Each objective trait has a corresponding economic weight and, along with the genetic and phenotypic relationships between the objective traits and the selection traits (the traits that are measured at selection age, ~6 to 10 years), selection index coefficients for each selection trait can be derived. The selection index is used to identify parent candidates for the next round of crossing and selection.
The economic weights have been derived using a bio-economic model that projects out to sometime in the future, say 40 years. Other uncertainties inherent in the calculation of a selection index for radiata pine is the estimates of correlations between selection age traits and rotation age traits (genetic parameters). The RPBC in collaboration with the University of Canterbury and PhD candidate Arturo Bascunan are redeveloping a bio-economic model to derive breeding objectives. The main aim of this project is to use this model to identify superior trees that will still perform well at harvest age under various future economic scenarios. It will also allow us to assess the strategic importance in future of the different traits being considered currently for breeding improvement and deployment.
Its application will profoundly impact on driving genetic gain.
RPBC will integrate genomic selection with forward selection and regional clonal testing as the key intervention to almost double genetic gain per unit time and substantially reduce the deployment time of new, genetically-improved, planting stock in commercial forests.
By studying the patterns of these markers in trees that already have their traits measured (a “training population”), we start to build a picture of how these patterns could be used to make predictions in trees that haven’t yet been measured. With a good set of markers and strong prediction models between the resulting fingerprint and the traits, it’s possible to screen and select elite trees at the seedling stage, reducing the need for field testing and speeding up the delivery of gain into the next generation of trees.
With DNA fingerprints, we can also confirm the identity of clones, reveal hidden relatedness and recover (and confirm) the true pedigree of trees. Access to accurate pedigree information further increases the accuracy of prediction model and breeding value estimates, and enables a more streamlined approach to the management of inbreeding.
Implementation will be via the operational programmes of the RPBC, and through the interface with seed orchards and clonal producers - the pathway to market for radiata pine germplasm.
This GS platform will provide step-change gains to industry and contribute to knowledge from other molecular technologies. Together with the Pinus radiata genome sequencing project underway at Scion, the RPBC’s genomic selection research will contribute to furthering other genetic technologies currently being researched.
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This requires the development of a core collection that captures the genetic diversity for conservation in various forms, such as
in situ stands, seed banks and cryo-preservation. This will require the collation and storage of eco-geographic, molecular, pedigree, genetic and phenotypic data in order to characterise, define and develop a core set. This will allow an efficient long-term genetic conservation policy for industry good that will move us away from an over-reliance on impromptu establishment of in situ forest stands.
A nucleus of top performing parents is being selected for cross-pollination and subsequent production of SE clonal progenies. These will be cryopreserved, genotyped and clonally-tested in NZ and Australian trial sites alongside non-SE clonal progenies. This will allow extraction post-testing and faster multiplication of selected clones either for further shareholder (region-specific) testing and/or entry into seed orchards as seed parents, or as a more expeditious and direct route for deployment to the production forest as tested clones.
There is also an opportunity to make more rapid genetic gains whilst relaxing some constraints on relatedness within the nucleus compared with the wider breeding population (where it is necessary to maintain a certain population size to constrain the rate of inbreeding). SE testing will be integrated with clonal testing of the general breeding population and will use genomic selection for more informed decision making.