题 目:Most human traits are complex: dissection of genetic variation for height, schizophrenia and motor neurone disease
报告人: Prof. Peter M. Visscher, Queensland Brain Institute, University of Queensland
Driven by advances in genome technologies, the last 7 years have witnessed a revolution in our understanding of complex trait variation in human populations. Results from genome-wide association studies and whole-genome exome studies have shown that the mutational target in the genome for most traits appears to be very large, such that many genes are involved in explaining genetic variation. Genetic architecture, the joint distribution of the effect size and frequency of variants that segregate in the population, is becoming clearer and differs between traits. I will show new results from disparate complex traits including height, schizophrenia, motor neurone disease and gene methylation, to illustrate polygenicity and the power of experimental sample size.
Peter Visscher did his first degree in the Netherlands. He moved to Edinburgh (UK) in 1987 for an MSc and subsequent PhD in animal breeding and genetics, working on the estimation of genetic parameters in large livestock pedigrees. A postdoctoral period in Melbourne (Australia) was followed by a return to Edinburgh, where he developed methods to map genetic loci underlying complex traits. In 1995 he moved to a faculty position at the University of Edinburgh, developing gene mapping methods and software tools, with practical applications in livestock and human populations. Visscher joined the Queensland Institute of Medical Research in Brisbane (Australia) in 2005 and in 2011 moved to the University of Queensland where he is Professor and Chair of Quantitative Genetics and Co-Director of the Centre for Neurogenetics and Statistical Genomics. Visscher is a Senior Principal Research Fellow of the Australian National Health and Medical Research Council and was elected a Fellow of the Australian Academy of Science in 2010.Visscher's research interests are focussed on a better understanding of genetic variation for complex traits, including quantitative traits and disease.