14 th QTL-MAS Workshop, Poznań University <strong>of</strong> Life Sciences, Poland 2010Genetic architecture <strong>of</strong> quantitative traitsWilliam G. Hill 1∗1 Institute <strong>of</strong> Evolutionary Biology, University <strong>of</strong> Edinburgh∗ Presenting author: William Hill, email: w.g.hill@ed.ac.ukUnderstanding the ‘black box’ <strong>of</strong> the genetics <strong>of</strong> quantitative traits has been a long standingobjective. Important unknowns are the numbers <strong>of</strong> loci involved, and the d<strong>is</strong>tribution <strong>of</strong> theirfrequencies, effects on the trait and their interactions <strong>The</strong>se depend both on the basicarchitecture and on the selective and other forces whereby variation <strong>is</strong> lost or maintained.Some information has come at the quantitative level from covariances among relatives,inbreeding and selection experiments which indicate many loci are responsible. <strong>The</strong>availability <strong>of</strong> dense markers provides the opportunity for deeper study, but although somegenes <strong>of</strong> large effect have been detected, genome wide association studies <strong>of</strong> traits in humansalso indicate many loci are contributing to variation.I shall d<strong>is</strong>cuss what we may expect on the bas<strong>is</strong> <strong>of</strong> population genetics theory and knowledge<strong>of</strong> parameters to be the d<strong>is</strong>tributions <strong>of</strong> effects and frequencies, how these influenceinferences that can be drawn from GWAS and similar studies, and how these relate toobservations.12
14 th QTL-MAS Workshop, Poznań University <strong>of</strong> Life Sciences, Poland 2010Re-examining ep<strong>is</strong>tatic interactions in Virginia line chickensMats E. Pettersson 1∗1Computational Genetics, Department <strong>of</strong> Animal Breeding and Genetics, Swed<strong>is</strong>h Univer<strong>is</strong>ty <strong>of</strong> Agriculture∗ Presenting author: Mats Pettersson, email: mats.pettersson@hgen.slu.seIt has previously been shown that a substantial fraction <strong>of</strong> the phenotypic difference betweenthe high growth and low growth lines <strong>of</strong> Virginia lines chicken, which show a nine-folddifference in body-weight after 50 generations <strong>of</strong> differential selection, can be attributed toep<strong>is</strong>tatic interactions between different QTL 1 .<strong>The</strong> present study <strong>is</strong> based on data from an advanced intercross line, with a pedigree reachingdown to an F 8 generation, that <strong>is</strong> an extension <strong>of</strong> the F2 population originally used. In th<strong>is</strong> dataset, which also has a higher density <strong>of</strong> markers, the ep<strong>is</strong>tatic interactions, as well as singleQTL effects, have been re-evaluated. I employ a bootstrapping method to improve thereliability <strong>of</strong> QTL detection, and use data stratification to show ep<strong>is</strong>tatic interactions.<strong>The</strong> results are that several <strong>of</strong> the ep<strong>is</strong>tatic interactions previously found are recovered in th<strong>is</strong>analys<strong>is</strong>, reaffirming the importance <strong>of</strong> ep<strong>is</strong>tas<strong>is</strong> in the system. However, there are also somedifferences; not all interacting pairs are replicated and the total effect <strong>of</strong> ep<strong>is</strong>tas<strong>is</strong> <strong>is</strong> somewhatlower. Nevertheless, the overall picture <strong>is</strong> largely the same.1. Carlborg, Ö., Jacobsson, L., Åhgren, P., Siegel, P. & Andersson, L. Ep<strong>is</strong>tas<strong>is</strong> and the release <strong>of</strong> geneticvariation during long-term selection. Nature Genetics 38, 418-419 (2006).13
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