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Cryptic population genetic structure: the number of inferred clusters depends on sample size
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Evolution, Genomics and Systematics.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution.
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2010 (English)In: Molecular Ecology Resources, ISSN 1755-098X, Vol. 10, no 2, 314-323 p.Article in journal (Refereed) Published
Abstract [en]

Clustering methods have been used extensively to unravel cryptic population genetic structure. We investigated the effect of the number of individuals sampled in each location on the resulting number of clusters. Our study was motivated by recent results in Arabidopsis thaliana: studies in which more than one individual was sampled per location apparently have led to a much higher number of clusters than studies where only one individual was sampled in each location, as is generally done in this species. We show, using computer simulations and microsatellite data in A. thaliana, that the number of sampled individuals indeed has a strong impact on the number of resulting clusters. This effect is smaller if the sampled populations have a hierarchical structure. In most cases, sampling 5-10 individuals per population should be enough. The results argue for abandoning the concept of 'accessions' in partially selfing organisms.

Place, publisher, year, edition, pages
2010. Vol. 10, no 2, 314-323 p.
Keyword [en]
Arabidopsis thaliana, Population structure, Sampling, STRUCTURE
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:uu:diva-97461DOI: 10.1111/j.1755-0998.2009.02756.xISI: 000274325400008OAI: oai:DiVA.org:uu-97461DiVA: diva2:172419
Available from: 2008-09-04 Created: 2008-09-04 Last updated: 2017-01-25Bibliographically approved
In thesis
1. Genetic structure and dispersal in plant populations
Open this publication in new window or tab >>Genetic structure and dispersal in plant populations
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis focuses on the spatial structure and methods to identify spatial structure in plants.

Methods that investigate genetic structure can mainly be divided into equilibrium methods that reveal summed dispersal over many generations, and cluster methods, that reveal more recent dispersal events. Depending on the spatial level, local or global, suitable methods are different.

The thesis consists of four papers.

The first explores the spatial genetic structure in two epiphytic bryophytes that have different dispersal strategies (Orthotrichum speciosum and O. obtusifolium) using three different approaches based on pairwise kinship coefficients assessed from AFLP data. The spatial kinship structure was detected with both autocorrelation analysis and generalized additive models, but linear regression failed to detect any structure in O. speciosum.

In the second paper the spatial genetic structure in marginal populations of the forest tree Quercus robur is investigated at both local and regional scales. At the local scale, dispersal kernels as estimated using maximum likelihood parentage methods showed to be comparable to results acquired in central located populations. At the regional scale the degree of isolation at the margin of the distribution is shown.

The third paper compares a number of sibship clustering methods. It was found that the performances of the sibship reconstruction algorithms are strongly dependent on fulfilling the assumptions of the model and that using an overly simple model produced very unreliable results. The amount of information included in the model affected the results; models including all the available information outperformed the models using only a subset of the information.

In the last paper we show that the number of clusters as estimated by the software Structurama depends on sample size. At high number of subpopulations, the estimated number of clusters tends to be grossly underestimated when the number of sampled individuals per subpopulation is low.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2008. 39 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 546
Keyword
population genetics, dispersal, structure, plant, gene flow
Identifiers
urn:nbn:se:uu:diva-9211 (URN)978-91-554-7262-7 (ISBN)
Public defence
2008-09-26, zootissalen, EBC, Norbyvägen 9, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2008-09-04 Created: 2008-09-04 Last updated: 2009-05-27Bibliographically approved

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Ågren, Jon

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