{"id":238186,"date":"2025-05-12T14:29:05","date_gmt":"2025-05-12T14:29:05","guid":{"rendered":"https:\/\/peraltafinancing.com\/anthropology\/mapping-the-genome-of-a-multi-ethnic-nation\/"},"modified":"2025-05-12T14:29:05","modified_gmt":"2025-05-12T14:29:05","slug":"mapping-the-genome-of-a-multi-ethnic-nation","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=238186","title":{"rendered":"Mapping the Genome of a Multi-Ethnic Nation"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div dir=\"auto\">\n<p>In a quiet room humming with server stacks, a genomic dataset from nearly 300,000 Americans is doing something anthropologists have long tried to accomplish: capturing a living mosaic of human ancestry at a scale once unimaginable.<\/p>\n<p><span>The participants belong to the <\/span><em>All of Us<\/em><span> Research Program, an ambitious effort by the National Institutes of Health to create a biomedical database that actually reflects the population of the United States\u2014not just those whose ancestry traces back to Northern Europe.<\/span><\/p>\n<p><span>The result<\/span><span>? A genomic map layered not only with centuries of migrations and admixture, but also with lessons for how ancestry\u2014understood through the language of DNA\u2014shapes and is shaped by human history, cultural geography, and inequality.<\/span><\/p>\n<blockquote>\n<p>\u201cWhat emerges is a complex web of similarity clusters,\u201d notes the study\u2019s senior author I. King Jordan. \u201cThey reflect not just where people come from, but how populations have blended, diverged, and lived together over time.\u201d<\/p>\n<\/blockquote>\n<p>The researchers used principal component analysis (PCA) and a rapid ancestry estimation method called Rye to identify distinct patterns of population structure. This wasn\u2019t simply a technical exercise. Their findings showed clusters of closely related individuals embedded in a much broader tapestry of admixture. Seven major clusters emerged from PCA, but further analysis using another method (UMAP) revealed up to 13 groupings\u2014suggesting layers of population complexity.<\/p>\n<div class=\"captioned-image-container\">\n<figure><a target=\"_blank\" href=\"https:\/\/substackcdn.com\/image\/fetch\/f_auto,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp\" data-component-name=\"Image2ToDOM\" rel=\"\" class=\"image-link image2 is-viewable-img\"><\/p>\n<div class=\"image2-inset\"><picture><source type=\"image\/webp\" srcset=\"https:\/\/substackcdn.com\/image\/fetch\/w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 424w, https:\/\/substackcdn.com\/image\/fetch\/w_848,c_limit,f_webp,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 848w, https:\/\/substackcdn.com\/image\/fetch\/w_1272,c_limit,f_webp,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 1272w, https:\/\/substackcdn.com\/image\/fetch\/w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 1456w\" sizes=\"100vw\"\/><img decoding=\"async\" src=\"https:\/\/substackcdn.com\/image\/fetch\/w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp\" width=\"1456\" height=\"1506\" data-attrs=\"{&quot;src&quot;:&quot;https:\/\/substack-post-media.s3.amazonaws.com\/public\/images\/c567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp&quot;,&quot;srcNoWatermark&quot;:null,&quot;fullscreen&quot;:null,&quot;imageSize&quot;:null,&quot;height&quot;:1506,&quot;width&quot;:1456,&quot;resizeWidth&quot;:null,&quot;bytes&quot;:192716,&quot;alt&quot;:null,&quot;title&quot;:null,&quot;type&quot;:&quot;image\/webp&quot;,&quot;href&quot;:null,&quot;belowTheFold&quot;:false,&quot;topImage&quot;:true,&quot;internalRedirect&quot;:&quot;https:\/\/www.anthropology.net\/i\/163395319?img=https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp&quot;,&quot;isProcessing&quot;:false,&quot;align&quot;:null}\" alt=\"\" srcset=\"https:\/\/substackcdn.com\/image\/fetch\/w_424,c_limit,f_auto,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 424w, https:\/\/substackcdn.com\/image\/fetch\/w_848,c_limit,f_auto,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 848w, https:\/\/substackcdn.com\/image\/fetch\/w_1272,c_limit,f_auto,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 1272w, https:\/\/substackcdn.com\/image\/fetch\/w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc567029e-cbbf-4f1b-b013-b631cfaa967d_1988x2056.webp 1456w\" sizes=\"100vw\" fetchpriority=\"high\" class=\"sizing-normal\"\/><\/picture><\/div>\n<p><\/a><figcaption class=\"image-caption\"><span>Genomic PCA with All of Us participants shown in gray and global reference population samples color-coded as shown in the key. Left panels show PC1 versus PC2 comparisons, and right panels show PC1 versus PC3 comparisons, with the percent of variance explained by each PC shown. <\/span><strong>b<\/strong><span> Genetic ancestry proportions for All of Us participants stratified by the genetic similarity groups shown in Fig. <\/span><a href=\"https:\/\/www.nature.com\/articles\/s41467-025-59351-8#Fig1\" rel=\"\">1c<\/a><span>. Average ancestry proportions are shown above each group, and numbers of participants are shown below each group. The remaining participants are individuals who did not fall into a dense PCA cluster.<\/span><\/figcaption><\/figure>\n<\/div>\n<p>While the majority of participants had significant European ancestry (~66.4%), almost 20% showed African ancestry, and over 13% carried lineages from Indigenous American, South Asian, East Asian, or West Asian origins.<\/p>\n<blockquote>\n<p>\u201cWe\u2019re not just seeing neat little bins of ancestry,\u201d said Jordan. \u201cWe\u2019re seeing gradients, overlaps, mosaics\u2014and that\u2019s important because this is how real human populations exist.\u201d<\/p>\n<\/blockquote>\n<p>This granular structure offers more than genealogical trivia. It challenges how researchers traditionally categorize populations. Many of these ancestry components do not align cleanly with socially constructed racial or ethnic identities, exposing the limits of fixed labels in science, medicine, and society.<\/p>\n<p>Genetic ancestry doesn\u2019t just map where someone\u2019s relatives lived\u2014it can also hint at when they lived and migrated. The study revealed a striking generational pattern: younger Americans tend to be more genetically admixed than their elders.<\/p>\n<p>In other words, the country\u2019s population isn\u2019t just becoming more diverse\u2014it\u2019s becoming more genomically entangled.<\/p>\n<p>This has implications beyond genomics. It speaks to cultural fluidity, the erosion of categorical boundaries, and the demographic reality that human identity has always been more braided than boxed.<\/p>\n<p>The research team also mapped these ancestry components across all 50 states and Puerto Rico. Predictably, African ancestry is most concentrated in the southeastern United States, while Indigenous American ancestry is more prominent in the Southwest and in California. European ancestry dominates throughout but shows the highest concentration in the northern Midwest and New England.<\/p>\n<p>Importantly, the northeast corridor and Florida showed higher levels of admixture, highlighting urban regions as mixing zones for human histories.<\/p>\n<blockquote>\n<p>\u201cThis isn\u2019t just about ancestry,\u201d explains co-author Robert Meller. \u201cIt\u2019s about how geography, migration, and policy have shaped\u2014and continue to shape\u2014what it means to be American.\u201d<\/p>\n<\/blockquote>\n<p>Although typically the domain of ancient DNA, this study demonstrates how archaeological thinking\u2014about movement, kinship, and cultural entanglement\u2014can be applied to contemporary populations.<\/p>\n<p>It also underscores the limitations of using a Eurocentric reference framework. For about 3% of the participants, especially those with South or West Asian ancestry, ancestry estimates were sensitive to the choice of reference populations. This is a call to action: geneticists need to expand and diversify their reference datasets, much like how archaeologists must question whose stories get preserved in the record.<\/p>\n<p>The team is aware of these pitfalls. <\/p>\n<blockquote>\n<p>\u201cReference populations are idealized,\u201d said Jordan. \u201cThey represent snapshots in time, often shaped by modern national boundaries or linguistic identities, which don\u2019t always reflect deeper historical processes.\u201d<\/p>\n<\/blockquote>\n<p>Anthropologists often work with bones, tools, and ancient genomes to tell the story of our species. But here, in the swabbed cheeks and sequenced blood of nearly 300,000 living people, another archive emerges\u2014one that extends deep into the past but remains entirely alive.<\/p>\n<p><span>The <\/span><em>All of Us<\/em><span> cohort is both a mirror and a time capsule. It shows how genetic variation echoes ancient human movements, colonial entanglements, the transatlantic slave trade, Indigenous resilience, and waves of global migration\u2014all the while pointing to the future of a society where genetic boundaries are increasingly hard to draw.<\/span><\/p>\n<p>This project is only the beginning. With every new genome added, the picture sharpens. But so does the need to think critically about how we use ancestry labels, who gets represented in the data, and what stories we choose to tell.<\/p>\n<p>Precision medicine can\u2019t be truly \u201cprecise\u201d if it leaves out large swaths of humanity. This research is a reminder that the diversity of the human story must be matched by the diversity of our science.<\/p>\n<ul>\n<li>\n<p><strong>Abul-Husn, N. S., &amp; Kenny, E. E.<\/strong><span> (2019). Personalized medicine and the power of electronic health records. <\/span><em>Cell, 177<\/em><span>(1), 58\u201369. https:\/\/doi.org\/10.1016\/j.cell.2019.02.039<\/span><\/p>\n<\/li>\n<li>\n<p><strong>Hellenthal, G., et al.<\/strong><span> (2014). A genetic atlas of human admixture history. <\/span><em>Science, 343<\/em><span>(6172), 747\u2013751. https:\/\/doi.org\/10.1126\/science.1243518<\/span><\/p>\n<\/li>\n<li>\n<p><strong>Maples, B. K., et al.<\/strong><span> (2013). RFMix: A discriminative modeling approach for rapid and robust local-ancestry inference. <\/span><em>Am. J. Hum. Genet., 93<\/em><span>(2), 278\u2013288. https:\/\/doi.org\/10.1016\/j.ajhg.2013.06.020<\/span><\/p>\n<\/li>\n<li>\n<p><strong>Bryc, K., et al.<\/strong><span> (2015). The genetic ancestry of African Americans, Latinos, and European Americans across the United States. <\/span><em>Am. J. Hum. Genet., 96<\/em><span>(1), 37\u201353. https:\/\/doi.org\/10.1016\/j.ajhg.2014.11.010<\/span><\/p>\n<\/li>\n<\/ul>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>In a quiet room humming with server stacks, a genomic dataset from nearly 300,000 Americans is doing something anthropologists have long tried to accomplish: capturing a living mosaic of human ancestry at a scale once unimaginable. The participants belong to the All of Us Research Program, an ambitious effort by the National Institutes of Health [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":238187,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11767],"tags":[24289,18357,87842,20171],"dealstore":[],"offerexpiration":[],"class_list":["post-238186","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-anthropology","tag-genome","tag-mapping","tag-multiethnic","tag-nation"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Mapping the Genome of a Multi-Ethnic Nation - Som2ny Network<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fivemor.com\/?p=238186\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Mapping the Genome of a Multi-Ethnic Nation - Som2ny Network\" \/>\n<meta property=\"og:description\" content=\"In a quiet room humming with server stacks, a genomic dataset from nearly 300,000 Americans is doing something anthropologists have long tried to accomplish: capturing a living mosaic of human ancestry at a scale once unimaginable. 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