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Variogram Analysis of the Spatial Genetic Structure of Continuous Populations Using Multilocus Microsatellite Data

journal contribution
posted on 10.02.2021, 22:53 by HH Wagner, R Holderegger, S Werth, F Gugerli, Susan Hoebee, C Scheidegger
A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation. Copyright © 2005 by the Genetics Society of America.

History

Publication Date

01/01/2005

Journal

Genetics

Volume

169

Issue

3

Pagination

(p. 1739-1752)

Publisher

GENETICS SOCIETY AMERICA

ISSN

1943-2631

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The Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.

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