Detecting and characterizing genomic signatures of positive selection in global populations

Inferring past demography and genetic adaptation in Spain using the GCAT cohort

Located in the southwestern corner of Europe, the Iberian Peninsula is separated from the rest of the continent by the Pyrenees Mountains and from Africa by the Strait of Gibraltar. This geographical position may have conditioned distinct selective pressures compared to the rest of Europe and influenced differential patterns of gene flow. In this work, we analyse 704 whole-genome sequences from the GCAT reference panel to quantify gene flow into Spain from various historical sources and identify the top signatures of positive (adaptive) selection. While we found no clear evidence of a 16th-century admixture event putatively related to the French diaspora during the Wars of Religion, we detected signals of North African admixture matching the Muslim period and the subsequent Christian Reconquista. Notably, besides finding that well-known candidate genes previously described in Eurasians also seem to be adaptive in Spain, we discovered novel top candidates for positive selection putatively associated with immunity and diet (UBL7, SMYD1, VAC14 and FDFT1). Finally, local ancestry deviation analysis revealed that the MHCIII genomic region underwent post-admixture selection following the post-Neolithic admixture with Steppe ancestry.

Natural selection and adaptive traits in the Maniq, a nomadic hunter-gatherer society from Mainland Southeast Asia

Asia is home to diverse hunter-gatherer populations characterized by significant morphological, anthropological, cultural, and linguistic diversity. Despite their importance in understanding ancestral human subsistence, little is known about the essential genetic adaptations of these groups. This study investigates the evolutionary pressures shaping the genome of the Maniq population, a nomadic hunter-gatherer group inhabiting the rainforests of southern Thailand. Using genome-wide approaches, including iHS, xp-EHH, PBE, and beta statistics, we identified signatures of positive and balancing selection. Genes under positive selection were enriched in pathways related to immunity, metabolic regulation, structural adaptation, cardiovascular performance, and neuromodulatory traits. Several genes associated with the Southeast Asian 'negrito-like' phenotype were also under positive selection. Balancing selection was primarily detected in immune-related genes, particularly within the HLA region, underscoring the critical role of genetic diversity in surviving pathogen-rich environments. Additionally, balancing selection in olfactory receptor genes highlights their importance in environmental sensing and adaptation. These results reveal the intricate interplay of positive and balancing selection in shaping the genetic landscape of the Maniq population and highlight their adaptations to the ecological and lifestyle challenges of life in the rainforest. This study contributes to our understanding of human evolutionary processes in tropical environments and hunter-gatherer societies.

Digital Image Processing to Detect Adaptive Evolution

In recent years, advances in image processing and machine learning have fueled a paradigm shift in detecting genomic regions under natural selection. Early machine learning techniques employed population-genetic summary statistics as features, which focus on specific genomic patterns expected by adaptive and neutral processes. Though such engineered features are important when training data are limited, the ease at which simulated data can now be generated has led to the recent development of approaches that take in image representations of haplotype alignments and automatically extract important features using convolutional neural networks. Digital image processing methods termed α-molecules are a class of techniques for multiscale representation of objects that can extract a diverse set of features from images. One such α-molecule method, termed wavelet decomposition, lends greater control over high-frequency components of images. Another α-molecule method, termed curvelet decomposition, is an extension of the wavelet concept that considers events occurring along curves within images. We show that application of these α-molecule techniques to extract features from image representations of haplotype alignments yield high true positive rate and accuracy to detect hard and soft selective sweep signatures from genomic data with both linear and nonlinear machine learning classifiers. Moreover, we find that such models are easy to visualize and interpret, with performance rivaling those of contemporary deep learning approaches for detecting sweeps.

Computational Genomics and Its Applications to Anthropological Questions

The advent of affordable genome sequencing and the development of new computational tools have established a new era of genomic knowledge. Sequenced human genomes number in the tens of thousands, including thousands of ancient human genomes. The abundance of data has been met with new analysis tools that can be used to understand populations' demographic and evolutionary histories. Thus, a variety of computational methods now exist that can be leveraged to answer anthropological questions. This includes novel likelihood and Bayesian methods, machine learning techniques, and a vast array of population simulators. These computational tools provide powerful insights gained from genomic datasets, although they are generally inaccessible to those with less computational experience. Here, we outline the theoretical workings behind computational genomics methods, limitations and other considerations when applying these computational methods, and examples of how computational methods have already been applied to anthropological questions. We hope this review will empower other anthropologists to utilize these powerful tools in their own research.

IBD sharing patterns as intra-breed admixture indicators in small ruminants

In this study, we investigated how IBD patterns shared between individuals of the same breed could be informative of its admixture level, with the underlying assumption that the most admixed breeds, i.e. the least genetically isolated, should have a much more fragmented genome. We considered 111 goat breeds (i.e. 2501 individuals) and 156 sheep breeds (i.e. 3304 individuals) from Europe, Africa and Asia, for which beadchip SNP genotypes had been performed. We inferred the breed's level of admixture from: (i) the proportion of the genome shared by breed's members (i.e. "genetic integrity level" assessed from ADMIXTURE software analyses), and (ii) the "AV index" (calculated from Reynolds' genetic distances), used as a proxy for the "genetic distinctiveness". In both goat and sheep datasets, the statistical analyses (comparison of means, Spearman correlations, LM and GAM models) revealed that the most genetically isolated breeds, also showed IBD profiles made up of more shared IBD segments, which were also longer. These results pave the way for further research that could lead to the development of admixture indicators, based on the characterization of intra-breed shared IBD segments, particularly effective as they would be independent of the knowledge of the whole genetic landscape in which the breeds evolve. Finally, by highlighting the fragmentation experienced by the genomes subjected to crossbreeding carried out over the last few generations, the study reminds us of the need to preserve local breeds and the integrity of their adaptive architectures that have been shaped over the centuries.

A genome-wide comparison between selected and unselected Valle del Belice sheep reveals differences in population structure and footprints of recent selection

About three decades of breeding and selection in the Valle del Belìce sheep are expected to have left several genomic footprints related to milk production traits. In this study, we have assembled a dataset with 451 individuals of the Valle del Belìce sheep breed: 184 animals that underwent directional selection for milk production and 267 unselected animals, genotyped for 40,660 single-nucleotide polymorphisms (SNPs). Three different statistical approaches, both within (iHS and ROH) and between (Rsb) groups, were used to identify genomic regions potentially under selection. Population structure analyses separated all individuals according to their belonging to the two groups. A total of four genomic regions on two chromosomes were jointly identified by at least two statistical approaches. Several candidate genes for milk production were identified, corroborating the polygenic nature of this trait and which may provide clues to potential new selection targets. We also found candidate genes for growth and reproductive traits. Overall, the identified genes may explain the effect of selection to improve the performances related to milk production traits in the breed. Further studies using high-density array data, would be particularly relevant to refine and validate these results.

Exploring genome-wide differentiation and signatures of selection in Italian and North American Holstein populations

Among Italian dairy cattle, the Holstein is the most reared breed for the production of Parmigiano Reggiano protected designation of origin cheese, which represents one of the most renowned products in the entire Italian dairy industry. In this work, we used a medium-density genome-wide data set consisting of 79,464 imputed SNPs to study the genetic structure of Italian Holstein breed, including the population reared in the area of Parmigiano Reggiano cheese production, and assessing its distinctiveness from the North American population. Multidimensional scaling and ADMIXTURE approaches were used to explore the genetic structure among populations. We also investigated putative genomic regions under selection among these 3 populations by combining 4 different statistical methods based either on allele frequencies (single marker and window-based) or extended haplotype homozygosity (EHH; standardized log-ratio of integrated EHH and cross-population EHH). The genetic structure results allowed us to clearly distinguish the 3 Holstein populations; however, the most remarkable difference was observed between Italian and North American stock. Selection signature analyses identified several significant SNPs falling within or closer to genes with known roles in several traits such as milk quality, resistance to disease, and fertility. In particular, a total of 22 genes related to milk production have been identified using the 2 allele frequency approaches. Among these, a convergent signal has been found in the VPS8 gene which resulted to be involved in milk traits, whereas other genes (CYP7B1, KSR2, C4A, LIPE, DCDC1, GPR20, and ST3GAL1) resulted to be associated with quantitative trait loci related to milk yield and composition in terms of fat and protein percentage. In contrast, a total of 7 genomic regions were identified combining the results of standardized log-ratio of integrated EHH and cross-population EHH. In these regions candidate genes for milk traits were also identified. Moreover, this was also confirmed by the enrichment analyses in which we found that the majority of the significantly enriched quantitative trait loci were linked to milk traits, whereas the gene ontology and pathway enrichment analysis pointed to molecular functions and biological processes involved in AA transmembrane transport and methane metabolism pathway. This study provides information on the genetic structure of the examined populations, showing that they are distinguishable from each other. Furthermore, the selection signature analyses can be considered as a starting point for future studies in the identification of causal mutations and consequent implementation of more practical application.

Characterization of large-scale genomic differences in the first complete human genome

BACKGROUND

The first telomere-to-telomere (T2T) human genome assembly (T2T-CHM13) release is a milestone in human genomics. The T2T-CHM13 genome assembly extends our understanding of telomeres, centromeres, segmental duplication, and other complex regions. The current human genome reference (GRCh38) has been widely used in various human genomic studies. However, the large-scale genomic differences between these two important genome assemblies are not characterized in detail yet.

RESULTS

Here, in addition to the previously reported "non-syntenic" regions, we find 67 additional large-scale discrepant regions and precisely categorize them into four structural types with a newly developed website tool called SynPlotter. The discrepant regions (~ 21.6 Mbp) excluding telomeric and centromeric regions are highly structurally polymorphic in humans, where the deletions or duplications are likely associated with various human diseases, such as immune and neurodevelopmental disorders. The analyses of a newly identified discrepant region-the KLRC gene cluster-show that the depletion of KLRC2 by a single-deletion event is associated with natural killer cell differentiation in ~ 20% of humans. Meanwhile, the rapid amino acid replacements observed within KLRC3 are probably a result of natural selection in primate evolution.

CONCLUSION

Our study provides a foundation for understanding the large-scale structural genomic differences between the two crucial human reference genomes, and is thereby important for future human genomics studies.

Selection signature analysis and genome-wide divergence of South African Merino breeds from their founders

Merino sheep are a breed of choice across the world, popularly kept for their wool and mutton value. They are often reared as a pure breed or used in crossbreeding and are a common component in synthetic breed development. This study evaluated genetic diversity, population structure, and breed divergence in 279 animals of Merino and Merino-based sheep breeds in South Africa using the Illumina Ovine SNP 50K BeadChip. The sheep breeds analysed included the three Merino-derived breeds of Dohne Merino (n = 50); Meatmaster (n = 47); and Afrino (n = 52) and five presumed ancestral populations of Merinos (Merino (n = 46); South African Merino (n = 10); and South African Mutton Merino (n = 8)); and the non-Merino founding breeds of Damara (n = 20); Ronderib Afrikaner (n = 17); and Nguni (n = 29). Highest genetic diversity values were observed in the Dohne Merino (DM), with H _o = 0.39 ± 0.01, followed by the Meatmaster and South African Merino (SAM), with H _o = 0.37 ± 0.03. The level of inbreeding ranged from 0.0 ± 0.02 (DM) to 0.27 ± 0.05 (Nguni). Analysis of molecular variance (AMOVA) showed high within-population variance (>80%) across all population categories. The first principal component (PC1) separated the Merino, South African Mutton Merino (SAMM), DM, and Afrino (AFR) from the Meatmaster, Damara, Nguni, and Ronderib Afrikaner (RDA). PC2 aligned each Merino-derived breed with its presumed ancestors and separated the SAMM from the Merino and SAM. The iHS analysis yielded selection sweeps across the AFR (12 sweeps), Meatmaster (four sweeps), and DM (29 sweeps). Hair/wool trait genes such as FGF12; metabolic genes of ICA1, NXPH1, and GPR171; and immune response genes of IL22, IL26, IFNAR1, and IL10RB were reported. Other genes include HMGA, which was observed as selection signatures in other populations; WNT5A, important in the development of the skeleton and mammary glands; ANTXR2, associated with adaptation to variation in climatic conditions; and BMP2, which has been reported as strongly selected in both fat-tailed and thin-tailed sheep. The DM vs. SAMM shared all six sweep regions on chromosomes 1, 10, and 11 with AFR vs. SAMM. Genes such as FGF12 on OAR 1:191.3-194.7 Mb and MAP2K4 on OAR 11:28.6-31.3 Mb were observed. The selection sweep on chromosome 10 region 28.6-30.3 Mb harbouring the RXFP2 for polledness was shared between the DM vs. Merino, the Meatmaster vs. Merino, and the Meatmaster vs. Nguni. The DM vs. Merino and the Meatmaster vs. Merino also shared an Rsb-based selection sweep on chromosome 1 region 268.5-269.9 Mb associated with the Calpain gene, CAPN7. The study demonstrated some genetic similarities between the Merino and Merino-derived breeds emanating from common founding populations and some divergence driven by breed-specific selection goals. Overall, information regarding the evolution of these composite breeds from their founding population will guide future breed improvement programs and management and conservation efforts.

Recombination and mutation shape variations in the major histocompatibility complex

The major histocompatibility complex (MHC) is closely associated with numerous diseases, but its high degree of polymorphism complicates the discovery of disease-associated variants. In principle, recombination and de novo mutations are two critical factors responsible for MHC polymorphisms. However, direct evidence for this hypothesis is lacking. Here, we report the generation of fine-scale MHC recombination and de novo mutation maps of ∼5 Mb by deep sequencing (> 100×) of the MHC genome for 17 MHC recombination and 30 non-recombination Han Chinese families (a total of 190 individuals). Recombination hotspots and Han-specific breakpoints are located in close proximity at haplotype block boundaries. The average MHC de novo mutation rate is higher than the genome-wide de novo mutation rate, particularly in MHC recombinant individuals. Notably, mutation and recombination generated polymorphisms are located within and outside linkage disequilibrium regions of the MHC, respectively, and evolution of the MHC locus was mainly controlled by positive selection. These findings provide insights on the evolutionary causes of the MHC diversity and may facilitate the identification of disease-associated genetic variants.

Analysis of Common SNPs across Continents Reveals Major Genomic Differences between Human Populations

Common alleles tend to be more ancient than rare alleles. These common SNPs appeared thousands of years ago and reflect intricate human evolution including various adaptations, admixtures, and migration events. Eighty-four thousand abundant region-specific alleles (ARSAs) that are common in one continent but absent in the rest of the world have been characterized by processing 3100 genomes from 230 populations. Also computed were 17,446 polymorphic sites with regional absence of common alleles (RACAs), which are widespread globally but absent in one region. A majority of these region-specific SNPs were found in Africa. America has the second greatest number of ARSAs (3348) and is even ahead of Europe (1911). Surprisingly, East Asia has the highest number of RACAs (10,524) and the lowest number of ARSAs (362). ARSAs and RACAs have distinct compositions of ancestral versus derived alleles in different geographical regions, reflecting their unique evolution. Genes associated with ARSA and RACA SNPs were identified and their functions were analyzed. The core 100 genes shared by multiple populations and associated with region-specific natural selection were examined. The largest part of them (42%) are related to the nervous system. ARSA and RACA SNPs are important for both association and human evolution studies.

Music Aptitude, Training, and Cognitive Transfer: A Mini-Review

In this mini-review, the genetic basis of music aptitude and the effects of music training are discussed. The review indicates that regardless of levels of innate ability, experience-induced neuroplasticity can occur as a result of music training. When that happens, it can be expressed as functional or structural brain changes. These changes are often accompanied by improvement in performance in tasks involving auditory analysis. Specifically, music training effects can transfer to a closely related cognitive domain such as auditory processing (near transfer). Music training can also affect more distantly related cognitive domains such as spatial and linguistic domains. Lastly, music training can affect general intelligence ("g") (far transfer). Music training can mold behavioral brain development and confers cognitive benefits beyond music.

Detection of selection signatures in South African Mutton Merino sheep using whole-genome sequencing data

The South African Mutton Merino (SAMM), a dual-purpose (meat and wool) sheep breed, is characterized by its excellent performance on growth, carcass traits and meat quality compared to other fine-wool Merino breeds. Nowadays, the SAMM breed has been widely used to cross with commercial and indigenous fine-wool or coarse-wool breeds to improve the growth and meat performance in many countries. To date, however, little is known about the genetic basis for its prominent characteristics. In this study, whole-genome sequences of 10 SAMM were sequenced and the selection signatures were analyzed together with those of 39 Australian Merino and Chinese Merino (wool-type Merino) by F_ST , iHS, and XP-EHH methods. In total, 313 genes in 277 regions were identified by at least 2 methods with the signal of selection and 21 of them were identified by all three methods. We highlighted a list of interesting genes, including GHR, LCORL, SMO, NCAPG, DCC, IBSP, PPARGC1A, PACRGL, PRDM5, XYLB, AHCYL2, TEFM, AFG1L, and FAM184B, which have been shown to be involved in growth, carcass traits, and meat quality by previous studies. Herein, GHR, encoding a transmembrane receptor for growth hormone, is the most notable one. We report the first study on selection signatures analysis of SAMM at whole-genome sequence level. These results provide new insights into the genetic mechanisms underlying the growth and carcass traits in SAMM.

Robust detection of natural selection using a probabilistic model of tree imbalance

Neutrality tests such as Tajima's D and Fay and Wu's H are standard implements in the population genetics toolbox. One of their most common uses is to scan the genome for signals of natural selection. However, it is well understood that D and H are confounded by other evolutionary forces-in particular, population expansion-that may be unrelated to selection. Because they are not model-based, it is not clear how to deconfound these tests in a principled way. In this article, we derive new likelihood-based methods for detecting natural selection, which are robust to fluctuations in effective population size. At the core of our method is a novel probabilistic model of tree imbalance, which generalizes Kingman's coalescent to allow certain aberrant tree topologies to arise more frequently than is expected under neutrality. We derive a frequency spectrum-based estimator that can be used in place of D, and also extend to the case where genealogies are first estimated. We benchmark our methods on real and simulated data, and provide an open source software implementation.

Using deep learning to identify recent positive selection in malaria parasite sequence data

BACKGROUND

Malaria, caused by Plasmodium parasites, is a major global public health problem. To assist an understanding of malaria pathogenesis, including drug resistance, there is a need for the timely detection of underlying genetic mutations and their spread. With the increasing use of whole-genome sequencing (WGS) of Plasmodium DNA, the potential of deep learning models to detect loci under recent positive selection, historically signals of drug resistance, was evaluated.

METHODS

A deep learning-based approach (called "DeepSweep") was developed, which can be trained on haplotypic images from genetic regions with known sweeps, to identify loci under positive selection. DeepSweep software is available from https://github.com/WDee/Deepsweep .

RESULTS

Using simulated genomic data, DeepSweep could detect recent sweeps with high predictive accuracy (areas under ROC curve > 0.95). DeepSweep was applied to Plasmodium falciparum (n = 1125; genome size 23 Mbp) and Plasmodium vivax (n = 368; genome size 29 Mbp) WGS data, and the genes identified overlapped with two established extended haplotype homozygosity methods (within-population iHS, across-population Rsb) (~ 60-75% overlap of hits at P < 0.0001). DeepSweep hits included regions proximal to known drug resistance loci for both P. falciparum (e.g. pfcrt, pfdhps and pfmdr1) and P. vivax (e.g. pvmrp1).

CONCLUSION

The deep learning approach can detect positive selection signatures in malaria parasite WGS data. Further, as the approach is generalizable, it may be trained to detect other types of selection. With the ability to rapidly generate WGS data at low cost, machine learning approaches (e.g. DeepSweep) have the potential to assist parasite genome-based surveillance and inform malaria control decision-making.

Integration of multi-omics approaches for functional characterization of muscle related selective sweep genes in Nanchukmacdon

Pig as a food source serves daily dietary demand to a wide population around the world. Preference of meat depends on various factors with muscle play the central role. In this regards, selective breeding abled us to develop "Nanchukmacdon" a pig breeds with an enhanced variety of meat and high fertility rate. To identify genomic regions under selection we performed whole-genome resequencing, transcriptome, and whole-genome bisulfite sequencing from Nanchukmacdon muscles samples and used published data for three other breeds such as Landrace, Duroc, Jeju native pig and analyzed the functional characterization of candidate genes. In this study, we present a comprehensive approach to identify candidate genes by using multi-omics approaches. We performed two different methods XP-EHH, XP-CLR to identify traces of artificial selection for traits of economic importance. Moreover, RNAseq analysis was done to identify differentially expressed genes in the crossed breed population. Several genes (UGT8, ZGRF1, NDUFA10, EBF3, ELN, UBE2L6, NCALD, MELK, SERP2, GDPD5, and FHL2) were identified as selective sweep and differentially expressed in muscles related pathways. Furthermore, nucleotide diversity analysis revealed low genetic diversity in Nanchukmacdon for identified genes in comparison to related breeds and whole-genome bisulfite sequencing data shows the critical role of DNA methylation pattern in identified genes that leads to enhanced variety of meat. This work demonstrates a way to identify the molecular signature and lays a foundation for future genomic enabled pig breeding.

Genome-Wide Natural Selection Signatures Are Linked to Genetic Risk of Modern Phenotypes in the Japanese Population

Elucidation of natural selection signatures and relationships with phenotype spectra is important to understand adaptive evolution of modern humans. Here, we conducted a genome-wide scan of selection signatures of the Japanese population by estimating locus-specific time to the most recent common ancestor using the ascertained sequentially Markovian coalescent (ASMC), from the biobank-based large-scale genome-wide association study data of 170,882 subjects. We identified 29 genetic loci with selection signatures satisfying the genome-wide significance. The signatures were most evident at the alcohol dehydrogenase (ADH) gene cluster locus at 4q23 (P_ASMC = 2.2 × 10⁻³⁶), followed by relatively strong selection at the FAM96A (15q22), MYOF (10q23), 13q21, GRIA2 (4q32), and ASAP2 (2p25) loci (P_ASMC < 1.0 × 10⁻¹⁰). The additional analysis interrogating extended haplotypes (integrated haplotype score) showed robust concordance of the detected signatures, contributing to fine-mapping of the genes, and provided allelic directional insights into selection pressure (e.g., positive selection for ADH1B-Arg48His and HLA-DPB1*04:01). The phenome-wide selection enrichment analysis with the trait-associated variants identified a variety of the modern human phenotypes involved in the adaptation of Japanese. We observed population-specific evidence of enrichment with the alcohol-related phenotypes, anthropometric and biochemical clinical measurements, and immune-related diseases, differently from the findings in Europeans using the UK Biobank resource. Our study demonstrated population-specific features of the selection signatures in Japanese, highlighting a value of the natural selection study using the nation-wide biobank-scale genome and phenotype data.

Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds

Domestication and selection are the major driving forces responsible for the determinative genetic variability in livestock. These selection patterns create unique genetic signatures within the genome. BovineSNP50 chip data from 236 animals (seven indicine and five taurine cattle breeds) were analyzed in the present study. We implemented three complementary approaches viz. iHS (Integrated haplotype score), ROH (Runs of homozygosity), and F_ST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and F_ST methods, respectively. We found several candidate genes (e.g., NCR3, ARID5A, HIST1H2BN, DEFB4, DEFB7, HSPA1L, HSPA1B, and DNAJB4) related to production traits and the adaptation of indigenous breeds to local environmental constraints such as heat stress and disease susceptibility. However, further studies are warranted to refine the findings using a larger sample size, whole-genome sequencing, and/or high density genotyping.

A Genomic Study of Myxomatous Mitral Valve Disease in Cavalier King Charles Spaniels

Cavalier King Charles spaniels (CKCSs) show the earliest onset and the highest incidence of myxomatous mitral valve disease (MMVD). Previous studies have suggested a polygenic inheritance of the disease in this breed and revealed an association with regions on canine chromosomes 13 and 14. Following clinical and echocardiographic examinations, 33 not-directly-related CKCSs were selected and classified as cases (n = 16) if MMVD was present before 5 years of age or as controls (n = 17) if no or very mild MMVD was present after 5 years of age. DNA was extracted from whole blood and genotyped with a Canine 230K SNP BeadChip instrument. Cases and controls were compared with three complementary genomic analyses (Wright's fixation index-F_ST, cross-population extended haplotype homozygosity-XP-EHH, and runs of homozygosity-ROH) to identify differences in terms of heterozygosity and regions of homozygosity. The top 1% single-nucleotide polymorphisms (SNPs) were selected and mapped, and the genes were thoroughly investigated. Ten consensus genes were found localized on chromosomes 3-11-14-19, partially confirming previous studies. The HEPACAM2, CDK6, and FAH genes, related to the transforming growth factor β (TGF-β) pathway and heart development, also emerged in the ROH analysis. In conclusion, this work expands the knowledge of the genetic basis of MMVD by identifying genes involved in the early onset of MMVD in CKCSs.

Identifying and Classifying Shared Selective Sweeps from Multilocus Data

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term [Formula: see text] and [Formula: see text] to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.

Antagonistic Pleiotropy in Human Disease

Between the 1930s and 1950s, scientists developed key principles of population genetics to try and explain the aging process. Almost a century later, these aging theories, including antagonistic pleiotropy and mutation accumulation, have been experimentally validated in animals. Although the theories have been much harder to test in humans despite research dating back to the 1970s, recent research is closing this evidence gap. Here we examine the strength of evidence for antagonistic pleiotropy in humans, one of the leading evolutionary explanations for the retention of genetic risk variation for non-communicable diseases. We discuss the analytical tools and types of data that are used to test for patterns of antagonistic pleiotropy and provide a primer of evolutionary theory on types of selection as a guide for understanding this mechanism and how it may manifest in other diseases. We find an abundance of non-experimental evidence for antagonistic pleiotropy in many diseases. In some cases, several studies have independently found corroborating evidence for this mechanism in the same or related sets of diseases including cancer and neurodegenerative diseases. Recent studies also suggest antagonistic pleiotropy may be involved in cardiovascular disease and diabetes. There are also compelling examples of disease risk variants that confer fitness benefits ranging from resistance to other diseases or survival in extreme environments. This provides increasingly strong support for the theory that antagonistic pleiotropic variants have enabled improved fitness but have been traded for higher burden of disease later in life. Future research in this field is required to better understand how this mechanism influences contemporary disease and possible consequences for their treatment.

Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa

Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.

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

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

Interethnic analyses of blood pressure loci in populations of East Asian and European descent

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, the authors perform discovery GWAS for BP in East Asians and meta-analysis in East Asians and Europeans and report ancestry-specific BP SNPs and selection signals.

McSwan: A joint site frequency spectrum method to detect and date selective sweeps across multiple population genomes

Inferring the mode and tempo of natural selection helps further our understanding of adaptation to past environmental changes. Here, we introduce McSwan, a method to detect and date past and recent natural selection events in the case of a hard sweep. The method is based on the comparison of site frequency spectra obtained under various demographic models that include selection. McSwan demonstrated high power (high sensitivity and specificity) in capturing hard selective sweep events without requiring haplotype phasing. It performed slightly better than SweeD when the recent effective population size was low and the genomic region was small. We then applied our method to a European (CEU) and an African (LWK) human re-sequencing data set. Most hard sweeps were detected in the CEU population (96%). Moreover, hard sweeps in the African population were estimated to have occurred further back in time (mode: 43,625 years BP) compared to those of Europeans (mode: 24,850 years BP). Most of the estimated ages of hard sweeps in Europeans were associated with the Last Glacial Maximum and were enriched in immunity-associated genes.

A Comprehensive Map of Genetic Variation in the World's Largest Ethnic Group-Han Chinese

As are most non-European populations, the Han Chinese are relatively understudied in population and medical genetics studies. From low-coverage whole-genome sequencing of 11,670 Han Chinese women we present a catalog of 25,057,223 variants, including 548,401 novel variants that are seen at least 10 times in our data set. Individuals from this data set came from 24 out of 33 administrative divisions across China (including 19 provinces, 4 municipalities, and 1 autonomous region), thus allowing us to study population structure, genetic ancestry, and local adaptation in Han Chinese. We identified previously unrecognized population structure along the East-West axis of China, demonstrated a general pattern of isolation-by-distance among Han Chinese, and reported unique regional signals of admixture, such as European influences among the Northwestern provinces of China. Furthermore, we identified a number of highly differentiated, putatively adaptive, loci (e.g., MTHFR, ADH7, and FADS, among others) that may be driven by immune response, climate, and diet in the Han Chinese. Finally, we have made available allele frequency estimates stratified by administrative divisions across China in the Geography of Genetic Variant browser for the broader community. By leveraging the largest currently available genetic data set for Han Chinese, we have gained insights into the history and population structure of the world's largest ethnic group.

Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity

Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and some may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics proposed in 2015 by Garud et al., which have power to detect both hard and soft sweeps, to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analog to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that, under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.

Genome-wide association studies and CRISPR/Cas9-mediated gene editing identify regulatory variants influencing eyebrow thickness in humans

Hair plays an important role in primates and is clearly subject to adaptive selection. While humans have lost most facial hair, eyebrows are a notable exception. Eyebrow thickness is heritable and widely believed to be subject to sexual selection. Nevertheless, few genomic studies have explored its genetic basis. Here, we performed a genome-wide scan for eyebrow thickness in 2961 Han Chinese. We identified two new loci of genome-wide significance, at 3q26.33 near SOX2 (rs1345417: P = 6.51×10(-10)) and at 5q13.2 near FOXD1 (rs12651896: P = 1.73×10(-8)). We further replicated our findings in the Uyghurs, a population from China characterized by East Asian-European admixture (N = 721), the CANDELA cohort from five Latin American countries (N = 2301), and the Rotterdam Study cohort of Dutch Europeans (N = 4411). A meta-analysis combining the full GWAS results from the three cohorts of full or partial Asian descent (Han Chinese, Uyghur and Latin Americans, N = 5983) highlighted a third signal of genome-wide significance at 2q12.3 (rs1866188: P = 5.81×10(-11)) near EDAR. We performed fine-mapping and prioritized four variants for further experimental verification. CRISPR/Cas9-mediated gene editing provided evidence that rs1345417 and rs12651896 affect the transcriptional activity of the nearby SOX2 and FOXD1 genes, which are both involved in hair development. Finally, suitable statistical analyses revealed that none of the associated variants showed clear signals of selection in any of the populations tested. Contrary to popular speculation, we found no evidence that eyebrow thickness is subject to strong selective pressure.

Identity-by-descent analyses for measuring population dynamics and selection in recombining pathogens

Identification of genomic regions that are identical by descent (IBD) has proven useful for human genetic studies where analyses have led to the discovery of familial relatedness and fine-mapping of disease critical regions. Unfortunately however, IBD analyses have been underutilized in analysis of other organisms, including human pathogens. This is in part due to the lack of statistical methodologies for non-diploid genomes in addition to the added complexity of multiclonal infections. As such, we have developed an IBD methodology, called isoRelate, for analysis of haploid recombining microorganisms in the presence of multiclonal infections. Using the inferred IBD status at genomic locations, we have also developed a novel statistic for identifying loci under positive selection and propose relatedness networks as a means of exploring shared haplotypes within populations. We evaluate the performance of our methodologies for detecting IBD and selection, including comparisons with existing tools, then perform an exploratory analysis of whole genome sequencing data from a global Plasmodium falciparum dataset of more than 2500 genomes. This analysis identifies Southeast Asia as having many highly related isolates, possibly as a result of both reduced transmission from intensified control efforts and population bottlenecks following the emergence of antimalarial drug resistance. Many signals of selection are also identified, most of which overlap genes that are known to be associated with drug resistance, in addition to two novel signals observed in multiple countries that have yet to be explored in detail. Additionally, we investigate relatedness networks over the selected loci and determine that one of these sweeps has spread between continents while the other has arisen independently in different countries. IBD analysis of microorganisms using isoRelate can be used for exploring population structure, positive selection and haplotype distributions, and will be a valuable tool for monitoring disease control and elimination efforts of many diseases.

There are growing concerns over the emergence of antimicrobial drug resistance, which threatens the efficacy of treatments for infectious diseases such as malaria. As such, it is important to understand the dynamics of resistance by investigating population structure, natural selection and disease transmission in microorganisms. The study of disease dynamics has been hampered by the lack of suitable statistical models for analysis of isolates containing multiple infections. We introduce a statistical model that uses population genomic data to identify genomic regions (loci) that are inherited from a common ancestor, in the presence of multiple infections. We demonstrate its potential for biological discovery using a global Plasmodium falciparum dataset. We identify low genetic diversity in isolates from Southeast Asia, possibly from clonal expansion following intensified control efforts after the emergence of artemisinin resistance. We also identify loci under positive selection, most of which contain genes that have been associated with antimalarial drug resistance. We discover two loci under strong selection in multiple countries throughout Southeast Asia and Africa where the selection pressure is currently unknown. We find that the selection pressure at one of these loci has originated from gene flow, while the other loci has originated from multiple independent events.

Patterns of shared signatures of recent positive selection across human populations

Signatures of recent positive selection often overlap across human populations, but the question of how often these overlaps represent a single ancestral event remains unresolved. If a single selective event spread across many populations, the same sweeping haplotype should appear in each population and the selective pressure could be common across populations and environments. Identifying such shared selective events could identify genomic loci and human traits important in recent history across the globe. In addition, genomic annotations that recently became available could help attach these signatures to a potential gene and molecular phenotype selected across populations. Here, we present a catalogue of selective sweeps in humans, and identify those that overlap and share a sweeping haplotype. We connect these sweep overlaps with potential biological mechanisms at several loci, including potential new sites of adaptive introgression, the glycophorin locus associated with malarial resistance and the alcohol dehydrogenase cluster associated with alcohol dependency.

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.

The fine-scale genetic structure and evolution of the Japanese population

The contemporary Japanese populations largely consist of three genetically distinct groups—Hondo, Ryukyu and Ainu. By principal-component analysis, while the three groups can be clearly separated, the Hondo people, comprising 99% of the Japanese, form one almost indistinguishable cluster. To understand fine-scale genetic structure, we applied powerful haplotype-based statistical methods to genome-wide single nucleotide polymorphism data from 1600 Japanese individuals, sampled from eight distinct regions in Japan. We then combined the Japanese data with 26 other Asian populations data to analyze the shared ancestry and genetic differentiation. We found that the Japanese could be separated into nine genetic clusters in our dataset, showing a marked concordance with geography; and that major components of ancestry profile of Japanese were from the Korean and Han Chinese clusters. We also detected and dated admixture in the Japanese. While genetic differentiation between Ryukyu and Hondo was suggested to be caused in part by positive selection, genetic differentiation among the Hondo clusters appeared to result principally from genetic drift. Notably, in Asians, we found the possibility that positive selection accentuated genetic differentiation among distant populations but attenuated genetic differentiation among close populations. These findings are significant for studies of human evolution and medical genetics.

Analysis of population-specific pharmacogenomic variants using next-generation sequencing data

Functional rare variants in drug-related genes are believed to be highly differentiated between ethnic- or racial populations. However, knowledge of population differentiation (PD) of rare single-nucleotide variants (SNVs), remains widely lacking, with the highest fixation indices, (F_st values), from both rare and common variants annotated to specific genes, having only been marginally used to understand PD at the gene level. In this study, we suggest a new, gene-based PD method, PD of Rare and Common variants (PDRC), for analyzing rare variants, as inspired by Generalized Cochran-Mantel-Haenszel (GCMH) statistics, to identify highly population-differentiated drug response-related genes (“pharmacogenes”). Through simulation studies, we reveal that PDRC adequately summarizes rare and common variants, due to PD, over a specific gene. We also applied the proposed method to a real whole-exome sequencing dataset, consisting of 10,000 datasets, from the Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) initiative, and 3,000 datasets from the Genetics of Type 2 diabetes (Go-T2D) repository. Among the 48 genes annotated with Very Important Pharmacogenetic summaries (VIPgenes), in the PharmGKB database, our PD method successfully identified candidate genes with high PD, including ACE, CYP2B6, DPYD, F5, MTHFR, and SCN5A.

Revealing phenotype-associated functional differences by genome-wide scan of ancient haplotype blocks

Genome-wide scans for positive selection have become important for genomic medicine, and many studies aim to find genomic regions affected by positive selection that are associated with risk allele variations among populations. Most such studies are designed to detect recent positive selection. However, we hypothesize that ancient positive selection is also important for adaptation to pathogens, and has affected current immune-mediated common diseases. Based on this hypothesis, we developed a novel linkage disequilibrium-based pipeline, which aims to detect regions associated with ancient positive selection across populations from single nucleotide polymorphism (SNP) data. By applying this pipeline to the genotypes in the International HapMap project database, we show that genes in the detected regions are enriched in pathways related to the immune system and infectious diseases. The detected regions also contain SNPs reported to be associated with cancers and metabolic diseases, obesity-related traits, type 2 diabetes, and allergic sensitization. These SNPs were further mapped to biological pathways to determine the associations between phenotypes and molecular functions. Assessments of candidate regions to identify functions associated with variations in incidence rates of these diseases are needed in the future.

The genomic landscape of evolutionary convergence in mammals, birds and reptiles

Many lineage-defining (nodal) mutations possess high functionality. However, differentiating adaptive nodal mutations from those that are functionally compensated remains challenging. To address this challenge, we identified functional nodal mutations (fNMs) in ~3,400 nuclear DNA (nDNA) and 4 mitochondrial DNA (mtDNA) protein structures from 91 and 1,003 species, respectively, representing the entire mammalian, bird and reptile phylogeny. A screen for candidate compensatory mutations among co-occurring amino acid changes in close structural proximity revealed that such compensated fNMs encompass 37% and 27% of the mtDNA and nDNA datasets, respectively. Analysis of the remaining (non-compensated) mutations, which are enriched for adaptive mutations, showed that birds and mammals share most such recurrent fNMs (N = 51). Among the latter, we discovered mutations in thermoregulation-related genes. These represent the best candidates to explain the molecular basis of convergent body thermoregulation in birds and mammals. Our analysis reveals the landscape of possible mutational compensation and convergence in amniote phylogeny.

Characterising private and shared signatures of positive selection in 37 Asian populations

The Asian Diversity Project (ADP) assembled 37 cosmopolitan and ethnic minority populations in Asia that have been densely genotyped across over half a million markers to study patterns of genetic diversity and positive natural selection. We performed population structure analyses of the ADP populations and divided these populations into four major groups based on their genographic information. By applying a highly sensitive algorithm haploPS to locate genomic signatures of positive selection, 140 distinct genomic regions exhibiting evidence of positive selection in at least one population were identified. We examined the extent of signal sharing for regions that were selected in multiple populations and observed that populations clustered in a similar fashion to that of how the ancestry clades were phylogenetically defined. In particular, populations predominantly located in South Asia underwent considerably different adaptation as compared with populations from the other geographical regions. Signatures of positive selection present in multiple geographical regions were predicted to be older and have emerged prior to the separation of the populations in the different regions. In contrast, selection signals present in a single population group tended to be of lower frequencies and thus can be attributed to recent evolutionary events.

Evidence of Recent Intricate Adaptation in Human Populations

Recent human adaptations have shaped population differentiation in genomic regions containing putative functional variants, mostly located in predicted regulatory elements. However, their actual functionalities and the underlying mechanism of recent adaptation remain poorly understood. In the current study, regions of genes and repeats were investigated for functionality depending on the degree of population differentiation, F_ST or ΔDAF (a difference in derived allele frequency). The high F_ST in the 5´ or 3´ untranslated regions (UTRs), in particular, confirmed that population differences arose mainly from differences in regulation. Expression quantitative trait loci (eQTL) analyses using lymphoblastoid cell lines indicated that the majority of the highly population-specific regions represented cis- and/or trans-eQTL. However, groups having the highest ΔDAFs did not necessarily have higher proportions of eQTL variants; in these groups, the patterns were complex, indicating recent intricate adaptations. The results indicated that East Asian (EAS) and European populations (EUR) experienced mutual selection pressures. The mean derived allele frequency of the high ΔDAF groups suggested that EAS and EUR underwent strong adaptation; however, the African population in Africa (AFR) experienced slight, yet broad, adaptation. The DAF distributions of variants in the gene regions showed clear selective pressure in each population, which implies the existence of more recent regulatory adaptations in cells other than lymphoblastoid cell lines. In-depth analysis of population-differentiated regions indicated that the coding gene, RNF135, represented a trans-regulation hotspot via cis-regulation by the population-specific variants in the region of selective sweep. Together, the results provide strong evidence of actual intricate adaptation of human populations via regulatory manipulation.

Genome-wide scans reveal variants at EDAR predominantly affecting hair straightness in Han Chinese and Uyghur populations

Hair straightness/curliness is one of the most conspicuous features of human variation and is particularly diverse among populations. A recent genome-wide scan found common variants in the Trichohyalin (TCHH) gene that are associated with hair straightness in Europeans, but different genes might affect this phenotype in other populations. By sampling 2899 Han Chinese, we performed the first genome-wide scan of hair straightness in East Asians, and found EDAR (rs3827760) as the predominant gene (P = 4.67 × 10^-16), accounting for 3.66 % of the total variance. The candidate gene approach did not find further significant associations, suggesting that hair straightness may be affected by a large number of genes with subtle effects. Notably, genetic variants associated with hair straightness in Europeans are generally low in frequency in Han Chinese, and vice versa. To evaluate the relative contribution of these variants, we performed a second genome-wide scan in 709 samples from the Uyghur, an admixed population with both eastern and western Eurasian ancestries. In Uyghurs, both EDAR (rs3827760: P = 1.92 × 10^-12) and TCHH (rs11803731: P = 1.46 × 10^-3) are associated with hair straightness, but EDAR (OR 0.415) has a greater effect than TCHH (OR 0.575). We found no significant interaction between EDAR and TCHH (P = 0.645), suggesting that these two genes affect hair straightness through different mechanisms. Furthermore, haplotype analysis indicates that TCHH is not subject to selection. While EDAR is under strong selection in East Asia, it does not appear to be subject to selection after the admixture in Uyghurs. These suggest that hair straightness is unlikely a trait under selection.

Molecular Signatures of Natural Selection for Polymorphic Genes of the Human Dopaminergic and Serotonergic Systems: A Review

A large body of research has examined the behavioral and mental health consequences of polymorphisms in genes of the dopaminergic and serotonergic systems. Along with this, there has been considerable interest in the possibility that these polymorphisms have developed and/or been maintained due to the action of natural selection. Episodes of natural selection on a gene are expected to leave molecular “footprints” in the DNA sequences of the gene and adjacent genomic regions. Here we review the research literature investigating molecular signals of selection for genes of the dopaminergic and serotonergic systems. The gene SLC6A4, which codes for a serotonin transport protein, was the one gene for which there was consistent support from multiple studies for a selective episode. Positive selection on SLC6A4 appears to have been initiated ∼ 20–25,000 years ago in east Asia and possibly in Europe. There are scattered reports of molecular signals of selection for other neurotransmitter genes, but these have generally failed at replication across studies. In spite of speculation in the literature about selection on these genes, current evidence from population genomic analyses supports selectively neutral processes, such as genetic drift and population dynamics, as the principal drivers of recent evolution in dopaminergic and serotonergic genes other than SLC6A4.

Detecting signatures of positive selection associated with musical aptitude in the human genome

Abilities related to musical aptitude appear to have a long history in human evolution. To elucidate the molecular and evolutionary background of musical aptitude, we compared genome-wide genotyping data (641 K SNPs) of 148 Finnish individuals characterized for musical aptitude. We assigned signatures of positive selection in a case-control setting using three selection methods: haploPS, XP-EHH and F_ST. Gene ontology classification revealed that the positive selection regions contained genes affecting inner-ear development. Additionally, literature survey has shown that several of the identified genes were known to be involved in auditory perception (e.g. GPR98, USH2A), cognition and memory (e.g. GRIN2B, IL1A, IL1B, RAPGEF5), reward mechanisms (RGS9), and song perception and production of songbirds (e.g. FOXP1, RGS9, GPR98, GRIN2B). Interestingly, genes related to inner-ear development and cognition were also detected in a previous genome-wide association study of musical aptitude. However, the candidate genes detected in this study were not reported earlier in studies of musical abilities. Identification of genes related to language development (FOXP1 and VLDLR) support the popular hypothesis that music and language share a common genetic and evolutionary background. The findings are consistent with the evolutionary conservation of genes related to auditory processes in other species and provide first empirical evidence for signatures of positive selection for abilities that contribute to musical aptitude.

Genes Regulated by Vitamin D in Bone Cells Are Positively Selected in East Asians

Vitamin D and folate are activated and degraded by sunlight, respectively, and the physiological processes they control are likely to have been targets of selection as humans expanded from Africa into Eurasia. We investigated signals of positive selection in gene sets involved in the metabolism, regulation and action of these two vitamins in worldwide populations sequenced by Phase I of the 1000 Genomes Project. Comparing allele frequency-spectrum-based summary statistics between these gene sets and matched control genes, we observed a selection signal specific to East Asians for a gene set associated with vitamin D action in bones. The selection signal was mainly driven by three genes CXXC finger protein 1 (CXXC1), low density lipoprotein receptor-related protein 5 (LRP5) and runt-related transcription factor 2 (RUNX2). Examination of population differentiation and haplotypes allowed us to identify several candidate causal regulatory variants in each gene. Four of these candidate variants (one each in CXXC1 and RUNX2 and two in LRP5) had a >70% derived allele frequency in East Asians, but were present at lower (20-60%) frequency in Europeans as well, suggesting that the adaptation might have been part of a common response to climatic and dietary changes as humans expanded out of Africa, with implications for their role in vitamin D-dependent bone mineralization and osteoporosis insurgence. We also observed haplotype sharing between East Asians, Finns and an extinct archaic human (Denisovan) sample at the CXXC1 locus, which is best explained by incomplete lineage sorting.

Mapping the genetic diversity of HLA haplotypes in the Japanese populations

Japan has often been viewed as an Asian country that possesses a genetically homogenous community. The basis for partitioning the country into prefectures has largely been geographical, although cultural and linguistic differences still exist between some of the districts/prefectures, especially between Okinawa and the mainland prefectures. The Major Histocompatibility Complex (MHC) region has consistently emerged as the most polymorphic region in the human genome, harbouring numerous biologically important variants; nevertheless the presence of population-specific long haplotypes hinders the imputation of SNPs and classical HLA alleles. Here, we examined the extent of genetic variation at the MHC between eight Japanese populations sampled from Okinawa, and six other prefectures located in or close to the mainland of Japan, specifically focusing at the haplotypes observed within each population, and what the impact of any variation has on imputation. Our results indicated that Okinawa was genetically farther to the mainland Japanese than were Gujarati Indians from Tamil Indians, while the mainland Japanese from six prefectures were more homogeneous than between northern and southern Han Chinese. The distribution of haplotypes across Japan was similar, although imputation was most accurate for Okinawa and several mainland prefectures when population-specific panels were used as reference.

Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes

Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB), a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23–34%) are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB.

Quantitative trait locus analysis of parasite density reveals that HbS gene carriage protects severe malaria patients against Plasmodium falciparum hyperparasitaemia

BACKGROUND

Haemoglobin S (HbS) is the gene known to confer the strongest advantage against malaria morbidity and mortality. Multiple HbS effects have been described resulting in protection against parasitaemia and reduction of severe malaria risk. This study aimed to explore HbS protection against severe malaria and Plasmodium falciparum parasitaemia in Angolan children exhibiting different severe malaria syndromes.

METHODS

A case-control study was designed with 430 malaria cases (n = 288 severe malaria and n = 142 uncomplicated malaria) and 319 uninfected controls, attending a central paediatric hospital in Luanda. Severe malaria syndromes were cerebral malaria (n = 130), severe malaria anaemia (n = 30) and hyperparasitaemia (n = 128). Quantitative trait locus analysis was carried out to study HbS association to parasite densities.

RESULTS

Previously reported HbS protection against severe malaria was confirmed in case-control analysis (P = 2 × 10(-13)) and corroborated by transmission disequilibrium test (P = 4 × 10(-3)). High parasite density protection conferred by HbS was detectable within severe malaria patients (P = 0.04). Stratifying severe malaria patients according parasite densities, it was found that HbS was highly associated to hyperparasitaemia protection (P = 1.9 × 10(-9)) but did not protect non-hyperparasitaemic children against severe malaria complications, namely cerebral malaria and severe malaria anaemia. Many studies have shown that HbS protects from severe malaria and controls parasite densities but the analysis further suggests that HbS protection against severe malaria syndromes was at a large extent correlated with control of parasitaemia levels.

CONCLUSIONS

This study supports the hypothesis that HbS confers resistance to hyperparasitaemia in patients exhibiting severe malaria syndromes and highlights that parasitaemia should be taken into account when evaluating HbS protection in severe malaria.

Fifteen years of genomewide scans for selection: trends, lessons and unaddressed genetic sources of complication

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example F(ST), cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach.

Impact of gene polymorphisms of gonadotropins and their receptors on human reproductive success

Gonadotropins and their receptors' genes carry several single-nucleotide polymorphisms resulting in endocrine genotypes modulating reproductive parameters, diseases, and lifespan leading to important implications for reproductive success and potential relevance during human evolution. Here we illustrate common genotypes of the gonadotropins and gonadotropin receptors' genes and their clinical implications in phenotypes relevant for reproduction such as ovarian cycle length, age of menopause, testosterone levels, polycystic ovary syndrome, and cancer. We then discuss their possible role in human reproduction and adaptation to the environment. Gonadotropins and their receptors' variants are differently distributed among human populations. Some hints suggest that they may be the result of natural selection that occurred in ancient times, increasing the individual chance of successful mating, pregnancy, and effective post-natal parental cares. The gender-related differences in the regulation of the reproductive endocrine systems imply that many of these genotypes may lead to sex-dependent effects, increasing the chance of mating and reproductive success in one sex at the expenses of the other sex. Also, we suggest that sexual conflicts within the FSH and LH-choriogonadotropin receptor genes contributed to maintain genotypes linked to subfertility among humans. Because the distribution of polymorphic markers results in a defined geographical pattern due to human migrations rather than natural selection, these polymorphisms may have had only a weak impact on reproductive success. On the contrary, such genotypes could acquire relevant consequences in the modern, developed societies in which parenthood attempts often occur at a later age, during a short, suboptimal reproductive window, making clinical fertility treatments necessary.

Positive Selection on Loci Associated with Drug and Alcohol Dependence

Much of the evolution of human behavior remains a mystery, including how certain disadvantageous behaviors are so prevalent. Nicotine addiction is one such phenotype. Several loci have been implicated in nicotine related phenotypes including the nicotinic receptor gene clusters (CHRNs) on chromosomes 8 and 15. Here we use 1000 Genomes sequence data from 3 populations (Africans, Asians and Europeans) to examine whether natural selection has occurred at these loci. We used Tajima's D and the integrated haplotype score (iHS) to test for evidence of natural selection. Our results provide evidence for strong selection in the nicotinic receptor gene cluster on chromosome 8, previously found to be significantly associated with both nicotine and cocaine dependence, as well as evidence selection acting on the region containing the CHRNA5 nicotinic receptor gene on chromosome 15, that is genome wide significant for risk for nicotine dependence. To examine the possibility that this selection is related to memory and learning, we utilized genetic data from the Collaborative Studies on the Genetics of Alcoholism (COGA) to test variants within these regions with three tests of memory and learning, the Wechsler Adult Intelligence Scale (WAIS) Block Design, WAIS Digit Symbol and WAIS Information tests. Of the 17 SNPs genotyped in COGA in this region, we find one significantly associated with WAIS digit symbol test results. This test captures aspects of reaction time and memory, suggesting that a phenotype relating to memory and learning may have been the driving force behind selection at these loci. This study could begin to explain why these seemingly deleterious SNPs are present at their current frequencies.