Genetic architecture of a selection response in Arabidopsis thaliana.
Quantitative trait locus (QTL) mapping has become an established and effective method for studying the genetic architecture of complex traits. In this report, we use a QTL mapping approach in combination with data from a large selection experiment in Arabidopsis thaliana to explore a response to selection of experimental populations with differentiated genetic backgrounds. Experimental populations with genetic backgrounds derived from ecotypes Landsberg and Niederzenz were exposed to multiple generations of fertility and viability selection. This selection resulted in phenotypic shifts in a number of life-history and fitness-related characters including early development time, flowering time, dry biomass, longevity, and fruit production. Quantitative trait loci were mapped for these traits and their positions were compared to previously characterized allele frequency changes in the experimental populations (Ungerer et al. 2003). Quantitative trait locus positions largely colocalized with genomic regions under strong and consistent selection in populations with differentiated genetic backgrounds, suggesting that alleles for these traits were selected similarly in differentiated genetic backgrounds. However, one QTL region exhibited a more variable response; being positively selected on one genetic background but apparently neutral in another. This study demonstrates how QTL mapping approaches can be combined with map-based population genetic data to study how selection acts on standing genetic variation in populations.
Ungerer
Mark C
MC
Department of Biology, Indiana University, Bloomington, Indiana 47405, USA. mcungere@unity.ncsu.edu
Rieseberg
Loren H
LH
D000704:Analysis of Variance; D017360:Arabidopsis / Q000235:genetics*; D018533:Biomass; D003433:Crosses, Genetic; D005298:Fertility / Q000235:genetics; D005787:Gene Frequency; D005828:Genetics, Population; D010641:Phenotype; D040641:Quantitative Trait Loci / Q000235:genetics*; D012098:Reproduction / Q000502:physiology; D012641:Selection, Genetic