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Can long-range microsatellite data be used to predict short-range linkage disequilibrium?

机译:可以使用远程微卫星数据来预测短程连锁不平衡吗?

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摘要

The distribution of linkage disequilibrium (LD) across the genome is highly complex. Little is known about the relationship between long-range and short-range LD in a genomic region. We assessed whether a dense set of microsatellite data could be used to predict short-range LD in family samples. We analyzed intermarker LD in data derived from chromosomal regions 18q22 and 10q25-26, densely genotyped with microsatellite markers. The pattern of LD was highly heterogeneous within and between both chromosomal regions. On 10q25-26, very little LD was detected. On 18q22, where marker density was higher, many marker pairs were in LD. We modeled the decay of LD over distance in this region. A classical model accounted for most of the relationship between LD and distance (R (2)=63%). We used this model to predict the proportion of markers expected to show useful levels of LD at short distances. This prediction agreed with estimates based on single-nucleotide polymorphism (SNP) marker genotypes in the region. Both microsatellite and SNP data predict that about 80% of marker pairs would display levels of LD that are useful for association studies at distances of up to 15 kb in this region. These projections also agree with levels of LD directly measured in a 10 kb set of SNP genotypes generated in a nearby region of finished sequence. Our results suggest that existing sets of microsatellite data, if sufficiently dense, may be used to develop good initial estimates of the density of additional markers needed to screen a region for disease alleles by association analysis.
机译:连锁不平衡(LD)在整个基因组中的分布非常复杂。对于基因组区域中的长距离和短距离LD之间的关系知之甚少。我们评估了是否可以使用密集的微卫星数据集来预测家庭样品中的短程LD。我们分析了来自染色体区域18q22和10q25-26的数据中的标记间LD,这些区域用微卫星标记进行了密集的基因分型。在两个染色体区域之内和之间,LD的模式都是高度异质的。在10q25-26,检测到很少的LD。在标记密度较高的18q22,LD中有许多标记对。我们对该区域中LD随距离的衰减进行了建模。经典模型解释了LD和距离之间的大部分关系(R(2)= 63%)。我们使用该模型来预测预期在短距离显示LD有用水平的标记物的比例。该预测与基于该区域单核苷酸多态性(SNP)标记基因型的估计相符。微卫星和SNP数据均预测,大约80%的标记对将显示LD水平,这对于在该区域最远15 kb的距离进行关联研究很有用。这些预测也与在完成序列附近区域产生的10 kb SNP基因型集中直接测量的LD水平一致。我们的结果表明,现有的微卫星数据集(如果足够密集)可用于开发通过关联分析筛选疾病等位基因所需的其他标记物密度的良好初始估计。

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