[PDF][PDF] Positional cloning by linkage disequilibrium

N Maniatis, A Collins, J Gibson, W Zhang… - The American Journal of …, 2004 - cell.com
N Maniatis, A Collins, J Gibson, W Zhang, W Tapper, NE Morton
The American Journal of Human Genetics, 2004cell.com
Recently, metric linkage disequilibrium (LD) maps that assign an LD unit (LDU) location for
each marker have been developed (Maniatis et al. 2002). Here we present a multiple
pairwise method for positional cloning by LD within a composite likelihood framework and
investigate the operating characteristics of maps in physical units (kb) and LDU for two
bodies of data (Daly et al. 2001; Jeffreys et al. 2001) on which current ideas of blocks are
based. False-negative indications of a disease locus (type II error) were examined by …
Recently, metric linkage disequilibrium (LD) maps that assign an LD unit (LDU) location for each marker have been developed (Maniatis et al. 2002). Here we present a multiple pairwise method for positional cloning by LD within a composite likelihood framework and investigate the operating characteristics of maps in physical units (kb) and LDU for two bodies of data (Daly et al. 2001; Jeffreys et al. 2001) on which current ideas of blocks are based. False-negative indications of a disease locus (type II error) were examined by selecting one single-nucleotide polymorphism (SNP) at a time as causal and taking its allelic count (0, 1, or 2, for the three genotypes) as a pseudophenotype, Y. By use of regression and correlation, association between every pseudophenotype and the allelic count of each SNP locus (X) was based on an adaptation of the Malecot model, which includes a parameter for location of the putative gene. By expressing locations in kb or LDU, greater power for localization was observed when the LDU map was fitted. The efficiency of the kb map, relative to the LDU map, to describe LD varied from a maximum of 0.87 to a minimum of 0.36, with a mean of 0.62. False-positive indications of a disease locus (type I error) were examined by simulating an unlinked causal SNP and the allele count was used as a pseudophenotype. The type I error was in good agreement with Wald's likelihood theorem for both metrics and all models that were tested. Unlike tests that select only the most significant marker, haplotype, or haploset, these methods are robust to large numbers of markers in a candidate region. Contrary to predictions from tagging SNPs that retain haplotype diversity, the sample with smaller size but greater SNP density gave less error. The locations of causal SNPs were estimated with the same precision in blocks and steps, suggesting that block definition may be less useful than anticipated for mapping a causal SNP. These results provide a guide to efficient positional cloning by SNPs and a benchmark against which the power of positional cloning by haplotype-based alternatives may be measured.
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