Selective constraint, background selection, and mutation accumulation variability within and between human populations

Why does the X chromosome lag behind autosomes in GWAS findings?

The X-chromosome is among the largest human chromosomes. It differs from autosomes by a number of important features including hemizygosity in males, an almost complete inactivation of one copy in females, and unique patterns of recombination. We used data from the Catalog of Published Genome Wide Association Studies to compare densities of the GWAS-detected SNPs on the X-chromosome and autosomes. The density of GWAS-detected SNPs on the X-chromosome is 6-fold lower compared to the density of the GWAS-detected SNPs on autosomes. Differences between the X-chromosome and autosomes cannot be explained by differences in the overall SNP density, lower X-chromosome coverage by genotyping platforms or low call rate of X-chromosomal SNPs. Similar differences in the density of GWAS-detected SNPs were found in female-only GWASs (e.g. ovarian cancer GWASs). We hypothesized that the lower density of GWAS-detected SNPs on the X-chromosome compared to autosomes is not a result of a methodological bias, e.g. differences in coverage or call rates, but has a real underlying biological reason-a lower density of functional SNPs on the X-chromosome versus autosomes. This hypothesis is supported by the observation that (i) the overall SNP density of X-chromosome is lower compared to the SNP density on autosomes and that (ii) the density of genic SNPs on the X-chromosome is lower compared to autosomes while densities of intergenic SNPs are similar.

Molecular and in vivo phenotyping of missense variants of the human glucagon receptor

Naturally occurring missense variants of G protein–coupled receptors with loss of function have been linked to metabolic disease in case studies and in animal experiments. The glucagon receptor, one such G protein–coupled receptor, is involved in maintaining blood glucose and amino acid homeostasis; however, loss-of-function mutations of this receptor have not been systematically characterized. Here, we observed fewer glucagon receptor missense variants than expected, as well as lower allele diversity and fewer variants with trait associations as compared with other class B1 receptors. We performed molecular pharmacological phenotyping of 38 missense variants located in the receptor extracellular domain, at the glucagon interface, or with previously suggested clinical implications. These variants were characterized in terms of cAMP accumulation to assess glucagon-induced Gα_s coupling, and of recruitment of β-arrestin-1/2. Fifteen variants were impaired in at least one of these downstream functions, with six variants affected in both cAMP accumulation and β-arrestin-1/2 recruitment. For the eight variants with decreased Gα_s signaling (D63^ECDN, P86^ECDS, V96^ECDE, G125^ECDC, R225^3.30H, R308^5.40W, V368^6.59M, and R378^7.35C) binding experiments revealed preserved glucagon affinity, although with significantly reduced binding capacity. Finally, using the UK Biobank, we found that variants with wildtype-like Gα_s signaling did not associate with metabolic phenotypes, whereas carriers of cAMP accumulation-impairing variants displayed a tendency toward increased risk of obesity and increased body mass and blood pressure. These observations are in line with the essential role of the glucagon system in metabolism and support that Gα_s is the main signaling pathway effecting the physiological roles of the glucagon receptor.

The Value of Reference Genomes in the Conservation of Threatened Species

Conservation initiatives are now more crucial than ever-over a million plant and animal species are at risk of extinction over the coming decades. The genetic management of threatened species held in insurance programs is recommended; however, few are taking advantage of the full range of genomic technologies available today. Less than 1% of the 13505 species currently listed as threated by the International Union for Conservation of Nature (IUCN) have a published genome. While there has been much discussion in the literature about the importance of genomics for conservation, there are limited examples of how having a reference genome has changed conservation management practice. The Tasmanian devil (Sarcophilus harrisii), is an endangered Australian marsupial, threatened by an infectious clonal cancer devil facial tumor disease (DFTD). Populations have declined by 80% since the disease was first recorded in 1996. A reference genome for this species was published in 2012 and has been crucial for understanding DFTD and the management of the species in the wild. Here we use the Tasmanian devil as an example of how a reference genome has influenced management actions in the conservation of a species.

Genetic Variation in Pan Species Is Shaped by Demographic History and Harbors Lineage-Specific Functions

Chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) are the closest living relatives of humans, but the two species show distinct behavioral and physiological differences, particularly regarding female reproduction. Despite their recent rapid decline, the demographic histories of the two species have been different during the past 1–2 Myr, likely having an impact on their genomic diversity. Here, we analyze the inferred functional consequences of genetic variation across 69 individuals, making use of the most complete data set of genomes in the Pan clade to date. We test to which extent the demographic history influences the efficacy of purifying selection in these species. We find that small historical effective population sizes (N_e) correlate not only with low levels of genetic diversity but also with a larger number of deleterious alleles in homozygosity and an increased proportion of deleterious changes at low frequencies. To investigate the putative genetic basis for phenotypic differences between chimpanzees and bonobos, we exploit the catalog of putatively deleterious protein-coding changes in each lineage. We show that bonobo-specific nonsynonymous changes are enriched in genes related to age at menarche in humans, suggesting that the prominent physiological differences in the female reproductive system between chimpanzees and bonobos might be explained, in part, by putatively adaptive changes on the bonobo lineage.

Understanding the Hidden Complexity of Latin American Population Isolates

Most population isolates examined to date were founded from a single ancestral population. Consequently, there is limited knowledge about the demographic history of admixed population isolates. Here we investigate genomic diversity of recently admixed population isolates from Costa Rica and Colombia and compare their diversity to a benchmark population isolate, the Finnish. These Latin American isolates originated during the 16th century from admixture between a few hundred European males and Amerindian females, with a limited contribution from African founders. We examine whole-genome sequence data from 449 individuals, ascertained as families to build mutigenerational pedigrees, with a mean sequencing depth of coverage of approximately 36×. We find that Latin American isolates have increased genetic diversity relative to the Finnish. However, there is an increase in the amount of identity by descent (IBD) segments in the Latin American isolates relative to the Finnish. The increase in IBD segments is likely a consequence of a very recent and severe population bottleneck during the founding of the admixed population isolates. Furthermore, the proportion of the genome that falls within a long run of homozygosity (ROH) in Costa Rican and Colombian individuals is significantly greater than that in the Finnish, suggesting more recent consanguinity in the Latin American isolates relative to that seen in the Finnish. Lastly, we find that recent consanguinity increased the number of deleterious variants found in the homozygous state, which is relevant if deleterious variants are recessive. Our study suggests that there is no single genetic signature of a population isolate.

Properties of human disease genes and the role of genes linked to Mendelian disorders in complex disease aetiology

Do genes presenting variation that has been linked to human disease have different biological properties than genes that have never been related to disease? What is the relationship between disease and fitness? Are the evolutionary pressures that affect genes linked to Mendelian diseases the same to those acting on genes whose variation contributes to complex disorders? The answers to these questions could shed light on the architecture of human genetic disorders and may have relevant implications when designing mapping strategies in future genetic studies. Here we show that, relative to non-disease genes, human disease (HD) genes have specific evolutionary profiles and protein network properties. Additionally, our results indicate that the mutation-selection balance renders an insufficient account of the evolutionary history of some HD genes and that adaptive selection could also contribute to shape their genetic architecture. Notably, several biological features of HD genes depend on the type of pathology (complex or Mendelian) with which they are related. For example, genes harbouring both causal variants for Mendelian disorders and risk factors for complex disease traits (Complex-Mendelian genes), tend to present higher functional relevance in the protein network and higher expression levels than genes associated only with complex disorders. Moreover, risk variants in Complex-Mendelian genes tend to present higher odds ratios than those on genes associated with the same complex disorders but with no link to Mendelian diseases. Taken together, our results suggest that genetic variation at genes linked to Mendelian disorders plays an important role in driving susceptibility to complex disease.

The impact of recent population history on the deleterious mutation load in humans and close evolutionary relatives

Over the past decade, there has been both great interest and confusion about whether recent demographic events-notably the Out-of-Africa-bottleneck and recent population growth-have led to differences in mutation load among human populations. The confusion can be traced to the use of different summary statistics to measure load, which lead to apparently conflicting results. We argue, however, that when statistics more directly related to load are used, the results of different studies and data sets consistently reveal little or no difference in the load of non-synonymous mutations among human populations. Theory helps to understand why no such differences are seen, as well as to predict in what settings they are to be expected. In particular, as predicted by modeling, there is evidence for changes in the load of recessive loss of function mutations in founder and inbred human populations. Also as predicted, eastern subspecies of gorilla, Neanderthals and Denisovans, who are thought to have undergone reductions in population sizes that exceed the human Out-of-Africa bottleneck in duration and severity, show evidence for increased load of non-synonymous mutations (relative to western subspecies of gorillas and modern humans, respectively). A coherent picture is thus starting to emerge about the effects of demographic history on the mutation load in populations of humans and close evolutionary relatives.

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10^-12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046-0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027-0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale.

The distribution of deleterious genetic variation in human populations

Population genetic studies suggest that most amino-acid changing mutations are deleterious. Such mutations are of tremendous interest in human population genetics as they are important for the evolutionary process and may contribute risk to common disease. Genomic studies over the past 5 years have documented differences across populations in the number of heterozygous deleterious genotypes, number of homozygous derived deleterious genotypes, number of deleterious segregating sites and proportion of sites that are potentially deleterious. These differences have been attributed to population history affecting the ability of natural selection to remove deleterious variants from the population. However, recent studies have suggested that the genetic load is the same across populations and that the efficacy of natural selection has not differed across human populations. Here I show that these observations are not incompatible with each other and that the apparent differences are due to examining different features of the genetic data and differing definitions of terms.

Characteristics of neutral and deleterious protein-coding variation among individuals and populations

Whole-genome and exome data sets continue to be produced at a frenetic pace, resulting in massively large catalogs of human genomic variation. However, a clear picture of the characteristics and patterns of neutral and deleterious variation within and between populations has yet to emerge, given that recent large-scale sequencing studies have often emphasized different aspects of the data and sometimes appear to have conflicting conclusions. Here, we comprehensively studied characteristics of protein-coding variation in high-coverage exome sequence data from 6,515 European American (EA) and African American (AA) individuals. We developed an unbiased approach to identify putatively deleterious variants and investigated patterns of neutral and deleterious single-nucleotide variants and alleles between individuals and populations. We show that there are substantial differences in the composition of genotypes between EA and AA populations and that small but statistically significant differences exist in the average number of deleterious alleles carried by EA and AA individuals. Furthermore, we performed extensive simulations to delineate the temporal dynamics of deleterious alleles for a broad range of demographic models and use these data to inform the interpretation of empirical patterns of deleterious variation. Finally, we illustrate that the effects of demographic perturbations, such as bottlenecks and expansions, often manifest in opposing patterns of neutral and deleterious variation depending on whether the focus is on populations or individuals. Our results clarify seemingly disparate empirical characteristics of protein-coding variation and provide substantial insights into how natural selection and demographic history have patterned neutral and deleterious variation within and between populations.

Whole-exome sequencing reveals a rapid change in the frequency of rare functional variants in a founding population of humans

Whole-exome or gene targeted resequencing in hundreds to thousands of individuals has shown that the majority of genetic variants are at low frequency in human populations. Rare variants are enriched for functional mutations and are expected to explain an important fraction of the genetic etiology of human disease, therefore having a potential medical interest. In this work, we analyze the whole-exome sequences of French-Canadian individuals, a founder population with a unique demographic history that includes an original population bottleneck less than 20 generations ago, followed by a demographic explosion, and the whole exomes of French individuals sampled from France. We show that in less than 20 generations of genetic isolation from the French population, the genetic pool of French-Canadians shows reduced levels of diversity, higher homozygosity, and an excess of rare variants with low variant sharing with Europeans. Furthermore, the French-Canadian population contains a larger proportion of putatively damaging functional variants, which could partially explain the increased incidence of genetic disease in the province. Our results highlight the impact of population demography on genetic fitness and the contribution of rare variants to the human genetic variation landscape, emphasizing the need for deep cataloguing of genetic variants by resequencing worldwide human populations in order to truly assess disease risk.