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This article is part of the supplement: IUFRO Tree Biotechnology Conference 2011: From Genomes to Integration and Delivery

Open Access Poster presentation

Association mapping of local adaptation traits of Scots pine in a European wide population sample

Timo Knürr1, Sonja Kujala2, Mikko J Sillanpää3, Komlan Avia4, Aleksia Vaattovaara4, Katri Kärkkäinen5 and Outi Savolainen4*

Author Affiliations

1 Dept. Mathematics and Stastistics, University of Helsinki, Finland

2 Dept. biology, Unviersity of Oulu, Finland

3 Dept. Mathematics and Statistics, University of Helsinki, Finland

4 Dept. Biology, University of Oulu, Finland

5 Finnish Forest Research Institute, Finland

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BMC Proceedings 2011, 5(Suppl 7):P38  doi:10.1186/1753-6561-5-S7-P38


The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1753-6561/5/S7/P38


Published:13 September 2011

© 2011 Knürr et al; licensee BioMed Central Ltd.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

Traits related to local adaptation by definition show high phenotypic differentiation. The underlying genetic patterns could be clines at individual loci or small effects and extensive linkage disequilibrium at the underlying loci. In any case, including many populations in an analysis provides more information, but may simultaneously induce problems due to genetic structure. Even if the neutral loci have little genetic structure, loci related to other clinally selected traits could show more structure. Here we have developed an approach to efficiently use the information along a latitudinal environmental gradient. Scots pine populations from central Europe to the species' northern range were sampled and patterns of phenotypic variation of both timing of budset and frost tolerance were measured in common garden experiments, (10 populations, a total of 270 halfsib families, 25 trees per family). By hierarchical modelling of the phenotype's clinal variation and accounting for varying allele frequencies across the 10 populations, the statistical approach simultaneously exploits the genetic variation between and within populations to detect association signals. We apply shrinkage-based Bayesian variable selection to detect genetic associations between timing of bud set and ~450 SNPs in Scots pine.