DOI: 10.5061/dryad.hhmgqnksj
title: scRNA-seq of splenic CD45+ Cells from Aire-knockout rats

description: This dataset examines the impact of anti-IFNα autoantibodies on immune
 cell populations and gene expression in peripheral immune tissues of
 Aire-knockout rats. Single-cell RNA sequencing (scRNA-seq) was performed
 on CD45+ splenic cells from 7-month-old Aire-knockout rats (n=4) with high
 levels of anti-IFNα autoantibodies and age-matched Aire-heterozygous
 controls (n=4). Splenic cells were isolated through mechanical
 homogenization, followed by erythrocyte lysis and CD45+ cell sorting using
 a MA900 cell sorter. Single cells were captured with the 10x Chromium
 microfluidics system, and barcoded cDNA libraries were prepared using the
 single-cell 3’ mRNA kit (10x Genomics). Sequencing was conducted on the
 Illumina MiSeq platform, and the data were mapped to the Rattus norvegicus
 reference genome (Rnor_6.0) and quantified using the Cell Ranger software
 suite. The dataset includes count matrices generated by Cell Ranger.
description: CD45+ splenic cells were isolated from 7-month-old Aire-knockout
 rats (n=4) with high levels of anti-IFNα autoantibodies and age-matched
 Aire-heterozygous controls (n=4). Spleens were homogenized mechanically,
 and erythrocytes were removed using an ACK lysis solution. The CD45+ cell
 population was sorted using a MA900 cell sorter (Sony Biotechnology).
 Single-cell RNA sequencing (scRNA-seq) was performed with the 10x Chromium
 microfluidics system, and barcoded cDNA libraries were constructed using
 the single-cell 3’ mRNA kit (10x Genomics). Sequencing was conducted on
 the Illumina MiSeq platform. The data were processed using the Cell Ranger
 software suite (Version 6.0.1, 10x Genomics Inc.) and aligned to the
 Rattus norvegicus reference genome (Rnor_6.0).
description: # README for scRNA-seq Dataset of Splenocytes from Aire-Deficient Rats ##
 Related Datasets This dataset is part of a coordinated set of
 transcriptomic and single-cell transcriptomic profiles generated from
 **Aire-knockout rats** for the associated research article. Additional
 related datasets can be accessed via Dryad at the following DOIs: *
 [10.5061/dryad.mpg4f4r9z](https://doi.org/10.5061/dryad.mpg4f4r9z):
 *Transcriptome Profiling of CD4+ T cell subpopulations* *
 [10.5061/dryad.p8cz8wb1s](https://doi.org/10.5061/dryad.p8cz8wb1s):
 *Transcriptome Profiling of Medullary Thymic Epithelial Cells* *
 [10.5061/dryad.8kprr4xz1](https://doi.org/10.5061/dryad.8kprr4xz1):
 *scRNA-seq of Thymic Epithelial Cells* *
 [10.5061/dryad.hhmgqnksj](https://doi.org/10.5061/dryad.hhmgqnksj):
 *scRNA-seq of Splenic CD45+ Cells* *
 [10.5061/dryad.5qfttdzhj](https://doi.org/10.5061/dryad.5qfttdzhj):
 *scRNA-seq of CD45+ Cells from Salivary Gland* ## Overview This dataset
 contains scRNA-seq data from Aire-deficient (KO) and Aire-sufficient (HE)
 animals, organized into separate folders for each sample. The data were
 collected to investigate immune cell populations and gene expression
 patterns in Aire-deficient and Aire-sufficient animals. Each folder
 corresponds to a specific sample, with naming conventions that indicate
 whether the sample was collected from an Aire-deficient (KO) or sufficient
 (HE) animal. ## Folder Structure The dataset archive contains 8 folders,
 each named using the following format: * `HE_`: Sample collected
 from an Aire-sufficient (HE) animal * `KO_`: Sample collected
 from an Aire-deficient (KO) animal The `` number after the
 underscore uniquely identifies each sample. ### Contents of Each Folder
 Each folder contains the following files related to the single-cell RNA
 sequencing data: * `barcodes.tsv.gz`: Barcode information for each cell in
 the sample. * `features.tsv.gz`: Information about the features (genes)
 detected in the sample. * `matrix.mtx.gz`: The matrix file containing the
 gene expression counts for each cell. ## Data Format * The files are
 compressed (`.gz`) and need to be extracted before use.