Journal: Frontiers in Immunology

Article Title: Prediction of HLA genotypes from single-cell transcriptome data

doi: 10.3389/fimmu.2023.1146826

Figure Lengend Snippet: Sequencing coverage of HLA allelic diversity (A) Rolling (100bp) mean Shannon entropy for published allele sequences of indicated HLA loci. (B) HLA coverage of reads mapped from bulk RNA-seq, 3’ (3p-based) scRNA-seq, and 5’ (5p)-based scRNA-seq. Grey lines represent individual samples, blue lines represent loess regression. (C) HLA-mapped reads per million total reads from bulk RNA-seq, 3’ (3p)-based scRNA-seq, and 5’ (5p)-based scRNA-seq.

Article Snippet: This data can be found here: (5 prime scRNA sequencing) https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-9357 , (3 prime scRNA sequencing) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120221 , (Bulk RNA sequencing) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120446 .

Techniques: Sequencing, RNA Sequencing

Journal: Cell Reports Medicine

Article Title: High NEK2 expression in myeloid progenitors suppresses T cell immunity in multiple myeloma

doi: 10.1016/j.xcrm.2023.101214

Figure Lengend Snippet: Loss of NEK2 reduces tumor-associated macrophages (TAMs) and Tregs (A) Experimental layout. (B) Serum IgG2b levels. n = 6–8 mice/group from two independent experiments with three technical replicates. Boxplot shows mean ± SD and the p value for the two-way ANOVA followed by Sidak multiple comparison test. ∗∗∗p < 0.001. (C) Survival analysis. n = 10 mice/group. ∗∗p < 0.01 (D) Stacked bar charts representing of BM cell populations following 10X Genomics scRNA-seq workflow (n = 6,379 cells for Nek2 +/+ , 5,746 cells for Nek2 −/− , 8,483 cells for 5TGM1/ Nek2 +/+ , and 9,676 cells for 5TGM1/ Nek2 −/− group). (E) Violin plot representing NEK2 expression in immune cell populations identified in (D). (F) Volcano plot showing differential gene expression in the macrophages of 5TGM1/ Nek2 −/− vs. 5TGM1/ Nek2 +/+ group with a |log 2 FC| > 1 and p < 0.05. (G) KEGG analysis of downregulated genes in macrophages of 5TGM1/ Nek2 −/− vs. 5TGM1/ Nek2 +/+ group. (H) Representative reconstructed μCT images of tibia sagittal sections showing bone lytic lesions and trabecular architecture. n = 5–10 mice/group from two independent experiments. (I) Quantitative histomorphometric analyses of TRAP-stained number of osteoclast surface per bone surface (Oc.S/BS) and osteoclast per bone perimeter (N.Oc/B.Pm). n = 10 mice/group from two independent experiments. n = 3 TRAP staining area from each slide were randomly selected and examined. Boxplot shows mean ± SD and the p value for two-tailed t test. ∗p < 0.05; ∗∗∗p < 0.001. (J) KEGG analysis of upregulated genes in macrophages of 5TGM1/ Nek2 −/− vs. 5TGM1/ Nek2 +/+ group. (K) UMAP plots of macrophage subpopulations (left) and violin plots showing their marker genes (right). (L) UMAP plots of NK/T subpopulations (left) and violin plots showing their marker genes (right). Please also see Figure S2 and Table S2 .

Article Snippet: ∗∗p < 0.01 (D) Stacked bar charts representing of BM cell populations following 10X Genomics scRNA-seq workflow (n = 6,379 cells for Nek2 +/+ , 5,746 cells for Nek2 −/− , 8,483 cells for 5TGM1/ Nek2 +/+ , and 9,676 cells for 5TGM1/ Nek2 −/− group). (E) Violin plot representing NEK2 expression in immune cell populations identified in (D). (F) Volcano plot showing differential gene expression in the macrophages of 5TGM1/ Nek2 −/− vs. 5TGM1/ Nek2 +/+ group with a |log 2 FC| > 1 and p < 0.05. (G) KEGG analysis of downregulated genes in macrophages of 5TGM1/ Nek2 −/− vs. 5TGM1/ Nek2 +/+ group. (H) Representative reconstructed μCT images of tibia sagittal sections showing bone lytic lesions and trabecular architecture. n = 5–10 mice/group from two independent experiments. (I) Quantitative histomorphometric analyses of TRAP-stained number of osteoclast surface per bone surface (Oc.S/BS) and osteoclast per bone perimeter (N.Oc/B.Pm). n = 10 mice/group from two independent experiments. n = 3 TRAP staining area from each slide were randomly selected and examined.

Techniques: Comparison, Expressing, Gene Expression, Staining, Two Tailed Test, Marker

Journal: The Journal of Experimental Medicine

Article Title: Rediscovering the human thymus through cutting-edge technologies

doi: 10.1084/jem.20230892

Figure Lengend Snippet: Single-cell and spatial omics methods

Article Snippet: , 10X Genomics 5′ scRNA-seq + scTCR-seq , mRNA, T cell receptor clonotype.

Techniques: Sequencing, Multiplex Assay, Expressing, Microarray, Imaging, Biomarker Discovery

Journal: Nature methods

Article Title: High-throughput and single-cell T cell receptor sequencing technologies

doi: 10.1038/s41592-021-01201-8

Figure Lengend Snippet: Overview of TCR sequencing methods

Article Snippet: Platform compatibility No. of cells assessed Paired TCRαβ TCR regions TCR targeting Gene expression Protein expression Chromatin accessibility No. of antigen specificities assessed a TCRαβ capture efficiency Select advantages Multiplex PCR (bulk) 22 – 24 – >10 5 No CDR3 Multiplex PCR – – – – – Compatible with either RNA or DNA as starting material 5′ RACE (bulk) 25 – 29 – >10 5 No Full length RACE PCR – – – – – Reduced PCR amplification bias Han et al. 10 Plate based 10 2 –10 3 Yes CDR3 Multiplex PCR Targeted panel – – – ~80% Can be implemented using standard laboratory reagents and equipment; high read coverage yields high-confidence TCR sequences pairSEQ 46 Plate based >10 5 Yes CDR3 Multiplex PCR – – – – – Does not require physical isolation of single cells; easily implemented with standard laboratory reagents and equipment Emulsion RT-PCR 48 – 52 Droplet 10 3 –10 6 Yes CDR3 Overlap extension multiplex PCR – – – – NAR High TCRαβ pairing efficiency due to physical linkage of transcripts; increased sensitivity and fewer artifacts as compared to standard PCR approaches Modified InDrop 70 Droplet 10 2 –10 4 Yes CDR3 Multiplex PCR Whole transcriptome – – – NAR Compatible with InDrop amplified RNA libraries Tu et al. 71 Microwell or droplet 10 3 –10 4 Yes CDR3 Multiplex PCR Whole transcriptome – – – ~35% Compatible with most 3′ scRNA-seq methods; applicable to preexisting amplified cDNA libraries RAGE-seq 72 Droplet 10 3 –10 4 Yes Full length Hybridization capture Whole transcriptome – – – ~17% Adaptable to any 3′ or 5′ scRNA-seq method 5′ V(D)J with feature barcoding 73 Droplet 10 3 –10 4 Yes Full length RACE PCR Whole transcriptome Yes – 44 ~65% Commercially available (10x Genomics) and easy to use ECCITE-seq 75 Droplet 10 3 –10 4 Yes Full length RACE PCR Whole transcriptome Yes – NAR ~65% Simultaneously captures many modalities, including sgRNA perturbations; highly modular T-ATAC-seq 74 Microwell 10 2 –10 3 Yes CDR3 Multiplex PCR – – Yes – ~70% Pairs TCR clonality with epigenomic state TetTCR-seq 96 Plate based 10 2 –10 3 Yes CDR3 Multiplex PCR – – – 315 ~70% Sensitive detection of rare antigen-specific T cell populations; easily scalable to large peptide libraries MATE-seq 98 Droplet 10 2 –10 4 Yes b CDR3 Multiplex PCR – – – 4 NAR Sensitive detection of rare antigen-specific T cell populations; compatible with lower sample inputs Open in a separate window a Demonstrated by original paper. b Paired TCRαβ per peptide, not per single cell.

Techniques: Sequencing, Gene Expression, Expressing, Multiplex Assay, Amplification, Isolation, Emulsion, Modification, Hybridization