Journal: bioRxiv

Article Title: Intrinsic coordination of dynamic molecular signatures shape the human prefrontal cortex

doi: 10.64898/2026.05.13.724991

Figure Lengend Snippet: A) Schematic of the YBX1 knock-down (KD) workflow in hCOs. Three stem cell lines (UCLA1 hESC, UCLA6 hESC, KOLF iPSC) were infected with a YBX1-targeting shRNA (EGFP-labeled). Cortical organoids were generated from each cell line, which, after 18 days, were dissociated and re-aggregated together in the presence of YBX1 shRNA lentivirus (Anton-Bolanos, et al., 2024; Nano et al., 2025). The resulting chimeroids were grown for 8 weeks in culture, at which time EGFP+ (YBX1-KD) and EGFP– (unperturbed) cells were isolated by FACS and captured for single-cell multi-omic profiling (simultaneous scRNA-seq and scATAC-seq). Representative immunofluorescence images of 5-week-old chimeroids show YBX1 shRNA (EGFP, green), SOX2 (DAPI), and CTIP2 (DAPI), confirming cortical identity. Scale bar = 300 μm. B) YBX1 expression is significantly and consistently depleted in YBX1-KD cells across all three cell lines. (Top) UMAP projection from both RNA and ATAC modalities (UMAP WNN) of YBX1-KD hCO cells colored by perturbation condition. (Bottom) YBX1 expression in unperturbed versus YBX1-KD cells for each cell line, summarized with boxplots (two-sided Wilcoxon test). C) Loss of YBX1 favors deep layer fate over upper layer fate. (Top) UMAP (WNN) projection of cells colored by cell type, with the Deep Layer Excitatory Neuron cluster highlighted. (Bottom) Percent change in cell type proportion in YBX1-KD versus unperturbed cells for each cell type. Individual dots represent each cell line, data summarized by boxplot. Dashed line at 0 indicates no change. D) Loss of YBX1 activates neuronal gene programs in both radial glia and deep layer neurons. Dot plots show the percent change in activity of developmental meta-modules (Nano et al., 2025) in YBX1-KD versus unperturbed cells in radial glia (top) and deep layer excitatory neurons (bottom), colored by biological process. Module 20, associated with deep layer fate (Nano et al., 2025), is among the most elevated modules in both cell types. Only statistically significant effects are shown (p < 0.05, two-sided Wilcoxon test). E) YBX1 depletion attenuates most PFC signatures across the excitatory neuronal lineage. Bar and error bars show the average percent change in PFC signature activity in YBX1-KD versus unperturbed cells across radial glia, IPC, deep layer excitatory neurons, and upper layer excitatory neurons. Values for each individual cell line shown as dots. Only statistically significant effects are shown (p < 0.05, two-sided Wilcoxon test). F) Across the glutamatergic lineage, YBX1 is required for the majority of cell type-specific PFC signatures. Pie charts summarizing the number of cell type-specific PFC signatures that are dependent (pink) versus independent (teal) of YBX1 in each cell type. White indicates signatures that are not enriched in the PFC within the indicated cell type. G) YBX1 depletion induces broad shifts in chromatin accessibility, with effects significantly amplifying from radial glia to deep layer excitatory neurons (two-sided Wilcoxon test). Dots represent significantly differentially accessible chromatin peaks between unperturbed and YBX1-KD cells within radial glia and deep layer excitatory neurons, plotted based on fold-change in accessibility (p < 0.05, logistic regression test). Data are colored by YBX1-dependent regions (less accessible in YBX1-KD), YBX1-repressed regions (more accessible in YBX1-KD), and relatively unchanged regions (less than 25% change in accessibility, grey dots). Data summarized by boxplot. H) Loss of YBX1 modestly decreases the chromatin accessibility of PFC signatures. The average promoter region accessibility in each PFC signature was calculated per cell. Data show the percent change in this “PFC signature chromatin accessibility” in YBX1-KD vs unperturbed cells. Comparisons were conducted within radial glia and deep layer neurons, focusing solely on the PFC signatures relevant to each cell type. Dots indicate the percent-change in average chromatin accessibility for each cell type-specific signature, summarized by boxplots. P-value calculated by two-sided Wilcoxon test. I) YBX1 regulates PFC signatures at both the chromatin and transcriptional level in radial glia, but acts predominantly as a transcriptional regulator in deep layer neurons. Dot plot displays the percent change induced by YBX1-KD in each cell type-specific PFC signature, both in terms of average chromatin accessibility (blue) and gene expression (green). Dashed line at 0 indicates no change. J–K) In YBX1-sensitive PFC signatures shared between radial glia and deep layer neurons (J), YBX1 is required to open chromatin in radial glia but shifts to a predominantly transcriptional role in deep layer neurons – a cascade not observed in non-YBX1-sensitive signatures (K). Bar and error bars show, for the indicated PFC signatures, the average percent change in chromatin accessibility (blue) and gene expression (green) induced by YBX1-KD. Effects in radial glia and deep layer neurons are shown, with the values from individual cell lines shown as dots.

Article Snippet: Multiomic libraries were generated using the Chromium Next GEM Single Cell Multiome ATAC + Gene Expression Kit (10X Genomics, CG000338 Rev F) according to manufacturer instructions, using 7-8 cycles for ATAC library amplification, 6-7 cycles for cDNA amplification, and 10-14 cycles for gene expression library amplification depending on input DNA amount.

Techniques: Knockdown, Infection, shRNA, Labeling, Generated, Isolation, Single Cell, Immunofluorescence, Expressing, Activity Assay, Gene Expression

Journal: iScience

Article Title: Neoadjuvant chemotherapy enhances anti-tumor immune response of tumor microenvironment in human esophageal squamous cell carcinoma

doi: 10.1016/j.isci.2023.106480

Figure Lengend Snippet: Key resources table

Article Snippet: The obtained single cell suspension was used for scRNA-seq. . scRNA-seq library preparation and sequencing Libraries for scRNA-seq were generated using the Chromium Next GEM Single Cell 3ʹ Reagent Kit v3.1 (10x Genomics, Pleasanton, California, USA).

Techniques: Recombinant, Red Blood Cell Lysis, RNA Sequencing, Software

Journal: Advanced Science

Article Title: CD168 Identifies Proliferating Pancreatic Islet Cells in Murine and Human

doi: 10.1002/advs.202510590

Figure Lengend Snippet: Identification of the CD168 + population that is enriched for proliferating islet cells with low Ins expression. A) UMAP plot of 68155 pancreatic single‐cell (sc) RNA‐seq profiles (points), colored by cluster assignment and annotated post hoc. The newly identified population (Proliferating) is circled in red. The number of cells is shown in brackets under the indicated cell type. Cells were pooled from n=4 datasets. Mensen., mesenchymal; Endo., endothelial. B) Heatmap of cell‐type‐enriched genes. Each column represents a single cell, and each row represents one signature gene. The colors ranging from purple to yellow indicate low to high relative gene expression levels. C) Selected GO terms of upregulated genes in the proliferating population. 375 genes were selected with min.pct =0.25 and logfc.threshold =0.25. D–F) Individual gene UMAP plots showing the expression levels and distribution of endocrine β (D) and proliferation (E) representative markers. The colors ranging from blue to red indicate low to high relative gene expression levels. The Vln plot shows the expression level (log2(TPM+1)) of the indicated genes in each cell type. The proliferating population expressed both proliferation markers and β‐cell markers, and expressed surface marker CD168 (F). G) FACS analysis of CD168‐expressing cells in hand‐picked mouse islets. The blood lineage cells (CD31 and CD45) were negatively selected, and epithelial cells (EpCAM) were positively selected. Within the CD31 − CD45 − EpCAM + islet endocrine compartment, 0.52% ± 0.02% of cells were CD168 + . Data were pooled from n=3 biological replicates and presented as mean ± SEM. H) qPCR analysis of CD168 , Mki67 , Ins1 , and Nkx6.1 of the proliferating population in FACS‐isolated cells. n=3 biological replicates. For each replicate, cells were isolated from 10 mice. Data are presented as mean ± SEM. An unpaired two‐tailed t ‐test was used for comparison. ** p <0.01, *** p <0.001. I and J) Islet CD168 + and CD168 − cells were sorted by FACS for CD168/Ins immunostaining (I). Quantification indicating that the majority (70.5%) of CD168 + cells were Ins low , whereas 58.8% of CD168 − cells were Ins high (J). Scale bar, 25 µm. Data were pooled from n=3 biological replicates and presented as mean ± SEM. K and L) Islet CD168 + and CD168 − cells were sorted by FACS for Nkx6.1 immunostaining (K). 73.1% of CD168 + cells were Nkx6.1 low , while 64.2% CD168 − cells were Nkx6.1 high (L). Scale bar, 25 µm. Data were pooled from n=3 biological replicates and presented as mean ± SEM. M) Quantification indicating ≈90.7% CD168 + cells were Ins + , 2.8% CD168 + cells were Gcg + , 1.2% CD168 + cells were Sst + , 0.9% CD168 + cells were Ppy + , and 4.4% CD168 + cells were hormone negative.

Article Snippet: CD168 antibody (Cell Signaling Technology, 87129S) was incubated on room temperature at a dilution of 1:50, and the second antibody (Donkey Anti‐Rabbit Alexa Fluor 647, Invitrogen, A31573 ) dilution of 1:100.

Techniques: Expressing, Single Cell, RNA Sequencing, Gene Expression, Marker, Isolation, Two Tailed Test, Comparison, Immunostaining

Journal: Advanced Science

Article Title: CD168 Identifies Proliferating Pancreatic Islet Cells in Murine and Human

doi: 10.1002/advs.202510590

Figure Lengend Snippet: CD168 marks proliferating cells in G2/M phase in pancreatic islets. A,B) Islet CD168 + and CD168 − cells were sorted by FACS for CD168/Ki67 immunostaining, showing that CD168 + cells expressed proliferation marker Ki67 (A). Quantification indicating that 91.4% of CD168 + cells were Ki67 + , while 0.5% of CD168 − cells were Ki67 + (B). Scale bar, 25 µm. Similar results were confirmed by n=3 mice. An unpaired two‐tailed t ‐test was used for comparison. *** p <0.001. C and D) Representative confocal image of an 8‐week‐old mouse islet whole mount immunostaining, indicating that CD168 + cells expressed Ki67 in situ (C). Scale bar, 25 µm. Quantification indicating that 85.7% of CD168 + cells were Ki67 + , while 0.9% of CD168 − cells were Ki67 + (D). Similar results were confirmed by n=3 mice. An unpaired two‐tailed t ‐test was used for comparison. *** p <0.001. E) FACS analysis of CD168 and Ki67 co‐staining in fixed handpicked islet cells from 8‐week‐old mice. The majority of CD168 + cells were Ki67 + , and ≈37.5% Ki67 + cells were CD168 + . Data were pooled from n=3 biological replicates and presented as mean ± SEM. F) The left panel shows newborn 1‐week‐old islet cells, and the right panel shows pregnant day 12.5 islet cells. Data were pooled from n=3 biological replicates and presented as mean ± SEM. G and H) Representative confocal image of an 8‐week‐old mouse islet whole mount immunostaining, indicating that the nuclear size of CD168 + cells was larger in situ (G). Scale bar, 25 µm. Quantification indicated that CD168 + cells exhibited a larger nuclear size than CD168 − cells. (H). Similar results were confirmed by n=3 mice. An unpaired two‐tailed t ‐test was used for comparison. *** p <0.001. I) FACS analysis of CD168 and PI co‐staining in fixed handpicked islet cells. The majority of CD168 + cells were PI high . Data were pooled from n=3 biological replicates and presented as mean ± SEM. J and K) Islet CD168 + and CD168 − cells were sorted by FACS for pHH3 immunostaining, showing that CD168 + cells expressed proliferation marker pHH3 (J). The left panel showed that pHH3 was punctate, indicating the cell was at the G2 phase. The middle panel showed that pHH3 smeared in the nucleus, indicating the cell was at mitotic prophase (J). Quantification indicating that 88.5% of CD168 + cells were at G2 phase, and 11.5% of CD168 + cells were at prophase (K). Scale bar, 25 µm. Similar results were confirmed by n=3 mice.

Article Snippet: CD168 antibody (Cell Signaling Technology, 87129S) was incubated on room temperature at a dilution of 1:50, and the second antibody (Donkey Anti‐Rabbit Alexa Fluor 647, Invitrogen, A31573 ) dilution of 1:100.

Techniques: Immunostaining, Marker, Two Tailed Test, Comparison, In Situ, Staining

Journal: Advanced Science

Article Title: CD168 Identifies Proliferating Pancreatic Islet Cells in Murine and Human

doi: 10.1002/advs.202510590

Figure Lengend Snippet: Lineage tracing of CD168 + cells in pancreatic islets and various tissues. A) Targeting strategy to generate the CD168‐CreERT2 knock‐in (KI) mouse. B) Illustration of the lineage tracing strategy of CD168 + cells using Rosa26‐mTmG reporter. 8‐week‐old mice were administered with tamoxifen (TAM) (4 mg/25 g body weight), and tissues were harvested after 4 h or 8 weeks post‐induction. C) The left two panels show representative confocal images of the islet whole mount from CD168‐CreERT2;Rosa26‐mTmG mice at 4 h, indicating that at the beginning of tracing (4 h), mGFP + labeled cells were Ki67 + . The right two panels show representative confocal images of the islet whole mount from CD168‐CreERT2;Rosa26‐mTmG mice 8 weeks after TAM treatment. n=3 mice. Scale bars: 25 µm. D) Flow cytometry analysis and quantification of mGFP + cell percentage in the islets at 4 hrs pi (left) and 8 wks pi (right). At 4 hrs pi, 0.14% of islet cells were labeled with mGFP, and all mGFP + cells were CD168 + . At 8 wks pi, the mGFP + cell percentage increased to 1.8%. Data were pooled from n=3 biological replicates and presented as mean ± SEM. E) Representative confocal images of intestine, liver, testis, and hair follicle frozen section from CD168‐CreERT2;Rosa26‐mTmG mice at 4 hrs pi, indicating that at the beginning of tracing, mGFP + labeled cells were Ki67 + (Left two panels). The right two panels show representative confocal images at 8 wks pi. n=3 mice. Scale bars: yellow, 100 µm; white, 25 µm.

Article Snippet: CD168 antibody (Cell Signaling Technology, 87129S) was incubated on room temperature at a dilution of 1:50, and the second antibody (Donkey Anti‐Rabbit Alexa Fluor 647, Invitrogen, A31573 ) dilution of 1:100.

Techniques: Knock-In, Labeling, Flow Cytometry

Journal: Advanced Science

Article Title: CD168 Identifies Proliferating Pancreatic Islet Cells in Murine and Human

doi: 10.1002/advs.202510590

Figure Lengend Snippet: Clonal analysis reveals unipotent and multipotent CD168 + cells. A) Illustration of the lineage tracing strategy of CD168 + cells using Rosa26‐Confetti reporter in adult islets. 8‐week‐old mice were administered TAM (2 mg/25 g body weight), and tissues were harvested after 8 weeks. B–E) Representative whole mount immunostaining of islets demonstrating the existence of uni‐β lineage (white solid arrowhead) (B), uni‐α lineage (yellow solid arrowhead) (C), uni‐δ lineage (yellow solid arrowhead) (D), and uni‐PP lineage (yellow solid arrowhead) (E). n=8 mice. Scale bar, 25 µm. F–H) Representative whole mount immunostaining of islets demonstrating the existence of multi‐lineage, including β (solid arrowhead) + α (arrow) + potential hormone negative cell (open arrowhead) clone (F), β (solid arrowhead) + δ (arrow) clone (G), and β (solid arrowhead) + PP (arrow) clone (H). n=8 mice. Scale bar, 25 µm. I) Clonal analysis at 8 weeks pi. β‐cell numbers are shown along the x ‐axis, and α, δ, or PP cell numbers are shown along the y ‐axis. Red shading indicates the relative frequency of certain clone compositions, with deeper shading indicating higher frequency. n=8 mice, 350 clones. J) Quantification indicating that 4.8% of clones were multi‐lineage, while 87.4% of clones were uni‐β lineage, 4.9% of clones were uni‐α lineage, 1.7% of clones were uni‐δ lineage, and 1.1% of clones were uni‐PP lineage. n=8 mice, 350 clones. K) Illustration of the CD168 + cell lineage model.

Article Snippet: CD168 antibody (Cell Signaling Technology, 87129S) was incubated on room temperature at a dilution of 1:50, and the second antibody (Donkey Anti‐Rabbit Alexa Fluor 647, Invitrogen, A31573 ) dilution of 1:100.

Techniques: Immunostaining, Clone Assay

Journal: Advanced Science

Article Title: CD168 Identifies Proliferating Pancreatic Islet Cells in Murine and Human

doi: 10.1002/advs.202510590

Figure Lengend Snippet: Lineage tracing documents the time course of β‐cell maturation. A) Illustration of the lineage tracing strategy of CD168 + cells using Rosa26‐Confetti reporter in adult islets. 8‐week‐old mice were administered with TAM (2 mg/25 g body weight) and tissues were harvested after 1 day, 4 days, 14 days, or 60 days. B) Representative islet whole mount immunostaining of mCFP and Nkx6.1 (left) and quantification (right) indicating that at the beginning of tracing (1 dpi), 80% of labeled cells were Nkx6.1 low , while 20% were Nkx6.1 high , n=3 mice, 105 labeled cells. Scale bar, 25 µm. C and D) Representative whole mount immunostaining of islets (C), indicating that the proportion of Nkx6.1 high in traced cells increased to 30.8% at 4 dpi, to 41.3% at 14 dpi, and to 91.1% at 60 dpi. The sky‐blue arrows indicate Nkx6.1 low cells, and the dark‐blue arrows indicate Nkx6.1 high cells. n=3 mice, >100 labeled cells in each group. Scale bar, 25 µm. Quantification of the percentage of Nkx6.1 high cells in traced clones (D). ** p <0.01, *** p <0.001. E) GSIS experiments using sorted CD168‐CreERT2;Rosa26‐mTmG traced cells, verifying that 14 dpi traced cells were less mature than 60 dpi traced cells. n.s., not significant. *** p <0.001.

Article Snippet: CD168 antibody (Cell Signaling Technology, 87129S) was incubated on room temperature at a dilution of 1:50, and the second antibody (Donkey Anti‐Rabbit Alexa Fluor 647, Invitrogen, A31573 ) dilution of 1:100.

Techniques: Immunostaining, Labeling, Clone Assay

Journal: Advanced Science

Article Title: CD168 Identifies Proliferating Pancreatic Islet Cells in Murine and Human

doi: 10.1002/advs.202510590

Figure Lengend Snippet: ATAC‐seq reveals epigenome remodeling and shift of transcription network during β‐cell maturation. A) Assay for transposase‐accessible chromatin with high‐throughput sequencing (ATAC‐seq) and RNA‐seq were performed using sorted CD168‐CreERT2;Rosa26‐mTmG traced cells at 14 dpi and 60 dpi, and mature β‐cells. B) Principal Component Analysis (PCA) of 14 dpi, 60 dpi, and β‐cells in ATAC‐seq. C) PCA of 14 dpi, 60 dpi, and β‐cells in RNA‐seq. D‐G) The difference analysis of peaks showed that 504 loci gradually opened during 14 dpi to 60 dpi (D). GO analysis of the 504 loci (E). Transcriptional factor (TF) network of the pro‐maturation 504 loci (F). The pro‐maturation TF motif (G). H–K) The difference analysis of peaks showed that 15865 loci specifically opened in 14 dpi (H). GO analysis of the 15865 loci (I). TF network of the immature β‐cell 15865 loci (J). The immature β‐cell TF motif (K).

Article Snippet: CD168 antibody (Cell Signaling Technology, 87129S) was incubated on room temperature at a dilution of 1:50, and the second antibody (Donkey Anti‐Rabbit Alexa Fluor 647, Invitrogen, A31573 ) dilution of 1:100.

Techniques: Next-Generation Sequencing, RNA Sequencing

Journal: Advanced Science

Article Title: CD168 Identifies Proliferating Pancreatic Islet Cells in Murine and Human

doi: 10.1002/advs.202510590

Figure Lengend Snippet: CD168 is a conserved proliferating cell surface marker in human PNETs. A) UMAP plot of normal human pancreas scRNA‐seq profiles (points), colored by cluster assignment and annotated post hoc. The new population (Proliferating) is circled in red. The number of cells is shown in brackets under the indicated cell type. Cells were pooled from published data. Mensen., mesenchymal; Endo., endothelial. B) The Vln plot shows the expression level (log2(TPM+1)) of the indicated gene in each cell type. The proliferating population expressed higher proliferation markers and lower β‐cell markers. C) Representative confocal image of a normal adult human pancreas sample frozen section, indicating that CD168 + cells were KI67 + (left two panels) and INS low (right two panels). Scale bar, 25 µm. D) UMAP plot of human PNET scRNA‐seq profiles (points), colored by cluster assignment and annotated post hoc. The new population (Proliferating) is circled in red. The number of cells is shown in brackets under the indicated cell type. Cells were pooled from published data. Mensen., mesenchymal; Endo., endothelial. E) The Vln plot shows the expression level (log2(TPM+1)) of the indicated gene in each cell type. The proliferating population expressed both proliferation markers and β‐cell markers. F) Representative confocal image of adult human PNET sample frozen section, indicating that CD168 + cells were KI67 + and INS low . Scale bar, 25 µm. G) FACS analysis of CD168‐expressing cells in human PNET sample and paracancerous tissue. The blood lineage (CD31 and CD45) + and non‐islet cells (CD56 − ) were excluded. Within the CD31 − CD45 − CD56 + islet endocrine compartment, the proportion of CD168 + cells was higher in the PNET sample. Data were presented as mean ± SEM. H) Quantification of CD168 + cell percentage in 5 PNET samples. An unpaired two‐tailed t ‐test was used for comparison. * p <0.05. I) RNA‐seq analysis indicating upregulation of proliferation‐related genes and downregulation of mature β‐cell‐related genes in CD168 + cells compared to CD168 − cells. J) GO analysis of CD168 + cells enriched proliferating pathways. K) RT‐qPCR analysis of proliferating markers CD168 , MKI67 , and CENPE , and mature β‐cell markers INS , NKX6.1 , and UCN3 in FACS‐isolated cells as indicated. n=3 biological replicates. For each replicate, cells were isolated from 1 human PNET sample. Data were presented as mean ± SEM. An unpaired two‐tailed t ‐test was used for comparison. ** p <0.01, *** p <0.001.

Article Snippet: CD168 antibody (Cell Signaling Technology, 87129S) was incubated on room temperature at a dilution of 1:50, and the second antibody (Donkey Anti‐Rabbit Alexa Fluor 647, Invitrogen, A31573 ) dilution of 1:100.

Techniques: Marker, Expressing, Two Tailed Test, Comparison, RNA Sequencing, Quantitative RT-PCR, Isolation

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Uniform Manifold Approximation and Projection (UMAP) of scATAC–seq from peripheral blood, colored by enrichment of lead SNPs in open chromatin peaks per cluster . b , Clustered hierarchical heatmap for haplotypes with at least one molecular mechanism assigned. Mechanistic assignment weight = 1/(number of distinct candidate mechanisms among SNPs in the haplotype). c , Micro-C from CD4 + T cells (3-kb bin size; pooled from three replicates), ATAC–seq (CD4 + , unstimulated blue, stimulated red, overlay) and CTCF ChIP–seq for the 1q24.3–25.1 locus: MCC for rs75084219 (eczema), rs78037933 (vitiligo), rs1474379684 (celiac disease) and rs62803660 (Crohn’s disease) with SNP–promoter contacts highlighted in gray (3 biological replicates, each with 6 technical replicates (18 in total)). d , Comparison of the number of variant–promoter ligation junctions identified by MCC (median = 828.2) and Micro-C (median = 2.07) ( n = 349 promoter contacts measured across 2 independent libraries for both methods, median (center line), 25th and 75th percentiles (box limits) and whiskers extending to the most extreme values within 1.5× the interquartile range). e , Gene ontology overrepresentation analysis of MCC-prioritized genes in CD4 + T cells (top ten pathways by gene ratio are shown (total significant hits = 251)). The gene ratio is defined as the number of genes in the input list that are annotated to the corresponding term (function) over the number of genes in the input list. f , Comparison between the enrichment of genes with the highest number of MCC contacts (primary nominated gene) versus genes with the second highest number of MCC contacts (secondary nominated gene) compared to background (all genes ±1 Mb from captured variants). For reference, the enrichment scores of the nearest and second nearest genes for each variant are also shown (essentiality (Depmap), drug target and approved drugs (open targets) and primary immunodeficiency (Genomics England)) ( χ 2 test, two-sided P values reported in ). cDCs, conventional dendritic cells; MAIT, mucosal-associated invariant T cells; NK, natural killer cells; pDCs, plasmacytoid dendritic cells; T CM , central memory T cells; T EM , effector memory T cells; T reg , regulatory T cells; B int, intermediate B cells.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: ChIP-sequencing, Comparison, Variant Assay, Ligation, Analysis

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Uniform Manifold Approximation and Projection (UMAP) of single-cell ATAC sequencing from peripheral blood. b , Upset plot of SNP prioritisation pipeline output. A total of 3238 IMID-GWAS signals were analysed, with 1441 having at least 1 SNP being identified in the six molecular mechanisms tested (coding, splicing, enhancer, CTCF, promoter, UTR). A total of 727 were classified as CTCF altering or enhancer altering in activated CD4 + /CD8 + T cells or Monocytes. c , Enrichment scores of IMID-associated SNPs for each molecular mechanism tested in the SNP prioritisation pipeline (n = 124,000) compared to dbSNP151 common variants across the genome (n = 15,000,000). Enrichment scores were calculated as: the fraction of GWAS variants that can be explained by the tested molecular mechanisms over fraction of total common variants explained by the tested molecular mechanism (Χ 2 test, two-sided, 3’UTR ( P = 0.001), coding ( P = 0.145), CTCF ( P = 0.203), promoter ( P = 3.68 × 10 −10 ), splicing (P = 7.97 × 10 −13 , enhancer (4.67 × 10 −53 )). d , 3 kb binned Micro-C, ATAC (CD4 + , unstimulated blue, stimulated red, overlay) and CTCF ChIP-seq for the 10q21.3 locus with MCC from rs12766391 . e , 1.5 kb binned Micro-C, ATAC (CD4 + , unstimulated blue, stimulated red, overlay) and CTCF ChIP-seq for the RUNX3 locus with MCC from rs57974094 (green) and rs4265380 (blue). cDCs, conventional dendritic cells; MAIT, mucosal-associated invariant T cells; NK, natural killer cells; pDCs, plasmacytoid dendritic cells; T cm , central memory T cells; T em , effector memory T cells; T reg , regulatory T cells; B int, intermediate B cells.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Single Cell, Sequencing, ChIP-sequencing

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Count data for PCR deduplicated reads containing the target SNP for a subset (donor 1 only) of heterozygous SNPs (n = 147 variant read counts from 6 independent MCC libraries from a single donor). This data is used to variant call the genotype of captured GWAS sites before applying the MCCv single-allele analysis pipeline. b , Summary of the number of variants captured by MCC (total) and those amenable to allelic analysis (heterozygous). c , Visualisation of the total number of heterozygous variants and the breakdown of those where allelic data was successfully generated using MCCv. We also include a theoretical estimation of the number of variants that could generate allele-specific data in a dpnII-based 3 C experiment (for example Capture C), where variants had to fall within 60 bp of a dpnII-cut site to be classified as successful. d , The distribution of SNPs in the MCCv dataset in terms of percentage of peaks which are significantly altered between alleles (relative to the total number of MCCv peak for that SNP). e , as in Fig. but data has been filtered for promoters, CTCF, or enhancer elements before plotting. f , MCCv profile for rs9526002 , with SNP-promoter contact highlighted in grey. Difference plots show alternate-minus-reference contacts, with CD4 + ATAC-seq and CTCF ChIP-seq tracks below. g , rs10950648 nanoscale contact maps generated using 10-bp directional windowing and mirrored on the diagonal. The AP-1 motif and enhancer sequence are shown, with the effect of the alternate allele highlighted (n = 12 (2 donors, 6 independent MCC libraries each), merged β = −1.10).

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Variant Assay, Analysis, Generated, Capture-C, ChIP-sequencing, Sequencing

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Alternate or reference normalized junction counts at MCCv peaks for heterozygous SNPs ( n depends on how many donors are heterozygous for the SNP from which the peak is derived (minimum of six independent libraries per donor), paired, two-sided Student’s t -test, local false discovery rate (FDR) estimation). b , Clustered hierarchical heatmap of the average ratio of alternate to reference junction counts for peaks overlapping different regulatory element categories per SNP. c , Percentage of variants with significant MCCv changes (two-sided χ 2 test, disease variants n = 227). Enrichment over controls (enrichment, P , n control): cell type = IMID variants intersecting monocyte enhancers (7.5, 0.0015 and 14); haplotype = SNPs in haplotype that do not intersect CD4 + T cell enhancers (7.5, 2.73 × 10 −13 and 82); enhancer = variants that intersect CD4 + T cell enhancers but are not associated with IMIDs (2.2, 0.000014 and 76). d , MCCv from rs10950648 with SNP–promoter contact in gray. Difference plots (alternate minus reference), ATAC–seq (CD4 + , unstimulated blue, stimulated red) and CTCF ChIP–seq shown underneath. e , Nanoscale contact maps of rs10950648 with 10-bp directional windowing. They are mirrored on the diagonal. PRDM1 motif and enhancer sequences are shown with the effect of the alternate allele highlighted ( n = 12, merged β = -1.09). f , ATAC–seq read skew for rs10950648 ( q = 0.024) and rs9526002 ( q = 0.025) ( n = 2 donors, mean ± s.d.). g , Allelic expression of primary or secondary nominated genes phased to a heterozygous variant: 88 variants (102 variant–gene pairs) tested. Twenty-three genes showed donor-level skew (variable-phased SNPs ( n ) per gene; two-sided, Wilcoxon’s signed-rank test was used per donor (Fisher’s method across donors) with the Benjamini–Hochberg correction). h , Percentage of allelically imbalanced genes by SNP–gene categories. Backgrounds were genome-wide allelic gene imbalance, 10.0% (231 out of 2,313) and allelic gene imbalance without MCCv skew, 8.9% (17 out of 190). The percentage of genes showing allelic imbalance linked to variants with evidence of MCCv changes (category: n variant-–gene pairs, enrichment over genome-wide ( p ), enrichment over MCCv ( p ); secondary genes: 6 of 23, 2.61 (0.0316); primary genes 10 of 33, 3.03 (0.0316), 3.40 (0.038); primary or secondary: 16 of 45, 3.55 (0.0001), 3.99 (0.0002) (two-tailed χ 2 test).

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Derivative Assay, Control, ChIP-sequencing, Expressing, Variant Assay, Genome Wide, Two Tailed Test

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Schematic of converting nanoscale heatmaps into directionally windowed heatmaps for the visualisation of contacts between transcription factor motifs. Reads that give rise to ligation junctions are thought to be protected from MNase cutting by bound transcription factors. The direction of the extension of the reads can be leveraged to estimate the position of the putatively bound transcription factor. This converts the negative signal of the transcription factor footprint into positive signal equating to potential contacts between transcription factors. b , MCC ultra tile over the rs10950648 -containing enhancer (n = 6 independent MCC libraries, bin size = 2, tile = 2.2 kb). Corresponding ATAC (CD4 + , unstimulated blue, stimulated red, overlay) and a unified CTCF track are shown underneath. The capture probe/SNP locations are shown by the horizontal bar and red triangle respectively. Zoom in shows MCCv single-allele directional windowed heatmaps for reference and alternate alleles at the variant shown in Fig. . c , As in b for the rs9526002 -containing enhancer with zoom in corresponding to directional windowed heatmap as shown in Extended Data Fig. (n = 6 independent MCC libraries, bin size = 2, tile = 1.9 kb). d and e , Footprinting data from ATAC-seq combined with MCCv based capture enrichment (above) and 1D-MCCv footprinting (below) for both reference and alternate alleles of rs10950648 and rs9526002 . SNP position is indicated with the red triangle.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Ligation, Variant Assay, Footprinting

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Effect size estimate of GLM from basepairC at tested SNPs (n = 231) (bottom 20% of variants based on read counts were filtered). Estimates were done between maps of different genotypes (allele-specific) (Genotype, mean β-coefficient (effect size) = 0.293). Random combinations of 6 reference and 6 alternate allele sample matrices were compared (mean β-coefficient = 0.097) (median (centre line), 25th and 75th percentiles (box limits), and whiskers extending to most extreme values within 1.5 × interquartile range). b , Effect size from basepairC matrix difference modelling in Jurkat controls (prioritised using ATAC skew) vs. T cell disease associated enhancers (prioritised by ATAC intersection only). Variants within lowest 10% of read counts for MCCv nanoscale maps were filtered from the correlation. Gain-of-function (MCCv nanoscale effect size ≥ 0.2) and loss-of-function (MCCv nanoscale effect size ≤ -0.2) variants are highlighted in green and purple respectively. Variants highlighted throughout the study are indicated on the plot (Jurkat controls – n = 38 variants (6 independent MCC libraries), IMID variants – n = 191 variants (6 independent MCC libraries from 1-3 biological donors, median (centre line), 25th and 75th percentiles (box limits), and whiskers extending to the most extreme values within 1.5 × the interquartile range.). c , Allelic ratio from ATAC-seq versus effect size from basepairC matrix difference modelling (n = 201, two-sided Spearman’s ρ = 0.62, P = 2.2 × 10 −16 ). Variants within the lowest 10% of read counts for either ATAC or MCCv were filtered from the correlation. Nominally gain-of-function (ATAC allelic ratio ≥ 0.55 & MCCv nanoscale effect size ≥ 0.05) and loss-of-function (ATAC allelic ratio ≤ 0.45 & MCCv nanoscale effect size ≤ -0.05) variants are highlighted in green and purple respectively.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques:

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Associations of rs4409785 from the National Center for Biotechnology Information (NCBI) GWAS catalog, with −log 10 ( P ) versus log 10 (odds ratio) for the tested allele plotted as a volcano. Associations reported with reference T allele are shown in purple, whereas associations reported with the alternate C allele are shown in green. Representative autoimmune disease signals are labeled (autoimmune thyroid disease (ATD), RA, MS, myasthenia gravis (MG) and vitiligo). b , CTCF consensus motif and the sequence around rs4409785 in humans. The effect of rs4409785 is highlighted in gray. Sequence alignment from early hominins and chimps is shown below. c , MCCv basepair resolution footprinting for reference and alternate alleles with the rs4409785 location marked by a red triangle. Corresponding nanoscale heatmaps are shown as in Fig. (bin size = 1 bp, 800-bp window, n = 6 merged per allele and merged β = 1.09). d , CTCF ChIP–seq ( q = 0.000123), ATAC–seq ( q = 0.000123) and H3K27ac ChIP–seq ( q = 0.156) skew in heterozygous donors ( n = 15 CTCF or ATAC, n = 12 H3K27ac; two-sided Wilcoxon’s matched-pairs, signed-rank test, two-stage step-up procedure for multiple-test correction, mean ± s.d.). e , CTCF ChIP–seq and ATAC–seq reads per kilobase of transcript per million mapped reads-normalized signal from three donors who are either homozygous reference (purple) or alternate (green) for rs4409785 . f , MCCv profiles for rs4409785 alleles with corresponding ATAC (CD4 + , unstimulated blue, stimulated red, overlay) and a unified CTCF track. Capture probe location or SNP is marked by the red triangle and CTCF elements with orientation are marked by purple triangles.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Labeling, Sequencing, Footprinting, ChIP-sequencing

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Schematic illustrating coupling of basepair-level editing technologies with basepair resolution MCCv. Incomplete genome editing is leveraged to make a population of cells with mixed alleles become deconvoluted with the platform’s single-allele capabilities. b , Base editing experimental design with CTCF guide RNA sequence as well as locations of rs4409785 and the CTCF motif shown. The location of an upstream control guide outside the extended CTCF motif but within the MCC capture oligonucleotide is also shown. c , Experimental set-up of the CTCF and control edits in primary T cells. Edits were performed in parallel and mixed to avoid double editing. The cell mix was then fixed and captured by MCCv. As these cells were heterozygous for risk variant rs4409785 this led to six different editing outcomes that were deconvoluted by single-allele MCCv. To increase the depth of the data, six independent replicates were performed. d , Allele-specific (relative to rs4409785 ) editing efficiency of BE4max in primary CD4 + T cell for both control and CTCF guides. Editing efficiencies are shown as a percentage of NGS reads with C-to-T substitution. Where multiple Cs could be edited, the one with highest editing efficiency is shown ( n = 2 independent experiments, mean ± s.d.). e , Edit-MCCv tracks for reference (purple) and alternate (green) alleles of rs4409785 with wild-type, control edit and CTCF edit shown. A CTCF ChIP–seq track is shown underneath. f , Nanoscale heatmaps for rs4409785 reference and alternate alleles with corresponding edit type (bin size = 1 bp, 800-bp window, n = 6 merged per allele). NGS, next-generation sequencing.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Sequencing, Control, Variant Assay, ChIP-sequencing, Next-Generation Sequencing

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Ligation junction counts between rs4409785 and the major downstream CTCF site (wild type vs. edit; q = 0.089 (reference) and q = 0.000001 (alternate), wild type vs. control; q = 0.141 (reference) and q = 0.079 (alternate)) (n = 6 independent MCC libraries across 1 biological donor with 3 independent nucleofections, Student’s t-test, two-sided, two-stage step-up procedure for multiple test correction, mean ± s.d.). b , Detailed schematic for MCCv phasing strategy employed in order to analyse super-enhancer–promoter contacts and RNA in an allele-specific manner. Zoom-in shows the locations of phased intronic SNPs for both SESN3 and FAM76B used in RNA skew analysis. c , Rank Ordering of Super-enhancers (ROSE) analysis of H3K27ac ChIP-seq data from activated CD4 + T cells. The dashed line marks the inflection point above which enhancers are classified as super-enhancers (SE). The SESN3 super-enhancer is labelled in red and is ranked as the 75 th strongest super-enhancer out of 760 super-enhancers and 15,281 total enhancers. d , RPKM normalised ATAC signal at a genomic window corresponding to the defined super enhancer in a variety of blood cell types with both unstimulated (blue) and stimulated (green) paired data.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Ligation, Control, Analysis, ChIP-sequencing

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , A 2.5-kb, binned Micro-C, ATAC–seq (CD4 + , unstimulated blue, stimulated red, overlay) and CTCF ChIP–seq for the 11q21 locus. Bulk MCCs from the promoters of SESN3 and FAM76B are shown in blue. The location of the super-enhancer is highlighted in gray. b , Phased enhancer–promoter contacts ( SESN3 ( q = 0.018, n = 24 peaks across six independent MCC libraries) and FAM76B ( q = 0.916, n = 24 peaks across six independent MCC libraries), Student’s t -test, two-stage step-up procedure for multiple-test correction, mean ± s.e.m.) and intron-rich RNA ( SESN3 ( q = 0.00054, n = 37 phased heterozygous variants across two donors) and FAM76B ( q = 0.11, n = 45 phased heterozygous variants across two donors), Wilcoxon’s signed-rank test, two-stage step-up procedure for multiple-test correction, mean ± s.e.m.) from MCCv-phased heterozygous variants for both SESN3 and FAM76B . c , Working mechanistic model for the 11q21 risk locus. The neo-CTCF site competes with canonical upstream boundary elements for convergent downstream CTCF sites, forming a subdomain that isolates the super-enhancer away from the promoter of SESN3 .

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: ChIP-sequencing

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , Experimental design of the mouse EAE model. b , Clinical EAE score for both Rosa26 and Sesn3 cohorts. For each day where both cohorts were represented, scores were compared statistically ( n = 6 mice per condition, day 12, q = 0.0024; day 13, q = 0.0089; day 14, q = 0.0024; two-sided, unpaired, Student’s t -test with single pooled variance, mean ± s.e.m.). c , Dot plot representation of SESN gene family members’ scRNA-seq expression from synovial tissue of patients wth RA . d , Representative flow cytometry contour plots showing a positive population of CD4 + ( y axis) and phospho-4E-BP1 + (mTORC1 signaling marker, x axis). e , Western blots for FLAG-tagged SESN3 or GATOR2 complex subunit, WDR59, either from cell lysate (input) or from co-immunoprecipitation using anti-FLAG antibody-conjugated beads. Experimental conditions compared were a medium control (fed state) versus a starved state in Hanks’ balanced salt solution (HBSS) with or without various free amino acids. Specific indicated free amino acids were added to the starved state during the 1-h starvation at 500 µM. f , Schematic for working model of the effect of rs4409785 on reducing SESN3 gene expression and, in turn, how this may affect mTORC1 signaling in starvation conditions, specifically low tryptophan availability. AAVS1 , adeno-associated virus integration site 1; CNS, central nervous system; E-P, enhancer–promoter; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; IFN, interferon; IP, immunoprecipitation; MOG, myelin oligodendrocyte glycoprotein; MT hi , mitochondrial high; mTORC1, mTOR complex 1; PTX, pertussis toxin.

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Expressing, Tissue, Flow Cytometry, Marker, Western Blot, Co-Immunoprecipitation Assay, Control, Gene Expression, Virus, Immunoprecipitation

Journal: Nature Genetics

Article Title: Single-allele nanoscale mapping of regulatory variants

doi: 10.1038/s41588-026-02776-8

Figure Lengend Snippet: a , % edited reads, 24 h post-nucleofection in mHSPCs for Rosa26 and Sesn3 guides (n = 1). b , CD45.1 + % in different cell types; CD8 + (q = 0.0029), CD4 + (q = 0.0098), Myeloid (q = 0.344), B cells (q = 0.723) in Rosa26 or Sesn3 conditions (n = 7 mice per condition, Student’s t-test single pooled variance, two-sided, unpaired, two-stage step-up procedure for multiple test correction, mean ± s.d.). c , Relative mouse weights for Rosa26 and Sesn3 cohorts (day 12, q = 0.023; day 13, q = 0.026; day 14, q = 0.026) (n = 6 mice per condition, Student’s t-test single pooled variance, two-sided, unpaired, two-stage step-up procedure for multiple test correction, mean ± s.e.m.). d , Survival curve post EAE-induction for Rosa26 and Sesn3 conditions ( P = 0.019, n = 6, Grehan-Brislow-Wilcoxon test, two-sided). e , % infiltrating activated T cells (CD4 + IFNγ + IL17 + CD44 high ) in CNS for Rosa26 and Sesn3 cohorts ( P = 0.0038, Student’s t-test, two-sided, n = 6 mice per condition, mean ± s.d.). f , Rooted phylogenetic maximum-likelihood tree of SESN gene family from amino-acid sequence. g , Single-cell RNA-seq UMAP from healthy volunteer PBMCs ( SESN3 expression highlighted in green). h , Experimental scheme for ex vivo human T cell editing in fed and starved conditions. i , Tracking of indels by decomposition analysis 72 h post-nucleofection of T cells for AAVS1 and SESN3 sgRNAs (n = 3 nucleofections, mean ± s.d.). j , Phospho-4E-BP + CD4 + T cells % for AAVS1 or SESN3 sgRNA nucleofections in media ( P = 0.462) or starvation ( P = 0.014) (n = 5 nucleofections across donors, Student’s t-test, two-sided, median, interquartile range (box; 25th–75th percentiles), whiskers extending to the most extreme data points within 1.5 × the interquartile range ) . k , Immunoblot for anti-FLAG-SESN3 in wildtype (WT), FLAG knock-in (Tag), and FLAG knock-in edited with sgRNAs targeting SESN3 (Tag-KO).

Article Snippet: The peripheral blood mononuclear cell layer was isolated and CD4 + or CD3 + pan-T cells were enriched with CD4 + magnetic beads (Miltenyi, cat. no. 130-045-101) or pan-T cell isolation kit (Miltenyi, cat. no. 130-096-535), respectively, as per the manufacturer’s instructions.

Techniques: Sequencing, Single Cell, RNA Sequencing, Expressing, Ex Vivo, Analysis, Western Blot, Knock-In