Correlated asymmetry of sequence and functional divergence between duplicate proteins of Saccharomyces cerevisiae

The role of sequence divergence in functional divergence of duplicate genes is a topic of great interest. In this study, we compare the numbers of amino acid substitutions in each sequence since two yeast duplicates diverged, using a preduplication ancestral outgroup. Using this strategy, we explored the relationship between sequence divergence and functional divergence between duplicate partners. We show that the degree of relative functional asymmetry between duplicate proteins is proportional to the relative sequence divergence between them. Furthermore, of the two duplicates, the copy closer to their ancestral sequence (fewer number of amino acid substitutions) interacts with more proteins and affects fitness more severely when deleted. Therefore, asymmetric sequence divergence between duplicates is correlated with asymmetric functional divergence and may underlie the duplicate's role in genetic robustness against mutations. Among the functional traits considered, protein abundance appears to have the strongest correlation with the nonsynonymous divergence between duplicates. Taken together with the results from whole-genome analyses, our results indicate that within-species duplicates are subject to the same evolutionary force that acts on interspecific sequence and functional divergence. In particular, we detect signs of purifying selection on the more slowly evolving duplicate.     

The effect of functional compensation among duplicate genes can constrain their evolutionary divergence

Gene duplicates have the inherent property of initially being functionally redundant. This means that they can compensate for the effect of deleterious variation occurring at one or more sister sites. Here, I present data bearing on evolutionary theory that illustrates the manner in which any functional adaptation in duplicate genes is markedly constrained because of the compensatory utility provided by a sustained genetic redundancy. Specifically, a two-locus epistatic model of paralogous genes was simulated to investigate the degree of purifying selection imposed, and whether this would serve to impede any possible biochemical innovation. Three population sizes were considered to see if, as expected, there was a significant difference in any selection for robustness. Interestingly, physical linkage between tandem duplicates was actually found to increase the probability of any neofunctionalization and the efficacy of selection, contrary to what is expected in the case of singleton genes. The results indicate that an evolutionary trade-off often exists between any functional change under either positive or relaxed selection and the need to compensate for failures due to degenerative mutations, thereby guaranteeing the reliability of protein production.     

Epistatic selection between coding and regulatory variation in human evolution and disease

Interaction (nonadditive effects) between genetic variants has been highlighted as an important mechanism underlying phenotypic variation, but the discovery of genetic interactions in humans has proved difficult. In this study, we show that the spectrum of variation in the human genome has been shaped by modifier effects of cis-regulatory variation on the functional impact of putatively deleterious protein-coding variants. We analyzed 1000 Genomes population-scale resequencing data from Europe (CEU [Utah residents with Northern and Western European ancestry from the CEPH collection]) and Africa (YRI [Yoruba in Ibadan, Nigeria]) together with gene expression data from arrays and RNA sequencing for the same samples. We observed an underrepresentation of derived putatively functional coding variation on the more highly expressed regulatory haplotype, which suggests stronger purifying selection against deleterious coding variants that have increased penetrance because of their regulatory background. Furthermore, the frequency spectrum and impact size distribution of common regulatory polymorphisms (eQTLs) appear to be shaped in order to minimize the selective disadvantage of having deleterious coding mutations on the more highly expressed haplotype. Interestingly, eQTLs explaining common disease GWAS signals showed an enrichment of putative epistatic effects, suggesting that some disease associations might arise from interactions increasing the penetrance of rare coding variants. In conclusion, our results indicate that regulatory and coding variants often modify the functional impact of each other. This specific type of genetic interaction is detectable from sequencing data in a genome-wide manner, and characterizing these joint effects might help us understand functional mechanisms behind genetic associations to human phenotypes-including both Mendelian and common disease.     

A Population-Genetic Lens into the Process of Gene Loss Following Whole-Genome Duplication

Whole-genome duplications (WGDs) have occurred in many eukaryotic lineages. However, the underlying evolutionary forces and molecular mechanisms responsible for the long-term retention of gene duplicates created by WGDs are not well understood. We employ a population-genomic approach to understand the selective forces acting on paralogs and investigate ongoing duplicate-gene loss in multiple species of Paramecium that share an ancient WGD. We show that mutations that abolish protein function are more likely to be segregating in retained WGD paralogs than in single-copy genes, most likely because of ongoing nonfunctionalization post-WGD. This relaxation of purifying selection occurs in only one WGD paralog, accompanied by the gradual fixation of nonsynonymous mutations and reduction in levels of expression, and occurs over a long period of evolutionary time, “marking” one locus for future loss. Concordantly, the fitness effects of new nonsynonymous mutations and frameshift-causing indels are significantly more deleterious in the highly expressed copy compared with their paralogs with lower expression. Our results provide a novel mechanistic model of gene duplicate loss following WGDs, wherein selection acts on the sum of functional activity of both duplicate genes, allowing the two to wander in expression and functional space, until one duplicate locus eventually degenerates enough in functional efficiency or expression that its contribution to total activity is too insignificant to be retained by purifying selection. Retention of duplicates by such mechanisms predicts long times to duplicate-gene loss, which should not be falsely attributed to retention due to gain/change in function.     

A class III myosin expressed in the retina is a potential candidate for Bardet-Biedl syndrome

Class III myosins are actin-based motors with amino-terminal kinase domains. Expression of these motors is highly enhanced in retinal photoreceptors. As mutations in the gene encoding NINAC, a Drosophila melanogaster class III myosin, cause retinal degeneration, human homologs of this gene are potential candidates for human retinal disease. We have recently reported the cloning of MYO3A, a human myosin III expressed predominantly in the retina and retinal pigmented epithelium [1]. The map locus of MYO3A is close to, but does not overlap, that of human Usher's 1F [2]. Here we introduce a shorter class III myosin isoform, MYO3B, which is expressed in the retina, kidney, and testis. We describe the cDNA sequence, genomic organization, and splice variants of MYO3B expressed in the human retina. A product of 36 exons, MYO3B has several splice variants containing either one or two calmodulin binding (IQ) motifs in the neck domain and one of three predominant tail variations: a short tail ending just past the second IQ motif, or two alternatively spliced longer tails. MYO3B maps to 2q31.1-q31.2, a region that overlaps the locus for a Bardet-Biedl syndrome (BBS5) linked to markers at 2q31 [3].     

A model for niemann-pick type C disease in the nematode Caenorhabditis elegans

Niemann-Pick type C (NP-C) disease is a progressive neurodegenerative disorder characterized by the inappropriate accumulation of unesterified cholesterol in lysosomes [1]. NP-C patients show various defects including hepatosplenomegaly, ataxia, dystonia and dementia. Most cases of NP-C are associated with inactivating mutations of the NPC1 gene [2], which encodes a protein implicated in the retrograde transport of sterols and other cargo from lysosomes [3]. Furthermore, localization of the NPC1 protein to lysosomal/endosomal compartments is essential for proper transport [4]. To create a model of NP-C disease in a simple, genetically tractable organism, we generated deletion mutations in two Caenorhabditis elegans homologs of the human NPC1 gene, designated npc-1 and npc-2. Animals mutant for npc-1 developed slowly, laid eggs prematurely, and were hypersensitive to cholesterol deprivation. Furthermore, npc-1; npc-2 double-mutant animals inappropriately formed dauer larvae under favorable growth conditions. These phenotypes in C. elegans provide a model system for both genetic and chemical suppressor screening that could identify promising drug targets and leads for NP-C disease.     

Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes

A central challenge in interpreting personal genomes is determining which mutations most likely influence disease. Although progress has been made in scoring the functional impact of individual mutations, the characteristics of the genes in which those mutations are found remain largely unexplored. For example, genes known to carry few common functional variants in healthy individuals may be judged more likely to cause certain kinds of disease than genes known to carry many such variants. Until now, however, it has not been possible to develop a quantitative assessment of how well genes tolerate functional genetic variation on a genome-wide scale. Here we describe an effort that uses sequence data from 6503 whole exome sequences made available by the NHLBI Exome Sequencing Project (ESP). Specifically, we develop an intolerance scoring system that assesses whether genes have relatively more or less functional genetic variation than expected based on the apparently neutral variation found in the gene. To illustrate the utility of this intolerance score, we show that genes responsible for Mendelian diseases are significantly more intolerant to functional genetic variation than genes that do not cause any known disease, but with striking variation in intolerance among genes causing different classes of genetic disease. We conclude by showing that use of an intolerance ranking system can aid in interpreting personal genomes and identifying pathogenic mutations.     

A Bayesian ensemble approach with a disease gene network predicts damaging effects of missense variants of human cancers

Large-scale sequencing of cancer genomes has revealed many novel mutations and inter-tumoral heterogeneity. Therefore, prioritizing variants according to their potential deleterious effects has become essential. We constructed a disease gene network and proposed a Bayesian ensemble approach that integrates diverse sources to predict the functional effects of missense variants. We analyzed 23,336 missense disease mutations and 36,232 neutral polymorphisms of 12,039 human proteins. The results showed successful improvement of prediction accuracy in both sensitivity and specificity, and we demonstrated the utility of the method by applying it to somatic mutations obtained from colorectal and breast cancer cell lines. The candidate genes with predicted deleterious mutations as well as known cancer genes were significantly enriched in many KEGG pathways related to carcinogenesis, supporting genetic homogeneity of cancer at the pathway level. The breast cancer-specific network increased the prediction accuracy for breast cancer mutations. This study provides a ranked list of deleterious mutations and candidate cancer genes and suggests that mutations affecting cancer may occur in important pathways and should be interpreted on the phenotype-related network or pathway. A disease gene network may be of value in predicting functional effects of novel disease-specific mutations.     

Outbreeding alleviates senescence in hermaphroditic snails as expected from the mutation-accumulation theory

Senescence, the decline in fitness components of an organism with age [1], is a nearly universal characteristic of living beings [2-6]. This ubiquity is challenging because natural selection does not favor the evolution of traits decreasing fitness [1, 7, 8]. Senescence may result from two nonexclusive mechanisms: the accumulation of deleterious mutations acting late in life, when the strength of natural selection against them declines [9-11] (mutation accumulation or MA hypothesis [12]) and the delayed cost of genes having beneficial effects early in life (antagonistic pleiotropy or AP hypothesis [13]). Few empirical studies have evaluated their contribution to the standing genetic variation in senescence. These studies focused on Drosophila and may be compromised by recent laboratory adaptation [14]. We here study genetic variation in aging patterns in snails (Physa acuta) freshly sampled in natural populations. Our results strongly support the MA theory by validating all its classical predictions, confirming previous results in Drosophila. We also report a striking, novel finding: interbreeding between natural populations alleviates the decline in survival with age. We provide new theoretical models showing this to be another consequence of MA. Our results offer interesting perspectives on how different populations may follow different genetic pathways to evolve senescence.     

Neutral evolution of robustness in Drosophila microRNA precursors

Mutational robustness describes the extent to which a phenotype remains unchanged in the face of mutations. Theory predicts that the strength of direct selection for mutational robustness is at most the magnitude of the rate of deleterious mutation. As far as nucleic acid sequences are concerned, only long sequences in organisms with high deleterious mutation rates and large population sizes are expected to evolve mutational robustness. Surprisingly, recent studies have concluded that molecules that meet none of these conditions--the microRNA precursors (pre-miRNAs) of multicellular eukaryotes--show signs of selection for mutational and/or environmental robustness. To resolve the apparent disagreement between theory and these studies, we have reconstructed the evolutionary history of Drosophila pre-miRNAs and compared the robustness of each sequence to that of its reconstructed ancestor. In addition, we "replayed the tape" of pre-miRNA evolution via simulation under different evolutionary assumptions and compared these alternative histories with the actual one. We found that Drosophila pre-miRNAs have evolved under strong purifying selection against changes in secondary structure. Contrary to earlier claims, there is no evidence that these RNAs have been shaped by either direct or congruent selection for any kind of robustness. Instead, the high robustness of Drosophila pre-miRNAs appears to be mostly intrinsic and likely a consequence of selection for functional structures.     

Viral RNA and evolved mutational robustness.

Many properties of organisms show great robustness against mutations. Whether this robustness is an evolved property or intrinsic to genetic systems is by and large unknown. An evolutionary origin of robustness would require a rethinking of key concepts in the field of molecular evolution, such as gene-specific neutral mutation rates, or the context-independence of deleterious mutations. We provide evidence that mutational robustness of the genome of RNA viruses to mutational changes in secondary structure has evolved. J. Exp. Zool. ( Mol. Dev. Evol.) 285:119-127, 1999.     

OrthoDisease: tracking disease gene orthologs across 100 species

Orthology is one of the most important tools available to modern biology, as it allows making inferences from easily studied model systems to much less tractable systems of interest, such as ourselves. This becomes important not least in the study of genetic diseases. We here review work on the orthology of disease-associated genes and also present an updated version of the InParanoid-based disease orthology database and web site OrthoDisease, with 14-fold increased species coverage since the previous version. Using this resource, we survey the taxonomic distribution of orthologs of human genes involved in different disease categories. The hypothesis that paralogs can mask the effect of deleterious mutations predicts that known heritable disease genes should have fewer close paralogs. We found large-scale support for this hypothesis as significantly fewer duplications were observed for disease genes in the OrthoDisease ortholog groups.     

Are rare variants responsible for susceptibility to complex diseases?

Little is known about the nature of genetic variation underlying complex diseases in humans. One popular view proposes that mapping efforts should focus on identification of susceptibility mutations that are relatively old and at high frequency. It is generally assumed-at least for modeling purposes-that selection against complex disease mutations is so weak that it can be ignored. In this article, I propose an explicit model for the evolution of complex disease loci, incorporating mutation, random genetic drift, and the possibility of purifying selection against susceptibility mutations. I show that, for the most plausible range of mutation rates, neutral susceptibility alleles are unlikely to be at intermediate frequencies and contribute little to the overall genetic variance for the disease. Instead, it seems likely that the bulk of genetic variance underlying diseases is due to loci where susceptibility mutations are mildly deleterious and where there is a high overall mutation rate to the susceptible class. At such loci, the total frequency of susceptibility mutations may be quite high, but there is likely to be extensive allelic heterogeneity at many of these loci. I discuss some practical implications of these results for gene mapping efforts.     

Predicting the functional impact of protein mutations: application to cancer genomics

As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (∼19 200), assumed to be strongly functional, from common polymorphisms (∼35 600), assumed to be weakly functional (area under the receiver operating characteristic curve of ∼0.86). In cancer, using recurrence, multiplicity and annotation for ∼10 000 mutations in the COSMIC database, the method does well in assigning higher scores to more likely functional mutations (‘drivers’). To guide experimental prioritization, we report a list of about 1000 top human cancer genes frequently mutated in one or more cancer types ranked by likely functional impact; and, an additional 1000 candidate cancer genes with rare but likely functional mutations. In addition, we estimate that at least 5% of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function.     

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.     

Function-specific accelerations in rates of sequence evolution suggest predictable epistatic responses to reduced effective population size

Changes in effective population size impinge on patterns of molecular evolution. Notably, slightly deleterious mutations are more likely to drift to fixation in smaller populations, which should typically also lead to an overall acceleration in the rates of evolution. This prediction has been validated empirically for several endosymbiont and island taxa. Here, we first show that rate accelerations are also evident in bacterial pathogens whose recent shifts in virulence make them prime candidates for reduced effective population size: Bacillus anthracis, Bordetella parapertussis, Mycobacterium leprae, Salmonella enterica typhi, Shigella spp., and Yersinia pestis. Using closely related genomes to analyze substitution rate dynamics across six phylogenetically independent bacterial clades, we demonstrate that relative rates of coding sequence evolution are biased according to gene functional category. Notably, genes that buffer against slightly deleterious mutations, such as chaperones, experience stronger rate accelerations than other functional classes at both nonsynonymous and synonymous sites. Although theory predicts altered evolutionary dynamics for buffer loci in the face of accumulating deleterious mutations, to observe even stronger rate accelerations is surprising. We suggest that buffer loci experience elevated substitution rates because the accumulation of deleterious mutations in the remainder of the genome favors compensatory substitutions in trans. Critically, the hyper-acceleration is evident across phylogenetically independent clades, supporting the hypothesis that reductions in effective population size predictably induce epistatic responses in genes that buffer against slightly deleterious mutations.     

Prediction of phenotypes of missense mutations in human proteins from biological assemblies

Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence‐based and structure‐based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure‐based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X‐ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease‐associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e‐5). When adding this information to sequence‐based features such as the difference between wildtype and mutant position‐specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence‐based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease‐associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Proteins 2013. © 2012 Wiley Periodicals, Inc.