Recent human adaptation: genomic approaches, interpretation and insights

Microbiome interactions with different risk factors in development of myocardial infarction

Among all non-communicable diseases, Cardiovascular Diseases (CVDs) stand as the leading global cause of mortality. Within this spectrum, Myocardial Infarction (MI) strikingly accounts for over 15 % of all deaths. The intricate web of risk factors for MI, comprising family history, tobacco use, oral health, hypertension, nutritional pattern, and microbial infections, is firmly influenced by the human gut and oral microbiota, their diversity, richness, and dysbiosis, along with their respective metabolites. Host genetic factors, especially allelic variations in signaling and inflammatory markers, greatly affect the progression or severity of the disease. Despite the established significance of the human microbiome-nutrient-metabolite interplay in associations with CVDs, the unexplored terrain of the gut-heart-oral axis has risen as a critical knowledge gap. Moreover, the pivotal role of the microbiome and the complex interplay with host genetics, compounded by age-related changes, emerges as an area of vital importance in the development of MI. In addition, a distinctive disease susceptibility and severity influenced by gender-based or ancestral differences, adds a crucial insights to the association with increased mortality. Here, we aimed to provide an overview on interactions of microbiome (oral and gut) with major risk factors (tobacco use, alcohol consumption, diet, hypertension host genetics, gender, and aging) in the development of MI and therapeutic regulation.

Star allele search: a pharmacogenetic annotation database and user-friendly search tool of publicly available 1000 Genomes Project biospecimens

Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n = 3,202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool ( www.coriell.org/StarAllele/Search ). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.

Differential Effects of ABCG5/G8 Gene Region Variants on Lipid Profile, Blood Pressure Status, and Gallstone Disease History in Taiwan

ABCG5 and ABCG8 are two key adenosine triphosphate-binding cassette (ABC) proteins that regulate whole-body sterol trafficking. This study aimed to elucidate the association between ABCG5/G8 gene region variants and lipid profile, cardiometabolic traits, and gallstone disease history in Taiwan. A total of 1494 Taiwan Biobank participants with whole-genome sequencing data and 117,679 participants with Axiom Genome-Wide CHB Array data were enrolled for analysis. Using genotype-phenotype and stepwise linear regression analyses, we found independent associations of four Asian-specific ABCG5 variants, rs119480069, rs199984328, rs560839317, and rs748096191, with total, low-density lipoprotein (LDL), and non-high-density lipoprotein (HDL) cholesterol levels (all p ≤ 0.0002). Four other variants, which were in nearly complete linkage disequilibrium, exhibited genome-wide significant associations with gallstone disease history, and the ABCG8 rs11887534 variant showed a trend of superiority for gallstone disease history in a nested logistic regression model (p = 0.074). Through regional association analysis of various other cardiometabolic traits, two variants of the PLEKHH2, approximately 50 kb from the ABCG5/G8 region, exhibited significant associations with blood pressure status (p < 10^-6). In conclusion, differential effects of ABCG5/G8 region variants were noted for lipid profile, blood pressure status, and gallstone disease history in Taiwan. These results indicate the crucial role of individualized assessment of ABCG5/G8 variants for different cardiometabolic phenotypes.

Pleiotropic Effects of APOB Variants on Lipid Profiles, Metabolic Syndrome, and the Risk of Diabetes Mellitus

Apolipoprotein B (ApoB) plays a crucial role in lipid and lipoprotein metabolism. The effects of APOB locus variants on lipid profiles, metabolic syndrome, and the risk of diabetes mellitus (DM) in Asian populations are unclear. We included 1478 Taiwan Biobank participants with whole-genome sequence (WGS) data and 115,088 TWB participants with Axiom genome-wide CHB array data and subjected them to genotype-phenotype analyses using APOB locus variants. Five APOB nonsynonymous mutations, including Asian-specific rs144467873 and rs13306194 variants, were selected from participants with the WGS data. Using a combination of regional association studies, a linkage disequilibrium map, and multivariate analysis, we revealed that the APOB locus variants rs144467873, rs13306194, and rs1367117 were independently associated with total, low-density lipoprotein (LDL), and non-high-density lipoprotein (non-HDL) cholesterol levels; rs1318006 was associated with HDL cholesterol levels; rs13306194 and rs35131127 were associated with serum triglyceride levels; rs144467873, rs13306194, rs56213756, and rs679899 were associated with remnant cholesterol levels; and rs144467873 and rs4665709 were associated with metabolic syndrome. Mendelian randomization (MR) analyses conducted using weighted genetic risk scores from three or two LDL-cholesterol-level-associated APOB variants revealed significant association with prevalent DM (p = 0.0029 and 8.2 × 10^-5, respectively), which became insignificant after adjustment for LDL-C levels. In conclusion, these results indicate that common and rare APOB variants are independently associated with various lipid levels and metabolic syndrome in Taiwanese individuals. MR analyses supported APOB variants associated with the risk of DM through their associations with LDL cholesterol levels.

Dissecting Complex Traits Using Omics Data: A Review on the Linear Mixed Models and Their Application in GWAS

Genome-wide association study (GWAS) is the most popular approach to dissecting complex traits in plants, humans, and animals. Numerous methods and tools have been proposed to discover the causal variants for GWAS data analysis. Among them, linear mixed models (LMMs) are widely used statistical methods for regulating confounding factors, including population structure, resulting in increased computational proficiency and statistical power in GWAS studies. Recently more attention has been paid to pleiotropy, multi-trait, gene-gene interaction, gene-environment interaction, and multi-locus methods with the growing availability of large-scale GWAS data and relevant phenotype samples. In this review, we have demonstrated all possible LMMs-based methods available in the literature for GWAS. We briefly discuss the different LMM methods, software packages, and available open-source applications in GWAS. Then, we include the advantages and weaknesses of the LMMs in GWAS. Finally, we discuss the future perspective and conclusion. The present review paper would be helpful to the researchers for selecting appropriate LMM models and methods quickly for GWAS data analysis and would benefit the scientific society.

What Geohistory Can Teach Us About Fundamental Causes of Health Inequities

The causes of cancer health inequities are complex, multilevel, and intersectional. The typical disciplines and data used to address these inequities focus on public health, health services, clinical, and fundamental science. Fundamental causes such as systemic racism are a source of much health inequity, but a broader scope of fundamental causes may be considered. Geohistorical events may intersect with other fundamental causes of health inequities. In this study, an example of relationships between ancient geological events, slavery, and subsequent effects of systematic racism are identified. These relationships support the hypothesis that health inequities have deep and complex origins. Geohistorical factors precede social, economic, and political influences on health inequities, and suggest that a full understanding of cancer health inequities and their elimination may be informed by geohistorical events. Thus, addressing inequities may involve disciplines not typically involved in health equity collaborations, including geography, history, economics, political science, and others.

Signatures of Convergent Evolution and Natural Selection at the Alcohol Dehydrogenase Gene Region are Correlated with Agriculture in Ethnically Diverse Africans

The alcohol dehydrogenase (ADH) family of genes encodes enzymes that catalyze the metabolism of ethanol into acetaldehyde. Nucleotide variation in ADH genes can affect the catalytic properties of these enzymes and is associated with a variety of traits, including alcoholism and cancer. Some ADH variants, including the ADH1B*48His (rs1229984) mutation in the ADH1B gene, reduce the risk of alcoholism and are under positive selection in multiple human populations. The advent of Neolithic agriculture and associated increase in fermented foods and beverages is hypothesized to have been a selective force acting on such variants. However, this hypothesis has not been tested in populations outside of Asia. Here, we use genome-wide selection scans to show that the ADH gene region is enriched for variants showing strong signals of positive selection in multiple Afroasiatic-speaking, agriculturalist populations from Ethiopia, and that this signal is unique among sub-Saharan Africans. We also observe strong selection signals at putatively functional variants in nearby lipid metabolism genes, which may influence evolutionary dynamics at the ADH region. Finally, we show that haplotypes carrying these selected variants were introduced into Northeast Africa from a West-Eurasian source within the last ∼2,000 years and experienced positive selection following admixture. These selection signals are not evident in nearby, genetically similar populations that practice hunting/gathering or pastoralist subsistence lifestyles, supporting the hypothesis that the emergence of agriculture shapes patterns of selection at ADH genes. Together, these results enhance our understanding of how adaptations to diverse environments and diets have influenced the African genomic landscape.

Impact of natural selection on global patterns of genetic variation and association with clinical phenotypes at genes involved in SARS-CoV-2 infection

Human genomic diversity has been shaped by both ancient and ongoing challenges from viruses. The current coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a devastating impact on population health. However, genetic diversity and evolutionary forces impacting host genes related to SARS-CoV-2 infection are not well understood. We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (angiotensin converting enzyme 2 [ACE2], transmembrane protease serine 2 [TMPRSS2], dipeptidyl peptidase 4 [DPP4], and lymphocyte antigen 6 complex locus E [LY6E]). We analyzed data from 2,012 ethnically diverse Africans and 15,977 individuals of European and African ancestry with electronic health records and integrated with global data from the 1000 Genomes Project. At ACE2, we identified 41 nonsynonymous variants that were rare in most populations, several of which impact protein function. However, three nonsynonymous variants (rs138390800, rs147311723, and rs145437639) were common among central African hunter-gatherers from Cameroon (minor allele frequency 0.083 to 0.164) and are on haplotypes that exhibit signatures of positive selection. We identify signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage compared with the chimpanzee genome. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19. Our study provides insights into global variation at host genes related to SARS-CoV-2 infection, which have been shaped by natural selection in some populations, possibly due to prior viral infections.

Similarity-based analysis of allele frequency distribution among multiple populations identifies adaptive genomic structural variants

Structural variants have a considerable impact on human genomic diversity. However, their evolutionary history remains mostly unexplored. Here, we developed a new method to identify potentially adaptive structural variants based on a similarity-based analysis that incorporates genotype frequency data from 26 populations simultaneously. Using this method, we analyzed 57,629 structural variants and identified 576 structural variants that show unusual population differentiation. Of these putatively adaptive structural variants, we further showed that 24 variants are multiallelic and overlap with coding sequences, and 20 variants are significantly associated with GWAS traits. Closer inspection of the haplotypic variation associated with these putatively adaptive and functional structural variants reveals deviations from neutral expectations due to: 1) population differentiation of rapidly evolving multiallelic variants, 2) incomplete sweeps, and 3) recent population-specific negative selection. Overall, our study provides new methodological insights, documents hundreds of putatively adaptive variants, and introduces evolutionary models that may better explain the complex evolution of structural variants.

Chromosome X-wide Analysis of Positive Selection in Human Populations: Common and Private Signals of Selection and its Impact on Inactivated Genes and Enhancers

The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic basis of population-specific adaptations genome-wide. Here, we present the analysis of recent selective sweeps, specifically in the X chromosome, in human populations from the third phase of the 1,000 Genomes Project using three different haplotype-based statistics. We describe instances of recent positive selection that fit the criteria of hard or soft sweeps, and detect a higher number of events among sub-Saharan Africans than non-Africans (Europe and East Asia). A global enrichment of neural-related processes is observed and numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection which might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.

Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection

We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (ACE2, TMPRSS2, DPP4, and LY6E). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2, we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.

Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection

We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection ( ACE2, TMPRSS2, DPP4 , and LY6E ). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2 , we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2 , we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.

Evolutionary genetics of skin pigmentation in African populations

Skin color is a highly heritable human trait, and global variation in skin pigmentation has been shaped by natural selection, migration and admixture. Ethnically diverse African populations harbor extremely high levels of genetic and phenotypic diversity, and skin pigmentation varies widely across Africa. Recent genome-wide genetic studies of skin pigmentation in African populations have advanced our understanding of pigmentation biology and human evolutionary history. For example, novel roles in skin pigmentation for loci near MFSD12 and DDB1 have recently been identified in African populations. However, due to an underrepresentation of Africans in human genetic studies, there is still much to learn about the evolutionary genetics of skin pigmentation. Here, we summarize recent progress in skin pigmentation genetics in Africans and discuss the importance of including more ethnically diverse African populations in future genetic studies. In addition, we discuss methods for functional validation of adaptive variants related to skin pigmentation.

Harnessing pluripotent stem cells as models to decipher human evolution

The study of human evolution, long constrained by a lack of experimental model systems, has been transformed by the emergence of the induced pluripotent stem cell (iPSC) field. iPSCs can be readily established from noninvasive tissue sources, from both humans and other primates; they can be maintained in the laboratory indefinitely, and they can be differentiated into other tissue types. These qualities mean that iPSCs are rapidly becoming established as viable and powerful model systems with which it is possible to address questions in human evolution that were until now logistically and ethically intractable, especially in the quest to understand humans' place among the great apes, and the genetic basis of human uniqueness. In this review, we discuss the key lessons and takeaways of this nascent field; from the types of research, iPSCs make possible to lingering challenges and likely future directions. We provide a comprehensive overview of how the seemingly unlikely combination of iPSCs and explicit evolutionary frameworks is transforming what is possible in our understanding of humanity's past and present.

Genomic Mechanisms of Physiological and Morphological Adaptations of Limestone Langurs to Karst Habitats

Knowledge of the physiological and morphological evolution and adaptation of nonhuman primates is critical to understand hominin origins, physiological ecology, morphological evolution, and applications in biomedicine. Particularly, limestone langurs represent a direct example of adaptations to the challenges of exploiting a high calcium and harsh environment. Here, we report a de novo genome assembly (Tfra_2.0) of a male François's langur (Trachypithecus francoisi) with contig N50 of 16.3 Mb and resequencing data of 23 individuals representing five limestone and four forest langur species. Comparative genomics reveals evidence for functional evolution in genes and gene families related to calcium signaling in the limestone langur genome, probably as an adaptation to naturally occurring high calcium levels present in water and plant resources in karst habitats. The genomic and functional analyses suggest that a single point mutation (Lys1905Arg) in the α1c subunit of the L-type voltage-gated calcium channel Cav1.2 (CACNA1C) attenuates the inward calcium current into the cells in vitro. Population genomic analyses and RNA-sequencing indicate that EDNRB is less expressed in white tail hair follicles of the white-headed langur (T. leucocephalus) compared with the black-colored François's langur and hence might be responsible for species-specific differences in body coloration. Our findings contribute to a new understanding of gene-environment interactions and physiomorphological adaptative mechanisms in ecologically specialized primate taxa.

An Asian-specific MPL genetic variant alters JAK-STAT signaling and influences platelet count in the population

Genomic discovery efforts for hematological traits have been successfully conducted through genome-wide association study on samples of predominantly European ancestry. We sought to conduct unbiased genetic discovery for coding variants that influence hematological traits in a Han Chinese population. A total of 5257 Han Chinese subjects from Beijing, China were included in the discovery cohort and analyzed by an Illumina ExomeChip array. Replication analyses were conducted in 3827 independent Chinese subjects. We analyzed 12 hematological traits and identified 22 exome-wide significant single-nucleotide polymorphisms (SNP)-trait associations with 15 independent SNPs. Our study provides replication for two associations previously reported but not replicated. Further, one association was identified and replicated in the current study, of a coding variant in the myeloproliferative leukemia (MPL) gene, c.793C > T, p.Leu265Phe (L265F) with increased platelet count (β = 20.6 109 cells/l, Pmeta-analysis = 2.6 × 10-13). This variant is observed at ~2% population frequency in East Asians, whereas it has not been reported in gnomAD European or African populations. Functional analysis demonstrated that expression of MPL L265F in Ba/F3 cells resulted in enhanced phosphorylation of Stat3 and ERK1/2 as compared with the reference MPL allele, supporting altered activation of the JAK-STAT signal transduction pathway as the mechanism underlying the novel association between MPL L265F and platelet count.

Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants

Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new ‘common treatment, common variant’ perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX’s in silico predictions.

Adaptive selection drives TRPP3 loss-of-function in an Ethiopian population

TRPP3 (also called PKD2L1) is a nonselective, cation-permeable channel activated by multiple stimuli, including extracellular pH changes. TRPP3 had been considered a candidate for sour sensor in humans, due to its high expression in a subset of tongue receptor cells detecting sour, along with its membership to the TRP channel family known to function as sensory receptors. Here, we describe the functional consequences of two non-synonymous genetic variants (R278Q and R378W) found to be under strong positive selection in an Ethiopian population, the Gumuz. Electrophysiological studies and 3D modelling reveal TRPP3 loss-of-functions produced by both substitutions. R278Q impairs TRPP3 activation after alkalinisation by mislocation of H⁺ binding residues at the extracellular polycystin mucolipin domain. R378W dramatically reduces channel activity by altering conformation of the voltage sensor domain and hampering channel transition from closed to open state. Sour sensitivity tests in R278Q/R378W carriers argue against both any involvement of TRPP3 in sour detection and the role of such physiological process in the reported evolutionary positive selection past event.

Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling Bias and Infection Clusters

A novel RNA virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the ongoing outbreak of coronavirus disease 2019 (COVID-19). Population genetic analysis could be useful for investigating the origin and evolutionary dynamics of COVID-19. However, due to extensive sampling bias and existence of infection clusters during the epidemic spread, direct applications of existing approaches can lead to biased parameter estimations and data misinterpretation. In this study, we first present robust estimator for the time to the most recent common ancestor (TMRCA) and the mutation rate, and then apply the approach to analyze 12,909 genomic sequences of SARS-CoV-2. The mutation rate is inferred to be 8.69 × 10-4 per site per year with a 95% confidence interval (CI) of [8.61 × 10-4, 8.77 × 10-4], and the TMRCA of the samples inferred to be Nov 28, 2019 with a 95% CI of [Oct 20, 2019, Dec 9, 2019]. The results indicate that COVID-19 might originate earlier than and outside of Wuhan Seafood Market. We further demonstrate that genetic polymorphism patterns, including the enrichment of specific haplotypes and the temporal allele frequency trajectories generated from infection clusters, are similar to those caused by evolutionary forces such as natural selection. Our results show that population genetic methods need to be developed to efficiently detangle the effects of sampling bias and infection clusters to gain insights into the evolutionary mechanism of SARS-CoV-2. Software for implementing VirusMuT can be downloaded at https://bigd.big.ac.cn/biocode/tools/BT007081.

Demographic history and admixture dynamics in African Sahelian populations

The Sahel/Savannah belt of Africa is a contact zone between two subsistence systems (nomadic pastoralism and sedentary farming) and of two groups of populations, namely Eurasians penetrating from northern Africa southwards and sub-Saharan Africans migrating northwards. Because pastoralism is characterized by a high degree of mobility, it leaves few significant archaeological traces. Demographic history seen through the lens of population genetic studies complements our historical and archaeological knowledge in this African region. In this review, we highlight recent advances in our understanding of demographic history in the Sahel/Savannah belt as revealed by genetic studies. We show the impact of food-producing subsistence strategies on population structure and the somewhat different migration patterns in the western and eastern part of the region. Genomic studies show that the gene pool of various groups of Sahelians consists in a complex mosaic of several ancestries. We also touch upon various signals of genetic adaptations such as lactase persistence, taste sensitivity and malaria resistance, all of which have different distribution patterns among Sahelian populations. Overall, genetic studies contribute to gain a deeper understanding about the demographic and adaptive history of human populations in this specific African region and beyond.

Identifying adaptive alleles in the human genome: from selection mapping to functional validation

The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.

Cross-Species Insights Into Genomic Adaptations to Hypoxia

Over millions of years, vertebrate species populated vast environments spanning the globe. Among the most challenging habitats encountered were those with limited availability of oxygen, yet many animal and human populations inhabit and perform life cycle functions and/or daily activities in varying degrees of hypoxia today. Of particular interest are species that inhabit high-altitude niches, which experience chronic hypobaric hypoxia throughout their lives. Physiological and molecular aspects of adaptation to hypoxia have long been the focus of high-altitude populations and, within the past decade, genomic information has become increasingly accessible. These data provide an opportunity to search for common genetic signatures of selection across uniquely informative populations and thereby augment our understanding of the mechanisms underlying adaptations to hypoxia. In this review, we synthesize the available genomic findings across hypoxia-tolerant species to provide a comprehensive view of putatively hypoxia-adaptive genes and pathways. In many cases, adaptive signatures across species converge on the same genetic pathways or on genes themselves [i.e., the hypoxia inducible factor (HIF) pathway). However, specific variants thought to underlie function are distinct between species and populations, and, in most cases, the precise functional role of these genomic differences remains unknown. Efforts to standardize these findings and explore relationships between genotype and phenotype will provide important clues into the evolutionary and mechanistic bases of physiological adaptations to environmental hypoxia.

Correlation Between the APOB rs1042034 SNP and Blood Lipid Characteristics of 2 Ethnic Groups in China

The apolipoprotein (Apo) B gene (APOB) is a susceptible gene for dyslipidemia. The purpose of this investigation was to explore the relationship between the APOB rs1042034 single-nucleotide polymorphism (SNP) and serum lipid levels in the Maonan and Han populations. A total of 598 Maonan participants and 609 Han participants were genotyped by polymerase chain reaction and restriction fragment length polymorphism, and the genotypes were also verified by sequencing. There were no differences in genotype and allele frequencies between the 2 ethnic groups or between males and females. The levels of triglyceride (TG) in Maonans were higher and high-density lipoprotein cholesterol was lower in the A allele carriers than the A allele noncarriers; the A allele carriers in Hans had higher TG levels and lower ApoA1/ApoB ratio than the A allele noncarriers (P < .05 for all). Subgroup analysis showed that the A allele carriers in Maonan females had higher TG levels and the A allele carriers in Han females had higher TG levels and lower ApoA1/ApoB ratio than the A allele noncarriers (P < .05 for all). In our study populations, there may be ethnicity- and/or sex-specific associations between the APOB rs1042034 SNP and serum lipid levels.

Single nucleotide polymorphisms in transcription factor genes associated with susceptibility to oral cancer

Oral cancer is a major public health concern in the Asian countries predominated by India which accounts for 33.81% of the annual global oral cancer burden. The well-established high-risk factors associated with oral cancer include tobacco, areca nut, alcohol consumption, and high-risk human papilloma virus types 16/18. Additionally, in the past two decades, the critical role of the genomic constitution of individuals in oral cancer susceptibility has emerged. Accumulating evidence indicates the association of several single nucleotide polymorphisms (SNPs) with oral cancer risk. Thus in the current study, we assessed the association of thirteen SNPs in seven transcription factor genes along with HBB (a control SNP) to identify high-risk genotypes associated with increased oral cancer risk in an Indian cohort of tobacco habitués. Fourteen SNPs were investigated in 500 patients with oral cancer and 500 clinically healthy long-term tobacco users as controls of Indian ethnicity. Allelic discrimination real-time polymerase chain reaction was the method of choice for genotyping the samples. Logistic regression analysis was performed and the association of SNPs with oral cancer risk was estimated using odds ratio (OR) and 95% confidence interval (CI). We observed five SNPs-rs2051526 (ETV6), rs6021247 (NFATC2), rs3757769 (SND1), rs7085532 (TCF7L2), and rs7778413 (SND1) indicating increased oral cancer risk with OR ranging from 1.61 to 34.60. Further, as a proof of concept, the coinheritance of high-risk genotypes in rs6021247 (NFATC2) GG (OR, 2.77; CI, 2.09-3.69) and rs7778413 (SND1) CC (OR, 34.60; CI, 17.32-69.13) reflected further increase in the risk with OR-49.94 (CI, 16.25-153.48). The present study indicates the association of transcription factor SNPs with increased oral cancer risk constituting "predictive biomarkers" in oral cancers.

Population History and Altitude-Related Adaptation in the Sherpa

The first ascent of Mount Everest by Tenzing Norgay and Sir Edmund Hillary in 1953 brought global attention to the Sherpa people and human performance at altitude. The Sherpa inhabit the Khumbu Valley of Nepal, and are descendants of a population that has resided continuously on the Tibetan plateau for the past ∼25,000 to 40,000 years. The long exposure of the Sherpa to an inhospitable environment has driven genetic selection and produced distinct adaptive phenotypes. This review summarizes the population history of the Sherpa and their physiological and genetic adaptation to hypoxia. Genomic studies have identified robust signals of positive selection across EPAS1, EGLN1, and PPARA, that are associated with hemoglobin levels, which likely protect the Sherpa from altitude sickness. However, the biological underpinnings of other adaptive phenotypes such as birth weight and the increased reproductive success of Sherpa women are unknown. Further studies are required to identify additional signatures of selection and refine existing Sherpa-specific adaptive phenotypes to understand how genetic factors have underpinned adaptation in this population. By correlating known and emerging signals of genetic selection with adaptive phenotypes, we can further reveal hypoxia-related biological mechanisms of adaptation. Ultimately this work could provide valuable information regarding treatments of hypoxia-related illnesses including stroke, heart failure, lung disease and cancer.

Nutrition and its role in human evolution

Our understanding of human evolution has improved rapidly over recent decades, facilitated by large-scale cataloguing of genomic variability amongst both modern and archaic humans. It seems clear that the evolution of the ancestors of chimpanzees and hominins separated 7-9 million years ago with some migration out of Africa by the earlier hominins; Homo sapiens slowly emerged as climate change resulted in drier, less forested African conditions. The African populations expanded and evolved in many different conditions with slow mutation and selection rates in the human genome, but with much more rapid mutation occurring in mitochondrial DNA. We now have evidence stretching back 300 000 years of humans in their current form, but there are clearly four very different large African language groups that correlate with population DNA differences. Then, about 50 000-100 000 years ago a small subset of modern humans also migrated out of Africa resulting in a persistent signature of more limited genetic diversity amongst non-African populations. Hybridization with archaic hominins occurred around this time such that all non-African modern humans possess some Neanderthal ancestry and Melanesian populations additionally possess some Denisovan ancestry. Human populations both within and outside Africa also adapted to diverse aspects of their local environment including altitude, climate, UV exposure, diet and pathogens, in some cases leaving clear signatures of patterns of genetic variation. Notable examples include haemoglobin changes conferring resistance to malaria, other immune changes and the skin adaptations favouring the synthesis of vitamin D. As humans migrated across Eurasia, further major mitochondrial changes occurred with some interbreeding with ancient hominins and the development of alcohol intolerance. More recently, an ability to retain lactase persistence into adulthood has evolved rapidly under the environmental stimulus of pastoralism with the ability to husband lactating ruminants. Increased amylase copy numbers seem to relate to the availability of starchy foods, whereas the capacity to desaturase and elongate monounsaturated fatty acids in different societies seems to be influenced by whether there is a lack of supply of readily available dietary sources of long-chain polyunsaturated fatty acids. The process of human evolution includes genetic drift and adaptation to local environments, in part through changes in mitochondrial and nuclear DNA. These genetic changes may underlie susceptibilities to some modern human pathologies including folate-responsive neural tube defects, diabetes, other age-related pathologies and mental health disorders.

Human cancer, the naked mole rat and faunal turnovers

We argue that the human evolutionary heritage with frequent adaptations through geological time to environmental change has affected a trade‐off between offspring variability and cancer resistance, and thus favored cancer‐prone individuals. We turn the attention to a factor setting the highly cancer‐resistant naked mole rat apart from most other mammals: it has remained phenotypically largely unchanged since 30‐50 million years ago. Research focusing on DNA stability mechanisms in ‘living fossil’ animals may help us find tools for cancer prevention and treatment.

Integrating Selection Mapping With Genetic Mapping and Functional Genomics

Genomic scans for signatures of selection allow us to, in principle, detect variants and genes that underlie recent adaptations. By combining selection mapping with genetic mapping of traits known to be relevant to adaptation, we can simultaneously investigate whether genes and variants show signals of recent selection and whether they impact traits that have likely been selected. There are three ways to integrate selection mapping with genetic mapping or functional genomics: (1) To use genetic mapping data from other populations as a form of genome annotation. (2) To perform experimental evolution or artificial selection to be able to study selected variants when they segregate, either by performing genetic mapping before selection or by crossing the selected individuals to some reference population. (3) To perform a comparative study of related populations facing different selection regimes. This short review discusses these different ways of integrating selection mapping with genetic mapping and functional genomics, with examples of how each has been done.

Genomes reveal marked differences in the adaptive evolution between orangutan species

BACKGROUND

Integrating demography and adaptive evolution is pivotal to understanding the evolutionary history and conservation of great apes. However, little is known about the adaptive evolution of our closest relatives, in particular if and to what extent adaptions to environmental differences have occurred. Here, we used whole-genome sequencing data from critically endangered orangutans from North Sumatra (Pongo abelii) and Borneo (P. pygmaeus) to investigate adaptive responses of each species to environmental differences during the Pleistocene.

RESULTS

Taking into account the markedly disparate demographic histories of each species after their split ~ 1 Ma ago, we show that persistent environmental differences on each island had a strong impact on the adaptive evolution of the genus Pongo. Across a range of tests for positive selection, we find a consistent pattern of between-island and species differences. In the more productive Sumatran environment, the most notable signals of positive selection involve genes linked to brain and neuronal development, learning, and glucose metabolism. On Borneo, however, positive selection comprised genes involved in lipid metabolism, as well as cardiac and muscle activities.

CONCLUSIONS

We find strikingly different sets of genes appearing to have evolved under strong positive selection in each species. In Sumatran orangutans, selection patterns were congruent with well-documented cognitive and behavioral differences between the species, such as a larger and more complex cultural repertoire and higher degrees of sociality. However, in Bornean orangutans, selective responses to fluctuating environmental conditions appear to have produced physiological adaptations to generally lower and temporally more unpredictable food supplies.

Evidence of Polygenic Adaptation to High Altitude from Tibetan and Sherpa Genomes

Although Tibetans and Sherpa present several physiological adjustments evolved to cope with selective pressures imposed by the high-altitude environment, especially hypobaric hypoxia, few selective sweeps at a limited number of hypoxia related genes were confirmed by multiple genomic studies. Nevertheless, variants at these loci were found to be associated only with downregulation of the erythropoietic cascade, which represents an indirect aspect of the considered adaptive phenotype. Accordingly, the genetic basis of Tibetan/Sherpa adaptive traits remains to be fully elucidated, in part due to limitations of selection scans implemented so far and mostly relying on the hard sweep model.

In order to overcome this issue, we used whole-genome sequence data and several selection statistics as input for gene network analyses aimed at testing for the occurrence of polygenic adaptation in these high-altitude Himalayan populations. Being able to detect also subtle genomic signatures ascribable to weak positive selection at multiple genes of the same functional subnetwork, this approach allowed us to infer adaptive evolution at loci individually showing small effect sizes, but belonging to highly interconnected biological pathways overall involved in angiogenetic processes.

Therefore, these findings pinpointed a series of selective events neglected so far, which likely contributed to the augmented tissue blood perfusion observed in Tibetans and Sherpa, thus uncovering the genetic determinants of a key biological mechanism that underlies their adaptation to high altitude.

Fine-tuning of Approximate Bayesian Computation for human population genomics

Approximate Bayesian Computation (ABC) is a flexible statistical tool widely applied to addressing a variety of questions regarding the origin and evolution of humans. The significant growth of genomic scale data from diverse geographic populations has facilitated the use of ABC in modelling the complex processes that underlie human demography and local adaptation. However, a fundamental issue still remains in how to efficiently capture patterns of genetic variation with a set of summary statistics in order to achieve better approximation of Bayesian inference. Here, we review recent advances in ABC methodology and its applications for human population genomics, with a particular focus on optimal tuning of ABC approaches for different types of genetic data and different sets of evolutionary parameters.

Cultural Genomics: Promises and Challenges

In this article, we attempt to integrate recent advances in our understanding of the relations between culture and genes into an emerging field—cultural genomics—and discuss its promises and theoretical and methodological challenges. We first provide a brief review of previous conceptualizations about the relations between culture and genes and then argue that recent advances in molecular evolution research has allowed us to reframe the discussion away from parallel genetic and cultural evolution to focus on the interactions between the two. After outlining the key issues involved in cultural genomics (unit of analysis, timescale, mechanisms, and direction of influence), we provide examples of research for the different levels of interactions between culture and genes. We then discuss ideological, theoretical, and methodological challenges in cultural genomics and propose tentative solutions.

FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations

We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated "gold standard" positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.

Adaptation of Arabidopsis thaliana to the Yangtze River basin

Background

Organisms need to adapt to keep pace with a changing environment. Examining recent range expansion aids our understanding of how organisms evolve to overcome environmental constraints. However, how organisms adapt to climate changes is a crucial biological question that is still largely unanswered. The plant Arabidopsis thaliana is an excellent system to study this fundamental question. Its origin is in the Iberian Peninsula and North Africa, but it has spread to the Far East, including the most south-eastern edge of its native habitats, the Yangtze River basin, where the climate is very different.

Results

We sequenced 118 A. thaliana strains from the region surrounding the Yangtze River basin. We found that the Yangtze River basin population is a unique population and diverged about 61,409 years ago, with gene flows occurring at two different time points, followed by a population dispersion into the Yangtze River basin in the last few thousands of years. Positive selection analyses revealed that biological regulation processes, such as flowering time, immune and defense response processes could be correlated with the adaptation event. In particular, we found that the flowering time gene SVP has contributed to A. thaliana adaptation to the Yangtze River basin based on genetic mapping.

Conclusions

A. thaliana adapted to the Yangtze River basin habitat by promoting the onset of flowering, a finding that sheds light on how a species can adapt to locales with very different climates.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1378-9) contains supplementary material, which is available to authorized users.

Detecting Recent Positive Selection with a Single Locus Test Bipartitioning the Coalescent Tree

Many population genomic studies have been conducted in the past to search for traces of recent events of positive selection. These traces, however, can be obscured by temporal variation of population size or other demographic factors. To reduce the confounding impact of demography, the coalescent tree topology has been used as an additional source of information for detecting recent positive selection in a population or a species. Based on the branching pattern at the root, we partition the hypothetical coalescent tree, inferred from a sequence sample, into two subtrees. The reasoning is that positive selection could impose a strong impact on branch length in one of the two subtrees while demography has the same effect on average on both subtrees. Thus, positive selection should be detectable by comparing statistics calculated for the two subtrees. Simulations demonstrate that the proposed test based on these principles has high power to detect recent positive selection even when DNA polymorphism data from only one locus is available, and that it is robust to the confounding effect of demography. One feature is that all components in the summary statistics ([Formula: see text]) can be computed analytically. Moreover, misinference of derived and ancestral alleles is seen to have only a limited effect on the test, and it therefore avoids a notorious problem when searching for traces of recent positive selection.

Harnessing ancient genomes to study the history of human adaptation

The past several years have witnessed an explosion of successful ancient human genome-sequencing projects, with genomic-scale ancient DNA data sets now available for more than 1,100 ancient human and archaic hominin (for example, Neandertal) individuals. Recent 'evolution in action' analyses have started using these data sets to identify and track the spatiotemporal trajectories of genetic variants associated with human adaptations to novel and changing environments, agricultural lifestyles, and introduced or co-evolving pathogens. Together with evidence of adaptive introgression of genetic variants from archaic hominins to humans and emerging ancient genome data sets for domesticated animals and plants, these studies provide novel insights into human evolution and the evolutionary consequences of human behaviour that go well beyond those that can be obtained from modern genomic data or the fossil and archaeological records alone.

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.

Inferring the Joint Demographic History of Multiple Populations: Beyond the Diffusion Approximation

Understanding variation in allele frequencies across populations is a central goal of population genetics. Classical models for the distribution of allele frequencies, using forward simulation, coalescent theory, or the diffusion approximation, have been applied extensively for demographic inference, medical study design, and evolutionary studies. Here we propose a tractable model of ordinary differential equations for the evolution of allele frequencies that is closely related to the diffusion approximation but avoids many of its limitations and approximations. We show that the approach is typically faster, more numerically stable, and more easily generalizable than the state-of-the-art software implementation of the diffusion approximation. We present a number of applications to human sequence data, including demographic inference with a five-population joint frequency spectrum and a discussion of the robustness of the out-of-Africa model inference to the choice of modern population.

Living in an adaptive world: Genomic dissection of the genus Homo and its immune response

More than a decade after the sequencing of the human genome, a deluge of genome-wide population data are generating a portrait of human genetic diversity at an unprecedented level of resolution. Genomic studies have provided new insight into the demographic and adaptive history of our species, Homo sapiens, including its interbreeding with other hominins, such as Neanderthals, and the ways in which natural selection, in its various guises, has shaped genome diversity. These studies, combined with functional genomic approaches, such as the mapping of expression quantitative trait loci, have helped to identify genes, functions, and mechanisms of prime importance for host survival and involved in phenotypic variation and differences in disease risk. This review summarizes new findings in this rapidly developing field, focusing on the human immune response. We discuss the importance of defining the genetic and evolutionary determinants driving immune response variation, and highlight the added value of population genomic approaches in settings relevant to immunity and infection.

Single nucleotide polymorphisms in an Indian cohort and association of CNTN4, MMP2 and SNTB1 variants with oral cancer

Oral cancer is a high incidence cancer in India primarily due to the prevalent tobacco/areca nut chewing habits and hence a major health concern. India constitutes 26% of the global oral cancer burden. Besides the well-established risk factors, the genomic constitution of an individual plays a role in oral cancer. The aim of the current study was to analyse genomic variants represented as single nucleotide polymorphisms (SNPs), analyse their prevalence and investigate risk association of allelotypes/genotypes to oral cancers. Eleven SNPs in genes associated with biological functions were analysed in an Indian cohort (n = 1000) comprising 500 oral cancer patients and 500 long term tobacco habitués as controls, using Allelic discrimination Real-Time PCR assay with SYBR Green dye. Fisher's exact test and Odds Ratio were used for statistical analysis. Increased risk was observed for rs9849237 CC [P = 0.008; OR 1.412 (1.09-1.82)] and rs243865 CT [P = 0.004; OR 1.469 (1.13-1.90)] genotypes, whereas rs9849237 CT [P = 0.034; OR 0.755 (0.58-0.97)], rs243865 CC [P = 0.002; OR 0.669 (0.51-0.86)] and rs10090787 CC [P = 0.049; OR 0.774 (0.60-0.99)] genotypes indicated decreased risk to oral cancer. The other SNPs showed equidistribution in both groups. Our data indicated genotypes and alleles in specific SNPs rs9849237, rs243865 and rs10090787 with increased/decreased risk to oral cancer.

Genomic translational research: Paving the way to individualized cardiac functional analyses and personalized cardiology

For most of Medicine's past, the best that physicians could do to cope with disease prevention and treatment was based on the expected response of an average patient. Currently, however, a more personalized/precise approach to cardiology and medicine in general is becoming possible, as the cost of sequencing a human genome has declined substantially. As a result, we are witnessing an era of precipitous advances in biomedicine and bourgeoning understanding of the genetic basis of cardiovascular and other diseases, reminiscent of the resurgence of innovations in physico-mathematical sciences and biology-anatomy-cardiology in the Renaissance, a parallel time of radical change and reformation of medical knowledge, education and practice. Now on the horizon is an individualized, diverse patient-centered, approach to medical practice that encompasses the development of new, gene-based diagnostics and preventive medicine tactics, and offers the broadest range of personalized therapies based on pharmacogenetics. Over time, translation of genomic and high-tech approaches unquestionably will transform clinical practice in cardiology and medicine as a whole, with the adoption of new personalized medicine approaches and procedures. Clearly, future prospects far outweigh present accomplishments, which are best viewed as a promising start. It is now essential for pluridisciplinary health care providers to examine the drivers and barriers to the clinical adoption of this emerging revolutionary paradigm, in order to expedite the realization of its potential. So, we are not there yet, but we are definitely on our way.

Inferences of African evolutionary history from genomic data

Africa is the origin of anatomically modern humans and a continent of linguistic, cultural, environmental, phenotypic, and genetic diversity. However, African populations remain underrepresented in genetic studies, which have largely focused on individuals with European and Asian ancestry. The expansion of high-throughput 'omic' technologies to interrogate multiple tissue types across many biomolecules-DNA, proteins, epigenetic modifications, metabolites, and others-has heralded a new era of investigation into African history. In this review, we summarize how some of these recent advances have been applied to contemporary sub-Saharan African populations to inform studies on human origins and adaptation.

Sherpas share genetic variations with Tibetans for high-altitude adaptation

Background

Sherpas, a highlander population living in Khumbu region of Nepal, are well known for their superior climbing ability in Himalayas. However, the genetic basis of their adaptation to high‐altitude environments remains elusive.

Methods

We collected DNA samples of 582 Sherpas from Nepal and Tibetan Autonomous Region of China, and we measured their hemoglobin levels and degrees of blood oxygen saturation. We genotyped 29 EPAS1 SNPs, two EGLN1 SNPs and the TED polymorphism (3.4 kb deletion) in Sherpas. We also performed genetic association analysis among these sequence variants with phenotypic data.

Results

We found similar allele frequencies on the tested 32 variants of these genes in Sherpas and Tibetans. Sherpa individuals carrying the derived alleles of EPAS1 (rs113305133, rs116611511 and rs12467821), EGLN1 (rs186996510 and rs12097901) and TED have lower hemoglobin levels when compared with those wild‐type allele carriers. Most of the EPAS1 variants showing significant association with hemoglobin levels in Tibetans were replicated in Sherpas.

Conclusion

The shared sequence variants and hemoglobin trait between Sherpas and Tibetans indicate a shared genetic basis for high‐altitude adaptation, consistent with the proposal that Sherpas are in fact a recently derived population from Tibetans and they inherited adaptive variants for high‐altitude adaptation from their Tibetan ancestors.

Neurogenomics and the role of a large mutational target on rapid behavioral change

BACKGROUND

Behavior, while complex and dynamic, is among the most diverse, derived, and rapidly evolving traits in animals. The highly labile nature of heritable behavioral change is observed in such evolutionary phenomena as the emergence of converged behaviors in domesticated animals, the rapid evolution of preferences, and the routine development of ethological isolation between diverging populations and species. In fact, it is believed that nervous system development and its potential to evolve a seemingly infinite array of behavioral innovations played a major role in the successful diversification of metazoans, including our own human lineage. However, unlike other rapidly evolving functional systems such as sperm-egg interactions and immune defense, the genetic basis of rapid behavioral change remains elusive.

PRESENTATION OF THE HYPOTHESIS

Here we propose that the rapid divergence and widespread novelty of innate and adaptive behavior is primarily a function of its genomic architecture. Specifically, we hypothesize that the broad diversity of behavioral phenotypes present at micro- and macroevolutionary scales is promoted by a disproportionately large mutational target of neurogenic genes. We present evidence that these large neuro-behavioral targets are significant and ubiquitous in animal genomes and suggest that behavior's novelty and rapid emergence are driven by a number of factors including more selection on a larger pool of variants, a greater role of phenotypic plasticity, and/or unique molecular features present in large genes. We briefly discuss the origins of these large neurogenic genes, as they relate to the remarkable diversity of metazoan behaviors, and highlight key consequences on both behavioral traits and neurogenic disease across, respectively, evolutionary and ontogenetic time scales.

TESTING THE HYPOTHESIS

Current approaches to studying the genetic mechanisms underlying rapid phenotypic change primarily focus on identifying signatures of Darwinian selection in protein-coding regions. In contrast, the large mutational target hypothesis places genomic architecture and a larger allelic pool at the forefront of rapid evolutionary change, particularly in genetic systems that are polygenic and regulatory in nature. Genomic data from brain and neural tissues in mammals as well as a preliminary survey of neurogenic genes from comparative genomic data support this hypothesis while rejecting both positive and relaxed selection on proteins or higher mutation rates. In mammals and invertebrates, neurogenic genes harbor larger protein-coding regions and possess a richer regulatory repertoire of miRNA targets and transcription factor binding sites. Overall, neurogenic genes cover a disproportionately large genomic fraction, providing a sizeable substrate for evolutionary, genetic, and molecular mechanisms to act upon. Readily available comparative and functional genomic data provide unexplored opportunities to test whether a distinct neurogenomic architecture can promote rapid behavioral change via several mechanisms unique to large genes, and which components of this large footprint are uniquely metazoan.

IMPLICATIONS OF THE HYPOTHESIS

The large mutational target hypothesis highlights the eminent roles of mutation and functional genomic architecture in generating rapid developmental and evolutionary change. It has broad implications on our understanding of the genetics of complex adaptive traits such as behavior by focusing on the importance of mutational input, from SNPs to alternative transcripts to transposable elements, on driving evolutionary rates of functional systems. Such functional divergence has important implications in promoting behavioral isolation across short- and long-term timescales. Due to genome-scaled polygenic adaptation, the large target effect also contributes to our inability to identify adapted behavioral candidate genes. The presence of large neurogenic genes, particularly in the mammalian brain and other neural tissues, further offers emerging insight into the etiology of neurodevelopmental and neurodegenerative diseases. The well-known correlation between neurological spectrum disorders in children and paternal age may simply be a direct result of aging fathers accumulating mutations across these large neurodevelopmental genes. The large mutational target hypothesis can also explain the rapid evolution of other functional systems covering a large genomic fraction such as male fertility and its preferential association with hybrid male sterility among closely related taxa. Overall, a focus on mutational potential may increase our power in understanding the genetic basis of complex phenotypes such as behavior while filling a general gap in understanding their evolution.

Understanding rare and common diseases in the context of human evolution

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

Population Structure of UK Biobank and Ancient Eurasians Reveals Adaptation at Genes Influencing Blood Pressure

Analyzing genetic differences between closely related populations can be a powerful way to detect recent adaptation. The very large sample size of the UK Biobank is ideal for using population differentiation to detect selection and enables an analysis of the UK population structure at fine resolution. In this study, analyses of 113,851 UK Biobank samples showed that population structure in the UK is dominated by five principal components (PCs) spanning six clusters: Northern Ireland, Scotland, northern England, southern England, and two Welsh clusters. Analyses of ancient Eurasians revealed that populations in the northern UK have higher levels of Steppe ancestry and that UK population structure cannot be explained as a simple mixture of Celts and Saxons. A scan for unusual population differentiation along the top PCs identified a genome-wide-significant signal of selection at the coding variant rs601338 in FUT2 (p = 9.16 × 10-9). In addition, by combining evidence of unusual differentiation within the UK with evidence from ancient Eurasians, we identified genome-wide-significant (p = 5 × 10-8) signals of recent selection at two additional loci: CYP1A2-CSK and F12. We detected strong associations between diastolic blood pressure in the UK Biobank and both the variants with selection signals at CYP1A2-CSK (p = 1.10 × 10-19) and the variants with ancient Eurasian selection signals at the ATXN2-SH2B3 locus (p = 8.00 × 10-33), implicating recent adaptation related to blood pressure.