Multiple instances of ancient balancing selection shared between humans and chimpanzees

Studying models of balancing selection using phase-type theory

Balancing selection (BLS) is the evolutionary force that maintains high levels of genetic variability in many important genes. To further our understanding of its evolutionary significance, we analyze models with BLS acting on a biallelic locus: an equilibrium model with long-term BLS, a model with long-term BLS and recent changes in population size, and a model of recent BLS. Using phase-type theory, a mathematical tool for analyzing continuous time Markov chains with an absorbing state, we examine how BLS affects polymorphism patterns in linked neutral regions, as summarized by nucleotide diversity, the expected number of segregating sites, the site frequency spectrum, and the level of linkage disequilibrium (LD). Long-term BLS affects polymorphism patterns in a relatively small genomic neighborhood, and such selection targets are easier to detect when the equilibrium frequencies of the selected variants are close to 50%, or when there has been a population size reduction. For a new mutation subject to BLS, its initial increase in frequency in the population causes linked neutral regions to have reduced diversity, an excess of both high and low frequency derived variants, and elevated LD with the selected locus. These patterns are similar to those produced by selective sweeps, but the effects of recent BLS are weaker. Nonetheless, compared to selective sweeps, nonequilibrium polymorphism and LD patterns persist for a much longer period under recent BLS, which may increase the chance of detecting such selection targets. An R package for analyzing these models, among others (e.g., isolation with migration), is available.

Three Signatures of Adaptive Polymorphism Exemplified by Malaria-Associated Genes

Malaria has been one of the strongest selective pressures on our species. Many of the best-characterized cases of adaptive evolution in humans are in genes tied to malaria resistance. However, the complex evolutionary patterns at these genes are poorly captured by standard scans for nonneutral evolution. Here, we present three new statistical tests for selection based on population genetic patterns that are observed more than once among key malaria resistance loci. We assess these tests using forward-time evolutionary simulations and apply them to global whole-genome sequencing data from humans, and thus we show that they are effective at distinguishing selection from neutrality. Each test captures a distinct evolutionary pattern, here called Divergent Haplotypes, Repeated Shifts, and Arrested Sweeps, associated with a particular period of human prehistory. We clarify the selective signatures at known malaria-relevant genes and identify additional genes showing similar adaptive evolutionary patterns. Among our top outliers, we see a particular enrichment for genes involved in erythropoiesis and for genes previously associated with malaria resistance, consistent with a major role for malaria in shaping these patterns of genetic diversity. Polymorphisms at these genes are likely to impact resistance to malaria infection and contribute to ongoing host-parasite coevolutionary dynamics.

Distinguishing between recent balancing selection and incomplete sweep using deep neural networks

Balancing selection is an important adaptive mechanism underpinning a wide range of phenotypes. Despite its relevance, the detection of recent balancing selection from genomic data is challenging as its signatures are qualitatively similar to those left by ongoing positive selection. In this study, we developed and implemented two deep neural networks and tested their performance to predict loci under recent selection, either due to balancing selection or incomplete sweep, from population genomic data. Specifically, we generated forward-in-time simulations to train and test an artificial neural network (ANN) and a convolutional neural network (CNN). ANN received as input multiple summary statistics calculated on the locus of interest, while CNN was applied directly on the matrix of haplotypes. We found that both architectures have high accuracy to identify loci under recent selection. CNN generally outperformed ANN to distinguish between signals of balancing selection and incomplete sweep and was less affected by incorrect training data. We deployed both trained networks on neutral genomic regions in European populations and demonstrated a lower false-positive rate for CNN than ANN. We finally deployed CNN within the MEFV gene region and identified several common variants predicted to be under incomplete sweep in a European population. Notably, two of these variants are functional changes and could modulate susceptibility to familial Mediterranean fever, possibly as a consequence of past adaptation to pathogens. In conclusion, deep neural networks were able to characterize signals of selection on intermediate frequency variants, an analysis currently inaccessible by commonly used strategies.

The inflated significance of neutral genetic diversity in conservation genetics

The current rate of species extinction is rapidly approaching unprecedented highs, and life on Earth presently faces a sixth mass extinction event driven by anthropogenic activity, climate change, and ecological collapse. The field of conservation genetics aims at preserving species by using their levels of genetic diversity, usually measured as neutral genome-wide diversity, as a barometer for evaluating population health and extinction risk. A fundamental assumption is that higher levels of genetic diversity lead to an increase in fitness and long-term survival of a species. Here, we argue against the perceived importance of neutral genetic diversity for the conservation of wild populations and species. We demonstrate that no simple general relationship exists between neutral genetic diversity and the risk of species extinction. Instead, a better understanding of the properties of functional genetic diversity, demographic history, and ecological relationships is necessary for developing and implementing effective conservation genetic strategies.

Transcriptome-wide analysis of introgression-resistant regions reveals genetic divergence genes under positive selection in Populus trichocarpa

Comparing gene expression patterns and genetic polymorphisms between populations is of central importance for understanding the origin and maintenance of biodiversity. Based on population-specific gene expression levels and allele frequency differences, we sought to identify population divergence (PD) genes across the introgression-resistant genomic regions of Populus trichocarpa. Genes containing highly diverged loci [i.e., genetic divergence (GD)] or showing expression divergence (ED) between populations were widely distributed in the genome and substantially enriched in functional categories related to stress responses, disease resistance, timing of flowering, cell cycle regulation, plant growth, and development. Nine genomic regions showing evidence of strong positive selection were overlapped with GD genes, which had significant differences between Oregon (a southernmost peripheral deme) and the other demes. However, we did not find evidence that genes under positive selection show an enrichment for ED. PD genes and genes under selection pertained to the same gene classes, such as SERINE/CYSTEINE PROTEASE, ABC TRANSPORTER, GLYCOSYLTRANSFERASE and other transferases. Our analysis also revealed that GD genes were polymorphic within the species (41.9 ± 3.66 biallelic variants per gene), as previously reported in herbaceous plants. By contrast, ED genes contained less genetic variants (10.73 ± 1.14) and were likely highly expressed. In addition, we found that trans- rather than cis-acting variants considerably contribute to the evolution of >90% PD genes. Overall, this study elucidates that cohorts of PD genes agree with the general attributes of known speciation genes and GD genes will provide substrates for positive selection to operate on.

An atlas of CNV maps in cattle, goat and sheep

Copy number variation (CNV) is the most prevalent type of genetic structural variation that has been recognized as an important source of phenotypic variation in humans, animals and plants. However, the mechanisms underlying the evolution of CNVs and their function in natural or artificial selection remain unknown. Here, we generated CNV region (CNVR) datasets which were diverged or shared among cattle, goat, and sheep, including 886 individuals from 171 diverse populations. Using 9 environmental factors for genome-wide association study (GWAS), we identified a series of candidate CNVRs, including genes relating to immunity, tick resistance, multi-drug resistance, and muscle development. The number of CNVRs shared between species is significantly higher than expected (P<0.00001), and these CNVRs may be more persist than the single nucleotide polymorphisms (SNPs) shared between species. We also identified genomic regions under long-term balancing selection and uncovered the potential diversity of the selected CNVRs close to the important functional genes. This study provides the evidence that balancing selection might be more common in mammals than previously considered, and might play an important role in the daily activities of these ruminant species.

Population Genomics in the Great Apes

The great apes play an important role as model organisms. They are our closest living relatives, allowing us to identify the genetic basis of phenotypic traits that we think of as characteristically human. However, the most significant asset of great apes as model organisms is that they share with humans most of their genetic makeup. This means that we can extend our vast knowledge of the human genome, its genes, and the associated phenotypes to these species. Comparative genomic studies of humans and apes thus reveal how very similar genomes react when exposed to different population genetic regimes. In this way, each species represents a natural experiment, where a genome highly similar to the human one, is differently exposed to the evolutionary forces of demography, population structure, selection, recombination, and admixture/hybridization. The initial sequencing of reference genomes for chimpanzee, orangutan, gorilla, the bonobo, each provided new insights and a second generation of sequencing projects has provided diversity data for all the great apes. In this chapter, we will outline some of the findings that population genomic analysis of great apes has provided, and how comparative studies have helped us understand how the fundamental forces in evolution have contributed to shaping the genomes and the genetic diversity of the great apes.

Host genetics and infectious disease: new tools, insights and translational opportunities

Understanding how human genetics influence infectious disease susceptibility offers the opportunity for new insights into pathogenesis, potential drug targets, risk stratification, response to therapy and vaccination. As new infectious diseases continue to emerge, together with growing levels of antimicrobial resistance and an increasing awareness of substantial differences between populations in genetic associations, the need for such work is expanding. In this Review, we illustrate how our understanding of the host–pathogen relationship is advancing through holistic approaches, describing current strategies to investigate the role of host genetic variation in established and emerging infections, including COVID-19, the need for wider application to diverse global populations mirroring the burden of disease, the impact of pathogen and vector genetic diversity and a broad array of immune and inflammation phenotypes that can be mapped as traits in health and disease. Insights from study of inborn errors of immunity and multi-omics profiling together with developments in analytical methods are further advancing our knowledge of this important area.

Infectious diseases are an ever-present global threat. In this Review, Kwok, Mentzer and Knight discuss our latest understanding of how human genetics influence susceptibility to disease. Furthermore, they discuss emerging progress in the interplay between host and pathogen genetics, molecular responses to infection and vaccination, and opportunities to bring these aspects together for rapid responses to emerging diseases such as COVID-19.

Human A-to-I RNA editing SNP loci are enriched in GWAS signals for autoimmune diseases and under balancing selection

BACKGROUND

Adenosine-to-inosine (A-to-I) RNA editing plays important roles in diversifying the transcriptome and preventing MDA5 sensing of endogenous dsRNA as nonself. To date, few studies have investigated the population genomic signatures of A-to-I editing due to the lack of editing sites overlapping with SNPs.

RESULTS

In this study, we applied a pipeline to robustly identify SNP editing sites from population transcriptomic data and combined functional genomics, GWAS, and population genomics approaches to study the function and evolution of A-to-I editing. We find that the G allele, which is equivalent to edited I, is overrepresented in editing SNPs. Functionally, A/G editing SNPs are highly enriched in GWAS signals of autoimmune and immune-related diseases. Evolutionarily, derived allele frequency distributions of A/G editing SNPs for both A and G alleles as the ancestral alleles are skewed toward intermediate frequency alleles relative to neutral SNPs, a hallmark of balancing selection, suggesting that both A and G alleles are functionally important. The signal of balancing selection is confirmed by a number of additional population genomic analyses.

CONCLUSIONS

We uncovered a hidden layer of A-to-I RNA editing SNP loci as a common target of balancing selection, and we propose that the maintenance of such editing SNP variations may be at least partially due to constraints on the resolution of the balance between immune activity and self-tolerance.

Flexible Mixture Model Approaches That Accommodate Footprint Size Variability for Robust Detection of Balancing Selection

Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. They also display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Moreover, we applied a specific version of the B statistics, termed B2, to a human population-genomic data set and recovered many top candidates from prior studies, including the then-uncharacterized STPG2 and CCDC169-SOHLH2, both of which are related to gamete functions. We further applied B2 on a bonobo population-genomic data set. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and SCN9A, associated with pain perception. Finally, we show that our methods can be extended to account for multiallelic balancing selection and integrated the set of statistics into open-source software named BalLeRMix for future applications by the scientific community.

Gene expression variability in human and chimpanzee populations share common determinants

Inter-individual variation in gene expression has been shown to be heritable and is often associated with differences in disease susceptibility between individuals. Many studies focused on mapping associations between genetic and gene regulatory variation, yet much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative analysis of gene expression variability and expression quantitative trait loci (eQTLs) in humans and chimpanzees, using gene expression data from primary heart samples. We found that expression variability in both species is often determined by non-genetic sources, such as cell-type heterogeneity. However, we also provide evidence that inter-individual variation in gene regulation can be genetically controlled, and that the degree of such variability is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of orthologous genes associated with eQTLs in both species. We conclude that gene expression variability in humans and chimpanzees often evolves under similar evolutionary pressures.

Background Selection Does Not Mimic the Patterns of Genetic Diversity Produced by Selective Sweeps

It is increasingly evident that natural selection plays a prominent role in shaping patterns of diversity across the genome. The most commonly studied modes of natural selection are positive selection and negative selection, which refer to directional selection for and against derived mutations, respectively. Positive selection can result in hitchhiking events, in which a beneficial allele rapidly replaces all others in the population, creating a valley of diversity around the selected site along with characteristic skews in allele frequencies and linkage disequilibrium among linked neutral polymorphisms. Similarly, negative selection reduces variation not only at selected sites but also at linked sites, a phenomenon called background selection (BGS). Thus, discriminating between these two forces may be difficult, and one might expect efforts to detect hitchhiking to produce an excess of false positives in regions affected by BGS. Here, we examine the similarity between BGS and hitchhiking models via simulation. First, we show that BGS may somewhat resemble hitchhiking in simplistic scenarios in which a region constrained by negative selection is flanked by large stretches of unconstrained sites, echoing previous results. However, this scenario does not mirror the actual spatial arrangement of selected sites across the genome. By performing forward simulations under more realistic scenarios of BGS, modeling the locations of protein-coding and conserved noncoding DNA in real genomes, we show that the spatial patterns of variation produced by BGS rarely mimic those of hitchhiking events. Indeed, BGS is not substantially more likely than neutrality to produce false signatures of hitchhiking. This holds for simulations modeled after both humans and Drosophila, and for several different demographic histories. These results demonstrate that appropriately designed scans for hitchhiking need not consider BGS's impact on false-positive rates. However, we do find evidence that BGS increases the false-negative rate for hitchhiking, an observation that demands further investigation.

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics

Sexually antagonistic (SA) genetic variation-in which alleles favored in one sex are disfavored in the other-is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research-including F ST and F IS statistics, genome-wide association studies, pedigree analyses, reciprocal transplant studies, and evolve-and-resequence experiments-to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.

Host-parasite co-evolution and its genomic signature

Studies in diverse biological systems have indicated that host-parasite co-evolution is responsible for the extraordinary genetic diversity seen in some genomic regions, such as major histocompatibility (MHC) genes in jawed vertebrates and resistance genes in plants. This diversity is believed to evolve under balancing selection on hosts by parasites. However, the mechanisms that link the genomic signatures in these regions to the underlying co-evolutionary process are only slowly emerging. We still lack a clear picture of the co-evolutionary concepts and of the genetic basis of the co-evolving phenotypic traits in the interacting antagonists. Emerging genomic tools that provide new options for identifying underlying genes will contribute to a fuller understanding of the co-evolutionary process.

Polymorphism clustering of the 21.5 kb DPA-promoter-DPB region reveals novel extended full-length haplotypes

DPB1 and DPA1 genes share the same promoter region. Single-nucleotide polymorphisms (SNPs) within the regulatory regions of DP have been reported. This study hypothesizes that by including the SNPs in the promoter region of DP, extended haplotypes are defined, and promoter polymorphism is more extensive than what is currently reported. To identify the SNPs in the region of interest, the DP region spanning 21.5 kb was amplified in three separate long-ranged polymerase chain reactions. A DNA panel consisting of 100 samples was selected to represent a broad range of DPB1 alleles. The panel was amplified and sequenced using a dual sequencing strategy. Binary alignment map (BAM) alignments were generated and the mapped sequence alignments were analyzed using Integrative Genomics Viewer. A total of 76 SNPs were identified, and SNPs were clustered into 12 SNP-linked haplotypes. Multiple sequence alignments of promoter sequences indicated four distinct lineages within the connective region (CR) between two genes. The relationship between DPA1, CR, DPB1, and amino acid motifs was found to be correlated with HV1 and HV6. Of the 12 promoter haplotypes, DPB1 alleles observed with ProDP-4 were in complete linkage with HV1/2/5/6, the rs9277534G SNP, and the highly immunogenic T-cell epitope group. Multiple extended haplotypes of different intronic subtypes of the same DPB1 alleles were also identified. This new view of the full DP haplotype shows the relation of polymorphism, genes, and alleles, and provides a basis for future functionality related nomenclature. The novel clustering of the DP-extended haplotype warrants future investigations of DP haplotype matching in the outcome of haematopoietic stem cell transplantation (HSCT).

Binding affinities of 438 HLA proteins to complete proteomes of seven pandemic viruses and distributions of strongest and weakest HLA peptide binders in populations worldwide

We report detailed peptide‐binding affinities between 438 HLA Class I and Class II proteins and complete proteomes of seven pandemic human viruses, including coronaviruses, influenza viruses and HIV‐1. We contrast these affinities with HLA allele frequencies across hundreds of human populations worldwide. Statistical modelling shows that peptide‐binding affinities classified into four distinct categories depend on the HLA locus but that the type of virus is only a weak predictor, except in the case of HIV‐1. Among the strong HLA binders (IC₅₀ ≤ 50), we uncovered 16 alleles (the top ones being A*02:02, B*15:03 and DRB1*01:02) binding more than 1% of peptides derived from all viruses, 9 (top ones including HLA‐A*68:01, B*15:25, C*03:02 and DRB1*07:01) binding all viruses except HIV‐1, and 15 (top ones A*02:01 and C*14:02) only binding coronaviruses. The frequencies of strongest and weakest HLA peptide binders differ significantly among populations from different geographic regions. In particular, Indigenous peoples of America show both higher frequencies of strongest and lower frequencies of weakest HLA binders. As many HLA proteins are found to be strong binders of peptides derived from distinct viral families, and are hence promiscuous (or generalist), we discuss this result in relation to possible signatures of natural selection on HLA promiscuous alleles due to past pathogenic infections. Our findings are highly relevant for both evolutionary genetics and the development of vaccine therapies. However they should not lead to forget that individual resistance and vulnerability to diseases go beyond the sole HLA allelic affinity and depend on multiple, complex and often unknown biological, environmental and other variables.

Human genetics and malaria resistance

Malaria has been the pre-eminent cause of early mortality in many parts of the world throughout much of the last five thousand years and, as a result, it is the strongest force for selective pressure on the human genome yet described. Around one third of the variability in the risk of severe and complicated malaria is now explained by additive host genetic effects. Many individual variants have been identified that are associated with malaria protection, but the most important all relate to the structure or function of red blood cells. They include the classical polymorphisms that cause sickle cell trait, α-thalassaemia, G6PD deficiency, and the major red cell blood group variants. More recently however, with improving technology and experimental design, others have been identified that include the Dantu blood group variant, polymorphisms in the red cell membrane protein ATP2B4, and several variants related to the immune response. Characterising how these genes confer their effects could eventually inform novel therapeutic approaches to combat malaria. Nevertheless, all together, only a small proportion of the heritable component of malaria resistance can be explained by the variants described so far, underscoring its complex genetic architecture and the need for continued research.

Evolutionary and population (epi)genetics of immunity to infection

Immune response is one of the functions that have been more strongly targeted by natural selection during human evolution. The evolutionary genetic dissection of the immune system has greatly helped to distinguish genes and functions that are essential, redundant or advantageous for human survival. It is also becoming increasingly clear that admixture between early Eurasians with now-extinct hominins such as Neanderthals or Denisovans, or admixture between modern human populations, can be beneficial for human adaptation to pathogen pressures. In this review, we discuss how the integration of population genetics with functional genomics in diverse human populations can inform about the changes in immune functions related to major lifestyle transitions (e.g., from hunting and gathering to farming), the action of natural selection to the evolution of the immune system, and the history of past epidemics. We also highlight the need of expanding the characterization of the immune system to a larger array of human populations-particularly neglected human groups historically exposed to different pathogen pressures-to fully capture the relative contribution of genetic, epigenetic, and environmental factors to immune response variation in humans.

Long-Read Nanopore Sequencing Validated for Human Leukocyte Antigen Class I Typing in Routine Diagnostics

Matching of human leukocyte antigen (HLA) gene polymorphisms by high-resolution DNA sequence analysis is the gold standard for determining compatibility between patient and donor for hematopoietic stem cell transplantation. Single-molecule sequencing (PacBio or MinION) is a newest (third) generation sequencing approach. MinION is a nanopore sequencing platform, which provides long targeted DNA sequences. The long reads provide unambiguous phasing, but the initial high error profile prevented its use in high-impact applications, such as HLA typing for HLA matching of donor and recipient in the transplantation setting. Ongoing developments on instrumentation and basecalling software have improved the per-base accuracy of 1D² nanopore reads tremendously. In the current study, two validation panels of samples covering 70 of the 71 known HLA class I allele groups were used to compare third field sequences obtained by MinION, with Sanger sequence-based typing showing a 100% concordance between both data sets. In addition, the first validation panel was used to set the acceptance criteria for the use of MinION in a routine setting. The acceptance criteria were subsequently confirmed with the second validation panel. In summary, the present study describes validation and implementation of nanopore sequencing HLA class I typing method and illustrates that nanopore sequencing technology has advanced to a point where it can be used in routine diagnostics with high accuracy.

Inference of natural selection from ancient DNA

Evolutionary processes, including selection, can be indirectly inferred based on patterns of genomic variation among contemporary populations or species. However, this often requires unrealistic assumptions of ancestral demography and selective regimes. Sequencing ancient DNA from temporally spaced samples can inform about past selection processes, as time series data allow direct quantification of population parameters collected before, during, and after genetic changes driven by selection. In this Comment and Opinion, we advocate for the inclusion of temporal sampling and the generation of paleogenomic datasets in evolutionary biology, and highlight some of the recent advances that have yet to be broadly applied by evolutionary biologists. In doing so, we consider the expected signatures of balancing, purifying, and positive selection in time series data, and detail how this can advance our understanding of the chronology and tempo of genomic change driven by selection. However, we also recognize the limitations of such data, which can suffer from postmortem damage, fragmentation, low coverage, and typically low sample size. We therefore highlight the many assumptions and considerations associated with analyzing paleogenomic data and the assumptions associated with analytical methods.

Genetic susceptibility to severe childhood asthma and rhinovirus-C maintained by balancing selection in humans for 150 000 years

Selective pressures imposed by pathogens have varied among human populations throughout their evolution, leading to marked inter-population differences at some genes mediating susceptibility to infectious and immune-related diseases. Here, we investigated the evolutionary history of a common polymorphism resulting in a Y529 versus C529 change in the cadherin related family member 3 (CDHR3) receptor which underlies variable susceptibility to rhinovirus-C infection and is associated with severe childhood asthma. The protective variant is the derived allele and is found at high frequency worldwide (69-95%). We detected genome-wide significant signatures of natural selection consistent with a rapid increase of the haplotypes carrying the allele, suggesting that non-neutral processes have acted on this locus across all human populations. However, the allele has not fixed in any population despite multiple lines of evidence suggesting that the mutation predates human migrations out of Africa. Using an approximate Bayesian computation method, we estimate the age of the mutation while explicitly accounting for past demography and positive or frequency-dependent balancing selection. Our analyses indicate a single emergence of the mutation in anatomically modern humans ~150 000 years ago and indicate that balancing selection has maintained the beneficial allele at high equilibrium frequencies worldwide. Apart from the well-known cases of the MHC and ABO genes, this study provides the first evidence that negative frequency-dependent selection plausibly acted on a human disease susceptibility locus, a form of balancing selection compatible with typical transmission dynamics of communicable respiratory viruses that might exploit CDHR3.

BetaScan2: Standardized Statistics to Detect Balancing Selection Utilizing Substitution Data

Long-term balancing selection results in a build-up of alleles at similar frequencies and a deficit of substitutions when compared with an outgroup at a locus. The previously published β(1) statistics detect balancing selection using only polymorphism data. We now propose the β(2) statistic which detects balancing selection using both polymorphism and substitution data. In addition, we derive the variance of all β statistics, allowing for their standardization and thereby reducing the influence of parameters which can confound other selection tests. The standardized β statistics outperform existing summary statistics in simulations, indicating β is a well-powered and widely applicable approach for detecting balancing selection. We apply the β(2) statistic to 1000 Genomes data and report two missense mutations with high β scores in the ACSBG2 gene. An implementation of all β statistics and their standardization are available in the BetaScan2 software package at https://github.com/ksiewert/BetaScan.

Phylogenomics of the genus Populus reveals extensive interspecific gene flow and balancing selection

Phylogenetic analysis is complicated by interspecific gene flow and the presence of shared ancestral polymorphisms, particularly those maintained by balancing selection. In this study, we aimed to examine the prevalence of these factors during the diversification of Populus, a model tree genus in the Northern Hemisphere. We constructed phylogenetic trees of 29 Populus taxa using 80 individuals based on re-sequenced genomes. Our species tree analyses recovered four main clades in the genus based on consensus nuclear phylogenies, but in conflict with the plastome phylogeny. A few interspecific relationships remained unresolved within the multiple-species clade because of inconsistent gene trees. Our results indicated that gene flow has been widespread within each clade and also occurred among the four clades during their early divergence. We identified 45 candidate genes with ancient polymorphisms maintained by balancing selection. These genes were mainly associated with mating compatibility, growth and stress resistance. Both gene flow and selection-mediated ancient polymorphisms are prevalent in the genus Populus. These are potentially important contributors to adaptive variation. Our results provide a framework for the diversification of model tree genus that will facilitate future comparative studies.

Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania

The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replicable associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus.  Previously reported HLA associations do not replicate in these samples. This large dataset will provide a foundation for further research on thegenetic determinants of malaria resistance in diverse populations.

Insights into the polymorphism in HLA-DRA and its evolutionary relationship with HLA haplotypes

HLA-DRA encodes the alpha chain of the HLA-DR protein, one of the classical HLA class II molecules. Reported polymorphism within HLA-DRA is currently limited compared with other HLA genes, as only a single polymorphism encodes an amino acid difference in the translated protein. Since this SNP (rs7192, HLA00662.1:g.4276G>T p.Val217Leu) lies within exon 4, in the region encoding the cytoplasmic tail, the resulting protein is effectively monomorphic. For this reason, in-depth studies on HLA-DRA and its function have been limited. However, analysis of sequences from the 1000 Genomes Project and preliminary data from our lab reveals unrepresented polymorphism within HLA-DRA, suggesting a more complex role within the MHC than previously assumed. This study focuses on elucidating the extent of HLA-DRA polymorphism, and extending our understanding of the gene's role in HLA-DR~HLA-DQ haplotypes. Ninety-eight samples were sequenced for full-length HLA-DRA, and from this analysis, we identified 20 novel SNP positions in the intronic sequences within the 5711 bp region represented in IPD-IMGT/HLA. This polymorphism gives rise to at least 22 novel HLA-DRA alleles, and the patterns of intronic and 3' UTR polymorphism correspond to HLA-DRA~HLA-DRB345~HLA-DRB1~HLA-DQB1 haplotypes. The current understanding of the organization of the genes within the HLA-DR region assumes a single lineage for the HLA-DRA gene, as opposed to multiple gene lineages, such as in HLA-DRB. This study suggests that the intron and 3' UTR polymorphism of HLA-DRA indicates different lineages, and represents the HLA-DRA~HLA-DRB345~HLA-DRB1~HLA-DQB1 haplotypes.

An Evolutionary Perspective on the Impact of Genomic Copy Number Variation on Human Health

Copy number variants (CNVs), deletions and duplications of segments of DNA, account for at least five times more variable base pairs in humans than single-nucleotide variants. Several common CNVs were shown to change coding and regulatory sequences and thus dramatically affect adaptive phenotypes involving immunity, perception, metabolism, skin structure, among others. Some of these CNVs were also associated with susceptibility to cancer, infection, and metabolic disorders. These observations raise the possibility that CNVs are a primary contributor to human phenotypic variation and consequently evolve under selective pressures. Indeed, locus-specific haplotype-level analyses revealed signatures of natural selection on several CNVs. However, more traditional tests of selection which are often applied to single-nucleotide variation often have diminished statistical power when applied to CNVs because they often do not show strong linkage disequilibrium with nearby variants. Recombination-based formation mechanisms of CNVs lead to frequent recurrence and gene conversion events, breaking the linkage disequilibrium involving CNVs. Similar methodological challenges also prevent routine genome-wide association studies to adequately investigate the impact of CNVs on heritable human disease. Thus, we argue that the full relevance of CNVs to human health and evolution is yet to be elucidated. We further argue that a holistic investigation of formation mechanisms within an evolutionary framework would provide a powerful framework to understand the functional and biomedical impact of CNVs. In this paper, we review several cases where studies reveal diverse evolutionary histories and unexpected functional consequences of CNVs. We hope that this review will encourage further work on CNVs by both evolutionary and medical geneticists.

Elevated Heterozygosity in Adults Relative to Juveniles Provides Evidence of Viability Selection on Eagles and Falcons

Viability selection yields adult populations that are more genetically variable than those of juveniles, producing a positive correlation between heterozygosity and survival. Viability selection could be the result of decreased heterozygosity across many loci in inbred individuals and a subsequent decrease in survivorship resulting from the expression of the deleterious alleles. Alternatively, locus-specific differences in genetic variability between adults and juveniles may be driven by forms of balancing selection, including heterozygote advantage, frequency-dependent selection, or selection across temporal and spatial scales. We use a pooled-sequencing approach to compare genome-wide and locus-specific genetic variability between 74 golden eagle (Aquila chrysaetos), 62 imperial eagle (Aquila heliaca), and 69 prairie falcon (Falco mexicanus) juveniles and adults. Although genome-wide genetic variability is comparable between juvenile and adult golden eagles and prairie falcons, imperial eagle adults are significantly more heterozygous than juveniles. This evidence of viability selection may stem from a relatively smaller imperial eagle effective population size and potentially greater genetic load. We additionally identify ~2000 single-nucleotide polymorphisms across the 3 species with extreme differences in heterozygosity between juveniles and adults. Many of these markers are associated with genes implicated in immune function or olfaction. These loci represent potential targets for studies of how heterozygote advantage, frequency-dependent selection, and selection over spatial and temporal scales influence survivorship in avian species. Overall, our genome-wide data extend previous studies that used allozyme or microsatellite markers and indicate that viability selection may be a more common evolutionary phenomenon than often appreciated.

Large-Scale Comparative Analysis of Codon Models Accounting for Protein and Nucleotide Selection

There are numerous sources of variation in the rate of synonymous substitutions inside genes, such as direct selection on the nucleotide sequence, or mutation rate variation. Yet scans for positive selection rely on codon models which incorporate an assumption of effectively neutral synonymous substitution rate, constant between sites of each gene. Here we perform a large-scale comparison of approaches which incorporate codon substitution rate variation and propose our own simple yet effective modification of existing models. We find strong effects of substitution rate variation on positive selection inference. More than 70% of the genes detected by the classical branch-site model are presumably false positives caused by the incorrect assumption of uniform synonymous substitution rate. We propose a new model which is strongly favored by the data while remaining computationally tractable. With the new model we can capture signatures of nucleotide level selection acting on translation initiation and on splicing sites within the coding region. Finally, we show that rate variation is highest in the highly recombining regions, and we propose that recombination and mutation rate variation, such as high CpG mutation rate, are the two main sources of nucleotide rate variation. Although we detect fewer genes under positive selection in Drosophila than without rate variation, the genes which we detect contain a stronger signal of adaptation of dynein, which could be associated with Wolbachia infection. We provide software to perform positive selection analysis using the new model.

Genome-wide analysis indicates association between heterozygote advantage and healthy aging in humans

Background

Genetic diversity is known to confer survival advantage in many species across the tree of life. Here, we hypothesize that such pattern applies to humans as well and could be a result of higher fitness in individuals with higher genomic heterozygosity.

Results

We use healthy aging as a proxy for better health and fitness, and observe greater heterozygosity in healthy-aged individuals. Specifically, we find that only common genetic variants show significantly higher excess of heterozygosity in the healthy-aged cohort. Lack of difference in heterozygosity for low-frequency variants or disease-associated variants excludes the possibility of compensation for deleterious recessive alleles as a mechanism. In addition, coding SNPs with the highest excess of heterozygosity in the healthy-aged cohort are enriched in genes involved in extracellular matrix and glycoproteins, a group of genes known to be under long-term balancing selection. We also find that individual heterozygosity rate is a significant predictor of electronic health record (EHR)-based estimates of 10-year survival probability in men but not in women, accounting for several factors including age and ethnicity.

Conclusions

Our results demonstrate that the genomic heterozygosity is associated with human healthspan, and that the relationship between higher heterozygosity and healthy aging could be explained by heterozygote advantage. Further characterization of this relationship will have important implications in aging-associated disease risk prediction.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0758-4) contains supplementary material, which is available to authorized users.

Integrative Genomics Reveals the Genetics and Evolution of the Honey Bee's Social Immune System

Social organisms combat pathogens through individual innate immune responses or through social immunity—behaviors among individuals that limit pathogen transmission within groups. Although we have a relatively detailed understanding of the genetics and evolution of the innate immune system of animals, we know little about social immunity. Addressing this knowledge gap is crucial for understanding how life-history traits influence immunity, and identifying if trade-offs exist between innate and social immunity. Hygienic behavior in the Western honey bee, Apis mellifera, provides an excellent model for investigating the genetics and evolution of social immunity in animals. This heritable, colony-level behavior is performed by nurse bees when they detect and remove infected or dead brood from the colony. We sequenced 125 haploid genomes from two artificially selected highly hygienic populations and a baseline unselected population. Genomic contrasts allowed us to identify a minimum of 73 genes tentatively associated with hygienic behavior. Many genes were within previously discovered QTLs associated with hygienic behavior and were predictive of hygienic behavior within the unselected population. These genes were often involved in neuronal development and sensory perception in solitary insects. We found that genes associated with hygienic behavior have evidence of positive selection within honey bees (Apis), supporting the hypothesis that social immunity contributes to fitness. Our results indicate that genes influencing developmental neurobiology and behavior in solitary insects may have been co-opted to give rise to a novel and adaptive social immune phenotype in honey bees.

Leucine rich repeat kinase 2: a paradigm for pleiotropy

The LRRK2 gene, coding for leucine rich repeat kinase 2 (LRRK2), is a key player in the genetics of Parkinson's disease. Despite extensive efforts, LRRK2 has proved remarkably evasive with regard to attempts to understand both the role it plays in disease and its normal physiological function. At least part of why LRRK2 has been so difficult to define is that it appears to be many things to many cellular functions and diseases - a pleiotropic actor at both the genetic and the molecular level. Gaining greater insight into the mechanisms and pathways allowing LRRK2 to act in this manner will have implications for our understanding of the role of genes in the aetiology of complex disease, the molecular underpinnings of signal transduction pathways in the cell, and drug discovery in the genome era.

Recent Adaptive Acquisition by African Rainforest Hunter-Gatherers of the Late Pleistocene Sickle-Cell Mutation Suggests Past Differences in Malaria Exposure

The hemoglobin βS sickle mutation is a textbook case in which natural selection maintains a deleterious mutation at high frequency in the human population. Homozygous individuals for this mutation develop sickle-cell disease, whereas heterozygotes benefit from higher protection against severe malaria. Because the overdominant βS allele should be purged almost immediately from the population in the absence of malaria, the study of the evolutionary history of this iconic mutation can provide important information about the history of human exposure to malaria. Here, we sought to increase our understanding of the origins and time depth of the βS mutation in populations with different lifestyles and ecologies, and we analyzed the diversity of HBB in 479 individuals from 13 populations of African farmers and rainforest hunter-gatherers. Using an approximate Bayesian computation method, we estimated the age of the βS allele while explicitly accounting for population subdivision, past demography, and balancing selection. When the effects of balancing selection are taken into account, our analyses indicate a single emergence of βS in the ancestors of present-day agriculturalist populations ∼22,000 years ago. Furthermore, we show that rainforest hunter-gatherers have more recently acquired the βS mutation from the ancestors of agriculturalists through adaptive gene flow during the last ∼6,000 years. Together, our results provide evidence for a more ancient exposure to malarial pressures among the ancestors of agriculturalists than previously appreciated, and they suggest that rainforest hunter-gatherers have been increasingly exposed to malaria during the last millennia.

Long-term balancing selection drives evolution of immunity genes in Capsella

Genetic drift is expected to remove polymorphism from populations over long periods of time, with the rate of polymorphism loss being accelerated when species experience strong reductions in population size. Adaptive forces that maintain genetic variation in populations, or balancing selection, might counteract this process. To understand the extent to which natural selection can drive the retention of genetic diversity, we document genomic variability after two parallel species-wide bottlenecks in the genus Capsella. We find that ancestral variation preferentially persists at immunity related loci, and that the same collection of alleles has been maintained in different lineages that have been separated for several million years. By reconstructing the evolution of the disease-related locus MLO2b, we find that divergence between ancient haplotypes can be obscured by referenced based re-sequencing methods, and that trans-specific alleles can encode substantially diverged protein sequences. Our data point to long-term balancing selection as an important factor shaping the genetics of immune systems in plants and as the predominant driver of genomic variability after a population bottleneck.

Immune Gene Diversity in Archaic and Present-day Humans

Genome-wide analyses of two Neandertals and a Denisovan have shown that these archaic humans had lower genetic heterozygosity than present-day people. A similar reduction in genetic diversity of protein-coding genes (gene diversity) was found in exome sequences of three Neandertals. Reduced gene diversity, particularly in genes involved in immunity, may have important functional consequences. In fact, it has been suggested that reduced diversity in immune genes may have contributed to Neandertal extinction. We therefore explored gene diversity in different human groups, and at different time points on the Neandertal lineage, with a particular focus on the diversity of genes involved in innate immunity and genes of the Major Histocompatibility Complex (MHC).

We find that the two Neandertals and a Denisovan have similar gene diversity, all significantly lower than any present-day human. This is true across gene categories, with no gene set showing an excess decrease in diversity compared with the genome-wide average. Innate immune-related genes show a similar reduction in diversity to other genes, both in present-day and archaic humans. There is also no observable decrease in gene diversity over time in Neandertals, suggesting that there may have been no ongoing reduction in gene diversity in later Neandertals, although this needs confirmation with a larger sample size. In both archaic and present-day humans, genes with the highest levels of diversity are enriched for MHC-related functions. In fact, in archaic humans the MHC genes show evidence of having retained more diversity than genes involved only in the innate immune system.

Detection of Shared Balancing Selection in the Absence of Trans-Species Polymorphism

Trans-species polymorphism has been widely used as a key sign of long-term balancing selection across multiple species. However, such sites are often rare in the genome and could result from mutational processes or technical artifacts. Few methods are yet available to specifically detect footprints of trans-species balancing selection without using trans-species polymorphic sites. In this study, we develop summary- and model-based approaches that are each specifically tailored to uncover regions of long-term balancing selection shared by a set of species by using genomic patterns of intraspecific polymorphism and interspecific fixed differences. We demonstrate that our trans-species statistics have substantially higher power than single-species approaches to detect footprints of trans-species balancing selection, and are robust to those that do not affect all tested species. We further apply our model-based methods to human and chimpanzee whole-genome sequencing data. In addition to the previously established major histocompatibility complex and malaria resistance-associated FREM3/GYPE regions, we also find outstanding genomic regions involved in barrier integrity and innate immunity, such as the GRIK1/CLDN17 intergenic region, and the SLC35F1 and ABCA13 genes. Our findings not only echo the significance of pathogen defense but also reveal novel candidates in maintaining balanced polymorphisms across human and chimpanzee lineages. Finally, we show that these trans-species statistics can be applied to and work well for an arbitrary number of species, and integrate them into open-source software packages for ease of use by the scientific community.

Frequent monoallelic or skewed expression for developmental genes in CNS-derived cells and evidence for balancing selection

Cellular mosaicism due to monoallelic autosomal expression (MAE), with cell selection during development, is becoming increasingly recognized as prevalent in mammals, leading to interest in understanding its extent and mechanism(s). We report here use of clonal cell lines derived from the CNS of adult female [Formula: see text] hybrid (C57BL/6 X JF1) mice to characterize MAE as neural stem cells (nscs) differentiate to astrocyte-like cells (asls). We found that different subsets of genes show MAE in the two populations of cells; in each case, there is strong enrichment for genes specific to the respective developmental state. Genes that exhibit MAE are 22% of nsc-specific genes and 26% of asl-specific genes. Moreover, the promoters of genes with MAE have reduced CpG dinucleotides but increased CpG differences between the two parental mouse strains. Extending the study of variability to wild populations of mice, we found evidence for balancing selection as a contributing force in evolution of those genes showing developmental specificity (i.e., expressed in either nsc or asl), not just for genes showing MAE. Furthermore, we found that genes showing skewed allelic expression (SKE) were similarly enriched among cell type-specific genes and also showed a heightened probability of balancing selection. Thus, developmental stage-specific genes and genes with MAE or SKE seem to make up overlapping classes subject to selection for increased diversity. The implications of these results for development and evolution are discussed in the context of a model with stochastic epigenetic modifications taking place only during a relatively brief developmental window.

Population genetic analysis of autophagy and phagocytosis genes in Drosophila melanogaster and D. simulans

Autophagy and phagocytosis are cellular immune mechanisms for internalization and elimination of intracellular and extracellular pathogens. Some pathogens have evolved the ability to inhibit or manipulate these processes, raising the prospect of adaptive reciprocal co-evolution by the host. We performed population genetic analyses on phagocytosis and autophagy genes in Drosophila melanogaster and D. simulans to test for molecular evolutionary signatures of immune adaptation. We found that phagocytosis and autophagy genes as a whole exhibited an elevated level of haplotype homozygosity in both species. In addition, we detected signatures of recent selection, notably in the Atg14 and Ykt6 genes in D. melanogaster and a pattern of elevated sequence divergence in the genderblind (gb) gene on the D. simulans lineage. These results suggest that the evolution of the host cellular immune system as a whole may be shaped by a dynamic conflict between Drosophila and its pathogens even without pervasive evidence of strong adaptive evolution at the individual gene level.

Signatures of Long-Term Balancing Selection in Human Genomes

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.

Full-length extension of HLA allele sequences by HLA allele-specific hemizygous Sanger sequencing (SSBT)

The gold standard for typing at the allele level of the highly polymorphic Human Leucocyte Antigen (HLA) gene system is sequence based typing. Since sequencing strategies have mainly focused on identification of the peptide binding groove, full-length sequence information is lacking for >90% of the HLA alleles. One of the goals of the 17th IHIWS workshop is to establish full-length sequences for as many HLA alleles as possible. In our component "Extension of HLA sequences by full-length HLA allele-specific hemizygous Sanger sequencing" we have used full-length hemizygous Sanger Sequence Based Typing to achieve this goal. We selected samples of which full length sequences were not available in the IPD-IMGT/HLA database. In total we have generated the full-length sequences of 48 HLA-A, 45 -B and 31 -C alleles. For HLA-A extended alleles, 39/48 showed no intron differences compared to the first allele of the corresponding allele group, for HLA-B this was 26/45 and for HLA-C 20/31. Comparing the intron sequences to other alleles of the same allele group revealed that in 5/48 HLA-A, 16/45 HLA-B and 8/31 HLA-C alleles the intron sequence was identical to another allele of the same allele group. In the remaining 10 cases, the sequence either showed polymorphism at a conserved nucleotide or was the result of a gene conversion event. Elucidation of the full-length sequence gives insight in the polymorphic content of the alleles and facilitates the identification of its evolutionary origin.

Predicting the clinical impact of human mutation with deep neural networks

Millions of human genomes and exomes have been sequenced, but their clinical applications remain limited due to the difficulty of distinguishing disease-causing mutations from benign genetic variation. Here we demonstrate that common missense variants in other primate species are largely clinically benign in human, enabling pathogenic mutations to be systematically identified by the process of elimination. Using hundreds of thousands of common variants from population sequencing of six non-human primate species, we train a deep neural network that identifies pathogenic mutations in rare disease patients with 88% accuracy and enables the discovery of 14 new candidate genes in intellectual disability at genome-wide significance. Cataloging common variation from additional primate species would improve interpretation for millions of variants of uncertain significance, further advancing the clinical utility of human genome sequencing.

The Effect of Balancing Selection on Population Differentiation: A Study with HLA Genes

Balancing selection is defined as a class of selective regimes that maintain polymorphism above what is expected under neutrality. Theory predicts that balancing selection reduces population differentiation, as measured by FST. However, balancing selection regimes in which different sets of alleles are maintained in different populations could increase population differentiation. To tackle the connection between balancing selection and population differentiation, we investigated population differentiation at the HLA genes, which constitute the most striking example of balancing selection in humans. We found that population differentiation of single nucleotide polymorphisms (SNPs) at the HLA genes is on average lower than that of SNPs in other genomic regions. We show that these results require using a computation that accounts for the dependence of FST on allele frequencies. However, in pairs of closely related populations, where genome-wide differentiation is low, differentiation at HLA is higher than in other genomic regions. Such increased population differentiation at HLA genes for recently diverged population pairs was reproduced in simulations of overdominant selection, as long as the fitness of the homozygotes differs between the diverging populations. The results give insight into a possible "divergent overdominance" mechanism for the nature of balancing selection on HLA genes across human populations.

Evolutionary and Medical Consequences of Archaic Introgression into Modern Human Genomes

The demographic history of anatomically modern humans (AMH) involves multiple migration events, population extinctions and genetic adaptations. As genome-wide data from complete genome sequencing becomes increasingly abundant and available even from extinct hominins, new insights of the evolutionary history of our species are discovered. It is currently known that AMH interbred with archaic hominins once they left the African continent. Current non-African human genomes carry fragments of archaic origin. This review focuses on the fitness consequences of archaic interbreeding in current human populations. We discuss new insights and challenges that researchers face when interpreting the potential impact of introgression on fitness and testing hypotheses about the role of selection within the context of health and disease.

Gene buddies: linked balanced polymorphisms reinforce each other even in the absence of epistasis

The fates of genetic polymorphisms maintained by balancing selection depend on evolutionary dynamics at linked sites. While coevolution across linked, epigenetically-interacting loci has been extensively explored, such supergenes may be relatively rare. However, genes harboring adaptive variation can occur in close physical proximity while generating independent effects on fitness. Here, I present a model in which two linked loci without epistasis are both under balancing selection for unrelated reasons. Using forward-time simulations, I show that recombination rate strongly influences the retention of adaptive polymorphism, especially for intermediate selection coefficients. A locus is more likely to retain adaptive variation if it is closely linked to another locus under balancing selection, even if the two loci have no interaction. Thus, two linked polymorphisms can both be retained indefinitely even when they would both be lost to drift if unlinked. While these results may be intuitive, they have important implications for genetic architecture: clusters of mutually reinforcing genes may underlie phenotypic variation in natural populations, and such genes cannot be assumed to be functionally associated. Future studies that measure selection coefficients and recombination rates among closely linked genes will be fruitful for characterizing the extent of this phenomenon.