Development and application of a set of breeder-friendly SNP markers for genetic analyses and molecular breeding of rice (Oryza sativa L.)
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Single nucleotide polymorphisms (SNPs) are the most abundant DNA markers in plant genomes. In this study, based on 54,465 SNPs between the genomes of two Indica varieties, Minghui 63 (MH63) and Zhenshan 97 (ZS97) and additional 20,705 SNPs between the MH63 and Nipponbare genomes, we identified and confirmed 1,633 well-distributed SNPs by PCR and Sanger sequencing. From these, a set of 372 SNPs were further selected to analyze the patterns of genetic diversity in 300 representative rice inbred lines from 22 rice growing countries worldwide. Using this set of SNPs, we were able to uncover the well-known Indica–Japonica subspecific differentiation and geographic differentiations within Indica and Japonica. Furthermore, our SNP results revealed some common and contrasting patterns of the haplotype diversity along different rice chromosomes in the Indica and Japonica accessions, which suggest different evolutionary forces possibly acting in specific regions of the rice genome during domestication and evolution of rice. Our results demonstrated that this set of SNPs can be used as anchor SNPs for large scale genotyping in rice molecular breeding research involving Indica–Japonica and Indica–Indica crosses.
KeywordsRice Genome Polymorphism Information Content Rice Accession East Asia Allele Frequency Difference
We are grateful to Drs. Qifa Zhang and Weibo Xie for sharing the SNP information between MH63 and ZS97 before their publication. We thank Hao Chen, Li Wang, Qiushi Huang, and Tiantian Zhu for their assistances in SNP verification. We appreciate Dr. Judy Lee’s help for manuscript editing. This work was supported by grants from the Bill and Melinda Gates foundation (51587-5), the Ministry of Science and Technology of China (2009DFB30030 and 2010AA101806), the Ministry of Agriculture of China (2008ZX08012-005, 2009ZX08012-021B, 2011-G2B and 2006-G51) and the Generation Challenge Program (#12) of CGIAR.
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