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A multi-ancestry polygenic risk score for Alzheimer disease is associated with cognitive decline, hippocampal atrophy and neuropathological hallmarks in diverse populations.

Alzheimer disease (AD) has a strong genetic basis, yet previously derived polygenic risk scores (PRS) are heavily weighted by the APOE locus and perform inconsistently across diverse ancestries. We developed an APOE-independent multi-ancestry AD PRS using genome-wide association study summary statistics from cohorts in the United States, Europe and East Asia that were applied to European ancestry (EA), African American (AA), Caribbean Hispanic (CH), and East Asian cohorts from the Alzheimer's Disease Genetics Consortium. PRS performance was evaluated in the multi-ancestry Alzheimer's Disease Sequencing Project (ADSP) dataset and validated in several additional multi-ancestry cohorts. The PRS was significantly associated with AD in the ADSP EA, AA, CH, and Native American Hispanic groups with adjusted odds ratios (ORs) between 1.14 and 1.52 per standard deviation of the PRS. PRS performance was validated in the replication cohorts (ORs 1.21-1.65). The PRS was also associated with poorer memory, executive function, and language performance; greater AD-related neuropathological burden (including CERAD, Braak stage, and Thal phase scores); reduced hippocampal volume; lower CSF Aβ42; and elevated total tau and phosphorylated tau (p-tau), with stronger p-tau associations observed in women. Longitudinal analyses revealed that individuals in the highest PRS decile exhibited the steepest cognitive decline, particularly among those who progressed to AD. Our findings demonstrate the utility of an ancestry-aware and APOE-independent PRS for advancing understanding of the genetic basis of AD across diverse populations. Associations observed with early biological and cognitive changes and potential sex-specific differences support the incorporation of a PRS in clinical trials and personalized intervention and prevention strategies.

Journal Article

Waist-to-height ratio as a practical indicator for screening pediatric metabolic dysfunction-associated steatotic liver disease in diverse populations and genetic backgrounds.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading chronic liver disease in children and adolescents; this parallels the global obesity epidemic. The contribution of genetic susceptibility to pediatric MASLD, and its interaction with anthropometric and biochemical indices used for non-invasive screening remains poorly understood. We aimed to evaluate waist-to-height ratio (WHtR) as a simple, equitable, and scalable tool for early identification of pediatric MASLD and relate this to genetic risk. METHODS: We combined school-based data from 1010 Chinese children with analyses of the Global Burden of Disease, the 1000 Genomes Project, and the US National Health and Nutrition Examination Survey (NHANES). Thirteen MASLD-related single-nucleotide polymorphisms (SNPs) were genotyped to construct a genetic risk score (GRS). We examined global epidemiological patterns, quantified inter-population allele divergence, and assessed how GRS modifies cutoffs and performance of nine anthropometric and biochemical indices. RESULTS: Genetic analysis revealed minimal frequency divergence across most ancestries (mean Fixation index&#x2009;<&#x2009;0.05), except for the African ancestry where there was moderate divergence. Higher GRS were associated with lower cutoffs across indices. When GRS Z-score increased from -3 to 3, visceral adiposity index showed the sharpest changes (Z-score decreased from 1.5 to -1.8), while BFP (1.2&#xa0;to&#xa0;0.1) and WHtR (1.5&#xa0;to&#xa0;0.1) showed gradual change. Furthermore, incorporating GRS into the base anthropometric models yielded only marginal improvements in overall screening performance [area under the receiver operating characteristic curve (AUC) and Youden Index]. Validation in NHANES showed WHtR&#x2009;&#x2265;&#x2009;0.48 retained high discrimination (AUC&#x2009;>&#x2009;0.87) across most genetic variants. CONCLUSIONS: This study suggests that WHtR is a consistent and practical tool for screening pediatric patients with MASLD across diverse populations. While genetic variation may influence optimal thresholds, WHtR&#x2009;&#x2265;&#x2009;0.48 appears broadly applicable, supporting its potential use as a frontline screening metric in diverse settings.

Humans

Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts.

Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N&#xa0;= 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.

Humans

2025 Donald Seldin Lecture: Leveraging Diverse Population Genomics and Multiomics Integration for Gene Discovery of Cardiovascular and Kidney Diseases.

This review discusses the implications of frameworks leveraging genetic admixture and multiomics data for advancing gene discovery in cardiovascular and kidney disease research. By broadening gene discovery efforts to additional populations that have a disproportionately high risk of disease and leveraging genetic diversity in admixed populations, studies can identify population-enriched risk variants that traditionally have been missed in genome-wide association studies. The use of multiomics approaches, including the transcriptome, proteome, and metabolome, advances a mechanistic understanding of disease beyond associations. As single-cell omics technologies continue to improve, their integration into gene discovery may help uncover cell-type-specific regulatory pathways and more precise biological contexts. The full potential of these approaches depends on sustained investment in diverse, well-characterized omics data sets, methodological innovation in multiancestry statistical approaches, and interdisciplinary collaboration bridging genomics, epidemiology, and clinical medicine. These efforts will need to be translated into clinically actionable insights, including ancestry-informed risk stratification and targeted therapeutics, to improve outcomes for cardiovascular and kidney diseases.

Humans

Genetically diverse populations hold the keys to climatic adaptation in the Western barn owl (Tyto alba).

Although local adaptation influences species distributions, its role in driving evolutionary resilience under climate change remains unclear. Current predictive models focus on genetic adaptation to present climates, providing limited insight into future adaptive capacity. We hypothesise that historical responses to climatic shifts can reveal candidate loci for local adaptation in the future. Combining ecological niche modelling and genomic analyses, we investigate spatiotemporal patterns and mechanisms of local adaptation of the Western Palearctic barn owl (Tyto alba). Ecological modelling reveals that barn owls now occupy a broader climatic niche than during the Last Glacial Maximum. Genomic analyses indicate ongoing adaptation, with regions under selection linked to environmental factors across all populations. We find that local adaptation drives evolutionary changes across populations, enabling colonisation of new habitats and shaping responses to climate change in resident populations. We show that standing genetic diversity plays a crucial role in adaptation to past, present, and future environmental shifts.

Animals

A multiancestry polygenic risk score for Alzheimer's disease is associated with cognitive decline and neuropathological hallmarks in diverse populations.

Previously derived polygenic risk scores (PRSs) for Alzheimer's disease (AD) perform inconsistently across diverse ancestries. We developed an APOE-independent multiancestry AD PRS using genome-wide association study summary statistics applied to European ancestry, African American, Caribbean Hispanic and East Asian cohorts. PRS performance was evaluated in a large independent multiancestry dataset and validated in several additional multiancestry cohorts. The PRS was significantly associated with AD in European ancestry, African American, Caribbean Hispanic and Native American Hispanic groups with adjusted odds ratios between 1.14 and 1.52 per PRS standard deviation. PRS performance was validated in the replication cohorts (odds ratios: 1.21-1.65). The PRS was also associated with poorer memory, executive function and language performance, greater AD-related neuropathological burden, reduced hippocampal volume, lower cerebrospinal fluid amyloid-&#x3b2;42 and elevated total tau and phosphorylated tau, with stronger phosphorylated tau associations observed in women. Our findings support the value of ancestry-aware PRSs as a component of broader multimodal risk stratification frameworks.

Aged

Genetic diversity, population structure in a historical panel of Brazilian soybean cultivars.

Soybean [Glycine max (L.) Merrill] is one of the most widely grown legumes in the world, with Brazil being its largest producer and exporter. Breeding programs in Brazil have resulted from multiple cycles of selection and recombination starting from a small number of USA cultivar ancestors in the 1950s and 1960s years. This process has led to the successful adaptation of this crop to tropical conditions, a phenomenon known as tropicalization. Many studies describe a narrow genetic background in Brazilian soybean cultivars. Various factors can affect the genetic diversity in species, especially in cultivated crops, such as the reproduction type, artificial selection, and the number and sources of variability in the breeding programs. In turns, the genetic diversity can affect the linkage disequilibrium blocks (LD) patterns and, consequently, molecular breeding strategies for selection of target loci for agronomic traits. We used high-throughput genotyping with SoySNP50K Illumina SNP markers to assess a collection of 370 Brazilian soybean accessions covering more than 60 years of soybean breeding in Brazil. Our goal was to investigate population structure and genetic diversity in the Brazilian germplasm, detect patterns of LD blocks, and identify regions presenting signals of selective swaps linked with quantitative trait loci (QTLs) of agronomic interest. Population structure analysis revealed two major groups among all genotypes, primarily differentiated by the year of release, separating old and new cultivars (before and after 2000&#xb4;s years), and by growth habit (stem termination type-SST). The group I comprises about 75% of the panel and includes cultivars release before 2000`s years, including the oldest cultivars released in Brazil, most of which exhibit a determinate growth habit and maturity groups VI and VII. Group II includes only 83 materials, but shows higher levels of diversity than group I, representing most recent introductions in Brazilian germplasm. Further analysis of substructure within Group I, identified seven subgroups with no clear trend for segregation based on maturity group, STT or year of release. Instead, these subgroups were based on the contribution of key donors of disease resistance and adaptability, as soybean cultivation expanded from the South to Central region of Brazil. This finding is consistent with the history of soybean expansion in Brazil. We identified 123 genomic regions under selection among the groups of Brazilian cultivars associated with 440 quantitative trait loci (QTLs), revealing regions fixed across the breeding process associated with yield, disease resistance, water efficiency use, and others.

Glycine max

Exploring depression treatment response by using polygenic risk scoring across diverse populations.

Treatment-resistant depression (TRD), usually defined as limited or no response to at least two antidepressants, occurs in approximately one-third of individuals diagnosed with major depressive disorder (MDD). Studies of individuals of European ancestry highlight a genetic overlap between TRD and MDD. We analyzed two large and diverse biobanks, the UCLA ATLAS Community Health Study (ATLAS) and the All of Us Research Program (AoU), to test for associations between a polygenic score for major depression (MDD-PGS) and TRD. Compared to treatment responders, TRD individuals have higher MDD-PGS across all ancestries. MDD-PGS was significantly associated with response to selective serotonin reuptake inhibitors in individuals of European and Hispanic/Latin American genetic ancestries in both biobanks. In AoU, a decreased MDD-PGS was observed in response to tricyclics or serotonin modulators in individuals of European American ancestry and in response to serotonin and norepinephrine reuptake inhibitors in individuals of African American ancestry. ATLAS found that MDD-PGS showed lower odds of responding to atypical agents than did TRD in MDD-affected individuals belonging to the Hispanic/Latin American group, MDD-PGS was associated with atypical agents. Overall, by leveraging larger sample sizes from two diverse biobanks, we provide new insights into antidepressant response and treatment specificity for MDD in individuals of diverse genetic ancestries.

Adult

Comparative genomic analysis of key oncogenic pathways in hepatocellular carcinoma among diverse populations.

BACKGROUND/OBJECTIVES: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with significant racial and ethnic disparities in incidence, tumor biology, and clinical outcomes. Hispanic/Latino (H/L) patients tend to be diagnosed at younger ages and more advanced stages than Non-Hispanic White (NHW) patients, yet the molecular mechanisms underlying these disparities remain poorly understood. Key oncogenic pathways, including RTK/RAS, TGF-Beta, WNT, PI3K, and TP53, play pivotal roles in tumor progression, treatment resistance, and response to targeted therapies. However, ethnicity-specific alterations within these pathways remain largely unexplored. This study aims to compare pathway-specific mutations in HCC between H/L and NHW patients, assess tumor mutation burden, and identify ethnicity-associated oncogenic drivers using publicly available datasets. Findings from this analysis may inform precision medicine strategies for improving early detection and targeted therapies in underrepresented populations. METHODS: We conducted a bioinformatics analysis using publicly available HCC datasets to assess mutation frequencies in RTK/RAS, TGF-Beta, WNT, PI3K, and TP53 pathway genes. The study included 547 patients, consisting of 69 H/L patients and 478 NHW patients. Patients were stratified by ethnicity (H/L vs. NHW) to evaluate differences in mutation prevalence. Chi-squared tests were used to compare mutation frequencies, while Kaplan-Meier survival analysis assessed overall survival differences associated with pathway-specific alterations in both populations. RESULTS: Significant differences were observed in the RTK/RAS pathway related genes, particularly in FGFR4 mutations, which were more prevalent in H/L patients compared to NHW patients (4.3% vs. 0.6%, p = 0.02). Additionally, IGF1R mutations exhibited borderline significance (7.2% vs. 2.9%, p = 0.07). In the PI3K pathway, INPP4B alterations were more frequent in H/L patients than in NHW patients (4.3% vs. 1%, p = 0.06), while in the TGF-Beta pathway, TGFBR2 mutations were more common in H/L patients (2.9% vs. 0.4%, p = 0.07), suggesting potential ethnicity-specific variations. Survival analysis revealed no significant differences in overall survival between H/L and NHW patients, indicating that molecular alterations alone may not fully explain survival disparities and suggesting a role for additional factors such as immune response, environmental exposures, or access to targeted therapies. CONCLUSIONS: This study provides one of the first ethnicity-focused analyses of key oncogenic pathway alterations in HCC, revealing distinct molecular differences between H/L and NHW patients. The findings suggest that RTK/RAS (FGFR4, IGF1R), PI3K (INPP4B), and TGF-Beta (TGFBR2) pathway alterations may play a distinct role in HCC among H/L patients, while their prognostic significance in NHW patients remains unclear. These insights emphasize the importance of incorporating ethnicity-specific molecular profiling into precision medicine approaches to improve early detection, targeted therapies, and clinical outcomes in HCC, particularly for underrepresented populations.

PI3K pathway

Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms.

Contrastive learning is a widely adopted self-supervised pretraining strategy, yet its dependence on cohort composition remains underexplored. We present Contrasting by Augmented Patient Electrocardiograms (CAPE) foundation model and pretrain on four cohorts (n&#x2009;=&#x2009;5,203,269), from diverse populations across three continents (North America, South America, Asia). We systematically assess how cohort demographics, health status, and population diversity influence the downstream performance for prediction tasks also including two additional cohorts from another continent (Europe). We find that downstream performance depends on the distributional properties of the pretraining cohort, including demographics and health status. Moreover, while pretraining with a multi-centre, demographically diverse cohort improves in-distribution accuracy, it reduces out-of-distribution (OOD) generalisation of our contrastive approach by encoding cohort-specific artifacts. To address this, we propose the In-Distribution Batch (IDB) strategy, which preserves intra-cohort consistency during pretraining, discourages learning of spurious cohort-specific features, and instead promotes clinically meaningful variability within cohorts. This leads to improved out-of-distribution robustness, with gains of 9-40% in downstream label prediction performance. This work provides insights into pretraining strategies for more clinically deployable and generalisable foundation models.

Journal Article

Genome-wide SNP-based genomic diversity and population structure analysis in alpaca populations from Europe and Peru.

This study aimed to analyze the genetic diversity and population structure of alpacas in Germany, Switzerland, and Austria (German-speaking regions, GSR) and to compare with that of the country of origin of the species (Peru). A total of 179 animals from GSR and 151 from Peru were genotyped with a species-specific 76k SNP array. The observed and expected heterozygosity was 0.305 and 0.311 for GSR and 0.310 and 0.312 for Peru. The mean FROH values were 0.029 for GSR and 0.023 for Peru. In general, results show that breeders in both analyzed regions efficiently maintain genetic diversity. Principal component analysis identified the GSR and Peru populations as separate from each other, but the relative proximity of both clusters indicates the shared genetic heritage. FST and XPEHH methods identified genomic regions under selection for traits such as coat color and adaptation. Genome-wide association studies comparing black and brown with white or gray alpacas identified associated genome regions containing the ASIP and KIT genes, respectively. The association of a recently identified keratin locus on chromosome 16 with differences in fleece type in alpacas was confirmed, while the putative causality of a TRPV3 variant was rejected.

Animals

Genetic Diversity and Population Structure of Urban and Rural Goshawks.

Urbanization poses a growing threat to biodiversity with potential impacts on species' genetic diversity and population structure. The Eurasian goshawk (Astur gentilis) is traditionally a forest-dwelling raptor that has recently established breeding populations in urban environments such as Helsinki, Finland. Here, we investigated genetic diversity and population structure across urban, suburban, and rural goshawk populations in Finland using 10 microsatellite markers and 72 individuals sampled between 1990 and 2020. Genetic diversity, measured by heterozygosity and allelic richness, was similar among populations. Genetic differentiation was low to moderate (F ST&#x2009;=&#x2009;0.022-0.074) and statistically non-significant. Despite urbanization, contemporary urban goshawks showed genetic similarity to adjacent contemporary non-urban goshawks, while greater differentiation was observed between temporally separated populations. Consistent with this pattern, clustering supported K&#x2009;=&#x2009;2 as the primary level of genetic structure, separating the contemporary urban and surrounding populations from the earlier surrounding and rural populations. Given the limited marker set and sample sizes, these findings are interpreted as broad-scale patterns rather than definitive evidence of fine-scale population structure. Further studies using larger sample sizes and genome-wide markers are needed to resolve population connectivity and the longer-term genetic effects of urbanization.

Astur gentilis

Assessment of Genetic Diversity and Population Structure on Azadirachta indica A. Juss. in an Urban Metropolitan: Ahmedabad, India.

Azadirachta indica (A. indica) A. Juss., commonly known as Neem, is a valuable multipurpose tree with profound medicinal properties and socioeconomic importance, widely recognized since ancient Ayurvedic times. Despite its prominence, knowledge about its genetic diversity within the metropolitan area of Ahmedabad is limited. This study marks the first in-depth exploration of the genetic diversity and population structure of A. indica in Ahmedabad. The authenticity of the species was validated through DNA barcoding, and a Geographical Information System (GIS) was used to collect the samples. A total of 35 A. indica accessions were analyzed using five Inter Simple Sequence Repeat (ISSR) primers. Genetic diversity and population structure were evaluated using Inter Simple Sequence Repeat (ISSR) markers through polymorphism assessment, clustering, ordination, and Bayesian population structure analyses. ISSRs revealed a high level of polymorphism (75.66%), indicating substantial genetic variability among accessions. An analysis of genetic diversity indices revealed low to moderate diversity (Hs&#x2009;=&#x2009;0.14, Ht&#x2009;=&#x2009;0.217, I&#x2009;=&#x2009;0.217). Analysis of Molecular Variance (AMOVA) analysis depicted 81% variation within the population and 19% among the population. Low to moderate genetic differentiation (Gst&#x2009;=&#x2009;0.319) and moderate gene flow (Nm&#x2009;=&#x2009;1.06) indicated that urban development has not hindered gene flow among populations. Mantel's test revealed a weak but significant correlation between genetic and geographic distances, suggesting limited isolation by distance. The estimated &#x394;K using STRUCTURE exhibited two subpopulations, representing two gene pools for A. indica accessions (K&#x2009;=&#x2009;2). Collectively, these patterns indicate that urbanization has not severely disrupted genetic connectivity in A. indica, reflecting its resilience and adaptive potential in a metropolitan environment. These findings provide pivotal knowledge for further understanding the genetic diversity and population structure of A. indica in one of the fastest-growing cities in India, which can be utilized for new breeding programmes, sustainable development and future conservation strategies around the globe.

India

Characterizing the genetic diversity and population structure of Plasmodium knowlesi in Aceh Province, Indonesia.

As in other parts of Southeast Asia, efforts to achieve or sustain malaria elimination in Indonesia have been threatened by the emergence of human infection with the primate species P. knowlesi. To understand the transmission dynamics of this species, investigation of P. knowlesi genetic diversity and population structure is needed. A molecular surveillance study was conducted in two phases between June 2014 and September 2018 at five primary health facilities in Aceh Province, Indonesia, an area nearing malaria elimination. Dried blood spot samples were collected from patients presenting with suspected malaria and testing positive for malaria by microscopy. PCR was performed for molecular confirmation and species identification. Forty-six samples were confirmed to be P. knowlesi, of which 41 were amplified with genotyping targeting ten known P. knowlesi microsatellite markers. For samples within a site, nearly all (9 of 10 loci) or all loci were polymorphic. Across sites, multiple identical haplotypes were observed, though linkage distribution in the population was low (index of association (IAS)&#x2009;=&#x2009;0.008). The parasite population was indicative of low diversity (expected heterozygosity [HE] =&#x2009; 0.63) and low complexity demonstrated by 92.7% monoclonal infections, a mean multiplicity of infection of 1.06, and a mean within-host infection fixation index (FST) of 0.05. Principal coordinate and neighbour-joining tree analyses indicated that P. knowlesi strains from Aceh were distinct from those reported in Malaysia. In a near-elimination setting in Indonesia, we demonstrate the first evidence that P. knowlesi strains were minimally diverse and were genetically distinct from Malaysian strains, suggesting highly localized transmission and limited connectivity to Malaysia. Ongoing genetic surveillance of P. knowlesi in Indonesia can inform tracking and planning of malaria control and elimination efforts.

Plasmodium knowlesi

Morphological characterization, genetic diversity and population structure of the rice blast pathogen Magnaporthe oryzae in Northeast India.

The blast pathogen, Magnaporthe oryzae, is one of the most destructive fungal pathogens of rice worldwide, yet its morphological features, genetic diversity and population structure in Northeast India remain poorly understood. In this study, twenty&#x2012;two M. oryzae isolates collected from eight states of Northeast India were characterized using morphological, molecular, and population genetic analyses. Morphological characterization revealed whitish to greyish&#x2012;white mycelia with sparse sporulation and colony diameters ranged from 36 to 90&#xa0;mm, classifying the isolates into 14 fast and 8 slow&#x2012;growing groups. Whole genome sequencing was performed to enable both ITS&#x2012;based identification and SSR locus mining from the assembled genomes. Molecular identification using ITS rDNA sequences confirmed all isolates as M. oryzae, with 95.5-100% similarity. Phylogenetic analysis grouped the isolates into two major clades and identified seven ITS sequence types (GenBank Accessions: PX273287-PX273293). Genetic diversity assessed using 30 SSR markers revealed substantial polymorphism, with 1-7 alleles per locus and polymorphism information content (PIC) values ranging from 0.00 to 0.81. Heatmap clustering, dendrogram analysis, and distance metrics consistently identified two major genetic groups, with some isolates forming nearly identical clusters and others showing moderate divergence. Principal Component Analysis (PCA) and Principal Coordinates Analysis (PCoA) accounted for 87.8% of the total variance (PC1 and PC2 accounted for 54.4% and 33.4% respectively of the total variance) and revealed distinct outliers. Analysis of Molecular Variance (AMOVA) attributed 80% of the total genetic variation to differences among populations while only 20% was attributed to within population differences highlighting significant inter&#x2012;population divergence and clonal population structure. The study revealed substantial morphological and genetic diversity among M. oryzae populations in Northeast India, underscoring the need for region&#x2012;specific disease management strategies.

India

Mitochondrial genome-derived microsatellites reveal genetic diversity and population structure in Callery pear populations.

Callery pear (Pyrus calleryana Decne.; PC) possesses many desirable characteristics valued in managed landscapes. This has driven the release of numerous cultivars, including both hybrids and selections derived from native populations. The extensive planting of PC cultivars in managed areas has contributed to the widespread occurrence of invasive individuals across a broad range of habitats in the eastern United States (US). Self-incompatibility, tolerance to various environmental conditions, pathogen and pest resistance, intraspecific hybridization among the cultivars, possible interspecific hybridization with other Pyrus species, and seed dispersal by various vertebrates have contributed to the spread and persistence of PC across diverse environments. Because effective and environmentally appropriate management options remain limited, improved understanding of PC genetics may help inform management strategies. Previous studies have characterized PC diversity using nuclear genomic short sequence repeats (gSSRs), however, neither a mitochondrial genome resource nor mitochondrial short sequence repeats (mtSSRs) have been developed for this purpose. Here, we assembled a mitochondrial genome of 485,892 bp and used five mtSSRs to characterize mitochondrial&#xa0;diversity and population structure among accessions from the species' native range in Asia (n&#x2009;=&#x2009;72), southeastern US escapees (SNesc; n&#x2009;=&#x2009;90), Tennessee escapees (TNesc; n&#x2009;=&#x2009;90), and US-released commercial cultivars (UScult; n&#x2009;=&#x2009;69 representing 14 unique cultivars). We found a high genetic diversity (He&#x2009;=&#x2009;0.728) and evidence of genetic structure in PC. In distance-based and multivariate analyses, UScult occupied an intermediate position between the Asian populations and the US escapees. The observed mitochondrial diversity among samples assigned to PC cultivars is consistent with a complex genetic landscape and may reflect distinct maternal lineages, cultivar-labeling or record-keeping discrepancies, and/or technical variation. This study underscores the need for broader genomic investigations using authenticated cultivar reference material and high-resolution nuclear markers to resolve cultivar ancestry, validate true-to-name identity, and inform species management.

Genetic Variation

Genetic Diversity and Population Structure of Zambian Indigenous Cattle.

A study was conducted to determine the genetic diversity of Zambian indigenous cattle using microsatellites. In Zambia, cattle provide draft power, food, manure and generate income. DNA extraction followed the Qiagen protocol, and Arlequin V3.0 was used for data analysis. 72 unrelated animals from three regions, Eastern (Angoni), Southern (Tonga) and Western (Barotse), were sampled. 315 alleles observed were higher in TGLA 263 (106&#xa0;bp) with 0.861, 0.824 and 0.753, BMS650 (160&#xa0;bp) with 0.710 and SPS 115 (248&#xa0;bp) with 0.581, 0.710 and 0.794 for Angoni, Tonga and Barotse, respectively. Effective allele frequency was 4.521 &#xb1; 0.351, 4.246 &#xb1; 0.299 and 3.888 &#xb1; 0.289 for Angoni, Tonga and Barotse, respectively. Global deficit of heterozygotes across populations (Fit) amounted to 4.2%. Overall mean deficit of heterozygotes (Fis = 1%), genetic differentiation among breeds (Fst = 3.2%),, and genetic flow between populations (Nm = 11.3) ranged from RM 067 (40.564) to BLI (3.016). Analysis of molecular variance revealed 2.7% genetic variation among populations and 97.3% within the cattle population, with a mean genetic diversity of 0.753. Structure analysis (PCoA) demonstrated the presence of two subpopulations in which all three populations are represented and these two groups showed evidence of substructuring. In the Bayesian analysis, Tonga and Barotse populations were clustered together, while the Angoni were separated from the rest of the populations in K = 2. There was no evidence of panmixia and linkage equilibrium; the VD (9.153) value is greater than L (5.929), indicating that the population was in equilibrium. This study presents a comprehensive genetic characterisation of indigenous cattle in Zambia, which is important for further studies.

Animals

The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup.

Polygenic risk scores (PRSs) depend on genetic ancestry due to differences in allele frequencies between ancestral populations. This leads to implementation challenges in diverse populations. We propose a framework to calibrate PRS based on ancestral makeup. We define a metric called "expected PRS" (ePRS), the expected value of a PRS based on one's global or local admixture patterns. We further define the "residual PRS" (rPRS), measuring the deviation of the PRS from the ePRS. Simulation studies confirm that it suffices to adjust for ePRS to obtain nearly unbiased estimates of the PRS-outcome association without further adjusting for PCs. Using the TOPMed dataset, the estimated effect size of the rPRS adjusting for the ePRS is similar to the estimated effect of the PRS adjusting for genetic PCs. Similarly, we applied the ePRS framework to six cardiovascular-related traits in the All of Us dataset, and the results are consistent with those from the TOPMed analysis. The ePRS framework can protect from population stratification in association analysis and provide an equitable strategy to quantify genetic risk across diverse populations.

Journal Article