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Image Search Results
Journal: Leukemia
Article Title: Spred1 deficit promotes treatment resistance and transformation of chronic phase CML
doi: 10.1038/s41375-021-01423-x
Figure Lengend Snippet: A Expression of SPRED1 in BM CD34+ cells from patients with BC CML and CP CML by Q-RT-PCR (n=8 samples for BC CML and n=12 samples for CP CML) and western blot and in BM by immunohistochemistry staining (one of three independent experiments with similar results was shown) (left), and expression of miR-126 in CD34+ and CD34+CD38− cells from BC CML (n=6 samples) and CP CML (n=10 samples) patients by Q-RT-PCR (right). B SPRED1 mRNA expression by Q-RT-PCR and protein expression by western blot, miR-126 levels by Q-RT-PCR, cell cycling by Ki-67 and DAPi staining (top) or by cell trace violet staining (bottom) followed by flow cytometry analysis in CML CD34+ cells transduced with SPRED1 siRNA to knock-down (KD) SPRED1 or with a non-targeting control siRNA (Ctrl). UND: undivided cells, G0; DIV: division. C Representative colonies and quantification of colony forming cells (CFC) in CML CD34+ (left) and CD34+CD38− (right) cells transduced with Spred1 siRNA to KD SPRED1 or with ctrl siRNA (n=3). Results shown represent mean ± SEM. Significance values: *, p<0.05; **, p<0.01; ***, p<0.001.
Article Snippet:
Techniques: Expressing, Reverse Transcription Polymerase Chain Reaction, Western Blot, Immunohistochemistry, Staining, Flow Cytometry, Transduction, Knockdown, Control
Journal: EBioMedicine
Article Title: A circular RNA map for human induced pluripotent stem cells of foetal origin
doi: 10.1016/j.ebiom.2020.102848
Figure Lengend Snippet: Stem cell transcriptome of MSC-hiPSC. a) Heatmap showing differentially expressed genes amongst MSC, hESC and MSC-hiPSC. Gene expression values are represented by the colour key. b) Dendrogram showing hierarchical clustering of MSC, hESC and MSC-hiPSC. c) Volcano plot showing p-value and fold change (FC) of gene expression data comparing MSC to MSC-hiPSC. Vertical dashed lines delimitate FC below and above 2, the horizontal dashed line shows p-value=0.05 [two-tailed t -test]. Colour code: FC greater than 2 reaching (green) or not (yellow) statistical significance; FC smaller than 2 reaching (red) or not (black) statistical significance. Enrichment in gene ontology terms of the biological processes category (GOTERM_BP_DIRECT) for upregulated genes of MSC (d) and MSC-hiPSC (e) is reported in the indicated tables [Fisher's exact test].
Article Snippet: The same day, CD34 + hematopoietic progenitor cells were isolated from cord blood by magnetic labelling using the
Techniques: Gene Expression, Two Tailed Test
Journal: EBioMedicine
Article Title: A circular RNA map for human induced pluripotent stem cells of foetal origin
doi: 10.1016/j.ebiom.2020.102848
Figure Lengend Snippet: Mesenchymal potential of MSC-hiPSC. a) Heatmap showing differentially expressed genes amongst different F-hiPSC and MSC-hiPSC. Gene expression values are represented by the colour key. b) Principal Component Analysis (PCA) showing 3D visualization of Principal Component (PC) 1, PC2 and PC3 of differentially expressed genes for different F-hiPSC, MSC-hiPSC and hESC. c) Volcano plot showing p-value and fold change (FC) of gene expression data comparing F-hiPSC to MSC-hiPSC. Vertical dashed lines delimitate FC below and above 2, the horizontal dashed line shows p-value=0.05 [two-tailed t -test]. Colour code: FC greater than 2 reaching (green) or not (yellow) statistical significance; FC smaller than 2 reaching (red) or not (black) statistical significance. Enrichment in gene ontology terms of the biological processes category (GOTERM_BP_DIRECT) for upregulated genes of MSC-hiPSC (d) and F-hiPSC (e) is reported in the indicated tables [Fisher's exact test]. f) Schematic of the differentiation protocol toward MSC-like cells. g) Representative images of adipogenic (A, scale bar is 50 µm), osteogenic (O, scale bar is 50 µm) and chondrogenic (C, scale bar is 400 µm) mesenchymal derivatives. h) Left panel: representative density plot showing CD45 + hematopoietic cells (P3) gated from total cells of the cobblestone area-forming cell assay; FSC-A, forward scatter area, a.u., arbitrary units. Right panel: representative histograms showing CD34 + hematopoietic progenitor subpopulation (purple) of CD45 + cells compared to unstained control (grey); the vertical axis represents event percentage count (Count%).
Article Snippet: The same day, CD34 + hematopoietic progenitor cells were isolated from cord blood by magnetic labelling using the
Techniques: Gene Expression, Two Tailed Test, Control
Journal: bioRxiv
Article Title: Genome-wide association study on 13,167 individuals identifies regulators of hematopoietic stem and progenitor cell levels in human blood
doi: 10.1101/2021.03.31.437808
Figure Lengend Snippet: Sequence variants influencing blood CD34 + cell levels identified in combined analysis of association data for 10,949 individuals of Swedish ancestry and 2,218 individuals of non-Swedish European ancestry. We identified 9 significant and 2 suggestive (*) associations ( Supplementary Table 3 ). The listed variants are the most significant (lead) variants for each association. We prioritized genes as candidate genes if they: (i) had a coding variant within the 99% credible set of probable causal variants ( Supplementary Table 4 ); (ii) had a cis -eQTL in CD34 + cells from 155 blood donors ( Supplementary Table 5 ); or (iii) the credible set contained a regulatory variant that maps either to the promoter, or to a region with a chromatin looping interaction with the promoter in CD34 + cells, as determined by PCHi-C. As regulatory variants, we considered variants in genomic regions whose chromatin is accessible in HSPCs, as determined by ATAC- sequencing. If none of these criteria were fulfilled, we prioritized the closest gene. The criterion used to call each gene a candidate gene is indicated in the matrix.
Article Snippet: We first enriched
Techniques: Sequencing, Variant Assay
Journal: bioRxiv
Article Title: Genome-wide association study on 13,167 individuals identifies regulators of hematopoietic stem and progenitor cell levels in human blood
doi: 10.1101/2021.03.31.437808
Figure Lengend Snippet: (a) LD score regression shows enrichments of heritability in regions with accessible chromatin in HSPC subpopulations. (b) To identify candidate genes with HSPC-intrinsic gene-regulatory effects, we generated eQTL data for sorted CD34 + cells from 155 blood donors. These figures illustrate strong cis -eQTLs identified at PPM1H , ENO1, RERE and ITGA9 ( Supplementary Table 5 ). Data are residual FPKM values after correction for 10 expression principal components. Wedges indicate directions of effects on blood CD34 + cell levels for the same variant. Notably, we detected an anti-correlation between PPM1H expression and CD34 + levels for the 12q14 variant. (c) Candidate gene expression in scRNA-seq data from blood and bone marrow mononuclear cells , showing enriched expression in HSPC populations ( Supplementary Fig. 7 and 8 ). (c,d) To map expression within the CD34 + compartment in better detail, we analyzed CITE-seq ( i.e. , mRNA-sequencing with antibody-derived tags) data for 4,905 lineage-negative CD34 + cells from adult bone marrow: (d) bulked expression in cell clusters inferred from mRNA levels; (e) bulked expression in clusters inferred from antibody-derived tags representing classical HSPC surface markers ( Supplementary Fig. 9 and 10 ). Abbreviations: Hematopoietic stem cells (HSC), multi-potent progenitors (MPP), common myeloid progenitors (CMP), granulocyte-monocyte progenitors (GMP), common lymphoid progenitors CLP), lymphoid-primed multipotent progenitors (LMPP), erythroid progenitors (ERY), megakaryocyte-erythrocyte progenitors (MEP), mast cell/basophil progenitors, (MB), dendritic cells (DC), plasma cells (PC), CD4 + T-cells (CD4), CD8 + T-cells (CD8), B-cells (B), pre B-cells (PreB), lymphoid progenitors (Ly), natural killer cells (NK), basophil (Baso), neutrophil (Neut), monocyte (Mono), cycling cells (Cyc).
Article Snippet: We first enriched
Techniques: Generated, Expressing, Variant Assay, Gene Expression, Sequencing, Derivative Assay, Clinical Proteomics
Journal: bioRxiv
Article Title: Genome-wide association study on 13,167 individuals identifies regulators of hematopoietic stem and progenitor cell levels in human blood
doi: 10.1101/2021.03.31.437808
Figure Lengend Snippet: (a) We detected four conditionally independent associations at 2p22, represented by a total of 69 credible set variants clustered around CXCR4 ( Supplementary Table 4 ). The credible sets are indicated in red (lead variant rs309137), green (rs11688530), cyan (rs555647251) and blue (rs10193623). The rs309137, rs11688530 and rs10193623 credible sets represent common variants, whereas rs555647251 represents a rare variant. By integrating ATAC-sequencing and PCHi-C data for CD34 + cells, we identified a single plausible causal variant within each credible set. rs309137 (“V1”) and rs10193623 (“V4”) have chromatin looping interactions with the CXCR4 promoter (red and blue arches; y -axis indicates PCHi-C P -score). rs59222832 (“V2”; credible set of rs11688530), and rs770321415 (“V3”; credible set of rs555647251) map to the CXCR4 promoter. (b) Chromatin accessibility at the four plausible causal variants; y -axis indicates ATAC-sequencing signal. (c) Using multi-variate regression, we detected conditional CXCR4 cis -eQTLs for the three common variants in our CD34 + cell mRNA-sequencing data from blood donors. Wedges indicate directions of effects on blood CD34 + cell levels. Of note, the effects of these three variants on CXCR4 expression are anti-directional to their effects on blood CD34 + cell levels. Data are residual FPKM values after correction for covariate SNPs and 10 principal components. (e) Using dual-sgRNA CRISPR/Cas9, we deleted 587 to 1421- bp regions harboring the four putative causal variants in MOLM-13 cells, resulting in downregulation of CXCR4 .
Article Snippet: We first enriched
Techniques: Variant Assay, Sequencing, Expressing, CRISPR
Journal: bioRxiv
Article Title: Genome-wide association study on 13,167 individuals identifies regulators of hematopoietic stem and progenitor cell levels in human blood
doi: 10.1101/2021.03.31.437808
Figure Lengend Snippet: (a) Top: the 12q14 signal is represented by a credible set of 32 variants in PPM1H intron 1. Middle: chromatin looping interactions in CD34 + cells with standard and internal promoter (red arches; y -axis indicates PCHi-C P -score). Bottom: we identified an approximately 500-bp-long chromosomal segment (red peak) where ATAC- sequencing signal (100-bp sliding window) shows strong positive correlation with PPM1H expression across 16 sorted blood cell populations ( y -axis indicates false discovery rate for Pearson correlation). (b) Four credible set variants map to the identified regulatory segment that is accessible in HSC, MPP, CMP and MEPs ( y -axis indicates ATAC-seq signal). (c) Luciferase analysis revealed higher activity with rs772557-G compared to rs772557-A constructs in the cis -eQTL direction ( P -value for one-sided Student’s t-test; ). Signals normalized to hg38 reference (left) alleles. (d) MYB binding site that is altered by rs772557; rs772557-G creates binding site, while rs772557-A abrogates it, by changing a critical recognition base (arrow). (e) ChIP-seq data for MYB in Jurkat cells (rs772557-heterozygous) show exclusive pull-down of reads harboring rs772557-G. (f) siRNA knockdown of MYB in K562 cells selectively attenuates rs772557-G luciferase activity. (g) Allele-specific CRISPR- Cas9 disruption at rs772557 ( Supplementary Fig. 14 ) in K562 cells, heterozygous for rs772557. We observed PPM1H downregulation with rs772557-G, but not with rs772557-A, sgRNA. (h) PPM1H and MYB are co-expressed in hematopoiesis . (i,j) Analysis of our CD34 + mRNA-sequencing data for blood donors revealed a correlation between MYB and PPM1H expression in rs772557-G carriers, and no correlation in non-carriers. Data are log 2 - transformed FPKM values, median-centered per genotype group.
Article Snippet: We first enriched
Techniques: Sequencing, Expressing, Luciferase, Activity Assay, Construct, Binding Assay, ChIP-sequencing, Knockdown, CRISPR, Disruption, Transformation Assay
Journal: bioRxiv
Article Title: Genome-wide association study on 13,167 individuals identifies regulators of hematopoietic stem and progenitor cell levels in human blood
doi: 10.1101/2021.03.31.437808
Figure Lengend Snippet: Since our cis -eQTL analysis identified an anti-correlation between blood CD34 + cell levels and PPM1H expression , we explored the effects of PPM1H downregulation on HSPC levels in better detail. (a) We first searched for effects of rs772557 on cell type composition within the CD34 + compartment in adults. For this, we calculated correlations between rs772557 genotype and gene expression in our CD34 + mRNA-sequencing data for blood donors, and tested for enrichment of correlation within sets of marker genes for HPSC subpopulations (Supplementary Fig. 15). This composite plot shows the distributions of Pearson correlation coefficients for the top 250 marker genes inferred using mRNA-sequencing data for sorted cells . We detected enrichments of positive correlations in the direction of rs772557-A allele for CMP, HSC, MEP, and MPP (red), and of negative correlations for CLP and LMPP (blue), compared to other genes in the genome (black) (details in Supplementary Fig. 15 ). This finding is consistent with rs772557-A increasing the relative abundance of CD34 + subpopulations in which the rs772557 region is accessible . (b) Quantifying HSPC subpopulations in 642 umbilical cord blood samples ( Supplementary Fig. 16 ), we observed association between rs772552-A and increased proportion of CMP and lower proportion of B/NK progenitors. (c) shRNA-knockdown of PPM1H induced an increase in the proportions of CD34 + and CD34 + 90 + primary cord blood cells out of green fluorescent protein (GFP)- positive. Data are proportion at day 7, 14 and 21 after transduction, normalized to shRNA- control. P -value is for permutation testing, taking into account the structure of the experimental design ( Online Methods ).
Article Snippet: We first enriched
Techniques: Expressing, Gene Expression, Sequencing, Marker, shRNA, Knockdown, Transduction, Control