Identification of reliable QTLs and designed QTL breeding for grain shape and milling quality in the reciprocal introgression lines in rice

Author:

Emelin Mwenda,Qiu Xianjin,Fan Fangjun,Alamin Md.,Faruquee Muhiuddin,Hu Hui,Xu Junying,Yang Jie,Xu Haiming,Ali Jauhar,Liu Bailong,Shi Yumin,Li Zhikang,Zhang Luyan,Zheng Tianqing,Xu Jianlong

Abstract

AbstractMilling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers’ final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.

Funder

National Nature Science Fund of China

Guangxi Key Laboratory of Rice Genetics and Breeding

Bill & Melinda Gates Foundation

National Key Research and Development Program of China

Key Special Program

Chinese Academy of Agricultural Sciences

Key Research and Development Program of Hainan

Publisher

Springer Science and Business Media LLC

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