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

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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Publication Details

Journal
Molecular Systems Biology
Published
2026-08-03
DOI
https://doi.org/10.1038/s44320-026-00235-4
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Songhao Luo, Zhenquan Zhang, Liying Zhou, Jiajun Zhang et al.
Molecular Systems Biology
Single-cell and spatial transcriptomics
article

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

Songhao Luo, Zhenquan Zhang, Liying Zhou, Jiajun Zhang, Zihao Wang, Zhiwei Huang
article en

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.

Molecular Systems Biology
Guangdong University of Technology (CN), Sun Yat-sen University (CN), University of California, Irvine (US)
National Natural Science Foundation of China, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 15%
Single-cell and spatial transcriptomics
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