Location: Plant Genetic Resources
Title: Comparative Gene Expression Of Architectural And Nutritional ESTs In Apple Root, Leaf And Stem Tissues Authors
Submitted to: Plant and Animal Genome Conference
Publication Type: Other
Publication Acceptance Date: December 15, 2009
Publication Date: January 9, 2010
Citation: Adhikary, D., Baldo, A.M., Fazio, G. 2010. Comparative Gene Expression Of Architectural And Nutritional ESTs In Apple Root, Leaf And Stem Tissues. Plant and Animal Genome Conference. Technical Abstract: There are number of phenotypic traits conferred by apple rootstock upon the scion and desirable rootstock traits. In an attempt to identify genes which may be responsible for these traits, we have used the public expressed sequences (ESTs and cDNA) to identify genes expressed uniquely in apple rootstock. 203,2211 EST and cDNA sequences from apple were downloaded, screened for vector and separated into 9,228 from root and 193,993 non-root tissues. Each set of sequences was separately clustered (root: 1,868 contigs, 3247 singletons) and 189 contigs and 955 singletons expressed in root tissue had no match among the non-root sequences (Blast E-value>1E -20). These sequences were annotated against SwissProt and the Genbank NR databases and annotations were used as a basis for the selection of genes potentially involved in hormone and other developmental pathways. Unique primers were designed and used to compare the gene expression in roots vs stems and leaves. Forty three primer pairs were designed for this study based on the above contigs and singletons. Apple rootstock G.41 leaf, stem and root tissues were utilized to assay expression levels in this experiment. Out of 43 amplicons, 8 were primarily were expressed in roots. Seven of the genes were expressed more in stems than in leaves and roots; three genes were more highly expressed in stem and root than in leaf; two genes were found to be more highly expressed well in stem and leaf than in root. Eight genes were more highly expressed in leaf tissue. These data are being utilized to identify candidate genes for selection of superior apple rootstocks.