Large Allele Frequency Differences Research Articles

Allele frequency impacts the cross-ancestry portability of gene expression prediction in lymphoblastoid cell lines.

Population-level genetic studies are overwhelmingly biased toward European ancestries. Transferring genetic predictions from European ancestries to other ancestries results in a substantial loss of accuracy. Yet, it remains unclear how much various genetic factors, such as causal effect differences, linkage disequilibrium (LD) differences, or allele frequency differences, contribute to the loss of prediction accuracy across ancestries. In this study, we used gene expression levels in lymphoblastoid cell lines to understand how much each genetic factor contributes to lowered portability of gene expression prediction from European to African ancestries. We found that cis-genetic effects on gene expression are highly similar between European and African individuals. However, we found that allele frequency differences of causal variants have a striking impact on prediction portability. For example, portability is reduced by more than 32% when the causal cis-variant is common (minor allele frequency, MAF >5%) in European samples (training population) but is rarer (MAF <5%) in African samples (prediction population). While large allele frequency differences can decrease portability through increasing LD differences, we also determined that causal allele frequency can significantly impact portability when the impact from LD is substantially controlled. This observation suggests that improving statistical fine-mapping alone does not overcome the loss of portability resulting from differences in causal allele frequency. We conclude that causal cis-eQTL effects are highly similar in European and African individuals, and allele frequency differences have a large impact on the accuracy of gene expression prediction.

Pitfalls and challenges with population assignments of individuals from admixed populations: Applying Genogeographer on Brazilian individuals

The assignment of individuals to a population can be of importance for the identification of mass disaster victims or criminal offenders in the field of forensic genetics. This assignment is based on biostatistical methods that process data of ancestry informative markers (AIMs), which are selected based on large allele frequency differences between the populations of interest.However, population assignments of individuals with an admixed genetic background are challenging. Admixed individuals are genetic mosaics of chromosomal segments from the parental populations, which may lead to ambiguous or no population assignment. This is problematic since admixture events are a substantial part of human history.In this study, we present challenges of interpreting the evidential weight of population assignments. We used Genogeographer for likelihood ratio (LR) calculations and Brazilians as examples of admixed individuals. Brazilians are a very heterogenous population representing a three-way admixture between Native Americans, Europeans, and Africans. Ancestry informative markers were typed in a total of 589 individuals from Brazil using the Precision ID Ancestry Panel. The Brazilians were assigned to six metapopulations (East Asia, Europe, Middle East, North Africa, South-Central Asia, Sub-Saharan Africa) defined in the Genogeographer software and LRs were calculated if the AIM profile was not an outlier in all metapopulations and simulated two-way (1:1) admixtures of the six metapopulations.Population assignments failed for 55% of the samples. These samples had significantly higher genetic contributions from East Asia, South-Central Asia and Sub-Saharan Africa, and significantly lower genetic contributions from Europe. Most of the individuals with population assignments were assigned to the metapopulations of Middle East (58%) or North Africa (36%), followed by Europe (4%), South-Central Asia (1%), and Sub-Saharan Africa (1%). For 8% of the samples, population assignments were only possible when assignments to simulated two-way (1:1) admixtures of the six metapopulations were considered. Most of these individuals were assigned to two-way admixtures of North Africa, South-Central Asia, or Sub-Saharan Africa.Relatively low median likelihood ratios (LRs<1000) were observed when comparing population likelihoods for Europe, Middle East, North Africa, South-Central Asia, or simulated 1:1 admixtures of these metapopulations. Comparisons including East Asian or Sub-Saharan African populations resulted in larger median LRs (LR>1010).The results suggested that the Precision ID Ancestry Panel provided too little information and that additional markers specifically selected for sub-continental differentiation may be required for accurate population assignment of admixed individuals. Furthermore, a Genogeographer database with additional populations including admixed populations would be advantageous for interpretation of admixed AIM profiles. It would likely increase the number of population assignments and illustrate alternatives to the most likely population, which would be valuable information for the case officer when writing the case report.

Race, Ethnicity, and Pharmacogenomic Variation in the United States and the United Kingdom.

The relevance of race and ethnicity to genetics and medicine has long been a matter of debate. An emerging consensus holds that race and ethnicity are social constructs and thus poor proxies for genetic diversity. The goal of this study was to evaluate the relationship between race, ethnicity, and clinically relevant pharmacogenomic variation in cosmopolitan populations. We studied racially and ethnically diverse cohorts of 65,120 participants from the United States All of Us Research Program (All of Us) and 31,396 participants from the United Kingdom Biobank (UKB). Genome-wide patterns of pharmacogenomic variation-6311 drug response-associated variants for All of Us and 5966 variants for UKB-were analyzed with machine learning classifiers to predict participants' self-identified race and ethnicity. Pharmacogenomic variation predicts race/ethnicity with averages of 92.1% accuracy for All of Us and 94.3% accuracy for UKB. Group-specific prediction accuracies range from 99.0% for the White group in UKB to 92.9% for the Hispanic group in All of Us. Prediction accuracies are substantially lower for individuals who identified with more than one group in All of Us (16.7%) or as Mixed in UKB (70.7%). There are numerous individual pharmacogenomic variants with large allele frequency differences between race/ethnicity groups in both cohorts. Frequency differences for toxicity-associated variants predict hundreds of adverse drug reactions per 1000 treated participants for minority groups in All of Us. Our results indicate that race and ethnicity can be used to stratify pharmacogenomic risk in the US and UK populations and should not be discounted when making treatment decisions. We resolve the contradiction between the results reported here and the orthodoxy of race and ethnicity as non-genetic, social constructs by emphasizing the distinction between global and local patterns of human genetic diversity, and we stress the current and future limitations of race and ethnicity as proxies for pharmacogenomic variation.

Genomic divergence of hatchery- and natural-origin Chinook salmon (Oncorhynchus tshawytscha) in two supplemented populations

Captive propagation is widely used for the conservation of imperiled populations. There have been concerns about the genetic effects of such propagation, but few studies have measured this directly at a genomic level. Here, we use moderate-coverage (10X) genome sequences from 80 individuals to evaluate the genomic distribution of variation of several paired groups of Chinook salmon (Oncorhynchus tshawytscha). These include (1) captive- and natural-origin fish separated by at least one generation, (2) fish within the same generation having high fitness in captivity compared to those with high fitness in the wild, and (3) fish listed as different Evolutionarily Significant Units (ESUs) under the US Endangered Species Act. The distribution of variation between high-fitness captive and high-fitness natural fish was nearly identical to that expected from random sampling, indicating that differential selection in the two environments did not create large allele frequency differences within a single generation. In contrast, the samples from distinct ESUs were clearly more divergent than expected by chance, including a peak of divergence near the GREB1L gene on chromosome 28, a gene previously associated with variation in time of return to fresh water. Comparison of hatchery- and natural-origin fish within a population fell between these extremes, but the maximum value of FST was similar to the maximum between ESUs, including a peak of divergence on chromosome 8 near the slc7a2 and pdgfrl genes. These results suggest that efforts at limiting genetic divergence between captive and natural fish in these populations have successfully kept the average divergence low across the genome, but at a small portion of their genomes, hatchery and natural salmon were as distinct as individuals from different ESUs.

Abstract PO-143: Differences in vitamin D genomic and epigenomic responses in colonic organoids from African- and European-Americans

Abstract Background: African Americans have the highest burden of colorectal cancer (CRC) in the US. Active 1,25(OH)2vitamin D (1,25vitD) protects from CRC, though the role of population differences in 1,25vitD responses to CRC disparities is unknown. To study inter-ethnic host-environment interactions in the colon, we have established human-derived colonic organoids from diverse populations. We used this approach to study differences in transcriptional and chromatin accessibility responses to 1,25vitD between Americans of African (AA) and European (EA) ancestry. Methods: Colonic organoids from 60 subjects (30 AA and 30 EA) were established. After passaging, organoids were differentiated for 24h and then treated with 100nM 1,25vitD or ethanol (vehicle control). Chromatin accessibility and gene expression were assessed at 4 and 6 hours by RNA-seq and ATAC-seq, respectively. Inter-ethnic responses were assessed using dream (Hoffman et al, 2020). Genotyping was performed using the Infinium OmniExpress-24, and ancestry was estimated using imputed genotypes. Expression quantitative trait loci (eQTL) mapping was performed using BRIdGE (Maranville et al, 2011). Results: Organoid lines from 54 subjects (28 AA and 26 EA) were included after removing 5 with inconsistent ancestry. For overall 1,25vitD response, 7816 differentially expressed protein-coding genes at a false discovery rate (FDR)&amp;lt;5% were found. Gene set enrichment included the KEGG pathway “colorectal cancer” (FDR&amp;lt;5%) with differentially responsive genes such as APC and MYC. eQTL mapping showed 131 1,25vitD-only and 21 control-only significant variants (FDR&amp;lt;5%). For inter-ethnic 1,25vitD responses, top genes included MORC3, MAP4K3, AMACR, KYNU, PIK3CA and POLB. Results for POLB, a base-excision repair polymerase, were particularly interesting given significant inter-ethnic differences in genomic and epigenomic responses to 1,25vitD likely due to a genetic mechanism. Specifically, organoids from AA showed significantly higher POLB expression with 1,25vitD. In the region, a POLB eQTL, rs2272733, showed large allele frequency differences for the ancestral T allele (80% in Africa; 14% in Europe). This eQTL is located in a POLB enhancer region, and there is a vitamin D-responsive ATAC peak ~10kb 5' to this SNP that is only present in T/T genotypes. Conclusion: Application of organoids from diverse populations enables genome-wide assessment of population differences in host-environment interactions related to CRC. In this study, overall 1,25vitD responses were robust and found pathways relevant to CRC. eQTL mapping further established a genetic basis for 1,25vitD colonic responses. We found a number of genes that showed differences in 1,25vitD transcriptional response between AA and EA with a particularly promising CRC-relevant candidate gene, POLB. These results provide new insights into differences in host-environment interactions between populations that could underlie cancer disparities. Citation Format: Sonia Kupfer, David Witonsky, Jinchao Li, Margaret Bielski, Kristi Lawrence. Differences in vitamin D genomic and epigenomic responses in colonic organoids from African- and European-Americans [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-143.

Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity while contributing to health and disease.

Large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans, and many of these regulatory variants have large allele frequency differences between populations. Here, we conducted genome-wide scans of selection to identify adaptive eQTLs (i.e., eQTLs with large population branch statistics). We then tested if tissue pleiotropy affects whether eQTLs are more or less likely to be adaptive and identified tissues that have been key targets of positive selection during the last 100,000 years. Top adaptive eQTL outliers include rs1043809, rs66899053, and rs2814778 (a SNP that is associated with malaria resistance). We found that effect sizes of eQTLs were negatively correlated with population branch statistics and that adaptive eQTLs affect two-thirds as many tissues as do non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results imply that pleiotropy inhibits adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we found that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for signatures of positive selection. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. Scans of selections also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that eQTLs have played an important role in recent human evolution.

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.

G6PD distribution in sub-Saharan Africa and potential risks of using chloroquine/hydroxychloroquine based treatments for COVID-19

Chloroquine/hydroxychloroquine have been proposed as potential treatments for COVID-19. These drugs have warning labels for use in individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency. Analysis of whole genome sequence data of 458 individuals from sub-Saharan Africa showed significant G6PD variation across the continent. We identified nine variants, of which four are potentially deleterious to G6PD function, and one (rs1050828) that is known to cause G6PD deficiency. We supplemented data for the rs1050828 variant with genotype array data from over 11,000 Africans. Although this variant is common in Africans overall, large allele frequency differences exist between sub-populations. African sub-populations in the same country can show significant differences in allele frequency (e.g. 16.0% in Tsonga vs 0.8% in Xhosa, both in South Africa, p = 2.4 × 10−3). The high prevalence of variants in the G6PD gene found in this analysis suggests that it may be a significant interaction factor in clinical trials of chloroquine and hydroxychloroquine for treatment of COVID-19 in Africans.

Genetic architecture of the metabolic pathway of salicylic acid biosynthesis in Populus

Salicylic acid (SA) is a vital hormone for adaptive responses to biotic and abiotic stresses, which facilitates growth-immunity trade-offs in plants. However, the genetic regulatory networks underlying the metabolic pathway of SA biosynthesis in perennial species remain unclear. Here, we integrated genome-wide association study (GWAS) with metabolite and expression profiling methodologies to dissect the genetic architecture of SA biosynthesis in Populus. First, we quantified nine intermediate metabolites of SA biosynthesis in 300 unrelated Populus tomentosa Carr. individuals. Then, we used a systematic genetic strategy to identify candidate genes for constructing the genetic regulatory network of SA biosynthesis. We focused on WRKY70, an efficient transcription factor, as the key causal gene in the regulatory network, and combined the novel genes coordinating the accumulation of SA. Finally, we identified eight GWAS signals and eight expression quantitative trait loci situated in a selective sweep, and showed the presence of large allele frequency differences among the three geographic populations, revealing that candidate genes subject to selection were involved in SA biosynthesis. This study provides an integrated strategy for dissecting the genetic architecture of the metabolic pathway of SA biosynthesis in Populus, thereby enhancing our understanding of genetic regulation of SA biosynthesis in trees, and accelerating marker-assisted breeding efforts toward high-resistance elite varieties of Populus.

Opportunities and challenges in assessing climate change vulnerability through genomics

By investigating how past selection has affected allele frequencies across space, genomic tools are providing new insights into adaptive evolutionary processes. Now researchers are considering how this genomic information can be used to predict the future vulnerability of species under climate change. Genomic vulnerability assessments show promise, but challenges remain.

A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa.

Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. Samples from Ghana and Nigeria clustered together, whereas samples from Senegal and South Africa yielded distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores for prostate cancer were higher in Nigeria than in Senegal. In summary, individual and population-level differences in prostate cancer risk were revealed using a novel genotyping array. SIGNIFICANCE: This study presents an Africa-specific genotyping array, which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers.

Admixture mapping identifies genetic regions associated with blood pressure phenotypes in African Americans.

Hypertension occurs at a higher rate in African Americans than in European Americans. Based on the assumption that causal variants are more frequently found on DNA segments inherited from the ancestral population with higher disease risk, we employed admixture mapping to identify genetic loci with excess local African ancestry associated with blood pressure. Chromosomal regions 1q21.2-21.3, 4p15.1, 19q12 and 20p13 were significantly associated with diastolic blood pressure (β = 5.28, -7.94, -6.82 and 5.89, P-value = 6.39E-04, 2.07E-04, 6.56E-05 and 5.04E-04, respectively); 1q21.2-21.3 and 19q12 were also significantly associated with mean arterial pressure (β = 5.86 and -6.40, P-value = 5.32E-04 and 6.37E-04, respectively). We further selected SNPs that had large allele frequency differences within these regions and tested their association with blood pressure. SNP rs4815428 was significantly associated with diastolic blood pressure after Bonferroni correction (β = -2.42, P-value = 9.57E-04), and it partially explained the admixture mapping signal at 20p13. SNPs rs771205 (β = -1.99, P-value = 3.37E-03), rs3126067, rs2184953 and rs58001094 (the latter three exhibit strong linkage disequilibrium, β = -2.3, P-value = 1.4E-03) were identified to be significantly associated with mean arterial pressure, and together they fully explained the admixture signal at 1q21.2-21.3. Although no SNP at 4p15.1 showed large ancestral allele frequency differences in our dataset, we detected association at low-frequency African-specific variants that mapped predominantly to the gene PCDH7, which is most highly expressed in aorta. Our results suggest that these regions may harbor genetic variants that contribute to the different prevalence of hypertension.

Ancestry informative markers (AIMs) for Korean and other East Asian and South East Asian populations.

Inference of ancestry from biological evidence can provide investigative information, especially for unknown DNA donors. Although tools for predicting ancestry have been developing, ancestry research focusing on populations relevant for South Korea is not common and markers are seldom chosen specifically to differentiate Koreans from other East Asian and South East Asian populations. Here, we report ancestry informative markers (AIMs) for distinguishing six East/South East Asian regional populations: China, Japan, Indonesia, Philippines, South Korea and Thailand. Individual genotypes from these six populations were available in PanSNPdb: The HUGO Pan-Asian SNP Database. To select AIMs, we calculated four population divergence metrics for each SNP: Nei's FST, Rosenberg's Informativeness (In), the average absolute allele frequency difference between populations (δFmean) and the maximum allele frequency difference between populations (δFmax). Based on these values, we selected 100 single nucleotide polymorphisms (SNPs) for distinguishing the six populations, 13 of which exhibited large allele frequency differences between Koreans and non-Koreans. To assess the performance of the AIMs, we performed principal coordinates analysis (PCoA) on the individuals from all six populations and inferred ancestral population clusters using the STRUCTURE program. In conclusion, we found that the selected AIMs can be applied to distinguish the six East/South East Asian groups and we suggest the markers in this study will be helpful to establish ancestry panels for Korea and neighbouring populations.

Optimal selection of genetic variants for adjustment of population stratification in European association studies.

Population stratification is usually corrected relying on principal component analysis (PCA) of genome-wide genotype data, even in populations considered genetically homogeneous, such as Europeans. The need to genotype only a small number of genetic variants that show large differences in allele frequency among subpopulations-so-called ancestry-informative markers (AIMs)-instead of the whole genome for stratification adjustment could represent an advantage for replication studies and candidate gene/pathway studies. Here we compare the correction performance of classical and robust principal components (PCs) with the use of AIMs selected according to four different methods: the informativeness for assignment measure ($IN$-AIMs), the combination of PCA and F-statistics, PCA-correlated measurement and the PCA weighted loadings for each genetic variant. We used real genotype data from the Population Reference Sample and The Cancer Genome Atlas to simulate European genetic association studies and to quantify type I error rate and statistical power in different case-control settings. In studies with the same numbers of cases and controls per country and control-to-case ratios reflecting actual rates of disease prevalence, no adjustment for population stratification was required. The unnecessary inclusion of the country of origin, PCs or AIMs as covariates in the regression models translated into increasing type I error rates. In studies with cases and controls from separate countries, no investigated method was able to adequately correct for population stratification. The first classical and the first two robust PCs achieved the lowest (although inflated) type I error, followed at some distance by the first eight $IN$-AIMs.

PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects.

Over the last decade, more diverse populations have been included in genome-wide association studies. If a genetic variant has a varying effect on a phenotype in different populations, genome-wide association studies applied to a dataset as a whole may not pinpoint such differences. It is especially important to be able to identify population-specific effects of genetic variants in studies that would eventually lead to development of diagnostic tests or drug discovery. In this paper, we propose PopCluster: an algorithm to automatically discover subsets of individuals in which the genetic effects of a variant are statistically different. PopCluster provides a simple framework to directly analyze genotype data without prior knowledge of subjects' ethnicities. PopCluster combines logistic regression modeling, principal component analysis, hierarchical clustering and a recursive bottom-up tree parsing procedure. The evaluation of PopCluster suggests that the algorithm has a stable low false positive rate (∼4%) and high true positive rate (>80%) in simulations with large differences in allele frequencies between cases and controls. Application of PopCluster to data from genetic studies of longevity discovers ethnicity-dependent heterogeneity in the association of rs3764814 (USP42) with the phenotype. PopCluster was implemented using the R programming language, PLINK and Eigensoft software, and can be found at the following GitHub repository: https://github.com/gurinovich/PopCluster with instructions on its installation and usage. Supplementary data are available at Bioinformatics online.

Ultraconserved elements (UCEs) illuminate the population genomics of a recent, high-latitude avian speciation event.

Using a large, consistent set of loci shared by descent (orthologous) to study relationships among taxa would revolutionize among-lineage comparisons of divergence and speciation processes. Ultraconserved elements (UCEs), highly conserved regions of the genome, offer such genomic markers. The utility of UCEs for deep phylogenetics is clearly established and there are mature analytical frameworks available, but fewer studies apply UCEs to recent evolutionary events, creating a need for additional example datasets and analytical approaches. We used UCEs to study population genomics in snow and McKay’s buntings (Plectrophenax nivalis and P. hyperboreus). Prior work suggested divergence of these sister species during the last glacial maximum (∼18–74 Kya). With a sequencing depth of ∼30× from four individuals of each species, we used a series of analysis tools to genotype both alleles, obtaining a complete dataset of 2,635 variable loci (∼3.6 single nucleotide polymorphisms/locus) and 796 invariable loci. We found no fixed allelic differences between the lineages, and few loci had large allele frequency differences. Nevertheless, individuals were 100% diagnosable to species, and the two taxa were different genetically (FST = 0.034; P = 0.03). The demographic model best fitting the data was one of divergence with gene flow. Estimates of demographic parameters differed from published mtDNA research, with UCE data suggesting lower effective population sizes (∼92,500–240,500 individuals), a deeper divergence time (∼241,000 years), and lower gene flow (2.8–5.2 individuals per generation). Our methods provide a framework for future population studies using UCEs, and our results provide additional evidence that UCEs are useful for answering questions at shallow evolutionary depths.

Genetic Hitchhiking and Population Bottlenecks Contribute to Prostate Cancer Disparities in Men of African Descent.

Prostate cancer incidence and mortality rates in African and African American men are greatly elevated compared with other ethnicities. This disparity is likely explained by a combination of social, environmental, and genetic factors. A large number of susceptibility loci have been reported by genome-wide association studies (GWAS), but the contribution of these loci to prostate cancer disparities is unclear. Here, we investigated the population structure of 68 previously reported GWAS loci and calculated genetic disparity contribution statistics to identify SNPs that contribute the most to differences in prostate cancer risk across populations. By integrating GWAS results with allele frequency data, we generated genetic risk scores for 45 African and 19 non-African populations. Tests of natural selection were used to assess why some SNPs have large allele frequency differences across populations. We report that genetic predictions of prostate cancer risks are highest for West African men and lowest for East Asian men. These differences may be explained by the out-of-Africa bottleneck and natural selection. A small number of loci appear to drive elevated prostate cancer risks in men of African descent, including rs9623117, rs6983267, rs10896449, rs10993994, and rs817826. Although most prostate cancer-associated loci are evolving neutrally, there are multiple instances where alleles have hitchhiked to high frequencies with linked adaptive alleles. For example, a protective allele at 2q37 appears to have risen to high frequency in Europe due to selection acting on pigmentation. Our results suggest that evolutionary history contributes to the high rates of prostate cancer in African and African American men.Significance: A small number of genetic variants cause an elevated risk of prostate cancer in men of West African descent. Cancer Res; 78(9); 2432-43. ©2018 AACR.

Genetic tests for estimating dairy breed proportion and parentage assignment in East African crossbred cattle

BackgroundSmallholder dairy farming in much of the developing world is based on the use of crossbred cows that combine local adaptation traits of indigenous breeds with high milk yield potential of exotic dairy breeds. Pedigree recording is rare in such systems which means that it is impossible to make informed breeding decisions. High-density single nucleotide polymorphism (SNP) assays allow accurate estimation of breed composition and parentage assignment but are too expensive for routine application. Our aim was to determine the level of accuracy achieved with low-density SNP assays.MethodsWe constructed subsets of 100 to 1500 SNPs from the 735k-SNP Illumina panel by selecting: (a) on high minor allele frequencies (MAF) in a crossbred population; (b) on large differences in allele frequency between ancestral breeds; (c) at random; or (d) with a differential evolution algorithm. These panels were tested on a dataset of 1933 crossbred dairy cattle from Kenya/Uganda and on crossbred populations from Ethiopia (N = 545) and Tanzania (N = 462). Dairy breed proportions were estimated by using the ADMIXTURE program, a regression approach, and SNP-best linear unbiased prediction, and tested against estimates obtained by ADMIXTURE based on the 735k-SNP panel. Performance for parentage assignment was based on opposing homozygotes which were used to calculate the separation value (sv) between true and false assignments.ResultsPanels of SNPs based on the largest differences in allele frequency between European dairy breeds and a combined Nelore/N’Dama population gave the best predictions of dairy breed proportion (r2 = 0.962 to 0.994 for 100 to 1500 SNPs) with an average absolute bias of 0.026. Panels of SNPs based on the highest MAF in the crossbred population (Kenya/Uganda) gave the most accurate parentage assignments (sv = −1 to 15 for 100 to 1500 SNPs).ConclusionsDue to the different required properties of SNPs, panels that did well for breed composition did poorly for parentage assignment and vice versa. A combined panel of 400 SNPs was not able to assign parentages correctly, thus we recommend the use of 200 SNPs either for breed proportion prediction or parentage assignment, independently.

Comparative physiogenomic analyses of weight loss in response to 2 modes of bariatric surgery: demonstration with candidate neuropsychiatric and cardiometabolic genes

BackgroundSurgical weight loss response is variable, with suboptimal outcomes in some patients. We hypothesized that genetic biomarkers may be related to weight change. MethodsWe tested 330 single nucleotide polymorphisms (SNPs) in genes relevant to metabolic regulation in 161 patients whose decrease in body mass index (BMI), 1 year after laparoscopic adjustable gastric banding (LAGB) or Roux-en-Y gastric bypass (RYGB), was small (lowest quartile response) or large (highest quartile response). LAGB patients whose BMI decreased≤4.7 or≥10.2 units comprised groups I (n = 43) and II (n = 40), respectively. RYGB patients whose BMI decreased≤13.6 or≥19.8 units comprised groups III (n = 39) and IV (n = 39), respectively. Within each surgery, SNPs with large differences in reference allele frequency (z score>2, corresponding to values displaced 2 standard deviations [SD] from the mean for all SNPs) in low versus high quartiles, were identified. We compared reference allele frequencies, within surgical procedure, using the χ2 test (using Bonferroni correction for multiple testing). ResultsThe mean percent excess weight losses (±SD) corresponding to groups I, II, III, and IV were: 16 (±12), 64 (±30), 55 (±16), and 75 (±17), respectively. SNPs with z score>2 were identified in genes involved in LAGB response, lipid metabolic regulation (APOE, rs439401; APOC4, rs2288911), neural processes (DRD3, rs167771; HTR3 B, rs3758987), and xeno- or endobiotic metabolism (CYP3 A4, rs12333983); and for RYGB response, in lipid transport (SCARB1, rs10846744), folate metabolism (MTHFR, rs2066470), regulation of glycolysis in immune cells (HIF1 A, rs1951795), vitamin K cycling (VKORC1, rs2359612), and xeno- or endobiotic metabolism (CYP3 A4, rs2242480). For LAGB response, APOE SNP frequencies were significantly different. ConclusionsWith further validation, information derived from patient DNA may be useful to predict surgical weight loss outcomes and guide selection of surgical approach.

RAD mapping reveals an evolving, polymorphic and fuzzy boundary of a plant pseudoautosomal region.

How loss of genetic exchanges (recombination) evolves between sex chromosomes is a long-standing question. Suppressed recombination may evolve when a sexually antagonistic (SA) polymorphism occurs in a partially sex-linked 'pseudoautosomal' region (or 'PAR'), maintaining allele frequency differences between the two sexes, and creating selection for closer linkage with the fully sex-linked region of the Y chromosome in XY systems, or the W in ZW sex chromosome systems. Most evidence consistent with the SA polymorphism hypothesis is currently indirect, and more studies of the genetics and population genetics of PAR genes are clearly needed. The sex chromosomes of the plant Silene latifolia are suitable for such studies, as they evolved recently and the loss of recombination could still be ongoing. Here, we used RAD sequencing to genetically map sequences in this plant, which has a large genome (c. 3 gigabases) and no available whole-genome sequence. We mapped 83 genes on the sex chromosomes, and comparative mapping in the related species S. vulgaris supports previous evidence for additions to an ancestral PAR and identified at least 12 PAR genes. We describe evidence that recombination rates have been reduced in meiosis of both sexes, and differences in recombination between S. latifolia families suggest ongoing recombination suppression. Large allele frequency differences between the sexes were found at several loci closely linked to the PAR boundary, and genes in different regions of the PAR showed striking sequence diversity patterns that help illuminate the evolution of the PAR.