1. ¹Department of Plant Sciences, University of California, CA, USA
2. ²Department of Forest Systems and Resources, Forest Research Institute, CIFOR-INIA, Madrid, Spain
3. ³School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA
4. ⁴Institute of Forest Genetics, Pacific Southwest Research Station, USDA Forest Service, Davis, CA, USA

Correspondence: Professor DB Neale, Department of Plant Sciences, University of California at Davis, One Shields Avenue, Davis, CA 95616, USA. E-mail: dbneale@ucdavis.edu

Received 29 August 2007; Revised 28 January 2008; Accepted 11 March 2008; Published online 14 May 2008.

Abstract

Dissection of complex traits that influence fitness is not only a central topic in evolutionary research but can also assist breeding practices for economically important plant species, such as loblolly pine (Pinus taeda L). In this study, 46 single nucleotide polymorphisms (SNPs) from 41 disease and abiotic stress-inducible genes were tested for their genetic association with carbon isotope discrimination (CID), a time-integrated trait measure of stomatal conductance. A family-based approach to detect genotype/phenotype genetic association was developed for the first time in plants by applying the quantitative transmission disequilibrium test on an association population of 961 clones from 61 families (adopted from previous breeding programs) evaluated for phenotypic expression of CID at two sites. Two particularly promising candidates for their genetic effects on CID are: dhn-1, involved in stabilization of cell structures, and lp5-like, a glycine rich protein putatively related to cell wall reinforcement proteins, both of which were shown in previous studies to be water-deficit inducible. Moreover, association in lp5-like involves a nonsynonymous mutation in linkage disequilibrium with two other nonsynonymous polymorphisms that could, by acting together, enhance overall phenotypic effects. This study highlights the complexity of dissecting CID traits and provides insights for designing second-generation association studies based on candidate gene approaches in forest trees.