Title
Quantifying population structure on short timescalesQuantifying population structure on short timescales
Author
Faculty/Department
Faculty of Sciences. Biology
Research group
Evolutionary ecology group (EVECO)
Department of Biology
Publication type
article
Publication
Oxford,
Subject
Chemistry
Biology
Source (journal)
Molecular ecology. - Oxford
Volume/pages
21(2012):14, p. 3458-3473
ISSN
0962-1083
ISI
000306087100009
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Quantifying the contribution of the various processes that influence population genetic structure is important, but difficult. One of the reasons is that no single measure appropriately quantifies all aspects of genetic structure. An increasing number of studies is analysing population structure using the statistic D, which measures genetic differentiation, next to GST, which quantifies the standardized variance in allele frequencies among populations. Few studies have evaluated which statistic is most appropriate in particular situations. In this study, we evaluated which index is more suitable in quantifying postglacial divergence between three-spined stickleback (Gasterosteus aculeatus) populations from Western Europe. Population structure on this short timescale (10 000 generations) is probably shaped by colonization history, followed by migration and drift. Using microsatellite markers and anticipating that D and GST might have different capacities to reveal these processes, we evaluated population structure at two levels: (i) between lowland and upland populations, aiming to infer historical processes; and (ii) among upland populations, aiming to quantify contemporary processes. In the first case, only D revealed clear clusters of populations, putatively indicative of population ancestry. In the second case, only GST was indicative for the balance between migration and drift. Simulations of colonization and subsequent divergence in a hierarchical stepping stone model confirmed this discrepancy, which becomes particularly strong for markers with moderate to high mutation rates. We conclude that on short timescales, and across strong clines in population size and connectivity, D is useful to infer colonization history, whereas GST is sensitive to more recent demographic events.
E-info
https://repository.uantwerpen.be/docman/iruaauth/831d1b/1fb2498.pdf
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