GSM8510304: T1_10770_S32; Gallus gallus; RNA-Seq
After euthanizing the birds, thymus were aseptically removed, and flash frozen in liquid nitrogen then stored at -80. The nuclei isolation methods performed were done via the Singulator2 instrument per manufacturer's protocols (S2 Genomics; Livermore, CA) with storage buffers containing 0.4U/ul RNase inhibitor (source), prior to microfluidic encapsulation on the 10X Chromium instrument (10x Genomics®, Pleasanton, CA) to nanoliter-scale Gel bead-in-EMulsions (GEMs). Single-nuclei libraries were generated using the GemCode Single-Cell Instrument and Single Cell 3′ Library and Gel Bead Kit v3 and Chip Kit (10x Genomics®, Pleasanton, CA) according to the manufacturer's protocol. Before sequencing, every library was analyzed on a Bioanalyzer high sensitivity chip to ensure the expected cDNA fragment size distribution was achieved. The appropriate number of individually barcoded GEM libraries were pooled and sequenced on a NovaSeq 6000 instrument (Illumina) with 2×150bp length using these sequencing parameters: 26 bp read 1 – 8 bp index 1 (i7) – 98 bp read 2 with 200 cycles.Single nuclei capture and cDNA preparation were performed with the 10X Genomics Chromium Single Cell 3' kit, version 2, and lipid encapsulation instrument (10X Genomics, Pleasanton, CA) according to the manufacturer's recommendations. Pooled libraries were barcoded by sample and sequenced (2x 150 bp length) on an Illumina HiSeq 6000 instrument (Illumina, Inc., San Diego, CA) to achieve 50,000 reads per nuclei. The individual tissue-specific sequenced Gel Bead-In Emulsion (GEM) libraries were each processed with the CellRanger v7.0.1 pipeline (10X Genomics), which performs demultiplexing, alignment, barcode processing, and sample aggregation to create a cellular barcode by genomic feature matrix. The chicken reference used for all single-nuclei read alignments was bGalGal1b or GRCg7b. First, we used the “cellranger mkgtf” command to filter out everything except protein-coding genes and long non-coding RNAs from the annotation, and then use the “cell ranger mkref” command to create the necessary indices. We aligned reads to this modified GRCg7b reference and generated count matrices for each sample individually using the command “cellranger count” with default options. Molecular barcodes that were most likely to be ambient signals and doublets were eliminated using the default settings of cellranger's “remove-background” v.0.2.0 function, and cell counts were calculated using cellranger default parameters