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At least 19 recordsLinked to original sources

Local ancestry inference identifies robust evidence of selection in Neolithic Europe.

During the European Neolithic, migrating Anatolian farmers admixed with local hunter-gatherers, coinciding with major shifts in diet, environment, and lifestyle that imposed strong selective pressures. Local ancestry inference is widely used to detect selection following admixture, but most methods were developed and validated on present-day populations. Their performance in ancient DNA - where reference panels are smaller, data are sparser, and admixture is more ancient - remains unresolved. We benchmark eight local ancestry inference methods on 176 imputed Neolithic genomes. While individual-level ancestry estimates are highly correlated across methods, inferred tract lengths and admixture time estimates vary by an order of magnitude. Overall, we recommend Gnomix or RFMix for general use. We also investigated our ability to detect natural selection using LAI. Integrating results across methods and replicating across methods and in two independent datasets (n=378 and 1,121) we identify a robust ancestry deviation at FADS1/2, consistent with adaptation on metabolism. We also identify IRAK4 (innate immunity) as a candidate locus, but with less consistent signal across methods. Finally, we replicate previous reports of excess hunter-gatherer ancestry at the HLA, but these results are inconsistent across methods and suggest that they may be affected by bias in local ancestry inference. Our findings demonstrate that while local ancestry inference recovers biologically meaningful signals in ancient genomes, results can be sensitive to the methods used for inference, particularly in complex regions like the HLA. Method choice critically influences inferred ancestry patterns and selection signals, underscoring the importance of multi-method validation.

Journal Article

Local Ancestry at the Major Histocompatibility Complex Region is Not a Major Contributor to Disease Heterogeneity in a Multiethnic Lupus Cohort.

OBJECTIVE: Systemic lupus erythematosus (SLE) is an autoimmune disease resulting in debilitating clinical manifestations that vary in severity by race and ethnicity with a disproportionate burden in African American, Mestizo, and Asian populations compared with populations of European descent. Differences in global and local genetic ancestry may shed light on the underlying mechanisms contributing to these disparities, including increased prevalence of lupus nephritis, younger age of symptom onset, and presence of autoantibodies. METHODS: A total of 1,139 European, African American, and Mestizos patients with SLE were genotyped using the Affymetrix LAT1 World array. Global ancestry proportions were estimated using ADMIXTURE, and local ancestry was estimated using RFMIXv2.0. We investigated associations between lupus nephritis, age at onset, and autoantibody status with both global and local ancestry proportions within the Major Histocompatibility Complex region. RESULTS: Our results showed small effect sizes that did not meet the threshold for statistical significance for global or local ancestry proportions in either African American or Mestizo patients with SLE who presented with the clinical manifestations of interest compared with those who did not. CONCLUSION: These findings suggest that local genetic ancestry within the Major Histocompatibility Complex region is not a major contributor to these SLE manifestations among patients with SLE from admixed populations.

Humans

Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.

The broader application of polygenic risk score (PRS) is hindered by the limited transferability of PRS developed in Europeans to non-European populations. While many statistical methods have been developed to improve the performance of PRS in non-European populations, most of them focused on discrete genetic ancestry clusters and did not consider admixed individuals. Admixed individuals pose a unique challenge for PRS calculation due to the complexity of local ancestry and cross-ancestry effect sizes. Here, we present a statistical method called SDPR_admix for calculating PRS in admixed individuals. SDPR_admix characterizes the joint distribution of the effect sizes of a genetic variant with two ancestries to be both zero, ancestry enriched, or shared with correlation. SDPR_admix outperformed other methods in simulations and improved the prediction of real traits in European-African admixed individuals in UK Biobank when trained on the Population Architecture using Genomics and Epidemiology (PAGE) dataset (N = 13,000). Deployment of SDPR_admix on All of Us (N = 52,000) further increased the prediction accuracy by approximately 5-fold on average compared with training on PAGE. This enhancement was achieved with manageable computational time and cost, demonstrating the feasibility of training PRS models on large-scale All of Us data. We provided several examples demonstrating that both ancestral-enriched and shared effects, as included in the SDPR_admix prediction model, are helpful for improving polygenic prediction in admixed populations. We also applied SDPR_admix to construct PRS for admixed Americans with mixture of European and Amerindigenous ancestries and showed that SDPR_admix overall outperformed other methods.

Humans

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.

Animals

Tractor workflow: a scalable Nextflow framework for local ancestry-aware genome-wide association studies.

MOTIVATION: The routine exclusion of admixed individuals from traditional genome-wide association studies (GWAS) due to concerns about spurious associations has limited multi-ancestry genetic discovery. Tractor addresses this issue by incorporating local ancestry into association testing, enabling the identification of ancestry-enriched signals and generating ancestry-specific summary statistics. However, adoption has been constrained by the complexity of prerequisite steps, including phasing and local ancestry inference, which require substantial bioinformatics expertise and introduce key analytical decision points. RESULTS: We developed a scalable, automated Nextflow workflow that integrates phasing, local ancestry inference, and Tractor association testing into a reproducible end-to-end pipeline. To demonstrate its utility, we applied the workflow to 32 blood biomarkers in 6245 two-way African-European admixed individuals from the UK Biobank. This pipeline performed efficiently at scale, replicating known associations and uncovering key ancestry-specific loci. These associations were largely driven by variants present on African ancestral tracts but absent from European tracts, underscoring the value of local ancestry-aware methods in uncovering previously masked genetic signals. AVAILABILITY AND IMPLEMENTATION: The workflow is modular, customizable, and compatible with commonly used phasing and local ancestry tools, minimizing manual intervention while preserving analytical flexibility. By lowering technical barriers to implementation, this framework facilitates broader adoption of local ancestry-aware GWAS, paving the way for expanded genetic discovery.

Humans

Tractor Workflow Pipeline: A Scalable Nextflow Framework for Local Ancestry-Aware Genome-Wide Association Studies.

The routine exclusion of admixed individuals from traditional Genome-Wide Association Studies (GWAS) due to concerns about spurious associations has hindered genetic analyses involving multiple ancestries. Tractor GWAS addresses this issue by incorporating local ancestry into its analysis, empowering identification of ancestry-enriched hits and generating ancestry-specific summary statistics. However, Tractor requires accurate genomic phasing and local ancestry inference as prerequisite steps, which requires additional bioinformatics expertise and decision points regarding reference panel setup. To streamline, harmonize, and automate this process, we present a scalable Nextflow workflow that integrates all necessary steps, minimizing the need for manual intervention while remaining modular and customizable. The workflow supports multiple commonly used tools and offers flexibility in how Tractor is implemented. To demonstrate its utility, we applied this pipeline to analyze 32 blood biomarkers in 6,245 two-way AFR-EUR admixed individuals from the UK Biobank. This pipeline ran efficiently at scale, replicated known associations, and identified novel ancestry-specific loci. These novel associations were largely driven by variants present on African ancestral tracts but absent from European tracts, underscoring the value of local ancestry-aware methods in uncovering previously missed genetic signals. By enabling the efficient analysis of admixed individuals, our workflow facilitates Tractor use, paving the way for more broader genetic discovery.

Journal Article

Idiopathic pulmonary fibrosis risk loci in East Asian populations mirror those of European populations.

RATIONALE: Common and rare variants that are associated with the risk of developing idiopathic pulmonary fibrosis (IPF) have been identified predominantly in European ancestry populations. OBJECTIVES: To better understand the genetic variants that contribute to IPF in individuals with Asian ancestry, we conducted a genome-wide association study of IPF in East Asian populations. METHODS: We included 1026 patients with IPF and compared them to 1723 unaffected controls of Japanese and Korean ancestry. Genome-wide association analysis was conducted in the Japanese and Korean ancestry cohorts separately and combined using meta-analysis. Restricted maximum likelihood was used to estimate the SNP-based heritability and local ancestry of chromosome 11 was inferred for each subject. MEASUREMENTS AND MAIN RESULTS: We identified loci on chromosomes 4 (FAM13A; rs7690839), 5 (TERT; rs7734992), 6 (DSP; rs2076295), and 11 (MUC5B; rs35705950) that were significantly associated with risk of IPF. Importantly, the sentinel variants in each of these loci are the same as, or in strong linkage disequilibrium with, the risk variants that have been observed in studies of European ancestry populations. In aggregate, common variants (not including the MUC5B promoter variant) account for approximately 25% of the risk of developing IPF in these East Asian ancestry cohorts. Moreover, local ancestry analysis indicates that the presence of MUC5B promoter variant in the East Asian population is not a result of admixture with European ancestry populations. CONCLUSIONS: We conclude that the IPF risk loci in East Asian populations are shared with those of European ancestry populations, although their risk allele frequencies and effect sizes differ. These findings indicate shared genetic risk factors of IPF across ancestries.

Aged

Large-scale admixture mapping in the All of Us Research Program improves the characterization of cross-population phenotypic differences.

Admixed individuals have largely been understudied in medical research due to their complex genetic ancestries. However, the consideration of admixture can help identify ancestry-enriched genetic associations, delineating some of the genetic underpinnings of cross-population phenotypic variation. To this end, we performed local ancestry inference within the All of Us Research Program to identify individuals with recent admixture between African (AFR) and European (EUR) populations (N=48,921). We identified evidence of local AFR ancestry enrichment at the HLA locus, suggestive of putative selection since admixture. Furthermore, we performed the largest admixture mapping (ADM) efforts in AFR-EUR Admixed individuals for 22 traits, identifying 71 associations between inferred local AFR ancestries and a trait. Variants from published GWAS could only account for 18 (25%) of the ADM associations, highlighting novel loci where ancestral haplotypes explained some phenotypic variation. Previous studies likely have not identified these loci due to the low availability of high-powered GWAS in populations genetically similar to AFR. One such loci was 9q21.33, associated with 1.4-fold risk of end-stage kidney disease (ESKD) for carriers of inferred local AFR ancestries at the region. This locus contains the gene SLC28A3, which has previously been linked to kidney function but has never been associated with cross-population ESKD prevalence differences. Together, our results expand upon the existing literature on phenotypic differences between populations, highlighting loci where genetic ancestries play a critical role in the genetic architecture of disease.

Journal Article

The Landscape of Genomic and Socioeconomic Variables in Patients with Colorectal Cancer Based on Genetic Ancestry.

BACKGROUND: Despite differences in tumor alterations across genetic ancestries, investigations of the colorectal cancer molecular landscape have used self-reported ethnicity instead of genetic ancestry. METHODS: We used tumor and matched normal whole-exome sequencing data from 16,388 patients with stage I to IV colorectal cancer to investigate colorectal cancer's germline and somatic molecular landscape and the potential influence of socioeconomic factors (Distressed Communities Index, DCI) across diverse genetic ancestries. Genetic ancestry determined via supervised local ancestry inference included African (AFR, N = 1,697), Native American (AMR, N = 1,291), East Asian (EAS, N = 2,247), European (EUR, N = 9,726), Levantine Middle Eastern (LME, N = 1,192), and South Asian (SAS, N = 184). RESULTS: Microsatellite instability (MSI) was the most common form of hypermutation (80.8%), higher in the EUR genetic ancestry than in the AFR, AMR, and EAS genetic ancestry. Among germline findings, positive results were most common in high-penetrance genes associated with Lynch syndrome. Enrichment patterns included MLH1 (SAS) and PMS2 (AFR). There were significant differences in the frequency of driver mutations in APC, BRAF, KRAS, TP53, and PIK3CA between the EUR and other ancestry groups in both MSI and microsatellite stable tumors. Mutational signatures suggested enrichment of reactive oxygen species and POLE in AFR, colibactin in EAS, and aflatoxin and NTHL1 in SAS. DCI scores differed by ancestry (higher distress in AFR/AMR than in EUR), but driver mutation frequencies did not vary across DCI quintiles. CONCLUSIONS: Genetic ancestry shapes hereditary risk, tumor biology, and environmental exposures. IMPACT: These findings suggest that incorporating ancestry into screening, trials, and precision oncology may improve equity, though outcome-linked prospective studies and implementation research are warranted.

Aged

Genetic analysis in African ancestry populations reveals genetic contributors to lung cancer susceptibility.

Striking disparities in lung cancer exist, with Black/African American individuals disproportionately affected by lung cancer, yet the genetic architecture in African ancestry individuals is poorly understood. We aimed to address this by performing a comprehensive genetic association study of lung cancer, incorporating local ancestry, across 6,490 African ancestry individuals (2,390 individuals with lung cancer and 4,100 control subjects). We identified a single genome-wide significant (p < 5 &#xd7; 10-8) locus, 15q25.1 (lead SNP rs17486278, OR [95% CI] = 1.34 [1.23-1.45], p = 4.52 &#xd7; 10-12), that has consistently shown a strong association with lung cancer across populations. Additionally, we identified nine suggestive (p < 1 &#xd7; 10-6) loci. Four of these loci (3p12.1, 8q22.2, 14q11.2, and 18q22.3) have no prior reported associations with lung cancer. We performed a multi-ancestry lung cancer meta-analysis using prior large-scale summary statistics from European and Asian ancestry populations, incorporating our African ancestry results. The meta-analysis identified 17 genome-wide significant loci, including an association with locus 4q35.2 (p = 1.22 &#xd7; 10-8), a genomic region that has been previously linked to forced expiratory volume. Genome-wide SNP-based heritability for lung cancer was 16% among African ancestry individuals. Follow-up in silico functional analyses identified genetically regulated gene expression (GReX) of nine genes (AC012184.3, ADK, CCDC12, CHRNA3, EML4, PSMA4, SNRNP200, TMEM50A, and ZYG11A) associated with lung cancer risk and biological pathways relevant to cancer and lung function. Cumulatively, these findings further elucidate the genetic architecture of lung cancer in African ancestry individuals, confirming prior loci and revealing new loci.

Female

An archaic reference-free method to jointly infer Neanderthal and Denisovan introgressed segments in modern human genomes.

Admixture between populations is a common feature of human history. Admixture events introduce new genetic variation that can fuel evolution. Characterizing the significance of admixture events on the evolution of populations across various species is of great interest to evolutionary geneticists. Local Ancestry Inference (LAI) methods infer genetic ancestry of an individual at a particular chromosomal location. Certain methods specialize in detecting archaic introgression, which consists of interbreeding between modern and archaic humans like Neanderthals and Denisovans. Most current LAI methods allow the detection of a single archaic ancestry, and post-processing may distinguish between multiple waves of introgression. These methods vary in how they choose archaic or modern reference genomes for the inference. Here, we present a new HMM-based method (DAIseg), which has the advantage of simultaneously distinguishing between multiple waves of ancient and recent admixture, using only modern human reference genomes. Simulations demonstrate that DAIseg achieves higher overall performance than state-of-the-art methods. We also apply DAIseg to Papuan populations to jointly detect Denisovan and Neanderthal introgressed segments, and identify a higher number of archaic segments than previous methods. Analysis of inferred introgressed segments, shows that we can identify evidence for two Denisovan introgression events in Papuans. Overall, on top of being able to deal with both Archaic and recent admixture, DAIseg provides a more principled approach for detecting and classifying Denisovan and Neanderthal segments which will improve downstream analysis of introgressed segments to infer the impact of archaic introgression in humans.

Denisovan

Carrying APOL1 G1 allele is associated with cardiovascular complications during COVID-19 in an admixed population.

BACKGROUND: The APOL1 G1 and G2 alleles were selected in the Sub-Saharan African population by conferring resistance to trypanosome infection. However, these alleles are associated with kidney diseases, and their role in cardiovascular complications remains uncertain. A second hit mediated by an inflammatory state is necessary for APOL1-mediated phenotypes. Thus, this cross-sectional study investigates the association of APOL1 alleles with COVID-19 outcomes such as cardiovascular complications and kidney injury in an admixed population. Whole-genome sequencing was performed for 485 patients with different outcomes from a Biobank in Southern Brazil. RESULTS: COVID-19 individuals presented median age of 51 years, 281 were hospitalized, and 10.9% had CKD previous to the infection. Global ancestry inference revealed 12.8% of African ancestry. The G1 allele frequency was 2.7% and G2 allele was 1.2%. Local ancestry inference evidenced African ancestry in the locus of APOL1 alleles. The G1 allele frequency was higher among patients with severe outcomes. The presence of this allele was associated with kidney injury (OR = 2.78; 95% CI = 1.04-7.42; p = 0.041) using a minimally adjusted model and cardiovascular complications with a minimally (OR = 4.61; 95% CI = 1.61-13.19; p = 0.004) and fully adjusted model (OR = 4.59; 95% CI = 1.41-14.96; p = 0.011). Four individuals carried two alleles (three G1/G1 and one G1/G2) and three of them progressed to severe COVID-19 developing kidney injury. CONCLUSION: APOL1 risk alleles are present in the Brazilian population due to genetic admixture and the G1 allele was associated with COVID-19 outcomes.

Humans

A genealogy-based approach for revealing ancestry-specific structures in admixed populations.

Elucidating ancestry-specific structures in admixed populations is crucial for comprehending population history and mitigating confounding effects in genome-wide association studies. Existing methods to reveal the ancestry-specific structures generally rely on frequency-based estimates of genetic relationship matrix (GRM) among admixed individuals after masking segments from ancestry components not being targeted for investigation. However, these approaches disregard linkage information between markers, potentially limiting their resolution in revealing structure within an ancestry component. We introduce ancestry-specific expected GRM (as-eGRM), a novel framework for estimating the relatedness within ancestry components between admixed individuals. The key design of as-eGRM consists of defining ancestry-specific pairwise relatedness between individuals based on genealogical trees encoded in the ancestral recombination graph (ARG) and local ancestry calls and then computing the expectation of the ancestry-specific relatedness across the genome. Comprehensive evaluations using both simulated stepping-stone models of population structure and empirical datasets based on three-way admixed Latino cohorts showed that analysis based on as-eGRM robustly outperforms existing methods in revealing the structure in admixed populations with diverse demographic histories, which in turn improves the robustness against confounding due to population structure in association testing.

Humans

Concordance and divergence between self-declared ancestry and genome-derived ancestry composition in 10&#x2009;250 participants from the HostSeq cohort.

Accurate characterization of human genetic diversity is essential for robust genomic analyses. We compared self-declared and genome-derived ancestry composition in 10&#x2009;250 participants from the pan-Canadian HostSeq cohort using whole-genome sequencing data. Global and local ancestry were inferred at the continental super-population level using the alignment-free ntRoot algorithm and evaluated through both hard-label concordance and multiclass Brier score analyses incorporating full ancestry fraction profiles. Strong agreement was observed among East Asian / Pacific Islander (mean Brier score&#xa0;&#xb1;&#xa0;SD: 0.012&#xa0;&#xb1;&#xa0;0.052), Black (0.013&#xa0;&#xb1;&#xa0;0.042), White (0.055&#xa0;&#xb1;&#xa0;0.022), and South Asian (0.057&#xa0;&#xb1;&#xa0;0.098) participants, whereas higher scores among Hispanic (0.083&#xa0;&#xb1;&#xa0;0.060) and Middle Eastern or Central Asian (0.122&#xa0;&#xb1;&#xa0;0.034) participants reflected broader and more admixed ancestry profiles. Principal component analysis of centered log-ratio-transformed ancestry fractions revealed overlapping ancestry gradients rather than discrete continental groupings. Entropy- and dominance margin-based analyses further indicated that many discordant cases reflected diffuse admixture rather than categorical mismatch. Together, these findings support representing ancestry as a continuous compositional spectrum rather than discrete categories. Genome-derived ancestry estimates describe patterns of genomic variation and should not be interpreted as proxies for race.

Humans

Nested Admixture During and After the Trans-Atlantic Slave Trade on the Island of S&#xe3;o Tom&#xe9;.

Human genetic admixture, involving the contact between two or more previously isolated populations, can be a complex process influenced by social dynamics. In this study, we aim to reconstruct complex admixture histories in S&#xe3;o Tom&#xe9;, an island in the Gulf of Guinea where the Portuguese established one of the first plantation-based slave societies. Since the 15th century, migration waves from Africa and Europe, slavery, marooning, and indentured labour led to profound demographic shifts and social stratification on the island. Examining 2.5 million SNPs newly genotyped in 96 S&#xe3;o Tom&#xe9;ans, we observed patterns of genetic differentiation that were more complex than those of other populations descended from enslaved Africans on either side of the Atlantic. Using local ancestry inference and Identical-by-Descent methods, we identified five genetic clusters in S&#xe3;o Tom&#xe9; and reconstructed shared ancestries between each cluster and 70 African and European population samples, including an extensive sample from the Cabo Verde archipelago. Our findings align with historical records, retracing the major slave trade routes and labour-driven migrations after the abolition of slavery. We also identified gene flow between recently admixed groups that were previously isolated on the island. We call this process, creating multiple layers of genetic ancestry in admixed genomes, nested admixture. We suggest that changing social structures in S&#xe3;o Tom&#xe9; transformed the genetic structure of its population and influenced the admixture process. This study demonstrates how successive admixture and isolation events during and after the Trans-Atlantic Slave Trade shaped extant genetic diversity patterns at local scale in Africa.

Humans

Population-scale disease-associated tandem repeat analysis reveals locus and ancestry-specific insights.

Tandem repeat (TR) expansions, including short TRs (motifs &#x2264;6&#x2009;bp) and variable number TRs (motifs >6&#x2009;bp), underlie many monogenic disorders, with variable length and sequence influencing pathogenicity, penetrance, severity, and onset. Accurate genotype-phenotype correlation and disease prevalence estimation require characterization beyond repeat length. Here we present a population-scale analysis of 66 disease-associated TR loci using long-read assemblies from 2530 diverse haplotypes from 1265 unaffected donors. Integrating repeat length, motif composition, local ancestry, linkage disequilibrium, and phylogenetic analyses, we reveal extensive locus-, population-, and allele-specific variation shaping disease risk. Up to 8.5% of individuals carry expansions above established pathogenic thresholds, many containing interrupting motifs or sequence structures that attenuate pathogenicity. After excluding alleles from loci with uncertain disease association, non-pathogenic interrupted expansions, and carrier states inconsistent with inheritance patterns, ~4% carried expansions predicted to confer disease risk, largely at adult-onset loci with reduced penetrance. Ancestry-resolved analyses uncover population-specific TR architectures contributing to epidemiological disparities in repeat expansion disorders. Phylogenetic analyses identify conserved ancestral alleles and loci with recent instability. We describe variable linkage disequilibrium patterns and recombination signatures around specific disease-associated TR loci. Our findings emphasize integrating sequence, ancestry, and evolutionary context to understand the complex landscape of disease-associated TRs.

Humans

Discovery of ancestry-specific variants associated with clopidogrel response among Caribbean Hispanics.

High on-treatment platelet reactivity (HTPR) with clopidogrel predicts ischemic events in adults with coronary artery disease, and while HTPR varies by ethnicity, no genome-wide association study (GWAS) of clopidogrel response has been conducted in Caribbean Hispanics. This study aimed to identify genetic predictors of HTPR in a cohort of 511 Puerto Rican cardiovascular patients treated with clopidogrel, stratified by P2Y12 reaction units (PRU) into responders and non-responders (HTPR). Local ancestry inference (LAI) and traditional GWAS identified variants in the CYP2C19 region associated with HTPR, primarily in individuals with European ancestry. Three variants (OSBPL10 rs1376606, DERL3 rs5030613, RGS6 rs9323567) showed suggestive significance, and a variant in UNC5C was linked to increased HTPR risk. These findings highlight the unique genetic landscape of Caribbean Hispanics and challenge the significance of CYP2C19*2 in predicting clopidogrel response in patients with high non-European ancestry. Further studies are needed to replicate these results in other diverse cohorts.

Journal Article

Genomics and social practices at Mogou and other Gansu sites during prehistoric trans-Eurasian exchange.

Beginning approximately 4,000 years ago, southwest-Asian-originating domesticated crops and livestock began appearing in Gansu, a key crossroads in northwestern China, yet the population dynamics and social practices underlying these historically transformative events in the region have not been fully explored. Despite the adoption of western domesticates, genome sequences of 149 individuals from the large Mogou cemetery and ten other sites in Gansu, dating between 4,700 and 3,000 years ago, revealed migrations within East Asian regions but no detectable evidence of genetic influence from western or central Eurasia, suggesting that early agricultural dispersals may have followed a model distinct from that documented in Europe and Central Asia. The Mogou cemetery represents a continuous community that interacted with surrounding regions but does not exhibit clear matrilocal or patrilocal residential patterns. We found no strong evidence that co-buried individuals represented biological relatives. Non-local ancestry appears to be linked to lower-status burial practices.

Humans