Abstract: Mutation is the source of genetic diversity on which natural selection acts, therefore understanding the rates of mutations is crucial for understanding evolutionary trajectories. In this Opinion article, the authors discuss how emerging experimental mutation-rate data from genome-wide sequencing studies, combined with population-genetic theory, can provide unifying explanations for the diversity in mutation rates between species and across genomic locations.

Abstract: The remarkable capacity of some viruses to adapt to new hosts and environments is highly dependent on their ability to generate de novo diversity in a short period of time. Rates of spontaneous mutation vary amply among viruses. RNA viruses mutate faster than DNA viruses, single-stranded viruses mutate faster than double-strand virus, and genome size appears to correlate negatively with mutation rate. Viral mutation rates are modulated at different levels, including polymerase fidelity, sequence context, template secondary structure, cellular microenvironment, replication mechanisms, proofreading, and access to post-replicative repair. Additionally, massive numbers of mutations can be introduced by some virus-encoded diversity-generating elements, as well as by host-encoded cytidine/adenine deaminases. Our current knowledge of viral mutation rates indicates that viral genetic diversity is determined by multiple virus- and host-dependent processes, and that viral mutation rates can evolve in response to specific selective pressures.

Abstract: Cells sense their environment and adapt to it by fine-tuning their transcriptome. Wired into this network of gene expression control are mechanisms to compensate for gene dosage. The increasing use of reverse genetics in zebrafish, and other model systems, has revealed profound differences between the phenotypes caused by genetic mutations and those caused by gene knockdowns at many loci, an observation previously reported in mouse and Arabidopsis. To identify the reasons underlying the phenotypic differences between mutants and knockdowns, we generated mutations in zebrafish egfl7, an endothelial extracellular matrix gene of therapeutic interest, as well as in vegfaa. Here we show that egfl7 mutants do not show any obvious phenotypes while animals injected with egfl7 morpholino (morphants) exhibit severe vascular defects. We further observe that egfl7 mutants are less sensitive than their wild-type siblings to Egfl7 knockdown, arguing against residual protein function in the mutants or significant off-target effects of the morpholinos when used at a moderate dose. Comparing egfl7 mutant and morphant proteomes and transcriptomes, we identify a set of proteins and genes that are upregulated in mutants but not in morphants. Among them are extracellular matrix genes that can rescue egfl7 morphants, indicating that they could be compensating for the loss of Egfl7 function in the phenotypically wild-type egfl7 mutants. Moreover, egfl7 CRISPR interference, which obstructs transcript elongation and causes severe vascular defects, does not cause the upregulation of these genes. Similarly, vegfaa mutants but not morphants show an upregulation of vegfab. Taken together, these data reveal the activation of a compensatory network to buffer against deleterious mutations, which was not observed after translational or transcriptional knockdown.

Abstract: Understanding the mutational heterogeneity within tumors is a keystone for the development of efficient cancer therapies. Here, we present SCITE, a stochastic search algorithm to identify the evolutionary history of a tumor from noisy and incomplete mutation profiles of single cells. SCITE comprises a flexible Markov chain Monte Carlo sampling scheme that allows the user to compute the maximum-likelihood mutation history, to sample from the posterior probability distribution, and to estimate the error rates of the underlying sequencing experiments. Evaluation on real cancer data and on simulation studies shows the scalability of SCITE to present-day single-cell sequencing data and improved reconstruction accuracy compared to existing approaches.

Abstract: Huazhong University of Science and Technology, Wuhan, China. 2Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, China. 3Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, China. 4School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China. 5Department of Computer Science, City University of Hong Kong, Hong Kong, China. e-mail: dingma424@yahoo.com, huit71@sohu. com or xuxun@genomics.cn

Abstract: To what extent is the convergent evolution of protein function attributable to convergent or parallel changes at the amino acid level? The mutations that contribute to adaptive protein evolution may represent a biased subset of all possible beneficial mutations owing to mutation bias and/or variation in the magnitude of deleterious pleiotropy. A key finding is that the fitness effects of amino acid mutations are often conditional on genetic background. This context dependence (epistasis) can reduce the probability of convergence and parallelism because it reduces the number of possible mutations that are unconditionally acceptable in divergent genetic backgrounds. Here, I review factors that influence the probability of replicated evolution at the molecular level.

Abstract: The fidelity of DNA replication together with repair mechanisms ensure that the genetic material is properly copied from one generation to another. However, on extremely rare occasions when damages to DNA or replication errors are not repaired, germline mutations can be transmitted to the next generation. Because of the rarity of these events, studying the rate at which new mutations arise across organisms has been a great challenge, especially in multicellular nonmodel organisms with large genomes. We sequenced the genomes of 11 birds from a three-generation pedigree of the collared flycatcher (Ficedula albicollis) and used highly stringent bioinformatic criteria for mutation detection and used several procedures to validate mutations, including following the stable inheritance of new mutations to subsequent generations. We identified 55 de novo mutations with a 10-fold enrichment of mutations at CpG sites and with only a modest male mutation bias. The estimated rate of mutation per site per generation was 4.6 × 10(-9), which corresponds to 2.3 × 10(-9) mutations per site per year. Compared to mammals, this is similar to mouse but about half of that reported for humans, which may be due to the higher frequency of male mutations in humans. We confirm that mutation rate scales positively with genome size and that there is a strong negative relationship between mutation rate and effective population size, in line with the drift-barrier hypothesis. Our study illustrates that it should be feasible to obtain direct estimates of the rate of mutation in essentially any organism from which family material can be obtained.

Abstract: Although it is well known that microbial populations can respond adaptively to challenges from antibiotics, empirical difficulties in distinguishing the roles of de novo mutation and natural selection have left several issues unresolved. Here, we explore the mutational properties of Escherichia coli exposed to long-term sublethal levels of the antibiotic norfloxacin, using a mutation accumulation design combined with whole-genome sequencing of replicate lines. The genome-wide mutation rate significantly increases with norfloxacin concentration. This response is associated with enhanced expression of error-prone DNA polymerases and may also involve indirect effects of norfloxacin on DNA mismatch and oxidative-damage repair. Moreover, we find that acquisition of antibiotic resistance can be enhanced solely by accelerated mutagenesis, i.e., without direct involvement of selection. Our results suggest that antibiotics may generally enhance the mutation rates of target cells, thereby accelerating the rate of adaptation not only to the antibiotic itself but to additional challenges faced by invasive pathogens.

Abstract: The performance of the differential evolution (DE) algorithm is significantly affected by the choice of mutation strategies and control parameters. Maintaining the search capability of various control parameter combinations throughout the entire evolution process is also a key issue. A self-adaptive DE algorithm with zoning evolution of control parameters and adaptive mutation strategies is proposed in this paper. In the proposed algorithm, the mutation strategies are automatically adjusted with population evolution, and the control parameters evolve in their own zoning to self-adapt and discover near optimal values autonomously. The proposed algorithm is compared with five state-of-the-art DE algorithm variants according to a set of benchmark test functions. Furthermore, seven nonparametric statistical tests are implemented to analyze the experimental results. The results indicate that the overall performance of the proposed algorithm is better than those of the five existing improved algorithms.

Abstract: Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.

Abstract: Mutation of the DNA molecule is one of the most fundamental processes in biology. In this study, we use 283 parent-offspring trios to estimate the rate of mutation for both single nucleotide variants (SNVs) and short length variants (indels) in humans and examine the mutation process. We found 17812 SNVs, corresponding to a mutation rate of 1.29 × 10-8 per position per generation (PPPG) and 1282 indels corresponding to a rate of 9.29 × 10-10 PPPG. We estimate that around 3% of human de novo SNVs are part of a multi-nucleotide mutation (MNM), with 558 (3.1%) of mutations positioned less than 20kb from another mutation in the same individual (median distance of 525bp). The rate of de novo mutations is greater in late replicating regions (p = 8.29 × 10-19) and nearer recombination events (p = 0.0038) than elsewhere in the genome.

Abstract: The distribution of effect sizes of adaptive substitutions has been central to evolutionary biology since the modern synthesis. Early theory proposed that because large-effect mutations have negative pleiotropic consequences, only small-effect mutations contribute to adaptation. More recent theory suggested instead that large-effect mutations could be favoured when populations are far from their adaptive peak. Here we suggest that the distributions of effect sizes are expected to differ among study systems, reflecting the wide variation in evolutionary forces and ecological conditions experienced in nature. These include selection, mutation, genetic drift, gene flow, and other factors such as the degree of pleiotropy, the distance to the phenotypic optimum, whether the optimum is stable or moving, and whether new mutation or standing genetic variation provides the source of adaptive alleles. Our goal is to review how these factors might affect the distribution of effect sizes and to identify new research directions. Until more theory and empirical work is available, we feel that it is premature to make broad generalizations about the effect size distribution of adaptive substitutions important in nature.

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Abstract: In the basic fitness landscape metaphor for molecular evolution, evolutionary pathways are presumed to follow uphill steps of increasing fitness. How evolution can cross fitness valleys is an open question. One possibility is that environmental changes alter the fitness landscape such that low-fitness sequences reside on a hill in alternate environments. We experimentally test this hypothesis on the antibiotic resistance gene TEM-15 β-lactamase by comparing four evolutionary strategies shaped by environmental changes. The strategy that included initial steps of selecting for low antibiotic resistance (negative selection) produced superior alleles compared with the other three strategies. We comprehensively examined possible evolutionary pathways leading to one such high-fitness allele and found that an initially deleterious mutation is key to the allele’s evolutionary history. This mutation is an initial gateway to an otherwise relatively inaccessible area of sequence space and participates in higher-order, positive epistasis with a number of neutral to slightly beneficial mutations. The ability of negative selection and environmental changes to provide access to novel fitness peaks has important implications for natural evolutionary mechanisms and applied directed evolution.

Abstract: Although the human germline mutation rate is higher than that in any other well-studied species, the rate is not exceptional once the effective genome size and effective population size are taken into consideration. Human somatic mutation rates are substantially elevated above those in the germline, but this is also seen in other species. What is exceptional about humans is the recent detachment from the challenges of the natural environment and the ability to modify phenotypic traits in ways that mitigate the fitness effects of mutations, e.g., precision and personalized medicine. This results in a relaxation of selection against mildly deleterious mutations, including those magnifying the mutation rate itself. The long-term consequence of such effects is an expected genetic deterioration in the baseline human condition, potentially measurable on the timescale of a few generations in westernized societies, and because the brain is a particularly large mutational target, this is of particular concern. Ultimately, the price will have to be covered by further investment in various forms of medical intervention. Resolving the uncertainties of the magnitude and timescale of these effects will require the establishment of stable, standardized, multigenerational measurement procedures for various human traits.

Abstract: The current standard model for identifying carriers of high-risk mutations in cancer-susceptibility genes (CSGs) generally involves a process that is not amenable to population-based testing: access to genetic tests is typically regulated by health-care providers on the basis of a labour-intensive assessment of an individual's personal and family history of cancer, with face-to-face genetic counselling performed before mutation testing. Several studies have shown that application of these selection criteria results in a substantial proportion of mutation carriers being missed. Population-based genetic testing has been proposed as an alternative approach to determining cancer susceptibility, and aims for a more-comprehensive detection of mutation carriers. Herein, we review the existing data on population-based genetic testing, and consider some of the barriers, pitfalls, and challenges related to the possible expansion of this approach. We consider mechanisms by which population-based genetic testing for cancer susceptibility could be delivered, and suggest how such genetic testing might be integrated into existing and emerging health-care structures. The existing models of genetic testing (including issues relating to informed consent) will very likely require considerable alteration if the potential benefits of population-based genetic testing are to be fully realized.

Abstract: Various forms of selective mutation testing have long been accepted as valid approximations to full mutation testing. This paper presents counterevidence to traditional selective mutation. The recent development of dominator mutants and minimal mutation analysis lets us analyze selective mutation without the noise introduced by the redundancy inherent in traditional mutation. We then exhaustively evaluate all small sets of mutation operators for the Proteum mutation system and determine dominator mutation scores and required work for each of these sets on an empirical test bed. The results show that all possible selective mutation approaches have poor dominator mutation scores on at least some of these programs. This suggests that to achieve high performance with respect to full mutation analysis, selective approaches will have to become more sophisticated, possibly by choosing mutants based on the specifics of the artifact under test, that is, specialized selective mutation.

Abstract: High-throughput sequencing has enabled genetic screens that can rapidly identify mutations that occur during experimental evolution. The presence of a mutation in an evolved lineage does not, however, constitute proof that the mutation is adaptive, given the well-known and widespread phenomenon of genetic hitchhiking, in which a non-adaptive or even detrimental mutation can co-occur in a genome with a beneficial mutation and the combined genotype is carried to high frequency by selection. We approximated the spectrum of possible beneficial mutations in Saccharomyces cerevisiae using sets of single-gene deletions and amplifications of almost all the genes in the S. cerevisiae genome. We determined the fitness effects of each mutation in three different nutrient-limited conditions using pooled competitions followed by barcode sequencing. Although most of the mutations were neutral or deleterious, ~500 of them increased fitness. We then compared those results to the mutations that actually occurred during experimental evolution in the same three nutrient-limited conditions. On average, ~35% of the mutations that occurred during experimental evolution were predicted by the systematic screen to be beneficial. We found that the distribution of fitness effects depended on the selective conditions. In the phosphate-limited and glucose-limited conditions, a large number of beneficial mutations of nearly equivalent, small effects drove the fitness increases. In the sulfate-limited condition, one type of mutation, the amplification of the high-affinity sulfate transporter, dominated. In the absence of that mutation, evolution in the sulfate-limited condition involved mutations in other genes that were not observed previously-but were predicted by the systematic screen. Thus, gross functional screens have the potential to predict and identify adaptive mutations that occur during experimental evolution.

Abstract: The site frequency spectrum (SFS) has long been used to study demographic history and natural selection. Here, we extend this summary by examining the SFS conditional on the alleles found at the same site in other species. We refer to this extension as the "phylogenetically-conditioned SFS" or cSFS. Using recent large-sample data from the Exome Aggregation Consortium (ExAC), combined with primate genome sequences, we find that human variants that occurred independently in closely related primate lineages are at higher frequencies in humans than variants with parallel substitutions in more distant primates. We show that this effect is largely due to sites with elevated mutation rates causing significant departures from the widely-used infinite sites mutation model. Our analysis also suggests substantial variation in mutation rates even among mutations involving the same nucleotide changes. In summary, we show that variable mutation rates are key determinants of the SFS in humans.

Abstract: Objective: To identify the genetic basis of a family segregating episodic ataxia, infantile seizures, and heterogeneous epilepsies and to study the phenotypic spectrum of KCNA2 mutations. Methods: A family with 7 affected individuals over 3 generations underwent detailed phenotyping. Whole genome sequencing was performed on a mildly affected grandmother and her grandson with epileptic encephalopathy (EE). Segregating variants were filtered and prioritized based on functional annotations. The effects of the mutation on channel function were analyzed in vitro by voltage clamp assay and in silico by molecular modeling. KCNA2 was sequenced in 35 probands with heterogeneous phenotypes. Results: The 7 family members had episodic ataxia (5), self-limited infantile seizures (5), evolving to genetic generalized epilepsy (4), focal seizures (2), and EE (1). They had a segregating novel mutation in the shaker type voltage-gated potassium channel KCNA2 (CCDS_827.1: c.765_773del; p.255_257del). A rare missense SCN2A (rs200884216) variant was also found in 2 affected siblings and their unaffected mother. The p.255_257del mutation caused dominant negative loss of channel function. Molecular modeling predicted repositioning of critical arginine residues in the voltage-sensing domain. KCNA2 sequencing revealed 1 de novo mutation (CCDS_827.1: c.890G>A; p.Arg297Gln) in a girl with EE, ataxia, and tremor. Conclusions: A KCNA2 mutation caused dominantly inherited episodic ataxia, mild infantile-onset seizures, and later generalized and focal epilepsies in the setting of normal intellect. This observation expands the KCNA2 phenotypic spectrum from EE often associated with chronic ataxia, reflecting the marked variation in severity observed in many ion channel disorders.