Selection of highly informative SNP markers for population affiliation of major US populations

Unsupervised discovery of ancestry-informative markers and genetic admixture proportions in biobank-scale datasets

Admixture estimation plays a crucial role in ancestry inference and genome-wide association studies (GWASs). Computer programs such as ADMIXTURE and STRUCTURE are commonly employed to estimate the admixture proportions of sample individuals. However, these programs can be overwhelmed by the computational burdens imposed by the 10⁵ to 10⁶ samples and millions of markers commonly found in modern biobanks. An attractive strategy is to run these programs on a set of ancestry-informative SNP markers (AIMs) that exhibit substantially different frequencies across populations. Unfortunately, existing methods for identifying AIMs require knowing ancestry labels for a subset of the sample. This supervised learning approach creates a chicken and the egg scenario. In this paper, we present an unsupervised, scalable framework that seamlessly carries out AIM selection and likelihood-based estimation of admixture proportions. Our simulated and real data examples show that this approach is scalable to modern biobank datasets. OpenADMIXTURE, our Julia implementation of the method, is open source and available for free.

Extensive set of African ancestry-informative markers (AIMs) to study ancestry and population health

Introduction: Human populations are often highly structured due to differences in genetic ancestry among groups, posing difficulties in associating genes with diseases. Ancestry-informative markers (AIMs) aid in the detection of population stratification and provide an alternative approach to map population-specific alleles to disease. Here, we identify and characterize a novel set of African AIMs that separate populations of African ancestry from other global populations including those of European ancestry. Methods: Using data from the 1000 Genomes Project, highly informative SNP markers from five African subpopulations were selected based on estimates of informativeness (In) and compared against the European population to generate a final set of 46,737 African ancestry-informative markers (AIMs). The AIMs identified were validated using an independent set and functionally annotated using tools like SIFT, PolyPhen. They were also investigated for representation of commonly used SNP arrays. Results: This set of African AIMs effectively separates populations of African ancestry from other global populations and further identifies substructure between populations of African ancestry. When a subset of these AIMs was studied in an independent dataset, they differentiated people who self-identify as African American or Black from those who identify their ancestry as primarily European. Most of the AIMs were found to be in their intergenic and intronic regions with only 0.6% in the coding regions of the genome. Most of the commonly used SNP array investigated contained less than 10% of the AIMs. Discussion: While several functional annotations of both coding and non-coding African AIMs are supported by the literature and linked these high-frequency African alleles to diseases in African populations, more effort is needed to map genes to diseases in these genetically diverse subpopulations. The relative dearth of these African AIMs on current genotyping platforms (the array with the highest fraction, llumina's Omni 5, harbors less than a quarter of AIMs), further demonstrates a greater need to better represent historically understudied populations.

An efficient ancestry informative SNPs panel for further discriminating East Asian populations

In forensic genetics, the use of ancestry informative single-nucleotide polymorphisms (AISNPs) panels can narrow the direction of the investigation by estimating an individual's biogeographic ancestry. However, distinguishing subgroups within continental regions requires more specific panels. In this study, we screened 19 AISNPs from the 1000 Genomes Project (1KG) based on their F_ST values to distinguish target populations in East Asia and obtained genotypes through SNaPshot. The 19 AISNPs could divide the global population of the 1KG into five clusters and could further divide the East Asian population into four clusters: Japanese, Han Chinese, Dai Chinese, and Kinh in Ho Chi Minh City of Vietnam. In summary, the 19-AISNP panel may serve as a useful and cost-effective tool for forensic ancestry inference in East Asian populations at a finer scale.

Forensic Feature Exploration and Comprehensive Genetic Insights Into Yugu Ethnic Minority and Northern Han Population via a Novel NGS-Based Marker Set

The MPS technology has expanded the potential applications of DNA markers and increased the discrimination power of the targeted loci by taking variations in their flanking regions into consideration. Here, a collection of nuclear and extranuclear DNA markers (totally six kinds of nuclear genetic markers and mtDNA hypervariable region variations) were comprehensively and systematically assessed for polymorphism detections, further employed to dissect the population backgrounds in the Yugu ethnic group from Gansu province (Yugu) and Han population from the Inner Mongolia Autonomous Region (NMH) of China. The elevated efficiencies of the marker set in separating full sibling and challenging half sibling determination cases in parentage tests (iiSNPs), as well as predicting ancestry origins of unknown individuals from at least four continental populations (aiSNPs) and providing informative characteristic-related clues for Chinese populations (piSNPs) are highlighted in the present study. To sum up, different sets of DNA markers revealed sufficient effciencies to serve as promising tools in forensic applications. Genetic insights from the perspectives of autosomal DNA, Y chromosomal DNA, and mtDNA variations yielded that the Yugu ethnic group was genetically close related to the Han populations of the northern region. But we admit that more reference populations (like Mongolian, Tibetan, Hui, and Tu) should be incorporated to gain a refined genetic background landscape of the Yugu group in future studies.

Comprehensive Insights Into Forensic Features and Genetic Background of Chinese Northwest Hui Group Using Six Distinct Categories of 231 Molecular Markers

The Hui minority is predominantly composed of Chinese-speaking Islamic adherents distributed throughout China, of which the individuals are mainly concentrated in Northwest China. In the present study, we employed the length and sequence polymorphisms-based typing system of 231 molecular markers, i.e., amelogenin, 22 phenotypic-informative single nucleotide polymorphisms (PISNPs), 94 identity-informative single nucleotide polymorphisms (IISNPs), 24 Y-chromosomal short tandem repeats (Y-STRs), 56 ancestry-informative single nucleotide polymorphisms (AISNPs), 7 X-chromosomal short tandem repeats (X-STRs), and 27 autosomal short tandem repeats (A-STRs), into 90 unrelated male individuals from the Chinese Northwest Hui group to comprehensively explore its forensic characteristics and genetic background. Total of 451 length-based and 652 sequence-based distinct alleles were identified from 58 short tandem repeats (STRs) in 90 unrelated Northwest Hui individuals, denoting that the sequence-based genetic markers could pronouncedly provide more genetic information than length-based markers. The forensic characteristics and efficiencies of STRs and IISNPs were estimated, both of which externalized high polymorphisms in the Northwest Hui group and could be further utilized in forensic investigations. No significant departure from the Hardy-Weinberg equilibrium (HWE) expectation was observed after the Bonferroni correction. Additionally, four group sets of reference population data were exploited to dissect the genetic background of the Northwest Hui group separately from different perspectives, which contained 26 populations for 93 IISNPs, 58 populations for 17 Y-STRs, 26 populations for 55 AISNPs (raw data), and 109 populations for 55 AISNPs (allele frequencies). As a result, the analyses based on the Y-STRs indicated that the Northwest Hui group primarily exhibited intimate genetic relationships with reference Hui groups from Chinese different regions except for the Sichuan Hui group and secondarily displayed close genetic relationships with populations from Central and West Asia, as well as several Chinese groups. However, the AISNP analyses demonstrated that the Northwest Hui group shared more intimate relationships with current East Asian populations apart from reference Hui group, harboring the large proportion of ancestral component contributed by East Asia.

Differentiation of Hispanic biogeographic ancestry with 80 ancestry informative markers

Ancestry informative single nucleotide polymorphisms (SNPs) can identify biogeographic ancestry (BGA); however, population substructure and relatively recent admixture can make differentiation difficult in heterogeneous Hispanic populations. Utilizing unrelated individuals from the Genomic Origins and Admixture in Latinos dataset (GOAL, n = 160), we designed an 80 SNP panel (Setser80) that accurately depicts BGA through STRUCTURE and PCA. We compared our Setser80 to the Seldin and Kidd panels via resampling simulations, which models data based on allele frequencies. We incorporated Admixed American 1000 Genomes populations (1000 G, n = 347), into a combined populations dataset to determine robustness. Using multinomial logistic regression (MLR), we compared the 3 panels on the combined dataset and found overall MLR classification accuracies: 93.2% Setser80, 87.9% Seldin panel, 71.4% Kidd panel. Naïve Bayesian classification had similar results on the combined dataset: 91.5% Setser80, 84.7% Seldin panel, 71.1% Kidd panel. Although Peru and Mexico were absent from panel design, we achieved high classification accuracy on the combined populations for Peru (MLR = 100%, naïve Bayes = 98%), and Mexico (MLR = 90%, naïve Bayes = 83.4%) as evidence of the portability of the Setser80. Our results indicate the Setser80 SNP panel can reliably classify BGA for individuals of presumed Hispanic origin.

Ancestry-informative marker (AIM) SNP panel for the Malay population

Ancestry-informative markers (AIMs) can be used to infer the ancestry of an individual to minimize the inaccuracy of self-reported ethnicity in biomedical research. In this study, we describe three methods for selecting AIM SNPs for the Malay population (Malay AIM panel) using different approaches based on pairwise F_ST, informativeness for assignment (I_n), and PCA-correlated SNPs (PCAIMs). These Malay AIM panels were extracted from genotype data stored in SNP arrays hosted by the Malaysian node of the Human Variome Project (MyHVP) and the Singapore Genome Variation Project (SGVP). In particular, genotype data from a total of 165 Malay individuals were analyzed, comprising data on 117 individual genotypes from the Affymetrix SNP-6 SNP array platform and data on 48 individual genotypes from the OMNI 2.5 Illumina SNP array platform. The HapMap phase 3 database (1397 individuals from 11 populations) was used as a reference for comparison with the Malay genotype data. The accuracy of each resulting Malay AIM panel was evaluated using a machine learning "ancestry-predictive model" constructed by using WEKA, a comprehensive machine learning platform written in Java. A total of 1250 SNPs were finally selected, which successfully identified Malay individuals from other world populations with an accuracy of 90%, but the accuracy decreased to 80% using 157 SNPs according to the pairwise F_ST method, while a panel of 200 SNPs selected using I_n and PCAIMs could be used to identify Malay individuals with an accuracy of approximately 80%.

Consequences of PCA graphs, SNP codings, and PCA variants for elucidating population structure

SNP datasets are high-dimensional, often with thousands to millions of SNPs and hundreds to thousands of samples or individuals. Accordingly, PCA graphs are frequently used to provide a low-dimensional visualization in order to display and discover patterns in SNP data from humans, animals, plants, and microbes—especially to elucidate population structure. PCA is not a single method that is always done the same way, but rather requires three choices which we explore as a three-way factorial: two kinds of PCA graphs by three SNP codings by six PCA variants. Our main three recommendations are simple and easily implemented: Use PCA biplots, SNP coding 1 for the rare allele and 0 for the common allele, and double-centered PCA (or AMMI1 if main effects are also of interest). We also document contemporary practices by a literature survey of 125 representative articles that apply PCA to SNP data, find that virtually none implement our recommendations. The ultimate benefit from informed and optimal choices of PCA graph, SNP coding, and PCA variant, is expected to be discovery of more biology, and thereby acceleration of medical, agricultural, and other vital applications.

Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs

Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (r) = 0.94), SCHP (r = 0.94), and EUCP (r = 0.99). Our results provided an example of using a small number of pig AIMs for classifications and estimating ancestry proportions with high accuracy and in a cost-effective manner.

Blood and dietary magnesium levels are not linked with lower prostate cancer risk in black or white men

Recent studies suggest a diet low in dietary magnesium intake or lower blood magnesium levels is linked with increased prostate cancer risk. This study investigates the race-specific link between blood magnesium and calcium levels, or dietary magnesium intake, and the diagnosis of low-grade and high-grade prostate cancer. The study included 637 prostate cancer cases and 715 biopsy-negative controls (50% black) recruited from Nashville, TN or Durham, NC. Blood was collected at the time of recruitment, and dietary intake was assessed by food frequency questionnaire. Percent genetic African ancestry was determined as a compliment to self-reported race. Blood magnesium levels and dietary magnesium intake were significantly lower in black compared to white men. However, magnesium levels or intake were not associated with risk of total prostate cancer or aggressive prostate cancer. Indeed, a higher calcium-to-magnesium diet intake was significantly protective for high-grade prostate cancer in black (OR = 0.66 (0.45, 0.96), p = 0.03) but not white (OR = 1.00 (0.79, 1.26), p = 0.99) men. In summary, there was a statistically significant difference in magnesium intake between black and white men, but the biological impact was unclear, and we did not confirm a lower prostate cancer risk associated with magnesium levels.

Breast Cancer Disparities: How Can We Leverage Genomics to Improve Outcomes?

Breast cancer mortality rates are higher in African American compared with white American women. Disproportionately rising incidence rates, coupled with higher rates of biologically aggressive disease among African Americans is resulting in a widening of the mortality disparity. Higher rates of triple-negative breast cancer among African American women, as well as women from western sub-Saharan Africa, has prompted questions regarding the role of African ancestry as a marker of hereditary susceptibility for specific disease phenotypes. Advances in germline genetics, as well as somatic tumor genomic research, hold great promise in the effort to understand the biology of breast cancer variations between different population subsets.

Microhaplotype identified and performed in genetic investigation using PCR-SSCP

The recently introduced concept of microhaplotype loci has attracted attention in forensics. Previous studies estimated the allele frequencies generally through obtaining genotypic data on the individual SNPs from a larger set of unrelated individuals then phasing microhaplotypes by statistical and computational techniques. Determining phase for a single new individual requires the larger set of individuals to have been genotyped previously. Rare microhaplotypes possessed only by the target individual or microhaplotypes private to a specific population not previously studied are unlikely to be accurately phased using data sets of SNPs. Thus, there is a demand for an approach that could directly determine a gain single individual's precise microhaplotype information. In the present study, we introduced potential approaches of single chain sequencing based Massively Parallel Sequencing Technology (MiSeq) and PCR based Single Strand Conformational Polymorphism (SSCP) technology which was simple, accurate, and cost-effective. The results indicated that microhaplotypes contain much more polymorphic information than divided SNPs per locus (average heterozygosity of microhaplotype 0.61 VS SNPs 0.41). When microhaplotype allele frequencies were compared among five Chinese ethnic populations, significantly different distributions were found between the Han and Uyghur populations. Further analysis of pairwise Fst values and analysis of molecular variance (AMOVA), showed significant population differentiation between the Uyghur and other populations.

[Efficiency of 27-plex single nucleotide polymorphism multiplex system for ancestry inference in different populations]

OBJECTIVE

To validate the efficiency of 27-plex single nucleotide polymorphism (SNP) multiplex system for ancestry inference.

METHODS

The 27-plex SNP system was validated for its sensitivity and species specificity. A total of 533 samples were collected from African, Southern Chinese Han, China's ethic minorities (Yi, Hui, Miao, Tibet, and Uygur), European, Central Asian, Western Asian, Southern Asian, Southeast Asian and South American populations for clustering analysis of the genotypes by citing 3 representative continental ancestral groups [East Asia (CHB), Europe (CEU), and Africa (YRI)] from HapMap database.

RESULTS

The system sensitivity is 0.125 ng. Twenty and six genotypes were detected in chimpanzee and monkeys, respectively. Except in rs10496971, no more products were found in other animals. The system was capable of differentiating intercontinental populations but not of distinguishing between East Asian and Southeast Asian population or between Southern Chinese Han population and Chinese Ethnic populations (Hui, Miao, Yi and Tibet). This system achieved a 100% accuracy for intercontinental population source inference for 46 blind test samples.

CONCLUSION

27-plex SNPs multiplex system has a high sensitivity and species specificity and can correctly differentiate the ancestry origins of individuals from African, European and East Asian for criminal case investigation. But this system is not capable of distinguishing subpopulation groups and more specific ancestry-informative markers are needed to improve its recognition of Southeast Asian and Chinese ethnic populations.