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Peer-reviewedCC BY 4.0Molecular Systems Biology

Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data

  • Liying Zhou1,2
  • Songhao Luo3
  • Zhiwei Huang1,2
  • Zhenquan Zhang4
  • Zihao Wang1,2
  • Jiajun Zhang1,2
4 affiliations
  1. 1School of Mathematics, Sun Yat-sen University, Guangzhou, 510275 China
  2. 2Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, 510275 China
  3. 3Department of Mathematics, University of California Irvine, Irvine, CA 92627 USA
  4. 4School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou, 510520 China
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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.

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Cite

BibTeXRIS
BibTeX
@article{zhou2026deciphering,
  title = {{Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data}},
  author = {Liying Zhou and Songhao Luo and Zhiwei Huang and Zhenquan Zhang and Zihao Wang and Jiajun Zhang},
  journal = {Molecular Systems Biology},
  year = {2026},
  month = aug,
  doi = {10.1038/s44320-026-00235-4},
  url = {https://doi.org/10.1038/s44320-026-00235-4},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Deciphering global transcriptional dynamics coordinated by gene-gene regulatory interactions using single-cell data
AU  - Liying Zhou
AU  - Songhao Luo
AU  - Zhiwei Huang
AU  - Zhenquan Zhang
AU  - Zihao Wang
AU  - Jiajun Zhang
PY  - 2026
DA  - 2026/08/03
JO  - Molecular Systems Biology
DO  - 10.1038/s44320-026-00235-4
UR  - https://doi.org/10.1038/s44320-026-00235-4
AB  - 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.
SN  - 1744-4292
ER  -