Analysis and implications of mutational variation

An additional proofreader contributes to DNA replication fidelity in mycobacteria

The removal of mis-incorporated nucleotides by proofreading activity ensures DNA replication fidelity. Whereas the ε-exonuclease DnaQ is a well-established proofreader in the model organism Escherichia coli, it has been shown that proofreading in a majority of bacteria relies on the polymerase and histidinol phosphatase (PHP) domain of replicative polymerase, despite the presence of a DnaQ homolog that is structurally and functionally distinct from E. coli DnaQ. However, the biological functions of this type of noncanonical DnaQ remain unclear. Here, we provide independent evidence that noncanonical DnaQ functions as an additional proofreader for mycobacteria. Using the mutation accumulation assay in combination with whole-genome sequencing, we showed that depletion of DnaQ in Mycolicibacterium smegmatis leads to an increased mutation rate, resulting in AT-biased mutagenesis and increased insertions/deletions in the homopolymer tract. Our results showed that mycobacterial DnaQ binds to the β clamp and functions synergistically with the PHP domain proofreader to correct replication errors. Furthermore, the loss of dnaQ results in replication fork dysfunction, leading to attenuated growth and increased mutagenesis on subinhibitory fluoroquinolones potentially due to increased vulnerability to fork collapse. By analyzing the sequence polymorphism of dnaQ in clinical isolates of Mycobacterium tuberculosis (Mtb), we demonstrated that a naturally evolved DnaQ variant prevalent in Mtb lineage 4.3 may enable hypermutability and is associated with drug resistance. These results establish a coproofreading model and suggest a division of labor between DnaQ and PHP domain proofreader. This study also provides real-world evidence that a mutator-driven evolutionary pathway may exist during the adaptation of Mtb.

Spontaneous mutations and mutational responses to penicillin treatment in the bacterial pathogen Streptococcus pneumoniae D39

Bacteria with functional DNA repair systems are expected to have low mutation rates due to strong natural selection for genomic stability. However, our study of the wild-type Streptococcus pneumoniae D39, a pathogen responsible for many common diseases, revealed a high spontaneous mutation rate of 0.02 per genome per cell division in mutation-accumulation (MA) lines. This rate is orders of magnitude higher than that of other non-mutator bacteria and is characterized by a high mutation bias in the A/T direction. The high mutation rate may have resulted from a reduction in the overall efficiency of selection, conferred by the tiny effective population size in nature. In line with this, S. pneumoniae D39 also exhibited the lowest DNA mismatch-repair (MMR) efficiency among bacteria. Treatment with the antibiotic penicillin did not elevate the mutation rate, as penicillin did not induce DNA damage and S. pneumoniae lacks a stress response pathway. Our findings suggested that the MA results are applicable to within-host scenarios and provide insights into pathogen evolution.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-024-00220-6.

Modelling genetic stability in engineered cell populations

Predicting the evolution of engineered cell populations is a highly sought-after goal in biotechnology. While models of evolutionary dynamics are far from new, their application to synthetic systems is scarce where the vast combination of genetic parts and regulatory elements creates a unique challenge. To address this gap, we here-in present a framework that allows one to connect the DNA design of varied genetic devices with mutation spread in a growing cell population. Users can specify the functional parts of their system and the degree of mutation heterogeneity to explore, after which our model generates host-aware transition dynamics between different mutation phenotypes over time. We show how our framework can be used to generate insightful hypotheses across broad applications, from how a device's components can be tweaked to optimise long-term protein yield and genetic shelf life, to generating new design paradigms for gene regulatory networks that improve their functionality.

Similar mutation rates but different mutation spectra in moderate and extremely halophilic archaea

Archaea are a major part of Earth's microbiota and extremely diverse. Yet, we know very little about the process of mutation that drives such diversification. To expand beyond previous work with the moderate halophilic archaeal species Haloferax volcanii, we performed a mutation-accumulation experiment followed by whole-genome sequencing in the extremely halophilic archaeon Halobacterium salinarum. Although Hfx. volcanii and Hbt. salinarum have different salt requirements, both species have highly polyploid genomes and similar GC content. We accumulated mutations for an average of 1250 generations in 67 mutation accumulation lines of Hbt. salinarum, and revealed 84 single-base substitutions and 10 insertion-deletion mutations. The estimated base-substitution mutation rate of 3.99 × 10-10 per site per generation or 1.0 × 10-3 per genome per generation in Hbt. salinarum is similar to that reported for Hfx. volcanii (1.2 × 10-3 per genome per generation), but the genome-wide insertion-deletion rate and spectrum of mutations are somewhat dissimilar in these archaeal species. The spectra of spontaneous mutations were AT biased in both archaea, but they differed in significant ways that may be related to differences in the fidelity of DNA replication/repair mechanisms or a simple result of the different salt concentrations.

Recommendations for improving statistical inference in population genomics

The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population genetic insights outpaced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous nonadaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.

Loss of Heterozygosity and Base Mutation Rates Vary Among Saccharomyces cerevisiae Hybrid Strains

A growing body of evidence suggests that mutation rates exhibit intra-species specific variation. We estimated genome-wide loss of heterozygosity (LOH), gross chromosomal changes, and single nucleotide mutation rates to determine intra-species specific differences in hybrid and homozygous strains of Saccharomyces cerevisiae. The mutation accumulation lines of the S. cerevisiae hybrid backgrounds - S288c/YJM789 (S/Y) and S288c/RM11-1a (S/R) were analyzed along with the homozygous diploids RM11, S288c, and YJM145. LOH was extensive in both S/Y and S/R hybrid backgrounds. The S/Y background also showed longer LOH tracts, gross chromosomal changes, and aneuploidy. Short copy number aberrations were observed in the S/R background. LOH data from the S/Y and S/R hybrids were used to construct a LOH map for S288c to identify hotspots. Further, we observe up to a sixfold difference in single nucleotide mutation rates among the S. cerevisiae S/Y and S/R genetic backgrounds. Our results demonstrate LOH is common during mitotic divisions in S. cerevisiae hybrids and also highlight genome-wide differences in LOH patterns and rates of single nucleotide mutations between commonly used S. cerevisiae hybrid genetic backgrounds.

Estimation of the Genome-Wide Mutation Rate and Spectrum in the Archaeal Species Haloferax volcanii

Organisms adapted to life in extreme habitats (extremophiles) can further our understanding of the mechanisms of genetic stability, particularly replication and repair. Despite the harsh environmental conditions they endure, these extremophiles represent a great deal of the Earth's biodiversity. Here, for the first time in a member of the archaeal domain, we report a genome-wide assay of spontaneous mutations in the halophilic species Haloferax volcanii using a direct and unbiased method: mutation accumulation experiments combined with deep whole-genome sequencing. H. volcanii is a key model organism not only for the study of halophilicity, but also for archaeal biology in general. Our methods measure the genome-wide rate, spectrum, and spatial distribution of spontaneous mutations. The estimated base substitution rate of 3.15 × 10^-10 per site per generation, or 0.0012 per genome per generation, is similar to the value found in mesophilic prokaryotes (optimal growth at ∼20-45°). This study contributes to a comprehensive phylogenetic view of how evolutionary forces and molecular mechanisms shape the rate and molecular spectrum of mutations across the tree of life.

Partial protection from cyclical selection generates a high level of polymorphism at multiple non-neutral sites

Temporally varying selection is known to maintain genetic polymorphism under certain restricted conditions. However, if part of a population can escape from selective pressure, a condition called the "storage effect" is produced, which greatly promotes balanced polymorphism. We investigate whether seasonally fluctuating selection can maintain polymorphism at multiple loci, if cyclically fluctuating selection is not acting on a subpopulation called a "refuge." A phenotype with a seasonally oscillating optimum is determined by alleles at multiple sites, across which the effects of mutations on phenotype are distributed randomly. This model resulted in long-term polymorphism at multiple sites, during which allele frequencies oscillate heavily, greatly increasing the level of nonneutral polymorphism. The level of polymorphism at linked neutral sites was either higher or lower than expected for unlinked neutral loci. Overall, these results suggest that for a protein-coding sequence, the nonsynonymous-to-synonymous ratio of polymorphism may exceed one. In addition, under randomly perturbed environmental oscillation, different sets of sites may take turns harboring long-term polymorphism, thus making trans-species polymorphism (which has been predicted as a classical signature of balancing selection) less likely.

Spatial Vulnerabilities of the Escherichia coli Genome to Spontaneous Mutations Revealed with Improved Duplex Sequencing

Investigation of spontaneous mutations by next-generation sequencing technology has attracted extensive attention lately due to the fundamental roles of spontaneous mutations in evolution and pathological processes. However, these studies only focused on the mutations accumulated through many generations during long-term (possibly be years of) culturing, but not the freshly generated mutations that occur at very low frequencies. In this study, we established a molecularly barcoded deep sequencing strategy to detect low abundant spontaneous mutations in genomes of bacteria cell cultures. Genome-wide spontaneous mutations in 15 Escherichia coli cell culture samples were defined with a high confidence (P < 0.01). We also developed a hotspot-calling approach based on the run-length encoding algorithm to find the genomic regions that are vulnerable to the spontaneous mutations. The hotspots for the mutations appeared to be highly conserved across the bacteria samples. Further biological annotation of these regions indicated that most of the spontaneous mutations were located at the repeat domains or nonfunctional domains of the genomes, suggesting the existence of mechanisms that could somehow prevent the occurrence of mutations in crucial genic areas. This study provides a more faithful picture of mutation occurrence and spectra in a single expansion process without long-term culturing.

The evolutionary trade-off between stem cell niche size, aging, and tumorigenesis

Many epithelial tissues within multicellular organisms are continually replenished by small independent populations of stem cells largely responsible for maintaining tissue homeostasis. These continually dividing populations are subject to mutations that can lead to tumorigenesis but also contribute to aging. Mutations accumulate in stem cell niches and change the rate of cell division and differentiation; the pace of this process and the fate of specific mutations depend strongly on niche population size. Here, we create a mathematical model of the intestinal stem cell niche, crypt system, and epithelium. We calculate the expected effect of fixed mutations in stem cell niches and their effect on tissue homeostasis throughout the intestinal epithelium over organismal lifetime. We find that, due to the small population size of stem cell niches, mutations predominantly fix via genetic drift and decrease stem cell fitness, leading to niche and tissue attrition, and contributing to organismal aging. We also explore mutation accumulation at various stem cell niche sizes and demonstrate that an evolutionary trade-off exists between niche size, tissue aging, and the risk of tumorigenesis. Further, mouse and human niches exist at a size that minimizes the probability of tumorigenesis, at the expense of accumulating deleterious mutations due to genetic drift. Finally, we show that the trade-off between the probability of tumorigenesis and the extent of aging depends on whether or not mutational effects confer a selective advantage in the stem cell niche.

Insertion sequence-caused large-scale rearrangements in the genome of Escherichia coli

A majority of large-scale bacterial genome rearrangements involve mobile genetic elements such as insertion sequence (IS) elements. Here we report novel insertions and excisions of IS elements and recombination between homologous IS elements identified in a large collection of Escherichia coli mutation accumulation lines by analysis of whole genome shotgun sequencing data. Based on 857 identified events (758 IS insertions, 98 recombinations and 1 excision), we estimate that the rate of IS insertion is 3.5 × 10(-4) insertions per genome per generation and the rate of IS homologous recombination is 4.5 × 10(-5) recombinations per genome per generation. These events are mostly contributed by the IS elements IS1, IS2, IS5 and IS186 Spatial analysis of new insertions suggest that transposition is biased to proximal insertions, and the length spectrum of IS-caused deletions is largely explained by local hopping. For any of the ISs studied there is no region of the circular genome that is favored or disfavored for new insertions but there are notable hotspots for deletions. Some elements have preferences for non-coding sequence or for the beginning and end of coding regions, largely explained by target site motifs. Interestingly, transposition and deletion rates remain constant across the wild-type and 12 mutant E. coli lines, each deficient in a distinct DNA repair pathway. Finally, we characterized the target sites of four IS families, confirming previous results and characterizing a highly specific pattern at IS186 target-sites, 5'-GGGG(N6/N7)CCCC-3'. We also detected 48 long deletions not involving IS elements.

Causes of natural variation in fitness: evidence from studies of Drosophila populations

DNA sequencing has revealed high levels of variability within most species. Statistical methods based on population genetics theory have been applied to the resulting data and suggest that most mutations affecting functionally important sequences are deleterious but subject to very weak selection. Quantitative genetic studies have provided information on the extent of genetic variation within populations in traits related to fitness and the rate at which variability in these traits arises by mutation. This paper attempts to combine the available information from applications of the two approaches to populations of the fruitfly Drosophila in order to estimate some important parameters of genetic variation, using a simple population genetics model of mutational effects on fitness components. Analyses based on this model suggest the existence of a class of mutations with much larger fitness effects than those inferred from sequence variability and that contribute most of the standing variation in fitness within a population caused by the input of mildly deleterious mutations. However, deleterious mutations explain only part of this standing variation, and other processes such as balancing selection appear to make a large contribution to genetic variation in fitness components in Drosophila.

The effects of demography and long-term selection on the accuracy of genomic prediction with sequence data

The use of dense SNPs to predict the genetic value of an individual for a complex trait is often referred to as "genomic selection" in livestock and crops, but is also relevant to human genetics to predict, for example, complex genetic disease risk. The accuracy of prediction depends on the strength of linkage disequilibrium (LD) between SNPs and causal mutations. If sequence data were used instead of dense SNPs, accuracy should increase because causal mutations are present, but demographic history and long-term negative selection also influence accuracy. We therefore evaluated genomic prediction, using simulated sequence in two contrasting populations: one reducing from an ancestrally large effective population size (Ne) to a small one, with high LD common in domestic livestock, while the second had a large constant-sized Ne with low LD similar to that in some human or outbred plant populations. There were two scenarios in each population; causal variants were either neutral or under long-term negative selection. For large Ne, sequence data led to a 22% increase in accuracy relative to ∼600K SNP chip data with a Bayesian analysis and a more modest advantage with a BLUP analysis. This advantage increased when causal variants were influenced by negative selection, and accuracy persisted when 10 generations separated reference and validation populations. However, in the reducing Ne population, there was little advantage for sequence even with negative selection. This study demonstrates the joint influence of demography and selection on accuracy of prediction and improves our understanding of how best to exploit sequence for genomic prediction.

The relation between the genetic architecture of quantitative traits and long-term genetic response

The genetic architecture of a quantitative trait refers to the number of genetic variants, allele frequencies, and effect sizes of variants that affect a trait and their mode of gene action. This study was conducted to investigate the effect of four shapes of allelic frequency distributions (constant, uniform, L-shaped and U-shaped) and different number of trait-affecting loci (50, 100, 200, 500) on allelic frequency changes, long term genetic response, and maintaining genetic variance. To this end, a population of 440 individuals composed of 40 males and 400 females as well as a genome of 200 cM consisting of two chromosomes and with a mutation rate of 2.5 × 10(-5) per locus was simulated. Selection of superior animals was done using best linear unbiased prediction (BLUP) with assumption of infinitesimal model. Selection intensity was constant over 30 generations of selection. The highest genetic progress obtained when the allelic frequency had L-shaped distribution and number of trait-affecting loci was high (500). Although quantitative genetic theories predict the extinction of genetic variance due to artificial selection in long time, our results showed that under L- and U-shapped allelic frequency distributions, the additive genetic variance is persistent after 30 generations of selection. Further, presence or absence of selection limit can be an indication of low (<50) or high (>100) number of trait-affecting loci, respectively. It was concluded that the genetic architecture of complex traits is an important subject which should be considered in studies concerning long-term response to selection.

Detection of structural variants involving repetitive regions in the reference genome

Next-generation sequencing techniques are now commonly used to characterize structural variations (SVs) in population genomics and elucidate their associations with phenotypes. Many of the computational tools developed for detecting structural variations work by mapping paired-end reads to a reference genome and identifying the discordant read-pairs whose mapped loci in the reference genome deviate from the expected insert size and orientation. However, repetitive regions in the reference genome represent a major challenge in SV detection, because the paired-end reads from these regions may be mapped to multiple loci in the reference genome, resulting in spuriously discordant read-pairs. To address this issue, we have developed an algorithmic approach for read mapping and SV detection based on the framework of A-Bruijn graphs. Instead of mapping reads to a linear sequence of the reference genome, we propose to map reads onto the A-Bruijn graph constructed from the reference genome in which all instances of the same repeat are collapsed into a single edge. As a result, any given read, either from repetitive regions or not, will be mapped to a unique location in the A-Bruijn graph, and each discordant read-pair in the A-Bruijn graph indicates a potentially true SV event. We also developed a simple clustering algorithm to derive valid clusters of these discordant read-pairs, each supporting a different SV event. Finally, we demonstrate the performance of this approach, compared to existing approaches, by identifying transposition events of insertion sequence (IS) elements, a class of simple mobile genetic elements (MGEs), in E. coli by using simulated and real paired-end sequence data acquired from E. coli mutation accumulation lines.

The interaction between selection, demography and selfing and how it affects population viability

Population extinction due to the accumulation of deleterious mutations has only been considered to occur at small population sizes, large sexual populations being expected to efficiently purge these mutations. However, little is known about how the mutation load generated by segregating mutations affects population size and, eventually, population extinction. We propose a simple analytical model that takes into account both the demographic and genetic evolution of populations, linking population size, density dependence, the mutation load, and self-fertilisation. Analytical predictions were found to be relatively good predictors of population size and probability of population viability when verified using an explicit individual based stochastic model. We show that initially large populations do not always reach mutation-selection balance and can go extinct due to the accumulation of segregating deleterious mutations. Population survival depends not only on the relative fitness and demographic stochasticity, but also on the interaction between the two. When deleterious mutations are recessive, self-fertilisation affects viability non-monotonically and genomic cold-spots could favour the viability of outcrossing populations.

The nature and extent of mutational pleiotropy in gene expression of male Drosophila serrata

The nature and extent of mutational pleiotropy remain largely unknown, despite the central role that pleiotropy plays in many areas of biology, including human disease, agricultural production, and evolution. Here, we investigate the variation in 11,604 gene expression traits among 41 mutation accumulation (MA) lines of Drosophila serrata. We first confirmed that these expression phenotypes were heritable, detecting genetic variation in 96% of them in an outbred, natural population of D. serrata. Among the MA lines, 3385 (29%) of expression traits were variable, with a mean mutational heritability of 0.0005. In most traits, variation was generated by mutations of relatively small phenotypic effect; putative mutations with effects of greater than one phenotypic standard deviation were observed for only 8% of traits. With most (71%) traits unaffected by any mutation, our data provide no support for universal pleiotropy. We further characterized mutational pleiotropy in the 3385 variable traits, using sets of 5, randomly assigned, traits. Covariance among traits chosen at random with respect to their biological function is expected only if pleiotropy is extensive. Taking an analytical approach in which the variance unique to each trait in the random 5-trait sets was partitioned from variance shared among traits, we detected significant (at 5% false discovery rate) mutational covariance in 21% of sets. This frequency of statistically supported covariance implied that at least some mutations must pleiotropically affect a substantial number of traits (>70; 0.6% of all measured traits).

Properties of spontaneous mutational variance and covariance for wing size and shape in Drosophila melanogaster

We estimated mutational variance-covariance matrices, M, for wing shape and size in two genotypes of Drosophila melanogaster after 192 generations of mutation accumulation. We characterized 21 potentially independent aspects of wing shape and size using geometric morphometrics, and analyzed the data using a likelihood-based factor-analytic approach. We implement a previously unused analysis that describes those directions with the greatest difference in evolvability between pairs of matrices. There are significant mutational effects on 19 of 21 possible aspects of wing form, consistent with the high dimensionality of standing genetic variation for wing shape previously identified in D. melanogaster. Mutations have partially recessive effects, consistent with average dominance around 0.25. Sex-specific matrices are relatively similar, although male-specific matrices are slightly larger, as expected due to dosage compensation on the X chromosome. Genotype-specific matrices are quite different. Matrices may differ both because of sampling error based on small samples of mutations with large phenotypic effects, and because of the mutational properties of the genotypes. Genotypic differences are likely to be involved, as the two genotypes have different molecular mutation rates and properties.

Mutation Load: The Fitness of Individuals in Populations Where Deleterious Alleles Are Abundant

Many multicellular eukaryotes have reasonably high per-generation mutation rates. Consequently, most populations harbor an abundance of segregating deleterious alleles. These alleles, most of which are of small effect individually, collectively can reduce substantially the fitness of individuals relative to what it would be otherwise; this is mutation load. Mutation load can be lessened by any factor that causes more mutations to be removed per selective death, such as inbreeding, synergistic epistasis, population structure, or harsh environments. The ecological effects of load are not clear-cut because some conditions (such as selection early in life, sexual selection, reproductive compensation, and intraspecific competition) reduce the effects of load on population size and persistence, but other conditions (such as interspecific competition and load on resource use efficiency) can cause small amounts of load to have strong effects on the population, even extinction. We suggest a series of studies to improve our understanding of the effects of mutation load.

Hidden epistastic interactions can favour the evolution of sex and recombination

Deleterious mutations can have a strong influence on the outcome of evolution. The nature of this influence depends on how mutations combine together to affect fitness. “Negative epistasis” occurs when a new deleterious mutation causes the greatest loss in fitness in a genome that already contains many deleterious mutations. Negative epistasis is a key ingredient for some of the leading hypotheses regarding the evolution of recombination, the evolution of sex, and a variety of other phenomena. In general, laboratory studies have not supported the idea that negative epistasis is ubiquitous, and this has led to doubts about its importance in biological evolution. Here, we show that these experimental results may be misleading, because negative epistasis can produce evolutionary advantages for sex and recombination while simultaneously being almost impossible to detect using current experimental methods. Under asexual reproduction, such hidden epistasis influences evolutionary outcomes only if the fittest individuals are present in substantial numbers, while also forming a very small proportion of the population as a whole. This implies that our results for asexuals will apply only for very large populations, and also limits the extent of the fitness benefits that hidden epistasis can provide. Despite these caveats, our results show that the fitness consequences of sex and recombination cannot always be inferred from observable epistasis alone.

Rate and molecular spectrum of spontaneous mutations in the bacterium Escherichia coli as determined by whole-genome sequencing

Knowledge of the rate and nature of spontaneous mutation is fundamental to understanding evolutionary and molecular processes. In this report, we analyze spontaneous mutations accumulated over thousands of generations by wild-type Escherichia coli and a derivative defective in mismatch repair (MMR), the primary pathway for correcting replication errors. The major conclusions are (i) the mutation rate of a wild-type E. coli strain is ~1 × 10(-3) per genome per generation; (ii) mutations in the wild-type strain have the expected mutational bias for G:C > A:T mutations, but the bias changes to A:T > G:C mutations in the absence of MMR; (iii) during replication, A:T > G:C transitions preferentially occur with A templating the lagging strand and T templating the leading strand, whereas G:C > A:T transitions preferentially occur with C templating the lagging strand and G templating the leading strand; (iv) there is a strong bias for transition mutations to occur at 5'ApC3'/3'TpG5' sites (where bases 5'A and 3'T are mutated) and, to a lesser extent, at 5'GpC3'/3'CpG5' sites (where bases 5'G and 3'C are mutated); (v) although the rate of small (≤4 nt) insertions and deletions is high at repeat sequences, these events occur at only 1/10th the genomic rate of base-pair substitutions. MMR activity is genetically regulated, and bacteria isolated from nature often lack MMR capacity, suggesting that modulation of MMR can be adaptive. Thus, comparing results from the wild-type and MMR-defective strains may lead to a deeper understanding of factors that determine mutation rates and spectra, how these factors may differ among organisms, and how they may be shaped by environmental conditions.

A resolution of the mutation load paradox in humans

Current information on the rate of mutation and the fraction of sites in the genome that are subject to selection suggests that each human has received, on average, at least two new harmful mutations from its parents. These mutations were subsequently removed by natural selection through reduced survival or fertility. It has been argued that the mutation load, the proportional reduction in population mean fitness relative to the fitness of an idealized mutation-free individual, allows a theoretical prediction of the proportion of individuals in the population that fail to reproduce as a consequence of these harmful mutations. Application of this theory to humans implies that at least 88% of individuals should fail to reproduce and that each female would need to have more than 16 offspring to maintain population size. This prediction is clearly at odds with the low reproductive excess of human populations. Here, we derive expressions for the fraction of individuals that fail to reproduce as a consequence of recurrent deleterious mutation () for a model in which selection occurs via differences in relative fitness, such as would occur through competition between individuals. We show that is much smaller than the value predicted by comparing fitness to that of a mutation-free genotype. Under the relative fitness model, we show that depends jointly on U and the selective effects of new deleterious mutations and that a species could tolerate 10's or even 100's of new deleterious mutations per genome each generation.

Quantitative genetics in the genomics era

The genetic analysis of quantitative or complex traits has been based mainly on statistical quantities such as genetic variances and heritability. These analyses continue to be developed, for example in studies of natural populations. Genomic methods are having an impact on progress and prospects. Actual relationships of individuals can be estimated enabling novel quantitative analyses. Increasing precision of linkage mapping is feasible with dense marker panels and designed stocks allowing multiple generations of recombination, and large SNP panels enable the use of genome wide association analysis utilising historical recombination. Whilst such analyses are identifying many loci for disease genes and traits such as height, typically each individually contributes a small amount of the variation. Only by fitting all SNPs without regard to significance can a high proportion be accounted for, so a classical polygenic model with near infinitesimally small effects remains a useful one. Theory indicates that a high proportion of variants will have low minor allele frequency, making detection difficult. Genomic selection, based on simultaneously fitting very dense markers and incorporating these with phenotypic data in breeding value prediction is revolutionising breeding programmes in agriculture and has a major potential role in human disease prediction.

Fisher's geometrical model of fitness landscape and variance in fitness within a changing environment

The fitness of an individual can be simply defined as the number of its offspring in the next generation. However, it is not well understood how selection on the phenotype determines fitness. In accordance with Fisher's fundamental theorem, fitness should have no or very little genetic variance, whereas empirical data suggest that is not the case. To bridge these knowledge gaps, we follow Fisher's geometrical model and assume that fitness is determined by multivariate stabilizing selection toward an optimum that may vary among generations. We assume random mating, free recombination, additive genes, and uncorrelated stabilizing selection and mutational effects on traits. In a constant environment, we find that genetic variance in fitness under mutation-selection balance is a U-shaped function of the number of traits (i.e., of the so-called "organismal complexity"). Because the variance can be high if the organism is of either low or high complexity, this suggests that complexity has little direct costs. Under a temporally varying optimum, genetic variance increases relative to a constant optimum and increasingly so when the mutation rate is small. Therefore, mutation and changing environment together can maintain high genetic variance. These results therefore lend support to Fisher's geometric model of a fitness landscape.

On the pleiotropic structure of the genotype-phenotype map and the evolvability of complex organisms

Analyses of effects of mutants on many traits have enabled estimates to be obtained of the magnitude of pleiotropy, and in reviews of such data others have concluded that the degree of pleiotropy is highly restricted, with implications on the evolvability of complex organisms. We show that these conclusions are highly dependent on statistical assumptions, for example significance levels. We analyze models with pleiotropic effects on all traits at all loci but by variable amounts, considering distributions of numbers of traits declared significant, overall pleiotropic effects, and extent of apparent modularity of effects. We demonstrate that these highly pleiotropic models can give results similar to those obtained in analyses of experimental data and that conclusions on limits to evolvability through pleiotropy are not robust.

Susceptibility of the male fitness phenotype to spontaneous mutation

Adult reproductive success can account for a large fraction of male fitness, however, we know relatively little about the susceptibility of reproductive traits to mutation-accumulation (MA). Estimates of the mutational rate of decline for adult fitness and its components are controversial in Drosophila melanogaster, and post-copulatory performance has not been examined. We therefore separately measured the consequences of MA for total male reproductive success and its major pre-copulatory and post-copulatory components: mating success and sperm competitive success. We also measured juvenile viability, an important fitness component that has been well studied in MA experiments. MA had strongly deleterious effects on both male viability and adult fitness, but the latter declined at a much greater rate. Mutational pressure on total fitness is thus much greater than would be predicted by viability alone. We also noted a significant and positive correlation between all adult traits and viability in the MA lines, suggesting pleiotropy of mutational effect as required by 'good genes' models of sexual selection.

Experimental mutation-accumulation on the X chromosome of Drosophila melanogaster reveals stronger selection on males than females

Background

Sex differences in the magnitude or direction of mutational effect may be important to a variety of population processes, shaping the mutation load and affecting the cost of sex itself. These differences are expected to be greatest after sexual maturity. Mutation-accumulation (MA) experiments provide the most direct way to examine the consequences of new mutations, but most studies have focused on juvenile viability without regard to sex, and on autosomes rather than sex chromosomes; both adult fitness and X-linkage have been little studied. We therefore investigated the effects of 50 generations of X-chromosome mutation accumulation on the fitness of males and females derived from an outbred population of Drosophila melanogaster.

Results

Fitness declined rapidly in both sexes as a result of MA, but adult males showed markedly greater fitness loss relative to their controls compared to females expressing identical genotypes, even when females were made homozygous for the X. We estimate that these mutations are partially additive (h ~ 0.3) in females. In addition, the majority of new mutations appear to harm both males and females.

Conclusions

Our data helps fill a gap in our understanding of the consequences of sexual selection for genetic load, and suggests that stronger selection on males may indeed purge deleterious mutations affecting female fitness.

Association of bovine CD4 and STAT5b single nucleotide polymorphisms with somatic cell scores and milk production traits in Chinese Holsteins

CD4+ T cells play a key role in the immune response of pathogen-induced mastitis in dairy cattle. Mammary gland factor STAT5b is involved in the regulation of CD4+T cell differentiation during inflammatory response and milk production. Little is known about the genetic variation effects of bovine CD4 and STAT5b genes on somatic cell score (SCS) and milk production traits in dairy cattle. The aim of the study was to investigate the single nucleotide polymorphisms (SNPs) of bovine CD4 and STAT5b in Chinese Holsteins and to analyse their association with estimated breeding values (EBVs) for SCS and milk production traits. In the present study, SNPs of CD4 (NC_007303 g.13598C>T) and STAT5b (NC_007317 g.31562 T>C) were identified and genotyped in Chinese Holstein population. The results showed that both SNPs were significantly associated with the EBVs for milk yield and protein yield in Chinese Holstein cows, and the SNP in CD4 was associated with the EBV for SCS (P<0.01). The additive effect of CD4 SNP on protein yield was significant (P<0.05), and the dominant effect of STAT5b SNP was significant on milk yield and protein yield (P<0.01). Cows with combination genotype C7 (CCTT: CD4 g.13598C>T and STAT5b g.31562 T>C) had the highest SCS EBV but lower milk yield, while cows with C2 (TTTC) produced more milk, fat and protein than the other eight combination genotypes. These results suggested that the SNPs in CD4 and STAT5b may be potential genetic markers for SCS and milk/protein yields selecting and warrant further functional research.

Genetic linkage and natural selection

The prevalence of recombination in eukaryotes poses one of the most puzzling questions in biology. The most compelling general explanation is that recombination facilitates selection by breaking down the negative associations generated by random drift (i.e. Hill-Robertson interference, HRI). I classify the effects of HRI owing to: deleterious mutation, balancing selection and selective sweeps on: neutral diversity, rates of adaptation and the mutation load. These effects are mediated primarily by the density of deleterious mutations and of selective sweeps. Sequence polymorphism and divergence suggest that these rates may be high enough to cause significant interference even in genomic regions of high recombination. However, neither seems able to generate enough variance in fitness to select strongly for high rates of recombination. It is plausible that spatial and temporal fluctuations in selection generate much more fitness variance, and hence selection for recombination, than can be explained by uniformly deleterious mutations or species-wide selective sweeps.

The population genetics of mutations: good, bad and indifferent

Population genetics is fundamental to our understanding of evolution, and mutations are essential raw materials for evolution. In this introduction to more detailed papers that follow, we aim to provide an oversight of the field. We review current knowledge on mutation rates and their harmful and beneficial effects on fitness and then consider theories that predict the fate of individual mutations or the consequences of mutation accumulation for quantitative traits. Many advances in the past built on models that treat the evolution of mutations at each DNA site independently, neglecting linkage of sites on chromosomes and interactions of effects between sites (epistasis). We review work that addresses these limitations, to predict how mutations interfere with each other. An understanding of the population genetics of mutations of individual loci and of traits affected by many loci helps in addressing many fundamental and applied questions: for example, how do organisms adapt to changing environments, how did sex evolve, which DNA sequences are medically important, why do we age, which genetic processes can generate new species or drive endangered species to extinction, and how should policy on levels of potentially harmful mutagens introduced into the environment by humans be determined?

Measurements of spontaneous rates of mutations in the recent past and the near future

The rate of spontaneous mutation in natural populations is a fundamental parameter for many evolutionary phenomena. Because the rate of mutation is generally low, most of what is currently known about mutation has been obtained through indirect, complex and imprecise methodological approaches. However, in the past few years genome-wide sequencing of closely related individuals has made it possible to estimate the rates of mutation directly at the level of the DNA, avoiding most of the problems associated with using indirect methods. Here, we review the methods used in the past with an emphasis on next generation sequencing, which may soon make the accurate measurement of spontaneous mutation rates a matter of routine.

Understanding and using quantitative genetic variation

Quantitative genetics, or the genetics of complex traits, is the study of those characters which are not affected by the action of just a few major genes. Its basis is in statistical models and methodology, albeit based on many strong assumptions. While these are formally unrealistic, methods work. Analyses using dense molecular markers are greatly increasing information about the architecture of these traits, but while some genes of large effect are found, even many dozens of genes do not explain all the variation. Hence, new methods of prediction of merit in breeding programmes are again based on essentially numerical methods, but incorporating genomic information. Long-term selection responses are revealed in laboratory selection experiments, and prospects for continued genetic improvement are high. There is extensive genetic variation in natural populations, but better estimates of covariances among multiple traits and their relation to fitness are needed. Methods based on summary statistics and predictions rather than at the individual gene level seem likely to prevail for some time yet.

Catalogues of mammalian long noncoding RNAs: modest conservation and incompleteness

A comparative evolutionary analysis of two mouse long noncoding RNA libraries reveals a much larger pool of noncoding RNAs remains yet to be discovered.

Background

Despite increasing interest in the noncoding fraction of transcriptomes, the number, species-conservation and functions, if any, of many non-protein-coding transcripts remain to be discovered. Two extensive long intergenic noncoding RNA (ncRNA) transcript catalogues are now available for mouse: over 3,000 macroRNAs identified by cDNA sequencing, and 1,600 long intergenic noncoding RNA (lincRNA) intervals that are predicted from chromatin-state maps. Previously we showed that macroRNAs tend to be more highly conserved than putatively neutral sequence, although only 5% of bases are predicted as constrained. By contrast, over a thousand lincRNAs were reported as being highly conserved. This apparent difference may account for the surprisingly small fraction (11%) of transcripts that are represented in both catalogues. Here we sought to resolve the reported discrepancy between the evolutionary rates for these two sets.

Results

Our analyses reveal lincRNA and macroRNA exon sequences to be subject to the same relatively low degree of sequence constraint. Nonetheless, our observations are consistent with the functionality of a fraction of ncRNA in these sets, with up to a quarter of ncRNA exons having evolved significantly slower than neighboring neutral sequence. The more tissue-specific macroRNAs are enriched in predicted RNA secondary structures and thus may often act in trans, whereas the more highly and broadly expressed lincRNAs appear more likely to act in the cis-regulation of adjacent transcription factor genes.

Conclusions

Taken together, our results indicate that each of the two ncRNA catalogues unevenly and lightly samples the true, much larger, ncRNA repertoire of the mouse.

The genetics of inbreeding depression

Inbreeding depression - the reduced survival and fertility of offspring of related individuals - occurs in wild animal and plant populations as well as in humans, indicating that genetic variation in fitness traits exists in natural populations. Inbreeding depression is important in the evolution of outcrossing mating systems and, because intercrossing inbred strains improves yield (heterosis), which is important in crop breeding, the genetic basis of these effects has been debated since the early twentieth century. Classical genetic studies and modern molecular evolutionary approaches now suggest that inbreeding depression and heterosis are predominantly caused by the presence of recessive deleterious mutations in populations.