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Genetic structure of the LXS panel of recombinant inbred mouse strains: a powerful resource for complex trait analysis
Authors:Robert W Williams  Beth Bennett  Lu Lu  Jing Gu  John C DeFries  Phyllis J Carosone–Link  Brad A Rikke  John K Belknap  Thomas E Johnson
Institution:(1) Center of Genomics and Bioinformatics, Institute of Neuroscience, Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA;(2) Institute for Behavioral Genetics, CB 447, University of Colorado, Boulder, Colorado 80309, USA;(3) Department of Psychology, CB 345, University of Colorado, Boulder, Colorado 80309, USA;(4) Portland Alcohol Research Center, Oregon Health Sciences University, Portland, Oregon 97239, USA
Abstract:The set of LXS recombinant inbred (RI) strains is a new and exceptionally large mapping panel that is suitable for the analysis of complex traits with comparatively high power. This panel consists of 77 strains—more than twice the size of other RI sets— and will typically provide sufficient statistical power (betathinsp=thinsp0.8) to map quantitative trait loci (QTLs) that account for sim25% of genetic variance with a genomewide p < 0.05. To characterize the genetic architecture of this new set of RI strains, we genotyped 330 MIT microsatellite markers distributed on all autosomes and the X Chromosome and assembled error-checked meiotic recombination maps that have an average F2-adjusted marker spacing of sim4 cM. The LXS panel has a genetic structure consistent with random segregation and subsequent fixation of alleles, the expected 3–4 × map expansion, a low level of nonsyntenic association among loci, and complete independence among all 77 strains. Although the parental inbred strains—Inbred Long-Sleep (ILS) and Inbred Short-Sleep (ISS)—were derived originally by selection from an 8-way heterogeneous stock selected for differential sensitivity to sedative effects of ethanol, the LXS panel is also segregating for many other traits. Thus, the LXS panel provides a powerful new resource for mapping complex traits across many systems and disciplines and should prove to be of great utility in modeling the genetics of complex diseases in human populations.(Robert W. Williams and Beth Bennett)These authors contributed equally to this work.
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