title: Genotypic and phenotypic characterization of genetic differentiation and diversity in the USDA rice mini-core collection.
abstract: A rice mini-core collection consisting of 217 accessions has been developed to represent the USDA core and whole collections that include 1,794 and 18,709 accessions, respectively. To improve the efficiency of mining valuable genes and broadening the genetic diversity in breeding, genetic structure and diversity were analyzed using both genotypic (128 molecular markers) and phenotypic (14 numerical traits) data. This mini-core had 13.5 alleles per locus, which is the most among the reported germplasm collections of rice. Similarly, polymorphic information content (PIC) value was 0.71 in the mini-core which is the highest with one exception. The high genetic diversity in the mini-core suggests there is a good possibility of mining genes of interest and selecting parents which will improve food production and quality. A model-based clustering analysis resulted in lowland rice including three groups, aus (39 accessions), indica (71) and their admixtures (5), upland rice including temperate japonica (32), tropical japonica (40), aromatic (6) and their admixtures (12) and wild rice (12) including glaberrima and four other species of Oryza. Group differentiation was analyzed using both genotypic distance Fst from 128 molecular markers and phenotypic (Mahalanobis) distance D(2) from 14 traits. Both dendrograms built by Fst and D(2) reached similar-differentiative relationship among these genetic groups, and the correlation coefficient showed high value 0.85 between Fst matrix and D(2) matrix. The information of genetic and phenotypic differentiation could be helpful for the association mapping of genes of interest. Analysis of genotypic and phenotypic diversity based on genetic structure would facilitate parent selection for broadening genetic base of modern rice cultivars via breeding effort.
authors.affiliation: College of Life Sciences, Zhejiang University, Hangzhou, China.
authors.forename: Xiaobai
authors.initials: X
authors.lastname: Li
authors.forename: Wengui
authors.initials: W
authors.lastname: Yan
authors.forename: Hesham
authors.initials: H
authors.lastname: Agrama
authors.forename: Biaolin
authors.initials: B
authors.lastname: Hu
authors.forename: Limeng
authors.initials: L
authors.lastname: Jia
authors.forename: Melissa
authors.initials: M
authors.lastname: Jia
authors.forename: Aaron
authors.initials: A
authors.lastname: Jackson
authors.forename: Karen
authors.initials: K
authors.lastname: Moldenhauer
authors.forename: Anna
authors.initials: A
authors.lastname: McClung
authors.forename: Dianxing
authors.initials: D
authors.lastname: Wu
mesh_terms: D000483:Alleles; D001947:Breeding; D016000:Cluster Analysis; D040961:Genetic Drift; D005819:Genetic Markers; D014644:Genetic Variation; D005838:Genotype; D012275:Oryza / Q000235:genetics*; D010641:Phenotype; D010802:Phylogeny; D011110:Polymorphism, Genetic; D014481:United States; D016885:United States Department of Agriculture
chemical_list: D005819:Genetic Markers