Project description:This study investigates how DPM1 regulates the ER stress sensor IRE1 and how this impacts antitumor immunity in a colorectal cancer model. Single cell data were generated from tumor infiltrating T cells isolated from BALB/c mice bearing CT26 colorectal tumors. Wild-type and Dpm1 knockout tumors were profiled using 10x Genomics Chromium Single Cell 5' gene expression, feature barcode hashtags, and paired TCR VDJ libraries. Raw reads are available in SRA under BioProject PRJNA1435810.
Project description:Animal R.401 was infused with ex-vivo expanded T-regulatory cells. After adoptive transfer, PBMC were obtained and stained with surface antibodies. Single cell libraries from sorted populations were generated using a UMI-based droplet-partitioning platform (10X Genomics) and sequenced using a NextSeq 500 (Illumina). Resulting reads were processed using Cellranger software (10X Genomics) and downstream analysis was performed using Monocle6,7 using a negative binomial model of distribution with fixed variance.
Project description:Single-nucleus multiomic data was generated from human fetal cochleae across 11, 14, and 16 post-conceptual weeks (PCW) using the 10X Genomics Chromium Next GEM Single Cell Multiome ATAC+ Gene Expression platform. Snap-frozen tissues were minced and lysed in ice-cold Nuclei Lysis Buffer, followed by filtration through a 40 μm strainer and centrifugation. Nuclear integrity was confirmed via trypan blue staining prior to mild permeabilization using 0.1× Lysis Buffer. After quenching and washing, nuclei were resuspended in Diluted Nuclei Buffer and concentration was adjusted to 4,000–8,000 nuclei/μL. Libraries were prepared following the standard 10X Multiome protocol for simultaneous gene expression and chromatin accessibility profiling. Sequencing was performed on the Illumina platform, producing paired-end reads. Raw data were processed through the Cell Ranger ARC pipeline (v2.0.0) with alignment to the GRCh38 human genome. The final output comprises paired gene expression matrices and chromatin accessibility peaks, both linked to the same individual nuclei through shared barcodes.
Project description:Purpose: The 10x Genomics Visium platform allows us to define the spatial topography of gene expression and provides detailed molecular maps that overcome limitations associated with sn/scRNA-seq and microscopy-based spatial transcriptomics methods. The goals of this study are to compare and identify unique transcriptome profiling (RNA-seq) signature between unfavorable and favorable Wilms Tumors and against human fetal kidney. Methods: Human fetal kidney and Wilms tumor spatial topography of gene expression were generated using the 10X Visium platform Results: Using an optimized data analysis workflow, we mapped the reads to the hg38 genome build and grouped the spots into 9 clusters based on gene expression profiles. Conclusion: Our study represents the first implement of Visium technology in human fetal kidney and Wilms Tumor tissue, providing a number of important functional insights about the spatial and molecular definitions of cell populations across human fetal kidney and different subtypes of Wilms Tumor through analyzing gene expression within the intact spatial organization of the human samples.
Project description:Human synovial Single cell RNA-seq was performed on three tissue samples from healthy donors. This experiment was done to explore the heterogeneity of cells in healthy human synovial joint and enabled the comparison of cellular states and composition to those of publicly available single cell RNA-seq datasets from psoriatic arthritis and rheumatoid arthritis patients. Human synovial cells were loaded immediately after tissue dissociation with up to 25,000 cells in a single well of a Chromium chip G (10x Genomics). 3’ gene expression libraries were generated using Chromium Next GEM Single Cell 3' Kit 3.1 with 3' Feature Barcode Kit and dual indexing (10x Genomics protocol CG000316 Rev C). Libraries were sequenced as paired end (PE) 150 bp by Illumina sequencing to 65-80% saturation. Reads were mapped to the GRCh38 human genome (GENCODE) using the 10x Genomics Cell Ranger pipeline (7.2.0).
Project description:Targeted spatial transcriptomic profiling was performed on seven formalin-fixed paraffin-embedded pleural mesothelioma tumor samples from four cases using the 10x Genomics Xenium platform. The Xenium Human Immuno-Oncology panel supplemented with 100 additional custom genes selected from known pleural mesothelioma biomarkers and single-cell RNA-seq-derived marker genes was used. Raw and processed Xenium files are provided for each sample. To ensure data integrity with downloaded Xenium files, md5 checksums are provided in 'Xenium_GEO.md5'. This dataset is part of a multi-modality study including matched scRNA-seq, bulk RNA-seq, and Xenium spatial transcriptomics generated from overlapping pleural mesothelioma samples. Related controlled-access sequencing data are available in dbGaP under accession phs004285.
Project description:The goals of this study are to determine tissue composition of human lung organoids (hLOs) when maintained long-term (day 230). hLOs consist of alveolar epithelial cells, mesenchymal/endothelial cells, smooth muscle cells and immune cells. After dissociated hLOs, a target capture of 1x 104 cells was performed using the 10X Genomics Chromium Single Cell RNA sequencing. Briefly, single cell gel bead-in-emulsions(GEMs) are generated by passing cells with enzyme mix, partitioning oil, and barcoded gel beads by 10X Chromium chip. After GEM formation, the gel bead is dissolved and co-partitioned cell is lysed. Subsequently, reverse transcription (RT) occurs inside GEMs and barcoded full-length cDNA is generated. After RT, amplified cDNAs with barcode sequences (cell index and UMI) are pooled and single cell library is constructed using the Single Cell 3` Reagent Kit (v3 chemistry). The resulting library was sequenced on illumina HiseqX platform with 150bp paired end. Raw base calling files generated by illumine sequencing were demultiplexed based on the sample index read to generate FASTQ files using the 10X Genomics Cell Ranger (v3.0.2) pipeline. The raw reads were trimmed from the 3’ end to get the recommended number of cycle for read pairs (read1: 28bp; read2 : 91bp). The trimmed reads were mapped to the hg38 reference human genome with subsequent analysis, including filtering, barcode counting, and UMI counting. The resulting data were used to generate the multidimensional feature-barcode matrix using the CellRanger count with default parameters.