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Parallel genome-scale CRISPR-Cas9 screens uncouple human pluripotent stem cell identity versus fitness [bulk RNA-seq]

ABSTRACT: Pluripotent stem cells are defined by their self-renewal capacity, which is the ability of the stem cells to proliferate indefinitely while maintaining the pluripotent identity essential for their ability to differentiate into any somatic cell lineage. However, understanding the mechanisms that control stem cell fitness versus the pluripotent cell identity is challenging. To investigate the interplay between these two aspects of pluripotency, we performed four parallel genome-scale CRISPR-Cas9 loss-of-function screens interrogating stem cell fitness in hPSC self-renewal conditions, and the dissolution of the primed pluripotency identity during early differentiation. Comparative analyses led to the discovery of genes with distinct roles in pluripotency regulation, including mitochondrial and metabolism regulators crucial for stem cell fitness, and chromatin regulators that control pluripotent identity during early differentiation. We further discovered a core set of factors that control both stem cell fitness and pluripotent identity, including a network of chromatin factors that safeguard pluripotency. Our unbiased and systematic screening and comparative analyses disentangle two interconnected aspects of pluripotency, provide rich datasets for exploring pluripotent cell identity versus cell fitness, and offer a valuable model for categorizing gene function in broad biological contexts.

ORGANISM(S): Homo sapiens

PROVIDER: GSE277070 | GEO | 2024/09/12

REPOSITORIES: GEO

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Project description:Chavez2009 - a core regulatory network of OCT4 in human embryonic stem cells A core OCT4-regulated network has been identified as a test case, to analyase stem cell characteristics and cellular differentiation. This model is described in the article: In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach. Chavez L, Bais AS, Vingron M, Lehrach H, Adjaye J, Herwig R BMC Genomics, 2009, 10:314 Abstract: BACKGROUND: The transcription factor OCT4 is highly expressed in pluripotent embryonic stem cells which are derived from the inner cell mass of mammalian blastocysts. Pluripotency and self renewal are controlled by a transcription regulatory network governed by the transcription factors OCT4, SOX2 and NANOG. Recent studies on reprogramming somatic cells to induced pluripotent stem cells highlight OCT4 as a key regulator of pluripotency. RESULTS: We have carried out an integrated analysis of high-throughput data (ChIP-on-chip and RNAi experiments along with promoter sequence analysis of putative target genes) and identified a core OCT4 regulatory network in human embryonic stem cells consisting of 33 target genes. Enrichment analysis with these target genes revealed that this integrative analysis increases the functional information content by factors of 1.3 - 4.7 compared to the individual studies. In order to identify potential regulatory co-factors of OCT4, we performed a de novo motif analysis. In addition to known validated OCT4 motifs we obtained binding sites similar to motifs recognized by further regulators of pluripotency and development; e.g. the heterodimer of the transcription factors C-MYC and MAX, a prerequisite for C-MYC transcriptional activity that leads to cell growth and proliferation. CONCLUSION: Our analysis shows how heterogeneous functional information can be integrated in order to reconstruct gene regulatory networks. As a test case we identified a core OCT4-regulated network that is important for the analysis of stem cell characteristics and cellular differentiation. Functional information is largely enriched using different experimental results. The de novo motif discovery identified well-known regulators closely connected to the OCT4 network as well as potential new regulators of pluripotency and differentiation. These results provide the basis for further targeted functional studies. This model is hosted on BioModels Database and identified by: MODEL1305010000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.