About the Conifer Translational Genomics Network

Background and Significance

Collectively, conifers may be the most economically and ecologically important crop in the US.

Globally, the gross value of the forestry sector, including manufacturing, is estimated to be US $354 billion, or about 1.2% of GDP (FAO, 2005). A third of the United States is covered by forestland and the American forest products industry contributes ~$50 billion annually to the income of ~ 1.6 million workers and their families. Southern pines alone provide ~58% of the timber in the US and 15.8% of the world's timber (Wear and Greis, 2002). Douglas-fir contributes a third of all U.S. log exports and over eight billion board feet of lumber annually (Howard, 2001; Howe et al., 2006). Collectively, timber is among the most highly valued commodities in America. Viewed as an agricultural crop, only corn currently exceeds timber in farmgate value on an annual basis. Loblolly, the principal southern pine, is the dominant tree species on 11.7 million ha of native forest (Baker and Langdon, 1990) and is established on over 12 million ha of plantation (Byram, 1999). Slash pine is the predominant tree species throughout Florida and the southern portion of the Gulf States. Douglas-fir grows on nearly 17 million ha, three million of which are in plantations (Smith et al., 2001). It is likely that what is learned in these species will have utility across much of the Pinaceae, a family containing most of the commercially important conifers of the world. The genus Pinus alone contains more than 110 species, or about 20% of all known gymnosperms (Richardson and Rundel, 1998).

Summary

The goal of the Conifer Translational Genomics Network (CTGN) is to bring marker based breeding to application, within the next five years, for tree breeding cooperatives that provide over 1.3 billion seedlings annually in the United States. Marker based breeding will have significant impact in conifers due to:

(1) Long breeding cycle times
(2) Biological and societal limits to genetic engineering
(3) Abundant genetic variation that can be accessed through markers
(4) Rapid decline of linkage disequilibrium

These allow SNPs within candidate genes to be directly associated with phenotypes. We will leverage over 50 years of tree breeding experience and population development with 15 years of experience in the molecular dissection of complex traits to further develop MAS/MAB tools that accelerate the rate of tree breeding. SNP by quantitative trait associations will be validated by genotyping 10,000 trees for 1536 select SNPs in operational breeding populations. New modules for handling conifer data will be added to TASSEL. Methods for implementing MAS/MAB in applied tree breeding programs will be defined and economically evaluated using assumptions derived from study results. Project outcomes will be delivered directly to breeders and documented in databases maintained on the web at the Dendrome/TreeGenes site.

An assertive and comprehensive education and outreach program will provide widespread training for school teachers, undergraduate and graduate students, tree breeders, managers, lay-people and other stakeholders.

The CTGN will draw from or deliver to virtually all conifer genomics scientists and tree breeders in the United States.

Goals and Objectives

The goal of the Conifer Translational Genomics Network (CTGN) is to bring marker based breeding to application within the next five years for the major tree breeding Cooperatives in the United States.

Extensive efforts within the conifer genomics community (see Figure 1 for complete legend) have culminated in our ability to genetically dissect complex traits of economic and ecologic significance in forest trees, to understand the relationship between naturally occurring genetic and phenotypic variation in those traits, and to develop tools that accelerate the rate and improve the efficiency of tree breeding. We are using association genetics and single nucleotide polymorphisms (SNPs) in candidate genes to link genes to phenotypes in loblolly pine (Pinus taeda L.) and Douglas-fir (Pseudotsuga menziesii [Mirb] Franco). Using this approach, we identified dozens of significant associations between candidate genes and important phenotypes (see Table 2). To be used in breeding programs, associations discovered in experimental populations must be validated (Objective 1.0) in advanced generation breeding populations. This will be done by genotyping 10,000 trees for 1536 select SNPs in operational breeding, testing, and deployment populations of loblolly pine, slash pine (Pinus elliottii Engelm.), and Douglas-fir. In addition, we will develop improved methods for detecting marker-trait associations and for finding complementary ways to combine phenotypic selection and MAS in conifers (Objective 2.0). We will continue to develop our extensive databases and web-based tools (Dendrome/Treegenes) to serve the CTGN and the larger community ( Conifer Genome Network; Objective 3.0) and we will undertake an assertive and comprehensive education and outreach program ($535,000/4yr) that will reach all levels of stakeholders and end-users (Objective 4.0).