The allelic and haplotypic diversity of the HLA-A, HLA-B, and HLA-C loci was investigated in 852 subjects from five sub-Saharan populations from Kenya (Nandi and Luo), Mali (Dogon), Uganda, and Zambia. Distributions of genotypes at all loci and in all populations fit Hardy-Weinberg equilibrium expectations. There was not a single allele predominant at any of the loci in these populations, with the exception of A*3002 [allele frequency (AF) = 0.233] in Zambians and Cw*1601 (AF = 0.283) in Malians. This distribution was consistent with balancing selection for all class I loci in all populations, which was evidenced by the homozygosity F statistic that was less than that expected under neutrality. Only in the A locus in Zambians and the C locus in Malians, the AF distribution was very close to neutrality expectations. There were six instances in which there were significant deviations of allele distributions from neutrality in the direction of balancing selection. All allelic lineages from each of the class I loci were found in all the African populations. Several alleles of these loci have intermediate frequencies (AF = 0.020-0.150) and seem to appear only in the African populations. Most of these alleles are widely distributed in the African continent and their origin may predate the separation of linguistic groups. In contrast to native American and other populations, the African populations do not seem to show extensive allelic diversification within lineages, with the exception of the groups of alleles A*02, A*30, B*57, and B*58. The alleles of human leukocyte antigen (HLA)-B are in strong linkage disequilibrium (LD) with alleles of the C locus, and the sets of B/C haplotypes are found in several populations. The associations between A alleles with C-blocks are weaker, and only a few A/B/C haplotypes (A*0201-B*4501-Cw*1601; A*2301-B*1503-Cw*0202; A*7401-B* 1503-Cw*0202; A*2902-B*4201-Cw*1701; A*3001-B*4201-Cw*1701; and A*3601-B*5301-Cw*0401) are found in multiple populations with intermediate frequencies [haplotype frequency (HF) = 0.010-0.100]. The strength of the LD associations between alleles of HLA-A and HLA-B loci and those of HLA-B and HLA-C loci was on average of the same or higher magnitude as those observed in other non-African populations for the same pairs of loci. Comparison of the genetic distances measured by the distribution of alleles at the HLA class I loci in the sub-Saharan populations included in this and other studies indicate that the Luo population from western Kenya has the closest distance with virtually all sub-Saharan population so far studied for HLA-A, a finding consistent with the putative origin of modern humans in East Africa. In all African populations, the genetic distances between each other are greater than those observed between European populations. The remarkable current allelic and haplotypic diversity in the HLA system as well as their variable distribution in different sub-Saharan populations is probably the result of evolutionary forces and environments that have acte...

The killer immunoglobulin-like receptor (KIR) gene cluster shows extensive genetic diversity, as do the HLA class I loci, which encode ligands for KIR molecules. We genotyped 1,642 individuals from 30 geographically distinct populations to examine population-level evidence for coevolution of these two functionally related but unlinked gene clusters. We observed strong negative correlations between the presence of activating KIR genes and their corresponding HLA ligand groups across populations, especially KIR3DS1 and its putative HLA-B Bw4-80I ligands (r = -0.66, P = 0.038). In contrast, we observed weak positive relationships between the various inhibitory KIR genes and their ligands. We observed a negative correlation between distance from East Africa and frequency of activating KIR genes and their corresponding ligands, suggesting a balance between selection on HLA and KIR loci. Most KIR-HLA genetic association studies indicate a primary influence of activating KIR-HLA genotypes in disease risk; concomitantly, activating receptor-ligand pairs in this study show the strongest signature of coevolution of these two complex genetic systems as compared with inhibitory receptor-ligand pairs.

summaryThe nature of polymorphism and molecular sequence variation in the genes of the human major histocompatibility complex (MHC) provides strong support for the idea that these genes are under selection. With the understanding that selection shapes MHC variation new questions have become the focus of study. What is the mode of selection that accounts for MHC polymorphism? Is variation maintained by pathogen pressure or by reproductive mechanisms? Discerning between these requires drawing on information from studies on association between HLA genes and infectious diseases, reproductive success and mating preferences relative to HLA genotypes, and theoretical studies that compare the outcomes of different selection regimes. The pattern that has emerged suggests that several types of selection are plausible for the maintenance of HLA polymorphism.

Balancing selection maintains advantageous diversity in populations through various mechanisms. Although extensively explored from a theoretical perspective, an empirical understanding of its prevalence and targets lags behind our knowledge of positive selection. Here, we describe the Non-central Deviation (NCD), a simple yet powerful statistic to detect long-term balancing selection (LTBS) that quantifies how close frequencies are to expectations under LTBS, and provides the basis for a neutrality test. NCD can be applied to a single locus or genomic data, and can be implemented considering only polymorphisms (NCD1) or also considering fixed differences with respect to an outgroup (NCD2) species. Incorporating fixed differences improves power, and NCD2 has higher power to detect LTBS in humans under different frequencies of the balanced allele(s) than other available methods. Applied to genome-wide data from African and European human populations, in both cases using chimpanzee as an outgroup, NCD2 shows that, albeit not prevalent, LTBS affects a sizable portion of the genome: ∼0.6% of analyzed genomic windows and 0.8% of analyzed positions. Significant windows (P < 0.0001) contain 1.6% of SNPs in the genome, which disproportionally fall within exons and change protein sequence, but are not enriched in putatively regulatory sites. These windows overlap ∼8% of the protein-coding genes, and these have larger number of transcripts than expected by chance even after controlling for gene length. Our catalog includes known targets of LTBS but a majority of them (90%) are novel. As expected, immune-related genes are among those with the strongest signatures, although most candidates are involved in other biological functions, suggesting that LTBS potentially influences diverse human phenotypes.

The hypothesis of gene flow between species with large differences in chromosome numbers has rarely been tested in the wild, mainly because species of different ploidy are commonly assumed to be reproductively isolated from each other because of instantaneous and strong postzygotic barriers. In this study, a broad-scale survey of molecular variation was carried out between two orchid species with different ploidy levels: Epidendrum fulgens (2n = 2x = 24 chromosomes) and Epidendrum puniceoluteum (2n = 4x = 52 chromosomes). To test the strength of their reproductive barriers, we investigated the distribution of genetic variation in sympatric and allopatric populations of these two species and conducted crossing experiments. Nuclear and plastid microsatellite loci were used to genotype 463 individuals from eight populations across the geographical range of both species along the Brazilian coastal plain. All six sympatric populations analysed presented hybrid zones, indicating that hybridization between E. fulgens and E. puniceoluteum is a common phenomenon. Bayesian assignment analysis detected the presence of F 1 and F 2 individuals and also signs of introgression, demonstrating a high potential for interspecific gene flow. Introgression occurs preferentially from E. fulgens to E. puniceoluteum. Pure parental individuals of both species display strong genotype-habitat associations, indicating that environment-dependent selection could be acting in all hybrid zones. This study suggests that hybridization and introgression are evolutionary processes playing a role in the diversification of Epidendrum and indicates the importance of investigations of hybrid zones in understanding reproductive barriers and speciation processes in Neotropical orchid species.

Many lines of evidence show that several HLA loci have experienced balancing selection. However, distinguishing among demographic and selective explanations for patterns of variation observed with HLA genes remains a challenge. In this study we address this issue using data from a diverse set of human populations at six classical HLA loci and, employing a comparative genomics approach, contrast results for HLA loci to those for non-HLA markers. Using a variety of analytic methods, we confirm and extend evidence for selection acting on several HLA loci. We find that allele frequency distributions for four of the six HLA loci deviate from neutral expectations and show that this is unlikely to be explained solely by demographic factors. Other features of HLA variation are explained in part by demographic history, including decreased heterozygosity and increased LD for populations at greater distances from Africa and a similar apportionment of genetic variation for HLA loci compared to putatively neutral non-HLA loci. On the basis of contrasts among different HLA loci and between HLA and non-HLA loci, we conclude that HLA loci bear detectable signatures of both natural selection and demographic history.

Software to analyze multi-locus genotype data for entire populations is useful for estimating haplotype frequencies, deviation from Hardy-Weinberg equilibrium and patterns of linkage disequilibrium. These statistical results are important to both those interested in human genome variation and disease predisposition as well as evolutionary genetics. As part of the 13 th International Histocompatibility and Immunogenetics Working Group (IHWG), we have developed a software frame-work (PyPop). The primary novelty of this package is that it allows integration of statistics across large numbers of data-sets by heavily utilizing the XML file format and the R statistical package to view graphical output, while retaining the ability to inter-operate with existing software.

Several decades of research have convincingly shown that classical human leukocyte antigen (HLA) loci bear signatures of natural selection. Despite this conclusion, many questions remain regarding the type of selective regime acting on these loci, the time frame at which selection acts, and the functional connections between genetic variability and natural selection. In this review, we argue that genomic datasets, in particular those generated by next-generation sequencing (NGS) at the population scale, are transforming our understanding of HLA evolution. We show that genomewide data can be used to perform robust and powerful tests for selection, capable of identifying both positive and balancing selection at HLA genes. Importantly, these tests have shown that natural selection can be identified at both recent and ancient timescales. We discuss how findings from genomewide association studies impact the evolutionary study of HLA genes, and how genomic data can be used to survey adaptive change involving interaction at multiple loci. We discuss the methodological developments which are necessary to correctly interpret genomic analyses involving the HLA region. These developments include adapting the NGS analysis framework so as to deal with the highly polymorphic HLA data, as well as developing tools and theory to search for signatures of selection, quantify differentiation, and measure admixture within the HLA region. Finally, we show that high throughput analysis of molecular phenotypes for HLA genes—namely transcription levels—is now a feasible approach and can add another dimension to the study of genetic variation.