Evaluating whole genome amplification via multiply-primed rolling circle amplification for SNP genotyping of samples with low DNA yield
Evaluating whole genome amplification via multiply-primed rolling circle amplification for SNP genotyping of samples with low DNA yield
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DOI：
10.1375/1832427054936664
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发表时间：
2005-08-01
影响因子：
0.9
通讯作者：
Saarela, J
中科院分区：
文献类型：
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作者：
Silander, K;Komulainen, K;Saarela, J
可用DNA的数量往往是对大规模人群进行遗传分析的限制因素。最近已经证明了血液中较高的DNA产量与与炎症状态相关的几种表型之间的关联，这表明排除DNA产量非常低的样本可能导致统计分析中的偏倚结果。全基因组扩增技术（WGA）可以解决DNA浓度依赖性的样本选择问题。目的是使用多重引物滚环扩增方法彻底评估低DNA产量样品的WGA。在一个人群队列获得的799个样本中，选择了59个DNA产量最低（低于7.5 μ g）的样本。通过对24个单核苷酸多态性（SNPs）进行分型，比较从两个重复WGA样品和原始基因组DNA获得的基因型。59个样本中有13个发现了多基因型差异。差异的最大部分是由于WGA样本中杂合基因型的等位基因缺失。在基因分型之前合并WGA DNA重复显著提高了样品的基因分型再现性，在4个样品中仅鉴定出7个差异。差异的性质主要是基因组DNA中的纯合子基因型和WGA样品中的杂合子基因型，表明由于DNA模板量非常低，基因组DNA样品中可能存在等位基因缺失。因此，WGA适用于低DNA产量样品，特别是如果使用合并的WGA样品。较高的基因分型错误率要求更加注意基因分型质量控制，并在解释结果时谨慎。
The amount of available DNA is often a limiting factor in pursuing genetic analyses of large-scale population cohorts. An association between higher DNA yield from blood and several phenotypes associated with inflammatory states has recently been demonstrated, suggesting that exclusion of samples with very low DNA yield may lead to biased results in statistical analyses. Whole genome amplification (WGA) could present a solution to the DNA concentration-dependent sample selection. The aim was to thoroughly assess WGA for samples with low DNA yield, using the multiply-primed rolling circle amplification method. Fifty-nine samples were selected with the lowest DNA yield (less than 7.5 mu g) among 799 samples obtained for one population cohort. The genotypes obtained from two replicate WGA samples and the original genomic DNA were compared by typing 24 single nucleotide polyrnorphisms (SNPs). Multiple genotype discrepancies were identified for 13 of the 59 samples. The largest portion of discrepancies was due to allele dropout in heterozygous genotypes in WGA samples. Pooling the WGA DNA replicates prior to genotyping markedly improved genotyping reproducibility for the samples, with only 7 discrepancies identified in 4 samples. The nature of discrepancies was mostly homozygote genotypes in the genomic DNA and heterozygote genotypes in the WGA sample, suggesting possible allele dropout in the genomic DNA sample due to very low amounts of DNA template. Thus, WGA is applicable for low DNA yield samples, especially if using pooled WGA samples. A higher rate of genotyping errors requires that increased attention be paid to genotyping quality control, and caution when interpreting results.