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Gene diversity measured by status number and other breeding concepts

Gene diversity measured by status number and other breeding concepts. Dag Lindgren. Department of Forest Genetics and Plant Physiology Swedish University of Agricultural Sciences SE-901 8 3 Umeå, Sweden. Raleigh Jan 17, 2003. Gain(BV). Inbreeding. Coancestry. Gene diversity. Cost.

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Gene diversity measured by status number and other breeding concepts

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  1. Gene diversity measured by status numberand other breeding concepts Dag Lindgren Department of Forest Genetics and Plant PhysiologySwedish University of Agricultural SciencesSE-901 83 Umeå, Sweden Raleigh Jan 17, 2003

  2. Gain(BV) Inbreeding Coancestry Gene diversity Cost Environments Technique Genetic parameters Interactions The art of breeding is combining a lot of things in a good way!

  3. To do that effectively, we must have quantitative concepts and measures To optimize, a quantitative measure must be defined and maximized!

  4. Some concepts useful for quantitative genetics Identical by descent(IBD) means that genes at the same locus are copies of the same original gene in some ancestor. The chance that both homologous genes in the same zygote are identical by descent is called inbreeding (F) (or coefficient of inbreeding).

  5. Coancestry(, f) between pair of individuals is the probability that genes, taken at random from each of the concerned individuals, are identical by descent (=coefficient of coancestry). A quantification of relatedness.  We will widen that concept! Self-coancestry: An individual's coancestry with itself is 0.5(1+F). This can be realised e.g. by considering that coancestry in the previous generation becomes inbreeding in next, and then consider selfing. If two individuals mate, their coancestry becomes the inbreeding of their offspring. Note that inbreeding and coancestry are relative to a situation with no inbreeding or relatedness.

  6. Relative Coancestry (f,) Unrelated 0 Half sibs 0.125 Full sibs 0.25 Parent-offspring 0.25 Cousin 0.0625 Itself (self-coancestry) 0.5 Coancestries are probabilities, thus 0 f 1. Some examples

  7. Gene poolmeans all genes in a population. It is convenient to consider genes at one locus. The gene pool is independent on how (or if) a population is organised in zygotes.

  8. Group coancestry Let's put all homologous genes in a big pool and select two (at random with replacement). The probability that two are IBD is group coancestry. (, this term was introduced by Cockerham 1967). f To get overall probability; average over all individual probabilities, f. Thus group coancestry could be called average coancestry.

  9. mother sister aunt uncle cousin What is the average relatedness (group coancestry) of this ”family”? Group coancestry

  10. Inbreeding and group coancestry Simulation of Swedish Norway spruce breeding program by 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 Rosvall, Lindgren & Mullin 1999 Generations

  11. Gene diversity!

  12. Group coancestry and gene diversity • Group coancestry is the probability that two genes are IBD; • Diversity means that things are different; • Gene Diversity means that genes are different. • Evidently 1 - group coancestry is the probability that the genes are non-identical, thus diverse.

  13. GD = 1 - group coancestry is the probability that the genes are non-identical, thus diverse. GD is Gene Diversity! Group coancestry is a measure of gene diversity lost! That seems to be something worth knowing!

  14. This way of thinking sees all genes in the source (reference) populations as unique (“tagged”). GD is similar to expected average heterozygosity (the chance that two genes are different). Group coancestry based measures are (like inbreeding) relative to some reference population. For forest tree breeding the wild forest usually constitutes a good reference. The gene diversity of the wild forest is 1, and the group coancestry is the share of the initial gene diversity lost. Monitor group coancestry in tree improvement operations! That says how much gene diversity has been lost since the initiation of the breeding program!

  15. Status number • Status number is half the inverse of group coancestry

  16. Status Number An attractive property of the status number is that it is the same as the census number for a population of unrelated, non-inbred trees. Status number is an intuitively appealing way of presenting group coancestry, as it connects to the familiar concept of number (population size). Status number is an effective number. It relates a real population to an ideal population. The ideal population consists of unrelated, non-inbred trees with the same probability of IBD.

  17. Status Number and seed orchard crops Seed orchard crops can be characterised by Status Number. I suggest this as a more useful and informative measure, than other concepts “effective population size of seed orchards”, which have been used. Lindgren and Mullin 1998

  18. “Effective number of clones” could be useful for describing seed orchards. It is the status number of the seed orchard clones, considering a variable ramet number. Kang et al. 2001

  19. Sibling coefficient could be useful for characterizing seed orchards or seed orchard crops. It is a probabilistic description of fertility variations. “The chance that two genes in the offspring come from the same parent”. It carries the same information as CV for fertility, and is thus not needed, just more convenient. Kang 2001

  20. Gene diversity as a function of status number Note that 1/2N is familiar in genetics!

  21. Status number versus variance effective number Gene frequency Generations Gene frequency over generations Variance effective number Status number

  22. Forest tree breeding and status number The status number concept is more useful to forest tree breeders than other breeders or geneticists. Forest tree breeders : • are still very close to the founders • thus close to the "wild forest“, a natural reference point for evaluating impact of breeding • deal with few generations • change strategy between generations • structure population in sublines • "own" and control the breeding population

  23. Conservation and improvement Gene conservation is to keep status number high and group coancestry low Genetic tree improvement is to combine a high gain and a reasonable status number or Genetic tree improvement is to balance gain and group coancestry

  24. Group merit Breeding valueandgene diversity are both desirable; they have to be balanced! The way to do it is: Maximise Group Merit!!!

  25. Group merit = weighted average of Breeding Value and Gene Diversity Weighting factor = “Penalty constant”; depends on specific circumstances

  26. A seed orchard crop can be characterized by its group merit; But as other factors, like inbreeding, are also important, I prefer to classify seed orchards and seed orchard crops by “benefit”; but the semantics is open for discussion…

  27. Group merit selection Modifications of group merit selection can be used for designing seed orchards. One modification is linear deployment. It applies to unrelated non inbred clones, and optimizes their contribution (=number of ramets) to an orchard.

  28. Group merit selection Selection of the genotypes, which maximises the group merit, using some predictor for Breeding Value and some weight for Gene Diversity. Lindgren and Mullin 1997

  29. Group merit selection Group merit is not a sum of individual merits! If the weight (penalty) can not be estimated? Group merit selection is anyway better than any alternative resulting in the same status number.

  30. Linear deployment Number of ramets g0 (intercept) b (slope) Breeding Value of Clone Linear deployment • Maximises gain at given Status number for a seed orchard • It is optimal to deploy clones linearly related to their breeding value Lindgren and Matheson 1986

  31. Linear deployment with constraint Ramets Breeding Value Linear deployment • Works also with constraint (genetic thinning of seed orchards)

  32. I suggest linear deployment (or modifications) to be considered in currently planned P taeda seed orchards. But in a decade, more advanced algorithms will be needed, because relatives will be frequent.

  33. The math, relations and considerations become too difficult to solve mathematically and the optimizing algorithms become to difficult to program and master. So, to optimize, we have to make use of existing optimizing programs, such as EXCEL solver. The problem is just to set up how things relate, and to decide what is the best value of the parameters.

  34. Long-term breeding Annual Advance in Group merit • Considers simultaneously three key factors • Gain; • Gene diversity; • Time. Wei and Lindgren 2001

  35. Long-term breeding criteria Annual Advance in Group merit at a given annual budget • Considers simultaneously four key factors • Gain; • Gene diversity; • Time; • Cost. Danusevičius and Lindgren 2002

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