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United States Department of Agriculture

Agricultural Research Service

Title: Sheath Blight Resistance Qtls Identified by Interval Analysis, Stepwise Regression and Discriminant Analysis

Authors
item Pinson, Shannon
item Oard, James - LSU
item Capdevielle, Fabian - LSU

Submitted to: Rice Technical Working Group Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: February 8, 2002
Publication Date: June 1, 2002
Citation: PINSON, S.R., OARD, J., CAPDEVIELLE, F. SHEATH BLIGHT RESISTANCE QTLS IDENTIFIED BY INTERVAL ANALYSIS, STEPWISE REGRESSION AND DISCRIMINANT ANALYSIS. RICE TECHNICAL WORKING GROUP MEETING PROCEEDINGS. 2002. p. 46.

Technical Abstract: Our objective was to map sheath blight QTLs through their linkage with molecular markers using a pure-breeding, replicatable set of nearly 300 recombinant inbred lines (RILs)derived from crossing Lemont and Teqing in order to verify the QTLs that were previously mapped using an earlier generation of this same cross. A second focus of this study was to evaluate edifferent statistical methods for identifying association between molecula markers and phenotypic. Interval analysis (IA)is a widely accepted method for identifying QTLs through genetic linkage with molecular markers, but it is not perfect, and Stepwise Regression (SR) is often used to supplement its results. In this study, we also compare QTLs for sheath blight resistance as identified by a new and emerging statistical method, discriminant analysis (DA). Seven chromosomal regions were previously reported from study of Lemont/Teqing progeny to contain genes for sheath blight resistance (SBR). IA of late-generation RIL data verified three loci; SR verified all seven loci, and DA verified only two. IA and SR co- located putative QTLs more often than did IA and DA; all three statistical methods identified two or more loci not substantiated by any other analysis method or previous reports of QTLs. Only three of the nine loci identified by DA were closely substantiated by IA and/or SR of the RIL data. Whether this means that DA is better or less accurate than IA and SR cannot be determined from present data. The analysis of a set of introgression lines recently provided by Dr. Li at IRRI will allow us to further verify all the putatively identified QTLs.

Last Modified: 12/26/2014
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