Gene flow and natural selection in oceanic human populations inferred from genome-wide SNP typing

Tracing the genealogy origin of geographic populations based on genomic variation and deep learning

Assigning a query individual animal or plant to its derived population is a prime task in diverse applications related to organismal genealogy. Such endeavors have conventionally relied on short DNA sequences under a phylogenetic framework. These methods naturally show constraints when the inferred population sources are ambiguously phylogenetically structured, a scenario demanding substantially more informative genetic signals. Recent advances in cost-effective production of whole-genome sequences and artificial intelligence have created an unprecedented opportunity to trace the population origin for essentially any given individual, as long as the genome reference data are comprehensive and standardized. Here, we developed a convolutional neural network method to identify population origins using genomic SNPs. Three empirical datasets (an Asian honeybee, a red fire ant, and a chicken datasets) and two simulated populations are used for the proof of concepts. The performance tests indicate that our method can accurately identify the genealogy origin of query individuals, with success rates ranging from  93 % to 100 %. We further showed that the accuracy of the model can be significantly increased by refining the informative sites through FST filtering. Our method is robust to configurations related to batch sizes and epochs, whereas model learning benefits from the setting of a proper preset learning rate. Moreover, we explained the importance score of key sites for algorithm interpretability and credibility, which has been largely ignored. We anticipate that by coupling genomics and deep learning, our method will see broad potential in conservation and management applications that involve natural resources, invasive pests and weeds, and illegal trades of wildlife products.

North African fox genomes show signatures of repeated introgression and adaptation to life in deserts

Elucidating the evolutionary process of animal adaptation to deserts is key to understanding adaptive responses to climate change. Here we generated 82 individual whole genomes of four fox species (genus Vulpes) inhabiting the Sahara Desert at different evolutionary times. We show that adaptation of new colonizing species to a hot arid environment has probably been facilitated by introgression and trans-species polymorphisms shared with older desert resident species, including a putatively adaptive 25 Mb genomic region. Scans for signatures of selection implicated genes affecting temperature perception, non-renal water loss and heat production in the recent adaptation of North African red foxes (Vulpes vulpes), after divergence from Eurasian populations approximately 78 thousand years ago. In the extreme desert specialists, Rueppell's fox (V. rueppellii) and fennec (V. zerda), we identified repeated signatures of selection in genes affecting renal water homeostasis supported by gene expression and physiological differences. Our study provides insights into the mechanisms and genetic underpinnings of a natural experiment of repeated adaptation to extreme conditions.

Detection of c.375A>G, c.385A>T, c.571C>T, and sedel2 of FUT2 via Real-Time PCR in a Single Tube

α(1,2)fucosyltransferase (Se enzyme) encoded by FUT2 is involved in the secretor status of ABH(O) blood group antigens. The se^del2 allele is one of the non-functional FUT2 (se) alleles in which 9.3 kb, containing the entire coding region of FUT2, is deleted by Alu-mediated nonhomologous recombination. In addition to this allele, three SNPs of FUT2, c.375A>G, c.385A>T, and c.571C>T, appear to be prevalent in certain Oceanian populations such as Polynesians. Recently, we developed an endpoint genotyping assay to determine se^del2 zygosity, using a FAM-labeled probe for detection of the se^del2 allele and a VIC-labeled probe for the detection of FUT2. In this study, instead of the VIC probe, a HEX-labeled probe covering both c.375A>G and c.385A>T and a Cy5-labeled probe covering c.571C>T were added to the se^del2 allele assay mixture to allow for the simultaneous detection of these four variations via endpoint genotyping for se^del2 zygosity and fluorescence melting curve analysis for c.375A>G, c.385A>T, and c.571C>T genotyping. The results obtained from 24 Samoan subjects using this method were identical to those obtained using previous methods. Therefore, it appears that the present method can accurately determine these four variations simultaneously.

Real-time PCR-based detection of the Alu-mediated deletion of FUT2 (sedel2)

Secretor status of the ABH(O) histoblood group antigens is regulated by secretor type α(1,2)fucosyltransferase encoded by FUT2. The se^del2 allele is a complete deletion of the FUT2 coding region generated by Alu-mediated homologous recombination. This deletion seems to be exclusively encountered in certain Oceanian populations. From the perspective of forensic science, se^del2 is considered to be one of ancestry informative markers for these populations. Real-time PCR followed by melting curve analysis was employed to find primer set to specifically amplify se^del2. We designed primers which produced a 231-bp amplicon specific to se^del2. The specificity of these primers was also confirmed by gel electrophoresis and sequencing of the PCR product. Then, two real-time PCR methods based on melting curve analysis and a hydrolysis probe were designed to determine se^del2 zygosity by adding FUT2-specific primers. These two methods were validated by analyzing 24 Samoan subjects. The results obtained from 24 Samoan subjects by the two methods were fully in accordance with those obtained by a previous conventional PCR method that amplified a 2.7-kb fragment of se^del2. Therefore, these two methods seemed to accurately determine the zygosity of se^del2 and were useful for investigation of the distribution and origin of this deletion.

Admixture with indigenous people helps local adaptation: admixture-enabled selection in Polynesians

Background

Homo sapiens have experienced admixture many times in the last few thousand years. To examine how admixture affects local adaptation, we investigated genomes of modern Polynesians, who are shaped through admixture between Austronesian-speaking people from Southeast Asia (Asian-related ancestors) and indigenous people in Near Oceania (Papuan-related ancestors).

Methods

In this study local ancestry was estimated across the genome in Polynesians (23 Tongan subjects) to find the candidate regions of admixture-enabled selection contributed by Papuan-related ancestors.

Results

The mean proportion of Papuan-related ancestry across the Polynesian genome was estimated as 24.6% (SD = 8.63%), and two genomic regions, the extended major histocompatibility complex (xMHC) region on chromosome 6 and the ATP-binding cassette transporter sub-family C member 11 (ABCC11) gene on chromosome 16, showed proportions of Papuan-related ancestry more than 5 SD greater than the mean (> 67.8%). The coalescent simulation under the assumption of selective neutrality suggested that such signals of Papuan-related ancestry enrichment were caused by positive selection after admixture (false discovery rate = 0.045). The ABCC11 harbors a nonsynonymous SNP, rs17822931, which affects apocrine secretory cell function. The approximate Bayesian computation indicated that, in Polynesian ancestors, a strong positive selection (s = 0.0217) acted on the ancestral allele of rs17822931 derived from Papuan-related ancestors.

Conclusions

Our results suggest that admixture with Papuan-related ancestors contributed to the rapid local adaptation of Polynesian ancestors. Considering frequent admixture events in human evolution history, the acceleration of local adaptation through admixture should be a common event in humans.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01900-y.

Admixture and natural selection shaped genomes of an Austronesian-speaking population in the Solomon Islands

People in the Solomon Islands today are considered to have derived from Asian- and Papuan-related ancestors. Papuan-related ancestors colonized Near Oceania about 47,000 years ago, and Asian-related ancestors were Austronesian (AN)-speaking population, called Lapita, who migrated from Southeast Asia about 3,500 years ago. These two ancestral populations admixed in Near Oceania before the expansion of Lapita people into Remote Oceania. To understand the impact of the admixture on the adaptation of AN-speaking Melanesians in Near Oceania, we performed the genome-wide single nucleotide polymorphism (SNP) analysis of 21 individuals from Munda, the main town of the New Georgia Islands in the western Solomon Islands. Population samples from Munda were genetically similar to other Solomon Island population samples. The analysis of genetic contribution from the two different ancestries to the Munda genome revealed significantly higher proportions of Asian- and Papuan-related ancestries in the region containing the annexin A1 (ANXA1) gene (Asian component > 82.6%) and in the human leukocyte antigen (HLA) class II region (Papuan component > 85.4%), respectively. These regions were suspected to have undergone natural selection since the time of admixture. Our results suggest that admixture had affected adaptation of AN-speaking Melanesians in the Solomon Islands.

Downstream targets of GWAS-detected genes for breast, lung, and prostate and colon cancer converge to G1/S transition pathway

Genome-wide association studies (GWASs) identified over 500 single nucleotide polymorphisms (SNPs) influencing cancer risk. It is logical to expect the cancer-associated genes to cluster in pathways directly involved in carcinogenesis, e.g. cell cycle. Nevertheless, analyses of the GWAS-detected cancer risk genes usually show no or weak enrichment by known cancer genes.We hypothesized that GWAS-detected cancer risk-associated genes function as upstream regulators of the genes directly involved in carcinogenesis. We have analyzed four common cancers: breast, colon, lung, and prostate. To identify downstream targets of GWAS-detected cancer risk genes we used MedScan, which is a text mining tool offered by PathwayStudio. We also used data on protein/protein interactions reported by BioGRID database. Among all identified targets we have selected common downstream targets. A gene was considered a common downstream target if it was a downstream target for at least three GWAS-detected genes for a given cancer type. Common downstream targets were identified separately for each cancer type. We found that common downstream targets for all four cancer types were enriched by cell cycle genes, more specifically, the genes involved in G1/S transition. Common downstream targets for bipolar disorder, Crohn's disease, and type 2 diabetes did not show G1/S transition enrichment.The results of this analysis suggest that many cancer risk genes function as upstream regulators of the genes directly involved in G1/S transition and exert their risk effects by reducing threshold for G1/S transition, elevating the background level of cell proliferation and cancer risk.

Lack of direct evidence for natural selection at the candidate thrifty gene locus, PPARGC1A

Background

The gene PPARGC1A, in particular the Gly482Ser variant (rs8192678), had been proposed to be subject to natural selection, particularly in recent progenitors of extant Polynesian populations. Reasons include high levels of population differentiation and increased frequencies of the derived type 2 diabetes (T2D) risk 482Ser allele, and association with body mass index (BMI) in a small Tongan population. However, no direct statistical tests for selection have been applied.

Methods

Using a range of Polynesian populations (Tongan, Māori, Samoan) we re-examined evidence for association between Gly482Ser with T2D and BMI as well as gout. Using also Asian, European, and African 1000 Genome Project samples a range of statistical tests for selection (F_ST, integrated haplotype score (iHS), cross population extended haplotype homozygosity (XP-EHH), Tajima’s D and Fay and Wu’s H) were conducted on the PPARGC1A locus.

Results

No statistically significant evidence for association between Gly482Ser and any of BMI, T2D or gout was found. Population differentiation (F_ST) was smallest between Asian and Pacific populations (New Zealand Māori ≤ 0.35, Samoan ≤ 0.20). When compared to European (New Zealand Māori ≤ 0.40, Samoan ≤ 0.25) or African populations (New Zealand Māori ≤ 0.80, Samoan ≤ 0.66) this differentiation was larger. We did not find any strong evidence for departure from neutral evolution at this locus when applying any of the other statistical tests for selection. However, using the same analytical methods, we found evidence for selection in specific populations at previously identified loci, indicating that lack of selection was the most likely explanation for the lack of evidence of selection in PPARGC1A.

Conclusion

We conclude that there is no compelling evidence for selection at this locus, and that this gene should not be considered a candidate thrifty gene locus in Pacific populations. High levels of population differentiation at this locus and the reported absence of the derived 482Ser allele in some Melanesian populations, can alternatively be explained by multiple out-of-Africa migrations by ancestral progenitors, and subsequent genetic drift during colonisation of Polynesia. Intermediate 482Ser allele frequencies in extant Western Polynesian populations could therefore be due to recent admixture with Melanesian progenitors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-016-0341-z) contains supplementary material, which is available to authorized users.

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.

Genome-wide insights into the genetic history of human populations

Although mtDNA and the non-recombining Y chromosome (NRY) studies continue to provide valuable insights into the genetic history of human populations, recent technical, methodological and computational advances and the increasing availability of large-scale, genome-wide data from contemporary human populations around the world promise to reveal new aspects, resolve finer points, and provide a more detailed look at our past demographic history. Genome-wide data are particularly useful for inferring migrations, admixture, and fine structure, as well as for estimating population divergence and admixture times and fluctuations in effective population sizes. In this review, we highlight some of the stories that have emerged from the analyses of genome-wide SNP genotyping data concerning the human history of Southern Africa, India, Oceania, Island South East Asia, Europe and the Americas and comment on possible future study directions. We also discuss advantages and drawbacks of using SNP-arrays, with a particular focus on the ascertainment bias, and ways to circumvent it.

Inferring positive selection in humans from genomic data

Adaptation can be described as an evolutionary process that leads to an adjustment of the phenotypes of a population to their environment. In the classical view, new mutations can introduce novel phenotypic features into a population that leave footprints in the genome after fixation, such as selective sweeps. Alternatively, existing genetic variants may become beneficial after an environmental change and increase in frequency. Although they may not reach fixation, they may cause a shift of the optimum of a phenotypic trait controlled by multiple loci. With the availability of polymorphism data from various organisms, including humans and chimpanzees, it has become possible to detect molecular evidence of adaptation and to estimate the strength and target of positive selection. In this review, we discuss the two competing models of adaptation and suitable approaches for detecting the footprints of positive selection on the molecular level.

KIR diversity in Māori and Polynesians: populations in which HLA-B is not a significant KIR ligand

HLA class I molecules and killer cell immunoglobulin-like receptors (KIR) form a diverse system of ligands and receptors that individualize human immune systems in ways that improve the survival of individuals and populations. Human settlement of Oceania by island-hopping East and Southeast Asian migrants started ~3,500 years ago. Subsequently, New Zealand was reached ~750 years ago by ancestral Māori. To examine how this history impacted KIR and HLA diversity, and their functional interaction, we defined at high resolution the allelic and haplotype diversity of the 13 expressed KIR genes in 49 Māori and 34 Polynesians. Eighty KIR variants, including four 'new' alleles, were defined, as were 35 centromeric and 22 telomeric KIR region haplotypes, which combine to give >50 full-length KIR haplotypes. Two new and divergent variant KIR form part of a telomeric KIR haplotype, which appears derived from Papua New Guinea and was probably obtained by the Asian migrants en route to Polynesia. Māori and Polynesian KIR are very similar, but differ significantly from African, European, Japanese, and Amerindian KIR. Māori and Polynesians have high KIR haplotype diversity with corresponding allotype diversity being maintained throughout the KIR locus. Within the population, each individual has a unique combination of HLA class I and KIR. Characterizing Māori and Polynesians is a paucity of HLA-B allotypes recognized by KIR. Compensating for this deficiency are high frequencies (>50 %) of HLA-A allotypes recognized by KIR. These HLA-A allotypes are ones that modern humans likely acquired from archaic humans at a much earlier time.

Molecular approaches to transfusion medicine in Polynesians and Maori in New Zealand

In recent years, with the application of genotyping technology, there has been a substantial increase in the number of reported blood group alleles. This survey was designed to evaluate new molecular blood group genotyping methods and compile reference blood group data sets for Polynesian and Maori subjects. Subsequent analyses of these results were used to calculate probability of random match, to trace Polynesian ancestry and migration patterns and to reveal past and present episodes of genetic admixture. Genomic DNA samples from Maori and Polynesian subjects were drawn from the Victoria University of Wellington DNA Bank and genotyped using combination of commercial PCR-SSP kits, hybridization SNP assay services or sequence-based typing. This survey also involves compilation of serological ABO and Rhesus blood group data from RakaiPaaka Iwi tribal members for comparison with those generated during our molecular blood group study. We observed perfect consistency between results obtained from all molecular methods for blood group genotyping. The A, O, DCcEe, DCCee, MNs, K-k+, Jk(a+b-), Jk(a+b+), Fy(a+b-), Fy(a+b+), Di(a+b-), Co(a+b-) and Do(a-b+) were predominant blood group phenotypes in both Polynesians and Maori. Overall, our survey data show only small differences in distributions of blood group phenotypes between Polynesian and Maori groups and their subgroups. These differences might be associated with selection, population history and gene flow from Europeans. In each case, we estimate that patients with certain blood groups have a very low probability of an exact phenotypic match, even if the patients were randomly transfused with blood from donors of their own ethnicity. The best way to avoid haemolytic transfusion reaction in such cases is to perform a pretransfusion cross-match and recruit increased numbers of donors with rare phenotype profiles. The conclusion of this study is that application of molecular method covering as many known variants as possible may help to improve the accuracy blood group genotyping and potentially conserve the routine requirements of transfusion centres.

Human platelet antigens frequencies in Maori and Polynesian populations

BACKGROUND

Allele frequencies of human platelet antigens (HPA) reflect population history and possibility of platelet-specific alloimmunization. Here, we report on screening of variants at HPA loci for Polynesian and Maori subjects.

OBJECTIVES

Our aims are to evaluate new HPA genotyping methods, compile and analyse new HPA datasets for these subjects, use HPA data for tracing ancestry, migration patterns, genetic admixture and its potential influence on health.

MATERIALS AND METHODS

A total of 75 Maori and 25 Polynesian DNA samples were genotyped using commercial BAGene HPA-TYPE DNA-SSP kits, BLOODchip hybridization SNP assays and DNA sequence based typing.

RESULTS

Genotyping was successful and cross validation of PCR-SSP and BLOODchip gave 100% agreement. Among the HPA loci tested, only six are dimorphic (HPA-1 to -3, -5, -6 and -15) and all others are monomorphic. The Polynesians and Maori have the 'a' allele form as the most common for all loci except HPA-15.

CONCLUSIONS

The newly observed HPA data as well as principal coordinate analysis clearly indicate genetic contributions from both, Asia and Australasia in Maori and Polynesian populations together with recent admixture with Europeans. In addition, different prevalences of HPA alleles among Polynesian, Maori and European populations contribute towards different risk profiles for platelet-specific alloimmunization. This is the first report for these populations and our findings are of direct practical relevance for blood transfusion centres, the management of pregnancies, assessment of neonatal alloimmune thrombocytopenia and management of multi-transfused patients.

Hypertension-susceptibility gene prevalence in the Pacific Islands and associations with hypertension in Melanesia

Human essential hypertension is partly caused by genetic factors. Angiotensinogen (AGT), G-protein β3-subunit (GNB3) and cytochrome P450 3A5 (CYP3A5) are candidate hypertension susceptibility genes and risk alleles at these loci have been thought to arise owing to human adaptation to climatic changes following the migration out-of-Africa. This study aimed to reveal the frequencies of hypertension-susceptibility genotypes in Pacific Island populations and associations of these single-nucleotide polymorphisms (SNPs) to hypertension. Genotyping was conducted for 804 individuals from Melanesian, Micronesian and Polynesian populations at SNPs in the genes encoding AGT (rs699, rs5049 and rs5051), GNB3 (rs5443) and CYP3A5*1/*3 (rs776746). Associations between these SNPs and hypertension were tested for 383 Melanesian Solomon Islanders. We found that the A/A genotype at rs5049 was a risk factor for hypertension (P=0.025) in the Melanesian Solomon Islanders; three SNPs for AGT were in linkage disequilibrium. The ancestral alleles of rs699, rs5051 and rs776746, and the derived allele of rs5443 were as frequent in the populations surveyed here as in other equatorial populations. Although other polymorphisms associated with hypertension and additional populations remain to be studied, these findings suggest that the Pacific Islanders' susceptibility to hypertension arose because of human migration and adaptation.

Dating the age of admixture via wavelet transform analysis of genome-wide data

We describe a PCA-based genome scan approach to analyze genome-wide admixture structure, and introduce wavelet transform analysis as a method for estimating the time of admixture. We test the wavelet transform method with simulations and apply it to genome-wide SNP data from eight admixed human populations. The wavelet transform method offers better resolution than existing methods for dating admixture, and can be applied to either SNP or sequence data from humans or other species.

The serum leptin level and body mass index in Melanesian and Micronesian Solomon Islanders: focus on genetic factors and urbanization

OBJECTIVES

This study examined the association between the serum leptin level and body mass index (BMI) and the effects of urbanization and polymorphisms of leptin (LEP) or leptin receptor (LEPR) genes on the leptin level in three Solomon Islands populations.

METHODS

A Melanesian population living in a remote area (participants: 106 males and 106 females, ages: 18-74 years), a Melanesian population in an urban area (89 and 94, 18-79 years), and a Micronesian population who migrated to a peri-urban area in the 1960s (84 and 69, 18-71 years) were studied. Anthropometric and serum leptin measurements and genotyping for LEP G-2548A and LEPR K109R and Q223R were performed.

RESULTS

The prevalence of obesity (BMI ≥ 30 kg/m(2)) was the highest in the Micronesian population (30.1%), followed by the urban (18.6%) and the rural (2.4%) Melanesian population. The serum leptin concentration was the highest in the urban Melanesian, followed by the Micronesian and the rural Melanesian populations (P < 0.05). Interestingly, the parameter coefficients of the leptin concentrations on the BMIs were nearly identical in the urban and rural Melanesians after adjusting for age and gender. The LEPR 223Q/Q genotype was associated with an increased leptin level only in the Micronesian population after adjusting for BMI (P = 0.0008 and 0.0016 referenced to the Q/R and the R/R types, respectively).

CONCLUSIONS

These observations suggest that the increase in obesity in the Micronesians had a genetic component while that in Melanesians might have been related with the urbanization.

Whole-genome genetic diversity in a sample of Australians with deep Aboriginal ancestry

Australia was probably settled soon after modern humans left Africa, but details of this ancient migration are not well understood. Debate centers on whether the Pleistocene Sahul continent (composed of New Guinea, Australia, and Tasmania) was first settled by a single wave followed by regional divergence into Aboriginal Australian and New Guinean populations (common origin) or whether different parts of the continent were initially populated independently. Australia has been the subject of relatively few DNA studies even though understanding regional variation in genomic structure and diversity will be important if disease-association mapping methods are to be successfully evaluated and applied across populations. We report on a genome-wide investigation of Australian Aboriginal SNP diversity in a sample of participants from the Riverine region. The phylogenetic relationship of these Aboriginal Australians to a range of other global populations demonstrates a deep common origin with Papuan New Guineans and Melanesians, with little evidence of substantial later migration until the very recent arrival of European colonists. The study provides valuable and robust insights into an early and important phase of human colonization of the globe. A broader survey of Australia, including diverse geographic sample populations, will be required to fully appreciate the continent's unique population history and consequent genetic heritage, as well as the importance of both to the understanding of health issues.

The human genetic history of Oceania: near and remote views of dispersal

The human history of Oceania is unique in the way that it encompasses both the first out-of-Africa expansion of modern humans to New Guinea and Australia as well as the last regional human occupation of Polynesia. Other anthropological peculiarities of Oceania include features like the extraordinarily rich linguistic diversity especially of New Guinea with about 1,000 often very distinct languages, the independent and early development of agriculture in the highlands of New Guinea about 10,000 years ago, or the long-term isolation of the entire region from the outside world, which lasted as long as until the 1930s for most of the interior of New Guinea. This review will provide an overview on the genetic aspects of human population history of Oceania and how some of the anthropological peculiarities are reflected in human genetic data. Due to current data availability it will mostly focus on insights from sex-specifically inherited mitochondrial DNA and Y-chromosomal DNA, whereas more genome-wide autosomal DNA data are soon expected to add additional details or may correct views obtained from these two, albeit highly complex, genetic loci.

Use of genome-wide expression data to mine the "Gray Zone" of GWA studies leads to novel candidate obesity genes

To get beyond the “low-hanging fruits” so far identified by genome-wide association (GWA) studies, new methods must be developed in order to discover the numerous remaining genes that estimates of heritability indicate should be contributing to complex human phenotypes, such as obesity. Here we describe a novel integrative method for complex disease gene identification utilizing both genome-wide transcript profiling of adipose tissue samples and consequent analysis of genome-wide association data generated in large SNP scans. We infer causality of genes with obesity by employing a unique set of monozygotic twin pairs discordant for BMI (n = 13 pairs, age 24–28 years, 15.4 kg mean weight difference) and contrast the transcript profiles with those from a larger sample of non-related adult individuals (N = 77). Using this approach, we were able to identify 27 genes with possibly causal roles in determining the degree of human adiposity. Testing for association of SNP variants in these 27 genes in the population samples of the large ENGAGE consortium (N = 21,000) revealed a significant deviation of P-values from the expected (P = 4×10⁻⁴). A total of 13 genes contained SNPs nominally associated with BMI. The top finding was blood coagulation factor F13A1 identified as a novel obesity gene also replicated in a second GWA set of ∼2,000 individuals. This study presents a new approach to utilizing gene expression studies for informing choice of candidate genes for complex human phenotypes, such as obesity.

Obesity has a strong genetic component and an estimated 45%–85% of the variation in adult relative weight is genetically determined. Many genes have recently been identified in genome-wide association studies. The individual effects of the identified genes, however, have been very modest, and their identification required very large sample sizes. New approaches are therefore needed to uncover further genetic variants that contribute to the development of obesity and related conditions. Much can be learned from studying the expression of genes in adipose tissue of obese and non-obese subjects, but it is very difficult to distinguish which genes' expression differences represent reactions to obesity from those related to causal processes. We studied monozygotic twin pairs discordant for obesity and contrasted the gene expression profiles of obese and lean co-twins (controlling for genetic variation) to those from unrelated individuals to try to discern the cause-and-effect relationships of the identified changes in gene expression in fat. Testing the identified genes in 21,000 individuals identified numerous new genes with possible roles in the development of obesity. Among the top findings was a gene involved in blood coagulation (Factor XIIIA1), possibly linking obesity with known complications including deep vein thrombosis, heart attack, and stroke.

Autosomal and X-linked single nucleotide polymorphisms reveal a steep Asian-Melanesian ancestry cline in eastern Indonesia and a sex bias in admixture rates

The geographical region between mainland Asia and New Guinea is characterized by numerous small islands with isolated human populations. Phenotypically, groups in the west are similar to their neighbours in mainland Southeast Asia, eastern groups near New Guinea are similar to Melanesians, and intervening populations are intermediate in appearance. A long-standing question is whether this pattern primarily reflects mixing between groups with distinct origins or whether natural selection has shaped this range of variation by acting differentially on populations across the region. To address this question, we genotyped a set of 37 single nucleotide polymorphisms that are evolutionarily independent, putatively neutral and highly informative for Asian-Melanesian ancestry in 1430 individuals from 60 populations spanning mainland Asia to Melanesia. Admixture analysis reveals a sharp transition from Asian to Melanesian genetic variants over a narrow geographical region in eastern Indonesia. Interestingly, this admixture cline roughly corresponds to the human phenotypic boundary noted by Alfred Russell Wallace in 1869. We conclude that this phenotypic gradient probably reflects mixing of two long-separated ancestral source populations-one descended from the initial Melanesian-like inhabitants of the region, and the other related to Asian groups that immigrated during the Paleolithic and/or with the spread of agriculture. A higher frequency of Asian X-linked markers relative to autosomal markers throughout the transition zone suggests that the admixture process was sex-biased, either favouring a westward expansion of patrilocal Melanesian groups or an eastward expansion of matrilocal Asian immigrants. The matrilocal marriage practices that dominated early Austronesian societies may be one factor contributing to this observed sex bias in admixture rates.

European and Polynesian admixture in the Norfolk Island population

The Norfolk Island population in the South Pacific is primarily the product of recent admixture between a small number of British male and Polynesian female founders. We identified and genotyped 128 Ancestry Informative Markers (AIMs) spread across the autosomes, X/Y chromosomes and mitochondrial DNA genome, to explore and quantify the current levels of genetic admixture in the Norfolk Islanders. On the basis of autosomal AIMs, the population shows mean European and Polynesian ancestry proportions of 88 and 12%, respectively. However, there is a substantial variation between individuals ranging from total European ancestry to near total Polynesian origin. There is a strong correlation between individual genetic estimates of Polynesian ancestry and those derived from the extensive pedigree and genealogical records of Islanders. Also in line with historical accounts, there is a substantial asymmetry in the maternal and paternal origins of the Islanders with almost all Y-chromosomes of European origin whereas at least 25% of mtDNAs appear to have a Polynesian origin. Accurate knowledge of ancestry will be important in future attempts to use the Island population in admixture mapping approaches to find the genes that underlie differences in the risk to some diseases between Europeans and Polynesians.

Genetic variation and recent positive selection in worldwide human populations: evidence from nearly 1 million SNPs

Background

Genome-wide scans of hundreds of thousands of single-nucleotide polymorphisms (SNPs) have resulted in the identification of new susceptibility variants to common diseases and are providing new insights into the genetic structure and relationships of human populations. Moreover, genome-wide data can be used to search for signals of recent positive selection, thereby providing new insights into the genetic adaptations that occurred as modern humans spread out of Africa and around the world.

Methodology

We genotyped approximately 500,000 SNPs in 255 individuals (5 individuals from each of 51 worldwide populations) from the Human Genome Diversity Panel (HGDP-CEPH). When merged with non-overlapping SNPs typed previously in 250 of these same individuals, the resulting data consist of over 950,000 SNPs. We then analyzed the genetic relationships and ancestry of individuals without assigning them to populations, and we also identified candidate regions of recent positive selection at both the population and regional (continental) level.

Conclusions

Our analyses both confirm and extend previous studies; in particular, we highlight the impact of various dispersals, and the role of substructure in Africa, on human genetic diversity. We also identified several novel candidate regions for recent positive selection, and a gene ontology (GO) analysis identified several GO groups that were significantly enriched for such candidate genes, including immunity and defense related genes, sensory perception genes, membrane proteins, signal receptors, lipid binding/metabolism genes, and genes involved in the nervous system. Among the novel candidate genes identified are two genes involved in the thyroid hormone pathway that show signals of selection in African Pygmies that may be related to their short stature.

Genomic landscape of positive natural selection in Northern European populations

Analyzing genetic variation of human populations for detecting loci that have been affected by positive natural selection is important for understanding adaptive history and phenotypic variation in humans. In this study, we analyzed recent positive selection in Northern Europe from genome-wide data sets of 250 000 and 500 000 single-nucleotide polymorphisms (SNPs) in a total of 999 individuals from Great Britain, Northern Germany, Eastern and Western Finland, and Sweden. Coalescent simulations were used for demonstrating that the integrated haplotype score (iHS) and long-range haplotype (LRH) statistics have sufficient power in genome-wide data sets of different sample sizes and SNP densities. Furthermore, the behavior of the F(ST) statistic in closely related populations was characterized by allele frequency simulations. In the analysis of the North European data set, 60 regions in the genome showed strong signs of recent positive selection. Out of these, 21 regions have not been discovered in previous scans, and many contain genes with interesting functions (eg, RAB38, INFG, NOS1AP, and APOE). In the putatively selected regions, we observed a statistically significant overrepresentation of genetic association with complex disease, which emphasizes the importance of the analysis of positive selection in understanding the evolution of human disease. Altogether, this study demonstrates the potential of genome-wide data sets to discover loci that lie behind evolutionary adaptation in different human populations.

Constructing genomic maps of positive selection in humans: where do we go from here?

Identifying targets of positive selection in humans has, until recently, been frustratingly slow, relying on the analysis of individual candidate genes. Genomics, however, has provided the necessary resources to systematically interrogate the entire genome for signatures of natural selection. To date, 21 genome-wide scans for recent or ongoing positive selection have been performed in humans. A key challenge is to begin synthesizing these newly constructed maps of positive selection into a coherent narrative of human evolutionary history and derive a deeper mechanistic understanding of how natural populations evolve. Here, I chronicle the recent history of the burgeoning field of human population genomics, critically assess genome-wide scans for positive selection in humans, identify important gaps in knowledge, and discuss both short- and long-term strategies for traversing the path from the low-resolution, incomplete, and error-prone maps of selection today to the ultimate goal of a detailed molecular, mechanistic, phenotypic, and population genetics characterization of adaptive alleles.

A genomewide comparison of population structure at STRPs and nearby SNPs in humans

Patterns of population structure provide insights into evolutionary processes and help identify groups of individuals for genotype-phenotype association studies. With increasing availability of polymorphic molecular markers across genomes, the examination of population structure using large numbers of unlinked loci has become a common practice in evolutionary biology and human genetics. The two classes of molecular variation most widely used for this purpose, short tandem repeat polymorphisms (STRPs) and single-nucleotide polymorphisms (SNPs), differ in mutational properties expected to affect population structure. To measure the relative ability of these loci to describe population structure, we compared diversity at neighboring STRPs and SNPs from 720 genomic regions in the four populations that comprise the Human HapMap. Comparing loci from the same genomic regions allowed us to focus on the contribution of mutational differences (rather than variation in genealogical history) to disparities in population structure between STRPs and SNPs. Relative to average values for SNPs from the same regions, STRPs had lower F(st), but higher G(st)' and I(n) values. STRP-SNP correlations in population structure across genomic regions were statistically significant but weak in magnitude. Separate analyses by repeat type showed that these correlations were driven primarily by tetranucleotide and trinucleotide STRPs; measures of population structure at dinucleotides and SNPs were not significantly correlated. Pairwise comparisons among populations revealed effects of divergence time on differences in population structure between STRPs and SNPs. Collectively, these results confirm that individual STRPs can provide more information about population structure than individual SNPs, but suggest that the difference in structure at STRPs and SNPs depends on local genealogical history. Our study motivates theoretical comparisons of population structure at loci with different mutational properties.