Predicting Environmental and Ecological Drivers of Human Population Structure

Predicting Environmental and Ecological Drivers of Human Population Structure

Abstract Landscape, climate, and culture can all structure human populations, but few existing methods are designed to simultaneously disentangle among a large number of variables in explaining genetic patterns. We developed a machine learning method for identifying the variables which best explain...

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Bibliographic Details
Published in:Molecular biology and evolution Vol. 40; no. 5
Main Authors: Pless, Evlyn, Eckburg, Anders M, Henn, Brenna M
Format: Journal Article
Language:English
Published: US Oxford University Press 02-05-2023
Subjects:
Africa, Eastern
Analysis
Animals
Climate
Genes
Genome-Wide Association Study
Genomics
Human Genetics
Human Migration
Humans
Language
Livestock
Machine learning
Methods
Models, Genetic
Physiological aspects
Single nucleotide polymorphisms
Tsetse Flies
Type 2 diabetes
Africa, Eastern
Ethiopia
Tanzania
gene flow
migration
SPRUCE
barriers
random forest
MAPS
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Summary:Abstract Landscape, climate, and culture can all structure human populations, but few existing methods are designed to simultaneously disentangle among a large number of variables in explaining genetic patterns. We developed a machine learning method for identifying the variables which best explain migration rates, as measured by the coalescent-based program MAPS that uses shared identical by descent tracts to infer spatial migration across a region of interest. We applied our method to 30 human populations in eastern Africa with high-density single nucleotide polymorphism array data. The remarkable diversity of ethnicities, languages, and environments in this region offers a unique opportunity to explore the variables that shape migration and genetic structure. We explored more than 20 spatial variables relating to landscape, climate, and presence of tsetse flies. The full model explained ∼40% of the variance in migration rate over the past 56 generations. Precipitation, minimum temperature of the coldest month, and elevation were the variables with the highest impact. Among the three groups of tsetse flies, the most impactful was fusca which transmits livestock trypanosomiasis. We also tested for adaptation to high elevation among Ethiopian populations. We did not identify well-known genes related to high elevation, but we did find signatures of positive selection related to metabolism and disease. We conclude that the environment has influenced the migration and adaptation of human populations in eastern Africa; the remaining variance in structure is likely due in part to cultural or other factors not captured in our model.
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ISSN:0737-4038
1537-1719
DOI:10.1093/molbev/msad094