Limitations of the human reference genome for personalized genomics.
Limitations of the human reference genome for personalized genomics.
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DOI：
10.1371/journal.pone.0040294
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Smith TM
中科院分区：
文献类型：
--
作者：
Rosenfeld JA;Mason CE;Smith TM
来自1000基因组计划(1KGP)和完全基因组学(CG)的数据极大地增加了已知基因变异的数量，并挑战了关于参考基因组及其在临床和研究环境中的用途的几个假设。具体地说，在已发表的针对各种疾病的基于阵列的GWAS研究中，34%的研究使用了与意想不到的单核苷酸多态(SNPs)、INDELs或结构变体重叠的探针。连锁不平衡(LD)区块长度取决于使用的标记数量，当基于HapMap的计算与根据1KGP数据计算的区块进行比较时，LD区块的平均大小从16kb减少到7kb。此外，当比较1KGP和CG变异体时，从共同基因组中报告的19%的单核苷酸变异体(SNV)对于一个数据集来说是独一无二的；可能是由于数据收集方法、对参考基因组的读取的比对以及变异体调用算法的不同造成的。总而言之，这些观察表明，目前的研究资源和信息学方法不足以解释人类群体中已经存在的高水平变异，需要做出重大努力来创建能够准确评估个人基因组学对健康、疾病和预测治疗结果的资源。
Data from the 1000 genomes project (1KGP) and Complete Genomics (CG) have dramatically increased the numbers of known genetic variants and challenge several assumptions about the reference genome and its uses in both clinical and research settings. Specifically, 34% of published array-based GWAS studies for a variety of diseases utilize probes that overlap unanticipated single nucleotide polymorphisms (SNPs), indels, or structural variants. Linkage disequilibrium (LD) block length depends on the numbers of markers used, and the mean LD block size decreases from 16 kb to 7 kb,when HapMap-based calculations are compared to blocks computed from1KGP data. Additionally, when 1KGP and CG variants are compared, 19% of the single nucleotide variants (SNVs) reported from common genomes are unique to one dataset; likely a result of differences in data collection methodology, alignment of reads to the reference genome, and variant-calling algorithms. Together these observations indicate that current research resources and informatics methods do not adequately account for the high level of variation that already exists in the human population and significant efforts are needed to create resources that can accurately assess personal genomics for health, disease, and predict treatment outcomes.
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