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Genetic and genomic approaches to assess adaptive genetic variation in plants: forest trees as a model
Author(s) -
Gailing Oliver,
Vornam Barbara,
Leinemann Ludger,
Finkeldey Reiner
Publication year - 2009
Publication title -
physiologia plantarum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.351
H-Index - 146
eISSN - 1399-3054
pISSN - 0031-9317
DOI - 10.1111/j.1399-3054.2009.01263.x
Subject(s) - biology , outcrossing , local adaptation , candidate gene , genetic variation , quantitative trait locus , single nucleotide polymorphism , nucleotide diversity , adaptation (eye) , evolutionary biology , genetics , gene , population , allele , ecology , genotype , haplotype , pollen , demography , neuroscience , sociology
With the increasing availability of sequence information at putatively important genes or regulatory regions, the characterization of adaptive genetic diversity and their association with phenotypic trait variation becomes feasible for many non‐model organisms such as forest trees. Especially in predominantly outcrossing forest tree populations with large effective size, a high genetic variation in relevant genes is maintained, that is the raw material for the adaptation to changing and variable environments, and likewise for plant breeding. Oaks ( Quercus spp.) are excellent model species to study the adaptation of forest trees to changing environments. They show a wide geographic distribution in Europe as dominant tree species in many forests and grow under a wide range of climatic and edaphic conditions. With the availability of a growing amount of functional and expressional candidate genes, we are now able to test the functional importance of single nucleotide polymorphisms (SNPs) by associating nucleotide variation in these genes with phenotypic variation in adaptive traits in segregating or natural populations. Here, we report on quantitative trait locus (QTL), candidate gene and association mapping approaches that are applicable to characterize gene markers and SNPs associated with variation in adaptive traits, such as bud burst, drought resistance and other traits showing selective responses to environmental change and stress. Because genome‐wide association mapping studies are not feasible because of the enormous amount of SNP markers required in outcrossing trees with high recombination rates, the success of such an approach depends largely on the reasonable selection of candidate genes.