic example of adaptation by random mutation and natural selection. We found a significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than in Europeans in the HBB region studied. Finally, the rate of the 20A→T mutation, called the "HbS mutation" when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations; no instances were observed elsewhere. Further studies will be needed to examine mutation rates at the single-mutation resolution across these and other loci and organisms and to uncover the molecular mechanisms responsible.

Sex: The power of randomization.

In evolutionary biology, randomness has been perceived as a force that, in and of itself, is capable of inventing: mutation creates new genetic information at random across the genome which leads to phenotypic change, which is then subject to selection. However, in science in general and in computer science in particular, the widespread use of randomness takes a different form. Here, randomization allows for the breaking of pattern, as seen for example in its removal of biases (patterns) by random sampling or random assignment to conditions. Combined with various forms of evaluation, this breaking of pattern becomes an extraordinarily powerful tool, as also seen in many randomized algorithms in computer science. Here we show that this power of randomness is harnessed in nature by sex and recombination. In a finite population, and under the assumption of interactions between genetic variants, sex and recombination allow selection to test how well an allele will perform in a sample of combinations of interacting genetic partners drawn at random from all possible such combinations; consequently, even a small number of tests of genotypes such as takes place in a finite population favors alleles that will most likely perform well in a vast number of yet unrealized genetic combinations. This power of randomization is not manifest in asexual populations.

Algorithms, games, and evolution.

Even the most seasoned students of evolution, starting with Darwin himself, have occasionally expressed amazement that the mechanism of natural selection has produced the whole of Life as we see it around us. There is a computational way to articulate the same amazement: "What algorithm could possibly achieve all this in a mere three and a half billion years?" In this paper we propose an answer: We demonstrate that in the regime of weak selection, the standard equations of population genetics describing natural selection in the presence of sex become identical to those of a repeated game between genes played according to multiplicative weight updates (MWUA), an algorithm known in computer science to be surprisingly powerful and versatile. MWUA maximizes a tradeoff between cumulative performance and entropy, which suggests a new view on the maintenance of diversity in evolution.

Sex, mixability, and modularity.

The assumption that different genetic elements can make separate contributions to the same quantitative trait was originally made in order to reconcile biometry and Mendelism and ever since has been used in population genetics, specifically for the trait of fitness. Here we show that sex is responsible for the existence of separate genetic effects on fitness and, more generally, for the existence of a hierarchy of genetic evolutionary modules. Using the tools developed in the process, we also demonstrate that in terms of their fitness effects, separation and fusion of genes are associated with the increase and decrease of the recombination rate between them, respectively. Implications for sex and evolution theory are discussed.

Evolutionary honing in and mutational replacement: how long-term directed mutational responses to specific environmental pressures are possible.

Recent results have shown that the human malaria-resistant hemoglobin S mutation originates de novo more frequently in the gene and in the population where it is of adaptive significance, namely, in the hemoglobin subunit beta gene compared to the nonresistant but otherwise identical 20A[Formula: see text]T mutation in the hemoglobin subunit delta gene, and in sub-Saharan Africans, who have been subject to intense malarial pressure for many generations, compared to northern Europeans, who have not. This finding raises a fundamental challenge to the traditional notion of accidental mutation. Here, we address this finding with the replacement hypothesis, according to which preexisting genetic interactions can lead directly and mechanistically to mutations that simplify and replace them. Thus, an evolutionary process under selection can gradually hone in on interactions of importance for the currently evolving adaptations, from which large-effect mutations follow that are relevant to these adaptations. We exemplify this hypothesis using multiple types of mutation, including gene fusion mutations, gene duplication mutations, A[Formula: see text]G mutations in RNA-edited sites and transcription-associated mutations, and place it in the broader context of a system-level view of mutation origination called interaction-based evolution. Potential consequences include that similarity of mutation pressures may contribute to parallel evolution in genetically related species, that the evolution of genome organization may be driven by mutational mechanisms, that transposable element movements may also be explained by replacement, and that long-term directed mutational responses to specific environmental pressures are possible. Such mutational phenomena need to be further tested by future studies in natural and artificial settings.

Genes that are Used Together are More Likely to be Fused Together in Evolution by Mutational Mechanisms: A Bioinformatic Test of the Used-Fused Hypothesis.

Cases of parallel or recurrent gene fusions in evolution as well as in genetic disease and cancer are difficult to explain, because unlike point mutations, they can require the repetition of a similar configuration of multiple breakpoints rather than the repetition of a single point mutation. The used-together-fused-together hypothesis holds that genes that are used together repeatedly and persistently in a specific context are more likely to undergo fusion mutation in the course of evolution for mechanistic reasons. This hypothesis offers to explain gene fusion in both evolution and disease under one umbrella. Using bioinformatic data, we tested this hypothesis against alternatives, including that all gene pairs can fuse by random mutation, but among pairs thus fused, those that had interacted previously are more likely to be favored by selection. Results show that across multiple measures of gene interaction, human genes whose orthologs are fused in one or more species are more likely to interact with each other than random pairs of genes of the same genomic distance between pair members; that an overlap exists between genes that fused in the course of evolution in non-human species and genes that undergo fusion in human cancers; and that across six primate species studied, fusions predominate over fissions and exhibit substantial evolutionary parallelism. Together, these results support the used-together-fused-together hypothesis over its alternatives. Multiple implications are discussed, including the relevance of mutational mechanisms to the evolution of genome organization, to the distribution of fitness effects of mutation, to evolutionary parallelism and more. Supplementary Information: The online version contains supplementary material available at 10.1007/s11692-022-09579-9.

An analytical contrast between fitness maximization and selection for mixability.

It has been recently shown numerically that sex enables selection for alleles that perform well across different genetic contexts, i.e., selection for mixability. Here we capture this result analytically in a simple case. This serves a dual purpose. First, it provides a clear distinction between fitness maximization and selection for mixability. Second, it points out a limitation of the traditional analytical approach as applied to mixability.

A mixability theory for the role of sex in evolution.

The question of what role sex plays in evolution is still open despite decades of research. It has often been assumed that sex should facilitate the increase in fitness. Hence, the fact that it may break down highly favorable genetic combinations has been seen as a problem. Here, we consider an alternative approach. We define a measure that represents the ability of alleles to perform well across different combinations and, using numerical iterations within a classical population-genetic framework, show that selection in the presence of sex favors this ability in a highly robust manner. We also show that the mechanism responsible for this effect has been out of the purview of previous theory, because it operates during the evolutionary transient, and that the breaking down of favorable genetic combinations is an integral part of it. Implications of these results and more to evolutionary theory are discussed.

The power of randomization by sex in multilocus genetic evolution.

BACKGROUND: Many hypotheses have been proposed for how sexual reproduction may facilitate an increase in the population mean fitness, such as the Fisher-Muller theory, Muller's ratchet and others. According to the recently proposed mixability theory, however, sexual recombination shifts the focus of natural selection away from favoring particular genetic combinations of high fitness towards favoring alleles that perform well across different genetic combinations. Mixability theory shows that, in finite populations, because sex essentially randomizes genetic combinations, if one allele performs better than another across the existing combinations of alleles, that allele will likely also perform better overall across a vast space of untested potential genotypes. However, this superiority has been established only for a single-locus diploid model. RESULTS: We show that, in both haploids and diploids, the power of randomization by sex extends to the multilocus case, and becomes substantially stronger with increasing numbers of loci. In addition, we make an explicit comparison between the sexual and asexual cases, showing that sexual recombination is the cause of the randomization effect. CONCLUSIONS: That the randomization effect applies to the multilocus case and becomes stronger with increasing numbers of loci suggests that it holds under realistic conditions. One may expect, therefore, that in nature the ability of an allele to perform well in interaction with existing genetic combinations is indicative of how well it will perform in a far larger space of potential combinations that have not yet materialized and been tested. Randomization plays a similar role in a statistical test, where it allows one to draw an inference from the outcome of the test in a small sample about its expected outcome in a larger space of possibilities-i.e., to generalize. Our results are relevant to recent theories examining evolution as a learning process. REVIEWERS: This article was reviewed by David Ardell and Brian Golding.

Systematic mistakes are likely in bounded optimal decision-making systems.

Systematic mistakes can be distinguished from other types of mistakes in that they are repeatable and predictable within a given organism, and are not due to uncertainty or lack of information. Here we provide a mathematical definition for the concept of systematic mistakes, which captures the way this concept has been used in the behavioral sciences. We also provide an analytical model of information processing networks that are made of large numbers of components, in analogy to the brain being made of a large number of neurons. We show that, for almost all behavioral tasks, and for a wide range of limitations on the computational complexity of the decision-making network, the best possible decision-makers will make systematic mistakes. This result, together with available empirical evidence, suggests that violations of rationality in humans and animals are consistent with natural selection, as the latter operates under constraints.

Simplification, Innateness, and the Absorption of Meaning from Context: How Novelty Arises from Gradual Network Evolution.

How does new genetic information arise? Traditional thinking holds that mutation happens by accident and then spreads in the population by either natural selection or random genetic drift. There have been at least two fundamental conceptual problems with imagining an alternative. First, it seemed that the only alternative is a mutation that responds "smartly" to the immediate environment; but in complex multicellulars, it is hard to imagine how this could be implemented. Second, if there were mechanisms of mutation that "knew" what genetic changes would be favored in a given environment, this would have only begged the question of how they acquired that particular knowledge to begin with. This paper offers an alternative that avoids these problems. It holds that mutational mechanisms act on information that is in the genome, based on considerations of simplicity, parsimony, elegance, etc. (which are different than fitness considerations). This simplification process, under the performance pressure exerted by selection, not only leads to the improvement of adaptations but also creates elements that have the capacity to serve in new contexts they were not originally selected for. Novelty, then, arises at the system level from emergent interactions between such elements. Thus, mechanistically driven mutation neither requires Lamarckian transmission nor closes the door on novelty, because the changes it implements interact with one another globally in surprising and beneficial ways. Finally, I argue, for example, that genes used together are fused together; that simplification leads to complexity; and that evolution and learning are conceptually linked.

The evolution of intergenerational discounting in offspring quality.

Intergenerational effects occur when an individual's actions affect not only its own survivorship and reproduction but also those of its offspring and possibly later descendants. In the presence of intergenerational effects, short-term and long-term measures of success (such as the expected numbers of surviving offspring and of farther descendants, respectively) may be in conflict. When such conflicts occur, life-history theory normally takes long-term measures to predict the outcome of selection. This ignores the fact that, because traits change in time--through mutation, sex, and recombination--long-term relations disintegrate. We study this issue with numerical simulations and analytical models combining intergenerational effects and evolutionary change. In the models, the parental investment per offspring, as well as the total reproductive effort, stand for investments in future generations. The models show that the rate of evolutionary change determines the level of those investments. Higher rates of mutation and of sexual as opposed to parthenogenetic reproduction favor lower parental investment per offspring and lower total reproductive effort. It follows that the level of investment of ancestors in descendants responds to the genetic relatedness between the generations of the lineage, in a manner unaccounted for by preexisting theory.

Interaction-based evolution: how natural selection and nonrandom mutation work together.

BACKGROUND: The modern evolutionary synthesis leaves unresolved some of the most fundamental, long-standing questions in evolutionary biology: What is the role of sex in evolution? How does complex adaptation evolve? How can selection operate effectively on genetic interactions? More recently, the molecular biology and genomics revolutions have raised a host of critical new questions, through empirical findings that the modern synthesis fails to explain: for example, the discovery of de novo genes; the immense constructive role of transposable elements in evolution; genetic variance and biochemical activity that go far beyond what traditional natural selection can maintain; perplexing cases of molecular parallelism; and more. PRESENTATION OF THE HYPOTHESIS: Here I address these questions from a unified perspective, by means of a new mechanistic view of evolution that offers a novel connection between selection on the phenotype and genetic evolutionary change (while relying, like the traditional theory, on natural selection as the only source of feedback on the fit between an organism and its environment). I hypothesize that the mutation that is of relevance for the evolution of complex adaptation-while not Lamarckian, or "directed" to increase fitness-is not random, but is instead the outcome of a complex and continually evolving biological process that combines information from multiple loci into one. This allows selection on a fleeting combination of interacting alleles at different loci to have a hereditary effect according to the combination's fitness. TESTING AND IMPLICATIONS OF THE HYPOTHESIS: This proposed mechanism addresses the problem of how beneficial genetic interactions can evolve under selection, and also offers an intuitive explanation for the role of sex in evolution, which focuses on sex as the generator of genetic combinations. Importantly, it also implies that genetic variation that has appeared neutral through the lens of traditional theory can actually experience selection on interactions and thus has a much greater adaptive potential than previously considered. Empirical evidence for the proposed mechanism from both molecular evolution and evolution at the organismal level is discussed, and multiple predictions are offered by which it may be tested. REVIEWERS: This article was reviewed by Nigel Goldenfeld (nominated by Eugene V. Koonin), Jürgen Brosius and W. Ford Doolittle.

An optimal brain can be composed of conflicting agents.

Many behaviors have been attributed to internal conflict within the animal and human mind. However, internal conflict has not been reconciled with evolutionary principles, in that it appears maladaptive relative to a seamless decision-making process. We study this problem through a mathematical analysis of decision-making structures. We find that, under natural physiological limitations, an optimal decision-making system can involve "selfish" agents that are in conflict with one another, even though the system is designed for a single purpose. It follows that conflict can emerge within a collective even when natural selection acts on the level of the collective only.