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Journal: Blood Advances
Article Title: Beyond FOXO1: AS1842856 inhibits GSK3 to enhance cytotoxic effects in B-ALL
doi: 10.1182/bloodadvances.2024015560
Figure Lengend Snippet: CTNNB1 contributes to the cytotoxic effect of AS1842856. (A-B) 018Z and RS4;11 cell lines were CRISPR/Cas9 edited with tandem CRISPR-RNA (crRNA) targeting CTNNB1. (A) The efficiency of CTNNB1 loss-of-function editing was measured by immunoblotting after 24-hour incubation with AS1842856 at a concentration of 100 nM to stabilize CTNNB1 (n = 2). (B) Dynamic of CTNNB1 inactivating mutations in CRISPR/Cas9-edited RS4;11 and 018Z cell lines. The proportion of inactivating mutations (KO score) was monitored by quantification of Sanger chromatograms of the edited region using the ICE (Inference of CRISPR Edits) CRISPR analysis tool ( https://ice.synthego.com , accessed on 13 June 2024; Synthego Corporation, Redwood City, CA). (C-I) CTNNB1-KO decreases the sensitivity of B-ALL to AS1842856 and CHIR-99021. The cytotoxic effect of the inhibitors on the survival of 018Z (C-E) and RS4;11 cell lines (F-I) was analyzed with the help of 6-day MTT assay. In panels E,H-I, the dose-effect data were fitted by nonlinear regression model and IC 50 values and AUC values were calculated with the help of GraphPad Prism software, version 10.30 (San Diego, CA). The significance of IC 50 or AUC differences was calculated by 2-sided nonpaired Student t test (n = 3).AUC, area under survival curve.
Article Snippet: The proportion of inactivating mutations (KO score) was monitored by quantification of Sanger chromatograms of the edited region using the
Techniques: CRISPR, Western Blot, Incubation, Concentration Assay, MTT Assay, Software
Journal: Science Advances
Article Title: Modulating immune cell fate and inflammation through CRISPR-mediated DNA methylation editing
doi: 10.1126/sciadv.adt1644
Figure Lengend Snippet: ( A ) Schematic of the dCas9-TET1 IL1RN promoter epigenome editing. The four sgRNAs targeting the IL1RN TSS are shown. #1 to #4 indicate the CpGs analyzed in (C). ( B ) ChIP-qPCR showing dCas9-TET1 enrichment at the IL1RN promoter. A 5-kb downstream region from the TSS is shown as a negative control region. Unpaired two-tailed Student’s t test, n = 3, mean SEM, (**** P < 0.0001). ( C ) DNAm levels (pyrosequencing) at four CpGs upstream of IL1RN TSS [as in (A)] in CTRL and edited B cells. One-way analysis of variance (ANOVA) with Dunnett’s post hoc correction, n = 3, means ± SEM, (* P < 0.05; ** P < 0.01, *** P <<0.001,**** P < 0.0001). ( D ) Top, IL1RN expression (RT-qPCR) in CTRL and edited B cells. Unpaired two-tailed Student’s t test, n = 3, means ± SEM, (*** P < 0.001). Bottom, IL1RN protein levels in CTRL and edited B cells. Fold change normalized to β-actin (CTRL versus sgIL1RN). ( E ) Schematic of the dCas9-DNMT3A IL1RN promoter epigenome editing experiment as in (A), showing two Infinium MethylationEPIC v2.0 probes. ( F ) Genome browser snapshot showing dCas9-DNMT3A binding at the IL1RN promoter. The location of the four sgRNAs targeting the IL1RN promoter and the two array probes is depicted. ( G ) Scatter plot showing differential dCas9-DNMT3A enrichment in sgIL1RN B cells. Large dots indicate top-bound promoters. ( H ) Scatter plot showing differentially hypermethylated CpGs in sgIL1RN day-3 cells. Blue dots indicate significantly hypermethylated CpGs (Δβ ≥ 0.3, FDR < 0.05, n = 13). Yellow dots highlight IL1RN probes shown in (E). ( I ) MA plot showing DEGs in sgIL1RN day-3 cells. ( J ) Upset plot depicting overlap of the dCas9-DNMT3A–binding sites, hypermethylated CpGs, and DEGs. ( K ) DNAm dynamics (array data) of two significantly hypermethylated IL1RN promoter CpGs. Unpaired two-tailed Student’s t test, n = 4, means ± SEM, (**** P < 0.0001). ( L ) IL1RN dynamics (RNA-seq) in CTRL and edited cells. Unpaired two-tailed Student’s t test, n = 2, means ± SEM, (*** P < 0.001).
Article Snippet: The design of the sgRNAs targeting the IL1RN promoter (chr2:113,127,440-113,127,701) and CTRL regions was performed using Benchling
Techniques: ChIP-qPCR, Negative Control, Two Tailed Test, Expressing, Quantitative RT-PCR, Binding Assay, RNA Sequencing
Journal: bioRxiv
Article Title: Genetic variation reveals a homeotic long noncoding RNA that modulates human hematopoietic stem cells
doi: 10.1101/2025.07.16.664824
Figure Lengend Snippet: (A) Schematic overview of experimental design for CRISPR/Cas9 or cytosine base editing (CBE) mediated editing of HOTSCRAMBL at rs17437411 in human CD34 + HSPCs, followed by genotyping, RNA, and in vitro functional assays at indicated timepoints. (B and C) Representative flow cytometry plots of CD34 + CD45RA-, CD34 + CD45RA-CD90 + CD133 + , and LT-HSC (CD34 + CD45RA-CD90 + CD133 + EPCR + ITGA3 + ) subsets at Day 5 post-editing in AAVS1 KO vs. HOTSCRAMBL KO (B), and AAVS1 CBE vs. HOTSCRAMBL rs17437411 (C). (D and E) Quantification of CD34 + CD45RA-, CD34 + CD45RA-CD90 + CD133 + , and LT-HSC populations at Day 5 (D) and Day 8 (E) post-editing based on flow cytometry. (F) Flow cytometric quantification of CD34 + CD45RA-CD90 + cells in S/G2/M phases at Day 5 by DyeCycle staining. (G) Representative CFSE flow cytometry plots showing cell division profiles of CD34 + CD45RA-CD90 + cells on Day 5. (H) Quantification of CFSE mean fluorescence intensity (MFI) in CD34 + CD45RA-CD90 + cells on Day 5. (I) Stacked bar plots of colony-forming unit (CFU) assay at 14 days post-plating, quantifying the distribution of erythroid (BFU-E), granulo-cyte/macrophage (CFU-G/M), and multilineage granulocyte-erythrocyte-monocyte-megakaryocyte (CFU-GEMM) colonies. All data are presented as mean ± SD, significance is indicated as ∗ P < 0.05, ∗∗ P < 0.01, ∗∗∗ P < 0.001, or n.s. (not significant).
Article Snippet: CRISPR/Cas9 editing efficiency and frameshift composition were analyzed using the Inference of
Techniques: CRISPR, In Vitro, Functional Assay, Flow Cytometry, Staining, Fluorescence, Colony-forming Unit Assay
Journal: bioRxiv
Article Title: Genetic variation reveals a homeotic long noncoding RNA that modulates human hematopoietic stem cells
doi: 10.1101/2025.07.16.664824
Figure Lengend Snippet: (A) Experimental workflow for using Locked Nucleic Acid (LNA) GapmeR knockdown of HOTSCRAMBL in human CD34 + HSPCs (in AAVS1 CBE and HOTSCRAMBL rs17437411). Cells were treated with HOTSCRAMBL-targeting or control GapmeRs and analyzed by flow cytometry and CFU assay at Day 5. (B) Flow cytometric quantification of CD34 + CD45RA-, CD34 + CD45RA-CD90 + CD133 + , and LT-HSC populations in cells treated with GapmeRs or control oligonucleotides under AAVS1 CBE or HOTSCRAMBL rs17437411 editing conditions at day 5, respectively. GR = GapmeR. (C) Stacked bar plots of CFU assay at 14 days post-plating, showing the distribution of BFU-E, CFU-G/M, and CFU-GEMM colonies. Cells were treated with GapmeRs or control oligonucleotides under AAVS1 CBE or HOTSCRAMBL rs17437411 editing conditions, respectively. (D) Experimental workflow for overexpression of HOTSCRAMBL or HOTSCRAMBL rs17437411 RNAs following CRISPR/Cas9-mediated HOTSCRAMBL knockout in human CD34 + HSPCs. Cells were transduced with SnoVectors expressing HOTSCRAMBL or HOTSCRAMBL rs17437411, and assessed by flow cytometry and CFU at Day 5. (E) Flow cytometric quantification of CD34 + CD45RA-, CD34 + CD45RA-CD90 + CD133 + , and LT-HSC populations in cells overexpressed with HOTSCRAMBL or HOTSCRAMBL rs17437411 RNAs under AAVS1 KO or HOTSCRAMBL KO editing conditions at day 5, respectively. (F) Stacked bar plots of CFU assay at 14 days post-plating, showing the distribution of BFU-E, CFU-G/M, and CFU-GEMM colonies. Cells were overexpressed with HOTSCRAMBL or HOTSCRAMBL rs17437411 RNAs under AAVS1 KO or HOTSCRAMBL KO editing conditions at day 5, respectively. All data are presented as mean ± SD, significance is indicated as ∗ P < 0.05, ∗∗ P < 0.01, ∗∗∗ P < 0.001, or n.s. (not significant).
Article Snippet: CRISPR/Cas9 editing efficiency and frameshift composition were analyzed using the Inference of
Techniques: Knockdown, Control, Flow Cytometry, Colony-forming Unit Assay, Over Expression, CRISPR, Knock-Out, Transduction, Expressing
Journal: bioRxiv
Article Title: Genetic variation reveals a homeotic long noncoding RNA that modulates human hematopoietic stem cells
doi: 10.1101/2025.07.16.664824
Figure Lengend Snippet: (A) Experimental workflow for gene editing in human CD34 + HSPCs followed by sorting of CD34 + CD45RA-CD90 + populations and bulk RNA sequencing to assess differential expressed genes (DEGs) and splicing events. (B) Volcano plots showing DEGs in HOTSCRAMBL KO vs. AAVS1 KO (left panel) and HOTSCRAMBL rs17437411 vs. AAVS1 CBE (right panel). (C) Heatmap of HOXA cluster genes in AAVS1 KO, HOTSCRAMBL KO, AAVS1 CBE and HOTSCRAMBL rs17437411 conditions. Color bar represents z-score (row-normalized expression), while circle size reflects relative expression level (non-normalized). (D) Sashimi plots of read coverage tracks at the HOXA9 locus showing exon usage and splicing patterns. (E) Quantification of total splice junction read counts mapped to HOXA9 exon 1-2. (F) Bar plot of normalized HOXA9 transcript counts derived from mRNA sequencing. (G) Western blot analysis of HOXA9 protein expression (up panel) and quantification normalized to VINCULIN (bottom panel). (H) Flow cytometric quantification of CD34 + CD45RA-, CD34 + CD45RA-CD90 + CD133 + , and LT-HSC populations in CD34 + HSPCs edited with AAVS1 -sgRNA (control) or two independent HOXA9 -targeting sgRNAs ( HOXA9 -sg1 and HOXA9 -sg2) using CRISPR/Cas9. (I) Schematic of lentiviral overexpression strategy using HOXA9 pre-mRNA or mature mRNA in AAVS1 CBE or HOTSCRAMBL rs17437411 edited groups, respectively. (J) Rescue of LT-HSC frequency in AAVS1 CBE or HOTSCRAMBL rs17437411 edited group by lentiviral expression of HOXA9 pre-mRNA or mRNA, quantified by flow cytometry. All data are presented as mean ± SD, significance is indicated as ∗ P < 0.05, ∗∗ P < 0.01, ∗∗∗ P < 0.001, or n.s. (not significant).
Article Snippet: CRISPR/Cas9 editing efficiency and frameshift composition were analyzed using the Inference of
Techniques: RNA Sequencing, Expressing, Derivative Assay, Sequencing, Western Blot, Control, CRISPR, Over Expression, Flow Cytometry