Rančelis Tautvydas, Arasimavičius Justas, Ambrozaitytė Laima, Kavaliauskienė Ingrida, Domarkienė Ingrida, Karčiauskaitė Dovilė, Kučinskienė Zita Aušrelė, Kučinskas Vaidutis
Department of Human and Medical Genetics,Faculty of Medicine,Vilnius University,Lithuania.
Department of Physiology, Biochemistry, Microbiology and Laboratory Medicine,Faculty of Medicine,Vilnius University,Lithuania.
Genet Res (Camb). 2017 Aug 30;99:e6. doi: 10.1017/S0016672317000040.
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.
下一代测序(NGS)成为发现遗传疾病新致病基因组变异的有效方法,并越来越多地用于诊断目的。收集致病变异数据的公共变异数据库正被用作临床诊断的来源。然而,利用公共数据库数据对致病变异的研究不仅可以在患者中进行,也可以在健康人群中开展。这可以为了解人群中最常见的隐性疾病提供线索。本研究的目的是利用NGS和ClinVar数据库的数据,鉴定立陶宛人群健康个体外显子中的致病变异。为实现这一目标,对96个外显子进行了测序。每个个体外显子平均发现42139个单核苷酸变异(SNV)和2306个短插入缺失。研究外显子的汇总数据共提供了243192个独特的SNV和31623个独特的短插入缺失。321个独特的SNV被分类为致病的。将千人基因组计划的欧洲数据与我们的数据进行比较,发现了5个以常染色体隐性模式遗传且在统计学上与欧洲人群数据有显著差异的致病基因组变异。