{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":["Yorick van de Grift"],"organism":["Mus musculus"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-16966"],"description":["Bcl9/9l fl/fl;Rosa26-CreERT2 small intestinal organoids were exposed to 1uM 4-OHT (or EtOH as a control) for 24 hours to induce recombination and induce a conditional Bcl9 and Bcl9l knockout. Intestinal epithelial cells were isolated 72 hours later for single cell RNA sequencing. BCL9 is a beta-catenin transcriptional cofactor involved in the transcriptional machinery of Wnt target genes. We found that BCL9/9L is a key player in coordinating the balance between Wnt mediated proliferation and differentiation in the intestinal epithelium by engaging with GATA transcription factors. In line with this observation, we observed an increase in secretory lineage cells upon loss of Bcl9/9l in intestinal organoids."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Growth Protocol - Organoids were culture in 15ul BME (3434-005-02, Trevigen) droplets in culture medium containing advanced DMEM/F12 (12634010, ThermoFisher Scientific) supplemented with 100U/ml Penicillin/Streptomycin (15276355, ThermoFisher Scientific), 2mM Glutamax (11574466, ThermoFisher Scientific), 10mM HEPES (15630-056, ThermoFisher Scientific), and 1.25mM N-acetylCysteine (A9165-5G, Sigma Aldrich), freshly added mEGF (50ng/ml, 315-09, PeproTech), 2% Noggin-Fc conditioned media (N002-100ml, AVSbio), 2% Rspo3-Fc conditioned media (R001 – 100ml, AVSbio) at 37°C and 5% CO2. For passaging, cell culture medium was removed and BME was broken into small pieces by scraping, followed by vigorous pipetting with ice-cold advanced DMEM/F12. Crypts were centrifuged at 400g for 5 min at 4°C. The supernatant was carefully removed, the pellet was resuspended in 50:50 advanced DMEM/F12:BME and plated on pre-warmed culture plates. Medium was refreshed every other day, and organoids were split once a week in a 1:3 ratio.","Sample Collection - Small intestinal organoids were harvested with ice-cold medium and transferred to a 15ml tube. Ice cold Advanced DMEM/F12 was added till 10ml, and the organoids were pelleted at 4°C for 5min at 400g. ‘Matrigel cloud’ was carefully removed and organoids were pelleted again in 10ml ice cold advanced DMEM/F12. Organoids were resuspended in 1ml TrypLE express enzyme, Phenol Red (12605010, Thermo Scientific) and incubated in a 37°C waterbath till the organoids were fully dissociated to single cells while gently shaking and occasional pipetting with a p1000 to prevent clumping. Cells were checked under a brighfield microscope every 5 min to assess dissociation. Once the organoids were fully dissociated to single cells the digestion was stopped with 500ul BCS, immediately topped till 10ml with ice cold Advanced DMEM/F12 and spin at 4°C for 5 min at 500g. The cells recovered from each condition were counted (range 100-200k) and scored for successful dissociation to single cells.","Sequencing - The final sub-libraries were evaluated on a TapeStation (Agilant) for size distribution and quantitative real time PCR (qPCR). 1 sublibrary was sequenced at a depth of 20.000 reads / cell on an Illumina NovaSeq 6000 S4 flow-cell with PE150 according to the results from library quality control and expected data volume by Novogene.If applicable output fastq files were concatenated to a single file for each read end. Fastq.gz files per sublibrary were demultiplexed and aligned to hg38 us-ing the Trailmaker pipeline by Parse Biosciences. Trailmaker was used to demultiplex the library. The unfiltered count matrix was used for further processing in the Trailmaker pipeline. The data was filtered based on cell size distribution, mitochondrial content, number of genes versus transcripts per cell, and filtered for doublets using automatic filter settings of the Trailmaker pipeline. Withing the Trailmaker pipeline, log-normalization, scaling and batch correction was per-formed with Seurat v4 and variance stabilizing transformation was performed with SCTransform v1 without removing covariates like mitochondrial, ribosomal or cell cycle genes. The top 2000 highly variable genes were used for integration with 30 principal components using the CCA method. The processed data was exported as a Seurat file and cell cluster identities were assigned in Seurat according to the markers derived from PangloaDB.","Library Construction - The recovered cells were fixed according to the manufacturer’s protocol (ECW02050, Parse BioSciences) including 0.5% BSA in the fixation solution (15260037, Fisher Scientific) and stored at -80°C. Before barcoding, cells suspensions were thawed and recounted and loaded on the first barcoding plate ac-cording to the manufacturer’s WT mega v2 sample loading table aiming at ~10k cells per condition. Further barcoding and sequencing library generation was performed according to the manufacturer’s protocol, generating 6 sub-libraries, with a target of 20000 cells each (note that more experiments were mixed in the sequencing library, amounting to ~1500 cells / condition / library).","Nucleic Acid Extraction - Nucleic acids were extracted from fixed nuclei according to the manufacturer's protocol (EXW02050, Parse Biosciences).","Sample Treatment - . Organoids were grown untill day 5 and treated with 1μM 4-OHT (H7904-5MG, Sigma-Aldrich) for 24 hours to delete Bcl9/9l. Organoids were harvest at day 8 for qPCR or scRNA-seq."],"figure_sub":["Organization","MINSEQE Score","Assays and Data","Processed Data","MAGE-TAB Files"],"data_protocol":["Data Transformation - If applicable output fastq files were concatenated to a single file for each read end. Fastq.gz files per sublibrary were demultiplexed and aligned to mm10 using the Trailmaker pipeline by Parse Biosciences. Trailmaker was used to demultiplex the library. The unfiltered count matrix was used for further processing in the Trailmaker pipeline. The data was filtered based on cell size distribution, mitochondrial content, number of genes versus transcripts per cell, and filtered for doublets using automatic filter settings of the Trailmaker pipeline. Withing the Trailmaker pipeline, log-normalization, scaling and batch correction was performed with Seurat v4 and variance stabilizing transformation was performed with SCTransform v1 without removing covariates like mitochondrial, riboso-mal or cell cycle genes. The top 2000 highly variable genes were used for integration with 30 principal components using the CCA method. The processed data was exported as a Seurat file and cell cluster identities were assigned in Seurat according to the markers in supplementary figure 1C (derived from PangloaDB)."],"omics_type":["Metabolomics","Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["Illumina NovaSeq X"],"study_type":["RNA-seq of coding RNA from single cells"],"species":["Mus musculus"],"pubmed_authors":["Claudio Cantù","Yorick van de Grift"],"additional_accession":[]},"is_claimable":false,"name":"scRNA-seq of Bcl9/9l fl/fl;Rosa26-CreERT2 small intestinal organoids","description":"Bcl9/9l fl/fl;Rosa26-CreERT2 small intestinal organoids were exposed to 1uM 4-OHT (or EtOH as a control) for 24 hours to induce recombination and induce a conditional Bcl9 and Bcl9l knockout. Intestinal epithelial cells were isolated 72 hours later for single cell RNA sequencing. BCL9 is a beta-catenin transcriptional cofactor involved in the transcriptional machinery of Wnt target genes. We found that BCL9/9L is a key player in coordinating the balance between Wnt mediated proliferation and differentiation in the intestinal epithelium by engaging with GATA transcription factors. In line with this observation, we observed an increase in secretory lineage cells upon loss of Bcl9/9l in intestinal organoids.","dates":{"release":"2026-07-07T00:00:00Z","modification":"2026-07-07T01:00:43.131Z","creation":"2026-04-28T14:33:26.949Z"},"accession":"E-MTAB-16966","cross_references":{"ENA":["ERP192733"],"EFO":["EFO_0002944","EFO_0004170","EFO_0003789","EFO_0005684","EFO_0005518","EFO_0003816","EFO_0004184","EFO_0003969"]}}