W286 Conifer Translational Genomics Network: Bringing Genomics Based Breeding To Application

Date: Sunday, January 15, 2012
Time: 10:00 AM
Room: Sunrise
Ross Whetten , North Carolina State University, Raleigh, NC
Tom Byram , Texas Forest Service, College Station, TX
Nicholas Wheeler , Oregon State University, Corvallis, OR
Steven McKeand , North Carolina State University, Raleigh, NC
Fikret Isik , North Carolina State University, Raleigh, NC
Dudley Huber , University of Florida, Gainesville, FL
Glenn Howe , Oregon State University, Corvallis, OR
C. Dana Nelson , Southern Institute of Forest Genetics, USDA Forest Service, Saucier, MS
Brad St Clair , USDA Forest Service, Corvallis, OR
Jill Wegrzyn , University of California, Davis, Davis, CA
David Neale , University of California, Davis, Davis, CA
The Conifer Translational Genomics Network (CTGN) consisted of researchers from six institutions representing genomics laboratories, USDA Forest Service research projects, and four tree improvement cooperatives that develop germplasm for most of the conifer planting stock used in the United States.  The goal of the CTGN project was to provide tree breeders with genomic based tools to make traditional tree breeding both more effective and efficient.  The four year project, funded by the USDA National Institute for Food and Agriculture (formerly CSREES) and the USDA Forest Service from 2007 to 2011, sought to leverage more than 50 years of traditional population development conducted by the tree improvement cooperatives with new genomic analysis technologies and analytical methods. Additional activities supported by the project included comprehensive education and outreach programs and the development of genetic stock centers for both southern pine and Douglas fir.  While each institution had its own research emphasis, all carried out genotyping large numbers of single nucleotide polymorphisms (SNPs) for substantial numbers of individual trees.  These data have been and will continue to be used to characterize genetic variation in managed populations, seek signatures of natural and artificial selection, and improve selection efficiency through marker-trait association and development of better analytical tools.  Just as the CTGN was built on previous research, one of its chief accomplishments has been to provide impetus and tools for future projects, most notably the recently announced Pine Reference Sequence Project and the Southern Pine Climate Change Mitigation and Adaptation Project.  A brief overview of significant progress emerging from the CTGN will be presented.