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利用焦磷酸测序法估计DNA池中的单核苷酸多态性等位基因频率

Estimation of single nucleotide polymorphism allele frequency in DNA pools by using Pyrosequencing.

作者信息

Gruber Jonathan D, Colligan Peter B, Wolford Johanna K

机构信息

Clinical Diabetes and Nutrition Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases/NIH, 4212 North 16th Street, Phoenix, AZ 85016, USA.

出版信息

Hum Genet. 2002 May;110(5):395-401. doi: 10.1007/s00439-002-0722-6. Epub 2002 Apr 9.

Abstract

Positional cloning of genes underlying complex diseases, such as type 2 diabetes mellitus (T2DM), typically follows a two-tiered process in which a chromosomal region is first identified by genome-wide linkage scanning, followed by association analyses using densely spaced single nucleotide polymorphic markers to identify the causal variant(s). The success of genome-wide single nucleotide polymorphism (SNP) detection has resulted in a vast number of potential markers available for use in the construction of such dense SNP maps. However, the cost of genotyping large numbers of SNPs in appropriately sized samples is nearly prohibitive. We have explored pooled DNA genotyping as a means of identifying differences in allele frequency between pools of individuals with T2DM and unaffected controls by using Pyrosequencing technology. We found that allele frequencies in pooled DNA were strongly correlated with those in individuals (r=0.99, P<0.0001) across a wide range of allele frequencies (0.02-0.50). We further investigated the sensitivity of this method to detect allele frequency differences between contrived pools, also over a wide range of allele frequencies. We found that Pyrosequencing was able to detect an allele frequency difference of less than 2% between pools, indicating that this method may be sensitive enough for use in association studies involving complex diseases where a small difference in allele frequency between cases and controls is expected.

摘要

复杂疾病(如2型糖尿病,T2DM)相关基因的定位克隆通常遵循一个两层的过程,即首先通过全基因组连锁扫描确定一个染色体区域,然后使用密集排列的单核苷酸多态性标记进行关联分析以确定致病变异。全基因组单核苷酸多态性(SNP)检测的成功使得大量潜在标记可用于构建此类密集的SNP图谱。然而,在适当规模的样本中对大量SNP进行基因分型的成本几乎令人望而却步。我们探索了混合DNA基因分型,作为一种通过焦磷酸测序技术识别T2DM患者组和未受影响对照组之间等位基因频率差异的方法。我们发现,在广泛的等位基因频率范围(0.02 - 0.50)内,混合DNA中的等位基因频率与个体中的等位基因频率高度相关(r = 0.99,P < 0.0001)。我们还进一步研究了该方法在同样广泛的等位基因频率范围内检测人为构建的混合样本之间等位基因频率差异的敏感性。我们发现焦磷酸测序能够检测到混合样本之间小于2%的等位基因频率差异,这表明该方法对于涉及复杂疾病的关联研究可能足够敏感,因为在这类研究中预计病例组和对照组之间的等位基因频率差异较小。

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