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Knock-down of lncRNA SNHG26 in human embryonic stem cells

GSE317557 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2026/08/01 Platform GPL26167
Summary
The recent development of long-read RNA sequencing (lrRNAseq) technologies has paved the way to the exploration of RNA isoform diversity and its relevance to better understand the gene regulatory network that sustains cell fate and plasticity. However, drawing conclusions regarding the functionality of these newly identified isoforms is still very scarce. Here, we devised a very efficient system to reprogram cells towards an induced pluripotent cell state and leveraged the strengths of lrRNAseq in order to study the isoform diversity of reprogramming. This strategy enabled us to identify differential isoforms throughout the reprogramming process, with a pressure on novel non-coding isoforms to be regulated. More specifically, we highlight a new long non-coding RNA (lncRNA), Snhg26 whose isoform switch during reprogramming enhances the conversion of cells’ identity towards pluripotency. We showes that knocking-down this lncRNA in mouse embryonic stem cells hinders the maintenance of a pluripotent state and primes the cells for differentiation. Additionally, with the data presented here, we show knockdown of the human SNHG26 is associated with loss of naive pluripotency markers in human embryonic stem cells. Together, our study provides a comprehensive resource to study full-length isoform regulation and mechanisms at stake during reprogramming, but more importantly it demonstrates the power of lrRNAseq to identify functionally relevant gene isoforms in the context of pluripotency.
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Direct links to NCBI, no account and no request form: the whole study as GSE317557_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1414461 and SRA study SRP666424. Searching any of these in the dataset finder brings you back here.

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