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The Effect of Linkage Disequilibrium and Family Relationships on the Reliability of Genomic Prediction

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Journal Genetics
Specialty Genetics
Date 2012 Dec 26
PMID 23267052
Citations 93
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Abstract

Although the concept of genomic selection relies on linkage disequilibrium (LD) between quantitative trait loci and markers, reliability of genomic predictions is strongly influenced by family relationships. In this study, we investigated the effects of LD and family relationships on reliability of genomic predictions and the potential of deterministic formulas to predict reliability using population parameters in populations with complex family structures. Five groups of selection candidates were simulated by taking different information sources from the reference population into account: (1) allele frequencies, (2) LD pattern, (3) haplotypes, (4) haploid chromosomes, and (5) individuals from the reference population, thereby having real family relationships with reference individuals. Reliabilities were predicted using genomic relationships among 529 reference individuals and their relationships with selection candidates and with a deterministic formula where the number of effective chromosome segments (M(e)) was estimated based on genomic and additive relationship matrices for each scenario. At a heritability of 0.6, reliabilities based on genomic relationships were 0.002 ± 0.0001 (allele frequencies), 0.022 ± 0.001 (LD pattern), 0.018 ± 0.001 (haplotypes), 0.100 ± 0.008 (haploid chromosomes), and 0.318 ± 0.077 (family relationships). At a heritability of 0.1, relative differences among groups were similar. For all scenarios, reliabilities were similar to predictions with a deterministic formula using estimated M(e). So, reliabilities can be predicted accurately using empirically estimated M(e) and level of relationship with reference individuals has a much higher effect on the reliability than linkage disequilibrium per se. Furthermore, accumulated length of shared haplotypes is more important in determining the reliability of genomic prediction than the individual shared haplotype length.

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References
1.
Spelman R, Ford C, McElhinney P, Gregory G, Snell R . Characterization of the DGAT1 gene in the New Zealand dairy population. J Dairy Sci. 2003; 85(12):3514-7. DOI: 10.3168/jds.S0022-0302(02)74440-8. View

2.
Pszczola M, Strabel T, Mulder H, Calus M . Reliability of direct genomic values for animals with different relationships within and to the reference population. J Dairy Sci. 2011; 95(1):389-400. DOI: 10.3168/jds.2011-4338. View

3.
Habier D, Fernando R, Dekkers J . The impact of genetic relationship information on genome-assisted breeding values. Genetics. 2007; 177(4):2389-97. PMC: 2219482. DOI: 10.1534/genetics.107.081190. View

4.
Solberg T, Sonesson A, Woolliams J, Meuwissen T . Genomic selection using different marker types and densities. J Anim Sci. 2008; 86(10):2447-54. DOI: 10.2527/jas.2007-0010. View

5.
Hayes B, Visscher P, Goddard M . Increased accuracy of artificial selection by using the realized relationship matrix. Genet Res (Camb). 2009; 91(1):47-60. DOI: 10.1017/S0016672308009981. View