Allele frequency matching between SNPs reveals an excess of linkage disequilibrium in genic regions of the human genome.
Allele frequency matching between SNPs reveals an excess of linkage disequilibrium in genic regions of the human genome.
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DOI：
10.1371/journal.pgen.0020142
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发表时间：
2006-09-08
期刊：
影响因子：
4.5
通讯作者：
Nickerson DA
中科院分区：
文献类型：
--
作者：
Eberle MA;Rieder MJ;Kruglyak L;Nickerson DA
通过全基因组关联研究绘制复杂性状的遗传易感性已经引起了极大的兴趣。这些研究依赖于关联的程度，即，连锁不平衡（LD），在人类基因组中的单核苷酸多态性（SNP）之间。LD描述了SNP对之间的非随机关联，并且可以在设计用于人类群体中的关联研究的最大信息量SNP组时用作度量。使用Perlegen基因分型的158万个SNP的数据，我们从经验和理论两方面探讨了LD统计量r 2的等位基因频率依赖性。我们发现，不匹配的等位基因频率的SNP之间的平均r 2值总是被限制到远小于1（理论上约为0.46至0.57为这个数据集）。SNP对的频率匹配为评估LD的平均衰减提供了更灵敏的测量，并在几乎整个信息范围（从0到0.89到0.95）内产生平均r2值。此外，我们使用频率匹配的SNP分析了完美LD（r 2 = 1.0）的程度，发现基因区域与基因间区域的LD程度存在显著差异。表现出完美LD的SNP对显示出对衍生的非祖先等位基因的显著偏倚，为人类基因组中的正自然选择提供了证据。 遗传学家的主要目标之一是通过遗传多态性与表型性状的关联来分离基因组中传递疾病风险增加的区域。最近可用的全基因组多态性数据（即，单核苷酸多态性[SNPs]）使得关联研究以前所未有的规模成为可能，并且用于这些研究的这些多态性的表征和选择已经成为主要关注的主题。选择信息性SNP的一种方法是比较SNP之间的相关性（称为连锁不平衡），但当比较不同频率的SNP时，这可能会产生混淆问题。在这项研究中，作者表明，如果将SNP与频率相等或接近相等的其他SNP进行比较，它们之间的相关性更准确地代表了真正的相关性。这也产生了一个更敏感的方法来确定连锁不平衡。使用这种方法，比较基因区域内和基因区域外的SNP，以检查每个区域中SNP之间的总体相关性。根据其频率匹配SNP极大地增加了最大可能的相关性，并显示基因内（基因内）与基因间（基因间）SNP之间的相关性显着更高。使用最近完成的黑猩猩序列，与基因间区域相比，在基因区域中完全相关的SNP对中发现了更大比例的高频人类特异性SNP。这些观察结果表明，基因周围的基因组区域一直处于选择压力之下，导致SNP之间的相关性更大。在SNP之间相关性最高的区域中发现的基因将对未来的基因型-表型关联研究特别感兴趣。
Significant interest has emerged in mapping genetic susceptibility for complex traits through whole-genome association studies. These studies rely on the extent of association, i.e., linkage disequilibrium (LD), between single nucleotide polymorphisms (SNPs) across the human genome. LD describes the nonrandom association between SNP pairs and can be used as a metric when designing maximally informative panels of SNPs for association studies in human populations. Using data from the 1.58 million SNPs genotyped by Perlegen, we explored the allele frequency dependence of the LD statistic r 2 both empirically and theoretically. We show that average r 2 values between SNPs unmatched for allele frequency are always limited to much less than 1 (theoretical approximately 0.46 to 0.57 for this dataset). Frequency matching of SNP pairs provides a more sensitive measure for assessing the average decay of LD and generates average r 2 values across nearly the entire informative range (from 0 to 0.89 through 0.95). Additionally, we analyzed the extent of perfect LD (r 2 = 1.0) using frequency-matched SNPs and found significant differences in the extent of LD in genic regions versus intergenic regions. The SNP pairs exhibiting perfect LD showed a significant bias for derived, nonancestral alleles, providing evidence for positive natural selection in the human genome. One of the primary goals for geneticists is isolating regions of the genome that convey increased risk of disease through the association of genetic polymorphisms with phenotypic traits. The recent availability of genome-wide polymorphism data (i.e., single nucleotide polymorphisms [SNPs]) has made association studies possible on an unprecedented scale, and the characterization and selection of these polymorphisms for these studies has been a topic of major interest. One method for choosing informative SNPs has been to compare the correlation between SNPs (a term called linkage disequilibrium), but this can create confounding problems when comparing SNPs of different frequencies. In this study, the authors show that if SNPs are compared to other SNPs of equal or near equal frequency, the correlation between them more accurately represents the true correlation. This also produces a more sensitive method for determining linkage disequilibrium. Using this method, SNPs were compared both within and outside of gene regions to examine the overall correlation between SNPs in each region. Matching SNPs according to their frequency greatly increased the maximum possible correlation and showed significantly higher correlations between SNPs within genes (intragenic) versus between genes (intergenic). Using the recently completed chimpanzee sequence, a larger fraction of high frequency human specific SNPs was found within the perfectly correlated SNP pairs in genic regions compared to intergenic regions. These observations suggest that regions of the genome around genes have been under selective pressure, leading to a greater correlation between SNPs. Genes found in regions with the highest correlations between SNPs will be of particular interest for future genotype-phenotype association studies.
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