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United States Department of Agriculture

Agricultural Research Service

Title: A Genome Scan for Gastrointestinal Nematode Resistance in Cattle.

Authors
item Sonstegard, Tad
item Gasbarre, Louis
item Van Tassell, Curtis
item Thallman, Richard
item Padilha, Terezina - EMBRAPA

Submitted to: Animal Genetics International Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: June 1, 2002
Publication Date: August 11, 2002
Citation: Sonstegard, T.S., Gasbarre, L.C., Van Tassell, C.P., Thallman, R.M., Padilha, T. 2002. A genome scan for gastrointestinal nematode resistance in cattle [abstract]. Animal Genetics International Conference Proceedings.

Technical Abstract: Breeding for host resistance offers an alternative method to control disease caused by gastrointestinal (GI) parasites. However, the genetic factors affecting host resistance and transmission in cattle have yet to be identified. Using a population of linebred Angus cattle that was divergently selected for resistance to GI parasites, we performed a genome-wide scan to identify QTL for traits related to infection. Genotypes for 196 microsatellite markers were generated from ~300 progeny with phenotypic records for parasite challenge, parents, and over 70 sires from the historic pedigree. Traits analyzed were mean, peak, and final numbers of nematode eggs/gram (EPG) of feces and mean and final serum pepsinogen levels. Marker segregations were determined using Genoprob. The analysis model included sex of calf, age of dam at calving, age of calf at parasite challenge, calving season, sire, and within-sire regression on the probability of inheriting one of the two QTL alleles of the sire. The number of progeny with both marker data and phenotypes ranged from 2 to 14 in each of the 43 sire families. A total of 175 of 37,539 tested effects were significant within family (P<0.001), and 17 marker by trait combinations on seven chromosomes out of 905 tested were significant (P<0.01) in across-family F-tests. In both analyses, adjacent markers were found to be significant. A permutation test is under development to account for non-normality of the EPG data and multiple testing.

Last Modified: 12/20/2014
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