SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model.
Weifang LiuWujuan ZhongPaola Giusti-RodríguezZhiyun JiangGeoffery W WangHuaigu SunMing HuYun LiPublished in: Briefings in bioinformatics (2024)
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.
Keyphrases
- single cell
- transcription factor
- rna seq
- dna methylation
- genome wide
- gene expression
- induced apoptosis
- high throughput
- binding protein
- genome wide association study
- cell cycle arrest
- electronic health record
- big data
- copy number
- small molecule
- stem cells
- cell proliferation
- machine learning
- mesenchymal stem cells
- dna damage
- bone marrow
- cell therapy