The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Feb. 27, 2024
Filed:
Sep. 22, 2020
The Regents of the University of California, Oakland, CA (US);
Prashant Mali, La Jolla, CA (US);
Udit Parekh, La Jolla, CA (US);
Yan Wu, La Jolla, CA (US);
Kun Zhang, La Jolla, CA (US);
The Regents of the University of California, Oakland, CA (US);
Abstract
Understanding the complex effects of genetic perturbations on cellular state and fitness in human pluripotent stem cells (hPSCs) has been challenging using traditional pooled screening techniques which typically rely on unidimensional phenotypic readouts. Here, Applicants use barcoded open reading frame (ORF) overexpression libraries with a coupled single-cell RNA sequencing (scRNA-seq) and fitness screening approach, a technique we call SEUSS (ScalablE fUnctional Screening by Sequencing), to establish a comprehensive assaying platform. Using this system, Applicants perturbed hPSCs with a library of developmentally critical transcription factors (TFs), and assayed the impact of TF overexpression on fitness and transcriptomic cell state across multiple media conditions. Applicants further leveraged the versatility of the ORF library approach to systematically assay mutant gene libraries and also whole gene families. From the transcriptomic responses, Applicants built genetic co-perturbation networks to identify key altered gene modules. Strikingly, we found that KLF4 and SNAI2 have opposing effects on the pluripotency gene module, highlighting the power of this method to characterize the effects of genetic perturbations. From the fitness responses, Applicants identified ETV2 as a driver of reprogramming towards an endothelial-like state.