Genome-wide SNP typing reveals signatures of population history

Current species distributions at high latitudes are the product of expansion from glacial refugia into previously uninhabitable areas at the end of the last glaciation. The traditional view of postglacial colonization is that southern populations expanded their ranges into unoccupied northern territories. Recent findings on mitochondrial DNA (mtDNA) of British small mammals have challenged this simple colonization scenario by demonstrating a more complex genetic turnover in Britain during the Pleistocene–Holocene transition where one mtDNA clade of each species was replaced by another mtDNA clade of the same species. Here, we provide evidence from one of those small mammals, the bank vole ( Clethrionomys glareolus ), that the replacement was genome-wide. Using more than 10 000 autosomal SNPs we found that similar to mtDNA, bank vole genomes in Britain form two (north and south) clusters which admix. Therefore, the genome of the original postglacial colonists (the northern cluster) was probably replaced by another wave of migration from a different continental European population (the southern cluster), and we gained support for this by modelling with approximate Bayesian computation. This finding emphasizes the importance of analysis of genome-wide diversity within species under changing climate in creating opportunities for sophisticated testing of population history scenarios.

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Genome‐wide SNP typing of ancient DNA: Determination of hair and eye color of Bronze Age humans from their skeletal remains

American Journal of Physical Anthropology ◽

10.1002/ajpa.23996 ◽

2020 ◽

Vol 172 (1) ◽

pp. 99-109 ◽

Cited By ~ 1

Author(s):

Nicole Schmidt ◽

Katharina Schücker ◽

Ina Krause ◽

Thilo Dörk ◽

Michael Klintschar ◽

...

Keyword(s):

Bronze Age ◽

Ancient Dna ◽

Skeletal Remains ◽

Eye Color ◽

Snp Typing ◽

Genome Wide

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Genome-wide single nucleotide polymorphisms reveal population history and adaptive divergence in wild guppies

Molecular Ecology ◽

10.1111/j.1365-294x.2010.04528.x ◽

2010 ◽

Vol 19 (5) ◽

pp. 968-984 ◽

Cited By ~ 103

Author(s):

EVA-MARIA WILLING ◽

PAUL BENTZEN ◽

COCK van OOSTERHOUT ◽

MARGARETE HOFFMANN ◽

JOANNE CABLE ◽

...

Keyword(s):

Single Nucleotide Polymorphisms ◽

Population History ◽

Adaptive Divergence ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Genome Wide

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A dynamic 6,000-year genetic history of Eurasia’s Eastern Steppe

10.1101/2020.03.25.008078 ◽

2020 ◽

Cited By ~ 4

Author(s):

Choongwon Jeong ◽

Ke Wang ◽

Shevan Wilkin ◽

William Timothy Treal Taylor ◽

Bryan K. Miller ◽

...

Keyword(s):

Bronze Age ◽

Population History ◽

Complex Interplay ◽

Cultural Changes ◽

Genetic History ◽

Nomadic Pastoralists ◽

Eurasian Steppe ◽

Genome Wide ◽

Genome Wide Data ◽

History Of

SummaryThe Eastern Eurasian Steppe was home to historic empires of nomadic pastoralists, including the Xiongnu and the Mongols. However, little is known about the region’s population history. Here we reveal its dynamic genetic history by analyzing new genome-wide data for 214 ancient individuals spanning 6,000 years. We identify a pastoralist expansion into Mongolia ca. 3000 BCE, and by the Late Bronze Age, Mongolian populations were biogeographically structured into three distinct groups, all practicing dairy pastoralism regardless of ancestry. The Xiongnu emerged from the mixing of these populations and those from surrounding regions. By comparison, the Mongols exhibit much higher Eastern Eurasian ancestry, resembling present-day Mongolic-speaking populations. Our results illuminate the complex interplay between genetic, sociopolitical, and cultural changes on the Eastern Steppe.

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The Multivariate Normal Distribution Framework for Analyzing Association Studies

10.1101/208199 ◽

2017 ◽

Author(s):

Jose A. Lozano ◽

Farhad Hormozdiari ◽

Jong Wha (Joanne) Joo ◽

Buhm Han ◽

Eleazar Eskin

Keyword(s):

Genetic Variants ◽

Statistical Power ◽

Association Studies ◽

Multiple Hypothesis Testing ◽

Population History ◽

Genome Wide Association Studies ◽

Multivariate Normal ◽

Association Testing ◽

Genome Wide ◽

Comprehensive Framework

AbstractGenome-wide association studies (GWAS) have discovered thousands of variants involved in common human diseases. In these studies, frequencies of genetic variants are compared between a cohort of individuals with a disease (cases) and a cohort of healthy individuals (controls). Any variant that has a significantly different frequency between the two cohorts is considered an associated variant. A challenge in the analysis of GWAS studies is the fact that human population history causes nearby genetic variants in the genome to be correlated with each other. In this review, we demonstrate how to utilize the multivariate normal (MVN) distribution to explicitly take into account the correlation between genetic variants in a comprehensive framework for analysis of GWAS. We show how the MVN framework can be applied to perform association testing, correct for multiple hypothesis testing, estimate statistical power, and perform fine mapping and imputation.

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Genes, Psychology and Population History

10.31234/osf.io/kgz2t ◽

2021 ◽

Author(s):

Ken Richardson

Keyword(s):

Social Policy ◽

Genetic Markers ◽

Complex Traits ◽

Population Stratification ◽

Association Studies ◽

Population History ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Historical Dynamics

Genome wide association studies (GWAS) are being increasingly used to identify genetic markers of variation in complex traits such as intelligence and education. However, GWAS are compromised by population stratification (PS) leading to spurious associations, and attempts to correct for them statistically are also proving to be inadequate. This suggests the need for a deeper understanding of the sources of such PS and how its roots in complex social and historical dynamics can seriously mislead interpretations from GWAS/PGS to social policy.

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