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Title: MULTIPLE REGRESSION AND MIXED MODEL METHODS TO MEASURE EFFECTS OF MOLECULARMARKERS ON PREDICTION OF QUANTITATIVE TRAITS FROM INBRED POPULATIONS

Author
item VAN ZYL, C. - UNIV. OF NEBR., LINCOLN
item Van Vleck, Lloyd
item JOHNSON, B. - UNIV. OF NEBR., LINCOLN
item SMITH, H. - PIONEER HYBRID,JOHNSON,IA

Submitted to: Gordon Research Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 2/9/1997
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The objective of this pilot study with corn as model was to determine if markers might be associated with genes that affect quantitative traits of progeny of inbred parental lines. Phenotypic data were obtained from F1 progeny resulting from matings between stiff stalk synthetic (SSS) and non- stiff stalk synthetic (NSS) heterotic groups of inbred lines. Marker information from 28 parental lines per heterotic group with 121 markers wa spread through the 10 chromosomes. Data for nine traits on related sets of single crosses were evaluated with derivative-free restricted maximum likelihood. Four models were used. In the basic model, lines in SSS were considered fixed and variance of lines in NSS was estimated with relationships among lines considered. The model of comparison also included marker alleles from NSS lines as covariates. Corresponding models considered lines in NSS as fixed and variance of lines in SSS was estimated dwith relationships considered. This procedure was used in an attempt to avoid confounding of marker alleles of one heterotic group and line effects of the other heterotic group. Covariates used with multiple regression of performance on marker alleles were entered on sequential basis. Markers on chromosomes other than chromosome one completely confounded with markers on chromosome one were subsequently deleted from the analysis. The log likelihood increased for all but one of nine traits when the twenty remaining sets of markers were included in the analysis when either SSS or NSS lines were considered as random effects. With marker information included, estimates of variance among SSS lines increased for six traits and estimates of variance among the NSS lines increased for all traits.