Unlocking the genetic diversity of the undomesticated rice relative Oryza longistaminata

Plant breeding;Rice;Crop wild relatives;Oryza

Labroo, Marlee Rose ; Moose, Stephen P., ; ,Lipka, Alexander E. ; Sacks ; Erik J.

关键词: Plant breeding;    Rice;    Crop wild relatives;    Oryza;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/98308/LABROO-THESIS-2017.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Rice (Oryza sativa) is a crucial part of the global food supply. Meeting projected increases in demand, which are rising fastest in sub-Saharan Africa, while using resources efficiently and adapting to a changing climate will require new sources of variation for trait improvement. The genetically diverse undomesticated African rice, Oryza longistaminata, which is native to a broad range of habitats throughout sub-Saharan Africa, is a valuable resource improving O. sativa with genes conferring biotic and abiotic stress tolerances, increased yield, super-ratooning ability, and floral traits conducive to hybrid rice production. The major obstacle to utilization of O. longistaminata in breeding programs is a breeding barrier which complicates interspecific hybridization with O. sativa, as well as the expense and difficulty of identifying which O. longistaminata accessions carrying useful genes. Breeding programs also rely on thorough ex-situ conservation of O. longistaminata, which enables long-term access to germplasm for breeders and other stakeholders. In this work, three genetic subpopulations were identified in O. longistaminata using individuals representing most of the species’ range genotyped with densely-spaced, genome-wide molecular markers. Spontaneous interspecific hybrids of O. longistaminata and O. sativa were discovered in germplasm from the International Rice Research Institute’s genebank, which can be used to accelerate introgression from O. longistaminata to O. sativa. A species distribution model of O. longistaminata was generated to identify sampling gaps in ex-situ collections, and environmental data was used to predict likely locations of O. longistaminata tolerant to abiotic stresses.