BMC Genomics · 2012 · 152 citations · 36 references
Life SciencesAnimal SciencesGeneticsGenomicsMarker-assisted SelectionStatistical GeneticsGenetic MappingGenomic PredictionLinkage DisequilibriumSwine GeneticsSwine GenomicsAssociation Between Linked Markers And TraitsGenetic Marker DensityLinkage Disequilibrium AnalysisLinkage Disequilibrium PatternsPersistencePredictionReliability Prediction
BACKGROUND: The success of marker assisted selection depends on the amount of linkage disequilibrium (LD) across the genome. To implement marker assisted selection in the swine breeding industry, information about extent and degree of LD is essential. The objective of this study is to estimate LD in four US breeds of pigs (Duroc, Hampshire, Landrace, and Yorkshire) and subsequently calculate persistence of phase among them using a 60 k SNP panel. In addition, we report LD when using only a fraction of the available markers, to estimate persistence of LD over distance. RESULTS: Average r2 between adjacent SNP across all chromosomes was 0.36 for Landrace, 0.39 for Yorkshire, 0.44 for Hampshire and 0.46 for Duroc. For markers 1 Mb apart, r2 ranged from 0.15 for Landrace to 0.20 for Hampshire. Reducing the marker panel to 10% of its original density, average r2 ranged between 0.20 for Landrace to 0.25 for Duroc. We also estimated persistence of phase as a measure of prediction reliability of markers in one breed by those in another and found that markers less than 10 kb apart could be predicted with a maximal accuracy of 0.92 for Landrace with Yorkshire. CONCLUSIONS: Our estimates of LD, although in good agreement with previous reports, are more comprehensive and based on a larger panel of markers. Our estimates also confirmed earlier findings reporting higher LD in pigs than in American Holstein cattle, especially at increasing marker distances (> 1 Mb). High average LD (r2 > 0.4) between adjacent SNP found in this study is an important precursor for the implementation of marker assisted selection within a livestock species.Results of this study are relevant to the US purebred pig industry and critical for the design of programs of whole genome marker assisted evaluation and selection. In addition, results indicate that a more cost efficient implementation of marker assisted selection using low density panels with genotype imputation, would be feasible for these breeds.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Linkage disequilibrium in the human genome
David Reich, Michele Cargill, Stacey Bolk et al. · Nature · 2001 · 1.8K citations