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Analysis of pathogenic variants from the ClinVar database in healthy people using next-generation sequencing

机译:利用下一代测序分析了健康人中临床数据库的致病变种

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Summary Next-generation sequencing (NGS) became an effective approach for finding novel causative genomic variants of genetic disorders and is increasingly used for diagnostic purposes. Public variant databases that gather data of pathogenic variants are being relied upon as a source for clinical diagnosis. However, research of pathogenic variants using public databases data could be carried out not only in patients, but also in healthy people. This could provide insights into the most common recessive disorders in populations. The study aim was to use NGS and data from the ClinVar database for the identification of pathogenic variants in the exomes of healthy individuals from the Lithuanian population. To achieve this, 96 exomes were sequenced. An average of 42?139 single-nucleotide variants (SNVs) and 2306 short INDELs were found in each individual exome. Pooled data of study exomes provided a total of 243?192 unique SNVs and 31?623 unique short INDELs. Three hundred and twenty-one unique SNVs were classified as pathogenic. Comparison of the European data from the 1000 Genomes Project with our data revealed five pathogenic genomic variants that are inherited in an autosomal recessive pattern and that statistically significantly differ from the European population data.
机译:发明内容下一代测序(NGS)成为寻找遗传疾病的新致病基因组变体的有效方法,并且越来越多地用于诊断目的。收集致病变体数据的公共变体数据库作为临床诊断的来源依赖于源。然而,使用公共数据库数据的致病变体的研究不仅可以在患者中进行,而且还可以在健康的人中进行。这可以为群体中最常见的隐性疾病提供见解。该研究目的是使用Clinvar数据库中的NGS和数据来确定来自立陶宛人群的健康个体展开的致病变异。为实现这一点,测序96个凸起。平均42?139个单核苷酸变体(SNV)和2306个短诱导在每个Exome中发现。汇总的学习展会数据共提供243件独特的SNV和31件独特的短款。三百二十一个独特的SNV被归类为致病性。从1000个基因组项目的欧洲数据与我们的数据进行比较揭示了五种致病基因组变体,其遗传到常染色体隐性模式,并且与欧洲人口数据有统计学意义显着不同。

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