Forward genetics approaches using animal models are undergoing a period of change, in part in response to the changes that have occurred in human genetics in the past few years. New experimental designs, including the collaborative cross and advanced heterogeneous stock populations, have the potential to yield large populations of animals with a genetic constitution that more accurately reflects the human genetic state with regard to diversity and heterozygosity. In addition, there has been rapid development of inexpensive high- throughput phenotyping capabilities, notably with gene expression microarrays, but metabolite and protein profiling will soon cross thresholds of quality and affordability. These changes necessitate the development of new computational and statistical tools for interpreting data.
Our aims are to develop statistical methods in anticipation of new experimental approaches, to develop and disseminate software and data resources, and to analyze and interpret new and historical data from forward genetics experiments in mice. Our focus will shift from the historical objectives which emphasized gene discovery to new model-based approaches that exploit high dimensional and cumulative data to model systemic responses to genetic and environmental perturbations. The timely development of statistical methods and software will be critical to the success of mouse genetics in the coming years.

Public Health Relevance

Experimental animals provide an important complement to genetic studies in humans and are essential when experiments involve potentially harmful exposure or are impossible to carry out with human subjects. This project will develop statistical and computational tools that are needed to interpret the outcomes of these experiments including newly developed approaches which enable us to work with mouse populations that more accurately reflect the human genetic state. )

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM070683-08
Application #
8286865
Study Section
Special Emphasis Panel (ZRG1-GGG-F (02))
Program Officer
Eckstrand, Irene A
Project Start
2004-04-01
Project End
2014-06-30
Budget Start
2012-07-01
Budget End
2014-06-30
Support Year
8
Fiscal Year
2012
Total Cost
$341,075
Indirect Cost
$145,055
Name
Jackson Laboratory
Department
Type
DUNS #
042140483
City
Bar Harbor
State
ME
Country
United States
Zip Code
04609
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Ram, Ramesh; Mehta, Munish; Balmer, Lois et al. (2014) Rapid identification of major-effect genes using the collaborative cross. Genetics 198:75-86
Lenarcic, Alan B; Svenson, Karen L; Churchill, Gary A et al. (2012) A general Bayesian approach to analyzing diallel crosses of inbred strains. Genetics 190:413-35
Threadgill, David W; Churchill, Gary A (2012) Ten years of the collaborative cross. G3 (Bethesda) 2:153-6
Threadgill, David W; Churchill, Gary A (2012) Ten years of the Collaborative Cross. Genetics 190:291-4
Zhang, Weidong; Korstanje, Ron; Thaisz, Jill et al. (2012) Genome-wide association mapping of quantitative traits in outbred mice. G3 (Bethesda) 2:167-74
Leduc, Magalie S; Blair, Rachael Hageman; Verdugo, Ricardo A et al. (2012) Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross. J Lipid Res 53:1163-75
Svenson, Karen L; Gatti, Daniel M; Valdar, William et al. (2012) High-resolution genetic mapping using the Mouse Diversity outbred population. Genetics 190:437-47
Collaborative Cross Consortium (2012) The genome architecture of the Collaborative Cross mouse genetic reference population. Genetics 190:389-401

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