A CLK3-HMGA2 Alternative Splicing Axis Impacts Human Hematopoietic Stem Cell Molecular Identity throughout Development

doi:10.1016/j.stem.2018.03.012

. 2018 Apr 5;22(4):575-588.e7.

doi: 10.1016/j.stem.2018.03.012.

A CLK3-HMGA2 Alternative Splicing Axis Impacts Human Hematopoietic Stem Cell Molecular Identity throughout Development

Marcella Cesana¹, Michael H Guo², Davide Cacchiarelli³, Lara Wahlster¹, Jessica Barragan¹, Sergei Doulatov⁴, Linda T Vo¹, Beatrice Salvatori⁵, Cole Trapnell⁶, Kendell Clement⁷, Patrick Cahan⁸, Kaloyan M Tsanov¹, Patricia M Sousa¹, Barbara Tazon-Vega⁷, Adriano Bolondi⁹, Federico M Giorgi⁵, Andrea Califano¹⁰, John L Rinn¹¹, Alexander Meissner¹², Joel N Hirschhorn², George Q Daley¹³

Affiliations

¹ Stem Cell Program, Division of Hematology/Oncology, Manton Center for Orphan Disease Research, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA.
² Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Endocrinology, Boston Children's Hospital, Boston, MA 02115, USA; Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
³ Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Telethon Institute of Genetics and Medicine (TIGEM), Armenise/Harvard Laboratory of Integrative Genomics, Pozzuoli 80078, Italy; Department of Translational Medicine, University of Naples "Federico II", Naples 80131, Italy.
⁴ Division of Hematology, University of Washington, Seattle, WA 98195, USA.
⁵ Department of Systems Biology, Columbia University, New York, NY 10032, USA.
⁶ Department of Genome Sciences, University of Washington, Seattle, WA 98115, USA.
⁷ Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
⁸ Department of Biomedical Engineering, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
⁹ Stem Cell Program, Division of Hematology/Oncology, Manton Center for Orphan Disease Research, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
¹⁰ Department of Systems Biology, Columbia University, New York, NY 10032, USA; Departments of Biomedical Informatics, Biochemistry and Molecular Biophysics, JP Sulzberger Columbia Genome Center, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA.
¹¹ Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; University of Colorado Boulder Biofrontiers, Boulder, CO 80301, USA.
¹² Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany.
¹³ Stem Cell Program, Division of Hematology/Oncology, Manton Center for Orphan Disease Research, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA. Electronic address: george.daley@childrens.harvard.edu.

PMID: 29625070
PMCID: PMC5957284
DOI: 10.1016/j.stem.2018.03.012

A CLK3-HMGA2 Alternative Splicing Axis Impacts Human Hematopoietic Stem Cell Molecular Identity throughout Development

Marcella Cesana et al. Cell Stem Cell. 2018.

. 2018 Apr 5;22(4):575-588.e7.

doi: 10.1016/j.stem.2018.03.012.

Authors

Affiliations

¹ Stem Cell Program, Division of Hematology/Oncology, Manton Center for Orphan Disease Research, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA.
² Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Endocrinology, Boston Children's Hospital, Boston, MA 02115, USA; Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
³ Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Telethon Institute of Genetics and Medicine (TIGEM), Armenise/Harvard Laboratory of Integrative Genomics, Pozzuoli 80078, Italy; Department of Translational Medicine, University of Naples "Federico II", Naples 80131, Italy.
⁴ Division of Hematology, University of Washington, Seattle, WA 98195, USA.
⁵ Department of Systems Biology, Columbia University, New York, NY 10032, USA.
⁶ Department of Genome Sciences, University of Washington, Seattle, WA 98115, USA.
⁷ Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
⁸ Department of Biomedical Engineering, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
⁹ Stem Cell Program, Division of Hematology/Oncology, Manton Center for Orphan Disease Research, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
¹⁰ Department of Systems Biology, Columbia University, New York, NY 10032, USA; Departments of Biomedical Informatics, Biochemistry and Molecular Biophysics, JP Sulzberger Columbia Genome Center, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10032, USA.
¹¹ Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; University of Colorado Boulder Biofrontiers, Boulder, CO 80301, USA.
¹² Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany.
¹³ Stem Cell Program, Division of Hematology/Oncology, Manton Center for Orphan Disease Research, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Biological Chemistry and Molecular Pharmacology, Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA. Electronic address: george.daley@childrens.harvard.edu.

PMID: 29625070
PMCID: PMC5957284
DOI: 10.1016/j.stem.2018.03.012

Abstract

While gene expression dynamics have been extensively cataloged during hematopoietic differentiation in the adult, less is known about transcriptome diversity of human hematopoietic stem cells (HSCs) during development. To characterize transcriptional and post-transcriptional changes in HSCs during development, we leveraged high-throughput genomic approaches to profile miRNAs, lincRNAs, and mRNAs. Our findings indicate that HSCs manifest distinct alternative splicing patterns in key hematopoietic regulators. Detailed analysis of the splicing dynamics and function of one such regulator, HMGA2, identified an alternative isoform that escapes miRNA-mediated targeting. We further identified the splicing kinase CLK3 that, by regulating HMGA2 splicing, preserves HMGA2 function in the setting of an increase in let-7 miRNA levels, delineating how CLK3 and HMGA2 form a functional axis that influences HSC properties during development. Collectively, our study highlights molecular mechanisms by which alternative splicing and miRNA-mediated post-transcriptional regulation impact the molecular identity and stage-specific developmental features of human HSCs.

Keywords: CLK3; HMGA2; RNA-seq; SRSF1; alternative splicing; human hematopoietic stem cells.

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Figures

**FIGURE 1. Transcriptional diversity among human HSCs along development**
A- Schematic of FACS sorting and transcriptomic analyses. Hematopoietic stem cells (HSC) and progenitor (PROG) cells were isolated according to the indicated surface markers from human Fetal Liver (FL), umbilical Cord Blood (CB) and Bone Marrow (BM) CD34+ cells. RNA-sequencing of both coding (mRNAs) and noncoding RNAs (lincRNAs) was performed along with miRNA expression quantification. B- (left) Pairwise comparisons showing the number of differentially expressed (DE) genes at FDR<0.01. (right) DE transcripts at isoform level (FDR < 0.01), but not at gene level (FDR > 0.01). Representative genes for each category are shown on the right. The full dataset can be found in Table S1. C- Expression heatmap of DE mRNA isoforms (top), lincRNAs (middle) and miRNAs (bottom). Representative isoforms shared among all HSC types (all-HSC) or progenitors (all-PROG), or specific to each population (as listed on left) are indicated on the right. The full dataset can be found in Table S2. D- (top) Gene structure of the most highly expressed *PROM1* isoforms (ISO) detected by RNA-seq. (bottom). Barplot showing *PROM1* expression (in FPKM) in the indicated HSC samples. Reference exons numbers are listed on top (constitutive exons are not shown), with coding exons in black and UTRs in gray. E- Violin plot representing distributions of statistically significant ΔPSI values (p<0.05) for different classes of PSI events: alternative 3’ splice site (A3), alternative 5’ splice site (A5), alternative first exon (AF), alternative last exon (AL), mutually exclusive exon (MX), retained intron (RI), and skipping exon (SE). Separate violins are shown for each pairwise comparison of HSC samples, and the number of events in each violin are shown on the right. ΔPSI values are shown for the second sample as compared to the first sample in each pair. F- *MEG3* lincRNA expression quantification by RNA-seq (in FPKM) in HSC and PROG samples. G- Barplot showing expression of *let-7* family members (red) and *miR-126* (green) in HSCs. Expression is shown as the percentage of total measured miRNA counts for each HSC population. Mean +/− s.d. values are shown for D, F and G. FPKM is Fragments Per Kilobase of transcript per Million mapped reads. H- BubbleMap visualization (Spinelli et al., 2015) of representative gene set enrichment analysis (GSEA) results between pairs of HSC samples. As indicated in the legend, for each GO category, colors (red versus blue) correspond to the sample label, shades represent statistical significance (FDR) and the area of the circle represents the enrichment (Normalized Enrichment Score, NES). Empty circles correspond to non-significant enrichments (FDR>0.05). The full dataset can be found in Table S4.

**FIGURE 2. HMGA2 alternative splicing in human HSCs**
A- Heatmap showing expression of *LIN28B, let-7* family members, the ranked median expression of the top 100 predicted *let-7* targets, and *HMGA2*. Previously dissected regulatory relationships of the LIN28-let-7-HMGA2 pathway (Viswanathan et al., 2008) are indicated with arrows. Scales are shown on the right as normalized z-scores. B- Visualization of RNA-seq reads (black bars) mapping at *HMGA2* (drawn to scale) in the indicated samples. A sashimi plot displaying the major splice junctions (FL-HSCs, *red*; CB-HSCs, *blue*) is superimposed. The abundance of each splicing junction is indicated and is normalized to the counts for the shared exon 2–3 splice junction (with value of 1). Arrows indicate the reads mapping to the terminal exons that distinguish the *HMGA2*-L and *HMGA2*-S isoforms. C- Structure of the human *HMGA2* locus (not drawn to scale). In the middle, locus coordinates are indicated along with coding exons (black) and UTRs (gray). Asterisk indicates location of major chromosomal rearrangements detected in malignancies (Kazmierczak et al., 1996). Red and blue dashed lines indicate how exons are spliced to result in *HMGA2*-L (top) and *HMGA2*-S (bottom). Gray boxes indicate the AT-binding hook domains. Green and black slashes indicate predicted binding sites of *let-7* family members and other conserved HSC-expressed miRNAs respectively. D- (top) Digital gel from RT-PCR electropherogram showing expression of *HMGA2*-L and *HMGA2*-S from the indicated HSC populations. Sizes of the amplicons are indicated on the right, along with the structure of each isoform (coding exons in black, UTRs in grey) and the position of the primers used for PCR co-amplification (black dots). (bottom) Digital gel from RT-PCR electropherogram showing expression of *HMGA2* pre-mRNA from the indicated HSC populations. *HPRT1* pre-mRNA was used as the control for both gels. Expression levels of *HMGA2* isoforms are indicated in Figure S2 and Table S2A. E- Shaded circles show *HMGA2* isoform expression (z-score normalized FPKM values) across HSCs and CB hierarchy from publicly available data (Stunnenberg et al., 2016). MPP: multipotent progenitors; CMP: common myeloid progenitors; MEP: myeloid erythroid progenitors; GMP: granulocyte macrophage progenitors; CLP: common lymphoid progenitors.

**FIGURE 3. Protein function of *HMGA2* isoforms**
A- Amount of DNA immunoprecipitated using V5 antibody in K562 and HPC-5F cells transduced with a control (C) or V5-tagged *HMGA2*-L (L) or *HMGA2*-S (S) ORF lentiviral overexpression (O/E) constructs. Mean +/− s.e.m. values are shown. B- Visualization of ChIP-seq read mapping at a sample locus. HPC-5F cells were transduced with V5-tagged *HMGA2*-L or *HMGA2*-S ORF constructs for overexpression of the protein coding regions of the respective isoforms (L or S). ChIP-seq profiles are shown for tagged-*HMGA2* (V5) or H3K4me2 (K4me2). Genes at the locus are indicated on the bottom. C- Number of gene promoters (total n=28314) enriched for HMGA2 (V5) and H3K4me2 (K4) upon overexpression of *HMGA2*-L (HMGA2-L-V5) or *HMGA2*-S (HMGA2-S-V5) ORFs. Promoters are considered highly enriched (Hi) for V5 or K4 if they rank in the top quartile of normalized read counts or depleted (Lo) if they fall in the bottom quartile. D- A/T content (as a percent) within immunoprecipitated promoter regions in the V5 Hi and V5 Lo categories or total promoter regions (as a background control). First and third quartiles, medians, and interquartile ranges are shown. E- *HMGA2*-L and *HMGA2*-S binding enrichment analysis shows 8456 differentially enriched promoters over the background signal. Correlation between *HMGA2*-L (L) and *HMGA2*-S (S)-enriched promoters is shown for V5 Hi and V5 Lo fractions. Values are reported as the log2 sum of ChIP replicate signals at promoter regions. PCC is Pearson′s correlation coefficient (r^2). Enrichment of GO categories from V5 Hi promoters are shown in Figure S3A. F- Differential expression analysis identified 1078 differentially expressed genes between *HMGA2*-L and *HMGA2*-S and the empty control. Correlation in expression between *HMGA2*-L (L) and *HMGA2*-S (S) treatments is shown. Values are reported as log2 average of FPKM replicates. PCC is Pearson′s correlation coefficient (r^2). The full pairwise comparisons are shown in Figure S3C. G- BubbleMap visualization (Spinelli et al., 2015) of GSEA results in HPC-5F cells transduced with *HMGA2*-L and *HMGA2*-S ORFs or control (CTRL) vectors. Gene sets were derived from HSC and PROG-specific signatures from Figure 1C (see Table S2C). As indicated in the legend, colors (red versus blue) correspond to the sample label, shades represent statistical significance (FDR) and the area of the circle represents the enrichment (Normalized Enrichment Score, NES). Empty circles correspond to non-significant (NS) enrichments (FDR>0.05). H- Human chimerism as percentage of GFP+CD45.1+ in the injected femur of xenografted mice 16 weeks after transplantation of HPC-5F cells transduced with lentivirus for *HMGA2*-L ORF, *HMGA2*-S ORF, or control (CTRL). Individual and mean values are shown. Mann-Whitney test was used individually comparing each indicated sample with respect to CTRL , p-values: <0.05 (*).

**FIGURE 4. Post-transcriptional regulation of *HMGA2* isoforms**
A- (left) Normalized luciferase (Renilla) activity in *Dgcr8*-KO MEF of constructs carrying 3’UTR sequences of *HMGA2*-L (Rluc-3’UTRwt_HMGA2-L) or a mutant derivative depleted for miRNA sites (Rluc-3’UTRmt_HMGA2-L). (right) Normalized luciferase (Renilla) activity in *Dgcr8*-KO MEF of constructs carrying 3’UTR sequences of *HMGA2*-L (Rluc-3’UTRwt_HMGA2-L) or *HMGA2*-S (Rluc-3’UTRwt_HMGA2-S). Normalized luciferase activities were reported with respect to Rluc-3’UTRmt_HMGA2-L (left panel) or Rluc-3’UTRwt_HMGA2-S (right panel), set to 100%. Mean +/− s.e.m values are shown. Unpaired t-test was used, p-values: <0.05 (*), <0.01 (**), <0.005 (***), borderline (° = 0.055). B- Quantification of miRNAs of interest in PC-3 and HPC-5F cells measured as by qRT-PCR. U6 snRNA was used as control. C- Relative quantification of *HMGA2* isoforms in PC-3 and HPC-5F cells transduced with lentiviral constructs carrying the *HMGA2* ORFs equipped with its corresponding 3’UTRs (HMGA2-L+3’UTRwt and HMGA2-S+3’UTRwt), or a derivative *HMGA2*-L isoform mutated for miRNA sites (HMGA2-L+3’UTRmt). Infected cells were treated with actinomycin D (Act-D) and harvested at the indicated time points. Expression values were normalized to *HPRT1* control, and then reported with respect to HMGA2-S+3’UTR-wt, set to 1. Mean +/− s.e.m values are shown. ANOVA was used, p-values: <0.05 (*), <0.01 (**), <0.005 (***).

**FIGURE 5. Modulation of *HMGA2* isoforms in human HSPCs**
**A,B**- Absolute expression of the indicated *HMGA2* isoforms (in FPKM) and miRNA families (as percentage of total measured miRNA content) in the indicated HSC populations. C- Scheme of *HMGA2* isoform modulation experiments in CB and BM CD34+ hematopoietic stem and progenitor cells (HSPCs). Lentiviral constructs (pLKO.1 and pLENTI) also express GFP as a marker to allow for isolation of infected cells. D- Phenotypic analysis of the stem cell compartment (CD133+CD34+CD38−) in CB CD34+ cells transduced with negative-control hairpin (luciferase - shLUC) or *HMGA2* isoform-specific shRNAs (shHMGA2-S or shHMGA2-L) following 7 days in culture. E- (left) Clonogenic progenitor assay of CD34+ CB cells following knockdown of *HMGA2* isoforms. Cells transduced with shLUC, shHMGA2-S and shHMGA2-L hairpins were plated 3 days post-infection and CFU potential was measured 14 days post-plating. (right) CFU potential of CD34+ CB transduced with hairpins against both *HMGA2* isoforms (shBOTH) was rescued upon overexpression of either the *HMGA2*-L or *HMGA2*-S ORFs. F- Phenotypic analysis of the stem cell compartment (CD133+CD34+CD38−) in BM CD34+ cells transduced with control (CTRL), HMGA2-L+3’UTRwt, HMGA2-L+3’UTRmt, or HMGA2-S+3’UTRwt constructs after 7 days in culture. G- Clonogenic progenitor assay of CD34+ BM cells following overexpression of *HMGA2* isoforms. Cells transduced with control (CTRL) were plated 3 days after infection and CFU potential was measured 14 days post-plating. Mean +/− s.e.m. values are shown for D, E, F, G. Analysis of deviance for generalized linear models (CFU analyses) or repeated measures ANOVA (FACS analyses) were used, p-values: <0.05 (*) or <0.01 (**), non-significant (NS).

FIGURE 6. *CLK3* affects *HMGA2* splicing through *SRSF1*
A- Schematic representation of the filtering strategy to identify regulators of *HMGA2* splicing. Genes were selected for the GO term “RNA binding” (GO:0003723), minimum expression, and ratio of expression in CB-HSC versus FL-HSC, as in the scheme. B- Ratio of expression of *HMGA2-S/HMGA2-L* following overexpression of the indicated candidate splicing factors in PC-3 cells. Controls (GFP and RFP) are shaded in gray. Values were normalized to the *HMGA2*-S/*HMGA2*-L ratio upon control GFP overexpression and shown as mean +/− s.e.m. C- *CLK3* expression by RNA-seq (in FPKM) in the indicated HSC populations. Mean +/− s.d. values are shown. FDR<0.01 (**). D- Schematic representation of *CLK3* and *HMGA2* modulation in BM HSPCs. E- *HMGA2* isoform quantification by RNA-seq (in FPKM) in BM-HSCs isolated upon overexpression of *CLK3* or control (CTRL) four days post-infection. Mean +/− s.d. values are shown. PCR validation is shown in Figure S5E. F- Violin plot representing distributions of statistically significant (p<0.05) ΔPSI values for different classes of PSI events (as in Figure 1H) in *CLK3* overexpression as compared to vector control. Individual significant events are shown. The number of events of each PSI class are shown below the plot. G- Schematic representation of *HMGA2*-L genomic structure (coding exons in black, UTRs in grey). SRSF1 binding motif sites are indicated by arrows in the corresponding exons. Sequence of exon 4 is indicated, and the predicted SRSF1 site (underlined in red) is shown. H- Schematic representation of the luciferase-based splicing reporter constructs. The pcDNA3.1-Luc plasmid contains an intron-spaced Firefly luciferase coding sequence (grey boxes) that produces bioactive luciferase protein only upon proper splicing of the intervening intron. The *HMGA2-L* genomic region encompassing exon 4 (black box) plus 500 bp on either side of the flanking introns (wild-type [WT] or mutated [mut] by deletion of SRSF1 site) was cloned into the intron of pcDNA3.1-Luc. Its inclusion in the luciferase coding sequencing abolishes bioactive luciferase. Normalized luciferase activities were tested with or without *CLK3* overexpression and reported with respect to Luc-exon-4 WT set to 100%. Mean +/− s.e.m. values are shown. Repeated measures ANOVA was used, p-value <0.05 (*).

**FIGURE 7. _CLK3 *HMGA2* axis orchestrates an HSC-specific program**
A- Phenotypic analysis of HSC content in BM CD34+ cells transduced with control (CTRL) or *CLK3* lentiviral constructs 4 days post-infection. Mean +/− s.e.m. values are shown. Unpaired t-test was used, p-value <0.01 (**). B- BubbleMap visualization (Spinelli et al., 2015) of GSEA results in BM-HSCs upon CTRL, *CLK3* or *HMGA2*-S-wt overexpression. Gene sets were derived from HSC and PROG -specific signatures from Figure 1C (see Table S2C). As indicated in the legend, colors (red versus blue) correspond to the sample label, shades represent statistical significance (FDR) and the area of the circle represents the enrichment (Normalized Enrichment Score, NES). Empty circles correspond to non-significant (NS) enrichments (FDR>0.05). Representative GSEA plot of the boxed BubbleMap is shown on the right. C- Venn diagrams of genes significantly DE (FDR<0.05) upon *CLK3* or *HMGA2*-S+3’UTRwt overexpression. D- RNA-seq based expression (in FPKM) of representative genes upon CTRL, *CLK3* and *HMGA2*-S+3’UTRwt overexpression in BM HSCs. Mean +/− s.d. values are shown. Cufflinks FDR <0.05 in all comparisons. E- Human chimerism as percentage of GFP+CD45.1+ in the injected femur of xenografted mice 8 weeks after transplantation of BM CD34+ HSPCs transduced with lentivirus for *HMGA2*-S+3’UTRwt, CLK3, or control (CTRL). Individual sample, mean +/− s.e.m. values are shown. Mann-Whitney test was used to individually compare each indicated sample with respect to CTRL , p-values: <0.05 (*).

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Comment in

Role of alternative splicing in hematopoietic stem cells during development.
Gao Y, Vasic R, Halene S. Gao Y, et al. Stem Cell Investig. 2018 Aug 23;5:26. doi: 10.21037/sci.2018.08.02. eCollection 2018. Stem Cell Investig. 2018. PMID: 30221171 Free PMC article. No abstract available.

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References

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1. Alamancos GP, Pagès A, Trincado JL, Bellora N, Eyras E. Leveraging transcript quantification for fast computation of alternative splicing profiles. RNA. 2015;21:1521–1531. - PMC - PubMed
1. Aubol BE, Wu G, Keshwani MM, Movassat M, Fattet L, Hertel KJ, Fu X-D, Adams JA. Release of SR Proteins from CLK1 by SRPK1: A Symbiotic Kinase System for Phosphorylation Control of Pre-mRNA Splicing. Mol. Cell. 2016;63:218–228. - PMC - PubMed
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[1] Agarwal V, Bell GW, Nam J-W, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 2015:4. - PMC - PubMed

[2] Agarwal V, Bell GW, Nam J-W, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 2015:4. - PMC - PubMed

[3] Alamancos GP, Pagès A, Trincado JL, Bellora N, Eyras E. Leveraging transcript quantification for fast computation of alternative splicing profiles. RNA. 2015;21:1521–1531. - PMC - PubMed

[4] Alamancos GP, Pagès A, Trincado JL, Bellora N, Eyras E. Leveraging transcript quantification for fast computation of alternative splicing profiles. RNA. 2015;21:1521–1531. - PMC - PubMed

[5] Aubol BE, Wu G, Keshwani MM, Movassat M, Fattet L, Hertel KJ, Fu X-D, Adams JA. Release of SR Proteins from CLK1 by SRPK1: A Symbiotic Kinase System for Phosphorylation Control of Pre-mRNA Splicing. Mol. Cell. 2016;63:218–228. - PMC - PubMed

[6] Aubol BE, Wu G, Keshwani MM, Movassat M, Fattet L, Hertel KJ, Fu X-D, Adams JA. Release of SR Proteins from CLK1 by SRPK1: A Symbiotic Kinase System for Phosphorylation Control of Pre-mRNA Splicing. Mol. Cell. 2016;63:218–228. - PMC - PubMed

[7] Babovic S, Eaves CJ. Hierarchical organization of fetal and adult hematopoietic stem cells. Exp. Cell Res. 2014;329:185–191. - PubMed

[8] Babovic S, Eaves CJ. Hierarchical organization of fetal and adult hematopoietic stem cells. Exp. Cell Res. 2014;329:185–191. - PubMed

[9] Bernitz JM, Kim HS, MacArthur B, Sieburg H, Moore K. Hematopoietic Stem Cells Count and Remember Self-Renewal Divisions. Cell. 2016;167:1296–1309. e10. - PMC - PubMed

[10] Bernitz JM, Kim HS, MacArthur B, Sieburg H, Moore K. Hematopoietic Stem Cells Count and Remember Self-Renewal Divisions. Cell. 2016;167:1296–1309. e10. - PMC - PubMed

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A CLK3-HMGA2 Alternative Splicing Axis Impacts Human Hematopoietic Stem Cell Molecular Identity throughout Development

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A CLK3-HMGA2 Alternative Splicing Axis Impacts Human Hematopoietic Stem Cell Molecular Identity throughout Development

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Abstract

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Medical

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