title: GSM4504590: Batf3 wt cDCs; Mus musculus; RNA-Seq
library_construction_protocol: Spleens were collected from mice and digested enzymatically and mechanically. Single cell suspensions underwent red blood cell lysis using ammonium chloride potassium (ACK) buffer and T and B cell depletion using EasySep Mouse Streptavidin RapidSpheres (StemCell Technologies). After that, live MHCII+CD11c+ cells were sorted from single cell suspensions via flow cytometric activated cell sorting. Sorted cells were stained with TotalSeq-A antibodies (Biolegend) and then counted for viability and numbers prior to loading into droplets. Cells were loaded onto the chip for Chromium Single Cell Gel Bead and Library Kit v3 (10x Genomics). The 10x Genomic User Guide was followed for GEM generation and barcoding, cDNA amplification and library construction. Eleven cDNA amplification cycles were performed, and one quarter of the cDNA was used as input for library construction. Library construction for CITE-seq was conducted in accordance to Totalseq-A antibody manufacturer protocol (Biolegend, v.3). Final indexing PCR was performed in a C1000 Touch thermal cycler with a Deep Well Reaction Module (Bio-Rad). For gene expression and CITE-seq libraries 11 and 10 SI-PCR cycles were used, respectively. Using the High Sensitivity DNA kit on Agilent BioAnalyser 2100 the libraries were quantified (Agilent, 5067-4626). Equimolar ratios were used to pool gene expression libraries, and of the total sequencing pool concentration 10% were spiked in cell hashing libraries. Quantification of the final pool was conducted by qPCR using KAPA Library Quantification Kit in combination with the Life Technologies Viia 7 real time PCR instrument (KAPA Biosystems, KK4824). Illumina NextSeq-500 was used for sequencing the denatured libraries using a 150 cycle High-Output Kit. This included Read 1 (28 bp) supplying the cell's barcode (16nt) and UMI (12nt), i7 (8bp) for sample index and Read 2 (111 bp) to capture the 3' sequence of the transcripts. In total, two sequencing runs were performed to obtain an average read depth of ~30,000 reads per cell.
attributes.tag: GEO Accession
attributes.value: GSM4504590