Ancestry Information Research Articles

Pure wild forest reindeer (Rangifer tarandus fennicus) or hybrids? A whole-genome sequencing approach to solve the taxonomical status

AbstractIn Finland, the geographic distribution of domestic reindeer (Rangifer tarandus tarandus) and Finnish wild forest reindeer (Rangifer tarandus fennicus) partly overlap in the vicinity of the southern border of the reindeer herding area. Additionally, domestic reindeer are occasionally kept as pets within the distribution range of the wild forest reindeer. Hybridisation of these two subspecies is one of the major threats for the wild forest reindeer population. Concerns about potential hybridisation served as the catalyst also for this study, which we aimed to clarify the taxonomic status of presumed wild forest reindeer individuals intended as founder individuals for a reintroduction project. To do this, we resequenced genomes of four Rangifer tarandus individuals with unknown taxonomical status and investigated their ancestries by comparing the genomic data with the existing resequenced data of the Finnish domestic reindeer and Finnish wild forest reindeer. The genetic relationship investigations indicated that all individuals we analysed were pure wild forest reindeer, making them suitable as founder individuals for the reintroduction project. Thus, our study provided critical knowledge for practical conservation action, where it was essential to recognise each individual’s origin. In the future, it will also offer novel insights into the spread of native wild forest reindeer to new geographic regions in Finland. For subsequent studies, additional resequenced genomic data of Rangifer individuals will be needed to develop an ancestry information marker panel of single nucleotide polymorphisms for rapid and cost-effective identification of hybrid individuals of these subspecies.

Development and evaluation of a panel of newly screened Y chromosome InDels for inferring paternal ancestry information in Southwest China.

Y-InDels (insertions/deletions) are genetic markers which are extremely understudied. It is unknown whether this type of markers can be utilized for genetic ancestry inference. We have developed an innovative Y chromosome ancestry inference system tailored for forensic applications. This panel amplifies 21 Y chromosome loci, encompassing Y-InDels and Y-SNPs (Single Nucleotide Polymorphism), utilizing the capillary electrophoresis (CE) platform. The system performed well at DNA concentrations greater than 0.125 ng/ul and produced accurate results at a 1:100 mixing ratio of male and female DNA. The Cumulative probability of matching (CPM) was between 0.95 and 0.97 in the experimental population. The system's efficacy in inferring ancestral origins was demonstrated through intercontinental population discrimination, revealing high discrimination power between African and East Asian populations. Population genetic analyses conducted on Han, Qiang and Hui populations in Southwest China, where the smallest FST value was 0.0002 between Han Chinese in Beijing (from 1000 Genomes Project) and Qiang Chinese from Sichuan (CQSC). Phylogenetic tree construction further illuminated distinct haplotypes among populations, with ethnically unique haplotypes observed in 34.6% of Hui and 7.1% of Qiang populations. K-fold cross-validation show the system's inference abilities at the intercontinental level. In addition, our investigations identified potential associations between the Y-InDel locus Y: 15,385,547 (GRCh37) and haplogroup R1a1a1b2a2- Z2124, as well as locus Y: 13,990,180 (GRCh37) and haplogroup F-M89. In conclusion, we have established a Y-chromosome inference system tailored for grassroots-level application, underscoring the value of incorporating Y-InDel markers in forensic analyses.

Motivations for Direct-to-Consumer Genetic Testing: Understanding Interpretations of Ancestry Results

AbstractDirect-to-consumer genetic testing (DTCGT) has the potential to significantly impact racial and ethnic identities as well as social concepts of race and ethnicity. Prior literature challenges the binary choice of essentialism vs. constructionism in understanding consumers’ interpretations of genetic ancestry results. Largely focusing on differences by race and ethnicity, this research finds that test takers selectively apply genetically determinist logic depending on their prior identities and interests. We extend this line of inquiry using in-depth interviews with thirty-six mostly white participants who had previously taken a DTCGT offering combined health and ancestry results, which provided an opportunity to explore how different motivations for testing – e.g., for health or ancestry information – impact interpretations of ancestry results. Our analysis reveals distinct patterns in how health- vs. ancestry-motivated consumers invoke genetic determinism in their interpretations of DTCGT results. At the same time, regardless of motivation for testing, we found little use of genetic results to challenge the coherence or biological basis of racial or ethnic categories. Our results suggest that even if genetic determinism is only selectively applied, and in ways that vary between consumers with different motivations for testing, at least among whites, discourses of genetics as “truth” and white normativity are nonetheless the prevailing interpretive frameworks for genetic ancestry results.

Abstract B012: Prioritization of ancestry-specific variations in disease data helps to alleviate bias in genomic data

Abstract 95% of sequencing data is from individuals of European descent. Underrepresentation of non- European individuals in genomic resources has limited our understanding of the effects of population-specific variants on complex traits and disease. Human populations have undergone selection for variants beneficial to survival in their environment, resulting in individuals with genetic variants unique to their ancestral populations. While these variants can impact disease occurrence and treatment outcome, genetic ancestry is often unaccounted for in disease modeling. Lack of ancestral population representation in data has led to disparate disease outcomes and treatment. While the primary proposed solution to this problem is more diverse sequencing of patients, these efforts will take years of effort and continual work to maintain the diversity balance. Additionally, they will not solve the issue; clinical trials cannot expect to capture human global diversity at every stage. Here we show we can mitigate data bias by utilizing readily available genomic population databases to target genes with ancestrally relevant variations. Our AI model, PhyloFrame, creates equitable gene signatures from transcriptomic input data. PhyloFrame corrects for ancestral bias in data by utilizing genomic population databases and functional interaction networks to identify genes both relevant to disease and associated with a variant unique to a single ancestry. PhyloFrame uses gnomAD data to quantify genome-wide ancestry-specific allele frequencies from a large cohort of healthy individuals, which PhyloFrame uses to create ancestry-agnostic signatures when modeling disease data. Our model demonstrates the utility of including readily available population-level data from healthy individuals in AI methods to overcome existing genomic data bias. PhyloFrame serves also as a demonstration of how equitable AI methods create gene signatures applicable across ancestries without requiring sample-specific ancestry information. Our model demonstrates how AI can be used to help mitigate ancestral bias in genomic data using preexisting data and contribute to equitable representation in medical research. Citation Format: Leslie A. Smith, Kiley Graim, James A. Cahill. Prioritization of ancestry-specific variations in disease data helps to alleviate bias in genomic data [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B012.

Local Ancestry Inference Based on Population-Specific Single-Nucleotide Polymorphisms-A Study of Admixed Populations in the 1000 Genomes Project.

Human populations have interacted throughout history, and a considerable portion of modern human populations show evidence of admixture. Local ancestry inference (LAI) is focused on detecting the genetic ancestry of chromosomal segments in admixed individuals and has wide applications. In this work, we proposed a new LAI method based on population-specific single-nucleotide polymorphisms (SNPs) and applied it in the analysis of admixed populations in the 1000 Genomes Project (1KGP). Based on population-specific SNPs in a sliding window, we computed local ancestry information vectors, which are moment estimators of local ancestral proportions, for two haplotypes of an admixed individual and inferred the local ancestral origins. Then we used African (AFR), East Asian (EAS), European (EUR) and South Asian (SAS) populations from the 1KGP and indigenous American (AMR) populations from the Human Genome Diversity Project (HGDP) as reference populations and conducted the proposed LAI analysis on African American populations and American populations in the 1KGP. The results were compared with those obtained by RFMix, G-Nomix and FLARE. We demonstrated that the existence of alleles in a chromosomal region that are specific to a particular reference population and the absence of alleles specific to the other reference populations provide reasonable evidence for determining the ancestral origin of the region. Contemporary AFR, AMR and EUR populations approximate ancestral populations of the admixed populations well, and the results from RFMix, G-Nomix and FLARE largely agree with those from the Ancestral Spectrum Analyzer (ASA), in which the proposed method was implemented. When admixtures are ancient and contemporary reference populations do not satisfactorily approximate ancestral populations, the performances of RFMix, G-Nomix and FLARE deteriorate with increased error rates and fragmented chromosomal segments. In contrast, our method provides fair results.

Global and local ancestry estimation in a captive baboon colony.

The last couple of decades have highlighted the importance of studying hybridization, particularly among primate species, as it allows us to better understand our own evolutionary trajectory. Here, we report on genetic ancestry estimates using dense, full genome data from 881 olive (Papio anubus), yellow (Papio cynocephalus), or olive-yellow crossed captive baboons from the Southwest National Primate Research Center. We calculated global and local ancestry information, imputed low coverage genomes (n = 830) to improve marker quality, and updated the genetic resources of baboons available to assist future studies. We found evidence of historical admixture in some putatively purebred animals and identified errors within the Southwest National Primate Research Center pedigree. We also compared the outputs between two different phasing and imputation pipelines along with two different global ancestry estimation software. There was good agreement between the global ancestry estimation software, with R2 > 0.88, while evidence of phase switch errors increased depending on what phasing and imputation pipeline was used. We also generated updated genetic maps and created a concise set of ancestry informative markers (n = 1,747) to accurately obtain global ancestry estimates.

Factors Associated With High Blood Pressure in Adults of São Paulo, Brazil: The Influence of Self-Reported Color-Ethnicity and Genomic Ancestry Information

Factors Associated With High Blood Pressure in Adults of São Paulo, Brazil: The Influence of Self-Reported Color-Ethnicity and Genomic Ancestry Information

How admixed captive breeding populations could be rescued using local ancestry information.

This paper asks the question: can genomic information be used to recover a species that is already on the pathway to extinction due to genetic swamping from a related and more numerous population? We show that a breeding strategy in a captive breeding program can use whole genome sequencing to identify and remove segments of DNA introgressed through hybridisation. The proposed policy uses a generalized measure of kinship or heterozygosity accounting for local ancestry, that is, whether a specific genetic location was inherited from the target of conservation. We then show that optimizing these measures would minimize undesired ancestry while also controlling kinship and/or heterozygosity, in a simulated breeding population. The process is applied to real data representing the hybridized Scottish wildcat breeding population, with the result that it should be possible to breed out domestic cat ancestry. The ability to reverse introgression is a powerful tool brought about through the combination of sequencing with computational advances in ancestry estimation. Since it works best when applied early in the process, important decisions need to be made about which genetically distinct populations should benefit from it and which should be left to reform into a single population.

Population structure and genomic diversity of the Einsiedler horse.

The breeding history of the Einsiedler horse is closely connected with the Benedictine cloister Einsiedeln. In the mid-nineteenth century, it was decided to use European Warmblood stallions for cross-breeding and to abandon the selection of stallions. Since that time, it has only been possible to trace back the origin of Einsiedler horses using maternal ancestry information. Here, we collected high-density genotype data for European Warmblood horses (Selle Français, Swiss Warmblood and Einsiedler) and Franches-Montagnes horses, the last native Swiss horse breed, to unravel the current population structure of the Einsiedler horse. Using commonly applied methods to ascertain fine-scale population structures, it was not possible to clearly differentiate the Einsiedler from other European Warmblood horses. However, by means of runs of homozygosity (ROH) we were able to detect breed-specific ROH islands for the Einsiedler horse, including genes involved in domestication and adaptation to high altitude. Therefore, future breeding activities should involve the screening of these breed-specific ROH segments, the revival of cryopreserved sperm and the selection of Einsiedler stallions.

Abstract 7129: DNA polymerase beta expression in head & neck cancer modulates the poly-ADP-ribose-mediated replication checkpoint

Abstract Head and Neck Squamous Cell Carcinoma (HNSCC) impose a significant health burden, necessitating innovative therapeutic strategies to enhance treatment efficacy. Current standard treatments, including surgery, radiation therapy, and chemotherapy, often exhibit limited effectiveness and cause substantial side effects. This underscores the critical need for novel therapies that selectively target cancer cells, sparing normal tissue. Survival from HNSCC is poor, and importantly, a racial disparity between African Americans (AfAm) and European Americans (EuAm) has been known for some time. Ancestry Informative Markers (AIMs) are associated with altered mRNA expression of Polβ where higher expression of Polβ was observed among AfAm patients in comparison to EuAm patients. Our research focuses on DNA polymerase beta (Polβ) and its role in replication stress and response to chemotherapy and DNA damage response modifiers. Elevated expression of Polβ is linked to increased DNA damage and genomic instability, contributing to treatment resistance. In this regard, our investigations reveal a regulatory role for base excision repair (BER) proteins, including Polβ, in the cellular response to inhibitors of poly(ADP-ribose) glycohydrolase (PARG), an enzyme involved in poly(ADP-ribose) (PAR) degradation. Inhibition of PARG triggers a robust intra-S phase response, activating ATR and CHK1 signaling. Exploiting the synthetic lethality between PARG inhibition and ATR/CHK1 inhibition, we have demonstrated the ability to overcome Polβ overexpression mediated treatment resistance in HNSCC cells. Specifically, our in vitro studies demonstrate that the response to a combination of an ATR inhibitor and PARG inhibitor is impacted by Polβ expression in HNSCC cells, with synergistic effects surpassing the efficacy of the individual inhibitors. Similarly, the combination of a CHK1 inhibitor and PARG inhibitor proves effective in cells with elevated Polβ expression, offering a potential dual therapeutic strategy. These combinations exhibit promising potential for HNSCC treatment when Polβ expression is elevated. In conclusion, our findings propose a novel therapeutic paradigm for HNSCC, employing combination therapy with ATR or CHK1 inhibitors and PARG inhibitors. This approach offers a targeted strategy, presenting a promising avenue for the development of more effective and less toxic treatment modalities in the management of HNSCC and may help overcome resistance from elevated expression of Polβ. Citation Format: Md Maruf Khan, Anusha Angajala, Denise Y. Gibbs, Jeffrey C. Liu, Camille Ragin, Robert W. Sobol. DNA polymerase beta expression in head & neck cancer modulates the poly-ADP-ribose-mediated replication checkpoint [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7129.

Race, ethnicity, ancestry, and aspects that impact HLA data and matching for transplant.

Race, ethnicity, and ancestry are terms that are often misinterpreted and/or used interchangeably. There is lack of consensus in the scientific literature on the definition of these terms and insufficient guidelines on the proper classification, collection, and application of this data in the scientific community. However, defining groups for human populations is crucial for multiple healthcare applications and clinical research. Some examples impacted by population classification include HLA matching for stem-cell or solid organ transplant, identifying disease associations and/or adverse drug reactions, defining social determinants of health, understanding diverse representation in research studies, and identifying potential biases. This article describes aspects of race, ethnicity and ancestry information that impact the stem-cell or solid organ transplantation field with particular focus on HLA data collected from donors and recipients by donor registries or transplant centers.

Systematic analyses of AISNPs screening and classification algorithms based on genome-wide data for forensic biogeographic ancestry inference

Identifying the biogeographic ancestral origin of biological sample left at a crime scene can provide important evidence for judicial case, as well as clue for narrowing down suspect. Ancestry informative single nucleotide polymorphism (AISNP) has become one of the most important genetic markers in recent years for screening ancestry information loci and analyzing the population genetic background and structure due to their high number and wide distributions in the human genome. In this study, based on data from 26 populations in the 1000 Genomes Project Phase 3, a Random Forest classification model was constructed with one-vs-rest classification strategy for embedded feature selection in order to obtain a panel with a small number of efficient AISNPs. The research aim was to clarify differentiations of population genetic structures among continents and subregions of East Asia. ADMIXTURE results showed that based on the 58 AISNPs selected by the machine learning algorithm, the 26 populations involved in the study could be categorized into six intercontinental ancestry components: North East Asia, South East Asia, Africa, Europe, South Asia, and America. The 24 continental-specific AISNPs and 34 East Asian-specific AISNPs were finally obtained, and used to construct the ancestry prediction model using XGBoost algorithm, resulting in the Matthews correlation coefficients of 0.94 and 0.89, and accuracies of 0.94 and 0.92, respectively. The machine learning models that we constructed using population-specific AISNPs were able to accurately predict the ancestral origins of continental and intra-East Asian populations. To summarize, screening a set of high-perform AISNPs to infer biogeographical ancestral information using embedded feature selection has potential application in creating a layered inference system that accurately differentiates from intercontinental populations to local subpopulations.

Development of a novel five dye insertion/deletion (INDEL) panel for ancestry determination.

The use of genetic markers, specifically Short Tandem Repeats (STRs), has been a valuable tool for identifying persons of interest. However, the ability to analyze additional markers including Single Nucleotide Polymorphisms (SNPs) and Insertion/Deletion (INDELs) polymorphisms allows laboratories to explore other investigative leads. INDELs were chosen in this study because large panels can be differentiated by size, allowing them to be genotyped by capillary electrophoresis. Moreover, these markers do not produce stutter and are smaller in size than STRs, facilitating the recovery of genetic information from degraded samples. The INDEL Ancestry Informative Markers (AIMs) in this study were selected from the 1000 Genomes Project based on a fixation index (FST) greater than 0.50, high allele frequency divergence, and genetic distance. A total of 25 INDEL-AIMs were optimized and validated according to SWGDAM guidelines in a five-dye multiplex. To validate the panel, genotyping was performed on 155 unrelated individuals from four ancestral groups (Caucasian, African, Hispanic, and East Asian). Bayesian clustering and principal component analysis (PCA) were performed revealing clear separation among three groups, with some observed overlap within the Hispanic group. Additionally, the PCA results were compared against a training set of 793 samples from the 1000 Genomes Project, demonstrating consistent results. Validation studies showed the assay to be reproducible, tolerant to common inhibitors, robust with challenging casework type samples, and sensitive down to 125 pg. In conclusion, our results demonstrated the robustness and effectiveness of a 25 loci INDEL system for ancestry inference of four ancestries commonly found in the United States.

Pharmacogenomics of intravenous immunoglobulin response in Kawasaki disease.

Kawasaki disease (KD) is a diffuse vasculitis in children. Response to high dose intravenous gamma globulin (IVIG), the primary treatment, varies according to genetic background. We sought to identify genetic loci, which associate with treatment response using whole genome sequencing (WGS). We performed WGS in 472 KD patients with 305 IVIG responders and 167 non-responders defined by AHA clinical criteria. We conducted logistic regression models to test additive genetic effect in the entire cohort and in four subgroups defined by ancestry information markers (Whites, African Americans, Asians, and Hispanics). We performed functional mapping and annotation using FUMA to examine genetic variants that are potentially involved IVIG non-response. Further, we conducted SNP-set [Sequence] Kernel Association Test (SKAT) for all rare and common variants. Of the 43,288,336 SNPs (23,660,970 in intergenic regions, 16,764,594 in introns and 556,814 in the exons) identified, the top ten hits associated with IVIG non-response were in FANK1, MAP2K3:KCNJ12, CA10, FRG1DP, CWH43 regions. When analyzed separately in ancestry-based racial subgroups, SNPs in several novel genes were associated. A total of 23 possible causal genes were pinpointed by positional and chromatin mapping. SKAT analysis demonstrated association in the entire MANIA2, EDN1, SFMBT2, and PPP2R5E genes and segments of CSMD2, LINC01317, HIVEPI, HSP90AB1, and TTLL11 genes. This WGS study identified multiple predominantly novel understudied genes associated with IVIG response. These data can serve to inform regarding pathogenesis of KD, as well as lay ground work for developing treatment response predictors.

The interest of informative ancestry markers (AIM) and their fields of application

This review focuses on the study of biogeographic ancestry using the Accurate Ancestry Identification Panel. Autosomal markers may provide little information about the nature of an individual's admixture due to ongoing human recombination and migration. Biogeographic ancestry assessment (BGA) is a term used to describe ancestry through DNA testing. This is usually accomplished by testing specific regions of DNA called ancestry information markers (AIMs). AIMs are chosen because they expose significantly different frequencies between different populations in different parts of the world. The panels of these AIMs can be assessed using next-generation sequencing (NGS) to predict the geographical origins of a person of interest's ancestors, usually in terms of continent of origin, and sometimes by smaller geographic regions. The use of ancestry informative markers (AIM) to identify genomic ancestry can be useful for a variety of studies in evolutionary genetics, biomedical research, and forensic analyses. However, there remains a major challenge in determining AIMs for populations with complex and highly mixed ancestry.

Whole-Genome Sequencing Reveals Distinct Mutational Signatures in Multiple Myeloma Patients with African Ancestry Compared with Those of Non-African Ancestry

INTRODUCTION: Improving health outcomes for patients with African ancestry (AA) is a key healthcare aim, but there is uncertainty in whether disparities arise predominantly from socioeconomic differences or from genetic differences in tumor biology. It remains an open question as to whether multiple myeloma (MM) occurring in AA patients has a similar or different spectrum of genomic abberations when compared to patients having European ancestry. To date, studies have suggested that AA have an excess of t(11;14) and a deficiency of TP53 mutations. We have established a series of 302 cases of MM precursor and newly diagnosed MM with whole-genome sequencing (WGS) available that is enriched for self-declared AA or diverse ethnic background. METHODS: In collaboration with the NYGC and Polyethnic-1000 consortium, we sequenced tumor samples to a depth of 60-80X and normal tissue to 30-40X. We a employed bioinformatics pipeline with a consensus mechanism for somatic variant calling, including Mutect2, Strelka2, and VarScan2 for SNVs; Mutect2, Strelka2, VarScan2, and SvABA for InDels; Battenberg and FACETS for CNVs; Manta, SvABA, DELLY2, and IgCaller for SVs. Additionally, an admixture workflow was used to estimate each individual's ancestral lineage using continentally-distinct references, comprising 23 regional populations within 5 super-populations from the 1000 Genomes Project (https://github.com/pblaney/mgp1000). Mutational signature were calculated using the R package mmsig (Rustad et al. Comm. Bio. 2021). RESULTS: Using admixture estimations from 302 patients with high-coverage WGS together with 941 patients from the CoMMpass trial, we identified five clusters corresponding to single dominant genetic ancestries (median proportion >75% assignment to reference super-population), together with a cluster characterized by highly admixed individuals with no dominant genetic ancestry (median proportion <50%). Of the total, 53.0% are in the European dominant (EUR) cluster, 26.5% African dominant (AFR), 8.6% American dominant (AMR), 7.9% highly admixed, 2.0% East Asian dominant (EAS) and South-East Asian dominant (SAS) clusters, respectively. Stratifying patients by their cluster assignment and calculating the frequency of subtype translocations, we show that t(11;14) occurred in 25.8% of EUR patients while in only 14.6% of AFR (p=0.045) and 7.7% of AMR (p=0.05) patients. The frequency of the t(4;14) was more closely distributed, with 15.7% in EUR, 11.5% in AMR, and 11% in AFR clusters. For the acquired somatic mutations, the tumor mutational burden (TMB) was lowest in the AFR cluster 2.21 (median, somatic mutations per Mb), significantly lower by comparison to the EUR cluster at 2.94 (FDR adj. P=4.3x10 -6). The most striking genomic difference was observed when comparing the mutational signatures landscape between AA and the other racial groups. Using WGS, AA had lower SBS1 and SBS5 absolute contribution compared to EUR, and this was largely responsible for the difference in TMB. SBS1 and SBS5 are known to be clock-like signatures, accumulating at a constant rate over time. Because no differences in age, cancer cell fraction, and coverage were observed between AA and EUR, this finding suggest different mutational clock-like rate between AA and EUR. The higher TMB observed in EUR was also driven by the higher APOBEC-mutational activity (SBS2 and SBS13) compared to AA (p=0.05). Interestingly, 72% of all EUR had APOBEC-activity evident, in contrast to 45% of the AA (p=0.001). This difference was confirmed after excluding the MM precursor patients, previously demonstrated to have lower APOBEC-activity (Oben et al. Natur Comm. 2021), and was validated on CoMMpass whole-exomes. CONCLUSIONS: Leveraging one of the largest series of diverse patients with WGS, and integrating genomic data with comprehensive ancestry information, AA MM emerged as biologically different in term of genomic drivers and mutational signatures, suggesting potential differences in etiology and genomic evolution over time. Further analysis will include molecular timing of clonal copy number gains, and reconstruction of phylogenetic trees, with view to improving our understanding of the etiology of MM development across patient genetic backgrounds. FIGURE: Genomic characteristics of myeloma across ancestries. A) Translocation percentage (number per cluster) and B) Tumor mutational burden across clusters.

Supplemental Material for Examining the Effects of Genetic Ancestry Information on Appraisals of Contested Racial Identities

Supplemental Material for Examining the Effects of Genetic Ancestry Information on Appraisals of Contested Racial Identities

Examining the effects of genetic ancestry information on appraisals of contested racial identities.

The increasing accessibility of DNA ancestry information may influence perceptions of others' and one's own racial identity. The current work tested whether the presence of genetic testing information influenced Black participants' perceptions of individuals who claim a mismatched racial identity (i.e., a racial identity that differs from their parents), and whether these perceptions are moderated by the amount of corroborating DNA evidence and racial claim of the target. Black participants (N = 1,041) were randomly assigned to read about an individual claiming a Black or White mismatched racial identity. The target either had a majority amount (71%) of corroborating genetic information, a minimal amount (29%) or made no mention of genetic information. When a majority percentage of corroborating genetic information was provided, participants evaluated Black-identified targets more favorably than White-identified targets. Additionally, Black-identified targets were evaluated most favorably when they had a majority amount of corroborating genetic information. Among Black perceivers, a majority amount of corroborating genetic information increased positive evaluations of a mismatched, Black-identified racial claim. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Developmental validation of a high-resolution panel genotyping 639 Y-chromosome SNP and InDel markers and its evolutionary features in Chinese populations

Uniparental-inherited haploid genetic marker of Y­chromosome single nucleotide polymorphisms (Y-SNP) have the power to provide a deep understanding of the human evolutionary past, forensic pedigree, and bio-geographical ancestry information. Several international cross-continental or regional Y-panels instead of Y-whole sequencing have recently been developed to promote Y-tools in forensic practice. However, panels based on next-generation sequencing (NGS) explicitly developed for Chinese populations are insufficient to represent the Chinese Y-chromosome genetic diversity and complex population structures, especially for Chinese-predominant haplogroup O. We developed and validated a 639-plex panel including 633 Y-SNPs and 6 Y-Insertion/deletions, which covered 573 Y haplogroups on the Y-DNA haplogroup tree. In this panel, subgroups from haplogroup O accounted for 64.4% of total inferable haplogroups. We reported the sequencing metrics of 354 libraries sequenced with this panel, with the average sequencing depth among 226 individuals being 3,741×. We illuminated the high level of concordance, accuracy, reproducibility, and specificity of the 639-plex panel and found that 610 loci were genotyped with as little as 0.03 ng of genomic DNA in the sensitivity test. 94.05% of the 639 loci were detectable in male-female mixed DNA samples with a mix ratio of 1:500. Nearly all of the loci were genotyped correctly when no more than 25 ng/μL tannic acid, 20 ng/μL humic acid, or 37.5 μM hematin was added to the amplification mixture. More than 80% of genotypes were obtained from degraded DNA samples with a degradation index of 11.76. Individuals from the same pedigree shared identical genotypes in 11 male pedigrees. Finally, we presented the complex evolutionary history of 183 northern Chinese Hans and six other Chinese populations, and found multiple founding lineages that contributed to the northern Han Chinese gene pool. The 639-plex panel proved an efficient tool for Chinese paternal studies and forensic applications.

Improving genetic risk prediction across diverse population by disentangling ancestry representations

Risk prediction models using genetic data have seen increasing traction in genomics. However, most of the polygenic risk models were developed using data from participants with similar (mostly European) ancestry. This can lead to biases in the risk predictors resulting in poor generalization when applied to minority populations and admixed individuals such as African Americans. To address this issue, largely due to the prediction models being biased by the underlying population structure, we propose a deep-learning framework that leverages data from diverse population and disentangles ancestry from the phenotype-relevant information in its representation. The ancestry disentangled representation can be used to build risk predictors that perform better across minority populations. We applied the proposed method to the analysis of Alzheimer’s disease genetics. Comparing with standard linear and nonlinear risk prediction methods, the proposed method substantially improves risk prediction in minority populations, including admixed individuals, without needing self-reported ancestry information.