ArticleNature cell biology2025
Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens.
Article in Nature cell biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Article
- ZBP1 in Neuroinflammation and Neurodegeneration: Z-Nucleic-Acid Sensing, RHIM Signalling and Therapeutic Targeting.International journal of molecular sciences · 2026Review
- Article
- Region-Level Design and Analysis of CRISPR Perturbation Screens with FRACTEL.bioRxiv : the preprint server for biology · 2026Article
- Causal effect estimation from trans-regulatory single-cell CRISPR screens.Cell genomics · 2026Review
- PSGRN: Gene regulatory network inference from single-cell perturbational data through self-training with synthetic gold standards.Science advances · 2026Article
- Interpretation, extrapolation and perturbation of single cells.Nature reviews. Genetics · 2026Review
- Artificial intelligence and multiomics integration for Parkinson's disease drug development.Molecules and cells · 2026Review
- Multiomic single-cell perturbation screens reveal critical lncRNA regulators of senescence.Nature aging · 2026Article
- Spatial perturb-seq: single-cell functional genomics within intact tissue architecture.Nature communications · 2026Article
- Genome-wide single-cell perturbation screens with VIPerturb-seq.bioRxiv : the preprint server for biology · 2026Article
- CRISPR screens in the context of immune selection identify CHD1 and MAP3K7 as mediators of cancer immunotherapy resistance.Cell reports. Medicine · 2026Article
- ClinMAVE: a curated database for clinical application of data from multiplexed assays of variant effect.Nucleic acids research · 2026Article
- Regulators of interferon-responsive microglia uncovered by Genome-wide CRISPRi screening.NPJ dementia · 2026Article
- Airqtl dissects cell state-specific causal gene regulatory networks with efficient single-cell eQTL mapping.Nature communications · 2025Article
- Transcriptional regulation of disease-relevant microglial activation programs.bioRxiv : the preprint server for biology · 2025Article
- Mapping transcriptional responses to cellular perturbation dictionaries with RNA fingerprinting.bioRxiv : the preprint server for biology · 2025Article
- Mouse-Specific Single cell cytokine activity prediction and Estimation (MouSSE).PLoS computational biology · 2025Article
- Iterative, multimodal, and scalable single-cell profiling for discovery and characterization of signaling regulators.bioRxiv : the preprint server for biology · 2025Article
- Fluctuation structure predicts genome-wide perturbation outcomes.Research square · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Recent advancements in functional genomics have provided an unprecedented ability to measure diverse molecular modalities, but predicting causal regulatory relationships from observational data remains challenging. Here, we leverage pooled genetic screens and single-cell sequencing (Perturb-seq) to systematically identify the targets of signalling regulators in diverse biological contexts. We demonstrate how Perturb-seq is compatible with recent and commercially available advances in combinatorial indexing and next-generation sequencing, and perform more than 1,500 perturbations split across six cell lines and five biological signalling contexts. We introduce an improved computational framework (Mixscale) to address cellular variation in perturbation efficiency, alongside optimized statistical methods to learn differentially expressed gene lists and conserved molecular signatures. Finally, we demonstrate how our Perturb-seq derived gene lists can be used to precisely infer changes in signalling pathway activation for in vivo and in situ samples. Our work enhances our understanding of signalling regulators and their targets, and lays a computational framework towards the data-driven inference of an 'atlas' of perturbation signatures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.