Genome-wide Selection Scans Research Articles

Genome-wide scans for footprints of natural selection

Detecting recent selected ‘genomic footprints’ applies directly to the discovery of disease genes and in the imputation of the formative events that molded modern population genetic structure. The imprints of historic selection/adaptation episodes left in human and animal genomes allow one to interpret modern and ancestral gene origins and modifications. Current approaches to reveal selected regions applied in genome-wide selection scans (GWSSs) fall into eight principal categories: (I) phylogenetic footprinting, (II) detecting increased rates of functional mutations, (III) evaluating divergence versus polymorphism, (IV) detecting extended segments of linkage disequilibrium, (V) evaluating local reduction in genetic variation, (VI) detecting changes in the shape of the frequency distribution (spectrum) of genetic variation, (VII) assessing differentiating between populations (FST), and (VIII) detecting excess or decrease in admixture contribution from one population. Here, we review and compare these approaches using available human genome-wide datasets to provide independent verification (or not) of regions found by different methods and using different populations. The lessons learned from GWSSs will be applied to identify genome signatures of historic selective pressures on genes and gene regions in other species with emerging genome sequences. This would offer considerable potential for genome annotation in functional, developmental and evolutionary contexts.

Tracking footprints of artificial selection in the dog genome

The size, shape, and behavior of the modern domesticated dog has been sculpted by artificial selection for at least 14,000 years. The genetic substrates of selective breeding, however, remain largely unknown. Here, we describe a genome-wide scan for selection in 275 dogs from 10 phenotypically diverse breeds that were genotyped for over 21,000 autosomal SNPs. We identified 155 genomic regions that possess strong signatures of recent selection and contain candidate genes for phenotypes that vary most conspicuously among breeds, including size, coat color and texture, behavior, skeletal morphology, and physiology. In addition, we demonstrate a significant association between HAS2 and skin wrinkling in the Shar-Pei, and provide evidence that regulatory evolution has played a prominent role in the phenotypic diversification of modern dog breeds. Our results provide a first-generation map of selection in the dog, illustrate how such maps can rapidly inform the genetic basis of canine phenotypic variation, and provide a framework for delineating the mechanistic basis of how artificial selection promotes rapid and pronounced phenotypic evolution.

From evolutionary genetics to human immunology: how selection shapes host defence genes

Pathogens have always been a major cause of human mortality, so they impose strong selective pressure on the human genome. Data from population genetic studies, including genome-wide scans for selection, are providing important insights into how natural selection has shaped immunity and host defence genes in specific human populations and in the human species as a whole. These findings are helping to delineate genes that are important for host defence and to increase our understanding of how past selection has had an impact on disease susceptibility in modern populations. A tighter integration between population genetic studies and immunological phenotype studies is now necessary to reveal the mechanisms that have been crucial for our past and present survival against infection.

Constructing genomic maps of positive selection in humans: Where do we go from here?

Identifying targets of positive selection in humans has, until recently, been frustratingly slow, relying on the analysis of individual candidate genes. Genomics, however, has provided the necessary resources to systematically interrogate the entire genome for signatures of natural selection. To date, 21 genome-wide scans for recent or ongoing positive selection have been performed in humans. A key challenge is to begin synthesizing these newly constructed maps of positive selection into a coherent narrative of human evolutionary history and derive a deeper mechanistic understanding of how natural populations evolve. Here, I chronicle the recent history of the burgeoning field of human population genomics, critically assess genome-wide scans for positive selection in humans, identify important gaps in knowledge, and discuss both short- and long-term strategies for traversing the path from the low-resolution, incomplete, and error-prone maps of selection today to the ultimate goal of a detailed molecular, mechanistic, phenotypic, and population genetics characterization of adaptive alleles.

Signals of recent positive selection in a worldwide sample of human populations

Genome-wide scans for recent positive selection in humans have yielded insight into the mechanisms underlying the extensive phenotypic diversity in our species, but have focused on a limited number of populations. Here, we present an analysis of recent selection in a global sample of 53 populations, using genotype data from the Human Genome Diversity-CEPH Panel. We refine the geographic distributions of known selective sweeps, and find extensive overlap between these distributions for populations in the same continental region but limited overlap between populations outside these groupings. We present several examples of previously unrecognized candidate targets of selection, including signals at a number of genes in the NRG-ERBB4 developmental pathway in non-African populations. Analysis of recently identified genes involved in complex diseases suggests that there has been selection on loci involved in susceptibility to type II diabetes. Finally, we search for local adaptation between geographically close populations, and highlight several examples.

Population Genomic Analysis of ALMS1 in Humans Reveals a Surprisingly Complex Evolutionary History

Mutations in the human gene ALMS1 result in Alström Syndrome, which presents with early childhood obesity and insulin resistance leading to Type 2 diabetes. Previous genomewide scans for selection in the HapMap data based on linkage disequilibrium and population structure suggest that ALMS1 was subject to recent positive selection. Through a detailed population genomic analysis of existing genomewide data sets and new resequencing data obtained in geographically diverse populations, we find that the signature of selection at ALMS1 is considerably more complex than what would be expected for an idealized model of a selective sweep acting on a newly arisen advantageous mutation. Specifically, we observed three highly divergent and globally dispersed haplogroups, two of which carry a set of seven derived nonsynonymous single nucleotide polymorphisms that are nearly fixed in Asian populations. Our data suggest that the interaction of human demographic history and positive selection on standing variation in Eurasian populations approximately 15 thousand years ago parsimoniously explains the spectrum of extant ALMS1 variation. These results provide new insights into the evolutionary history of ALMS1 in humans and suggest that selective events identified in genomewide scans may be more complex than currently appreciated.

Controlling Type-I Error of the McDonald–Kreitman Test in Genomewide Scans for Selection on Noncoding DNA

Departures from the assumption of homogenously interdigitated neutral and putatively selected sites in the McDonald-Kreitman test can lead to false rejections of the neutral model in the presence of intermediate levels of recombination. This problem is exacerbated by small sample sizes, nonequilibrium demography, recombination rate variation, and in comparisons involving more recently diverged species. I propose that establishing significance levels by coalescent simulation with recombination can improve the fidelity of the test in genomewide scans for selection on noncoding DNA.

Positive Selection in East Asians for an EDAR Allele that Enhances NF-κB Activation

Genome-wide scans for positive selection in humans provide a promising approach to establish links between genetic variants and adaptive phenotypes. From this approach, lists of hundreds of candidate genomic regions for positive selection have been assembled. These candidate regions are expected to contain variants that contribute to adaptive phenotypes, but few of these regions have been associated with phenotypic effects. Here we present evidence that a derived nonsynonymous substitution (370A) in EDAR, a gene involved in ectodermal development, was driven to high frequency in East Asia by positive selection prior to 10,000 years ago. With an in vitro transfection assay, we demonstrate that 370A enhances NF-κB activity. Our results suggest that 370A is a positively selected functional genetic variant that underlies an adaptive human phenotype.

Gene Flow and Natural Selection in Oceanic Human Populations Inferred from Genome-Wide SNP Typing

It is suggested that the major prehistoric human colonizations of Oceania occurred twice, namely, about 50,000 and 4,000 years ago. The first settlers are considered as ancestors of indigenous people in New Guinea and Australia. The second settlers are Austronesian-speaking people who dispersed by voyaging in the Pacific Ocean. In this study, we performed genome-wide single-nucleotide polymorphism (SNP) typing on an indigenous Melanesian (Papuan) population, Gidra, and a Polynesian population, Tongans, by using the Affymetrix 500K assay. The SNP data were analyzed together with the data of the HapMap samples provided by Affymetrix. In agreement with previous studies, our phylogenetic analysis indicated that indigenous Melanesians are genetically closer to Asians than to Africans and European Americans. Population structure analyses revealed that the Tongan population is genetically originated from Asians at 70% and indigenous Melanesians at 30%, which thus supports the so-called Slow train model. We also applied the SNP data to genome-wide scans for positive selection by examining haplotypic variation and identified many candidates of locally selected genes. Providing a clue to understand human adaptation to environments, our approach based on evolutionary genetics must contribute to revealing unknown gene functions as well as functional differences between alleles. Conversely, this approach can also shed some light onto the invisible phenotypic differences between populations.

Genomic signatures of positive selection in humans and the limits of outlier approaches

Identifying regions of the human genome that have been targets of positive selection will provide important insights into recent human evolutionary history and may facilitate the search for complex disease genes. However, the confounding effects of population demographic history and selection on patterns of genetic variation complicate inferences of selection when a small number of loci are studied. To this end, identifying outlier loci from empirical genome-wide distributions of genetic variation is a promising strategy to detect targets of selection. Here, we evaluate the power and efficiency of a simple outlier approach and describe a genome-wide scan for positive selection using a dense catalog of 1.58 million SNPs that were genotyped in three human populations. In total, we analyzed 14,589 genes, 385 of which possess patterns of genetic variation consistent with the hypothesis of positive selection. Furthermore, several extended genomic regions were found, spanning >500 kb, that contained multiple contiguous candidate selection genes. More generally, these data provide important practical insights into the limits of outlier approaches in genome-wide scans for selection, provide strong candidate selection genes to study in greater detail, and may have important implications for disease related research.

Multilocus patterns of nucleotide variability and the demographic and selection history of Drosophila melanogaster populations

Uncertainty about the demographic history of populations can hamper genome-wide scans for selection based on population genetic models. To obtain a portrait of the effects of demographic history on genome variability patterns in Drosophila melanogaster populations, we surveyed noncoding DNA polymorphism at 10 X-linked loci in large samples from three African and two non-African populations. All five populations show significant departures from expectations under the standard neutral model. We detect weak but significant differentiation between East (Kenya and Zimbabwe) and West/Central sub-Saharan (Gabon) African populations. A skew toward high-frequency-derived polymorphisms, elevated levels of linkage disequilibrium (LD) and significant heterogeneity in levels of polymorphism and divergence in the Gabon sample suggest that this population is further from mutation-drift equilibrium than the two Eastern African populations. Both non-African populations harbor significantly higher levels of LD, a large excess of high-frequency-derived mutations and extreme heterogeneity among loci in levels of polymorphism and divergence. Rejections of the neutral model in D. melanogaster populations using these and similar features have been interpreted as evidence for an important role for natural selection in shaping genome variability patterns. Based on simulations, we conclude that simple bottleneck models are sufficient to account for most, if not all, polymorphism features of both African and non-African populations. In contrast, we show that a steady-state recurrent hitchhiking model fails to account for several aspects of the data. Demographic departures from equilibrium expectations in both ancestral and derived populations thus represent a serious challenge to detecting positive selection in genome-wide scans using current methodologies.

Genome-wide scans for loci under selection in humans.

Natural selection, which can be defined as the differential contribution of genetic variants to future generations, is the driving force of Darwinian evolution. Identifying regions of the human genome that have been targets of natural selection is an important step in clarifying human evolutionary history and understanding how genetic variation results in phenotypic diversity, it may also facilitate the search for complex disease genes. Technological advances in high-throughput DNA sequencing and single nucleotide polymorphism genotyping have enabled several genome-wide scans of natural selection to be undertaken. Here, some of the observations that are beginning to emerge from these studies will be reviewed, including evidence for geographically restricted selective pressures (ie local adaptation) and a relationship between genes subject to natural selection and human disease. In addition, the paper will highlight several important problems that need to be addressed in future genome-wide studies of natural selection.