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Sample GSM5777133

Query DataSets for GSM5777133

Status

Public on Jan 28, 2022

Title

EAE_Peak_RNA

Sample type

SRA

Source name

Sox10GFP+/DAPI-

Organism

Mus musculus

Characteristics

condition: EAE_disease_Peak
multiome_modality: Expression

Treatment protocol

For the induction of EAE, the mouse model of MS, animals were injected subcutaneously with an emulsion of MOG35-55 peptide in complete Freud’s adjuvant (CFA; EK-2110 kit from Hooke Laboratories) followed by intraperitoneal injection with pertussis toxin in PBS (200 ng per animal) on the day of immunization and with 24 hours delay (according to manufacturer’s instructions). Control animals underwent the same treatment, but CFA without MOG35-55 peptide (CK-2110 kit from Hooke Laboratories) was used instead. Spinal cord and brains were collected at the peak of the disease when clinical score 3 has been reached, which corresponds to limp tail and complete paralysis of hind legs. Animals that did not reach this clinical score were not analyzed in this study.

Extracted molecule

total RNA

Extraction protocol

Mice were sacrificed with a ketaminol/xylazine intraperitoneal injection followed by intracardiac perfusion with PBS where after spinal cords were collected and dissociated using the adult brain dissociation kit (130-107-677, Miltenyi) following manufacturer’s instructions. Instead of myelin debris removal (Miltenyi), Percoll (Cytiva 17-0891-01) mixed with HBSS was used to generate a percoll gradient of 38% to remove myelin debris.
Immediately after dissociation, cells were stained with DAPI and sorted on a FACS Aria III cell sorter (BD Biosciences). Sox10GFP+/DAPI- cells were collected in PBS + 0.5% BSA. The pool of cells was then lysed and washed according to the Demonstrated Protocol: Nuclei Isolation for Single cell ATAC Sequencing (10x Genomics) with modifications from the Demonstrated Protocol: Nuclei Isolation for Single Cell Multiome ATAC + Gene Expression Sequencing (10x Genomics) as follows: the cells were centrifuged for 10 minutes at 300xg and 4°C, resuspended in ATAC lysis buffer (containing 0.01% IGEPAL (CA-630), 0.01% Tween-20, 0.001% Digitonin, 1% BSA, 1 mM DTT, 1 U/ul RNase inhibitor, 10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2) and incubated on ice for 3 minutes. After the incubation, wash buffer (containing 0.1% Tween-20, 1% BSA, 1 mM DTT, 1 U/ul RNase inhibitor, 10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2) was added on top without mixing and the nuclei were centrifuged for 5 min at 500xg and 4°C. Nuclei were washed once in Diluted Nuclei buffer (10x Genomics) containing 1% BSA, 1 mM DTT and 1 U/ul RNase inhibitor, and incubated for 60 minutes at 37°C in tagmentation mix (10x Genomics). The Chromium Next GEM Single Cell Multiome ATAC + Gene Expression v1 Chemistry was used to create single nuclei ATAC and RNA libraries from the same cell. Two EAE and two CFA-Ctr animals were used for independent replicates. Libraries were sequenced on an Illumina Novaseq 6000 with a 50-8-24-49 read set-up for ATAC (minimum 25 000 read pairs per cell) and a 28-10-10-90 read set-up for RNA (minimum 20 000 read pairs per cell).
Chromium Next GEM Single Cell Multiome ATAC + Gene Expression

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina NovaSeq 6000

Data processing

Samples for RNA modality were sequenced on NovaSeq6000 (NovaSeq Control Software 1.7.5/RTA v3.4.4) with a 28nt(Read1)-10nt(Index1)-10nt(Index2)-90nt(Read2) setup using 'NovaSeqStandard' workflow in 'SP' mode flowcell. The Bcl to FastQ conversion was performed using bcl2fastq_v2.20.0.422 from the CASAVA software suite. The quality scale used is Sanger / phred33 / Illumina 1.8+.
Samples for ATAC modalidity were sequenced on NovaSeq6000 (NovaSeq Control Software 1.7.5/RTA v3.4.4) with a 50nt(Read1)-8nt(Index1)-24nt(Index2)-49nt(Read2) setup using 'NovaSeqStandard' workflow in 'SP' mode flowcell. The Bcl to FastQ conversion was performed using bcl2fastq_v2.20.0.422 from the CASAVA software suite. The quality scale used is Sanger / phred33 / Illumina 1.8+.
Single cell multiome mouse (10X Genomics) data was processed with default parameters with cellranger-arc (v2.0.0) count function. Reads were aligned to mm10 (ata-cellranger-arc-mm10-2020-A-2.0.0‎) reference genome. Normalized single feature-barcode matrix combining all the samples from both modalities was calculated with the parameter cellranger-arc aggr with default parameters, samples were normalized to depth for both ATAC and gene expression modalities. which resulted in a median fragments per cell of 12928, median UMI counts per cell of 4240, median genes per cell of 1849 and 5769 cells.
We used Cellranger-arc called peaks for preQC measurements. After QC we run macs2 whithin Seurat/Signac to call the peaks, to recover consistent peak set within the whole dataset. For downstrean analyses we combined Signac v1.4.0 and Seurat v4.0.0 joint RNA and ATAC analysis. We used as QC metrics nCount_ATAC < 100000 & nCount_RNA < 25000 & nCount_ATAC > 500 & nCount_RNA > 500 & nucleosome_signal < 2 & TSS.enrichment > 1, which resulted in 5264 cells.
Gene activity was calculated over the 500bp promoter regions of annotated protein_coding genes from mm10 EnsEmbl79. Pooled replicates cells were identified based on CHRX and CHRY module score calculated from BiomaRt. Data processing was performed in RNA and ATAC modalities separately with Seurat/Signac. RNA modality was integrated with Harmony based on sample variable, normalized and dimension reduction PCA, dims=1:50. For the ATAC modality we performed latent semantic indexing (LSI) on the Harmony integrated space for dims=2:50. Using the weighted nearest neighbor (WNN) from Seurat v4 we computed the joint neighbor graph of RNA and ATAC modalities. We run FindClusters in the ATAC graph, RNA graph and joint WNN graph. Cells were annotated using transfer_anchors on the RNA modality to Falcao et al. 2019 scRNA-seq data and manually curated based on known gene markers, which allowed us to identify Astrocyte cells. By annotating the data to the Falcao et al. 2019 reference we can compare the cell clusters indentified in the scATAC-seq data to the single cell multiome cells clusters. We then called again the peaks using MACS2 on the identified cell clusters.
Peak to gene interaction were predicted based on co-accessibility and expression from identified celltypes using R package ArchR.
Genome_build: mm10
Supplementary_files_format_and_content: Output files from cellranger-arc (v2.0.0), as aligned RNA-seq and ATAC-seq modality bam files, filtered feature matrix h5 file, filtered expression matrix h5 file, called ATAC fragments for Ctrl sample (P21208_1004) and EAE_Peak samle (P21208_1005). Wig signal files for each identified celltype in Ctrl and EAE_Peak samples. Due to different number of cells in each celltype cluster, the wig files were built with a maximun of randomly selected 100 cells from each type. Predicted peak to gene interactions for each celltype, based on co-accessibility and expression as bedpe format. Bed file of identified celltype peaks. Processed data R object (.rds R.4.1.0) Signac 1.4.0/Seurat 4.0.5 used in the study.
Supplementary_files_format_and_content: Aggregated output matrix and ATAC fragments from both Ctrl and EAE_Peak sample, atac_fragments.tsv.gz and filtered_feature_bc_matrix.h5.

Submission date

Jan 07, 2022

Last update date

Jan 28, 2022

Contact name

Eneritz Agirre

Organization name

Karolinska Institutet

Department

MBB

Lab

Castelo-Branco, Molecular Neurobiology