1. Harnessing the hidden genetic diversity for improving multiple abiotic stress tolerance in rice (Oryza sativa L.).
- Author
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Jauhar Ali, Jian-Long Xu, Yong-Ming Gao, Xiu-Fang Ma, Li-Jun Meng, Ying Wang, Yun-Long Pang, Yong-Sheng Guan, Mei-Rong Xu, Jastin E Revilleza, Neil J Franje, Shao-Chuan Zhou, and Zhi-Kang Li
- Subjects
Medicine ,Science - Abstract
To develop superior rice varieties with improved yield in most rainfed areas of Asia/Africa, we started an introgression-breeding program for simultaneously improving yield and tolerances of multiple abiotic stresses. Using eight BC1 populations derived from a widely adaptable recipient and eight donors plus three rounds of phenotypic selection, we developed 496 introgression lines (ILs) with significantly higher yield under drought, salt and/or non-stress conditions in 5 years. Six new varieties were released in the Philippines and Pakistan and many more are being evaluated in multi-location yield trials for releasing in several countries. Marker-facilitated genetic characterization revealed three interesting aspects of the breeding procedure: (1) the donor introgression pattern in specific BC populations was characteristic; (2) introgression frequency in different genomic regions varied considerably, resulting primarily from strong selection for the target traits; and (3) significantly lower heterozygosity was observed in BC progenies selected for drought and salinity tolerance. Applying strong phenotypic selection under abiotic stresses in early segregating generations has major advantages for not only improving multiple abiotic stress tolerance but also achieving quicker homozygosity in early generations. This breeding procedure can be easily adopted by small breeding programs in developing countries to develop high-yielding varieties tolerant of abiotic stresses. The large set of trait-specific ILs can be used for genetic mapping of genes/QTL that affect target and non-target traits and for efficient varietal development by designed QTL pyramiding and genomics-based recurrent selection in our Green Super Rice breeding technology.
- Published
- 2017
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