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ARS Home » Research » Publications at this Location » Publication #86943


item Yonash, Nissim
item Bacon, Larry
item Witter, Richard
item Cheng, Hans

Submitted to: Plant and Animal Genome VX Conference Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 1/15/1998
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Previously, several QTL conferring susceptibility to MD were revealed using a 272 F2 resource population derived from the inbred chicken lines 6 (MD resistant) and 7 (MD susceptible) which were challenged with the MD virus (JM strain) at 1 week of age. The QTL were identified using a combination of single-point ANOVA and interval mapping algorithms. Due to the limitation of markers on the chicken genome map, several of the QTL lie in large marker intervals (50+ cM) or linked to only a single marker. The goal of this study was to saturate these QTL regions with additional markers to better resolve the location and size of effect. For three QTL regions (Ch. 4, Ch. 7, and linkage group E41), additional informative microsatellite markers were identified and typed. For Ch. 4 which contained a QTL in a large marker interval, one microsatellite was mapped in the interval and better associations to this marker were revealed by both ANOVA and interval mapping. For Ch. 7 which contained another QTL in a large marker interval, three additional microsatellites were placed in the interval. No effects on MD susceptibility traits were associated with these three markers, but better associations were revealed to the extreme markers of the interval suggesting that the initial QTL detected was actually two QTL. Two additional markers were located in one side of the single marker linked to the QTL in E41. These markers were less associated with any of the MD traits suggesting the QTL lie on the opposite side of the linked marker. In summary, the additional markers both confirm and better resolve the location of each QTL. Furthermore, comparing the various QTL analyses indicate that single-point ANOVA is comparable to interval mapping algorithms and is more simple to perform.