bioRxivGenomicsPreprint
Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq
Kathryn Geiger-SchulleriD, Basak EraslaniD, Olena KuksenkoiD, Kushal K. DeyiD, Karthik A. JagadeeshiD, Pratiksha I. Thakore, Özge KarayeliD, Andrea R. YungiD, Anugraha R. RajagopalaniD, Ana M. MeirelesiD, Karren YangiD, Liat Amir-Zilberstein, Toni Marie DeloreyiD, Devan PhillipsiD, Raktima Raychowdhury, Christine MoussioniD, Alkes L. PriceiD, Nir HacoheniD, John G. DoenchiD, Caroline UhleriD, Orit Rozenblatt–RoseniD, Aviv RegeviD
Abstract
E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation. Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle. Genetic interactions were more prevalent within than between modules, and a deep learning model, com{beta}VAE, predicts the outcome of new combinations by leveraging modularity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.
- organism: mouse
- assay: CRISPR screen
- research focus: perturbation response prediction
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: deep learning
- approach: experimental assay
- Citations
- 22
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