A sequence-based approach demonstrates that balancing selection in classical human leukocyte antigen (HLA) loci is asymmetric

A novel expectation-maximization approach to infer general diploid selection from time-series genetic data

Detecting and quantifying the strength of selection is a main objective in population genetics. Since selection acts over multiple generations, many approaches have been developed to detect and quantify selection using genetic data sampled at multiple points in time. Such time series genetic data is commonly analyzed using Hidden Markov Models, but in most cases, under the assumption of additive selection. However, many examples of genetic variation exhibiting non-additive mechanisms exist, making it critical to develop methods that can characterize selection in more general scenarios. Thus, we extend a previously introduced expectation-maximization algorithm for the inference of additive selection coefficients to the case of general diploid selection, in which the heterozygote and homozygote fitness are parameterized independently. We furthermore introduce a framework to identify bespoke modes of diploid selection from given data, as well as a procedure for aggregating data across linked loci to increase power and robustness. Using extensive simulation studies, we find that our method accurately and efficiently estimates selection coefficients for different modes of diploid selection across a wide range of scenarios; however, power to classify the mode of selection is low unless selection is very strong. We apply our method to ancient DNA samples from Great Britain in the last 4,450 years, and detect evidence for selection in six genomic regions, including the well-characterized LCT locus. Our work is the first genome-wide scan characterizing signals of general diploid selection.

Genetic history of Cambridgeshire before and after the Black Death

The extent of the devastation of the Black Death pandemic (1346-1353) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at the local scale. Here, we report 275 ancient genomes, including 109 with coverage >0.1×, from later medieval and postmedieval Cambridgeshire of individuals buried before and after the Black Death. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. While we detect long-term shifts in local genetic ancestry in Cambridgeshire, we find no evidence of major changes in genetic ancestry nor higher differentiation of immune loci between cohorts living before and after the Black Death.

Joint estimation of selection intensity and mutation rate under balancing selection with applications to HLA

A composite likelihood method is introduced for jointly estimating the intensity of selection and the rate of mutation, both scaled by the effective population size, when there is balancing selection at a single multi-allelic locus in an isolated population at demographic equilibrium. The performance of the method is tested using simulated data. Average estimated mutation rates and selection intensities are close to the true values but there is considerable variation about the averages. Allowing for both population growth and population subdivision does not result in qualitative differences but the estimated mutation rates and selection intensities do not in general reflect the current effective population size. The method is applied to three class I (HLA-A, HLA-B and HLA-C) and two class II loci (HLA-DRB1 and HLA-DQA1) in the 1000 Genomes populations. Allowing for asymmetric balancing selection has only a slight effect on the results from the symmetric model. Mutations that restore symmetry of the selection model are preferentially retained because of the tendency of natural selection to maximize average fitness. However, slight differences in selective effects result in much longer persistence time of some alleles. Trans-species polymorphism (TSP), which is characteristic of major-histocompatibility loci in vertebrates, is more likely when there are small differences in allelic fitness than when complete symmetry is assumed. Therefore, variation in allelic fitness expands the range of parameter values consistent with observations of TSP.

Similar patterns of genetic diversity and linkage disequilibrium in Western chimpanzees (Pan troglodytes verus) and humans indicate highly conserved mechanisms of MHC molecular evolution

BACKGROUND

Many species are threatened with extinction as their population sizes decrease with changing environments or face novel pathogenic threats. A reduction of genetic diversity at major histocompatibility complex (MHC) genes may have dramatic effects on populations' survival, as these genes play a key role in adaptive immunity. This might be the case for chimpanzees, the MHC genes of which reveal signatures of an ancient selective sweep likely due to a viral epidemic that reduced their population size a few million years ago. To better assess how this past event affected MHC variation in chimpanzees compared to humans, we analysed several indexes of genetic diversity and linkage disequilibrium across seven MHC genes on four cohorts of chimpanzees and we compared them to those estimated at orthologous HLA genes in a large set of human populations.

RESULTS

Interestingly, the analyses uncovered similar patterns of both molecular diversity and linkage disequilibrium across the seven MHC genes in chimpanzees and humans. Indeed, in both species the greatest allelic richness and heterozygosity were found at loci A, B, C and DRB1, the greatest nucleotide diversity at loci DRB1, DQA1 and DQB1, and both significant global linkage disequilibrium and the greatest proportions of haplotypes in linkage disequilibrium were observed at pairs DQA1 ~ DQB1, DQA1 ~ DRB1, DQB1 ~ DRB1 and B ~ C. Our results also showed that, despite some differences among loci, the levels of genetic diversity and linkage disequilibrium observed in contemporary chimpanzees were globally similar to those estimated in small isolated human populations, in contrast to significant differences compared to large populations.

CONCLUSIONS

We conclude, first, that highly conserved mechanisms shaped the diversity of orthologous MHC genes in chimpanzees and humans. Furthermore, our findings support the hypothesis that an ancient demographic decline affecting the chimpanzee populations - like that ascribed to a viral epidemic - exerted a substantial effect on the molecular diversity of their MHC genes, albeit not more pronounced than that experienced by HLA genes in human populations that underwent rapid genetic drift during humans' peopling history. We thus propose a model where chimpanzees' MHC genes regenerated molecular variation through recombination/gene conversion and/or balancing selection after the selective sweep.

Learning the properties of adaptive regions with functional data analysis

Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.

Fine-Scale Inference of Ancestry Segments Without Prior Knowledge of Admixing Groups

We present an algorithm for inferring ancestry segments and characterizing admixture events, which involve an arbitrary number of genetically differentiated groups coming together. This allows inference of the demographic history of the species, properties of admixing groups, identification of signatures of natural selection, and may aid disease gene mapping. The algorithm employs nested hidden Markov models to obtain local ancestry estimation along the genome for each admixed individual. In a range of simulations, the accuracy of these estimates equals or exceeds leading existing methods. Moreover, and unlike these approaches, we do not require any prior knowledge of the relationship between subgroups of donor reference haplotypes and the unseen mixing ancestral populations. Our approach infers these in terms of conditional "copying probabilities." In application to the Human Genome Diversity Project, we corroborate many previously inferred admixture events (e.g., an ancient admixture event in the Kalash). We further identify novel events such as complex four-way admixture in San-Khomani individuals, and show that Eastern European populations possess [Formula: see text] ancestry from a group resembling modern-day central Asians. We also identify evidence of recent natural selection favoring sub-Saharan ancestry at the human leukocyte antigen (HLA) region, across North African individuals. We make available an R and C++ software library, which we term MOSAIC (which stands for MOSAIC Organizes Segments of Ancestry In Chromosomes).

Multiplicative fitness, rapid haplotype discovery, and fitness decay explain evolution of human MHC

The major histocompatibility complex (MHC) is a central component of the vertebrate immune system and hence evolves in the regime of a host-pathogen evolutionary race. The MHC is associated with quantitative traits which directly affect fitness and are subject to selection pressure. The evolution of haplotypes at the MHC HLA (HLA) locus is generally thought to be governed by selection for increased diversity that is manifested in overdominance and/or negative frequency-dependent selection (FDS). However, recently, a model combining purifying selection on haplotypes and balancing selection on alleles has been proposed. We compare the predictions of several population dynamics models of haplotype frequency evolution to the distributions derived from 6.59-million-donor HLA typings from the National Marrow Donor Program registry. We show that models that combine a multiplicative fitness function, extremely high haplotype discovery rates, and exponential fitness decay over time produce the best fit to the data for most of the analyzed populations. In contrast, overdominance is not supported, and population substructure does not explain the observed haplotype frequencies. Furthermore, there is no evidence of negative FDS. Thus, multiplicative fitness, rapid haplotype discovery, and rapid fitness decay appear to be the major factors shaping the HLA haplotype frequency distribution in the human population.

Divergent Allele Advantage Provides a Quantitative Model for Maintaining Alleles with a Wide Range of Intrinsic Merits

The Major Histocompatibility Complex (MHC) is the most genetically diverse region of the genome in most vertebrates. Some form of balancing selection is necessary to account for the extreme diversity, but the precise mechanism of balancing selection is unknown. Due to the way MHC molecules determine immune recognition, overdominance (also referred to as heterozygote advantage) has been suggested as the main driving force behind this unrivalled diversity. However, both theoretical results and simulation models have shown that overdominance in its classical form cannot maintain large numbers of alleles unless all alleles confer unrealistically similar levels of fitness. There is increasing evidence that heterozygotes containing genetically divergent alleles allow for broader antigen presentation to immune cells, providing a selective mechanism for MHC polymorphism. By framing competing models of overdominance within a general framework, we show that a model based on Divergent Allele Advantage (DAA) provides a superior mechanism for maintaining alleles with a wide range of intrinsic merits, as intrinsically less-fit MHC alleles that are more divergent can survive under DAA. Specifically, our results demonstrate that a quantitative mechanism built from the DAA hypothesis is able to maintain polymorphism in the MHC. Applying such a model to both livestock breeding and conservation could provide a better way of identifying superior heterozygotes, and quantifying the advantages of genetic diversity at the MHC.

Tissue-Specific Differential Expression of Novel Genes and Long Intergenic Noncoding RNAs in Humans With Extreme Response to Evoked Endotoxemia

BACKGROUND

Cytokine responses to activation of innate immunity differ between individuals, yet the genomic and tissue-specific transcriptomic determinants of inflammatory responsiveness are not well understood. We hypothesized that tissue-specific mRNA and long intergenic noncoding RNA (lincRNA) induction differs between individuals with divergent evoked inflammatory responses.

METHODS

In the GENE Study (Genetics of Evoked Response to Niacin and Endotoxemia), we performed an inpatient endotoxin challenge (1 ng/kg lipopolysaccharide [LPS]) in healthy humans. We selected individuals in the top (high responders) and bottom (low responders) extremes of inflammatory responses and applied RNA sequencing to CD14 monocytes (N=15) and adipose tissue (N=25) before and after LPS administration.

RESULTS

Although only a small number of genes were differentially expressed at baseline, there were clear differences in the magnitude of the transcriptional response post-LPS between high and low responders, with a far greater number of genes differentially expressed by endotoxemia in high responders. Furthermore, tissue responses differed during inflammation, and we found a number of tissue-specific differentially expressed lincRNAs post-LPS, which we validated. Relative to nondifferentially expressed lincRNAs, differentially expressed lincRNAs were equally likely to be nonconserved as conserved between human and mouse, indicating that conservation is not a predictor of lincRNAs associated with human inflammatory pathophysiology. Differentially expressed genes also were enriched for signals with inflammatory and cardiometabolic disease in published genome-wide association studies. CTB-41I6.2 ( AC002091.1), a nonconserved human-specific lincRNA, is one of the top lincRNAs regulated by endotoxemia in monocytes, but not in adipose tissue. Knockdown experiments in THP-1 monocytes suggest that this lincRNA enhances LPS-induced interleukin 6 ( IL6) expression in monocytes, and we now refer to this as monocyte LPS-induced lincRNA regulator of IL6 ( MOLRIL6).

CONCLUSIONS

We highlight mRNAs and lincRNAs that represent novel candidates for modulation of innate immune and metabolic responses in humans.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov . Unique identifier: NCT00953667.

HLA Population Genetics in Solid Organ Transplantation

HLAs are fundamental to the adaptive immune response and play critical roles in the cellular and humoral response in solid organ transplantation. The genes encoding HLA proteins are the most polymorphic within the human genome, with thousands of different allelic variants known within the population. Application of the principles of population genetics to the HLA genes has resulted in the development of a numeric metric, the calculated panel-reactive antibody (CPRA) that predicts the likelihood of a positive crossmatch as a function of a transplant candidate's unacceptable HLA antigens. The CPRA is an indispensible measure of access to transplantation for sensitized candidates and is used as the official measure of sensitization for allocation of points in the US Kidney Allocation System and Eurotransplant. Here, we review HLA population genetics and detail the mathematical basis of the CPRA. An understanding of these principles by transplant clinicians will lay the foundation for continued innovation in the care of sensitized patients.

HLA class I haplotype diversity is consistent with selection for frequent existing haplotypes

The major histocompatibility complex (MHC) contains the most polymorphic genetic system in humans, the human leukocyte antigen (HLA) genes of the adaptive immune system. High allelic diversity in HLA is argued to be maintained by balancing selection, such as negative frequency-dependent selection or heterozygote advantage. Selective pressure against immune escape by pathogens can maintain appreciable frequencies of many different HLA alleles. The selection pressures operating on combinations of HLA alleles across loci, or haplotypes, have not been extensively evaluated since the high HLA polymorphism necessitates very large sample sizes, which have not been available until recently. We aimed to evaluate the effect of selection operating at the HLA haplotype level by analyzing HLA A~C~B~DRB1~DQB1 haplotype frequencies derived from over six million individuals genotyped by the National Marrow Donor Program registry. In contrast with alleles, HLA haplotype diversity patterns suggest purifying selection, as certain HLA allele combinations co-occur in high linkage disequilibrium. Linkage disequilibrium is positive (D_ij'>0) among frequent haplotypes and negative (D_ij'<0) among rare haplotypes. Fitting the haplotype frequency distribution to several population dynamics models, we found that the best fit was obtained when significant positive frequency-dependent selection (FDS) was incorporated. Finally, the Ewens-Watterson test of homozygosity showed excess homozygosity for 5-locus haplotypes within 23 US populations studied, with an average Fnd of 28.43. Haplotype diversity is most consistent with purifying selection for HLA Class I haplotypes (HLA-A, -B, -C), and was not inferred for HLA Class II haplotypes (-DRB1 and—DQB1). We discuss our empirical results in the context of evolutionary theory, exploring potential mechanisms of selection that maintain high linkage disequilibrium in MHC haplotype blocks.

The adaptive immune system presents antigens derived from pathogenic and normal self proteins on the cell surface using human leukocyte antigen (HLA) molecules. The HLA loci coding for these molecules are found in major histocompatibility complex (MHC) region, the most polymorphic region in the human genome, with over 15,000 HLA alleles observed so far in the world population. A high frequency of many different HLA alleles is thought be sustained by balancing selection. New HLA alleles may have an advantage over existing frequent alleles since immune escape mutations in pathogens within a population are maintained primarily in epitopes presented on frequent HLA alleles. Host immune function is not determined by single HLA alleles, but by both copies of autosomal HLA genes together (genotypes). Complementarity in function across the two potentially-variant copies of HLA at each locus can result in overdominance and heterozygote advantage at the genotype level. Less explored are selection mechanisms that may be operating across combinations of HLA alleles across loci (haplotypes). Indeed, in addition to high allelic diversity, HLA also has distinctive patterns of haplotype diversity, as certain HLA alleles co-occur in high linkage disequilibrium across five classical HLA loci (HLA-A, -B, -C, -DRB1, -DQB1). We applied multiple population genetic models to a dataset of HLA haplotype frequencies derived from over six million individuals with the goal of determining what type of selection may impact HLA haplotype diversity. We found frequent haplotypes were preferentially maintained in the population across 23 US populations studied. Thus, balancing selection at the allele level and purifying selection at the haplotype level may together affect HLA diversity in human populations.

Determination of HLA-A, -B, and -DRB1 Allele and Haplotype Frequencies in the Croatian Population Based on a Family Study

In the present study, HLA allele and haplotype frequencies among Croatian families were investigated to evaluate valuable information about HLA genotypes and to compare them with data from the Croatian Bone Marrow Donor Registry (CBMDR). A total of 350 families which have been typed for the purpose of HSCT were included. All individuals were tested using PCR-SSO or PCR-SSP methods for HLA-A, -B, and -DRB1 alleles. The HLA-A-B-DRB1 haplotypes were determined by segregation and directly counted. A total of 30 HLA-A, 54 HLA-B, and 38 HLA-DRB1 alleles and 716 different HLA-A-B-DRB1 haplotypes were identified. Of these, the three most frequent alleles at HLA-A, -B, and -DRB1 loci, respectively, were A*02:01 (30.39%), A*11:01 (13.37%), A*24:02 (10.91%); B*51:01 (12.48%), B*18:01 (8.35%), B*08:01 (8.06%); DRB1*03:01 (11.20%), DRB1*01:01 (9.84%), DRB1*16:01 (9.63%). The following HLA alleles were detected only once: A*02:09, A*24:03, A*24:04, A*24:07; B*07:04, B*15:07, B*15:08, B*39:04, B*39:10, B*39:24, B*40:04; DRB1*08:03, DRB1*11:06, DRB1*13:32, DRB1*14:05. Five most frequent haplotypes were: A*01:01-B*08:01-DRB1*03:01 (5.34%), A*02:01-B*18:01-DRB1*11:04 (1.57%), A*02:01-B*27:02-DRB1*16:01 (1.50%), A*02:01-B*27:05-DRB1*01:01 (1.42%) and A*02:01-B*44:02:01G-DRB1*16:01 (1.28%). The haplotype frequencies based on the family study were compared with the frequencies from CBMDR, and similar results were obtained for all except for the HLA-A*26:01-B*38:01-DRB1*04:02 haplotype. A significantly higher frequency (P = 0.0017) of this haplotype was observed among family individuals. Nine haplotypes were unique and data about their frequencies do not exist in current databases. The data obtained in this study could be useful for anthropology, transplantation and disease association studies.

Understanding rare and common diseases in the context of human evolution

The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.

HLA class I molecular variation and peptide-binding properties suggest a model of joint divergent asymmetric selection

The main function of HLA class I molecules is to present pathogen-derived peptides to cytotoxic T lymphocytes. This function is assumed to drive the maintenance of an extraordinary amount of polymorphism at each HLA locus, providing an immune advantage to heterozygote individuals capable to present larger repertories of peptides than homozygotes. This seems contradictory, however, with a reduced diversity at individual HLA loci exhibited by some isolated populations. This study shows that the level of functional diversity predicted for the two HLA-A and HLA-B genes considered simultaneously is similar (almost invariant) between 46 human populations, even when a reduced diversity exists at each locus. We thus propose that HLA-A and HLA-B evolved through a model of joint divergent asymmetric selection conferring all populations an equivalent immune potential. The distinct pattern observed for HLA-C is explained by its functional evolution towards killer cell immunoglobulin-like receptor (KIR) activity regulation rather than peptide presentation.

A limit to the divergent allele advantage model supported by variable pathogen recognition across HLA-DRB1 allele lineages

Genetic diversity in human leukocyte antigen (HLA) molecules is thought to have arisen from the co-evolution between host and pathogen and maintained by balancing selection. Heterozygote advantage is a common proposed scenario for maintaining high levels of diversity in HLA genes, and extending from this, the divergent allele advantage (DAA) model suggests that individuals with more divergent HLA alleles bind and recognize a wider array of antigens. While the DAA model seems biologically suitable for driving HLA diversity, there is likely an upper threshold to the amount of sequence divergence. We used peptide-binding and pathogen-recognition capacity of DRB1 alleles as a model to further explore the DAA model; within the DRB1 locus, we examined binding predictions based on two distinct phylogenetic groups (denoted group A and B) previously identified based on non-peptide-binding region (PBR) nucleotide sequences. Predictions in this study support that group A allele and group B allele lineages have contrasting binding/recognition capacity, with only the latter supporting the DAA model. Furthermore, computer simulations revealed an inconsistency in the DAA model alone with observed extent of polymorphisms, supporting that the DAA model could only work effectively in combination with other mechanisms. Overall, we support that the mechanisms driving HLA diversity are non-exclusive. By investigating the relationships among HLA alleles, and pathogens recognized, we can provide further insights into the mechanisms on how humans have adapted to infectious diseases over time.

Nonfrequent but well-documented, rare and very rare HLA alleles observed in the Croatian population

The aim of the study was to evaluate the presence of nonfrequent, rare and very rare alleles among Croats and to estimate whether they are associated with specific alleles at other human leukocyte antigen (HLA) loci. This retrospective study included the typing results from the last 10 years; total number of individuals included was approximately 45,000. Among 17 alleles so far observed only once in our population, 6 (A*24:41, B*07:02:28, B*35:03:03, B*39:40N, DRB1*13:23 and DRB1*14:111) belong to very rare alleles, 2 (B*44:16 and DRB1*01:31) belong to rare alleles according to the 'Rare Alleles Detector' tool ( www.allelefrequencies.net), while for the B*35:101:01 allele published data exist only in the IMGT/HLA database. The remaining eight HLA alleles observed only once among Croats are considered as frequent according to the 'Rare Alleles Detector'. Those 17 HLA alleles are not declared as common well defined (CWD) alleles in the CWD allele catalogue 2.0.0. Haplotype analysis of nonfrequent alleles detected in our sample supports the idea that different populations, although similar in some aspects regarding HLA allele and haplotype distribution, still have some unique characteristics. This is the case for A*01:02, B*39:10 and DRB1*13:32 which form haplotypes unreported to date among our subjects.

Advantageous diversity maintained by balancing selection in humans

Most human polymorphisms are neutral or slightly deleterious, but some genetic variation is advantageous and maintained in populations by balancing selection. Considered a rarity and overlooked for years, balanced polymorphisms have recently received renewed attention with several lines of evidence showing their relevance in human evolution. From theoretical work on its role in adaptation to empirical studies that identify its targets, recent developments have showed that balancing selection is more prevalent than previously thought. Here we review these developments and discuss their implications in our understanding of the influence of balancing selection in human evolution. We also review existing evidence on the biological functions that benefit most from advantageous diversity, and the functional consequences of these variants. Overall, we argue that balancing selection must be considered an important selective force in human evolution.