Dataset Information

UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts.

ABSTRACT: Human populations feature both discrete and continuous patterns of variation. Current analysis approaches struggle to jointly identify these patterns because of modelling assumptions, mathematical constraints, or numerical challenges. Here we apply uniform manifold approximation and projection (UMAP), a non-linear dimension reduction tool, to three well-studied genotype datasets and discover overlooked subpopulations within the American Hispanic population, fine-scale relationships between geography, genotypes, and phenotypes in the UK population, and cryptic structure in the Thousand Genomes Project data. This approach is well-suited to the influx of large and diverse data and opens new lines of inquiry in population-scale datasets.

SUBMITTER: Diaz-Papkovich A

PROVIDER: S-EPMC6853336 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts.

Diaz-Papkovich Alex A Anderson-Trocmé Luke L Ben-Eghan Chief C Gravel Simon S

PLoS genetics 20191101 11

Human populations feature both discrete and continuous patterns of variation. Current analysis approaches struggle to jointly identify these patterns because of modelling assumptions, mathematical constraints, or numerical challenges. Here we apply uniform manifold approximation and projection (UMAP), a non-linear dimension reduction tool, to three well-studied genotype datasets and discover overlooked subpopulations within the American Hispanic population, fine-scale relationships between geogr ...[more]

PMID: 31675358

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Project description:Endangered species are grouped into genetically discrete populations to direct conservation efforts. Mitochondrial control region (mtCR) haplotypes are used to elucidate deep divergences between populations, as compared to nuclear microsatellites that can detect recent structuring. When prior populations are unknown, it is useful to subject microsatellite data to clustering and/or ordination population inference. Olive ridley sea turtles (Lepidochelys olivacea) are the most abundant sea turtle, yet few studies have characterized olive ridley population structure. Recently, clustering results of olive ridleys in the Eastern Tropical Pacific Ocean suggested weak structuring (F ST = 0.02) between Mexico and Central America. We analyzed mtCR haplotypes, new microsatellite genotypes from Costa Rica, and preexisting microsatellite genotypes from olive ridleys across the Eastern Tropical Pacific, to further explore population structuring in this region. We subjected inferred populations to multiple analyses to explore the mechanisms behind their structuring. We found 10 mtCR haplotypes from 60 turtles nesting at three sites in Costa Rica, but did not detect divergence between Costa Rican sites, or between Central America and Mexico. In Costa Rica, clustering suggested one population with no structuring, but ordination suggested four cryptic clusters with moderate structuring (F ST = 0.08, p < .001). Across the Eastern Tropical Pacific, ordination suggested nine cryptic clusters with moderate structuring (F ST = 0.103, p < .001) that largely corresponded to Mexican and Central American populations. All ordination clusters displayed significant internal relatedness relative to global relatedness (p < .001) and contained numerous sibling pairs. This suggests that broadly dispersed family lineages have proliferated in Eastern Tropical Pacific olive ridleys and corroborates previous work showing basin-wide connectivity and shallow population structure in this region. The existence of broadly dispersed kin in Eastern Tropical Pacific olive ridleys has implications for management of olive ridleys in this region, and adds to our understanding of sea turtle ecology and life history, particularly in light of the natal-homing paradigm.

Dataset Information

UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts.

Publications

UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts.

Similar Datasets

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