Davis Lab

Principal Investigators

Charles Langley

University of California at Davis

David Neale

University of California at Davis

Barry Goldfarb

North Carolina State University

Bailian Li

North Carolina State University

Tim Mullin

North Carolina State University

Gary Peter

University of Florida

John Davis

University of Florida

George Casella

University of Florida

Dudley Huber

University of Florida

Carol Loopstra

Texas A&M

Tom Byram

Texas A&M

Agency: National Science Foundation

$5,902,005.00

4 years (9/15/05 - 9/14/09)

Project Overview: Identification of specific genes and alleles controlling naturally occurring phenotypic variation of complex traits is both biologically and economically relevant, providing 1) a greater understanding of trait genetic architecture in plants, 2) an indirect selection tool for tree breeders, and 3) a set of potentially useful genetic reagents for genetic modification. By aggressively seeking to identify most of the major genes controlling specific wood property and disease related traits in loblolly pine, we anticipate a significant breakthrough in our understanding of the genetics of complex traits and the potential economic impact of indirect selection. Marker-aided selection based on desired allelic variants in genes controlling economic traits can be used across pedigrees within both breeding and natural populations. Such a tool would have immediate and beneficial ramifications for applied tree improvement programs by dramatically reducing testing costs and breeding cycle times. Ultimately, such information could be useful in guiding gene conservation efforts and enhancing our ability to cope with the growing challenges of climate change, shifting habitats and evolving pest populations.

Davis Lab Role: Our role is to screen a loblolly pine association population comprised of ~500 clonally propagated genotypes for resistance to two diseases incited by fungal pathogens endemic to the southeastern U.S., fusiform rust (incited by Cronartium quercuum f.sp. fusiforme), and pitch canker (incited by Fusarium circinatum). Genetic parameters and genotype rankings will be calculated and compared to results of a previous screen in an association discovery population. Genotype information will be combined with the phenotype information via association analysis, which is statistical detection of genes responsible for variation in disease resistance.