{"doi":"10.1093/bib/bbaf520","title":"Navigating the 3D genome at single-cell resolution: techniques, computation, and mechanistic landscapes","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>The 3D organization of the genome is critical for gene expression regulation, cellular identity, and disease progression. Traditional methods that analyze bulk genomic data often obscure cell-to-cell heterogeneity, limiting the resolution of intrinsic variability within complex biological systems. To overcome this, single-cell 3D genomics has emerged, revealing chromatin architecture at the individual cell level. Advanced experimental approaches enable genome-wide chromatin contact mapping, while computational frameworks reconstruct dynamic chromatin topologies from high-dimensional data. Building on these breakthroughs, recent advances in single-cell 3D genomics have led to transformative progress in epigenetics, linking 3D genome architecture with gene regulation, cellular identity, and disease phenotypes. This review focuses on the breakthroughs in single-cell 3D genomics, demonstrating how integrated experimental, computational, and mechanistic approaches decode chromatin architecture. These insights have deepened the understanding of genome function at the single-cell level and lay the foundation for future advances in precision medicine and topology-guided therapeutic strategies.</jats:p>","journal":"Briefings in Bioinformatics","year":2025,"id":624874,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1615504,"name":"Kaiyuan Han","orcid":null,"position":1,"is_corresponding":false},{"id":1615505,"name":"Yuduo Hao","orcid":null,"position":2,"is_corresponding":false},{"id":608871,"name":"Wei Su","orcid":"0000-0002-8578-6203","position":3,"is_corresponding":false},{"id":1525446,"name":"Xueqin Xie","orcid":"0000-0002-7807-9930","position":4,"is_corresponding":false},{"id":683976,"name":"Xiaolong Li","orcid":"0000-0002-6647-5565","position":5,"is_corresponding":false},{"id":1615507,"name":"Qiuming Chen","orcid":null,"position":6,"is_corresponding":false},{"id":1615508,"name":"Yijie Wei","orcid":null,"position":7,"is_corresponding":false},{"id":1304531,"name":"Xinwei Luo","orcid":null,"position":8,"is_corresponding":false},{"id":1615509,"name":"Sijia Xie","orcid":null,"position":9,"is_corresponding":false},{"id":1226309,"name":"Benjamin Lebeau","orcid":"0000-0003-1218-2983","position":10,"is_corresponding":false},{"id":1615510,"name":"Crystal Ling","orcid":null,"position":11,"is_corresponding":false},{"id":1595729,"name":"Hao Lv","orcid":"0000-0002-7580-0155","position":12,"is_corresponding":false},{"id":1064426,"name":"Li Liu","orcid":"0000-0001-6126-2635","position":13,"is_corresponding":false},{"id":89721,"name":"Hao Lin","orcid":"0000-0001-6265-2862","position":14,"is_corresponding":false},{"id":288716,"name":"Fanny Dao","orcid":"0000-0001-5285-6044","position":15,"is_corresponding":false},{"id":1615503,"name":"Feitong Hong","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Navigating the 3D genome at single-cell resolution: techniques, computation, and mechanistic landscapes","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>The 3D organization of the genome is critical for gene expression regulation, cellular identity, and disease progression. Traditional methods that analyze bulk genomic data often obscure cell-to-cell heterogeneity, limiting the resolution of intrinsic variability within complex biological systems. To overcome this, single-cell 3D genomics has emerged, revealing chromatin architecture at the individual cell level. Advanced experimental approaches enable genome-wide chromatin contact mapping, while computational frameworks reconstruct dynamic chromatin topologies from high-dimensional data. Building on these breakthroughs, recent advances in single-cell 3D genomics have led to transformative progress in epigenetics, linking 3D genome architecture with gene regulation, cellular identity, and disease phenotypes. This review focuses on the breakthroughs in single-cell 3D genomics, demonstrating how integrated experimental, computational, and mechanistic approaches decode chromatin architecture. 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