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. 2003 Jan;163(1):347–365. doi: 10.1093/genetics/163.1.347

On marker-assisted prediction of genetic value: beyond the ridge.

Daniel Gianola 1, Miguel Perez-Enciso 1, Miguel A Toro 1
PMCID: PMC1462425  PMID: 12586721

Abstract

Marked-assisted genetic improvement of agricultural species exploits statistical dependencies in the joint distribution of marker genotypes and quantitative traits. An issue is how molecular (e.g., dense marker maps) and phenotypic information (e.g., some measure of yield in plants) is to be used for predicting the genetic value of candidates for selection. Multiple regression, selection index techniques, best linear unbiased prediction, and ridge regression of phenotypes on marker genotypes have been suggested, as well as more elaborate methods. Here, phenotype-marker associations are modeled hierarchically via multilevel models including chromosomal effects, a spatial covariance of marked effects within chromosomes, background genetic variability, and family heterogeneity. Lorenz curves and Gini coefficients are suggested for assessing the inequality of the contribution of different marked effects to genetic variability. Classical and Bayesian methods are presented. The Bayesian approach includes a Markov chain Monte Carlo implementation. The generality and flexibility of the Bayesian method is illustrated when a Lorenz curve is to be inferred.

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Selected References

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  1. Caron H., van Schaik B., van der Mee M., Baas F., Riggins G., van Sluis P., Hermus M. C., van Asperen R., Boon K., Voûte P. A. The human transcriptome map: clustering of highly expressed genes in chromosomal domains. Science. 2001 Feb 16;291(5507):1289–1292. doi: 10.1126/science.1056794. [DOI] [PubMed] [Google Scholar]
  2. Farnir F., Coppieters W., Arranz J. J., Berzi P., Cambisano N., Grisart B., Karim L., Marcq F., Moreau L., Mni M. Extensive genome-wide linkage disequilibrium in cattle. Genome Res. 2000 Feb;10(2):220–227. doi: 10.1101/gr.10.2.220. [DOI] [PubMed] [Google Scholar]
  3. Hayes B., Goddard M. E. The distribution of the effects of genes affecting quantitative traits in livestock. Genet Sel Evol. 2001 May-Jun;33(3):209–229. doi: 10.1186/1297-9686-33-3-209. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Hazel L N. The Genetic Basis for Constructing Selection Indexes. Genetics. 1943 Nov;28(6):476–490. doi: 10.1093/genetics/28.6.476. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Hwang J. T. Gene, Nettleton Dan. Investigating the probability of sign inconsistency in the regression coefficients of markers flanking quantitative trait loci. Genetics. 2002 Apr;160(4):1697–1705. doi: 10.1093/genetics/160.4.1697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Lande R., Thompson R. Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics. 1990 Mar;124(3):743–756. doi: 10.1093/genetics/124.3.743. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Lange C., Whittaker J. C. On prediction of genetic values in marker-assisted selection. Genetics. 2001 Nov;159(3):1375–1381. doi: 10.1093/genetics/159.3.1375. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Meuwissen T. H., Hayes B. J., Goddard M. E. Prediction of total genetic value using genome-wide dense marker maps. Genetics. 2001 Apr;157(4):1819–1829. doi: 10.1093/genetics/157.4.1819. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Ollivier L. The accuracy of marker-assisted selection for quantitative traits within populations in linkage equilibrium. Genetics. 1998 Mar;148(3):1367–1372. doi: 10.1093/genetics/148.3.1367. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Wang T., Fernando R. L., Grossman M. Genetic evaluation by best linear unbiased prediction using marker and trait information in a multibreed population. Genetics. 1998 Jan;148(1):507–515. doi: 10.1093/genetics/148.1.507. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Whittaker J. C., Thompson R., Denham M. C. Marker-assisted selection using ridge regression. Genet Res. 2000 Apr;75(2):249–252. doi: 10.1017/s0016672399004462. [DOI] [PubMed] [Google Scholar]
  12. Xu S. Mapping quantitative trait loci using multiple families of line crosses. Genetics. 1998 Jan;148(1):517–524. doi: 10.1093/genetics/148.1.517. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Zeng Z. B. Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc Natl Acad Sci U S A. 1993 Dec 1;90(23):10972–10976. doi: 10.1073/pnas.90.23.10972. [DOI] [PMC free article] [PubMed] [Google Scholar]

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