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非酒精性脂肪性肝病进展过程中的染色质可及性景观。

The Chromatin Accessibility Landscape of Nonalcoholic Fatty Liver Disease Progression.

机构信息

Department of Biological Sciences, Institute of Molecular Biology & Genetics, Seoul National University, Seoul 08826, Korea.

Department of Life Sciences, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.

出版信息

Mol Cells. 2022 May 31;45(5):343-352. doi: 10.14348/molcells.2022.0001.

Abstract

The advent of the assay for transposase-accessible chromatin using sequencing (ATAC-seq) has shown great potential as a leading method for analyzing the genome-wide profiling of chromatin accessibility. A comprehensive reference to the ATAC-seq dataset for disease progression is important for understanding the regulatory specificity caused by genetic or epigenetic changes. In this study, we present a genome-wide chromatin accessibility profile of 44 liver samples spanning the full histological spectrum of nonalcoholic fatty liver disease (NAFLD). We analyzed the ATAC-seq signal enrichment, fragment size distribution, and correlation coefficients according to the histological severity of NAFLD (healthy control vs steatosis vs fibrotic nonalcoholic steatohepatitis), demonstrating the high quality of the dataset. Consequently, 112,303 merged regions (genomic regions containing one or multiple overlapping peak regions) were identified. Additionally, we found differentially accessible regions (DARs) and performed transcription factor binding motif enrichment analysis and motif analysis to determine new biomarker candidates. These data revealed the generegulatory interactions and noncoding factors that can affect NAFLD progression. In summary, our study provides a valuable resource for the human epigenome by applying an advanced approach to facilitate diagnosis and treatment by understanding the non-coding genome of NAFLD.

摘要

利用转座酶可及染色质测序(ATAC-seq)进行检测的出现,为分析染色质可及性的全基因组图谱提供了一种很有前途的方法。全面参考 ATAC-seq 数据集对于疾病进展非常重要,有助于了解由遗传或表观遗传变化引起的调控特异性。在这项研究中,我们对跨越非酒精性脂肪性肝病(NAFLD)全组织学谱的 44 个肝脏样本进行了全基因组染色质可及性图谱分析。我们根据 NAFLD 的组织学严重程度(健康对照 vs 脂肪变性 vs 纤维化非酒精性脂肪性肝炎)分析了 ATAC-seq 信号富集、片段大小分布和相关系数,证明了数据集的高质量。结果确定了 112,303 个合并区域(包含一个或多个重叠峰区域的基因组区域)。此外,我们还发现了可及性差异区域(DAR),并进行了转录因子结合基序富集分析和 motif 分析,以确定新的生物标志物候选物。这些数据揭示了影响 NAFLD 进展的基因调控相互作用和非编码因子。总之,通过应用先进的方法来理解 NAFLD 的非编码基因组,我们的研究为人类表观基因组提供了有价值的资源,有助于通过诊断和治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dee/9095509/60138090c6c7/molce-45-5-343-f1.jpg

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