Is the mutation rate lower in genomic regions of stronger selective constraints?

Intragenomic mutational heterogeneity: structural and functional insights from gene evolution

Variation of mutation rates between species has been documented over decades, but the variation between different regions of a genome has been less often discussed. Recent studies using high-quality sequence data have revealed previously unknown levels of intragenomic heterogeneity of mutation rates and their association with other structural and functional features of DNA sequences. This article reviews accumulating evidence of this intragenomic heterogeneity and speculates its cause and influence on organismal phenotypes.

Amino Acid Properties, Substitution Rates, and the Nearly Neutral Theory

Do the properties of amino acids affect their rates of substitution? The neutral theory predicts that greater selective constraint leads to slower rates of evolution; similarly, we expect amino acids that are more different from each other to have lower rates of exchange because such changes are most likely to affect protein structure and function. Here, we test these predictions, using substitution rates estimated from empirical amino acid exchangeability matrices. To measure degree of amino acid difference, we focused on two physicochemical properties, charge and size, uncorrelated metrics that are known to have important implications for protein structure and function. We find that for both charge and size, amino acid pairs with large differences had lower rates of substitution. We also found that amino acids that differed in both properties had the lowest rates of substitution, suggesting that both physicochemical properties are under selective constraint. Mutation properties, such as the number of mutations or the number of transitions as opposed to transversions separating amino acid pairs, were also important predictors of substitution rates. The relationship between amino acid substitution rates and differences in their physiochemical properties holds across several taxonomically restricted datasets. This finding suggests that purifying selection affects amino acid substitution rates in a similar manner across taxonomic groups with different effective population sizes.

Exploring the Relationship Between Gene Expression and Low-Frequency Somatic Mutations in Arabidopsis with Duplex Sequencing

Intragenomic mutation rates can vary dramatically due to transcription-associated mutagenesis or transcription-coupled repair, which vary based on local epigenomic modifications that are nonuniformly distributed across genomes. One feature associated with decreased mutation is higher expression level, which depends on environmental cues. To understand the magnitude of expression-dependent mutation rate variation, we perturbed expression through a heat treatment in Arabidopsis thaliana. We quantified gene expression to identify differentially expressed genes, which we then targeted for mutation detection using duplex sequencing. This approach provided a highly accurate measurement of the frequency of rare somatic mutations in vegetative plant tissues, which has been a recent source of uncertainty. Somatic mutations in plants may be useful for understanding drivers of DNA damage and repair in the germline since plants experience late germline segregation and both somatic and germline cells share common repair machinery. We included mutant lines lacking mismatch repair (MMR) and base excision repair (BER) capabilities to understand how repair mechanisms may drive biased mutation accumulation. We found wild-type (WT) and BER mutant mutation frequencies to be very low (mean variant frequency 1.8 × 10-8 and 2.6 × 10-8, respectively), while MMR mutant frequencies were significantly elevated (1.13 × 10-6). Interestingly, in the MMR mutant lines, there was no difference in the somatic mutation frequencies between temperature treatments or between highly versus lowly expressed genes. The extremely low somatic variant frequencies in WT plants indicate that larger datasets will be needed to address fundamental evolutionary questions about whether environmental change leads to gene-specific changes in mutation rate.

Characterization and distribution of de novo mutations in the zebra finch

Germline de novo mutations (DNMs) provide the raw material for evolution. The DNM rate varies considerably between species, sexes and chromosomes. Here, we identify DNMs in the zebra finch (Taeniopygia guttata) across 16 parent-offspring trios using two genome assemblies of different quality. Using an independent genotyping assay, we validate 82% of the 150 candidate DNMs. DNM rates are consistent between both assemblies, with estimates of 6.14 × 10-9 and 6.36 × 10-9 per site per generation. We observe a strong paternal bias in DNM rates (male-to-female ratio ɑ ≈ 4), but this bias is in transition mutations only, leading to a transition-to-transversion ratio of 3.18 and 3.57. Finally, we find that DNMs tend to be randomly distributed across chromosomes, not associated with recombination hotspots or genic regions. However, the sex chromosome chrZ shows a roughly fourfold increased DNM rate compared to autosomes, which is more than the expected increase due to chrZ spending two-thirds of its time in males. Overall, our results further enhance our understanding of DNMs in passerine songbirds.

(Epi)mutation Rates and the Evolution of Composite Trait Architectures

AbstractMutation rates vary widely along genomes and across inheritance systems. This suggests that complex traits-resulting from the contributions of multiple determinants-might be composite in terms of the underlying mutation rates. Here we investigate through mathematical modeling whether such a heterogeneity may drive changes in a trait's architecture, especially in fluctuating environments, where phenotypic instability can be beneficial. We first identify a convexity principle related to the shape of the trait's fitness function, setting conditions under which composite architectures should be adaptive or, conversely and more commonly, should be selected against. Simulations reveal, however, that applying this principle to realistic evolving populations requires taking into account pervasive epistatic interactions that take place in the system. Indeed, the fate of a mutation affecting the architecture depends on the (epi)genetic background, which itself depends on the current architecture in the population. We tackle this problem by borrowing the adaptive dynamics framework from evolutionary ecology-where it is routinely used to deal with such resident/mutant dependencies-and find that the principle excluding composite architectures generally prevails. Yet the predicted evolutionary trajectories will typically depend on the initial architecture, possibly resulting in historical contingencies. Finally, by relaxing the large population size assumption, we unexpectedly find that not only the strength of selection on a trait's architecture but also its direction depend on population size, revealing a new occurrence of the recently identified phenomenon coined "sign inversion."

The Evolutionary Interplay of Somatic and Germline Mutation Rates

Novel sequencing technologies are making it increasingly possible to measure the mutation rates of somatic cell lineages. Accurate germline mutation rate measurement technologies have also been available for a decade, making it possible to assess how this fundamental evolutionary parameter varies across the tree of life. Here, we review some classical theories about germline and somatic mutation rate evolution that were formulated using principles of population genetics and the biology of aging and cancer. We find that somatic mutation rate measurements, while still limited in phylogenetic diversity, seem consistent with the theory that selection to preserve the soma is proportional to life span. However, germline and somatic theories make conflicting predictions regarding which species should have the most accurate DNA repair. Resolving this conflict will require carefully measuring how mutation rates scale with time and cell division and achieving a better understanding of mutation rate pleiotropy among cell types.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic, intricately governed by natural selection and historically garnering considerable attention. Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain, ushering in an unprecedented era of mutation rate research. This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates. It examines various types of mutations, explores the evolutionary dynamics and associated theories, and synthesizes both classical and contemporary hypotheses. Furthermore, this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies, mutational patterns, molecular mechanisms, and driving forces influencing variations in mutation rates across species and tissues. Finally, it proposes several potential research directions and pressing questions for future investigations.

The evolutionary consequences of interactions between the epigenome, the genome and the environment

The epigenome is the suite of interacting chemical marks and molecules that helps to shape patterns of development, phenotypic plasticity and gene regulation, in part due to its responsiveness to environmental stimuli. There is increasing interest in understanding the functional and evolutionary importance of this sensitivity under ecologically realistic conditions. Observations that epigenetic variation abounds in natural populations have prompted speculation that it may facilitate evolutionary responses to rapid environmental perturbations, such as those occurring under climate change. A frequent point of contention is whether epigenetic variants reflect genetic variation or are independent of it. The genome and epigenome often appear tightly linked and interdependent. While many epigenetic changes are genetically determined, the converse is also true, with DNA sequence changes influenced by the presence of epigenetic marks. Understanding how the epigenome, genome and environment interact with one another is therefore an essential step in explaining the broader evolutionary consequences of epigenomic variation. Drawing on results from experimental and comparative studies carried out in diverse plant and animal species, we synthesize our current understanding of how these factors interact to shape phenotypic variation in natural populations, with a focus on identifying similarities and differences between taxonomic groups. We describe the main components of the epigenome and how they vary within and between taxa. We review how variation in the epigenome interacts with genetic features and environmental determinants, with a focus on the role of transposable elements (TEs) in integrating the epigenome, genome and environment. And we look at recent studies investigating the functional and evolutionary consequences of these interactions. Although epigenetic differentiation in nature is likely often a result of drift or selection on stochastic epimutations, there is growing evidence that a significant fraction of it can be stably inherited and could therefore contribute to evolution independently of genetic change.

H3K4me1 recruits DNA repair proteins in plants

DNA repair proteins can be recruited by their histone reader domains to specific epigenomic features, with consequences on intragenomic mutation rate variation. Here, we investigated H3K4me1-associated hypomutation in plants. We first examined 2 proteins which, in plants, contain Tudor histone reader domains: PRECOCIOUS DISSOCIATION OF SISTERS 5 (PDS5C), involved in homology-directed repair, and MUTS HOMOLOG 6 (MSH6), a mismatch repair protein. The MSH6 Tudor domain of Arabidopsis (Arabidopsis thaliana) binds to H3K4me1 as previously demonstrated for PDS5C, which localizes to H3K4me1-rich gene bodies and essential genes. Mutations revealed by ultradeep sequencing of wild-type and msh6 knockout lines in Arabidopsis show that functional MSH6 is critical for the reduced rate of single-base substitution (SBS) mutations in gene bodies and H3K4me1-rich regions. We explored the breadth of these mechanisms among plants by examining a large rice (Oryza sativa) mutation data set. H3K4me1-associated hypomutation is conserved in rice as are the H3K4me1-binding residues of MSH6 and PDS5C Tudor domains. Recruitment of DNA repair proteins by H3K4me1 in plants reveals convergent, but distinct, epigenome-recruited DNA repair mechanisms from those well described in humans. The emergent model of H3K4me1-recruited repair in plants is consistent with evolutionary theory regarding mutation modifier systems and offers mechanistic insight into intragenomic mutation rate variation in plants.

Investigating low frequency somatic mutations in Arabidopsis with Duplex Sequencing

Mutations are the source of novel genetic diversity but can also lead to disease and maladaptation. The conventional view is that mutations occur randomly with respect to their environment-specific fitness consequences. However, intragenomic mutation rates can vary dramatically due to transcription coupled repair and based on local epigenomic modifications, which are non-uniformly distributed across genomes. One sequence feature associated with decreased mutation is higher expression level, which can vary depending on environmental cues. To understand whether the association between expression level and mutation rate creates a systematic relationship with environment-specific fitness effects, we perturbed expression through a heat treatment in Arabidopsis thaliana. We quantified gene expression to identify differentially expressed genes, which we then targeted for mutation detection using Duplex Sequencing. This approach provided a highly accurate measurement of the frequency of rare somatic mutations in vegetative plant tissues, which has been a recent source of uncertainty in plant mutation research. We included mutant lines lacking mismatch repair (MMR) and base excision repair (BER) capabilities to understand how repair mechanisms may drive biased mutation accumulation. We found wild type (WT) and BER mutant mutation frequencies to be very low (mean variant frequency 1.8×10-8 and 2.6×10-8, respectively), while MMR mutant frequencies were significantly elevated (1.13×10-6). These results show that somatic variant frequencies are extremely low in WT plants, indicating that larger datasets will be needed to address the fundamental evolutionary question as to whether environmental change leads to gene-specific changes in mutation rate.

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.

Mutation bias and adaptation in bacteria

Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.

The divergence of mutation rates and spectra across the Tree of Life

Owing to advances in genome sequencing, genome stability has become one of the most scrutinized cellular traits across the Tree of Life. Despite its centrality to all things biological, the mutation rate (per nucleotide site per generation) ranges over three orders of magnitude among species and several-fold within individual phylogenetic lineages. Within all major organismal groups, mutation rates scale negatively with the effective population size of a species and with the amount of functional DNA in the genome. This relationship is most parsimoniously explained by the drift-barrier hypothesis, which postulates that natural selection typically operates to reduce mutation rates until further improvement is thwarted by the power of random genetic drift. Despite this constraint, the molecular mechanisms underlying DNA replication fidelity and repair are free to wander, provided the performance of the entire system is maintained at the prevailing level. The evolutionary flexibility of the mutation rate bears on the resolution of several prior conundrums in phylogenetic and population-genetic analysis and raises challenges for future applications in these areas.

Somatic mutations inferred from RNA-seq data highlight the contribution of replication timing to mutation rate variation in a model plant

Variation in the rates and characteristics of germline and somatic mutations across the genome of an organism is informative about DNA damage and repair processes and can also shed light on aspects of organism physiology and evolution. We adapted a recently developed method for inferring somatic mutations from bulk RNA-seq data and applied it to a large collection of Arabidopsis thaliana accessions. The wide range of genomic data types available for A. thaliana enabled us to investigate the relationships of multiple genomic features with the variation in the somatic mutation rate across the genome of this model plant. We observed that late replicated regions showed evidence of an elevated rate of somatic mutation compared to genomic regions that are replicated early. We identified transcriptional strand asymmetries, consistent with the effects of transcription-coupled damage and/or repair. We also observed a negative relationship between the inferred somatic mutation count and the H3K36me3 histone mark which is well documented in the literature of human systems. In addition, we were able to support previous reports of an inverse relationship between inferred somatic mutation count and guanine-cytosine content as well as a positive relationship between inferred somatic mutation count and DNA methylation for both cytosine and noncytosine mutations.

Developmental Selection and the Perception of Mutation Bias

The notion that mutations are random relative to their fitness effects is central to the Neo-Darwinian view of evolution. However, a recent interpretation of the patterns of mutation accumulation in the genome of Arabidopsis thaliana has challenged this notion, arguing for the presence of a targeted DNA repair mechanism that causes a nonrandom association of mutation rates and fitness effects. Specifically, this mechanism was suggested to cause a reduction in the rates of mutations on essential genes, thus lowering the rates of deleterious mutations. Central to this argument were attempts to rule out selection at the population level. Here, we offer an alternative and parsimonious interpretation of the patterns of mutation accumulation previously attributed to mutation bias, showing how they can instead or additionally be caused by developmental selection, that is selection occurring at the cellular level during the development of a multicellular organism. Thus, the depletion of deleterious mutations in A. thaliana may indeed be the result of a selective process, rather than a bias in mutation. More broadly, our work highlights the importance of considering development in the interpretation of population-genetic analyses of multicellular organisms, and it emphasizes that efforts to identify mechanisms involved in mutational biases should explicitly account for developmental selection.

Population Genetic Considerations Regarding Evidence for Biased Mutation Rates in Arabidopsis thaliana

It has recently been proposed that lower mutation rates in gene bodies compared with upstream and downstream sequences in Arabidopsis thaliana are the result of an "adaptive" modification of the rate of beneficial and deleterious mutations in these functional regions. This claim was based both on analyses of mutation accumulation lines and on population genomics data. Here, we show that several questionable assumptions were used in the population genomics analyses. In particular, we demonstrate that the difference between gene bodies and less selectively constrained sequences in the magnitude of Tajima's D can in principle be explained by the presence of sites subject to purifying selection and does not require lower mutation rates in regions experiencing selective constraints.

What Has Genomics Taught An Evolutionary Biologist?

Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.