Linked Life Data

9475759

Source:http://linkedlifedata.com/resource/pubmed/id/9475759

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1998-3-31
pubmed:abstractText
Genetic evaluation by best linear unbiased prediction (BLUP) requires modeling genetic means, variances, and covariances. This paper presents theory to model means, variances, and covariances in a multibreed population, given marker and breed information, in the presence of gametic disequilibrium between the marker locus (ML) and linked quantitative trait locus (MQTL). Theory and algorithms are presented to construct the matrix of conditional covariances between relatives (Gv) for the MQTL effects in a multibreed population and to obtain the inverse of Gv efficiently. Theory presented here accounts for heterogeneity of variances among pure breeds and for segregation variances between pure breeds. A numerical example was used to illustrate how the theory and algorithms can be used for genetic evaluation by BLUP using marker and trait information in a multibreed population.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0016-6731
pubmed:author
pubmed:issnType
Print
pubmed:volume
148
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
507-15
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Genetic evaluation by best linear unbiased prediction using marker and trait information in a multibreed population.
pubmed:affiliation
Department of Animal Sciences, University of Illinois, Urbana 61801, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't