Association Genetics of Natural Genetic Variation and Complex Traits in Loblolly Pine |
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Princiapl Investigator |
David Neale |
University of California - Davis |
Co-Investigators |
Charles Langley |
University of California - Davis |
Gary Peter |
University of Florida |
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John Davis |
University of Florida |
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George Caselle |
University of Florida |
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Dudley Huber |
University of Florida |
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Matias Kirst |
University of Florida |
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Carol Loopstra |
Texas A&M |
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Tom Byran |
Texas A&M |
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Barry Goldfarb |
North Carolina State University |
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Bailian Li |
North Carolina State University |
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Agency |
NSF |
4 Years |
Project Overview:
This project’s goal is to genetically dissect complex traits and understand the relationship between naturally occurring genetic and phenotypic variation in loblolly pine.
Our lab’s specific role as part of this project is to identify heritable differences in gene expression among individuals, and associate SNPs in candidate genes with variation in gene expression, wood quality and disease resistance phenotypes. Associations between SNPs and more than one phenotype reveal pleiotropic effects of individual genes on multiple traits. Heritable differences in mRNA levels have been reported for other organisms, but only recently in our work in forest trees. In Eucalyptus we related quantitative differences in mRNA levels with wood quality and growth QTLs using a linkage mapping approach. This study demonstrated the feasibility of a population genomic approach for identifying allelic variation responsible for gene expression differences in forest trees.
We propose to use a population genomic approach to associate gene expression phenotypes with cis and trans acting loci in loblolly pine. Gene expression phenotyping for association tests will proceed in a two-step manner. In step one, variation in gene expression will be measured using 14K cDNA microarrays with 10 unrelated genotypes, where we expect to identify a large number of genes whose expression varies significantly among genotypes. In the second step, we will use real-time quantitative PCR to measure contributions of 200 gene family members to heritable patterns of expression in the NCSU verification population (to be carried out by Carol Loopstra at TAMU).