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Understanding population structure in an evolutionary context: population-specific FST and pairwise FST

View ORCID ProfileShuichi Kitada, Reiichiro Nakamichi, Hirohisa Kishino
doi: https://doi.org/10.1101/2020.01.30.927186
Shuichi Kitada
1Tokyo University of Marine Science and Technology, Tokyo 108-8477, Japan
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  • For correspondence: kitada@kaiyodai.ac.jp
Reiichiro Nakamichi
2Japan Fisheries Research and Education Agency, Yokohama 236-8648, Japan
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Hirohisa Kishino
3Graduate School of Agriculture and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan
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Abstract

Populations are shaped by their history. Therefore, it is crucial to interpret population structure in an evolutionary context. Wright’s FST measures current population structure, whereas population-specific FST measures deviation from the ancestral population. To understand current population structure and a population’s history of range expansion, we propose a novel representation method that overlays population-specific FST estimates on an unrooted neighbor-joining tree inferred from a pairwise FST distance matrix and on a map of sampling locations. We examined the usefulness of our procedure by conducting simulations that mimicked population colonization from an ancestral population and analyzing published human, Atlantic cod, and wild poplar genotype data sets. Our results demonstrated that population-specific FST values identify the source population and trace the evolutionary history of its derived populations based on genetic diversity. In contrast, pairwise FST values represent the current population structure. By integrating results of both estimators, we obtained a new picture of current population structure that incorporates evolutionary history. The generalized least squares of genome-wide population-specific FST indicated that the wild poplar population expanded its distribution to the north where it adapted to longer day lengths, to seashores where it adapted to abundant rainfall, and to the south where it adapted to dry summers. Genomic data highlight the power of the bias-corrected moment estimators of FST. All FST moment estimators described in this paper have reasonable CPU times and are useful in population genomics studies. The R codes for our representation method and simulations are available in the Supporting Information.

  • Adaptation
  • evolution
  • genetic diversity
  • migration
  • population structure

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted August 04, 2020.
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Understanding population structure in an evolutionary context: population-specific FST and pairwise FST
Shuichi Kitada, Reiichiro Nakamichi, Hirohisa Kishino
bioRxiv 2020.01.30.927186; doi: https://doi.org/10.1101/2020.01.30.927186
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Understanding population structure in an evolutionary context: population-specific FST and pairwise FST
Shuichi Kitada, Reiichiro Nakamichi, Hirohisa Kishino
bioRxiv 2020.01.30.927186; doi: https://doi.org/10.1101/2020.01.30.927186

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