Project description:eCLIP was performed for ENO1 in HeLa cells, following the protocol described by Van Nostrand et al. (2016). Libraries for six immunoprecipitation and size-matched input controls were produced. In addition, libraries were produced for two no-crosslinking controls. The libraries were sequenced using paired-end sequencing (PE125) on an Illumina HiSeq2000 platform.
Project description:CD47 is a transmembrane glycoprotein that is ubiquitously expressed in different organs and tissues (Barclay and Van den Berg 2014; Liu, et al. 2017). In the human immune system, CD47 interacts with some integrins, two counter-receptor signal regulator protein (SIRP) family members, and the secreted thrombospondin-1 (TSP1) (Barclay and Van den Berg 2014; Gao, et al. 2016; Kaur, et al. 2013; Oldenborg, et al. 2000). CD47 has two established roles in the immune system. The CD47-SIRPα interaction was identified as a critical innate immune checkpoint, which delivers an antiphagocytic signal to macrophages and inhibits neutrophil cytotoxicity (Martínez- Sanz, et al. 2021). Its interaction with inhibitory SIRPα is a physiological anti-phagocytic “don’t eat me” signal on circulating red blood cells that is co-opted by cancer cells (Matlung, et al. 2017). Many malignant cells overexpress CD47 (Betancur, et al. 2017; Chao, et al. 2011; Jaiswal, et al. 2009; Majeti, et al. 2009; Oronsky, et al. 2020; Petrova, et al. 2017). CD47/SIRPα-targeted therapeutics have been developed to overcome this immune checkpoint for cancer treatment (Kaur, et al. 2020; Matlung, et al. 2017). Secondly, engagement of CD47 on T cells by TSP1 regulates their differentiation and survival (Grimbert, et al. 2006; Lamy, et al. 2007) and inhibits T cell receptor signaling and antigen presentation by dendritic cells (DCs) (Kaur, et al. 2014; Li, et al. 2002; Liu, et al. 2015; Miller, et al. 2013; Soto-Pantoja, et al. 2014; Weng, et al. 2014). TSP1/CD47 signaling has similar inhibitory functions to limit NK cell activation (Kim, et al. 2008; Nath, et al. 2018; Nath, et al. 2019; Schwartz, et al. 2019) and IL1β production by macrophages (Stein, et al. 2016). CD47 is therefore a checkpoint that regulates both innate and adaptive immunity. The recent understanding of CD47 antagonism associated with increased antigen presentation by DCs (Liu, et al. 2016) and natural killer cell cytotoxicity (Nath, et al. 2019) contributes to the heightened interest in CD47 as a therapeutic target (Kaur, et al. 2020).
Project description:S. aureus strain JKD6009 RNase III-HTF and USA300 RNase III-HTF were used in our study to capture the RNA-binding proteome in Staphylococcus aureus. Both strains were inoculated in TSB (Tryptone soya broth, Oxioid CM0129) and overnight cultured in 37°C, 200 rpm shaker. Strain JKD6009 RNase III-HTF was sub-cultured into 190 ml LPM (Coombes et al., 2004) (Low phosphate, low magnesium medium, 5 mM KCl, 7.5 mM (NH4)2SO4, 0.5 mM K2SO4, 8 µM MgCl2, 1 M KH2PO4, 16 mM Tris-HCl, 0.1% casamino acids, 0.3% Glycerol) and grew from OD600 0.01 to 1. Overnight cultures of USA300 RNase III-HTF was re-inoculated to 65 ml fresh TSB to OD600 0.05 and left to grow to an OD600 of ~3. Cells were then filtered through 0.45 µm filters using a vacuum filtration device (UVO3; (McKellar et al., JoVe 2020; Van Nues et al., Nature Communications 2017)) shifted to same volume of LPM medium for 15 min at 37ºC and UV irradiated in LPM in the Vari-X-linker (λ =254 nm) (https://www.vari-x-link.com; (McKellar et al., 2020; Van Nues et al., 2017)) with an energy dose of 2J/cm2. In total, 6 replicates were collected (three technical and two biological replicates) for each experiment.
Project description:S. aureus strain JKD6009 RNase III-HTF and USA300 RNase III-HTF were used in our study to capture the RNA-binding proteome in Staphylococcus aureus. Both strains were inoculated in TSB (Tryptone soya broth, Oxioid CM0129) and overnight cultured in 37°C, 200 rpm shaker. Strain JKD6009 RNase III-HTF was sub-cultured into 190 ml LPM (Coombes et al., 2004) (Low phosphate, low magnesium medium, 5 mM KCl, 7.5 mM (NH4)2SO4, 0.5 mM K2SO4, 8 µM MgCl2, 1 M KH2PO4, 16 mM Tris-HCl, 0.1% casamino acids, 0.3% Glycerol) and grew from OD600 0.01 to 1. Overnight cultures of USA300 RNase III-HTF was re-inoculated to 65 ml fresh TSB to OD600 0.05 and left to grow to an OD600 of ~3. Cells were then filtered through 0.45 µm filters using a vacuum filtration device (UVO3; (McKellar et al., JoVe 2020; Van Nues et al., Nature Communications 2017)) shifted to same volume of LPM medium for 15 min at 37ºC and UV irradiated in LPM in the Vari-X-linker (λ =254 nm) (https://www.vari-x-link.com; (McKellar et al., 2020; Van Nues et al., 2017)) with an energy dose of 2J/cm2. In total, 6 replicates were collected (three technical and two biological replicates) for each experiment.
Project description:S. aureus strain JKD6009 RNase III-HTF and USA300 RNase III-HTF were used in our study to capture the RNA-binding proteome in Staphylococcus aureus. Both strains were inoculated in TSB (Tryptone soya broth, Oxioid CM0129) and overnight cultured in 37°C, 200 rpm shaker. Strain JKD6009 RNase III-HTF was sub-cultured into 190 ml LPM (Coombes et al., 2004) (Low phosphate, low magnesium medium, 5 mM KCl, 7.5 mM (NH4)2SO4, 0.5 mM K2SO4, 8 µM MgCl2, 1 M KH2PO4, 16 mM Tris-HCl, 0.1% casamino acids, 0.3% Glycerol) and grew from OD600 0.01 to 1. Overnight cultures of USA300 RNase III-HTF was re-inoculated to 65 ml fresh TSB to OD600 0.05 and left to grow to an OD600 of ~3. Cells were then filtered through 0.45 µm filters using a vacuum filtration device (UVO3; (McKellar et al., JoVe 2020; Van Nues et al., Nature Communications 2017)) shifted to same volume of LPM medium for 15 min at 37ºC and UV irradiated in LPM in the Vari-X-linker (λ =254 nm) (https://www.vari-x-link.com; (McKellar et al., 2020; Van Nues et al., 2017)) with an energy dose of 2J/cm2. In total, 6 replicates were collected (three technical and two biological replicates) for each experiment.
Project description:These files represent single cell RNA-Seq data generated on a 10x Chromium genomics platform from four biological replicates of iPSC-derived human kidney organoids, in two batches, differentiated according to our published protocol (Takasato et al., Nature Protocols 2016). The aggregated human organoid data contains populations representing endothelial cells, podocytes, stroma, nephron, and off-target populations with similarity to neurons.
Project description:The experiment was designed to look into chromatin accessibility changes during cell cycle progression in human embryonic stem cells (hESCs) during definitive endoderm differentiation. For this, FUCCI hESCs were sorted in Early G1 (EG1), and differentiation into endoderm was performed for up to 72 hours with a combination of cytokines as described in Pauklin and Vallier (2013) and Pauklin et al. (2016). Samples at 0, 12, 24, 36, 48 and 72 hours were generated from two independent experiments, with 100,000 cells per sample, as previously described in Kumasaka et al. (2016). Library preparation and sequencing were performed at the Wellcome Sanger Institute next-generation sequencing facility. ATAC-seq libraries were prepared with one of i5 and i7 Nextera tags combination (see protocol details), and pooled equimolarly. Sequencing was performed on Illumina HiSeq 2000, 2 x 75bp paired-end reads.
Project description:These files represent single cell RNA-Seq data generated on a 10x Chromium genomics platform from three biological replicates from the embryonic day (E)18.5 developing mouse kidney and three biological replicates of iPSC-derived human kidney organoids differentiated according to our published protocol (Takasato et al., Nature Protocols 2016). When aggregated, the mouse data represents >6000 cells that passed our QC, containing most major cell types known to exist in the developing mouse kidney. The aggregated human organoid data contains of >7000 cells that passed our QC and contains populations representing endothelial cells, podocytes, stroma, nephron, and off-target populations with similarity to neurons.
Project description:DNA damage can promote altered RNA splicing and decreased gene expression (Gregersen and Svejstrup, 2018; Milek et al., 2017; Munoz et al., 2009; Shkreta and Chabot, 2015), and aberrant splicing is implicated in neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), Fragile X syndrome and spinal muscular atrophy (SMA) (Conlon et al., 2016; Jia et al., 2012; Loomis et al., 2014; Qiu et al., 2014; Scotti and Swanson, 2016). Therefore, we used RNA-seq data to assess RNA-splicing in double-mutant brain tissue using multivariate analysis of transcriptional splicing (rMATS) (Shen et al., 2014) and a splicing deficiency score algorithm (Bai et al., 2013) to assess intron retention.