GENETIC DIVERSITY AND POPULATION STRUCTURE IN RICE

¹ Cornell University, 240 Emerson Hall, Ithaca, NY, 14853, USA

² Cornell University, 175 Biotechnology Bldg, Ithaca, NY 14853, USA

³ USDA/ARS/DBNRRC, 2890 Hwy 130 E, Stuttgart, AR, 72160, USA

⁴ Cornell University, 439 Warren Hall, Ithaca, NY, 14853, USA

⁵ FARA, PMB CT 173 Cantonments, 2 Gowa Close, Roman Ridge, Accra, Ghana

⁶ USDA/ARS/CPGRU, One Shield Avenue, Plant Pathology Dept., Davis, CA, 95616

Understanding the population structure of an organism is critical to the interpretation of molecular diversity. In domesticated species, the breeding system and the complexity of the breeding history may result in significant population structure. Within Oryza sativa, there is a well-established divergence between the indica and japonica subspecies, however a higher degree of resolution of population structure is required in order to effectively utilize population-based approaches such as linkage disequilibrium and association mapping. In this study, a sample of 236 pure lines of O. sativa was genotyped at 169 nuclear and two chloroplast loci. Five distinct populations were detected, corresponding to indica, aus, aromatic, temperate japonica and tropical japonica rices. Nuclear and chloroplast data support a closer evolutionary relationship between the aus with indica and aromatic with tropical japonicas, but all groups are sufficiently distinct to be considered separate populations. In parallel, a collection of 198 O. glaberrima accessions was genotyped at 93 SSR loci, and significant population structure was also observed. Five distinct sub-groups were detected within the collection of O. glaberrima, three of which were associated with significant phenotypic differences corresponding to ecologically distinct clusters of germplasm, and two of which clustered with indica and japonica varieties of O. sativa, reflecting a history of co-cultivation of the two species in West Africa. The population differences in diversity within Asian and African rice can be explained through differences in their demographic history. Using this framework of genetically defined populations, it may be possible to exploit the rice gene pools more effectively using population genetics-based approaches and the extensive rice genetic resources collection.