Population genomics reveal recent speciation and rapid evolutionary adaptation in polar bears.

Polar bears are uniquely adapted to life in the High Arctic and have undergone drastic physiological changes in response to Arctic climates and a hyper-lipid diet of primarily marine mammal prey. We analyzed 89 complete genomes of polar bear and brown bear using population genomic modeling and show that the species diverged only 479-343 thousand years BP. We find that genes on the polar bear lineage have been under stronger positive selection than in brown bears; nine of the top 16 genes under strong positive selection are associated with cardiomyopathy and vascular disease, implying important reorganization of the cardiovascular system. One of the genes showing the strongest evidence of selection, APOB, encodes the primary lipoprotein component of low-density lipoprotein (LDL); functional mutations in APOB may explain how polar bears are able to cope with life-long elevated LDL levels that are associated with high risk of heart disease in humans.

Disentangling Signatures of Selection Before and After European Colonization in Latin Americans.

Throughout human evolutionary history, large-scale migrations have led to intermixing (i.e., admixture) between previously separated human groups. Although classical and recent work have shown that studying admixture can yield novel historical insights, the extent to which this process contributed to adaptation remains underexplored. Here, we introduce a novel statistical model, specific to admixed populations, that identifies loci under selection while determining whether the selection likely occurred post-admixture or prior to admixture in one of the ancestral source populations. Through extensive simulations, we show that this method is able to detect selection, even in recently formed admixed populations, and to accurately differentiate between selection occurring in the ancestral or admixed population. We apply this method to genome-wide SNP data of ∼4,000 individuals in five admixed Latin American cohorts from Brazil, Chile, Colombia, Mexico, and Peru. Our approach replicates previous reports of selection in the human leukocyte antigen region that are consistent with selection post-admixture. We also report novel signals of selection in genomic regions spanning 47 genes, reinforcing many of these signals with an alternative, commonly used local-ancestry-inference approach. These signals include several genes involved in immunity, which may reflect responses to endemic pathogens of the Americas and to the challenge of infectious disease brought by European contact. In addition, some of the strongest signals inferred to be under selection in the Native American ancestral groups of modern Latin Americans overlap with genes implicated in energy metabolism phenotypes, plausibly reflecting adaptations to novel dietary sources available in the Americas.

ngsLD: evaluating linkage disequilibrium using genotype likelihoods.

MOTIVATION: Linkage disequilibrium (LD) measures the correlation between genetic loci and is highly informative for association mapping and population genetics. As many studies rely on called genotypes for estimating LD, their results can be affected by data uncertainty, especially when employing a low read depth sequencing strategy. Furthermore, there is a manifest lack of tools for the analysis of large-scale, low-depth and short-read sequencing data from non-model organisms with limited sample sizes. RESULTS: ngsLD addresses these issues by estimating LD directly from genotype likelihoods in a fast, reliable and user-friendly implementation. This method makes use of the full information available from sequencing data and provides accurate estimates of linkage disequilibrium patterns compared with approaches based on genotype calling. We conducted a case study to investigate how LD decays over physical distance in two avian species. AVAILABILITY AND IMPLEMENTATION: The methods presented in this work were implemented in C/C and are freely available for non-commercial use from https://github.com/fgvieira/ngsLD. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes.

The Greenlandic population, a small and historically isolated founder population comprising about 57,000 inhabitants, has experienced a dramatic increase in type 2 diabetes (T2D) prevalence during the past 25 years. Motivated by this, we performed association mapping of T2D-related quantitative traits in up to 2,575 Greenlandic individuals without known diabetes. Using array-based genotyping and exome sequencing, we discovered a nonsense p.Arg684Ter variant (in which arginine is replaced by a termination codon) in the gene TBC1D4 with an allele frequency of 17%. Here we show that homozygous carriers of this variant have markedly higher concentrations of plasma glucose (ß = 3.8 mmol l(-1), P = 2.5 × 10(-35)) and serum insulin (ß = 165 pmol l(-1), P = 1.5 × 10(-20)) 2 hours after an oral glucose load compared with individuals with other genotypes (both non-carriers and heterozygous carriers). Furthermore, homozygous carriers have marginally lower concentrations of fasting plasma glucose (ß = -0.18 mmol l(-1), P = 1.1 × 10(-6)) and fasting serum insulin (ß = -8.3 pmol l(-1), P = 0.0014), and their T2D risk is markedly increased (odds ratio (OR) = 10.3, P = 1.6 × 10(-24)). Heterozygous carriers have a moderately higher plasma glucose concentration 2 hours after an oral glucose load than non-carriers (ß = 0.43 mmol l(-1), P = 5.3 × 10(-5)). Analyses of skeletal muscle biopsies showed lower messenger RNA and protein levels of the long isoform of TBC1D4, and lower muscle protein levels of the glucose transporter GLUT4, with increasing number of p.Arg684Ter alleles. These findings are concomitant with a severely decreased insulin-stimulated glucose uptake in muscle, leading to postprandial hyperglycaemia, impaired glucose tolerance and T2D. The observed effect sizes are several times larger than any previous findings in large-scale genome-wide association studies of these traits and constitute further proof of the value of conducting genetic association studies outside the traditional setting of large homogeneous populations.

Survival and divergence in a small group: The extraordinary genomic history of the endangered Apennine brown bear stragglers.

About 100 km east of Rome, in the central Apennine Mountains, a critically endangered population of ∼50 brown bears live in complete isolation. Mating outside this population is prevented by several 100 km of bear-free territories. We exploited this natural experiment to better understand the gene and genomic consequences of surviving at extremely small population size. We found that brown bear populations in Europe lost connectivity since Neolithic times, when farming communities expanded and forest burning was used for land clearance. In central Italy, this resulted in a 40-fold population decline. The overall genomic impact of this decline included the complete loss of variation in the mitochondrial genome and along long stretches of the nuclear genome. Several private and deleterious amino acid changes were fixed by random drift; predicted effects include energy deficit, muscle weakness, anomalies in cranial and skeletal development, and reduced aggressiveness. Despite this extreme loss of diversity, Apennine bear genomes show nonrandom peaks of high variation, possibly maintained by balancing selection, at genomic regions significantly enriched for genes associated with immune and olfactory systems. Challenging the paradigm of increased extinction risk in small populations, we suggest that random fixation of deleterious alleles (i) can be an important driver of divergence in isolation, (ii) can be tolerated when balancing selection prevents random loss of variation at important genes, and (iii) is followed by or results directly in favorable behavioral changes.

ImaGene: a convolutional neural network to quantify natural selection from genomic data.

BACKGROUND: The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determining such genetic bases is an evolutionary framework. As sites targeted by natural selection are likely to harbor important functionalities for the carrier, the identification of selection signatures in the genome has the potential to unveil the genetic mechanisms underpinning human phenotypes. Popular methods of detecting such signals rely on compressing genomic information into summary statistics, resulting in the loss of information. Furthermore, few methods are able to quantify the strength of selection. Here we explored the use of deep learning in evolutionary biology and implemented a program, called ImaGene, to apply convolutional neural networks on population genomic data for the detection and quantification of natural selection. RESULTS: ImaGene enables genomic information from multiple individuals to be represented as abstract images. Each image is created by stacking aligned genomic data and encoding distinct alleles into separate colors. To detect and quantify signatures of positive selection, ImaGene implements a convolutional neural network which is trained using simulations. We show how the method implemented in ImaGene can be affected by data manipulation and learning strategies. In particular, we show how sorting images by row and column leads to accurate predictions. We also demonstrate how the misspecification of the correct demographic model for producing training data can influence the quantification of positive selection. We finally illustrate an approach to estimate the selection coefficient, a continuous variable, using multiclass classification techniques. CONCLUSIONS: While the use of deep learning in evolutionary genomics is in its infancy, here we demonstrated its potential to detect informative patterns from large-scale genomic data. We implemented methods to process genomic data for deep learning in a user-friendly program called ImaGene. The joint inference of the evolutionary history of mutations and their functional impact will facilitate mapping studies and provide novel insights into the molecular mechanisms associated with human phenotypes.

Phenotypic sexual dimorphism is associated with genomic signatures of resolved sexual conflict.

Intralocus sexual conflict, where an allele benefits one sex at the expense of the other, has an important role in shaping genetic diversity of populations through balancing selection. However, the potential for mating systems to exert balancing selection through sexual conflict on the genome remains unclear. Furthermore, the nature and potential for resolution of sexual conflict across the genome has been hotly debated. To address this, we analysed de novo transcriptomes from six avian species, chosen to reflect the full range of sexual dimorphism and mating systems. Our analyses combine expression and population genomic statistics across reproductive and somatic tissue, with measures of sperm competition and promiscuity. Our results reveal that balancing selection is weakest in the gonad, consistent with the resolution of sexual conflict and evolutionary theory that phenotypic sex differences are associated with lower levels of ongoing conflict. We also demonstrate a clear link between variation in sexual conflict and levels of genetic variation across phylogenetic space in a comparative framework. Our observations suggest that this conflict is short-lived, and is resolved via the decoupling of male and female gene expression patterns, with important implications for the role of sexual selection in adaptive potential and role of dimorphism in facilitating sex-specific fitness optima.

Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse.

The rich fossil record of equids has made them a model for evolutionary processes. Here we present a 1.12-times coverage draft genome from a horse bone recovered from permafrost dated to approximately 560-780 thousand years before present (kyr BP). Our data represent the oldest full genome sequence determined so far by almost an order of magnitude. For comparison, we sequenced the genome of a Late Pleistocene horse (43 kyr BP), and modern genomes of five domestic horse breeds (Equus ferus caballus), a Przewalski's horse (E. f. przewalskii) and a donkey (E. asinus). Our analyses suggest that the Equus lineage giving rise to all contemporary horses, zebras and donkeys originated 4.0-4.5 million years before present (Myr BP), twice the conventionally accepted time to the most recent common ancestor of the genus Equus. We also find that horse population size fluctuated multiple times over the past 2 Myr, particularly during periods of severe climatic changes. We estimate that the Przewalski's and domestic horse populations diverged 38-72 kyr BP, and find no evidence of recent admixture between the domestic horse breeds and the Przewalski's horse investigated. This supports the contention that Przewalski's horses represent the last surviving wild horse population. We find similar levels of genetic variation among Przewalski's and domestic populations, indicating that the former are genetically viable and worthy of conservation efforts. We also find evidence for continuous selection on the immune system and olfaction throughout horse evolution. Finally, we identify 29 genomic regions among horse breeds that deviate from neutrality and show low levels of genetic variation compared to the Przewalski's horse. Such regions could correspond to loci selected early during domestication.

Archaic Adaptive Introgression in TBX15/WARS2.

A recent study conducted the first genome-wide scan for selection in Inuit from Greenland using single nucleotide polymorphism chip data. Here, we report that selection in the region with the second most extreme signal of positive selection in Greenlandic Inuit favored a deeply divergent haplotype that is closely related to the sequence in the Denisovan genome, and was likely introgressed from an archaic population. The region contains two genes, WARS2 and TBX15, and has previously been associated with adipose tissue differentiation and body-fat distribution in humans. We show that the adaptively introgressed allele has been under selection in a much larger geographic region than just Greenland. Furthermore, it is associated with changes in expression of WARS2 and TBX15 in multiple tissues including the adrenal gland and subcutaneous adipose tissue, and with regional DNA methylation changes in TBX15.

Uncovering the genetic history of the present-day Greenlandic population.

Because of past limitations in samples and genotyping technologies, important questions about the history of the present-day Greenlandic population remain unanswered. In an effort to answer these questions and in general investigate the genetic history of the Greenlandic population, we analyzed ∼200,000 SNPs from more than 10% of the adult Greenlandic population (n = 4,674). We found that recent gene flow from Europe has had a substantial impact on the population: more than 80% of the Greenlanders have some European ancestry (on average ∼25% of their genome). However, we also found that the amount of recent European gene flow varies across Greenland and is far smaller in the more historically isolated areas in the north and east and in the small villages in the south. Furthermore, we found that there is substantial population structure in the Inuit genetic component of the Greenlanders and that individuals from the east, west, and north can be distinguished from each other. Moreover, the genetic differences in the Inuit ancestry are consistent with a single colonization wave of the island from north to west to south to east. Although it has been speculated that there has been historical admixture between the Norse Vikings who lived in Greenland for a limited period ∼600-1,000 years ago and the Inuit, we found no evidence supporting this hypothesis. Similarly, we found no evidence supporting a previously hypothesized admixture event between the Inuit in East Greenland and the Dorset people, who lived in Greenland before the Inuit.

Oral microbiomes from hunter-gatherers and traditional farmers reveal shifts in commensal balance and pathogen load linked to diet.

Maladaptation to modern diets has been implicated in several chronic disorders. Given the higher prevalence of disease such as dental caries and chronic gum diseases in industrialized societies, we sought to investigate the impact of different subsistence strategies on oral health and physiology, as documented by the oral microbiome. To control for confounding variables such as environment and host genetics, we sampled saliva from three pairs of populations of hunter-gatherers and traditional farmers living in close proximity in the Philippines. Deep shotgun sequencing of salivary DNA generated high-coverage microbiomes along with human genomes. Comparing these microbiomes with publicly available data from individuals living on a Western diet revealed that abundance ratios of core species were significantly correlated with subsistence strategy, with hunter-gatherers and Westerners occupying either end of a gradient of Neisseria against Haemophilus, and traditional farmers falling in between. Species found preferentially in hunter-gatherers included microbes often considered as oral pathogens, despite their hosts' apparent good oral health. Discriminant analysis of gene functions revealed vitamin B5 autotrophy and urease-mediated pH regulation as candidate adaptations of the microbiome to the hunter-gatherer and Western diets, respectively. These results suggest that major transitions in diet selected for different communities of commensals and likely played a role in the emergence of modern oral pathogens.

Tracking the origins of Yakutian horses and the genetic basis for their fast adaptation to subarctic environments.

Yakutia, Sakha Republic, in the Siberian Far East, represents one of the coldest places on Earth, with winter record temperatures dropping below -70 °C. Nevertheless, Yakutian horses survive all year round in the open air due to striking phenotypic adaptations, including compact body conformations, extremely hairy winter coats, and acute seasonal differences in metabolic activities. The evolutionary origins of Yakutian horses and the genetic basis of their adaptations remain, however, contentious. Here, we present the complete genomes of nine present-day Yakutian horses and two ancient specimens dating from the early 19th century and ∼5,200 y ago. By comparing these genomes with the genomes of two Late Pleistocene, 27 domesticated, and three wild Przewalski's horses, we find that contemporary Yakutian horses do not descend from the native horses that populated the region until the mid-Holocene, but were most likely introduced following the migration of the Yakut people a few centuries ago. Thus, they represent one of the fastest cases of adaptation to the extreme temperatures of the Arctic. We find cis-regulatory mutations to have contributed more than nonsynonymous changes to their adaptation, likely due to the comparatively limited standing variation within gene bodies at the time the population was founded. Genes involved in hair development, body size, and metabolic and hormone signaling pathways represent an essential part of the Yakutian horse adaptive genetic toolkit. Finally, we find evidence for convergent evolution with native human populations and woolly mammoths, suggesting that only a few evolutionary strategies are compatible with survival in extremely cold environments.

Speciation with gene flow in equids despite extensive chromosomal plasticity.

Horses, asses, and zebras belong to a single genus, Equus, which emerged 4.0-4.5 Mya. Although the equine fossil record represents a textbook example of evolution, the succession of events that gave rise to the diversity of species existing today remains unclear. Here we present six genomes from each living species of asses and zebras. This completes the set of genomes available for all extant species in the genus, which was hitherto represented only by the horse and the domestic donkey. In addition, we used a museum specimen to characterize the genome of the quagga zebra, which was driven to extinction in the early 1900s. We scan the genomes for lineage-specific adaptations and identify 48 genes that have evolved under positive selection and are involved in olfaction, immune response, development, locomotion, and behavior. Our extensive genome dataset reveals a highly dynamic demographic history with synchronous expansions and collapses on different continents during the last 400 ky after major climatic events. We show that the earliest speciation occurred with gene flow in Northern America, and that the ancestor of present-day asses and zebras dispersed into the Old World 2.1-3.4 Mya. Strikingly, we also find evidence for gene flow involving three contemporary equine species despite chromosomal numbers varying from 16 pairs to 31 pairs. These findings challenge the claim that the accumulation of chromosomal rearrangements drive complete reproductive isolation, and promote equids as a fundamental model for understanding the interplay between chromosomal structure, gene flow, and, ultimately, speciation.

Prehistoric genomes reveal the genetic foundation and cost of horse domestication.

The domestication of the horse ∼ 5.5 kya and the emergence of mounted riding, chariotry, and cavalry dramatically transformed human civilization. However, the genetics underlying horse domestication are difficult to reconstruct, given the near extinction of wild horses. We therefore sequenced two ancient horse genomes from Taymyr, Russia (at 7.4- and 24.3-fold coverage), both predating the earliest archeological evidence of domestication. We compared these genomes with genomes of domesticated horses and the wild Przewalski's horse and found genetic structure within Eurasia in the Late Pleistocene, with the ancient population contributing significantly to the genetic variation of domesticated breeds. We furthermore identified a conservative set of 125 potential domestication targets using four complementary scans for genes that have undergone positive selection. One group of genes is involved in muscular and limb development, articular junctions, and the cardiac system, and may represent physiological adaptations to human utilization. A second group consists of genes with cognitive functions, including social behavior, learning capabilities, fear response, and agreeableness, which may have been key for taming horses. We also found that domestication is associated with inbreeding and an excess of deleterious mutations. This genetic load is in line with the "cost of domestication" hypothesis also reported for rice, tomatoes, and dogs, and it is generally attributed to the relaxation of purifying selection resulting from the strong demographic bottlenecks accompanying domestication. Our work demonstrates the power of ancient genomes to reconstruct the complex genetic changes that transformed wild animals into their domesticated forms, and the population context in which this process took place.

Estimating inbreeding coefficients from NGS data: Impact on genotype calling and allele frequency estimation.

Most methods for next-generation sequencing (NGS) data analyses incorporate information regarding allele frequencies using the assumption of Hardy-Weinberg equilibrium (HWE) as a prior. However, many organisms including those that are domesticated, partially selfing, or with asexual life cycles show strong deviations from HWE. For such species, and specially for low-coverage data, it is necessary to obtain estimates of inbreeding coefficients (F) for each individual before calling genotypes. Here, we present two methods for estimating inbreeding coefficients from NGS data based on an expectation-maximization (EM) algorithm. We assess the impact of taking inbreeding into account when calling genotypes or estimating the site frequency spectrum (SFS), and demonstrate a marked increase in accuracy on low-coverage highly inbred samples. We demonstrate the applicability and efficacy of these methods in both simulated and real data sets.

ngsTools: methods for population genetics analyses from next-generation sequencing data.

SUMMARY: Next-generation sequencing technologies produce short reads that are either de novo assembled or mapped to a reference genome. Genotypes and/or single-nucleotide polymorphisms are then determined from the read composition at each site, which become the basis for many downstream analyses. However, for low sequencing depths, e.g. , there is considerable statistical uncertainty in the assignment of genotypes because of random sampling of homologous base pairs in heterozygotes and sequencing or alignment errors. Recently, several probabilistic methods have been proposed to account for this uncertainty and make accurate inferences from low quality and/or coverage sequencing data. We present ngsTools, a collection of programs to perform population genetics analyses from next-generation sequencing data. The methods implemented in these programs do not rely on single-nucleotide polymorphism or genotype calling and are particularly suitable for low sequencing depth data. AVAILABILITY: Programs included in ngsTools are implemented in C/C++ and are freely available for noncommercial use at https://github.com/mfumagalli/ngsTools. CONTACT: mfumagalli82@gmail.com SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

A scan for human-specific relaxation of negative selection reveals unexpected polymorphism in proteasome genes.

Environmental or genomic changes during evolution can relax negative selection pressure on specific loci, permitting high frequency polymorphisms at previously conserved sites. Here, we jointly analyze population genomic and comparative genomic data to search for functional processes showing relaxed negative selection specifically in the human lineage, whereas remaining evolutionarily conserved in other mammals. Consistent with previous studies, we find that olfactory receptor genes display such a signature of relaxation in humans. Intriguingly, proteasome genes also show a prominent signal of human-specific relaxation: multiple proteasome subunits, including four members of the catalytic core particle, contain high frequency nonsynonymous polymorphisms at sites conserved across mammals. Chimpanzee proteasome genes do not display a similar trend. Human proteasome genes also bear no evidence of recent positive or balancing selection. These results suggest human-specific relaxation of negative selection in proteasome subunits; the exact biological causes, however, remain unknown.

Crohn's disease loci are common targets of protozoa-driven selection.

Previous studies indicated that a few risk variants for autoimmune diseases are subject to pathogen-driven selection. Nonetheless, the proportion of risk loci that has been targeted by pathogens and the type of infectious agent(s) that exerted the strongest pressure remain to be evaluated. We assessed whether different pathogens exerted a pressure on known Crohn's disease (CD) risk variants and demonstrate that these single-nucleotide polymorphisms (SNPs) are preferential targets of protozoa-driven selection (P = 0.008). In particular, 19% of SNPs associated with CD have been subject to protozoa-driven selective pressure. Analysis of P values from genome-wide association studies (GWASs) and meta-analyses indicated that protozoan-selected SNPs display significantly stronger association with CD compared with nonselected variants. This same behavior was not observed for GWASs of other autoimmune diseases. Thus, we integrated selection signatures and meta-analysis results to prioritize five genic SNPs for replication in an Italian cohort. Three SNPs were significantly associated with CD risk, and combination with meta-analysis results yielded P values < 4 × 10(-6). The bona fide risk alleles are located in ARHGEF2, an interactor of NOD2, NSF, a gene involved in autophagy, and HEBP1, encoding a possible mediator of inflammation. Pathway analysis indicated that ARHGEF2 and NSF participate in a molecular network, which also contains VAMP3 (previously associated to CD) and is centered around miR-31 (known to be disregulated in CD). Thus, we show that protozoa-driven selective pressure had a major role in shaping predisposition to CD. We next used this information for the identification of three bona fide novel susceptibility loci.

Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution.

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes.

Long-standing balancing selection in the THBS4 gene: influence on sex-specific brain expression and gray matter volumes in Alzheimer disease.

The THBS4 gene encodes a glycoprotein involved in inflammatory responses and synaptogenesis. THBS4 is expressed at higher levels in the brain of humans compared with nonhuman primates, and the protein accumulates in ß-amyloid plaques. We analyzed THBS4 genetic variability in humans and show that two haplotypes (hap1 and hap2) are maintained by balancing selection and modulate THBS4 expression in lymphocytes. Indeed, the balancing selection region covers a predicted transcriptional enhancer. In humans, but not in macaques and chimpanzees, THBS4 brain expression increases with age, and variants in the balancing selection region interact with sex in influencing THBS4 expression (pinteraction = 0.038), with hap1 homozygous females showing lowest expression. In Alzheimer disease (AD) patients, significant interactions between sex and THBS4 genotype were detected for peripheral gray matter (pinteraction = 0.014) and total gray matter (pinteraction = 0.012) volumes. Similarly to the gene expression results, the interaction is mainly mediated by hap1 homozygous AD females, who show reduced volumes. Thus, the balancing selection target in THBS4 is likely represented by one or more variants that regulate tissue-specific and sex-specific gene expression. The selection signature associated with THBS4 might not be related to AD pathogenesis, but rather to inflammatory responses.