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POSTER 160 - CHARACTERIZATION OF LOCI CAUSING AIRWAY HYPERRESPONSIVENESS USING PHENOTYPE-DRIVEN SELECTION AND CHROMOSOME SUBSTITUTION STRAINS
Beier D
Brigham and Women's Hospital and Harvard Medical
School, Boston, MA
Co-Authors: 1) Ackerman K G, 1) Grasemann H, 1) Huang H, 1)
De Sanctis G T, 1) Puma C, 2) Singer J, 2) Lander E, 3) Hill A,
3) Nadeau J, 1) Drazen J M
Institutions: 1) Brigham and Women's Hospital and
Harvard Medical School, Boston, MA. 2) Whitehead Insitute, MIT,
Cambridge, MA 3) Case Western Reserve University School of
Medicine, Cleveland, OH
Interstrain variability of naïve airway hyperresponsiveness (AHR) provides an important tool for genetic analysis of loci contributing to this trait, which is a component of human asthma. A phenotype-driven strategy was used to select congenic mice from a serial backcross of hyperresponsive A/J mice to B6 mice. Genotyping of N7 hyperresponsive males revealed 3 retained A/J regions on chromosomes 2, 6, and 10. To test the causal association of the retained regions, hyperresponsive N7 males were backcrossed to create an expanded N8 population. QTL analysis of over 120 unselected N8 males did not identify a significant association of any single locus with AHR. However, when the data was analyzed to account for interactions, a highly significant association was found for inheritance of A/J alleles on chromosomes 2 and 6 together (Lod = 4.93).
Chromosome substitution strains (CSS) were used to independently evaluate these results. Strains heterozygous for A/J on both 2 and 6 had higher AHR than mice heterozygous on chromosome 2 (p<0.05) or chromosome 6 (p<0.0001) alone. CSS mice homozygous for A/J alleles on chromosomes 2 or 6 had significantly elevated AHR (p<0.0001). Inheritance of A/J chromosome 10 did not contribute to AHR.
Thus, a completely independent analysis using CSS confirms our observation that A/J chromosomes 2 and 6 contain genes contributing to AHR and supports the conclusion that they function as interacting loci. These results have important implications not only for understanding human asthma, but for the more general analysis of complex traits using association analysis.
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