SnapHiC-G:通过全局背景模型从单细胞 Hi-C 数据中识别长程增强子-启动子相互作用。

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Weifang Liu, Wujuan Zhong, Paola Giusti-Rodríguez, Zhiyun Jiang, Geoffery W Wang, Huaigu Sun, Ming Hu, Yun Li
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引用次数: 0

摘要

利用单细胞基因组学技术的力量,单细胞Hi-C(scHi-C)及其衍生技术为测量单个细胞中调控元件及其靶基因之间的空间接近性提供了强大的工具。利用全局背景模型,我们提出了一种计算方法 SnapHiC-G,从 scHi-C 数据中识别长程增强子-启动子相互作用。我们将 SnapHiC-G 应用于小鼠胚胎干细胞和人脑皮质细胞产生的 scHi-C 数据集。SnapHiC-G 在识别长程增强子-启动子相互作用方面具有很高的灵敏度。此外,SnapHiC-G 还能识别非编码全基因组关联研究(GWAS)变异的潜在靶基因,而且在 SnapHiC-G 识别的相互作用中,单核苷酸多态性(SNPs)以细胞类型特异的方式丰富了神经精神疾病的遗传性。总之,SnapHiC-G 是表征复杂组织中细胞类型特异性增强子-启动子相互作用的强大工具,有助于发现染色质相互作用对生物相关细胞类型中基因调控的重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model.

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.

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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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