Distribution of the strength of selection against amino acid replacements in human proteins

The temporal dynamics of processes underlying Y chromosome degeneration

Y chromosomes originate from ordinary autosomes and degenerate by accumulating deleterious mutations. This accumulation results from a lack of recombination on the Y and is driven by interference among deleterious mutations (Muller's ratchet and background selection) and the fixation of beneficial alleles (genetic hitchhiking). Here I show that the relative importance of these processes is expected to vary over the course of Y chromosome evolution due to changes in the number of active genes. The dominant mode of degeneration on a newly formed gene-rich Y chromosome is expected to be Muller's ratchet and/or background selection due to the large numbers of deleterious mutations arising in active genes. However, the relative importance of these modes of degeneration declines rapidly as active genes are lost. In contrast, the rate of degeneration due to hitchhiking is predicted to be highest on Y chromosomes containing an intermediate number of active genes. The temporal dynamics of these processes imply that a gradual restriction of recombination, as inferred in mammals, will increase the importance of genetic hitchhiking relative to Muller's ratchet and background selection.

Assessing the evolutionary impact of amino acid mutations in the human genome

Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein coding-genes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find strong evidence for great variability in the selective effects of new amino acid replacing mutations. In both populations, the patterns of variation are consistent with a leptokurtic distribution of selection coefficients (e.g., gamma or log-normal) peaked near neutrality. Specifically, we predict 27-29% of amino acid changing (nonsynonymous) mutations are neutral or nearly neutral (|s|<0.01%), 30-42% are moderately deleterious (0.01%<|s|<1%), and nearly all the remainder are highly deleterious or lethal (|s|>1%). Our results are consistent with 10-20% of amino acid differences between humans and chimpanzees having been fixed by positive selection with the remainder of differences being neutral or nearly neutral. Our analysis also predicts that many of the alleles identified via whole-genome association mapping may be selectively neutral or (formerly) positively selected, implying that deleterious genetic variation affecting disease phenotype may be missed by this widely used approach for mapping genes underlying complex traits.

Joint inference of the distribution of fitness effects of deleterious mutations and population demography based on nucleotide polymorphism frequencies

The distribution of fitness effects of new mutations (DFE) is important for addressing several questions in genetics, including the nature of quantitative variation and the evolutionary fate of small populations. Properties of the DFE can be inferred by comparing the distributions of the frequencies of segregating nucleotide polymorphisms at selected and neutral sites in a population sample, but demographic changes alter the spectrum of allele frequencies at both neutral and selected sites, so can bias estimates of the DFE if not accounted for. We have developed a maximum-likelihood approach, based on the expected allele-frequency distribution generated by transition matrix methods, to estimate parameters of the DFE while simultaneously estimating parameters of a demographic model that allows a population size change at some time in the past. We tested the method using simulations and found that it accurately recovers simulated parameter values, even if the simulated demography differs substantially from that assumed in our analysis. We use our method to estimate parameters of the DFE for amino acid-changing mutations in humans and Drosophila melanogaster. For a model of unconditionally deleterious mutations, with effects sampled from a gamma distribution, the mean estimate for the distribution shape parameter is approximately 0.2 for human populations, which implies that the DFE is strongly leptokurtic. For Drosophila populations, we estimate that the shape parameter is approximately 0.35. Differences in the shape of the distribution and the mean selection coefficient between humans and Drosophila result in significantly more strongly deleterious mutations in Drosophila than in humans, and, conversely, nearly neutral mutations are significantly less frequent.

The McDonald-Kreitman test and slightly deleterious mutations

It is possible to estimate the proportion of substitutions that are due to adaptive evolution using the numbers of silent and nonsilent polymorphisms and substitutions in a McDonald and Kreitman-type analysis. Unfortunately, this estimate of adaptive evolution is biased downward by the segregation of slightly deleterious mutations. It has been suggested that 1 way to cope with the effects of these slightly deleterious mutations is to remove low-frequency polymorphisms from the analysis. We investigate the performance of this method theoretically. We show that although removing low-frequency polymorphisms does indeed reduce the bias in the estimate of adaptive evolution, the estimate is always downwardly biased, often to the extent that one would not be able to detect adaptive evolution, even if it existed. The method is reasonably satisfactory, only if the rate of adaptive evolution is high and the distribution of fitness effects for slightly deleterious mutations is very leptokurtic. Our analysis suggests that adaptive evolution could be quite prevalent in humans (>8%) and still not be detectable using current methodologies. Our analysis also suggests that the level of adaptive evolution has probably been underestimated, possibly substantially, in both bacteria and Drosophila.

Extensive parallelism in protein evolution

BACKGROUND

Independently evolving lineages mostly accumulate different changes, which leads to their gradual divergence. However, parallel accumulation of identical changes is also common, especially in traits with only a small number of possible states.

RESULTS

We characterize parallelism in evolution of coding sequences in three four-species sets of genomes of mammals, Drosophila, and yeasts. Each such set contains two independent evolutionary paths, which we call paths I and II. An amino acid replacement which occurred along path I also occurs along path II with the probability 50-80% of that expected under selective neutrality. Thus, the per site rate of parallel evolution of proteins is several times higher than their average rate of evolution, but still lower than the rate of evolution of neutral sequences. This deficit may be caused by changes in the fitness landscape, leading to a replacement being possible along path I but not along path II. However, constant, weak selection assumed by the nearly neutral model of evolution appears to be a more likely explanation. Then, the average coefficient of selection associated with an amino acid replacement, in the units of the effective population size, must exceed approximately 0.4, and the fraction of effectively neutral replacements must be below approximately 30%. At a majority of evolvable amino acid sites, only a relatively small number of different amino acids is permitted.

CONCLUSION

High, but below-neutral, rates of parallel amino acid replacements suggest that a majority of amino acid replacements that occur in evolution are subject to weak, but non-trivial, selection, as predicted by Ohta's nearly-neutral theory.

Accumulation of slightly deleterious mutations in mitochondrial protein-coding genes of large versus small mammals

After the effective size of a population, N(e), declines, some slightly deleterious amino acid replacements which were initially suppressed by purifying selection become effectively neutral and can reach fixation. Here we investigate this phenomenon for a set of all 13 mitochondrial protein-coding genes from 110 mammalian species. By using body mass as a proxy for N(e), we show that large mammals (i.e., those with low N(e)) as compared with small ones (in our sample these are, on average, 369.5 kg and 275 g, respectively) have a 43% higher rate of accumulation of nonsynonymous nucleotide substitutions relative to synonymous substitutions, and an 8-40% higher rate of accumulation of radical amino acid substitutions relative to conservative substitutions, depending on the type of amino acid classification. These higher rates result in a 6% greater amino acid dissimilarity between modern species and their most recent reconstructed ancestors in large versus small mammals. Because nonsynonymous substitutions are likely to be more harmful than synonymous substitutions, and radical amino acid substitutions are likely to be more harmful than conservative ones, our results suggest that large mammals experience less efficient purifying selection than small mammals. Furthermore, because in the course of mammalian evolution body size tends to increase and, consequently, N(e) tends to decline, evolution of mammals toward large body size may involve accumulation of slightly deleterious mutations in mitochondrial protein-coding genes, which may contribute to decline or extinction of large mammals.

Looking for Darwin in all the wrong places: the misguided quest for positive selection at the nucleotide sequence level

Recent years have seen an explosion of interest in evidence for positive Darwinian selection at the molecular level. This quest has been hampered by the use of statistical methods that fail adequately to rule out alternative hypotheses, particularly the relaxation of purifying selection and the effects of population bottlenecks, during which the effectiveness of purifying selection is reduced. A further problem has been the assumption that positive selection will generally involve repeated amino-acid changes to a single protein. This model was derived from the case of the vertebrate major histocompatibility complex (MHC), but the MHC proteins are unusual in being involved in protein-protein recognition and in a co-evolutionary process of pathogens. There is no reason to suppose that repeated amino-acid changes to a single protein are involved in selectively advantageous phenotypes in general. Rather adaptive phenotypes are much more likely to result from other causes, including single amino-acid changes; deletion or silencing of genes or changes in the pattern of gene expression.

Most rare missense alleles are deleterious in humans: implications for complex disease and association studies

The accumulation of mildly deleterious missense mutations in individual human genomes has been proposed to be a genetic basis for complex diseases. The plausibility of this hypothesis depends on quantitative estimates of the prevalence of mildly deleterious de novo mutations and polymorphic variants in humans and on the intensity of selective pressure against them. We combined analysis of mutations causing human Mendelian diseases, of human-chimpanzee divergence, and of systematic data on human genetic variation and found that ~20% of new missense mutations in humans result in a loss of function, whereas ~27% are effectively neutral. Thus, the remaining 53% of new missense mutations have mildly deleterious effects. These mutations give rise to many low-frequency deleterious allelic variants in the human population, as is evident from a new data set of 37 genes sequenced in >1,500 individual human chromosomes. Surprisingly, up to 70% of low-frequency missense alleles are mildly deleterious and are associated with a heterozygous fitness loss in the range 0.001-0.003. Thus, the low allele frequency of an amino acid variant can, by itself, serve as a predictor of its functional significance. Several recent studies have reported a significant excess of rare missense variants in candidate genes or pathways in individuals with extreme values of quantitative phenotypes. These studies would be unlikely to yield results if most rare variants were neutral or if rare variants were not a significant contributor to the genetic component of phenotypic inheritance. Our results provide a justification for these types of candidate-gene (pathway) association studies and imply that mutation-selection balance may be a feasible evolutionary mechanism underlying some common diseases.

Inferring the distribution of mutational effects on fitness in Drosophila

The properties of the distribution of deleterious mutational effects on fitness (DDME) are of fundamental importance for evolutionary genetics. Since it is extremely difficult to determine the nature of this distribution, several methods using various assumptions about the DDME have been developed, for the purpose of parameter estimation. We apply a newly developed method to DNA sequence polymorphism data from two Drosophila species and compare estimates of the parameters of the distribution of the heterozygous fitness effects of amino acid mutations for several different distribution functions. The results exclude normal and gamma distributions, since these predict too few effectively lethal mutations and power-law distributions as a result of predicting too many lethals. Only the lognormal distribution appears to fit both the diversity data and the frequency of lethals. This DDME arises naturally in complex systems when independent factors contribute multiplicatively to an increase in fitness-reducing damage. Several important parameters, such as the fraction of effectively neutral non-synonymous mutations and the harmonic mean of non-neutral selection coefficients, are robust to the form of the DDME. Our results suggest that the majority of non-synonymous mutations in Drosophila are under effective purifying selection.

Human catechol-O-methyltransferase haplotypes modulate protein expression by altering mRNA secondary structure

Catechol-O-methyltransferase (COMT) is a key regulator of pain perception, cognitive function, and affective mood. Three common haplotypes of the human COMT gene, divergent in two synonymous and one nonsynonymous position, code for differences in COMT enzymatic activity and are associated with pain sensitivity. Haplotypes divergent in synonymous changes exhibited the largest difference in COMT enzymatic activity, due to a reduced amount of translated protein. The major COMT haplotypes varied with respect to messenger RNA local stem-loop structures, such that the most stable structure was associated with the lowest protein levels and enzymatic activity. Site-directed mutagenesis that eliminated the stable structure restored the amount of translated protein. These data highlight the functional significance of synonymous variations and suggest the importance of haplotypes over single-nucleotide polymorphisms for analysis of genetic variations.

Stabilizing selection of protein function and distribution of selection coefficient among sites

In this study, I take a new approach to modeling the evolutionary constraint of protein sequence, introducing the stabilizing selection of protein function into the nearly-neutral theory. In other words, protein function under stabilizing selection generates the evolutionary conservation at the sequence level. With the help of random mutational effects of nucleotides on protein function, I have derived the distribution of selection coefficient among sites, called the S-distribution whose parameters have clear biological interpretations. Moreover, I have studied the inverse relationship between the evolutionary rate and the effective population size, showing that the number of molecular phenotypes of protein function, i.e., independent components in the fitness of the organism, may play a key role for the molecular clock under the nearly-neutral theory. These results are helpful for having a better understanding of the underlying evolutionary mechanism of protein sequences, as well as human disease-related mutations.

Higher intensity of purifying selection on >90% of the human genes revealed by the intrinsic replacement mutation rates

For over 3 decades, the rate of replacement mutations has been assumed to be equal to, and estimated from, the rate of "strictly" neutral sequence divergence in noncoding regions and in silent-codon positions where mutations do not alter the amino acid encoded. This assumption is fundamental to estimating the fraction of harmful protein mutations and to identifying adaptive evolution at individual codons and proteins. We show that the assumption is not justifiable because a much larger fraction of codon positions is involved in hypermutable CpG dinucleotides as compared with the introns, leading to a higher expected replacement mutation rate per site in a vast majority of the genes. Consideration of this difference reveals a higher intensity of purifying natural selection than previously inferred in human genes. We also show that a much smaller number of genes are expected to be evolving with positive selection than that predicted using sequence divergence at intron and silent positions in the human genome. These patterns indicate the need for using new approaches for estimating rates of amino acid-altering mutations in order to find positively selected genes and codons in genomes that contain hypermutable CpG's.

How reliable are empirical genomic scans for selective sweeps?

The beneficial substitution of an allele shapes patterns of genetic variation at linked sites. Thus, in principle, adaptations can be mapped by looking for the signature of directional selection in polymorphism data. In practice, such efforts are hampered by the need for an accurate characterization of the demographic history of the species and of the effects of positive selection. In an attempt to circumvent these difficulties, researchers are increasingly taking a purely empirical approach, in which a large number of genomic regions are ordered by summaries of the polymorphism data, and loci with extreme values are considered to be likely targets of positive selection. We evaluated the reliability of the "empirical" approach, focusing on applications to human data and to maize. To do so, we considered a coalescent model of directional selection in a sensible demographic setting, allowing for selection on standing variation as well as on a new mutation. Our simulations suggest that while empirical approaches will identify several interesting candidates, they will also miss many--in some cases, most--loci of interest. The extent of the trade-off depends on the mode of positive selection and the demographic history of the population. Specifically, the false-discovery rate is higher when directional selection involves a recessive rather than a co-dominant allele, when it acts on a previously neutral rather than a new allele, and when the population has experienced a population bottleneck rather than maintained a constant size. One implication of these results is that, insofar as attributes of the beneficial mutation (e.g., the dominance coefficient) affect the power to detect targets of selection, genomic scans will yield an unrepresentative subset of loci that contribute to adaptations.

The distribution of fitness effects of new deleterious amino acid mutations in humans

The distribution of fitness effects of new mutations is a fundamental parameter in genetics. Here we present a new method by which the distribution can be estimated. The method is fairly robust to changes in population size and admixture, and it can be corrected for any residual effects if a model of the demography is available. We apply the method to extensively sampled single-nucleotide polymorphism data from humans and estimate the distribution of fitness effects for amino acid changing mutations. We show that a gamma distribution with a shape parameter of 0.23 provides a good fit to the data and we estimate that >50% of mutations are likely to have mild effects, such that they reduce fitness by between one one-thousandth and one-tenth. We also infer that <15% of new mutations are likely to have strongly deleterious effects. We estimate that on average a nonsynonymous mutation reduces fitness by a few percent and that the average strength of selection acting against a nonsynonymous polymorphism is approximately 9 x 10(-5). We argue that the relaxation of natural selection due to modern medicine and reduced variance in family size is not likely to lead to a rapid decline in genetic quality, but that it will be very difficult to locate most of the genes involved in complex genetic diseases.