ArticleCell systems2018
Mapping Cellular Reprogramming via Pooled Overexpression Screens with Paired Fitness and Single-Cell RNA-Sequencing Readout.
Article in Cell systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
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Who cites it
41 citing papers in PubMed.
- Developmental and MAPK-responsive transcription factors regulate distinct malignant cell states and associated genetic dependencies in pancreatic cancer.Nature genetics · 2026Article
- Benchmarking methods for inferring single-cell transcription factor activity using large-scale perturbation sequencing data.Briefings in bioinformatics · 2026Article
- Knowledge-guided contextual gene set analysis with large language models.Bioinformatics (Oxford, England) · 2026Article
- Computational blueprints for cell fate programming.Stem cell reports · 2026Review
- Combinatorial transcription factor interactions drive modular gene regulatory networks.bioRxiv : the preprint server for biology · 2026Article
- Systematic mapping of chromatin dysregulation driven by viral transcriptional regulators at scale.bioRxiv : the preprint server for biology · 2026Article
- Chemical optimization of the exercise mimetic SLU-PP-332 enables insight into estrogen-related receptor signaling.International journal of biological macromolecules · 2026Article
- Benchmarking algorithms for generalizable single-cell perturbation response prediction.Nature methods · 2026Article
- An inducible model of human post-implantation development derived from primed and naive stem cells.Cell stem cell · 2025Article
- Dissecting the impact of transcription factor dose on cell reprogramming heterogeneity using scTF-seq.Nature genetics · 2025Article
- Genome-wide CRISPR screen identifies Menin and SUZ12 as regulators of human developmental timing.Nature cell biology · 2025Article
- An automated ATAC-seq method reveals sequence determinants of transcription factor dose response in the open chromatin.bioRxiv : the preprint server for biology · 2025Article
- Refate identifies chemical compounds to target trans-regulatory networks for cellular conversion.bioRxiv : the preprint server for biology · 2025Article
- Large-scale discovery of chromatin dysregulation induced by oncofusions and other protein-coding variants.Nature biotechnology · 2025Article
- Gene regulation technologies for gene and cell therapy.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Review
- Identification of Cell Fate Determining Transcription Factors for Generating Brain Endothelial Cells.Stem cell reviews and reports · 2025Article
- Castrate-resistant prostate cancer response to taxane is determined by an HNF1-dependent apoptosis resistance circuit.Cell reports. Medicine · 2024Article
- Epigenome editing technologies for discovery and medicine.Nature biotechnology · 2024Review
- Interface-guided phenotyping of coding variants in the transcription factor RUNX1.Cell reports · 2024Article
- Long-term expandable mouse and human-induced nephron progenitor cells enable kidney organoid maturation and modeling of plasticity and disease.Cell stem cell · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Understanding the effects of genetic perturbations on the cellular state has been challenging using traditional pooled screens, which typically rely on the delivery of a single perturbation per cell and unidimensional phenotypic readouts. Here, we use barcoded open reading frame overexpression libraries coupled with single-cell RNA sequencing to assay cell state and fitness, a technique we call SEUSS (scalable functional screening by sequencing). Using SEUSS, we perturbed hPSCs with a library of developmentally critical transcription factors (TFs) and assayed the impact of TF overexpression on fitness and transcriptomic states. We further leveraged the versatility of the ORF library approach to assay mutant genes and whole gene families. From the transcriptomic responses, we built genetic co-regulatory networks to identify altered gene modules and found that KLF4 and SNAI2 drive opposing effects along the epithelial-mesenchymal transition axis. From the fitness responses, we identified ETV2 as a driver of reprogramming toward an endothelial-like state.
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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.