Biomathematics & Statistics Scotland
Association studies have been used to locate single genes for some diseases in humans. In plant studies, the analysis is complicated by issues of selection, self-fertilisation and especially population substructure. The latter varies from large scale structure, such as plants selected for different traits in different regions, to smaller scale differences in degrees of kinship. Different substructure models have been proposed, but when applied to experimental data often identify different regions as containing the quantitative trait loci (QTLs) that controlling important traits such as yield.
Simulation studies enable methods to be compared in a population where QTL locations, population structure and pedigrees are all known. We have modelled a simulation study on a real collection of barley germplasm from five regions. Ten genotyped landraces from each region were taken as founders. One thousand generations of landraces were generated with a selfing probability of 0.92. This was followed by 24 generations of selection on drought tolerance, yield or heading date, depending on region, to generate cultivars.
This simulated population is enabling us to compare methods for estimating kinship from various types of
DNA marker data with the known pedigrees, and to explore the accuracy and limitations of models including
population substructure and kinship to identify genuine QTLs. For example, we find many falsely significant
associations (high values for -log 10 p-values) are estimated ignoring population structure that vanish when the
structure is included in the model.
Assumptions about population structure have an important effect on the strength of evidence for associations of position on chromosome 1H with heading date of barley in a dry environment in Spain.
Further details from: Christine Hackett
