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United States Department of Agriculture

Agricultural Research Service

Title: Analysis of Qtl Associated with the Allelopathic Effect of Rice Using Water-Soluble Extracts

Authors
item Ebana, Kaworu - NIAR, TSUKUBA, JAPAN
item Yan, Wengui
item Dilday, Robert - USDA ARS RETIRED
item Namai, Hyoji - UNIV TSUKUBA, JAPAN
item Okuno, Kazutoshi - NIAR & HNAES, JAPAN

Submitted to: Journal of Breeding Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 3, 2000
Publication Date: N/A

Interpretive Summary: Fighting with weeds by chemical and physical means is one of the major operations in farming. Allelopathic activity in rice can be potentially useful in controlling useful in controlling weeds biologically in the rice field. Seven quantitative trait loci (QTL) associated with the allelopathic effect were identified by RFLP markers on chromosome 1, 3, 5, 6, 7, 11 and 12 in rice. The QTL on chromosome 6 had the largest effect on expression of the allelopathic effect of rice and explained 16.1% of the phenotypic variation. The remaining six QTL explained the variation in the range of 9.4 to 15.1%. The genetic information from the present study is important for breeders to integrate allelopathic gene(s) into rice cultivars for biological control of weeds, and for chemists to identify compounds responsible to rice allelopathy.

Technical Abstract: Quantitative trait loci (QTL) associated with the allelopathic effect of rice (Oryza sativa L.) were identified using RFLP markers. The allelopathic effect was assessed by the growth inhibition of water- soluble extracts from the rice seedlings on lettuce seedlings. QTL analysis was carried out using the F2 population from the cross between an Indica type line PI312777 (highly inhibitory) and a Japonica cultivar Rexmont (less inhibitory). Seven QTL were identified on chromosomes 1, 3, 5, 6, 7, 11 and 12. One of the QTL on chromosome 6 had the largest effect on the expression of the allelopathic effect of rice and explained 16.1% of the phenotypic variation. The other six QTL explained the3 variation in the range from 9.4% to 15.1%. A multiple QTL model estimated that five QTL with LOD scores higher than 3.0 explained 36.6% of the total phenotypic variation. Digenic interactions in five pairs between the seven QTLs were detected.

Last Modified: 11/22/2014
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