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A geographic history of human genetic ancestry.

ABSTRACT: Describing the distribution of genetic variation across individuals is a fundamental goal of population genetics. In humans, traditional approaches for describing population genetic variation often rely on discrete genetic ancestry labels, which, despite their utility, can obscure the complex, multifaceted nature of human genetic history. These labels risk oversimplifying ancestry by ignoring its temporal depth and geographic continuity, and may therefore conflate notions of race, ethnicity, geography, and genetic ancestry. Here, we present a method that capitalizes on the rich genealogical information encoded in genomic tree sequences to infer the geographic locations of the shared ancestors of a sample of sequenced individuals. We use this method to infer the geographic history of genetic ancestry of a set of human genomes sampled from Europe, Asia, and Africa, accurately recovering major population movements on those continents. Our findings demonstrate the importance of defining the spatial-temporal context of genetic ancestry to describing human genetic variation and caution against the oversimplified interpretations of genetic data prevalent in contemporary discussions of race and ancestry.

SUBMITTER: Grundler MC

PROVIDER: S-EPMC10996620 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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A geographic history of human genetic ancestry.

Grundler Michael C MC Terhorst Jonathan J Bradburd Gideon S GS

bioRxiv : the preprint server for biology 20240819

Describing the distribution of genetic variation across individuals is a fundamental goal of population genetics. In humans, traditional approaches for describing population genetic variation often rely on discrete genetic ancestry labels, which, despite their utility, can obscure the complex, multi-faceted nature of human genetic history. These labels risk oversimplifying ancestry by ignoring its temporal depth and geographic continuity, and may therefore conflate notions of race, ethnicity, ge ...[more]

PMID: 38585733

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Project description:Individuals of African descent in the United States suffer disproportionately from diseases with a metabolic etiology (obesity, metabolic syndrome, and diabetes), and from the pathological consequences of these disorders (hypertension and cardiovascular disease). Using a combination of genetic/genomic and bioinformatics approaches, we identified a large number of genes that were both differentially expressed between American subjects self-identified to be of either African or European ancestry and that also contained single nucleotide polymorphisms that distinguish distantly related ancestral populations. Several of these genes control the metabolism of simple carbohydrates and are direct targets for the SREBP1, a metabolic transcription factor also differentially expressed between our study populations. These data support the concept of stable patterns of gene transcription unique to a geographic ancestral lineage. The coordinated transcriptional adaptation of carbohydrate metabolism to dietary environmental pressures suggests a genetic and transcriptional mechanism for the disproportionate levels of obesity, diabetes, and cardiovascular disease observed in Americans with African ancestry. Keywords: Ancestry-dependent gene expression, functional genomics, personalized medicine, multi-factoral disease, nutrition, diabetes We utilized a “sample x reference” experimental design strategy in which RNA extracted from human peripheral blood mononuclear cells was hybridized to the microarray slide in the presence of labeled Universal Human Reference RNA (UHRR, Stratagene, LaJolla, CA). A total of 161 subjects were used in this analysis. Briefly, five hundred nanograms of total RNA were used for gene expression profiling following reverse transcription and T-7 polymerase-mediated amplification/labeling with Cyanine-5 CTP. Labeled subject cRNA was co-hybridized to Agilent G4112A Whole Human Genome 44K oligonucleotide arrays with equimolar amounts of Cyanine-3 labeled UHRR. Slides were hybridized, washed, and scanned on an Axon 4000b microarray scanner. The data were processed using GenePix Pro 6 software

Dataset Information

A geographic history of human genetic ancestry.

Publications

A geographic history of human genetic ancestry.

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