Size of breeding population Dag Lindgren and Darius Danusevicius DaDa March 2004 For some reason all slides are not visible from my portable, but from.

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Presentation transcript:

Size of breeding population Dag Lindgren and Darius Danusevicius DaDa March 2004 For some reason all slides are not visible from my portable, but from other computers

Start with two other matters  The Swedish long-term breeding is still rather open as most of it has not really started yet, thus easy to reconsider.  A number of possible limitations on breeding cycler has to be mentioned and discussed

Swedish long-term breeding - Intentions 20+ subpopulations with BP=50+ (Gpop and Tpop) for spruce and pine Norway spruce  Karlsson & Rosvall (1993) suggest 40*14 ramets per parent in a 20 year cycle Scots pine  Wilhelmsson & Andersson (1993) made a suggestion, which depends on the success of progeny-testing F1 uncertain cycling time

Swedish spruce breeding status 2002 per subpopulation

Year 50 P, dpm 500 F1 Candidates Station pc F2 progeny trials evaluation F2 selection 50 F1, dpm Standard pine strategy Picture stolen from Bengt Andersson

Swedish Scots pine breeding status 2002 per subpopulation

Scots pine - addition Tpop 11 has run a whole cycle to F2, seems “phenotypic” in DaDa language. Tpop 17; OP seeds have been collected from 20 year old F1; 8 progeny tests with plants. If cycle length is 25 and BP=50, 25000/(50*25)=20 +, so if that was typical annual cost for pine would be >20 trees per BP parent and year, seems “phen/prog” in DaDa language I could find only a single case (Tpop17) of major progeny-testing F1 initiated. Things take time….

That long-term breeding takes much time is no surprise. Thanks to the current good documentation (Annual status rapports are available), we will better grasp the time-line and avoid delays. Long-term breeding has not proceeded far for most Swedish populations, thus the methods of long term breeding are not well- established or based on much experience, but open for discussion. It has been thought that methods to force early flowering to get progeny-test initiated really early on pine should become important. This has not yet been done for a single Tpop. Our calculations indicate that this line of breeding is less efficient than progeny-testing of field-tested F1 genotypes.

Alternative pine strategy (cheap) Graft archive (5*30) Progeny test 20*5*40 PC + 30*5*20 OP = 7000 Year (approx) Top grafts (5*20) Field test 5000 F 1 (50*100) Planting Next Cycle BP DPM Select 5 best in 20 best fam.s BP N=50 Top grafting Polycross Select 5 in worse 30 fam.s Planting Grafting DPM pollen

Phenotypic vs progeny  In future seed orchards tested clones will probably be preferrable to somewhat better - but untested - fresh 15 year old phenotypic selections  Progeny offers options which phenotype does not (like observations on survival, estimates of genetic correlations and other parameters).

Constraints and limitations of breeding cycler  Shit in – shit out, entries must be chosen with care. Sometimes they are not important but sometimes they are  The input values may need some adjustment from the most evident for considering factors not considered in the math  Breeding heads for an area and gets information from a limited number of sites with limited materials, this can be considered by a reduction of CVAm  The test environments may not be considered a sample of future forest environments, this can also be considered by a reduction of CVAm.

Constraints and limitations of breeding cycler –continued 1  If ever leading for the details for Sweden (or elsewhere) I recommend breeding cycler to be rerun after a more engaged debate about the inputs. We are willing to do the reruns.  Any decision support tool may need modifications for conciderations beyond the model.  Breeding heads for improvement in many characters, we set the goal as one character “value for forestry” and the observed character can be seen as an index with as high correlation as possible to the goal.  The “observation” is an index of observations, and J*M is thought of as time development of observed vs goal.

Constraints and limitations of breeding cycler – continued2  Plant cost is seen as independent of age of evaluation. This can cause problems for some type of comparisons (e.g. expensive flowering induction). This difficulty can be overcome by inserting different costs for different compared alternatives.  It is easy to add many types of considerations to the EXCEL sheet, but it makes it difficult and complex for the user and journal papers. Those who want a special feature can often rather easy program it into the existing breeding cycler or even I can do it if you ask.  Phenotypic preselection reduces the genetic variance somewhat in our pheno/progeny calculations, quantitatively the effect is negliable (3%) in our main scenario.  The gain by within family phenotypic selection may be slightly overexegarated with large families. This effect is probably small and very depending on as well the experimental lay-out as the evaluation method.

Constraints and limitations of breeding cycler – continued 3  The optimal breeding strategy is too chaotic to be found by formulas, stochastic simulation is needed instead of breeding cycler.

Constraints and limitations of breeding cycler – continued 4  Breeding cycler does not specifically link to seed orchards. To cream off seed orchards with sufficient diversity and little inbreeding is the most important reason for tree breeding! But this is taken care of by the choice of the diversity coeff (penalty).

Constraints and limitations of breeding cycler – continued 5  Genetic correlation are likely to change over generations  Breeding cycler considers the first cycle, the cumulative effect of some cycles can be assumed to be additive, but after a number of cycles this oversimplifications become unrealistic.

Swedish Norway spruce breeding Generation breeding pop 10 clone seed orchard 10 clone clonal mixture Rosvall, Lindgren & Mullin 1998 Conclusions: Accumulative progress for many generations Orchard progress follows breeding pop progress

Inbreeding follows group coancestry Simulation of Swedish Norway spruce breeding program by POPSIM, BP=48, DPM, equal representation (2/parent) Generations Probability of identity by descent f Rosvall, Lindgren & Mullin 1999 Conclusions: Accumulative change over many cycles

Cycling will accumulate gain. Where is the limit?

Balanced long-term breeding  Some unbalance is favourable  The inoptimality loss seem to be small; it is tricky to utilize unbalance, and the balance is unlikely to affect recommendations much.

Imbalance at initiation of breeding  At initiation of breeding there is no “balance”.  Truncating tested plus trees to long term breeding has sometimes been done with inoptimal imbalance.  I believe it is more optimal to sacrify the gene diversity in the initial selections slower.  This has been discussed i förädlingsrådet 1999 (see link on seminar page), and one argument is in Routsalainen’s thesis (2002).

Sweden started imbalanced Swedish recently decided to decrease the breeding population drastically (= very low Ne first generation), 6000 plus trees  1000 founders

Flowering – when? We assume flowering in phenotypes of conifers at ages around 11. That may work with top-grafting. To make progeny-testing with open pollination possible may take 20 years. It is important that hard data on flowering time and flowering variations in modern progeny trials are collected and well documented. In our current figures we probably have discounted early flowering assuming pollen collection, hormone injections and top grafting whenever possible. It is also important to document and systematize how efficient such actions are.

More constraints on breeding population number  An unpublished manus, which was produced during a hectic month in the autumn 2003, is not much fuel  Results are contraintuitive to me, before the study I thought the study would suggest larger population size  Decrease of breeding population is something one should be very conservative about  No immediate reason to go downward!

Earlier considerations on breeding population number Most considerations (including Swedish) is to choose the lowest number, which ensures sustainability and conservation and assurance against loss of alleles, not optimal trade-off with gain. It has not been well investigated if the optimal number could be higher than applied.

Genetic progress as function of Ne Expected gain after 1, 5, 10, and infinite (  ) generations of selection for different values of Ne in a model population (Baker and Curnow 1969 from Johnson et al ). Generation Ne   Ne > 50 in one subpop and much larger in the metapop, so we may not constrain future genetic progress

E globulus CELBI -Portugal 300 APM - Australia 300 E grandis ARACRUZ – Brazil 400 E nitens APM – Australia 300 New Zealand 270 E. regnans APM – Australia 300 New Zealand 300 E. Urophylla ARACRUZ – Brazil 400 Picea abies Sweden >1000 Picea glauca Nova Scotia 450 P mariana New Brunswick 400 Pinus elliottiiCFGRP - USA900 WGFTIP - USA800 Pinus radiata STBA - Australia300 FRI – New Zealand 550 Pinus taedaNCSU- USA160 WGGTIP800 Pseudots. Menziesii BC - Canada450 NWTIC - USA404 Tsuga heterophylla HEMTIC CAN- USA 150 Note sometimes values refer to what is available for a zone but mostly a meta- population for a larger area Pinus banksiana Lake states - USA 400 Manitoba -Canada 116 Pinus caribea QFS - Australia BP sizes reported in tree improvement programs from Johnson et al ow_2001.pdf).

Comment: The Swedish breeding population seems unusually large (this may be justified by the ecological amplitude covered by the Swedish breeding program)

The current Swedish breeding program is sustainable for more than 10 generations. Ten generations downstream will offer new unknown options. There is gene banking and natural resources besides breeders activities. The current breeders responsibility do not stretch longer. Question 1: Can it be made more narrow to save money or to boost gain without loosing sustainability? Question 2: Are there gains to be made by enlarging BP

How many are needed and desired?

Summary Census number 50 per subpopulation and in meta- population for pine and spruce is OK to continue in the coming decades.

Optimal breeding population size What is more beneficial at a fixed budget: larger Breeding population (diversity) and smaller testing pop (test precision) or vice versa? Find the breeding population size which maximizes the annual progress in group merit under the annual budget

How optimally allocate the resources Test precision (testing pop.) Diversity (breeding pop.)

Main findings Spruce, BP < 50 is beneficial, as clonal test= higher benefit from the gain- generating capacity, Pine, BP ~ 50, as the gain-generating capacity of the testing strategy is not powerful enough to motivate reduction of gene diversity.

Parameters and scenarios

Testing strategy Annual progress would benefit from lower BP for spruce, where testing can be clonal!

Testing strategy For Phenotype: the optimal is above 50, but only slightly. However, if budget is higher, it is better to increase breeding pop size beyond 50, than to increase offspring size. For Progeny the low optimum may reflect high testing cost, the total cost must be reduced by low BP size. Note that progeny is superior to phenotype at very high budget! For a mixed Phenotype/Progeny philosophy, similar low numbers as for progeny appeared. For Clone, low BP size probably reflects the high gain, which makes the gene diversity loss important

Heritability High heritability boosts gain and makes loss of gene diversity less important. Low heritability justifies higher BP size, but the dependence is not strong, and I suggest we can regard the dependence as unimportant Breeding Population Size Annual Group Merit, % h 2 = 0.5 h 2 = 0.1, main scenario

Annual Budget Optimal BP size increases with the budget, but only marginally and unimportant. But if spruce has a higher budget than pine, it is also an argument for a larger BP Annual Budget (main scenario 500) Optimal BP Size

Optimum share of resource invested in testing increases with the budget Annual budget Testing cost as % of budget

Cost of gene diversity Optimal BP is very dependent (close to linear) on cost of gene diversity. It is critical and is difficult to assign a value. Main scenario approach is that the cost is double as high as if all production were lost if no gene diversity remains. This seems sufficiently conservative Diversity cost (inbreeding depression = F = 100) main scenario = 200 Optimal BP Size

Genetic variation Optimal BP size is very dependent on genetic variation in value for forestry. It ought to be possible to assign better estimates as trials grow older. The main scenario approach is that the CV of value for forestry is 10% within family, an educated guess based on estimates from younger trials is 12.5% (which may be adjusted to 10 for uncertanties) Genetic variation in value for forestry, CV main scenario=10 % Optimum BP size

Genetic variation We are now exploring genetic variation in value for forestry in old trials, if we find that to be smaller than CV=10%, that may be reason to increase breeding population size Genetic variation in value for forestry, CV main scenario=10 % Optimum BP size

Less balance in spruce!?  Economically more important for Sweden (  BP)  More plants produced (  BP)  Higher investment in breeding (  BP)  Higher site index (  ?)  More flexible, present populations may later be merged (  BP)  Can be more efficiently bred by clonal testing (  BP)  A lower BP may be defended. Instead I suggest to breed more aggressively, thus less balance in the selections.

Spruce breeding population  We have decided that 50 is needed and should not be keen on reducing it only a decade later.  However there is another reason to reduce spruce BP, that is that it is more flexible, thus zones can be larger.  I suggest to manage spruce BP more unbalanced than pine.  And be more prepared for a reduction some decades ahead by reducing the number of populations.

For pine it is more important to go on with present BP  Lower investment in breeding (  = BP)  Less flexible, more difficult to draw on adjacent zones (  = BP)  Can not be bred by clonal testing (  = BP)  Thus for long term breeding insufficient reason to decrease or increase BP and it may be desirable to keep breeding rather balanced.

End of the slides Shall we have a final discussion? Or someone may have tried Breeding Cycler and experienced a problem?

End slide beer Or just relax?