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ARS Home » Research » Publications at this Location » Publication #259394
Title: Phylogenetic relationships among Maloideae species

Author
item Volk, Gayle
item Richards, Christopher
item Baldo, Angela

Submitted to: Government Publication/Report
Publication Type: Government Publication
Publication Acceptance Date: 11/1/2010
Publication Date: 11/14/2010
Citation: Volk, G.M., Richards, C.M., Baldo, A.M. 2010. Phylogenetic relationships among Maloideae species. Meeting Abstract. 5th International Rosaceae Genomics Conference, November 14-17, 2010. South Africa. pp. O52.

Interpretive Summary: Genetic relationships among the species of apple and pears have not been fully elucidated. When the relatedness among species is known, it becomes possible to evaluate the completeness of the apple and pear accessions within the USDA-ARS National Plant Germplasm System collections. Sequencing chloroplast regions allowed us to differentiate species. Wild species could be separated based on their geographic regions of origin.

Technical Abstract: The Maloideae is a highly diverse sub-family of the Rosaceae containing several agronomically important species (Malus sp. and Pyrus sp.) and their wild relatives. Previous phylogenetic work within the group has revealed extensive intergeneric hybridization and polyploidization. In order to develop a framework for estimating diversity above the species level within the accession holding within USDA-ARS National Plant Germplasm system, we sampled 150 species representing 16 genera within the Maloideae from the Plant Genetic Resources Unit Geneva, NY and National Clonal Repository in Corvallis, OR. Sequence data taken from 7 chloroplast regions representing ~2.5 kb were collected from up to 10 individual genotypes for each of the nearly 800 accessions. Results indicate high levels of diversity of haplotypes with over 200 SNPs identified. These data can be used not only to organize and validate this important collection but can serve as the basis for further comparative studies aimed at integrating nuclear, plastid and quantitative data.