title: GSM9107751: replicate1, 3scRNAseq; Mus musculus; RNA-Seq
library_construction_protocol: C57BL/6J mice were purchased from Jiangsu JCYK Bioscience Co. Ltd (Jiangsu, China), housed and bred under SPF condition (Specific Pathogen Free) at the Laboratory Animal Center of West China Second University Hospital, and were allowed access to diet and water ad libitum. All animal experiments were carried out following the protocols approved by the Institutional Animal Care and Use Committee of West China Second University Hospital [(2018) Animal Ethics Approval No. 004]. The bone marrow cells were obtained from the femur and tibia of C57BL/6 mice aged about 8 weeks and filtered via a 70-μm cell strainer (BD Biosciences). After centrifuging (300 g, 5 min, 4℃), the cells were resuspended in 200 mL EasySep Buffer and CD117 MicroBeads (20 μL/one mouse). The whole solution was transferred to a 1.5 mL centrifuge tube and incubated on ice for 20~30 min. A 1 mL sample was added to the MS separation column. The MS separation column was cleared with EasySep Buffer 3 times on the Magnetic Separation Rack, and then the MS separation column was eluted with 5 mL of EasySep Buffer off the Magnetic Separation Rack to obtain Lin- cells. 20 μL cells were taken and counted, and the remaining samples were centrifuged (300 g, 5 min, 4℃). SCM (+) medium was used to resuspend (4 mL/one mouse) and then placed in an incubator (37℃, 5% CO₂) at constant temperature for 12~24 hr. RNA purity was checked using the NanoPhotometer® spectrophotometer (IMPLEN, CA, USA) and the concentration was measured using Qubit® 2.0 Fluorometer (Life Technologies, CA, USA). The integrity of RNA was assessed using the Qubit® 1.0 Fluorometer. Single cells were prepared in the Chromium Single Cell Gene Expression Solution using the Chromium Single Cell 5′ Gel Bead, Chip and Library Kits v2 (10x Genomics) as per the manufacturer's protocol. Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) is a single-cell multi-omics technology that measures RNA and protein expression simultaneously in single cells. We generated a 5' CITE-seq dataset of mouse bone marrow lineage negative (LIN−) cells, which consists of 388 cells and 8 proteins. The cells were then partitioned into Gel Beads in Emulsion in the Chromium instrument, where cell lysis and barcoded reverse transcription of RNA occurred, followed by amplification, which was under the action of poly(dT) and enzyme. In GEMs, each pair-end contains read 1 (R1) and read 2 (R2), the former consists of (i) a 16nt 10x Barcode, (ii) a 10nt unique molecular identifier (UMI), and (iii) a 13nt TSO. Libraries were sequenced on the Illumina NovaSeq 6000 platform at Novogene, Beijing, China [CITE-seq].  The collected cells were resuspended in PBS containing 1% BSA at the concentration at 1 × 106 cells/mL and prepared for single cell library preparation. Single cells were prepared in the Chromium Single Cell Gene Expression Solution using the Chromium Single Cell 3 Gel Bead, Chip and Library Kits v2 (10× Genomics) as per the manufacturer's protocol. The cells were then partitioned into Gel Beads in Emulsion in the Chromium instrument, where cell lysis and barcoded reverse transcription of RNA occurred, followed by amplification, shearing 5 adaptor, and sample index attachment. Libraries were sequenced on the Illumina NovaSeq 6000 platform at Novogene, Beijing, China [3' scRNA-seq].  The Pychopper (v2.5.0) software was used to identify, orient and trim long-read sequencing reads with default parameters. The number of reads, read length and quality were analyzed using NanoComp software (v1.33.1) with the parameter of “–raw–store–tsv_stats” and visualized using R package ggplot2 (v3.5.1). Pychopper processed reads were aligned to the reference genome GRCm38 with annotation from ENSEMBL release 101 for mouse and the reference genome GRCh38 using minimap2 (v2.17) with the following parameters: minimap2 -ax splice -uf --secondary=no -C5 --MD. Then, mismatches, insertions, deletions, and non-canonical splice sites in alinged reads were corrected using TranscriptClean (v2.0.3) software. Finally, TranscriptClean-corrected reads were aligned again to the reference mentioned before. Finally, reads were assigned to known genes to generate comprehensive count matrices, enabling the quantification of expression at both the gene and isoform levels for each individual cell [scONT].