Comendul Arianna, Ruf-Zamojski Frederique, Ford Colby T, Agarwal Pankaj, Zaslavsky Elena, Nudelman German, Hariharan Manoj, Rubenstein Aliza, Pincas Hanna, Nair Venugopalan D, Michaleas Adam M, Fremont-Smith Philip D, Ricke Darrell O, Sealfon Stuart C, Woods Christopher W, Claypool Kajal T, Jaimes Rafael
Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, USA.
Cedars-Sinai Medical Center, Department of Medicine, Los Angeles, CA, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA.
STAR Protoc. 2025 Mar 21;6(1):103607. doi: 10.1016/j.xpro.2025.103607. Epub 2025 Jan 26.
Host response to environmental exposures such as pathogens and chemicals can include modifications to the epigenome and transcriptome. Improved signature discovery, including the identification of the agent and timing of exposure, has been enabled by advancements in assaying techniques to detect RNA expression, DNA base modifications, histone modifications, and chromatin accessibility. The interrogation of the epigenome and transcriptome cascade requires analyzing disparate datasets from multiple assay types, often at single-cell resolution, derived from the same biospecimen. However, there remains a paucity of rigorous quality control standards of those datasets that reflect quality assurance of the underlying assay. This guide outlines a comprehensive suite of metrics that can be used to ensure quality from 11 different epigenetics and transcriptomics assays. Recommended mitigative actions to address failed metrics are provided. The workflow presented aims to improve benchwork protocols and dataset quality to enable accurate discovery of exposure signatures.
宿主对病原体和化学物质等环境暴露的反应可能包括表观基因组和转录组的改变。检测RNA表达、DNA碱基修饰、组蛋白修饰和染色质可及性的检测技术的进步，使得改进特征发现成为可能，包括识别暴露的因子和时间。对表观基因组和转录组级联的研究需要分析来自多种检测类型的不同数据集，这些数据集通常来自同一生物样本，且往往是单细胞分辨率的。然而，反映基础检测质量保证的那些数据集仍然缺乏严格的质量控制标准。本指南概述了一套全面的指标，可用于确保11种不同表观遗传学和转录组学检测的质量。针对未达标的指标提供了推荐的缓解措施。所展示的工作流程旨在改进实验操作方案和数据集质量，以准确发现暴露特征。
