Pranckėnienė Laura, Jakaitienė Audronė, Ambrozaitytė Laima, Kavaliauskienė Ingrida, Kučinskas Vaidutis
Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.
Front Genet. 2018 Aug 14;9:315. doi: 10.3389/fgene.2018.00315. eCollection 2018.
In the last decade, one of the biggest challenges in genomics research has been to distinguish definitive pathogenic variants from all likely pathogenic variants identified by next-generation sequencing. This task is particularly complex because of our lack of knowledge regarding overall genome variation and pathogenicity of the variants. Therefore, obtaining sufficient information about genome variants in the general population is necessary as such data could be used for the interpretation of mutations (DNMs) in the context of patient's phenotype in cases of sporadic genetic disease. In this study, data from whole-exome sequencing of the general population in Lithuania were directly examined. In total, 84 (VarScan) and 95 (VarSeq) DNMs were identified and validated using different algorithms. Thirty-nine of these mutations were considered likely to be pathogenic based on gene function, evolutionary conservation, and mutation impact. The mutation rate estimated per position pair per generation was 2.74 × 10 [95% CI: 2.24 × 10-3.35 × 10] (VarScan) and 2.4 × 10 [95% CI: 1.96 × 10-2.99 × 10] (VarSeq), with 1.77 × 10 [95% CI: 6.03 × 10-5.2 × 10] indels per position per generation. The rate of germline DNMs in the Lithuanian population and the effects of the genomic and epigenetic context on DNM formation were calculated for the first time in this study, providing a basis for further analysis of DNMs in individuals with genetic diseases. Considering these findings, additional studies in patient groups with genetic diseases with unclear etiology may facilitate our ability to distinguish certain pathogenic or adaptive DNMs from tolerated background DNMs and to reliably identify disease-causing DNMs by their properties through direct observation.
在过去十年中,基因组学研究面临的最大挑战之一是从下一代测序鉴定出的所有可能的致病变异中区分出明确的致病变异。由于我们对整体基因组变异和变异致病性缺乏了解,这项任务尤其复杂。因此,获取普通人群中基因组变异的充分信息是必要的,因为这类数据可用于在散发性遗传疾病病例中结合患者表型解释突变(新发突变,DNMs)。在本研究中,直接检查了立陶宛普通人群全外显子测序的数据。总共使用不同算法鉴定并验证了84个(VarScan)和95个(VarSeq)新发突变。基于基因功能、进化保守性和突变影响,其中39个突变被认为可能具有致病性。每代每个位置对估计的突变率为2.74×10[95%置信区间:2.24×10⁻³.35×10](VarScan)和2.4×10[95%置信区间:1.96×10⁻².99×10](VarSeq),每代每个位置有1.77×10[95%置信区间:6.03×10⁻⁵.2×10]个插入缺失。本研究首次计算了立陶宛人群中生殖系新发突变率以及基因组和表观遗传背景对新发突变形成的影响,为进一步分析遗传病个体中的新发突变提供了基础。考虑到这些发现,对病因不明的遗传病患者群体进行更多研究可能有助于我们从可耐受的背景新发突变中区分出某些致病或适应性新发突变,并通过直接观察根据其特性可靠地鉴定致病新发突变。