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Next generation sequencing exome data analysis aids in the discovery of SNP and INDEL patterns in Parkinson's disease.
Genomics ( IF 3.4 ) Pub Date : 2020-04-27 , DOI: 10.1016/j.ygeno.2020.04.025
Rajasree Odumpatta 1 , Arumugam Mohanapriya 1
Affiliation  

Whole exome sequencing is an adept method to reveal novel and disease-related SNPs and INDELs as it screen the actionable areas of the genome. We evaluated the exome sequenced datasets of patients with Parkinson's disease (PD) in South African ethnic origin. The primary focus of this study was to discover the SNPs and INDELs patterns responsible for PD. The variant discovery was performed with genome analysis tool kit best practices variant detection pipelines. The SNPs were linked to the genes and categorized based on the filter-based annotation from ANNOVAR. We identified a total of 7955 SNPs and 9952 INDELs in all seven datasets together. A total of 130 missense nsSNPs were prioritized based on its damaging effect predicted from SIFT and Polyphen2 annotation. We noticed a novel nsSNP rs111655870 in gene LRRK2 that shows the mutation of a Leucine to Phenylalanine at position 208 which can alter the protein function. The study also filtered seven nsSNPs in genes NAGA, SULT4A1, MYH8, FLNA, TPM3, ATP13A1, CLN8 that have potentially deleterious effects predicted by various computational tools. This analysis suggested that the above filtered nsSNPs and INDELs have a functional impact and provide the footing for genetic studies related to PD. Further screening of these variations provides deeper insight for molecular mechanism of disease progression.

中文翻译:

下一代测序外显子组数据分析有助于发现帕金森病中的 SNP 和 INDEL 模式。

全外显子组测序是一种巧妙的方法,可以在筛选基因组的可操作区域时揭示新的和疾病相关的 SNP 和 INDEL。我们评估了南非族裔帕金森病 (PD) 患者的外显子组测序数据集。本研究的主要重点是发现导致 PD 的 SNP 和 INDEL 模式。变异发现是使用基因组分析工具包最佳实践变异检测管道进行的。SNP 与基因相关联,并根据来自 ANNOVAR 的基于过滤器的注释进行分类。我们在所有七个数据集中总共确定了 7955 个 SNP 和 9952 个 INDEL。根据 SIFT 和 Polyphen2 注释预测的破坏性影响,共有 130 个错义 nsSNP 被优先考虑。我们注意到 LRRK2 基因中的一个新的 nsSNP rs111655870,它显示了第 208 位亮氨酸到苯丙氨酸的突变,这可以改变蛋白质功能。该研究还过滤了基因 NAGA、SULT4A1、MYH8、FLNA、TPM3、ATP13A1、CLN8 中的七个 nsSNP,这些基因具有各种计算工具预测的潜在有害影响。该分析表明,上述过滤后的 nsSNP 和 INDEL 具有功能影响,并为与 PD 相关的遗传研究提供了基础。进一步筛选这些变异为疾病进展的分子机制提供了更深入的了解。该分析表明,上述过滤后的 nsSNP 和 INDEL 具有功能影响,并为与 PD 相关的遗传研究提供了基础。进一步筛选这些变异为疾病进展的分子机制提供了更深入的了解。该分析表明,上述过滤后的 nsSNP 和 INDEL 具有功能影响,并为与 PD 相关的遗传研究提供了基础。进一步筛选这些变异为疾病进展的分子机制提供了更深入的了解。
更新日期:2020-04-27
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