{"database":"GEO","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE328nnn/GSE328457/"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"omics_type":["Transcriptomics"],"species":["Homo sapiens"],"gds_type":["Expression profiling by high throughput sequencing"],"full_dataset_link":["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE328457"],"repository":["GEO"],"entry_type":["GSE"],"additional_accession":[]},"is_claimable":false,"name":"Pooled combinatorial screening identifies transcription factor sets that drive hematopoietic progenitor-like cell fate","description":"Mammalian cells can be directed towards specific fates by overexpression of transcription factors (TFs). However, discovering and optimizing which TFs in combination produce a state of interest remains challenging. Here, we develop a scalable screening platform that addresses this challenge by combining high-MOI pooled delivery of barcoded TF ORFs, data augmentation, targeted cell enrichments, and single-cell transcriptomic readouts. As proof of principle, we apply the platform to optimize the generation of hematopoietic stem and progenitor-like cells (HSPCs) from human embryonic stem cells. Our data demonstrate technical performance across a range of key metrics and reveal a richly structured reprogramming fitness landscape over millions of TF combinations. In silico optimization of HSPC-similarity metrics over this landscape revealed two TF combinations that demonstrate superior potency in generating naïve multipotent hematopoietic progenitors relative to gold-standard controls. This study demonstrates a powerful approach for data-driven cell fate engineering using complex combinatorial perturbations.","dates":{"publication":"2026/07/12"},"accession":"GSE328457","cross_references":{"GSM":["GSM9683920","GSM9683921","GSM9683919","GSM9683917","GSM9683918","GSM9683915","GSM9683916","GSM9683913","GSM9683914","GSM9683911","GSM9683912","GSM9683898","GSM9683910","GSM9683899","GSM9683896","GSM9683897","GSM9683894","GSM9683895","GSM9683892","GSM9683893","GSM9683890","GSM9683891","GSM9683908","GSM9683909","GSM9683906","GSM9683907","GSM9683926","GSM9683904","GSM9683905","GSM9683927","GSM9683902","GSM9683924","GSM9683925","GSM9683903","GSM9683900","GSM9683889","GSM9683922","GSM9683923","GSM9683901"],"GPL":["18573"],"GSE":["328457"],"taxon":["Homo sapiens"]}}