Ke Xiayi, Hunt Sarah, Tapper William, Lawrence Robert, Stavrides George, Ghori Jilur, Whittaker Pamela, Collins Andrew, Morris Andrew P, Bentley David, Cardon Lon R, Deloukas Panos
Wellcome Trust Centre for Human Genetics, University of Oxford, UK.
Hum Mol Genet. 2004 Mar 15;13(6):577-88. doi: 10.1093/hmg/ddh060. Epub 2004 Jan 20.
Linkage disequilibrium (LD) is a measure of the degree of association between alleles in a population. The detection of disease-causing variants by association with neighbouring single nucleotide polymorphisms (SNPs) depends on the existence of strong LD between them. Previous studies have indicated that the extent of LD is highly variable in different chromosome regions and different populations, demonstrating the importance of genome-wide accurate measurement of LD at high resolution throughout the human genome. A uniform feature of these studies has been the inability to detect LD in regions of low marker density. To investigate the dependence of LD patterns on marker selection we performed a high-resolution study in African-American, Asian and UK Caucasian populations. We selected over 5000 SNPs with an average spacing of approximately 1 SNP per 2 kb after validating ca 12 000 SNPs derived from a dense SNP collection (1 SNP per 0.3 kb on average). Applications of different statistical methods of LD assessment highlight similar areas of high and low LD. However, at high resolution, features such as overall sequence coverage in LD blocks and block boundaries vary substantially with respect to marker density. Model-based linkage disequilibrium unit (LDU) maps appear robust to marker density and consistently influenced by marker allele frequency. The results suggest that very dense marker sets will be required to yield stable views of fine-scale LD in the human genome.
连锁不平衡（LD）是衡量群体中等位基因之间关联程度的指标。通过与相邻单核苷酸多态性（SNP）的关联来检测致病变异取决于它们之间强连锁不平衡的存在。先前的研究表明，连锁不平衡的程度在不同染色体区域和不同人群中高度可变，这表明在整个人类基因组中以高分辨率进行全基因组连锁不平衡准确测量的重要性。这些研究的一个共同特点是无法在低标记密度区域检测到连锁不平衡。为了研究连锁不平衡模式对标记选择的依赖性，我们在非裔美国人、亚洲人和英国白种人群体中进行了一项高分辨率研究。在验证了约12000个来自密集SNP集合（平均每0.3kb有1个SNP）的SNP后，我们选择了5000多个SNP，平均间距约为每2kb有1个SNP。不同连锁不平衡评估统计方法的应用突出了相似的高连锁不平衡和低连锁不平衡区域。然而，在高分辨率下，连锁不平衡块中的总体序列覆盖范围和块边界等特征在标记密度方面有很大差异。基于模型的连锁不平衡单位（LDU）图谱似乎对标记密度具有鲁棒性，并始终受标记等位基因频率的影响。结果表明，需要非常密集的标记集才能获得人类基因组中精细尺度连锁不平衡的稳定视图。
