Project description:Here, we performed RNA-interactome capture (RIC) on nuclear fractions from human embryonic stem cells (hESCs). The poly(A)+ RNA-bound proteome was determined by UV light-mediated cross-linking (CL) of RNAs to proteins in living cells, followed by nuclei isolation, oligo(dT) purification of poly(A)-RNA-protein complexes, and mass spectrometry analysis of captured proteins. As a control, we applied a similar strategy to non-cross-linked (non-CL) samples. RIC was performed in four independent biological replicates. This data accompanies the manuscript: "Uncovering the RNA-binding protein landscape in the pluripotency network of human embryonic stem cells". Abstract: "Embryonic stem cell (ESC) self-renewal and cell-fate decisions are driven by a broad array of molecular signals. While transcriptional regulators have been extensively studied in human ESCs (hESCs), the extent to which RNA-binding proteins (RBPs) contribute to human pluripotency remains unclear. Here, we carry out a proteome-wide screen and identify 810 proteins that directly bind RNA in hESCs. We reveal that RBPs are preferentially expressed in hESCs and dynamically regulated during exit from pluripotency and early lineage specification. Moreover, we show that nearly 200 RBPs are affected by knockdown of OCT4, a master regulator of pluripotency, several dozen of which are directly bound by this factor. Intriguingly, over 20 percent of the proteins detected in our study are putative DNA- and RNA-binding proteins (DRBPs), among them key transcription factors (TFs). Using fluorescently labeled RNA and seCLIP (single-end enhanced crosslinking and immunoprecipitation) experiments, we discover that the pluripotency-associated STAT3 and OCT4 TFs interact with RNA in hESCs and confirm the direct binding of STAT3 to the conserved NORAD long-noncoding RNA. Taken together, our findings indicate that RBPs have a more widespread role in human pluripotency than previously appreciated, reinforcing the importance of post-transcriptional regulation in stem cell biology".
Project description:The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNA sequencing on commercially available embryonic stem cell lines as control samples against which to compare HipSci's iPS cell lines.
Project description:Embryonic stem cell (ESC) self-renewal and cell-fate decisions are driven by a broad array of molecular signals. While transcriptional regulators have been extensively studied in human ESCs (hESCs), the extent to which RNA-binding proteins (RBPs) contribute to human pluripotency remains unclear. Here, we carried out a proteome-wide screen and identified 810 proteins that directly bind RNA in hESCs. We determined the RBP catalog by using RNA-interactome capture (RIC), a method based on UV light-mediated cross-linking (CL) of RNAs to proteins in living cells, followed by oligo(dT) purification of poly(A)-RNA-protein complexes and mass spectrometry analysis of captured proteins. As control, we applied a similar strategy to non-cross-linked (non-CL) samples. To uncover the identity of the eluted proteins, we performed in-solution tryptic digestion of CL and non-CL eluates and analyzed their contents by a high-resolution mass spectrometer (Q-Exactive Plus). We then performed differential proteome analysis between CL and non-CL eluates, resulting in a set of 810 high-confidence protein groups, defined as the hESC RNA-interactome. RIC was carried out in four independent biological replicates. This data accompanies the manuscript: "Uncovering the RNA-binding protein landscape in the pluripotency network of human embryonic stem cells".
Project description:In order to investigate the characteristics and mechanisms of embryonic stem cell derived exosomes attenuates transverse aortic constriction induced ventricular remodeling, the proteomic profiles of human embryonic stem cell derived exosomes were analysed by label-free quantification.
