A human genome diversity cell line panel

Colonialism, ethnogenesis, and biogeographic ancestry in the US Southwest

OBJECTIVE

Differences between self-perceived biogeographic ancestry and estimates derived from DNA are potentially informative about the formation of ethnic identities in different sociohistorical contexts. Here, we compared self-estimates and DNA-estimates in New Mexico, where notions of shared ancestry and ethnic identity have been shaped by centuries of migration and admixture.

MATERIALS AND METHODS

We asked 507 New Mexicans of Spanish-speaking descent (NMS) to list their ethnic identity and to estimate their percentages of European and Native American ancestry. We then compared self-estimates to estimates derived from 291,917 single nucleotide polymorphisms (SNPs), and we examined how differences between the estimates varied by ethnic identity.

RESULTS

Most NMS (94%) predicted that they had non-zero percentages of European and Native American ancestry. Self-estimates and SNP-estimates were positively correlated (rEuropean  = 0.38, rNative-American  = 0.36, p < 0.001). The correlations belie systematic patterns of underestimation and overestimation based on ethnic identity. NMS with ancestral ties to 20th century immigrants, who identified as Mexican or Mexican American, often underestimated their European ancestry (self-estimate < SNP-estimate) and overestimated their Native American ancestry. The pattern was reversed for NMS who emphasized deep connections to colonial New Mexico and identified as Spanish or Spanish American.

DISCUSSION

While NMS accurately predicted that they had European and Native American ancestry, they predicted ancestry percentages with only moderate accuracy. Differences between self-estimated and SNP-estimated ancestry were associated with ethnic identities that were shaped by migration to the region over the past 400 years. We connect ethnic identities and patterns of ancestry estimation to resistance to colonial hegemony and discuss the implications of our results for the construction of ethnic identities, now and in the past.

Further insight into the global variability of the OCA2-HERC2 locus for human pigmentation from multiallelic markers

The OCA2-HERC2 locus is responsible for the greatest proportion of eye color variation in humans. Numerous studies extensively described both functional SNPs and associated patterns of variation over this region. The goal of our study is to examine how these haplotype structures and allelic associations vary when highly variable markers such as microsatellites are used. Eleven microsatellites spanning 357 Kb of OCA2-HERC2 genes are analyzed in 3029 individuals from worldwide populations. We found that several markers display large differences in allele frequency (10% to 35% difference) among Europeans, East Asians and Africans. In Europe, the alleles showing increased frequency can also discriminate individuals with (IrisPlex) predicted blue and brown eyes. Distinct haplotypes are identified around the variants C and T of the functional SNP rs12913832 (associated to blue eyes), with linkage disequilibrium r² values significant up to 237 Kb. The haplotype carrying the allele rs12913832 C has high frequency (76%) in blue eye predicted individuals (30% in brown eye predicted individuals), while the haplotype associated to the allele rs12913832 T is restricted to brown eye predicted individuals. Finally, homozygosity values reach levels of 91% near rs12913832. Odds ratios show values of 4.2, 7.4 and 10.4 for four markers around rs12913832 and 7.1 for their core haplotype. Hence, this study provides an example on the informativeness of multiallelic markers that, despite their current limited potential contribution to forensic eye color prediction, supports the use of microsatellites for identifying causing variants showing similar genetic features and history.

Genetic ancestry, admixture, and population structure in rural Dominica

The Caribbean is a genetically diverse region with heterogeneous admixture compositions influenced by local island ecologies, migrations, colonial conflicts, and demographic histories. The Commonwealth of Dominica is a mountainous island in the Lesser Antilles historically known to harbor communities with unique patterns of migration, mixture, and isolation. This community-based population genetic study adds biological evidence to inform post-colonial narrative histories in a Dominican horticultural village. High density single nucleotide polymorphism data paired with a previously compiled genealogy provide the first genome-wide insights on genetic ancestry and population structure in Dominica. We assessed family-based clustering, inferred global ancestry, and dated recent admixture by implementing the fastSTRUCTURE clustering algorithm, modeling graph-based migration with TreeMix, assessing patterns of linkage disequilibrium decay with ALDER, and visualizing data from Dominica with Human Genome Diversity Panel references. These analyses distinguish family-based genetic structure from variation in African, European, and indigenous Amerindian admixture proportions, and analyses of linkage disequilibrium decay estimate admixture dates 5–6 generations (~160 years) ago. African ancestry accounts for the largest mixture components, followed by European and then indigenous components; however, our global ancestry inferences are consistent with previous mitochondrial, Y chromosome, and ancestry marker data from Dominica that show uniquely higher proportions of indigenous ancestry and lower proportions of African ancestry relative to known admixture in other French- and English-speaking Caribbean islands. Our genetic results support local narratives about the community’s history and founding, which indicate that newly emancipated people settled in the steep, dense vegetation along Dominica’s eastern coast in the mid-19^th century. Strong genetic signals of post-colonial admixture and family-based structure highlight the localized impacts of colonial forces and island ecologies in this region, and more data from other groups are needed to more broadly inform on Dominica’s complex history and present diversity.

Genetic risk for obesity and the effectiveness of the ChooseWell 365 workplace intervention to prevent weight gain and improve dietary choices

BACKGROUND

It is unknown whether behavioral interventions to improve diet are effective in people with a genetic predisposition to obesity.

OBJECTIVES

To examine associations between BMI genetic risk and changes in weight and workplace purchases by employees participating in a randomized controlled trial of an automated behavioral workplace intervention to promote healthy food choices.

METHODS

Participants were hospital employees enrolled in a 12-mo intervention followed by a 12-mo follow-up. Hospital cafeterias utilized a traffic-light labeling system (e.g., green = healthy, red = unhealthy) that was used to calculate a validated Healthy Purchasing Score (HPS; higher = healthier). A weighted genome-wide BMI genetic score was generated by summing BMI-increasing alleles.

RESULTS

The study included 397 adults of European ancestry (mean age, 44.9 y; 80.9% female). Participants in the highest genetic quartile (Q4) had a lower HPS and higher purchases of red-labeled items relative to participants in the lowest quartile (Q1) at baseline [Q4-Q1 Beta HPS, -4.66 (95% CI, -8.01 to -1.32); red-labeled items, 4.26% (95% CI, 1.45%-7.07%)] and at the 12-mo [HPS, -3.96 (95% CI, -7.5 to -0.41); red-labeled items, 3.20% (95% CI, 0.31%-6.09%)] and 24-mo [HPS, -3.70 (95% CI, -7.40 to 0.00); red-labeled items, 3.48% (95% CI, 0.54%-6.41%)] follow-up periods. In the intervention group, increases in HPS were similar in Q4 and Q1 at 12 mo (Q4-Q1 Beta, 1.04; 95% CI, -2.42 to 4.50). At the 24-mo follow-up, the change in BMI from baseline was similar between Q4 and Q1 (0.17 kg/m2; 95% CI, -0.55 to 0.89 kg/m2) in the intervention group, but higher in Q4 than Q1 (1.20 kg/m2; 95% CI, 0.26-2.13 kg/m2) in the control group. No interaction was evident between the treatment arm and genetic score for BMI or HPS.

CONCLUSIONS

Having a high BMI genetic risk was associated with greater increases in BMI and lower quality purchases over 2 y. The 12-mo behavioral intervention improved employees' food choices, regardless of the genetic burden, and may have attenuated weight gain conferred by having the genetic risk.

Understanding population structure in an evolutionary context: population-specific FST and pairwise FST

Populations are shaped by their history. It is crucial to interpret population structure in an evolutionary context. Pairwise F_ST measures population structure, whereas population-specific F_ST measures deviation from the ancestral population. To understand the current population structure and a population’s history of range expansion, we propose a representation method that overlays population-specific F_ST estimates on a sampling location map, and on an unrooted neighbor-joining tree and a multi-dimensional scaling plot inferred from a pairwise F_ST distance matrix. We examined the usefulness of our procedure using simulations that mimicked population colonization from an ancestral population and by analyzing published human, Atlantic cod, and wild poplar data. Our results demonstrated that population-specific F_ST values identify the source population and trace the evolutionary history of its derived populations. Conversely, pairwise F_ST values represent the current population structure. By integrating the results of both estimators, we obtained a new picture of the population structure that incorporates evolutionary history. The generalized least squares estimate of genome-wide population-specific F_ST indicated that the wild poplar population expanded its distribution to the north, where daylight hours are long in summer, to coastal areas with abundant rainfall, and to the south where summers are dry. Genomic data highlight the power of the bias-corrected moment estimators of F_ST, whether global, pairwise, or population-specific, that provide unbiased estimates of F_ST. All F_ST moment estimators described in this paper have reasonable processing times and are useful in population genomics studies.

Ancestral patterns of recessive dystrophic epidermolysis bullosa mutations in Hispanic populations suggest sephardic ancestry

Recessive dystrophic epidermolysis bullosa (RDEB) is a rare genodermatosis caused by mutations in the gene coding for type VII collagen (COL7A1). More than 800 different pathogenic mutations in COL7A1 have been described to date; however, the ancestral origins of many of these mutations have not been precisely identified. In this study, 32 RDEB patient samples from the Southwestern United States, Mexico, Chile, and Colombia carrying common mutations in the COL7A1 gene were investigated to determine the origins of these mutations and the extent to which shared ancestry contributes to disease prevalence. The results demonstrate both shared European and American origins of RDEB mutations in distinct populations in the Americas and suggest the influence of Sephardic ancestry in at least some RDEB mutations of European origins. Knowledge of ancestry and relatedness among RDEB patient populations will be crucial for the development of future clinical trials and the advancement of novel therapeutics.

Population-specific reference panels are crucial for genetic analyses: an example of the CREBRF locus in Native Hawaiians

Statistical imputation applied to genome-wide array data is the most cost-effective approach to complete the catalog of genetic variation in a study population. However, imputed genotypes in underrepresented populations incur greater inaccuracies due to ascertainment bias and a lack of representation among reference individuals, further contributing to the obstacles to study these populations. Here we examined the consequences due to the lack of representation by genotyping in a large number of self-reported Native Hawaiians (N = 3693) a functionally important, Polynesian-specific variant in the CREBRF gene, rs373863828. We found the derived allele was significantly associated with several adiposity traits with large effects (e.g. ~ 1.28 kg/m2 per allele in body mass index as the most significant; P = 7.5 × 10-5), consistent with the original findings in Samoans. Due to the current absence of Polynesian representation in publicly accessible reference sequences, rs373863828 or its proxies could not be tested through imputation using these existing resources. Moreover, the association signals at the entire CREBRF locus could not be captured by alternative approaches, such as admixture mapping. In contrast, highly accurate imputation can be achieved even if a small number (<200) of internally constructed Polynesian reference individuals were available; this would increase sample size and improve the statistical evidence of associations. Taken together, our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci such as CREBRF. Yet, they could be easily detected and prioritized with improved representation of diverse populations in sequencing studies.

Admixture mapping reveals the association between Native American ancestry at 3q13.11 and reduced risk of Alzheimer's disease in Caribbean Hispanics

BACKGROUND

Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci.

METHODS

We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry.

RESULTS

Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry.

CONCLUSION

These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.

Copy Number Profiles of Prostate Cancer in Men of Middle Eastern Ancestry

Simple Summary

Prostate cancer is the most commonly diagnosed non-skin malignancy in men. Numerous studies have been undertaken to explore the role that genomics plays in prostate cancer initiation and progression. Most of this genomic data comes tumors arising in men with European or Asian ancestry, leaving other ancestry groups understudied. To fill this gap, we investigated the differences in copy number aberrations between prostate cancers arising in men of Middle Eastern ethnicity and those of European, African, or East Asian ethnicities in the hope of better understanding the incidence and risk of prostate cancer in different populations. We identified ancestry-specific gains and deletions, as well as differences in overall genomic instability between ancestry groups. This confirms that ancestry should be considered when investigating and characterizing biomarkers and molecular signatures relative to disease progression, prognosis, and potentially therapeutic targeting.

Abstract

Our knowledge of prostate cancer (PCa) genomics mainly reflects European (EUR) and Asian (ASN) populations. Our understanding of the influence of Middle Eastern (ME) and African (AFR) ancestry on the mutational profiles of prostate cancer is limited. To characterize genomic differences between ME, EUR, ASN, and AFR ancestry, fluorescent in situ hybridization (FISH) studies for NKX3-1 deletion and MYC amplification were carried out on 42 tumors arising in individuals of ME ancestry. These were supplemented by analysis of genome-wide copy number profiles of 401 tumors of all ancestries. FISH results of NKX3-1 and MYC were assessed in the ME cohort and compared to other ancestries. Gene level copy number aberrations (CNAs) for each sample were statistically compared between ancestry groups. NKX3-1 deletions by FISH were observed in 17/42 (17.5%) prostate tumors arising in men of ME ancestry, while MYC amplifications were only observed in 1/42 (2.3%). Using CNAs called from arrays, the incidence of NKX3-1 deletions was significantly lower in ME vs. other ancestries (20% vs. 52%; p = 2.3 × 10⁻³). Across the genome, tumors arising in men of ME ancestry had fewer CNAs than those in men of other ancestries (p = 0.014). Additionally, the somatic amplification of 21 specific genes was more frequent in tumors arising in men of ME vs. EUR ancestry (two-sided proportion test; Q < 0.05). Those included amplifications in the glutathione S-transferase family on chromosome 1 (GSTM1, GSTM2, GSTM5) and the IQ motif-containing family on chromosome 3 (IQCF1, IQCF2, IQCF13, IQCF4, IQCF5, IQCF6). Larger studies investigating ME populations are warranted to confirm these observations.

Genetic relationships of Southwest Asian and Mediterranean populations

The Southwest Asian, circum-Mediterranean, and Southern European populations (collectively, SWAMSE) together with Northern European populations form one of five "continental" groups of global populations in many analyses of population relationships. This region is of great anthropologic and forensic interest but relationships of large numbers of populations within the region have not been able to be cleanly resolved with autosomal genetic markers. To examine the genetic boundaries to the SWAMSE region and whether internal structure can be detected we have assembled data for a total of 151 separate autosomal genetic markers on populations in this region and other parts of the world for a global set of 95 populations. The markers include 83 ancestry informative SNPs as singletons and 68 microhaplotype loci defined by 204 SNPs. The 151 loci are ancestry informative on a global scale, identifying at least five biogeographic clusters. One of those clusters is a clear grouping of 37 populations containing the SWAMSE plus northern European populations to the exclusion of populations in South Central Asia and populations from farther East. A refined analysis of the 37 populations shows the northern European populations clustering separately from the SWAMSE populations. Within Southwest Asia the Samaritans and Shabaks are distinct outliers. The Yemenite Jews, Saudi, Kuwaiti, Palestinian Arabs, and Southern Tunisians cluster together loosely while the remaining populations from Northern Iraq, Mediterranean Europe, the Caucasus region, and Iran cluster in a more complex graded fashion. The majority of the SWAMSE populations from the mainland of Southwest Asia form a cluster with little internal structure reflecting a very complex history of endogamy and migrations. The set of 151 DNA polymorphisms not only distinguishes major geographical regions globally but can distinguish ancestry to a small degree within geographical regions such as SWAMSE. We discuss forensic characteristics of the polymorphisms and also identify those that rank highest by Rosenberg's I_n measure for the SWAMSE region populations and for the global set of populations analyzed. DATA AVAILABILITY: Genotypes on all 151 markers for all 3790 individuals typed in the Kidd Lab on the 72 Kidd lab populations have been deposited in the Zenodo archive and can be freely accessed at https://doi.org/10.5281/zenodo.4658892. Some of the data has been made public previously as supplemental files appended to publications. Data for the additional individuals included in the analyses was taken from already public datasets as indicated in the text.

The analysis of ancestry with small-scale forensic panels of genetic markers

In the last 10 years, forensic genetic analysis has been extended beyond identification tests that link a suspect to crime scene evidence using standard DNA profiling, to new supplementary tests that can provide information to investigators about a suspect in the absence of a database hit or eyewitness testimony. These tests now encompass the prediction of physical appearance, ancestry and age. In this review, we give a comprehensive overview of the full range of DNA-based ancestry inference tests designed to work with forensic contact traces, when the level of DNA is often very low or highly degraded. We outline recent developments in the design of ancestry-informative marker sets, forensic assays that use capillary electrophoresis or massively parallel sequencing, and the statistical analysis frameworks that examine the test profile and compares it to reference population variation. Three casework ancestry analysis examples are described which were successfully accomplished in the authors' laboratory, where the ancestry information obtained was critical to the outcome of the DNA analyses made.

Integrating Linguistics, Social Structure, and Geography to Model Genetic Diversity within India

India represents an intricate tapestry of population substructure shaped by geography, language, culture, and social stratification. Although geography closely correlates with genetic structure in other parts of the world, the strict endogamy imposed by the Indian caste system and the large number of spoken languages add further levels of complexity to understand Indian population structure. To date, no study has attempted to model and evaluate how these factors have interacted to shape the patterns of genetic diversity within India. We merged all publicly available data from the Indian subcontinent into a data set of 891 individuals from 90 well-defined groups. Bringing together geography, genetics, and demographic factors, we developed Correlation Optimization of Genetics and Geodemographics to build a model that explains the observed population genetic substructure. We show that shared language along with social structure have been the most powerful forces in creating paths of gene flow in the subcontinent. Furthermore, we discover the ethnic groups that best capture the diverse genetic substructure using a ridge leverage score statistic. Integrating data from India with a data set of additional 1,323 individuals from 50 Eurasian populations, we find that Indo-European and Dravidian speakers of India show shared genetic drift with Europeans, whereas the Tibeto-Burman speaking tribal groups have maximum shared genetic drift with East Asians.

Radiation-related genomic profile of papillary thyroid carcinoma after the Chernobyl accident

The 1986 Chernobyl nuclear power plant accident increased papillary thyroid carcinoma (PTC) incidence in surrounding regions, particularly for radioactive iodine (¹³¹I)-exposed children. We analyzed genomic, transcriptomic, and epigenomic characteristics of 440 PTCs from Ukraine (from 359 individuals with estimated childhood ¹³¹I exposure and 81 unexposed children born after 1986). PTCs displayed radiation dose-dependent enrichment of fusion drivers, nearly all in the mitogen-activated protein kinase pathway, and increases in small deletions and simple/balanced structural variants that were clonal and bore hallmarks of nonhomologous end-joining repair. Radiation-related genomic alterations were more pronounced for individuals who were younger at exposure. Transcriptomic and epigenomic features were strongly associated with driver events but not radiation dose. Our results point to DNA double-strand breaks as early carcinogenic events that subsequently enable PTC growth after environmental radiation exposure.

Hypomethylation mediates genetic association with the major histocompatibility complex genes in Sjögren's syndrome

Differential methylation of immune genes has been a consistent theme observed in Sjögren's syndrome (SS) in CD4+ T cells, CD19+ B cells, whole blood, and labial salivary glands (LSGs). Multiple studies have found associations supporting genetic control of DNA methylation in SS, which in the absence of reverse causation, has positive implications for the potential of epigenetic therapy. However, a formal study of the causal relationship between genetic variation, DNA methylation, and disease status is lacking. We performed a causal mediation analysis of DNA methylation as a mediator of nearby genetic association with SS using LSGs and genotype data collected from 131 female members of the Sjögren's International Collaborative Clinical Alliance registry, comprising of 64 SS cases and 67 non-cases. Bumphunter was used to first identify differentially-methylated regions (DMRs), then the causal inference test (CIT) was applied to identify DMRs mediating the association of nearby methylation quantitative trait loci (MeQTL) with SS. Bumphunter discovered 215 DMRs, with the majority located in the major histocompatibility complex (MHC) on chromosome 6p21.3. Consistent with previous findings, regions hypomethylated in SS cases were enriched for gene sets associated with immune processes. Using the CIT, we observed a total of 19 DMR-MeQTL pairs that exhibited strong evidence for a causal mediation relationship. Close to half of these DMRs reside in the MHC and their corresponding meQTLs are in the region spanning the HLA-DQA1, HLA-DQB1, and HLA-DQA2 loci. The risk of SS conferred by these corresponding MeQTLs in the MHC was further substantiated by previous genome-wide association study results, with modest evidence for independent effects. By validating the presence of causal mediation, our findings suggest both genetic and epigenetic factors contribute to disease susceptibility, and inform the development of targeted epigenetic modification as a therapeutic approach for SS.

Lack of transgenerational effects of ionizing radiation exposure from the Chernobyl accident

Effects of radiation exposure from the Chernobyl nuclear accident remain a topic of interest. We investigated germline de novo mutations (DNMs) in children born to parents employed as cleanup workers or exposed to occupational and environmental ionizing radiation after the accident. Whole-genome sequencing of 130 children (born 1987-2002) and their parents did not reveal an increase in the rates, distributions, or types of DNMs relative to the results of previous studies. We find no elevation in total DNMs, regardless of cumulative preconception gonadal paternal [mean = 365 milligrays (mGy), range = 0 to 4080 mGy] or maternal (mean = 19 mGy, range = 0 to 550 mGy) exposure to ionizing radiation. Thus, we conclude that, over this exposure range, evidence is lacking for a substantial effect on germline DNMs in humans, suggesting minimal impact from transgenerational genetic effects.

Toward a fine-scale population health monitoring system

Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens and environmental factors impacting specific sub-populations. Here, we propose a framework for repurposing data from electronic health records (EHRs) in concert with genomic data to explore the demographic ties that can impact disease burdens. Using data from a diverse biobank in New York City, we identified 17 communities sharing recent genetic ancestry. We observed 1,177 health outcomes that were statistically associated with a specific group and demonstrated significant differences in the segregation of genetic variants contributing to Mendelian diseases. We also demonstrated that fine-scale population structure can impact the prediction of complex disease risk within groups. This work reinforces the utility of linking genomic data to EHRs and provides a framework toward fine-scale monitoring of population health.

Genomic insight into the population history of Central Han Chinese

BACKGROUND

In recent decades, considerable attention has been paid to exploring the population genetic characteristics of Han Chinese, mainly documenting a north-south genetic substructure. However, the central Han Chinese have been largely underrepresented in previous studies.

AIM

To infer a comprehensive understanding of the homogenisation process and population history of Han Chinese.

SUBJECTS AND METHODS

We collected samples from 122 Han Chinese from seven counties of Hubei province in central China and genotyped 534,000 genome-wide SNPs. We compared Hubei Han with both ancient and present-day Eurasian populations using Principal Component Analysis, ADMIXTURE, f statistics, qpWave and qpAdm.

RESULTS

We observed Hubei Han Chinese are at a genetically intermediate position on the north-south Han Chinese cline. We have not detected any significant genetic substructure in the studied groups from seven different counties. Hubei Han show significant evidence of genetic admixture deriving about 63% of ancestry from Tai-Kadai or Austronesian-speaking southern indigenous groups and 37% from Tungusic or Mongolic related northern populations.

CONCLUSIONS

The formation of Han Chinese has involved extensive admixture with Tai-Kadai or Austronesian-speaking populations in the south and Tungusic or Mongolic speaking populations in the north. The convenient transportation and central location of Hubei make it the key region for the homogenisation of Han Chinese.

European genetic ancestry associated with risk of childhood ependymoma

BACKGROUND

Ependymoma is a histologically defined central nervous system tumor most commonly occurring in childhood. Population-level incidence differences by race/ethnicity are observed, with individuals of European ancestry at highest risk. We aimed to determine whether extent of European genetic ancestry is associated with ependymoma risk in US populations.

METHODS

In a multi-ethnic study of Californian children (327 cases, 1970 controls), we estimated the proportions of European, African, and Native American ancestry among recently admixed Hispanic and African American subjects and estimated European admixture among non-Hispanic white subjects using genome-wide data. We tested whether genome-wide ancestry differences were associated with ependymoma risk and performed admixture mapping to identify associations with local ancestry. We also evaluated race/ethnicity-stratified ependymoma incidence data from the Central Brain Tumor Registry of the United States (CBTRUS).

RESULTS

CBTRUS data revealed that African American and Native American children have 33% and 36%, respectively, reduced incidence of ependymoma compared with non-Hispanic whites. In genetic analyses, a 20% increase in European ancestry was associated with a 1.31-fold higher odds of ependymoma among self-reported Hispanics and African Americans (95% CI: 1.08-1.59, Pmeta = 6.7 × 10-3). Additionally, eastern European ancestral substructure was associated with increased ependymoma risk in non-Hispanic whites (P = 0.030) and in Hispanics (P = 0.043). Admixture mapping revealed a peak at 20p13 associated with increased local European ancestry, and targeted fine-mapping identified a lead variant at rs6039499 near RSPO4 (odds ratio = 1.99; 95% CI: 1.45-2.73; P = 2.2 × 10-5) but which was not validated in an independent set of posterior fossa type A patients.

CONCLUSIONS

Interethnic differences in ependymoma risk are recapitulated in the genomic ancestry of ependymoma patients, implicating regions to target in future association studies.

Complete mitogenomes document substantial genetic contribution from the Eurasian Steppe into northern Pakistani Indo-Iranian speakers

To elucidate whether Bronze Age population dispersals from the Eurasian Steppe to South Asia contributed to the gene pool of Indo-Iranian-speaking groups, we analyzed 19,568 mitochondrial DNA (mtDNA) sequences from northern Pakistani and surrounding populations, including 213 newly generated mitochondrial genomes (mitogenomes) from Iranian and Dardic groups, both speakers from the ancient Indo-Iranian branch in northern Pakistan. Our results showed that 23% of mtDNA lineages with west Eurasian origin arose in situ in northern Pakistan since ~5000 years ago (kya), a time depth very close to the documented Indo-European dispersals into South Asia during the Bronze Age. Together with ancient mitogenomes from western Eurasia since the Neolithic, we identified five haplogroups (~8.4% of maternal gene pool) with roots in the Steppe region and subbranches arising (age ~5-2 kya old) in northern Pakistan as genetic legacies of Indo-Iranian speakers. Some of these haplogroups, such as W3a1b that have been found in the ancient samples from the late Bronze Age to the Iron Age period individuals of Swat Valley northern Pakistan, even have sub-lineages (age ~4 kya old) in the southern subcontinent, consistent with the southward spread of Indo-Iranian languages. By showing that substantial genetic components of Indo-Iranian speakers in northern Pakistan can be traced to Bronze Age in the Steppe region, our study suggests a demographic link with the spread of Indo-Iranian languages, and further highlights the corridor role of northern Pakistan in the southward dispersal of Indo-Iranian-speaking groups.

Genetic determinants of daytime napping and effects on cardiometabolic health

Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference.

A comprehensive analysis comparing linear and generalized linear models in detecting adaptive SNPs

To understand how organisms adapt to their environment, a gene-environmental association (GEA) analysis is commonly conducted. GEA methods based on mixed models, such as linear latent factor mixed models (LFMM) and LFMM2, have grown in popularity for their robust performance in terms of power and computational speed. However, it is unclear how the assumption of a Gaussian distribution for the response variables influences model performance. In this paper, we develop a generalized linear model (GLM) that allows for non-Gaussian distribution in the genotypic response variables, and treatment of multiallelic nucleotide polymorphisms. Moreover, this multinomial logistic regression model (MLR) is combined with an admixture-based model or principal components analysis to correct for population structure (MLR-ADM and MLR-PC). Using simulations, we evaluate the type 1 error, false discovery rates (FDR), and power to detect selected SNPs, to guide model choice and best practices. With genomic control, MLR-PC and LFMM2 have similar type 1 error, FDRs, and power when analysing biallelic SNPs, while dramatically outperforming models not accounting for population structure. Differences in performance occur under continuous population structure where MLR-PC outperforms LFMM/LFMM2, especially when a larger number of clusters or triallelic SNPs are analysed. The Human Genome Diversity Project (HGDP) data set shows that both MLR-PC and LFMM2 control the inflation of P -values. Analysis of the 1,000 Genome Project Phase 3 data set illustrates that MLR-PC and LFMM2 produce consistent results for most significant SNPs, while MLR-PC discovered additional SNPs corresponding to certain genes, suggesting MLR-PC may be a useful alternative to GEA inference.

Exploring European ancestry among the Kalash population: a mitogenomic perspective

With a population of around 4 000 individuals, the Kalash people have been living in the Hindu-Kush mountain valleys of present-day northern Pakistan for centuries. Due to their mysterious origin and fairer European complexion, the genetic history of this ethnic group has been investigated previously using different markers. To date, however, the maternal genetic architecture has not been systematically dissected based on high-resolution complete mitochondrial genomes (mitogenomes), making their maternal genetic history, especially their genetic connection with Europeans from a matrilineal perspective, unclear. To unravel this issue, we analyzed mitogenome data of 34 Kalash samples together with 6 075 individuals from across Eurasia. Our results indicated exclusive western Eurasian origin of the Kalash people, represented by eight haplogroups. Among these haplogroups, J2b1a7a and R0a5a (accounting for ~50% of the Kalash gene pool) displayed in situ differentiations in the Kalash and could be traced to the Mediterranean region. Age estimations suggested these haplogroups arose in the Kalash population ~2.26 and 3.01 thousand years ago (kya), a time frame consistent with the invasion of Alexander III of Macedon to the region. One possible explanation for the maternal genetic contribution from Europeans to the Kalash people would be the involvement of women in foreign campaigns of ancient Greek warfare, followed by a founder effect. Our study thus sheds important light on the genetic origin of the Kalash community of Pakistan.

Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power

Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African-European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants.

Creating artificial human genomes using generative neural networks

Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements in machine learning algorithms and increased computational power. Despite these impressive achievements, the ability of generative models to create realistic synthetic data is still under-exploited in genetics and absent from population genetics. Yet a known limitation in the field is the reduced access to many genetic databases due to concerns about violations of individual privacy, although they would provide a rich resource for data mining and integration towards advancing genetic studies. In this study, we demonstrated that deep generative adversarial networks (GANs) and restricted Boltzmann machines (RBMs) can be trained to learn the complex distributions of real genomic datasets and generate novel high-quality artificial genomes (AGs) with none to little privacy loss. We show that our generated AGs replicate characteristics of the source dataset such as allele frequencies, linkage disequilibrium, pairwise haplotype distances and population structure. Moreover, they can also inherit complex features such as signals of selection. To illustrate the promising outcomes of our method, we showed that imputation quality for low frequency alleles can be improved by data augmentation to reference panels with AGs and that the RBM latent space provides a relevant encoding of the data, hence allowing further exploration of the reference dataset and features for solving supervised tasks. Generative models and AGs have the potential to become valuable assets in genetic studies by providing a rich yet compact representation of existing genomes and high-quality, easy-access and anonymous alternatives for private databases.

Large-scale Inference of Population Structure in Presence of Missingness using PCA

MOTIVATION

Principal component analysis (PCA) is a commonly used tool in genetics to capture and visualize population structure. Due to technological advances in sequencing, such as the widely used non-invasive prenatal test, massive datasets of ultra-low coverage sequencing are being generated. These datasets are characterized by having a large amount of missing genotype information.

RESULTS

We present EMU, a method for inferring population structure in the presence of rampant non-random missingness. We show through simulations that several commonly used PCA methods can not handle missing data arisen from various sources, which leads to biased results as individuals are projected into the PC space based on their amount of missingness. In terms of accuracy, EMU outperforms an existing method that also accommodates missingness while being competitively fast. We further tested EMU on around 100K individuals of the Phase 1 dataset of the Chinese Millionome Project, that were shallowly sequenced to around 0.08x. From this data we are able to capture the population structure of the Han Chinese and to reproduce previous analysis in a matter of CPU hours instead of CPU years. EMU's capability to accurately infer population structure in the presence of missingness will be of increasing importance with the rising number of large-scale genetic datasets.

AVAILABILITY

EMU is written in Python and is freely available at https://github.com/rosemeis/emu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exploring Population Structure with Admixture Models and Principal Component Analysis

Population structure is a commonplace feature of genetic variation data, and it has importance in numerous application areas, including evolutionary genetics, conservation genetics, and human genetics. Understanding the structure in a sample is necessary before more sophisticated analyses are undertaken. Here we provide a protocol for running principal component analysis (PCA) and admixture proportion inference-two of the most commonly used approaches in describing population structure. Along with hands-on examples with CEPH-Human Genome Diversity Panel and pragmatic caveats, readers will learn to analyze and visualize population structure on their own data.

Variation in genes implicated in B-cell development and antibody production affects susceptibility to pemphigus

Pemphigus foliaceus (PF) is an autoimmune blistering skin disease characterized by the presence of pathogenic autoantibodies against desmoglein 1, a component of intercellular desmosome junctions. PF occurs sporadically across the globe and is endemic in some Brazilian regions. Because PF is a B-cell-mediated disease, we aimed to study the impact of variants within genes encoding molecules involved in the different steps of B-cell development and antibody production on the susceptibility of endemic PF. We analysed 3,336 single nucleotide polymorphisms (SNPs) from 167 candidate genes genotyped with Illumina microarray in a cohort of 227 PF patients and 193 controls. After quality control and exclusion of non-informative and redundant SNPs, 607 variants in 149 genes remained in the logistic regression analysis, in which sex and ancestry were included as covariates. Our results revealed 10 SNPs within or nearby 11 genes that were associated with susceptibility to endemic PF (OR >1.56; p < 0.005): rs6657275*G (TGFB2); rs1818545*A (RAG1/RAG2/IFTAP);rs10781530*A (PAXX), rs10870140*G and rs10781522*A (TRAF2); rs535068*A (TNFRSF1B); rs324011*A (STAT6);rs6432018*C (YWHAQ); rs17149161*C (YWHAG); and rs2070729*C (IRF1). Interestingly, these SNPs have been previously associated with differential gene expression, mostly in peripheral blood, in publicly available databases. For the first time, we show that polymorphisms in genes involved in B-cell development and antibody production confer differential susceptibility to endemic PF, and therefore are candidates for possible functional studies to understand immunoglobulin gene rearrangement and its impact on diseases.

Genetic ancestry, skin pigmentation, and the risk of cutaneous squamous cell carcinoma in Hispanic/Latino and non-Hispanic white populations

Although cutaneous squamous cell carcinoma (cSCC) is one of the most common malignancies in individuals of European ancestry, the incidence of cSCC in Hispanic/Latinos is also increasing. cSCC has both a genetic and environmental etiology. Here, we examine the role of genetic ancestry, skin pigmentation, and sun exposure in Hispanic/Latinos and non-Hispanic whites on cSCC risk. We observe an increased cSCC risk with greater European ancestry (P = 1.27 × 10⁻⁴²) within Hispanic/Latinos and with greater northern (P = 2.38 × 10⁻⁶⁵) and western (P = 2.28 × 10⁻⁴⁹) European ancestry within non-Hispanic whites. These associations are significantly, but not completely, attenuated after considering skin pigmentation-associated loci, history of actinic keratosis, and sun-protected versus sun-exposed anatomical sites. We also report an association of the well-known pigment variant Ala111Thr (rs1426654) at SLC24A5 with cSCC in Hispanic/Latinos. These findings demonstrate a strong correlation of northwestern European genetic ancestry with cSCC risk in both Hispanic/Latinos and non-Hispanic whites, largely but not entirely mediated through its impact on skin pigmentation.

Eric Jorgenson and Hélène Choquet et al. find that northwestern European genetic ancestry is associated with increased risk of cutaneous squamous cell carcinoma (cSCC) in non-Hispanic whites, and more so in Hispanic/Latinos of the US. The ancestry effect is largely, but not entirely explained by genetic determinants of skin pigmentation in both populations.

Population history of North Africa based on modern and ancient genomes

Compared with the rest of the African continent, North Africa has provided limited genomic data. Nonetheless, the genetic data available show a complex demographic scenario characterized by extensive admixture and drift. Despite the continuous gene flow from the Middle East, Europe and sub-Saharan Africa, an autochthonous genetic component that dates back to pre-Holocene times is still present in North African groups. The comparison of ancient and modern genomes has evidenced a genetic continuity in the region since Epipaleolithic times. Later population movements, especially the gene flow from the Middle East associated with the Neolithic, have diluted the genetic autochthonous component, creating an east to west gradient. Recent historical movements, such as the Arabization, have also contributed to the genetic landscape observed currently in North Africa and have culturally transformed the region. Genome analyses have not shown evidence of a clear correlation between cultural and genetic diversity in North Africa, as there is no genetic pattern of differentiation between Tamazight (i.e. Berber) and Arab speakers as a whole. Besides the gene flow received from neighboring areas, the analysis of North African genomes has shown that the region has also acted as a source of gene flow since ancient times. As a result of the genetic uniqueness of North African groups and the lack of available data, there is an urgent need for the study of genetic variation in the region and its implications in health and disease.

Genetic admixture in Brazil

We review studies from our laboratories using different molecular tools to characterize the Amerindian, European and African ancestry of Brazilians. Initially we used uniparental DNA markers to investigate the contribution of distinct Y chromosome and mitochondrial DNA lineages to present-day populations. High levels of genetic admixture and strong directional mating between European males and Amerindian and African females were unraveled. We next analyzed different types of biparental autosomal polymorphisms. Especially useful was a set of 40 insertion-deletion polymorphisms (indels) that when studied worldwide proved exquisitely sensitive in discriminating between Amerindians, Europeans and Sub-Saharan Africans. When applied to the study of Brazilians these markers confirmed extensive genomic admixture. We then studied ancestry differences in different regions by statistically controlling them to eliminate color considerations. The European ancestry was predominant in all regions studied, with proportions ranging from 60.6% in the Northeast to 77.7% in the South. We propose that the immigration of 6 million Europeans to Brazil in the 19th and 20th centuries is in large part responsible for dissipating previous ancestry dissimilarities that reflected region-specific population histories. Brazilians should be assessed individually, as 210 million human beings, and not as members of specific regions or color groups.

Positive selection in admixed populations from Ethiopia

BACKGROUND

In the process of adaptation of humans to their environment, positive or adaptive selection has played a main role. Positive selection has, however, been under-studied in African populations, despite their diversity and importance for understanding human history.

RESULTS

Here, we have used 119 available whole-genome sequences from five Ethiopian populations (Amhara, Oromo, Somali, Wolayta and Gumuz) to investigate the modes and targets of positive selection in this part of the world. The site frequency spectrum-based test SFselect was applied to idfentify a wide range of events of selection (old and recent), and the haplotype-based statistic integrated haplotype score to detect more recent events, in each case with evaluation of the significance of candidate signals by extensive simulations. Additional insights were provided by considering admixture proportions and functional categories of genes. We identified both individual loci that are likely targets of classic sweeps and groups of genes that may have experienced polygenic adaptation. We found population-specific as well as shared signals of selection, with folate metabolism and the related ultraviolet response and skin pigmentation standing out as a shared pathway, perhaps as a response to the high levels of ultraviolet irradiation, and in addition strong signals in genes such as IFNA, MRC1, immunoglobulins and T-cell receptors which contribute to defend against pathogens.

CONCLUSIONS

Signals of positive selection were detected in Ethiopian populations revealing novel adaptations in East Africa, and abundant targets for functional follow-up.

Broadening the Applicability of a Custom Multi-Platform Panel of Microhaplotypes: Bio-Geographical Ancestry Inference and Expanded Reference Data

The development of microhaplotype (MH) panels for massively parallel sequencing (MPS) platforms is gaining increasing relevance for forensic analysis. Here, we expand the applicability of a 102 autosomal and 11 X-chromosome panel of MHs, previously validated with both MiSeq and Ion S5 MPS platforms and designed for identification purposes. We have broadened reference population data for identification purposes, including data from 240 HGDP-CEPH individuals of native populations from North Africa, the Middle East, Oceania and America. Using the enhanced population data, the panel was evaluated as a marker set for bio-geographical ancestry (BGA) inference, providing a clear differentiation of the five main continental groups of Africa, Europe, East Asia, Native America, and Oceania. An informative degree of differentiation was also achieved for the population variation encompassing North Africa, Middle East, Europe, South Asia, and East Asia. In addition, we explored the potential for individual BGA inference from simple mixed DNA, by simulation of mixed profiles followed by deconvolution of mixture components.

A review of UMAP in population genetics

Uniform manifold approximation and projection (UMAP) has been rapidly adopted by the population genetics community to study population structure. It has become common in visualizing the ancestral composition of human genetic datasets, as well as searching for unique clusters of data, and for identifying geographic patterns. Here we give an overview of applications of UMAP in population genetics, provide recommendations for best practices, and offer insights on optimal uses for the technique.

Massively parallel sequencing of sex-chromosomal STRs in Saudi Arabia reveals patrilineage-associated sequence variants

Massively parallel sequencing (MPS) of forensic STRs has the potential to reveal additional allele diversity compared to conventional capillary electrophoresis (CE) typing strategies, but population studies are currently relatively few in number. The Verogen ForenSeq™ DNA Signature Prep Kit includes both Y-STRs and X-STRs among its targeted loci, and here we report the sequences of these loci, analysed using Verogen's ForenSeq™ Universal Analysis Software (UAS) v1.3 and STRait Razor v3.0, in a representative sample of 89 Saudi Arabian males. We identified 56 length variants (equivalent to CE alleles) and 75 repeat sequence sub-variants across the six X-STRs analysed; equivalent figures for the set of 24 Y-STRs were 147 and 192 respectively. We also observed two flanking sequence variants for the X-, and six for the Y-STRs. Recovery of sequence data and concordance with CE data (where available) across the tested loci was good, though rare flanking variation affected interpretation and allele calling at DYF387S1 and DXS7132. Examination of flanking sequences of the Y-STRs revealed five SNPs (L255, M4790, BY7692, Z16708 and S17543) previously shown to define specific haplogroups by Y-chromosome sequencing. These define Y-haplogroups in 62 % of our sample, a proportion that increases to 91 % when haplogroup-associated repeat-sequence motifs are also considered. A population-level comparison of the Saudi Arabian X-STRs with a global sample showed our dataset to be part of a large cluster of populations of West Eurasian and Middle Eastern origin.

Genetic Consequences of the Transatlantic Slave Trade in the Americas

According to historical records of transatlantic slavery, traders forcibly deported an estimated 12.5 million people from ports along the Atlantic coastline of Africa between the 16th and 19th centuries, with global impacts reaching to the present day, more than a century and a half after slavery's abolition. Such records have fueled a broad understanding of the forced migration from Africa to the Americas yet remain underexplored in concert with genetic data. Here, we analyzed genotype array data from 50,281 research participants, which-combined with historical shipping documents-illustrate that the current genetic landscape of the Americas is largely concordant with expectations derived from documentation of slave voyages. For instance, genetic connections between people in slave trading regions of Africa and disembarkation regions of the Americas generally mirror the proportion of individuals forcibly moved between those regions. While some discordances can be explained by additional records of deportations within the Americas, other discordances yield insights into variable survival rates and timing of arrival of enslaved people from specific regions of Africa. Furthermore, the greater contribution of African women to the gene pool compared to African men varies across the Americas, consistent with literature documenting regional differences in slavery practices. This investigation of the transatlantic slave trade, which is broad in scope in terms of both datasets and analyses, establishes genetic links between individuals in the Americas and populations across Atlantic Africa, yielding a more comprehensive understanding of the African roots of peoples of the Americas.

A linkage disequilibrium-based statistical test for Genome-Wide Epistatic Selection Scans in structured populations

The quest for signatures of selection using single nucleotide polymorphism (SNP) data has proven efficient to uncover genes involved in conserved and/or adaptive molecular functions, but none of the statistical methods were designed to identify interacting alleles as targets of selective processes. Here, we propose a statistical test aimed at detecting epistatic selection, based on a linkage disequilibrium (LD) measure accounting for population structure and heterogeneous relatedness between individuals. SNP-based ([Formula: see text]) and window-based ([Formula: see text]) statistics fit a Student distribution, allowing to test the significance of correlation coefficients. As a proof of concept, we use SNP data from the Medicago truncatula symbiotic legume plant and uncover a previously unknown gene coadaptation between the MtSUNN (Super Numeric Nodule) receptor and the MtCLE02 (CLAVATA3-Like) signaling peptide. We also provide experimental evidence supporting a MtSUNN-dependent negative role of MtCLE02 in symbiotic root nodulation. Using human HGDP-CEPH SNP data, our new statistical test uncovers strong LD between SLC24A5 (skin pigmentation) and EDAR (hairs, teeth, sweat glands development) world-wide, which persists after correction for population structure and relatedness in Central South Asian populations. This result suggests that epistatic selection or coselection could have contributed to the phenotypic make-up in some human populations. Applying this approach to genome-wide SNP data will facilitate the identification of coadapted gene networks in model or non-model organisms.

Investigating the genetic characteristics of the Csangos, a traditionally Hungarian speaking ethnic group residing in Romania

Csango people are an East-Central European ethnographic group living mostly in the historical region of Moldavia, Romania. Their traditional language, the Csango is an old Hungarian dialect, which is a severely endangered language due to language shift. Their origin is still disputed among experts and there are many hypotheses since the 19th century. Previous genetic studies found connection with ethnic groups living in Hungary and provided evidence which might support their Hungarian origin. Another study found Inner Asian Altaic ancestry in their genetic makeup. The goal of this study was to analyze the genetic characteristics of the Csango people by comparing their genetic characteristics to contemporary Eurasian populations based on genome-wide autosomal marker data. Our findings suggest that genetic affinity of Csangos to Hungarians is more significant than to Romanians. They also have a detectable connection with Central-Asian and Siberian Turkic ethnic groups. Besides the presumable Middle Eastern/Central-Asian Turkic ancestry, Csangos show ~4% Turkic ancestry from Central Asia/Siberia, which makes them unique in comparison to all other East-Central European populations investigated in this study. The admixture that resulted in this Turkic ancestry could have occurred 30-40 generations ago, which date interval corresponds to Hungarian historical events regarding their migration and the conquest of the Carpathian basin.

Whole Genome Sequencing of Four Representatives From the Admixed Population of the United Arab Emirates

Whole genome sequences (WGS) of four nationals of the United Arab Emirates (UAE) at an average coverage of 33X have been completed and described. The selection of suitable subpopulation representatives was informed by a preceding comprehensive population structure analysis. Representatives were chosen based on their central location within the subpopulation on a principal component analysis (PCA) and the degree to which they were admixed. Novel genomic variations among the different subgroups of the UAE population are reported here. Specifically, the WGS analysis identified 4,161,067-4,798,806 variants in the four individual samples, where approximately 80% were single nucleotide polymorphisms (SNPs) and 20% were insertions or deletions (indels). An average of 2.75% was found to be novel variants according to dbSNP (build 151). This is the first report of structural variants (SV) from WGS data from UAE nationals. There were 15,677-20,339 called SVs, of which around 13.5% were novel. The four samples shared 1,399,178 variants, each with distinct variants as follows: 1,085,524 (for the individual denoted as UAE S011), 1,228,559 (UAE S012), 791,072 (UAE S013), and 906,818 (UAE S014). These results show a previously unappreciated population diversity in the region. The synergy of WGS and genotype array data was demonstrated through variant annotation of the former using 2.3 million allele frequencies for the local population derived from the latter technology platform. This novel approach of combining breadth and depth of array and WGS technologies has guided the choice of population genetic representatives and provides complementary, regionalized allele frequency annotation to new genomes comprising millions of loci.

Population Structure, Stratification, and Introgression of Human Structural Variation

Structural variants contribute substantially to genetic diversity and are important evolutionarily and medically, but they are still understudied. Here we present a comprehensive analysis of structural variation in the Human Genome Diversity panel, a high-coverage dataset of 911 samples from 54 diverse worldwide populations. We identify, in total, 126,018 variants, 78% of which were not identified in previous global sequencing projects. Some reach high frequency and are private to continental groups or even individual populations, including regionally restricted runaway duplications and putatively introgressed variants from archaic hominins. By de novo assembly of 25 genomes using linked-read sequencing, we discover 1,643 breakpoint-resolved unique insertions, in aggregate accounting for 1.9 Mb of sequence absent from the GRCh38 reference. Our results illustrate the limitation of a single human reference and the need for high-quality genomes from diverse populations to fully discover and understand human genetic variation.

Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial

BACKGROUND

The influence of genetic risk for obesity on food choice behaviors is unknown and may be in the causal pathway between genetic risk and weight gain. The aim of this study was to examine associations between genetic risk for obesity and food choice behaviors using objectively assessed workplace food purchases.

METHODS AND FINDINGS

This study is a secondary analysis of baseline data collected prior to the start of the "ChooseWell 365" health-promotion intervention randomized control trial. Participants were employees of a large hospital in Boston, MA, who enrolled in the study between September 2016 and February 2018. Cafeteria sales data, collected retrospectively for 3 months prior to enrollment, were used to track the quantity (number of items per 3 months) and timing (median time of day) of purchases, and participant surveys provided self-reported behaviors, including skipping meals and preparing meals at home. A previously validated Healthy Purchasing Score was calculated using the cafeteria traffic-light labeling system (i.e., green = healthy, yellow = less healthy, red = unhealthy) to estimate the healthfulness (quality) of employees' purchases (range, 0%-100% healthy). DNA was extracted and genotyped from blood samples. A body mass index (BMI) genome-wide polygenic score (BMIGPS) was generated by summing BMI-increasing risk alleles across the genome. Additionally, 3 polygenic risk scores (PRSs) were generated with 97 BMI variants previously identified at the genome-wide significance level (P < 5 × 10-8): (1) BMI97 (97 loci), (2) BMICNS (54 loci near genes related to central nervous system [CNS]), and (3) BMInon-CNS (43 loci not related to CNS). Multivariable linear and logistic regression tested associations of genetic risk score quartiles with workplace purchases, adjusted for age, sex, seasonality, and population structure. Associations were considered significant at P < 0.05. In 397 participants, mean age was 44.9 years, and 80.9% were female. Higher genetic risk scores were associated with higher BMI. The highest quartile of BMIGPS was associated with lower Healthy Purchasing Score (-4.8 percentage points [95% CI -8.6 to -1.0]; P = 0.02), higher quantity of food purchases (14.4 more items [95% CI -0.1 to 29.0]; P = 0.03), later time of breakfast purchases (15.0 minutes later [95% CI 1.5-28.5]; P = 0.03), and lower likelihood of preparing dinner at home (Q4 odds ratio [OR] = 0.3 [95% CI 0.1-0.9]; P = 0.03) relative to the lowest BMIGPS quartile. Compared with the lowest quartile, the highest BMICNS quartile was associated with fewer items purchased (P = 0.04), and the highest BMInon-CNS quartile was associated with purchasing breakfast at a later time (P = 0.01), skipping breakfast (P = 0.03), and not preparing breakfast (P = 0.04) or lunch (P = 0.01) at home. A limitation of this study is our data come from a relatively small sample of healthy working adults of European ancestry who volunteered to enroll in a health-promotion study, which may limit generalizability.

CONCLUSIONS

In this study, genetic risk for obesity was associated with the quality, quantity, and timing of objectively measured workplace food purchases. These findings suggest that genetic risk for obesity may influence eating behaviors that contribute to weight and could be targeted in personalized workplace wellness programs in the future.

TRIAL REGISTRATION

Clinicaltrials.gov NCT02660086.

The Cystic Fibrosis Transmembrane Conductance Regulator 470 Met Allele Is Associated with an Increased Risk of Chronic Pancreatitis in Both Asian and Caucasian Populations: A Meta-Analysis

Background: The Met470Val polymorphism (1540A>G [rs213950]) within the cystic fibrosis transmembrane conductance regulator (CFTR) protein has been reported to be associated with chronic pancreatitis (CP). The results remain inconclusive, and therefore, we performed this meta-analysis to clarify the association between M470V and CP risk. Methodology/Results: We conducted a meta-analysis of 7 case-control studies, including a total of 1121 CP patients and 2209 controls from Asian and Caucasian populations. We calculated the odds ratio (OR) and 95% confidence intervals (95% CI). Met470Val was found to be significantly associated with an increased risk of CP under all the genetic models (M vs. V, OR = 1.260, 95% CI: 1.134-1.399; MV vs. VV, OR = 1.292, 95% CI: 1.091-1.530; MM vs. VV, OR = 1.579, 95% CI: 1.274-1.956; MV/MV vs. VV, OR = 1.366, 95% CI: 1.165-1.603; MM vs. MV/VV, OR = 1.346, 95% CI: 1.114-1.621). Met470Val was also found to be significantly associated with an increased risk of idiopathic CP (ICP) in allele contrast, codominant, and recessive models (M vs. V, OR = 1.298, 95% CI: 1.020-1.653; MV vs. VV, OR = 1.297, 95% CI: 1.074-1.566; MM vs. VV, OR = 1.473, 95% CI: 1.165-1.862; MM vs. MV/VV, OR = 1.254, 95% CI: 1.023-1.538). Conclusions: The CFTR 470 M allele is significantly associated with an increased risk of CP in both Asian and Caucasian populations. The CFTR 470 M allele is also significantly associated with risk of ICP.

TeraPCA: a fast and scalable software package to study genetic variation in tera-scale genotypes

MOTIVATION

Principal Component Analysis is a key tool in the study of population structure in human genetics. As modern datasets become increasingly larger in size, traditional approaches based on loading the entire dataset in the system memory (Random Access Memory) become impractical and out-of-core implementations are the only viable alternative.

RESULTS

We present TeraPCA, a C++ implementation of the Randomized Subspace Iteration method to perform Principal Component Analysis of large-scale datasets. TeraPCA can be applied both in-core and out-of-core and is able to successfully operate even on commodity hardware with a system memory of just a few gigabytes. Moreover, TeraPCA has minimal dependencies on external libraries and only requires a working installation of the BLAS and LAPACK libraries. When applied to a dataset containing a million individuals genotyped on a million markers, TeraPCA requires <5 h (in multi-threaded mode) to accurately compute the 10 leading principal components. An extensive experimental analysis shows that TeraPCA is both fast and accurate and is competitive with current state-of-the-art software for the same task.

AVAILABILITY AND IMPLEMENTATION

Source code and documentation are both available at https://github.com/aritra90/TeraPCA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evaluation of model fit of inferred admixture proportions

Model based methods for genetic clustering of individuals, such as those implemented in structure or ADMIXTURE, allow the user to infer individual ancestries and study population structure. The underlying model makes several assumptions about the demographic history that shaped the analysed genetic data. One assumption is that all individuals are a result of K homogeneous ancestral populations that are all well represented in the data, while another assumption is that no drift happened after the admixture event. The histories of many real world populations do not conform to that model, and in that case taking the inferred admixture proportions at face value might be misleading. We propose a method to evaluate the fit of admixture models based on estimating the correlation of the residual difference between the true genotypes and the genotypes predicted by the model. When the model assumptions are not violated, the residuals from a pair of individuals are not correlated. In the case of a bad fitting admixture model, individuals with similar demographic histories have a positive correlation of their residuals. Using simulated and real data, we show how the method is able to detect a bad fit of inferred admixture proportions due to using an insufficient number of clusters K or to demographic histories that deviate significantly from the admixture model assumptions, such as admixture from ghost populations, drift after admixture events and nondiscrete ancestral populations. We have implemented the method as an open source software that can be applied to both unphased genotypes and low depth sequencing data.

Skin pigmentation and genetic variants in an admixed Brazilian population of primarily European ancestry

Although many genes have been shown to be associated with human pigmentary traits and forensic prediction assays exist (e.g. HIrisPlex-S), the genetic knowledge about skin colour remains incomplete. The highly admixed Brazilian population is an interesting study population for investigation of the complex genotype-phenotype architecture of human skin colour because of its large variation. Here, we compared variants in 22 pigmentary genes with quantitative skin pigmentation levels on the buttock, arm, and forehead areas of 266 genetically admixed Brazilian individuals. The genetic ancestry of each individual was estimated by typing 46 AIM-InDels. The mean proportion of genetic ancestry was 68.8% European, 20.8% Sub-Saharan African, and 10.4% Native American. A high correlation (adjusted R² = 0.65, p < 0.05) was observed between nine SNPs and quantitative skin pigmentation using multiple linear regression analysis. The correlations were notably smaller between skin pigmentation and biogeographic ancestry (adjusted R² = 0.45, p < 0.05), or markers in the leading forensic skin colour prediction system, the HIrisPlex-S (adjusted R² = 0.54, p < 0.05). Four of the nine SNPs, OCA2 rs1448484 (rank 2), APBA2 rs4424881 (rank 4), MFSD12 rs10424065 (rank 8), and TYRP1 1408799 (rank 9) were not investigated as part of the HIrisPlex-S selection process, and therefore not included in the HIrisPlex-S model. Our results indicate that these SNPs account for a substantial part of the skin colour variation in individuals of admixed ancestry. Hence, we suggest that these SNPs are considered when developing future skin colour prediction models.

Association of NOD2 and IFNG single nucleotide polymorphisms with leprosy in the Amazon ethnic admixed population

Leprosy is a chronic infectious disease, caused by Mycobacterium leprae, which affects skin and peripheral nerves. Polymorphisms in genes associated with autophagy, metabolism, innate and adaptive immunity confer susceptibility to leprosy. However, these associations need to be confirmed through independent replication studies in different ethnicities. The population from Amazon state (northern Brazil) is admixed and it contains the highest proportion of Native American genetic ancestry in Brazil. We conducted a case-control study for leprosy in which we tested fourteen previously associated SNPs in key immune response regulating genes: TLR1 (rs4833095), NOD2 (rs751271, rs8057341), TNF (rs1800629), IL10 (rs1800871), CCDC122/LACC1 (rs4942254), PACRG/PRKN (rs9356058, rs1040079), IFNG (rs2430561), IL6 (rs2069845), LRRK2 (rs7298930, rs3761863), IL23R (rs76418789) and TYK2 (rs55882956). Genotyping was carried out by allelic discrimination in 967 controls and 412 leprosy patients. Association with susceptibility was assessed by logistic regression analyses adjusted for the following covariates: gender, age and ancestry. Genetic ancestry was similar in case and control groups. Statistically significant results were only found for IFNG and NOD2. The rs8057341 polymorphism within NOD2 was identified as significant for the AA genotype (OR = 0.56; 95% CI, 0.37-0.84; P = 0.005) and borderline for the A allele (OR = 0.76; 95% CI, 0.58-1.00; P = 0.053) and carrier (OR = 0.76; 95% CI, 0.58-1.00; P = 0.051). The rs2430561 SNP in IFNG was associated with disease susceptibility for the AT genotype (OR = 1.40; 95% CI, 1.06-1.85; P = 0.018) and carrier (OR = 1.44; 95% CI, 1.10-1.88; P = 0.008). We confirmed that NOD2 and IFNG are major players in immunity against M.leprae in the Amazon ethnic admixed population.

Studying human and nonhuman primate evolutionary biology with powerful in vitro and in vivo functional genomics tools

In recent years, tools for functional genomic studies have become increasingly feasible for use by evolutionary anthropologists. In this review, we provide brief overviews of several exciting in vitro techniques that can be paired with "-omics" approaches (e.g., genomics, epigenomics, transcriptomics, proteomics, and metabolomics) for potentially powerful evolutionary insights. These in vitro techniques include ancestral protein resurrection, cell line experiments using primary, immortalized, and induced pluripotent stem cells, and CRISPR-Cas9 genetic manipulation. We also discuss how several of these methods can be used in vivo, for transgenic organism studies of human and nonhuman primate evolution. Throughout this review, we highlight example studies in which these approaches have already been used to inform our understanding of the evolutionary biology of modern and archaic humans and other primates while simultaneously identifying future opportunities for anthropologists to use this toolkit to help answer additional outstanding questions in evolutionary anthropology.

Germline APOBEC3B deletion influences clinicopathological parameters in luminal-A breast cancer: evidences from a southern Brazilian cohort

PURPOSE

APOBEC3A and APOBEC3B cytidine deaminases have been implicated in the pathogenesis of multiple cancers, including breast cancer (BC). A germline deletion linking APOBEC3A and APOBEC3B loci (A3A/B) has been associated with higher APOBEC-mediated mutational burden, but its association with BC risk have been controversial. Therefore, this study investigated the association between A3A/B and BC susceptibility and clinical presentation in a Brazilian cohort.

METHODS

A3A/B deletion was evaluated through allele-specific PCR in 341 BC patients and 397 women without familial or personal history of neoplasia from Brazil and associations with susceptibility to BC subtypes were tested through age-adjusted logistic models while correlations with clinicopathological parameters were tested using Kendall's tests.

RESULTS

No association was found between A3A/B and BC susceptibility; however, in Luminal-A BCs, it was positively correlated with tumor size (Tau-c = 0.125) and Ki67 (Tau-c = 0.116) and negatively correlated with lymph node metastasis (LNM) (Tau-c = - 0.162). The negative association between A3A/B with LNM in Luminal-A BCs remained significant even after adjusting for tumor size and Ki67 in logistic models (OR = 0.22; p = 0.008).

CONCLUSION

These results show that although A3A/B may not modify BC susceptibility in Brazilian population, it may affect clinicopathological features in BC subtypes, promoting tumor cell proliferation while being negatively associated with LNM in Luminal-A BCs.