Predicting quantitative variation within rice germplasm using molecular markers

• Published in: Heredity 1996-03, Vol.76 (3), p.296-304
• Main Authors: Virk, Parminder S, Ford-Lloyd, Brian V, Jackson, Michael T, Pooni, Harpal S, Clemeno, Tomas P, Newbury, H John
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Biomedical and Life Sciences; Biomedicine; Classical genetics, quantitative genetics, hybrids; Cytogenetics; Ecology; Evolutionary Biology; Fundamental and applied biological sciences. Psychology; Genetics of eukaryotes. Biological and molecular evolution; Human Genetics; original-article; Oryza sativa; Plant Genetics and Genomics; Pteridophyta, spermatophyta; Vegetals
• ISSN: 0018-067X; 1365-2540
• DOI: 10.1038/hdy.1996.43

Diverse Asian rice ( Oryza sativa ) germplasm has been used to identify associations between various quantitative traits and RAPD molecular markers using multiple regression analysis. This has allowed us to predict for other samples of germplasm their performance for traits such as culm length and number, days to flowering, grain width, and panicle and leaf length using only RAPD marker data. Such predictive capability is possible because of the availability of extensive diversity held in genebanks, and can be used in the future to facilitate the exploitation of that biodiversity. More specifically the methodology could facilitate crop improvement by rapid ideotype prediction. For the mapping and isolation of QTLs (genes controlling quantitative traits) the method would provide information to guide the selection of parental material for hybridization and markers expected to show linkage to QTLs. It may also be possible that these associations could lead the way towards marker-assisted selection during breeding programs. In the future, this demonstration of association between markers and easily measured traits could also be extended to the study of important adaptive traits, such as stress tolerance, found either within germplasm collections or in natural populations.