Development of an allele-mining set in rice using a heuristic algorithm and SSR genotype data with least redundancy for the post-genomic era

• Published in: Molecular breeding Vol. 26; no. 4; pp. 639 - 651
• Main Authors: Zhao, Weiguo, Cho, Gyu-Taek, Ma, Kyung-Ho, Chung, Jong-Wook, Gwag, Jae-Gyun, Park, Yong-Jin
• Format: Journal Article
• Language: English
• Published: Dordrecht Dordrecht : Springer Netherlands 01.12.2010; Springer Netherlands; Springer Nature B.V
• Subjects: Algorithms; Allele mining; Alleles; Biomedical and Life Sciences; Biotechnology; Collection; Gene frequency; Genetic diversity; genetic variation; Genetics; Genomes; Genomics; Genotypes; Heuristic; Heuristic approach; Heuristic methods; Life Sciences; Markers; Molecular biology; Oryza; Plant biology; Plant Genetics and Genomics; Plant Pathology; Plant Physiology; Plant Sciences; Redundancy; Rice; Simple sequence repeats (SSRs); Starch; Allele mining; Genetic diversity; Heuristic approach; Rice; Simple sequence repeats (SSRs)
• ISSN: 1380-3743; 1572-9788
• DOI: 10.1007/s11032-010-9400-x

The allelic diversity of a collection of 4046 rice accessions was assessed using 15 neutral SSR markers distributed throughout the genome. A total of 482 alleles were detected; the average allelic richness was 32.1 alleles per locus. Using a heuristic approach, an allele-mining set was successfully developed on the basis of SSR marker data. 162 accessions of the allele-mining set, accounting for about 4.0% of the entire collection, captured all of the alleles (482) retained in the entire collection, which showed 100% coverage of alleles with minimum redundancy. As a result of validation of this heuristic approach using another 14 SSR markers associated with starch, 70% of the total alleles and 83% of the restricted alleles (allele frequency > 0.05%) were captured in this allele-mining set. The results showed that the heuristic approach meets the condition as an allele-mining set even when applied to another specific set of markers related to starch synthesis in the same entire and allele-mining set. The newly developed methodology for developing allele-mining sets can be used in other crop species. By retaining all alleles of the entire collection, this allele-mining set will be useful for future studies on introducing unused useful alleles into elite rice varieties by breeders in the post-genomic era.