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Sample GSM6211330

Query DataSets for GSM6211330

Status

Public on Aug 05, 2023

Title

SMM36142 [T lymphocytes]

Sample type

SRA

Source name

bone marrow

Organism

Homo sapiens

Characteristics

tissue: bone marrow
cell line: T lymphocytes
cell type: T cells

Extracted molecule

total RNA

Extraction protocol

scRNA-seq + scTCR-seq were performed in 17 bone marrow aspirates from 3 healthy adults, 3 MGUS, 2 SMM, 9 MM patients and 8 bone marrow aspirates from 2 healthy (Ycɣ1), 3 MGUS (BIcɣ1) and 3 MM (BIcɣ1) bearing mice. Cells were FACS sorted (a mix of 0.8x105 T cells + 0.8x105 NK cells + 0.25x105 monocytes + 0.15x105 B cells) in 100 µL of PBS+0.05% BSA. Samples with at least 90% viability were processed using the 10X Genomics (CA, USA) scRNA/TCRseq kit, following the manufacturer’s instructions (Chromium Next GEM Single Cell V(D)J v1.1 protocol rev F for human samples and Chromium Next GEM Single Cell 5’ v2 Dual Index protocol rev B for mice samples). Quality control was performed with Qubit Fluorometric Quantification (ThermoFisher Scientific, MA, USA) using the double-stranded DNA high-sensitivity assay kit, and with TapeStation (Agilent, Santa Clara, CA) using high-sensitivity screentapes. Libraries were sequenced on a NextSeq 550 (Illumina, San Diego, CA).
Library was performed according to the manufacter’s instructions (Chromium Next GEM Single Cell V(D)J v1.1 protocol rev F for human samples and Chromium Next GEM Single Cell 5’ v2 Dual Index protocol rev B for mice samplesl, 10x Genomics). Briefly, GCs were resuspended in the master mix and loaded together with partitioning oil and gel beads into the chip to generate the gel bead-in-emulsion (GEM). The poly-A RNA from the cell lysate contained in every single GEM was retrotranscripted to cDNA, which contains an Ilumina R1 primer sequence, Unique Molecular Identifier (UMI) and the 10x Barcode. The pooled barcoded cDNA was then cleaned up with Silane DynaBeads, amplified by PCR and the apropiated sized fragments were selected with SPRIselect reagent for subsequent library construction. During the library construction Ilumina R2 primer sequence, paired-end constructs with P5 and P7 sequences and a sample index were added. Of note, according to TCR-seq protocol from manufacturer, we further sequenced (after specific amplification) CDR3 sequences from each CD3+ T cells.

Library strategy

RNA-Seq

Library source

transcriptomic single cell

Library selection

cDNA

Instrument model

Illumina NextSeq 500

Description

10x Genomics
sc_BM_T_humans.RDS

Data processing

scRNA-seq and scTCR-seq data from humans and mice were analyzed separately. Sample demultiplexing, alignment to the hg38 human reference genome (or the respective mice genome) and single-cell gene count was performed using the Cell Ranger Single-Cell Software Suite v.2.0.1 (https://www.10xgenomics.com/). Expression matrixes were analyzed with the R package seurat 4.0 (https://satijalab.org/seurat/) and cells were filtered according to < 10% mitochondrial expression and at least 200 (but less than 2500) mRNA counts per cell. Once scaled and normalized, a genelist including the most variable genes was obtained by the FindVariableFeatures function. After removing genes belonging to the immunoglobulin families (which could work as a confounding factor during clustering), the genelist was used to derive the principal component analysis (PCA) vectors for each sample. The first 100 PCA were used to align samples (batch removal) using the R package harmony. The new harmonized coordinates were used to develop UMAPs (dimensionality reduction). The shared nearest neighbor (SNN) algorithm based on 50 batch-corrected dimensions was used for clustering the cells into homogeneous groups that were manually identified according to the expression of canonical genes (see Supplemental Information) obtained from curated gene-sets. A sequential subclustering strategy (which consists basically in repeating the same steps as before on a specific subpopulation) to focus on clonotypic T cells was performed. Reconstruction of T cell trajectories was performed by ordering single cells in “pseudotime” according to their RNA expression through Monocle 2 R package. This package accurately resolves biological processes (ordering cells) by learning an explicit principal graph from the single cell genomics data through Reverse Graph Embedding algorithm.
TCR sequences defined by their CDR3 were obtained from Cell Ranger. T cells were considered as clonotypic if their frequency was >2/1000 cells and present in at least 3 cells, and this information was added to the Seurat object to analyze the transcriptome of these cells. scRepertoire R package was used to assess clonotype distribution as well as to investigate clonal “diversity”, characterized by clones frequency, repertoire richness and convergence (Borcherding, Bormann and Kraus, 2020; Chiffelle et al., 2020). To estimate clonal diversity and richness we used Chao and ACE indices which have been developed to deal with under sampling (i.e. ‘unseen species’), and could therefore mitigate the fact that for technical reasons, only a fraction of repertoires is sequenced and analyzed (Chiffelle et al., 2020).
Assembly: GRCh38 and mm10BM_T_humans.RDS
Supplementary files format and content: We allegated 2 different RDS files: which ventually include oll the parients
Supplementary files format and content: sc_BM_T_humans.RDS
Supplementary files format and content: sc_BM_T_mice.RDS

Submission date

Jun 02, 2022

Last update date

Aug 05, 2023

Contact name

Cirino Botta

E-mail(s)

cirino.botta@gmail.com

Organization name

"Annunziata" Hospital of Cosenza

Department

Hematology Unit