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United States Department of Agriculture

Agricultural Research Service

Title: Confirmation and Further Mapping of Sheath Blight Resistance Qtls in Rice Using Interval Anaylyis, Stepwise Regression and Discriminant Analysis of Ril Data

Authors
item Pinson, Shannon
item Oard, James - LA STATE UNIV
item Capdevielle, Fabian - LA STATE UNIV
item Marchetti, Marco - COLLABORATOR

Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: October 11, 2002
Publication Date: January 11, 2003
Citation: PINSON,S.R., OARD,J.H., CAPDEVIELLE,F.M., MARCHETTI,M.A., CONFIRMATION AND FURTHER MAPPING OF SHEATH BLIGHT RESISTANCE QTLS IN RICE USING INTERVAL ANAYLYIS, STEPWISE REGRESSION AND DISCRIMINANT ANALYSIS OF RIL DATA, PLANT AND ANIMAL GENOME CONFERENCE PROCEEDINGS, 2003. p. 158.

Technical Abstract: One method for confirming the existence of QTLs is to identify the loci in multiple populations and/or environments. The literature contains two publications reporting the location of QTLs affecting sheath blight resistance (SBR) in rice (Oryza sativa L.). Unfortunately, the two studies do not corroborate each other, leaving a total of 12 QTLs unconfirmed. Marker assisted selection of this very important trait will not proceed without confirmed QTLs. Both of the published SBR QTL studies were based on evaluation of early-generation materials. Their linkage analyses were confounded by genetic heterozygosity and by imprecise phenotypic data due to limitations in plot size and/or replication. The present study sought to confirm and further map SBR QTLs using a set of nearly 300 recombinant inbred lines (RILs) derived from `Lemont' x `Teqing' in a replicated trial. These RILs were in fact F2:10 progeny of the early-generation population evaluated in the earliest rice SBR QTL publication. The identification of QTLs in these RILs was further enhanced by the use of three statistical methods for identifying marker-trait linkage-interval analysis (IA), a widely accepted but imperfect method for identifying QTLs; Stepwise Regression (SR), often used to supplement IA; and discriminant analysis (DA), an emerging statistical method reportedly less sensitive to population structure than IA. This analysis of RIL data confirmed the existence of 10 of the 12 previously reported SBR QTLs, and putatively identified seven additional loci. DA appears useful for identifying marker-trait linkages, though IA and SR co-located QTLs more often than IA and DA.

Last Modified: 12/19/2014
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