Long term tree breeding as analyzed by the breeding cycler tool

1. Long term tree breeding as analyzed by the breeding cycler tool DaDa (Dag & Darius) or (Darius & Dag)

2. Information on the net… http://www.genfys.slu.se/staff/dagl/ This seminar has a homepage with useful information for further discussions about long-term breeding. In particular we try to formulate a document with possible implications The breeding cycler EXCEL tool is on the web. It is free to anyone to make own assumptions or developments. We would be happy to help.

3. Breeding cycler and the road to it… Breeding cycler and the road to it Message: Breeding cycler contains accumulated knowledge over several decades

4. Earlier formula handling • Ca 1976 I made calculations for the efficiency of progeny testing. Progenies in Swedish tree breeding appeared much too large to be efficient (they are now smaller) • 1983 I was in Australia and thought clone testing was good, and this could be supported by calculations. I contacted Martin Werner • That resulted in gain equations in year book and later (1988) in spruce proceeding on a sib seed orchard based on clonal tested full sibs (with more precise gain formulas formulated in cooperation with Öje Danell). • It dealt with key elements simultaneously: gain, diversity, cost, time and technique, but in a clumsy way.

5. “GAINPRED” was developed • Deterministic Excel-based simulator available to the World at my “Tree Breeding Tool” web site was developed. • I believed at that time that the World would gratefully receive the tools offered. But that was a disappointment, the only users seem to be my collaborators. But the tools were useful in producing papers by me and collaborators (even for collaborators operating independent). That has contributed to that I may appear a bit scientific narrow, but otherwise been fruitful. • Rosvall et al 2001 SkogForsk redogörelse 1 is inspired from gain pred • Gain pred is linear, it goes from plus tree selection over some breeding activities to seed orchards. • It was later developed to Breeding Cycler for a long-term benefit

6. Let's put all homologous genes in a pool Take two (at random with replacement). The probability for IBD is group coancestry. f Key-problem: How to deal with relatedness, effective number and gene diversity Solution: Group coancestry (equivalent Status number, New Zealand, Xmas 1993)

7. Gene diversity and group coancestry GD = 1 - group coancestry = the probability that the genes are non-identical, thus diverse. Group coancestry is a measure of gene diversity lost!

8. Mating Components of Tree Breeding Gain Initiation Plus trees Seed orchard Long-term breeding Testing Selection

9. Long term breeding goes on for many repeated cycles Mating Long-term breeding Testing Selection

10. Initiation Gain Plus trees Seed orchard Testing? Mating? GainPred is linear Non-repeated activities instead of repeated in cycles

11. Breeding cycler studies what happens in one complete cycle Mating Long-term breeding Testing Selection

12. During one complete cycle The breeding value increases The gene diversity decreases Long-term breeding How to assign a single value to the increase in breeding value and the decrease in gene diversity?

13. Group merit weighted average of Breeding Value and Gene Diversity Weight = “Penalty coefficient”; depends on the specific circumstances Lindgren and Mullin 1997

14. Inbreeding follows group coancestry Simulation of Swedish Norway spruce breeding programby POPSIM, BP=48, DPM, equal representation (2/parent) 0.08 Message: Group coancestry can often be regarded as a potential inbreeding, which becomes realized some generations later 0.06 f Probability of identity by descent 0.04 0.02 0 0 2 4 6 8 10 Generations Rosvall, Lindgren & Mullin 1999

15. During one complete cycle The cycle takes a number of years, depending on the duration of testing, mating and different waiting times Mating Long-term breeding Testing Selection How to consider the cycle time?

16. Progress in annual Group Merit considers three key factors: • Genetic gain; • Gene diversity; • Time. Wei and Lindgren 2001

17. During one complete cycle Costs during a cycle is depending on number of test plants, mating techniques, testing strategy etc. Mating Long-term breeding Testing Selection How to consider the cost?

18. Annual Group Merit progress at a given annual cost considers four key factors: • Genetic gain; • Gene diversity; • Time; • Cost. Danusevicius and Lindgren 2002

19. Earlier there were analogous equivalents…

20. But now we have digital ways..

21. We have thought a lot on how to get the cycler good and relevant

22. Breeding cycler is based on within family selection Acknowledgement: Large thanks to Swedish breeding for giving us the justification to construct a reasonable simple breeding cycler, that is balanced and where each breeding pop member get exactly one offspring in next generation breeding population. Loss of gene diversity is only a function of Breeding Population Size. It would have been much harder without this simplification! DaDa

23. Examples of what Breeding Cycler can do • Which is the best testing strategy • What is optimum breeding population size? • What is the influence of the parameters? • When to select and what numbers to test ? • Where to allocate resources to strengthen your breeding plan?

24. How the Cycler works (in principle) Size of breeding population? Test methodClone?Progeny? Mating • Inputs • Genetic parameters • Time components • Cost component Long-term breeding Selection age ? Testing size ? Find resource allocation that maximises GM/year?

25. How the Cycler works… Inputs Results You do almost nothing – input the parameters and look for result

26. Variables - Genetic parameters • Additive variance in test • Dominance variance in test • Environmental variance in test • Coefficient of variance for additive “value for forestry” at mature age • Breeding population size

27. Time and cost components Cycle cost • Recombination (cost can be either per BP member or in total) • Cost per tested genotype (it costs to do a clone or a progeny) • Test plant can be economical unit Under budget constraint Cycle time • Recombination • Time for e.g. cloning or creation of progeny • Production of test plants • Testing time (actually usually calculated from other inputs (annual cost) • Note that a longer cycle allows higher cost during the cycle

28. Variables - Others • Rotation time (for J*M considerations) • Annual budget (the most important factor as any breeder knows) • Test method (clonal, progeny or phenotype) • J*M development curve • Weighting factor for diversity versus gain

29. J-M correlation is important Choice can be made of J-M function including custom, Lambeth and Dill 2001 (genetic) is our favourite.

30. How the Cycler work Insert all red values (or let them remain at the initial choices). The worksheet will calculate the blue values with information of the consequences of your choices. You may use the tool just to compare alternatives. Technical Tip: It may be a good idea to use empty space on the worksheet to note outcomes of different alternatives.

31. To optimise with breeding cycler • Choose the red inputs to be optimised • Input relevant values for the other parameters • Let “EXCEL SOLVER” find the values (allocation) which maximise progress in group merit