Chapter title |
Heterogeneous Stock Populations for Analysis of Complex Traits
|
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Chapter number | 2 |
Book title |
Systems Genetics
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6427-7_2 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6425-3, 978-1-4939-6427-7
|
Authors |
Leah C. Solberg Woods, Richard Mott, Woods, LCS, Mott, R |
Editors |
Klaus Schughart, Robert W. Williams |
Abstract |
Heterogeneous Stock (HS) populations allow for fine-resolution genetic mapping of a variety of complex traits. HS mice and rats were created from breeding together eight inbred strains, followed by maintaining the colony in a manner that minimizes inbreeding. After 50 or more generations of breeding, the resulting animals' chromosomes represent a genetic mosaic of the founders' haplotypes, with the average distance between recombination events in the centiMorgan range. This allows for genetic mapping to only a few Mb, a much smaller region than what can be identified using traditional F2 intercross or backcross mapping strategies. HS animals have been used to fine-map a variety of complex traits including anxiety and fear behaviors, diabetes, asthma, and heart disease, among others. Once a quantitative trait locus (QTL) has been identified, founder sequence and expression analysis can be used to identify underlying causal genes. In the following review, we provide an overview of how HS rats and mice have been used to identify genetic loci, and in some cases the causal genes, underlying complex traits. We discuss the creation and breeding strategies for both HS rats and mice. We then discuss the statistical analyses used to identify genetic loci, as well as strategies to identify causal genes underlying these loci. We end the chapter by discussing limitations faced when using HS populations, including several statistical challenges that have not been fully resolved. |
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Mendeley readers
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Unknown | 16 | 100% |
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Student > Ph. D. Student | 5 | 31% |
Researcher | 3 | 19% |
Professor | 2 | 13% |
Student > Bachelor | 1 | 6% |
Professor > Associate Professor | 1 | 6% |
Other | 0 | 0% |
Unknown | 4 | 25% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 6 | 38% |
Biochemistry, Genetics and Molecular Biology | 3 | 19% |
Neuroscience | 2 | 13% |
Immunology and Microbiology | 1 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
Other | 0 | 0% |
Unknown | 3 | 19% |