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PerturbSci-Kinetics: Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens

Xu, Z.; Sziraki, A.; Lee, J.; Zhou, W.; Cao, J.

2023-01-31 genomics
10.1101/2023.01.29.526143 bioRxiv
Show abstract

Here we described PerturbSci-Kinetics, a novel combinatorial indexing method for capturing three-layer single-cell readout (i.e., whole transcriptomes, nascent transcriptomes, sgRNA identities) across hundreds of genetic perturbations. Through PerturbSci-Kinetics profiling of pooled CRISPR screens targeting a variety of biological processes, we were able to decipher the complexity of RNA regulations at multiple levels (e.g., synthesis, processing, degradation), and revealed key regulators involved in miRNA and mitochondrial RNA processing pathways. Our technique opens the possibility of systematically decoding the genome-wide regulatory network underlying RNA temporal dynamics at scale and cost-effectively.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.