{
  "abstract": "Transcription is an inherently dynamic and stochastic process that often occurs in bursts, governed by gene–gene regulatory interactions and thereby driving cell-to-cell heterogeneity. However, a genome-wide, mechanistic understanding of how regulatory networks globally shape transcriptional bursting dynamics remains lacking. Here, we present BurstLink, an interpretable and tractable statistical-mechanistic framework that simultaneously infers coupled regulatory interactions and transcriptional bursting kinetics at the genome-wide scale from single-cell data. BurstLink introduces reweighted mutual information to quantify regulatory strength as network edge weights, while jointly inferring regulatory directionality and interaction type for each gene pair within a unified mechanistic model of transcriptional bursting. Applied to mouse embryonic fibroblasts data, BurstLink reveals several genome-wide regulatory mechanisms on transcriptional bursting: downstream target genes exhibit higher burst frequency and gene-expression variability than upstream transcription factor genes; stronger transcription factor binding affinity is associated with lower burst frequency and higher burst size of target genes. Notably, positive regulation primarily enhances the burst frequency and gene-expression variability in target genes, in contrast to negative regulation. In summary, BurstLink deciphers multiple general principles of global transcriptional dynamics, providing novel biological insights into cell fate decisions.",
  "abstract_shown": true,
  "affiliations": [
    "School of Mathematics, Sun Yat-sen University, Guangzhou, 510275 China",
    "Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, 510275 China",
    "Department of Mathematics, University of California Irvine, Irvine, CA 92627 USA",
    "School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou, 510520 China"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Liying Zhou",
      "orcid": "0009-0004-9648-2696"
    },
    {
      "affs": [
        2
      ],
      "name": "Songhao Luo",
      "orcid": "0000-0003-1162-9608"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Zhiwei Huang"
    },
    {
      "affs": [
        3
      ],
      "name": "Zhenquan Zhang",
      "orcid": "0000-0002-2913-4905"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Zihao Wang",
      "orcid": "0000-0001-5440-843X"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Jiajun Zhang",
      "orcid": "0000-0001-7107-4814"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4ejn385jry4ay.bib",
  "cited_by": 1,
  "doi": "10.1038/s44320-026-00235-4",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13728105/",
  "id": "4ejn385jry4ay",
  "issns": [
    "1744-4292"
  ],
  "landing_url": "https://doi.org/10.1038/s44320-026-00235-4",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "1312|Gene Regulatory Network Analysis"
    ]
  ],
  "openalex": "W7172303703",
  "pdf_url": "https://link.springer.com/content/pdf/10.1038/s44320-026-00235-4.pdf",
  "pmcid": "PMC13728105",
  "pmid": "42547851",
  "published": "2026-08-03",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/4ejn385jry4ay.ris",
  "sources": [
    {
      "first_seen": "2026-11-06T12:23:51Z",
      "native_id": "PMC13728105",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s44320-026-00235-4"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Gene Regulatory Network Analysis",
      "subfield": "molecular-biology"
    }
  ],
  "title": "Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data",
  "title_text": "Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T12:23:51Z",
  "url": "https://research.draconitic.com/paper/4ejn385jry4ay",
  "venue": "Molecular Systems Biology",
  "versions": []
}