Linked Life Data

21406356

Source:http://linkedlifedata.com/resource/pubmed/id/21406356

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2011-3-16
pubmed:abstractText
Salmonella propagation by apparently healthy chickens could be decreased by the selection and use of chicken lines that are more resistant to carrier state. Using a reduced set of markers, this study investigates, for the first time to the authors' knowledge, the feasibility of a genomic selection approach for resistance to carrier state in hen lines. In this study, commercial laying hen lines were divergently selected for resistance to Salmonella carrier state at 2 different ages: young chicks and adults at the peak of lay. A total of 600 birds were typed with 831 informative SNP markers and artificially infected with Salmonella Enteritidis. Phenotypes were collected 28 d (389 young animals) or 38 d (208 adults) after infection. Two types of variance component analyses, including SNP data or not, were performed and compared. The set of SNP used was efficient in capturing a large part of the genetic variation. Average accuracies from mixed model equations did not change between analyses, showing that using SNP data does not increase information in this data set. These results confirm that genomic selection for Salmonella carrier state resistance in laying hens is promising. Nevertheless, a denser SNP coverage of the genome on a greater number of animals is still needed to assess its feasibility and efficiency.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0032-5791
pubmed:author
pubmed:issnType
Print
pubmed:volume
90
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
731-6
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Use of a reduced set of single nucleotide polymorphisms for genetic evaluation of resistance to Salmonella carrier state in laying hens.
pubmed:affiliation
INRA, UR 631 SAGA, F-31326 Castanet Tolosan, France. andres.legarra@toulouse.inra.fr
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't