Summary
Data on a genetic marker linked to a gene affecting an important trait could help us to estimate breeding values for that trait more accurately. The accuracy is enhanced if many genetic markers are used and if important genes are bracketed by two markers. A mixed model for analysis of this type of data is presented. The model is appropriate for an arbitrary pedigree structure in an outbreeding species. It uses a “relationship” matrix among marked chromosome segments or QTL alleles. By using an analysis analogous to a reduced animal model, the number of effects to be estimated can be greatly reduced. A grouping strategy that can account for crossbreeding and linkage disequilibrium between markers and QTL alleles is included in the model. For analyses of a cross between inbred lines the model can be simplified. This simplification shows clearly the relationship of the mixed model analyses to multiple regression models used previously. The simplified model may also be useful for some experiments in outbreeding populations.
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References
Beckman JS, Soller M (1988) Detection of linkage between marker loci and loci affecting quantitative traits in crosses between segregating populations. Theor Appl Genet 76:228–236
Cantet RJC, Smith C (1991) Reduced animal model for marker assisted selection using best linear unbiased prediction. Genet Sel Evol 23:221–233
Fernando RL (1990) Statistical problems in marker-assisted selection for QTL. Proc 4th World Congr Genet Appl Livestock Prod 13:433–436
Fernando RL, Grossman M (1989) Marker-assisted selection using best linear unbiased prediction. Genet Sel Evol 21:467–477
Haldane JBS (1919) The combination of linkage values and the calculation of distance between loci of linked factors. J Genetics 8:299–309
Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743–756
Nienhuis J, Helentjaris T (1989) Simultaneous selection for multiple polygenic traits through RFLP analyses. In: Development and application of molecular markers to problems in plant genetics. Cold Spring Habor Laboratory Press, Cold Spring Harbor/NY, pp 107–112
Quaas RL (1988) Additive genetic model with groups and relationships. J Dairy Sci 71:1338–1345
Quaas RL, Pollock EJ (1980) Mixed model methodoly for farm and ranch beef cattle testing programs. J Anim Sci 51:1277
Quaas RL, Pollock EJ (1981) Modified equations for sire models with groups. J Dairy Sci 64:1868
Robinson GK (1986) Group effects and computing strategies for models of estimated breeding values. J Dairy Sci 69:3106–3111
Smith C, Simpson SP (1986) The use of genetic polymorphism in livestock improvement. J Anim Breed Genet 103:205–217
Soller M, Beckman JS (1983) Genetic polymorphism in varietal identification and genetic improvement. Theor Appl Genet 67:25–33
Thompson R (1979) Sire evaluations. Biometrics 35: 339
Westell RA, Quaas RL, Van Vleck LD (1988) Genetic groups in an animal model. J Dairy Sci 71:1310–1318
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Communicated by J. S. F. Barker
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Goddard, M.E. A mixed model for analyses of data on multiple genetic markers. Theoret. Appl. Genetics 83, 878–886 (1992). https://doi.org/10.1007/BF00226711
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DOI: https://doi.org/10.1007/BF00226711