Suppr超能文献

颊拭子、SNP 芯片和 CNV:使用高密度基因分型微阵列评估通过邮寄采集的口腔刷 DNA 样本生成的拷贝数变异体调用的质量。

Cheek swabs, SNP chips, and CNVs: assessing the quality of copy number variant calls generated with subject-collected mail-in buccal brush DNA samples on a high-density genotyping microarray.

机构信息

Department of Biostatistics, College of Medicine, University of Arkansas for Medical Science, 4301 W, Markham Street, Mail Slot 781, Little Rock, AR 72205-7199, USA.

出版信息

BMC Med Genet. 2012 Jun 26;13:51. doi: 10.1186/1471-2350-13-51.

Abstract

BACKGROUND

Multiple investigators have established the feasibility of using buccal brush samples to genotype single nucleotide polymorphisms (SNPs) with high-density genome-wide microarrays, but there is currently no consensus on the accuracy of copy number variants (CNVs) inferred from these data. Regardless of the source of DNA, it is more difficult to detect CNVs than to genotype SNPs using these microarrays, and it therefore remains an open question whether buccal brush samples provide enough high-quality DNA for this purpose.

METHODS

To demonstrate the quality of CNV calls generated from DNA extracted from buccal samples, compared to calls generated from blood samples, we evaluated the concordance of calls from individuals who provided both sample types. The Illumina Human660W-Quad BeadChip was used to determine SNPs and CNVs of 39 Arkansas participants in the National Birth Defects Prevention Study (NBDPS), including 16 mother-infant dyads, who provided both whole blood and buccal brush DNA samples.

RESULTS

We observed a 99.9% concordance rate of SNP calls in the 39 blood-buccal pairs. From the same dataset, we performed a similar analysis of CNVs. Each of the 78 samples was independently segmented into regions of like copy number using the Optimal Segmentation algorithm of Golden Helix SNP & Variation Suite 7.Across 640,663 loci on 22 autosomal chromosomes, segment-mean log R ratios had an average correlation of 0.899 between blood-buccal pairs of samples from the same individual, while the average correlation between all possible blood-buccal pairs of samples from unrelated individuals was 0.318. An independent analysis using the QuantiSNP algorithm produced average correlations of 0.943 between blood-buccal pairs from the same individual versus 0.332 between samples from unrelated individuals.Segment-mean log R ratios had an average correlation of 0.539 between mother-offspring dyads of buccal samples, which was not statistically significantly different than the average correlation of 0.526 between mother-offspring dyads of blood samples (p=0.302).

CONCLUSIONS

We observed performance from the subject-collected mail-in buccal brush samples comparable to that of blood. These results show that such DNA samples can be used for genome-wide scans of both SNPs and CNVs, and that high rates of CNV concordance were achieved whether using a change-point-based algorithm or one based on a hidden Markov model (HMM).

摘要

背景

多位研究人员已经证实,使用颊拭子样本结合高通量全基因组微阵列可以对单核苷酸多态性(SNP)进行基因分型,但是目前对于从这些数据中推断出的拷贝数变异(CNV)的准确性尚无共识。无论 DNA 的来源如何,使用这些微阵列检测 CNV 都比 SNP 基因分型更困难,因此颊拭子样本是否能提供足够高质量的 DNA 来实现这一目的仍然是一个悬而未决的问题。

方法

为了证明从颊拭子样本中提取的 DNA 生成的 CNV 检测结果的质量,我们评估了个体同时提供两种样本类型时,来自这两种样本的检测结果的一致性。我们使用 Illumina Human660W-Quad BeadChip 对来自美国国家出生缺陷预防研究(NBDPS)的 39 名阿肯色州参与者的 SNP 和 CNV 进行了检测,其中包括 16 对母婴对,他们同时提供了全血和颊拭子 DNA 样本。

结果

在 39 对血-颊样本中,我们观察到 SNP 检测结果的一致性达到了 99.9%。我们对来自同一数据集的 CNV 进行了类似的分析。使用 Golden Helix SNP & Variation Suite 7 中的最优分割算法,对每个样本中的 78 个样本分别进行了相同拷贝数的分割。在 22 条常染色体上的 640663 个位点中,来自同一个体的血-颊样本的分段平均对数比(log R)比值的平均相关性为 0.899,而来自无亲缘关系个体的所有可能血-颊样本对之间的平均相关性为 0.318。使用 QuantiSNP 算法进行的独立分析产生了来自同一个体的血-颊样本之间的平均相关性为 0.943,而来自无亲缘关系个体的样本之间的平均相关性为 0.332。来自颊拭子样本的母婴对的分段平均对数比(log R)比值的平均相关性为 0.539,与来自血液样本的母婴对的平均相关性(0.526)没有统计学差异(p=0.302)。

结论

我们观察到邮寄采集的颊拭子样本的表现与血液样本相当。这些结果表明,这种 DNA 样本可用于 SNP 和 CNV 的全基因组扫描,并且无论使用基于突变点的算法还是基于隐马尔可夫模型(HMM)的算法,都能实现高的 CNV 一致性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58b4/3506514/4cac9b4c890c/1471-2350-13-51-1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验