title: GSM9207343: Bone-EAMG; Rattus norvegicus; RNA-Seq
library_construction_protocol: Lennon score in the EAMG group were assessed, and 3 rats with a clinical score ≥ 2, along with corresponding control rats in 28 days after second immunization, were selected for the experiment. The rats were anesthetized and placed in a biosafety cabinet, where blood was collected from the eyeball into EDTA-anticoagulated tubes. The spleen, thymus, lymph nodes, and tibias were dissected out and immediately placed in 5 mL of RPMI 1640 medium. The spleen, thymus, and lymph node tissues were thoroughly homogenized, then centrifuged at 300g for 5 minutes at room temperature. The supernatant was discarded, and after washing, the cell pellet was resuspended in PBS (HyClone, Marlborough, MA, USA) to form a single-cell suspension. GEXSCOPE red blood cell lysis buffer (Singleron Biotechnologies, Nanjing, China) was added to the cell suspension to remove red blood cells. The mixture was then centrifuged and resuspended in PBS. Trypan blue exclusion test was used to assess cell viability. We counted the cells using a TC20 automated cell counter (Bio-Rad, Hercules, CA, USA) and prepared a cell suspension with a final concentration of 1 × 10^5 cells/mL. The single-cell suspension was loaded onto microwell chip using the Singleron Matrix® Single Cell Processing System. The scRNA-seq library was constructed using the GEXSCOPE® Single Cell RNA Library Kit (Singleron Biotechnologies, Nanjing, China) and the Singleron Matrix® Automated Single Cell Processing System (Singleron Biotechnologies, Köln, Germany) based on the Singleron GEXSCOPE® protocol. After dilution to 4 nM, individual libraries were pooled for sequencing. The libraries were then sequenced on an Illumina HiSeq X with 150 bp paired-end reads (Illumina, San Diego, CA, USA). Raw reads from scRNA-seq were processed to generate gene expression matrixes using CeleScope (https://github.com/singleron-RD/CeleScope) v1.9.0 pipeline. Briefly, raw reads were first processed with CeleScope to remove low quality reads with Cutadapt v1.17 (Martin,M. (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J., 17, 10–12.) to trim poly-A tail and adapter sequences. Cell barcode and UMI were extracted. After that, we used STAR v2.6.1a (Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA-seq aligner[J]. Bioinformatics, Volume 29, Issue 1, 1 January 2013, Pages 15–21.) to map reads to the reference genome GRCr8. UMI counts and gene counts of each cell were acquired with featureCounts v2.0.1 (Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).) software, and used to generate expression matrix files for subsequent analysis.