The effects of scale:: variation in the APOA1/C3/A4/A5 gene cluster
The effects of scale:: variation in the APOA1/C3/A4/A5 gene cluster
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DOI：
10.1007/s00439-004-1106-x
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发表时间：
2004-06-01
期刊：
影响因子：
5.3
通讯作者：
Weiss, KM
中科院分区：
文献类型：
--
作者：
Fullerton, SM;Buchanan, AV;Weiss, KM
虽然选择几个SNP来代表局部染色体区域中所有或大部分DNA序列变异性的想法相当有吸引力，但量化采用这种方法时丢失的细节也很重要。为了解决这个问题，我们比较了同一基因组区域（11号染色体上的APOA 1/C3/A4/A5基因簇）的高分辨率和低分辨率序列多样性。首先，广泛的重新测序确定了来自三个人群的72个个体中的所有核苷酸和序列单倍型变异：来自密西西比州杰克逊的非洲裔美国人，来自芬兰北卡累利阿的欧洲人和来自明尼苏达州罗切斯特的欧美人。我们在17.7 kb内鉴定出124个SNPs，基因间变异差异显著。APOC 3基因多样性在高分辨率下特别独特，显示杰克逊和其他两个样本之间的等位基因频率差异较大（F-ST值>0.250），以及不同的群体特异性单倍型谱系。接下来，我们使用由Stram等人（2003）建议的算法，以大约每kb一个SNP的密度，为每个基因选择单倍型标记SNP（htSNP）。然后使用所确定的17个htSNPs来重建低分辨率单倍型，从中还得出关于变异结构的推断。这种比较表明，虽然htSNPs成功地标记了常见的单倍型变异，但它们也留下了许多未检测到的潜在序列多样性，并且在某些情况下未能对密切相关的单倍型组进行共分类。这些研究结果的影响，为其他单倍型为基础的描述人类的变化进行了讨论。
While there is considerable appeal to the idea of selecting a few SNPs to represent all, or much, of the DNA sequence variability in a local chromosomal region, it is also important to quantify what detail is lost in adopting such an approach. To address this issue, we compared high- and low-resolution depictions of sequence diversity for the same genomic region, the APOA1/C3/A4/A5 gene cluster on chromosome 11. First, extensive re-sequencing identified all nucleotide and sequence haplotype variation of the linked apolipoprotein genes in 72 individuals from three populations: African-Americans from Jackson, Miss., Europeans from North Karelia, Finland, and European-Americans from Rochester, Minn.. We identified 124 SNPs in 17.7 kb and significant differences in variation among genes. APOC3 gene diversity was particularly distinctive at high resolution, showing large allele frequency differences (F-ST values >0.250) between Jackson and the other two samples, and divergent population-specific haplotype lineages. Next, we selected haplotype-tagging SNPs (htSNPs) for each gene, at a density of approximately one SNP per kb, using an algorithm suggested by Stram et al. (2003). The 17 htSNPs identified were then used to reconstruct low-resolution haplotypes, from which inferences about the structure of variation were also drawn. This comparison showed that while the htSNPs successfully tagged common haplotype variation, they also left much underlying sequence diversity undetected and failed, in some cases, to co-classify groups of closely related haplotypes. The implications of these findings for other haplotype-based descriptions of human variation are discussed.