Trimodal single-cell profiling of transcriptome, epigenome and 3D genome in complex tissues with scHiCAR

Bonev, B. et al. Multiscale 3D genome rewiring during mouse neural development. Cell 171, 557–572 (2017).
Google Scholar
Freire-Pritchett, P. et al. Global reorganisation of cis-regulatory units upon lineage commitment of human embryonic stem cells. Elife 6, e21926 (2017).
Google Scholar
Greenwald, W. W. et al. Subtle changes in chromatin loop contact propensity are associated with differential gene regulation and expression. Nat. Commun. 10, 1054 (2019).
Google Scholar
Zheng, H. & Xie, W. The role of 3D genome organization in development and cell differentiation. Nat. Rev. Mol. Cell Biol. 20, 535–550 (2019).
Google Scholar
Kraft, K. et al. Polycomb-mediated genome architecture enables long-range spreading of H3K27 methylation. Proc. Natl Acad. Sci. USA 119, e2201883119 (2022).
Google Scholar
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
Google Scholar
Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).
Google Scholar
Nora, E. P. et al. Spatial partitioning of the regulatory landscape of the X-inactivation centre. Nature 485, 381–385 (2012).
Google Scholar
Dixon, J. R. et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376–380 (2012).
Google Scholar
Rao, S. S. P. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).
Google Scholar
Dryden, N. H. et al. Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-C. Genome Res. 24, 1854–1868 (2014).
Google Scholar
Mumbach, M. R. et al. HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat. Methods 13, 919–922 (2016).
Google Scholar
Fang, R. et al. Mapping of long-range chromatin interactions by proximity ligation-assisted ChIP-seq. Cell Res. 26, 1345–1348 (2016).
Google Scholar
Fullwood, M. J. et al. An oestrogen-receptor-α-bound human chromatin interactome. Nature 462, 58–64 (2009).
Google Scholar
Sati, S. et al. HiCuT: an efficient and low input method to identify protein-directed chromatin interactions. PLoS Genet. 18, e1010121 (2022).
Google Scholar
Wei, X. et al. HiCAR is a robust and sensitive method to analyze open-chromatin-associated genome organization. Mol. Cell 82, 1225–1238 (2022).
Google Scholar
Jung, I. et al. A compendium of promoter-centered long-range chromatin interactions in the human genome. Nat. Genet. 51, 1442–1449 (2019).
Google Scholar
Cao, J. et al. Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science 361, 1380–1385 (2018).
Google Scholar
Ma, S. et al. Chromatin potential identified by shared single-cell profiling of RNA and chromatin. Cell 183, 1103–1116 (2020).
Google Scholar
Zhu, C. et al. Joint profiling of histone modifications and transcriptome in single cells from mouse brain. Nat. Methods 18, 283–292 (2021).
Google Scholar
Lee, D.-S. et al. Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nat. Methods 16, 999–1006 (2019).
Google Scholar
Liu, Z. et al. Linking genome structures to functions by simultaneous single-cell Hi-C and RNA-seq. Science 380, 1070–1076 (2023).
Google Scholar
Wu, H. et al. Simultaneous single-cell three-dimensional genome and gene expression profiling uncovers dynamic enhancer connectivity underlying olfactory receptor choice. Nat. Methods 21, 974–982 (2024).
Google Scholar
Zhou, T. et al. GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells. Nat. Genet. 56, 1701–1711 (2024).
Google Scholar
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).
Google Scholar
Mathur, R. et al. Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective. Cell 187, 446–463.e16 (2024).
Google Scholar
Chai, H. et al. Tri-omic single-cell mapping of the 3D epigenome and transcriptome in whole mouse brains throughout the lifespan. Nat. Methods 22, 994–1007 (2025).
Google Scholar
Tan, L., Xing, D., Chang, C.-H., Li, H. & Xie, X. S. Three-dimensional genome structures of single diploid human cells. Science 361, 924–928 (2018).
Google Scholar
Ramsköld, D. et al. Full-length mRNA-seq from single-cell levels of RNA and individual circulating tumor cells. Nat. Biotechnol. 30, 777–782 (2012).
Google Scholar
Wei, X., Tran, D. & Diao, Y. HiCAR: analysis of open chromatin associated long-range chromatin interaction using low-input materials. Curr. Protoc. 3, e899 (2023).
Google Scholar
Yang, T. et al. HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient. Genome Res. 27, 1939–1949 (2017).
Google Scholar
Yu, M. et al. Integrative analysis of the 3D genome and epigenome in mouse embryonic tissues. Nat. Struct. Mol. Biol. 32, 479–490 (2025).
Google Scholar
Xie, Y. et al. Droplet-based single-cell joint profiling of histone modifications and transcriptomes. Nat. Struct. Mol. Biol. 30, 1428–1433 (2023).
Google Scholar
Zhang, R., Zhou, T. & Ma, J. Ultrafast and interpretable single-cell 3D genome analysis with Fast-Higashi. Cell Syst. 13, 798–807.e6 (2022).
Google Scholar
Santoni, G. et al. Chromatin plasticity predetermines neuronal eligibility for memory trace formation. Science 385, eadg9982 (2024).
Google Scholar
Gorkin, D. U. et al. An atlas of dynamic chromatin landscapes in mouse fetal development. Nature 583, 744–751 (2020).
Google Scholar
Liu, H. et al. Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain. Nature 624, 366–377 (2023).
Google Scholar
Li, Y. E. et al. An atlas of gene regulatory elements in adult mouse cerebrum. Nature 598, 129–136 (2021).
Google Scholar
Li, Y. E. et al. A comparative atlas of single-cell chromatin accessibility in the human brain. Science 382, eadf7044 (2023).
Google Scholar
Kim, K. & Jung, I. covNorm: An R package for coverage based normalization of Hi-C and capture Hi-C data. Comput. Struct. Biotechnol. J. 19, 3149–3159 (2021).
Google Scholar
Salameh, T. J. et al. A supervised learning framework for chromatin loop detection in genome-wide contact maps. Nat. Commun. 11, 3428 (2020).
Google Scholar
Wolff, J. et al. Galaxy HiCExplorer 3: a web server for reproducible Hi-C, capture Hi-C and single-cell Hi-C data analysis, quality control and visualization. Nucleic Acids Res. 48, W177–W184 (2020).
Google Scholar
Juric, I. et al. MAPS: model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments. PLoS Comput. Biol. 15, e1006982 (2019).
Google Scholar
Yang, D., Chung, T. & Kim, D. DeepLUCIA: predicting tissue-specific chromatin loops using deep learning-based universal chromatin interaction annotator. Bioinformatics 38, 3501–3512 (2022).
Google Scholar
Fudenberg, G. et al. Formation of chromosomal domains by loop extrusion. Cell Rep. 15, 2038–2049 (2016).
Google Scholar
Nichols, M. H. & Corces, V. G. A CTCF code for 3D genome architecture. Cell 162, 703–705 (2015).
Google Scholar
Sanborn, A. L. et al. Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes. Proc. Natl Acad. Sci. USA 112, E6456–E6465 (2015).
Google Scholar
Davidson, I. F. et al. CTCF is a DNA-tension-dependent barrier to cohesin-mediated loop extrusion. Nature 616, 822–827 (2023).
Google Scholar
Rahme, G. J. et al. Modeling epigenetic lesions that cause gliomas. Cell 186, 3674–3685 (2023).
Google Scholar
Schreiber, J., Singh, R., Bilmes, J. & Noble, W. S. A pitfall for machine learning methods aiming to predict across cell types. Genome Biol. 21, 282 (2020).
Google Scholar
Visel, A., Minovitsky, S., Dubchak, I. & Pennacchio, L. A. VISTA enhancer browser—a database of tissue-specific human enhancers. Nucleic Acids Res. 35, D88–D92 (2007).
Google Scholar
Song, M. et al. Cell-type-specific 3D epigenomes in the developing human cortex. Nature 587, 644–649 (2020).
Google Scholar
Schmitt, A. D. et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 17, 2042–2059 (2016).
Google Scholar
Lumpkin, E. A. et al. Math1-driven GFP expression in the developing nervous system of transgenic mice. Gene Expr. Patterns 3, 389–395 (2003).
Google Scholar
Abdul-Aziz, D., Hathiramani, N., Phung, L., Sykopetrites, V. & Edge, A. S. B. HIC1 represses Atoh1 transcription and hair cell differentiation in the cochlea. Stem Cell Rep. 16, 797–809 (2021).
Google Scholar
Lipton, S. A. et al. Autistic phenotype from MEF2C knockout cells. Science 323, 208 (2009).
Google Scholar
Li, H. et al. Transcription factor MEF2C influences neural stem/progenitor cell differentiation and maturation in vivo. Proc. Natl Acad. Sci. USA 105, 9397–9402 (2008).
Google Scholar
Yu, M. et al. SnapHiC: a computational pipeline to identify chromatin loops from single-cell Hi-C data. Nat. Methods 18, 1056–1059 (2021).
Google Scholar
Li, X. et al. SnapHiC2: a computationally efficient loop caller for single cell Hi-C data. Comput. Struct. Biotechnol. J. 20, 2778–2783 (2022).
Google Scholar
Zemke, N. R. et al. Conserved and divergent gene regulatory programs of the mammalian neocortex. Nature 624, 390–402 (2023).
Google Scholar
Jung, I. & Diao, Y. Mouse frontal cortex scHiCAR 22 cell types scDeepLUCIA loops. Zenodo https://doi.org/10.5281/zenodo.18196030 (2026).




