PT  - JOURNAL ARTICLE
AU  - Shuichi Kitada
AU  - Reiichiro Nakamichi
AU  - Hirohisa Kishino
TI  - Population-specific &lt;em&gt;F&lt;/em&gt;&lt;sub&gt;ST&lt;/sub&gt; and Pairwise &lt;em&gt;F&lt;/em&gt;&lt;sub&gt;ST&lt;/sub&gt;: History and Environmental Pressure
AID  - 10.1101/2020.01.30.927186
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.01.30.927186
4099  - http://biorxiv.org/content/early/2020/01/31/2020.01.30.927186.short
4100  - http://biorxiv.org/content/early/2020/01/31/2020.01.30.927186.full
AB  - Appropriate estimates of population structure are the basis of population genetics, with applications varying from evolutionary and conservation biology to association mapping and forensic identification. The common procedure is to first compute Wright’s FST over all samples (global FST) and then routinely estimate between-population FST values (pairwise FST). An alternative approach for estimating population differentiation is the use of population-specific FST measures. Here, we characterize population-specific FST and pairwise FST estimators by analyzing publicly available human, Atlantic cod and wild poplar data sets. The bias-corrected moment estimator of population-specific FST identified the source population and traced the migration and evolutionary history of its derived populations by way of genetic diversity, whereas the bias-corrected moment estimator of pairwise FST was found to represent current population structure. Generally, the first axis of multi-dimensional scaling for the pairwise FST distance matrix reflected population history, while subsequent axes indicated migration events, languages and the effect of environment. The relative contributions of these factors were dependent on the ecological characters of the species. Given shrinkage towards mean allele frequencies, maximum likelihood and Bayesian estimators of locus-specific global FST improved the power to detect genes under environmental selection. In contrast, bias-corrected moment estimators of global FST measured species divergence and enabled reliable interpretation of population structure. The genomic data highlight the usefulness of the bias-corrected moment estimators of FST. The R package FinePop2_ver.0.2 for computing these FST estimators is available at CRAN.