Comprehensive perturbation of transcription factors in human cardiomyocytes reveals the regulatory architecture of congenital heart disease

Over 100 genes have been implicated in congenital heart disease (CHD), yet the genetic basis for >50% of CHD remains unexplained. A key challenge is to define the regulatory architecture of CHD genes. Here, we systematically perturb 1983 transcription factors (TFs) during cardiomyocyte differentiation of human stem cells. Our analysis links TFs to gene expression phenotypes across scales and nominates TFs in cardiac cell fate commitment, dosage sensitivity, and transposable element regulation. By deriving TF-gene regulatory networks from experimental perturbation, we gain insights into how developmental networks are structured, use this map to interpret the regulatory architecture of CHD, and deorphanize TFs with roles in CHD that have been under-sampled by genetic studies. To extend these networks to include enhancer-TF-gene linkages, we also perturb 981 putative enhancers of TFs. Finally, we develop a deep learning transformer model to accurately predict perturbed TFs from altered transcriptomes, which we apply to interpret CHD patient transcriptomes. This reference map represents a foundational platform to model the functions of TFs and aids in interpreting CHD variants and mechanisms.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2025-12-17
DOI
https://doi.org/10.64898/2025.12.15.694070
Primary Topic
Congenital heart defects research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive perturbation of transcription factors in human cardiomyocytes reveals the regulatory architecture of congenital heart disease

Sushama Sivakumar, Anjana Sundarrajan, Minnie Deng, W. Lee Kraus et al.
bioRxiv (Cold Spring Harbor Laboratory)
Congenital heart defects research
article

Comprehensive perturbation of transcription factors in human cardiomyocytes reveals the regulatory architecture of congenital heart disease

Sushama Sivakumar, Anjana Sundarrajan, Minnie Deng, W. Lee Kraus, Jun Wu, Maria H. Chahrour, Bruce A. Posner, Sean C. Goetsch, Gary C. Hon, Chikara Takeuchi, Lin Xu, Yihan Wang, Lei Wang, Nikhil Munshi, Mpathi Nzima, Huan Zhao, Krishnaji Kulkarni
article en

Abstract

Over 100 genes have been implicated in congenital heart disease (CHD), yet the genetic basis for >50% of CHD remains unexplained. A key challenge is to define the regulatory architecture of CHD genes. Here, we systematically perturb 1983 transcription factors (TFs) during cardiomyocyte differentiation of human stem cells. Our analysis links TFs to gene expression phenotypes across scales and nominates TFs in cardiac cell fate commitment, dosage sensitivity, and transposable element regulation. By deriving TF-gene regulatory networks from experimental perturbation, we gain insights into how developmental networks are structured, use this map to interpret the regulatory architecture of CHD, and deorphanize TFs with roles in CHD that have been under-sampled by genetic studies. To extend these networks to include enhancer-TF-gene linkages, we also perturb 981 putative enhancers of TFs. Finally, we develop a deep learning transformer model to accurately predict perturbed TFs from altered transcriptomes, which we apply to interpret CHD patient transcriptomes. This reference map represents a foundational platform to model the functions of TFs and aids in interpreting CHD variants and mechanisms.

bioRxiv (Cold Spring Harbor Laboratory)
Southwestern Medical Center (US), Southwestern Medical Center (US), The University of Texas Southwestern Medical Center (US)
Openalex Percentile: Top 63%
Congenital heart defects research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.