bioRxivGenomicsPreprint
Robust Hi-C chromatin loop maps in human neurogenesis and brain tissues at high-resolution
Leina LuiD, Xiaoxiao LiuiD, Wei‐Kai HuangiD, Paola Giusti‐RodrígueziD, Jian CuiiD, Shanshan ZhangiD, Wanying XuiD, Zhexing WeniD, Shufeng MaiD, Jonathan D. RoseniD, Zheng Quan XuiD, Cynthia F. BartelsiD, Riki KawaguchiiD, Ming HuiD, Peter C. ScacheriiD, Zhili RongiD, Yun LiiD, Patrick F. SullivaniD, Hongjun SongiD, Guo‐li MingiD, Yan LiiD, Fulai JiniD
Abstract
Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input \"easy Hi-C\" (eHi-C) protocol to map the 3D genome architecture in neurogenesis and brain tissues, and also developed an improved Hi-C bias-correction pipeline (HiCorr) enabling better identification of enhancer loops or aggregates at sub-TAD level. We compared ultra-deep 3D genome maps from 10 human tissue- or cell types, with a focus on stem cells and neural development. We found several large loci in skin-derived human iPSC lines showing recurrent 3D compartmental memory of somatic heterochromatin. Chromatin loop interactions, but not genome compartments, are hallmarks of neural differentiation. Interestingly, we observed many cell type- or differentiation-specific enhancer aggregates spanning large neighborhoods, supporting a phase-separation mechanism that stabilizes enhancer contacts during development. Finally, we demonstrated that chromatin loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.\n\nHighlightsO_LILow input \"easy Hi-C\" protocol compatible with 50-100K cells\nC_LIO_LIImproved Hi-C bias correction allows direct observation and accurate identification of sub-TAD chromatin loops and enhancer aggregates\nC_LIO_LIRecurrent architectural memory of somatic heterochromatin at compartment level in skin-derived hiPSCs\nC_LIO_LIChromatin loop, but not genome compartment, marks neural differentiation\nC_LIO_LIChromatin loop outperforms eQTL in defining brain GWAS target genes\nC_LI
- organism: human
- assay: Hi-C
- research focus: gene regulatory network inference
- research focus: GWAS / association mapping
- research focus: benchmarking
- approach: experimental assay
- approach: statistical model
- Citations
- 3
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- HiCORE: Hi-C analysis for identification of core chromatin loops with higher resolution and reliability
Hongwoo Lee, Pil Joon Seo·bioRxiv·Oct 1, 2020
- SnapHiC: a computational pipeline to map chromatin contacts from single cell Hi-C data
Miao Yu, Armen Abnousi, … Ming Hu·bioRxiv·Dec 13, 2020
- Hi-C sequencing data from cortex of laboratory rats
Panjun Kim, Rachel R. Ward, … Hao Chen·bioRxiv·Feb 9, 2025
- Easy Hi-C: A simple efficient protocol for 3D genome mapping in small cell populations
Leina Lu, Xiaoxiao Liu, … Fulai Jin·bioRxiv·Jan 10, 2018
- Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes
Karolina Jodkowska, Zofia Parteka-Tojek, … Dariusz Plewczyński·bioRxiv·May 16, 2024
- Long-Range Enhancer Networks Gradually Emerge as Key Regulators During Human Cortical Neurogenesis
Lumeng Jia, Yingping Hou, … Cheng Li·bioRxiv·Jul 24, 2024