23rd Summer Institute in Statistical Genetics (SISG)

Module 8: Quantitative Genetics

Session 3: Mon Jul 16 to Wed Jul 18
Instructor(s):

Module dates/times: Monday, July 16; 8:30 a.m. -5 p.m.; Tuesday, July 17, 8:30 a.m.-5 p.m., and Wednesday, July 18, 8:30 a.m.-Noon

This module assumes the material in Module 1: Probability and Statistical Inference and Module 4: Regression Methods: Concepts & Applications, and provides a foundation for many later modules.

Quantitative Genetics is the analysis of complex characters where both genetic and environment factors contribute to trait variation. Since this includes most traits of interest — disease susceptibility, crop yield, growth and reproduction in animals, human and animal behavior, and all gene expression data (transcriptome and proteome) — a working knowledge of quantitative genetics is critical in diverse fields from plant and animal breeding, human genetics, genomics, and behavior, to ecology and evolutionary biology.

The course will cover the basics of quantitative genetics including: genetic basis for complex traits, population genetic assumptions including detection of admixture, Fisher’s variance decomposition, covariance between relatives, calculation of the numerator relationship matrix based on IBD alleles and an arbitrary pedigree, the genomic relationship matrix based on AIS alleles, heritability in the broad and narrow sense, inbreeding and cross-breeding, and response to selection.

The module also includes an introduction to advanced topics such as: Mixed Models, Best Linear Unbiased Prediction (BLUP), Genomic selection (GBLUP), Genome Wide Association Analysis (GWAS), QTL mapping, detection of selection from genomic data, correlated characters; and the multivariate response to selection.

Guilherme Rosa is Professor of Animal Science at the University of Wisconsin, Madison. He teaches courses and develops research on quantitative genetics and statistical genomics, including design of experiments and data analysis tools. Some specific areas of interest include mixed effects models, graphical models, Bayesian analysis and Monte Carlo methods, and prediction of complex traits using genomic information. He recently published “One hundred years of statistical developments in animal breeding.” Annual Review of Animal Biosciences 3: 19-56, 2015

Bruce Walsh is Professor of Ecology and Evolutionary Biology at the University of Arizona. His interests are broadly in using mathematical models to explore the interface of genetics and evolution, with particular focus on two areas: the evolution of genome structure and the analysis of complex genetic characters (aka quantitative genetics). He is well-known as co-author of “Genetics and Analysis of Quantitative Characters.” 980 pp. Sinauer Associations.

Access 2017 Course Materials (2018 materials will be uploaded to this page prior to the start of the module)