Genetics and Genome Biology Program, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada.
Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.
Curr Protoc. 2022 Nov;2(11):e597. doi: 10.1002/cpz1.597.
There are more than 700 genes that encode proteins that function in epigenetic regulation and chromatin modification. Germline variants in these genes (typically heterozygous) are associated with rare neurodevelopmental disorders (NDDs) characterized by growth abnormalities and intellectual and developmental delay. Advancements in next-generation sequencing have dramatically increased the detection of pathogenic sequence variants in genes encoding epigenetic machinery associated with NDDs and, concurrently, the number of clinically uninterpretable variants classified as variants of uncertain significance (VUS). Recently, DNA methylation (DNAm) signatures, disorder-specific patterns of DNAm change, have emerged as a functional tool that provides insights into disorder pathophysiology and can classify pathogenicity of variants in NDDs. To date, our group and others have identified DNAm signatures for more than 60 Mendelian neurodevelopmental disorders caused by variants in genes encoding epigenetic machinery. There is broad interest in both the research and clinical communities to develop and catalog DNAm signatures in rare NDDs, but there are challenges in optimizing study design considerations and availability of platforms that integrate bioinformatics tools with the appropriate statistical framework required to analyze genome-wide DNAm data. We previously published EpigenCentral, a platform for analysis of DNAm data in rare NDDs. In this article, we utilize the published Weaver syndrome dataset to provide step-by-step protocols for using EpigenCentral for exploratory analysis to identify DNAm signatures and for classification of NDD variants. We also provide important considerations for experimental design and interpretation of DNAm results. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Exploratory analysis to identify disorder-specific DNAm signatures Basic Protocol 2: Classification of variants associated with neurodevelopmental disorders.
有超过 700 个基因编码参与表观遗传调控和染色质修饰的蛋白质。这些基因中的种系变异(通常为杂合子)与以生长异常和智力及发育迟缓为特征的罕见神经发育障碍(NDD)有关。下一代测序技术的进步极大地提高了与 NDD 相关的表观遗传机制基因中致病性序列变异的检测率,同时,也增加了被归类为意义不明的变异(VUS)的临床不可解释变异的数量。最近,DNA 甲基化(DNAm)特征,即 DNAm 变化的特定疾病模式,已成为一种功能工具,可以深入了解疾病的病理生理学,并可以对 NDD 中的变异的致病性进行分类。迄今为止,我们小组和其他小组已经为 60 多种由编码表观遗传机制的基因变异引起的孟德尔神经发育障碍确定了 DNAm 特征。在研究和临床界都广泛关注在罕见 NDD 中开发和编目 DNAm 特征,但在优化研究设计考虑因素和平台可用性方面存在挑战,这些平台需要整合生物信息学工具和分析全基因组 DNAm 数据所需的适当统计框架。我们之前发表了 EpigenCentral,这是一个用于分析罕见 NDD 中 DNAm 数据的平台。在本文中,我们利用已发表的 Weaver 综合征数据集,提供使用 EpigenCentral 进行探索性分析以识别 DNAm 特征和对 NDD 变异进行分类的分步协议。我们还提供了实验设计和 DNAm 结果解释的重要考虑因素。©2022Wiley Periodicals LLC. 基本方案 1:探索性分析以识别疾病特异性的 DNAm 特征 基本方案 2:分类与神经发育障碍相关的变异。