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ARS Home » Northeast Area » Kearneysville, West Virginia » Appalachian Fruit Research Laboratory » Innovative Fruit Production, Improvement, and Protection » Research » Research Project #445144

Research Project: Dissecting the Molecular Basis for Dormancy in Trees

Location: Innovative Fruit Production, Improvement, and Protection

Project Number: 8080-21000-033-014-A
Project Type: Cooperative Agreement

Start Date: Sep 25, 2023
End Date: Sep 27, 2023

The objective of the research is to characterize the genomes of various forest and fruit tree species and compare known loci associated with dormancy phenotypes in trees. The work will include genome assembly and analysis of genetic data to identify gene targets for functional analyses.

Understanding the genetic control of tree dormancy and flowering is tantamount to implementing strategies to improve fruit and forest tree performance in the Anthropocene. Significant inroads have been achieved in uncovering the networks of genes and their actions governing phenological traits in model systems but we need to translate these advances to tree species that underpin our agricultural and forest industries, particularly in light of the challenges posed by a rapidly warming climate. Leveraging these model system advances, genes and networks controlling these traits are being assessed in fruit and forest tree materials that exhibit phenotypic variation in dormancy and flowering through QTL mapping and RNAseq analyses. The approach to address the objectives for this cooperative are as follows. 1) ARS and the cooperator will analyze a broad range of tree genomes coupled with RNAseq data of tree buds progressing from late August through budburst in the spring to characterize the gene action of specific dormancy and flowering associated genes and gene networks and to identify additionally important genes and networks potentially controlling these traits. 2) ARS and the cooperator will integrate data from previous and proposed studies in fruit trees with datasets of mapped genomic intervals controlling these traits in key forest tree species to uncover genes and networks in common for controlling these traits. These will be targets of selections for improvement of tree performance.