Point mutations in the PDX1 transactivation domain impair human β-cell development and function

doi:10.1016/j.molmet.2019.03.006

. 2019 Jun:24:80-97.

doi: 10.1016/j.molmet.2019.03.006. Epub 2019 Mar 20.

Point mutations in the PDX1 transactivation domain impair human β-cell development and function

Xianming Wang¹, Michael Sterr¹, Ansarullah², Ingo Burtscher², Anika Böttcher², Julia Beckenbauer², Johanna Siehler¹, Thomas Meitinger³, Hans-Ulrich Häring⁴, Harald Staiger⁵, Filippo M Cernilogar⁶, Gunnar Schotta⁶, Martin Irmler⁷, Johannes Beckers⁸, Christopher V E Wright⁹, Mostafa Bakhti¹⁰, Heiko Lickert¹¹

Affiliations

¹ Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Technische Universität München, Ismaningerstraße 22, 81675 München, Germany.
² Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
³ Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany.
⁴ Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Zentrum München at the University of Tübingen, 72076 Tübingen, Germany; Department of Internal Medicine, Division of Endocrinology, Diabetology, Vascular Medicine, Nephrology and Clinical Chemistry, University of Tübingen, 72076 Tübingen, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany.
⁵ Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Zentrum München at the University of Tübingen, 72076 Tübingen, Germany; Institute of Pharmaceutical Sciences, Department of Pharmacy and Biochemistry, Eberhard Karls University Tübingen, 72076 Tübingen, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany.
⁶ Biomedical Center and Center for Integrated Protein Science Munich, Ludwig-Maximilians-University, 82152 Planegg-Martinsried, Germany.
⁷ Institute of Experimental Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
⁸ German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany; Institute of Experimental Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Chair of Experimental Genetics, School of Life Sciences Weihenstephan, Technische Universität München, 85354 Freising, Germany.
⁹ Vanderbilt University Program in Developmental Biology, Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN 37232, USA; Vanderbilt Center for Stem Cell Biology, Vanderbilt University, Nashville, TN 37232, USA.
¹⁰ Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany.
¹¹ Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Technische Universität München, Ismaningerstraße 22, 81675 München, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany. Electronic address: heiko.lickert@helmholtz-muenchen.de.

PMID: 30930126
PMCID: PMC6531841
DOI: 10.1016/j.molmet.2019.03.006

Point mutations in the PDX1 transactivation domain impair human β-cell development and function

Xianming Wang et al. Mol Metab. 2019 Jun.

. 2019 Jun:24:80-97.

doi: 10.1016/j.molmet.2019.03.006. Epub 2019 Mar 20.

Authors

Affiliations

¹ Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Technische Universität München, Ismaningerstraße 22, 81675 München, Germany.
² Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
³ Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany.
⁴ Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Zentrum München at the University of Tübingen, 72076 Tübingen, Germany; Department of Internal Medicine, Division of Endocrinology, Diabetology, Vascular Medicine, Nephrology and Clinical Chemistry, University of Tübingen, 72076 Tübingen, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany.
⁵ Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Zentrum München at the University of Tübingen, 72076 Tübingen, Germany; Institute of Pharmaceutical Sciences, Department of Pharmacy and Biochemistry, Eberhard Karls University Tübingen, 72076 Tübingen, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany.
⁶ Biomedical Center and Center for Integrated Protein Science Munich, Ludwig-Maximilians-University, 82152 Planegg-Martinsried, Germany.
⁷ Institute of Experimental Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
⁸ German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany; Institute of Experimental Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Chair of Experimental Genetics, School of Life Sciences Weihenstephan, Technische Universität München, 85354 Freising, Germany.
⁹ Vanderbilt University Program in Developmental Biology, Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN 37232, USA; Vanderbilt Center for Stem Cell Biology, Vanderbilt University, Nashville, TN 37232, USA.
¹⁰ Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany.
¹¹ Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Technische Universität München, Ismaningerstraße 22, 81675 München, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany. Electronic address: heiko.lickert@helmholtz-muenchen.de.

PMID: 30930126
PMCID: PMC6531841
DOI: 10.1016/j.molmet.2019.03.006

Abstract

Objective: Hundreds of missense mutations in the coding region of PDX1 exist; however, if these mutations predispose to diabetes mellitus is unknown.

Methods: In this study, we screened a large cohort of subjects with increased risk for diabetes and identified two subjects with impaired glucose tolerance carrying common, heterozygous, missense mutations in the PDX1 coding region leading to single amino acid exchanges (P33T, C18R) in its transactivation domain. We generated iPSCs from patients with heterozygous PDX1^P33T/+, PDX1^C18R/+ mutations and engineered isogenic cell lines carrying homozygous PDX1^P33T/P33T, PDX1^C18R/C18R mutations and a heterozygous PDX1 loss-of-function mutation (PDX1^+/-).

Results: Using an in vitro β-cell differentiation protocol, we demonstrated that both, heterozygous PDX1^P33T/+, PDX1^C18R/+ and homozygous PDX1^P33T/P33T, PDX1^C18R/C18R mutations impair β-cell differentiation and function. Furthermore, PDX1^+/- and PDX1^P33T/P33T mutations reduced differentiation efficiency of pancreatic progenitors (PPs), due to downregulation of PDX1-bound genes, including transcription factors MNX1 and PDX1 as well as insulin resistance gene CES1. Additionally, both PDX1^P33T/+ and PDX1^P33T/P33T mutations in PPs reduced the expression of PDX1-bound genes including the long-noncoding RNA, MEG3 and the imprinted gene NNAT, both involved in insulin synthesis and secretion.

Conclusions: Our results reveal mechanistic details of how common coding mutations in PDX1 impair human pancreatic endocrine lineage formation and β-cell function and contribute to the predisposition for diabetes.

Keywords: Insulin secretion; PDX1; PDX1-Bound genes; Transactivation domain; β-Cell differentiation.

PubMed Disclaimer

Figures

**Figure 1**
Generation of β-like cells from patients carrying *PDX1*^P33T/+and *PDX1*^C18R/+**mutations.** (A) Schematic of iPSC-derived β-like cells protocol. (B) Immunostaining for CPEP, GCG, PDX1, and NKX6.1 in the XM001, *PDX1*^P33T/+ and *PDX1*^C18R/+ cells at the S7 stage. Scale bar indicates 25 μm. (C) Representative FACS plots of CPEP⁺ cells in the XM001, *PDX1*^P33T/+ and *PDX1*^C18R/+ cells at the S7 stage. (D) FACS quantification of the percentage of CPEP⁺ cells in the XM001, *PDX1*^P33T/+ and *PDX1*^C18R/+ cells at the S7 stage (n = 3). (E) RT-qPCR analysis of *INS* gene expression in the XM001, *PDX1*^P33T/+ and *PDX1*^C18R/+ cells at the S7 stage (n = 3). (F) Glucose-stimulated insulin secretion assay for the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the S7 stage. The fold change of insulin secretion with high glucose (16.7 mM) relative to low glucose (2.8 mM) treatment is shown (n = 3).

**Figure 2**
Characterization of *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18Rmutations at the early pancreatic stage (PP1). (A) Representative FACS plots of PDX1⁺ cells in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the early pancreatic stage. (B) Representative immunofluorescence staining of PDX1 in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R. Scale bar indicates 50 μm. (C) FACS quantification of the percentage of PDX1⁺ cells in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T and *PDX1*^C18R/C18R cells at the PP1 stage (n = 3). (D) Representative immunoblot of PDX1 expression from XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the PP1 stage. (E) Representative FACS histograms comparing the differentiation efficiencies towards the PDX1⁺ cells in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells. (F) Median Fluorescence Intensity (MFI) quantification for XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the PP1 stage stained with PDX1 antibody (n = 6).

**Figure 3**
Characterization of *PDX1*^+/−, *PDX1*^P33T/P33Tand *PDX1*^C18R/C18Rmutations at the late pancreatic stage (PP2). (A) Representative immunofluorescence staining of PDX1 and NKX6.1 in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells. Scale bar indicates 50 μm. (B) Representative FACS plots of PDX1⁺ and NKX6.1⁺cells in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the PP2 stage. (C) FACS quantification of the percentage of PDX1⁺ and NKX6.1⁺cells in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the PP2 stage (n = 3).

**Figure 4**
Characterization of the impact of *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18Rmutations on β-like cell differentiation. (A) Representative immunofluorescence staining for C-peptide, Glucagon, PDX1 and NKX6.1 in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage. Scale bar indicates 50 μm. (B) Representative FACS plots of CPEP⁺ and GCG⁺ cells in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage. (C) FACS quantification of the percentage of total CPEP⁺ cells in the XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage (n = 3). (D) FACS quantification of the percentage of mono-hormonal CPEP⁺ cells in the XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage (n = 3).

**Figure 5**
*PDX1* mutations reduce glucose-responsive function of β-like cells. (A) Representative FACS plots for C-peptide⁺ and NKX6.1⁺ in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T and *PDX1*^C18R/C18R cells at the S7 stage. (B) FACS quantification of the percentage of total CPEP⁺ and NKX6.1⁺ cells in the XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage (n = 3). (C) GSIS assay for the XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage. The fold change of insulin secretion with high glucose (16.7 mM) relative to low glucose (2.8 mM) treatment is shown (n = 3). (D) RT-qPCR analysis of expression of β-cell transcription factors, hormonal markers and β-cell functional markers at the S7 stage (n = 4).

**Figure 6**
RNA-seq profiling of pancreatic progenitors (PP1) from *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18RiPSC lines. (A) MA plot showing the mean log₂ expression against the log₂-fold change of the RNA-Seq data obtained from XM001 iPSCs and PPs from XM001 and isogenic *PDX1* mutants. Genes with significantly different expression (log₂ fold change ≥ 2 and adjusted p-value ≤ 0.05) are drawn in color. Red depicts increased expression in PPs, whereas orange depicts increased expression in iPSCs. (B) Bar graph of p-values from pathway enrichment analysis, showing selected GO terms and KEGG and Reactome pathways from differentially expressed genes. (C) Principal component analysis (PCA) of iPSCs and PP1 cells. (D–F) MA plots showing the mean log₂ expression against the log₂ fold change of the RNA-Seq data obtained from *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R compared to XM001. Genes with significantly different expression (log₂ fold change ≥ 1 and adjusted p-value ≤ 0.1) are drawn in color. Red depicts increased expression in XM001 control PPs, blue, green and purple depict increased expression in *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R, respectively. Black circles genes with PDX1 binding sites in XM001 PPs. (G) Venn diagrams showing the overlap of up- and downregulated genes from *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R PPs compared to XM001 PPs. Some relevant pancreatic and disease associated genes are set in bold.

**Figure 7**
Characterization of PDX1 binding in patient-derived *PDX1*^P33T/+**pancreatic progenitors (PP1).** (A) Distribution of PDX1 binding sites among genomic features. PDX1^P33T/+ binds predominantly to intergenic, intronic and promoter regions. (B) Meta-genomic plot showing the enrichment of PDX1 at the transcriptional start sites (TSS) of its target genes displayed as binding sites per base pair (bp) per gene over the genomic regions of all RefSeq genes. (C) Most enriched motif detected by motif analysis resembles the known PDX1 consensus sequence and is identified in 71.3% of all PDX1-bound sequences. (D) Average ChIP-seq Signal of H3K27ac (blue) and PDX1 (red) at PDX1 binding sites shows enrichment of H3K27ac at PDX1-bound sites. (E) Venn diagram showing the overlap of PDX1-binding sites in XM001 PPs and *PDX1*^P33T/+ PPs. (F) Heatmap of PDX1 ChIP-seq signal at all PDX1 binding sites in XM001 and *PDX1*^P33T/+ PPs, showing high resemblance of PDX1 binding in these cells. (G) ChIP-seq data tracks showing the enrichment of H3K27ac (blue) and PDX1 (red) at the loci of important pancreatic genes.

**Figure 8**
mRNA profiles of patient-derived *PDX1*^P33T/+**pancreatic progenitors (PP1).** (A) MA plot showing the mean log₂ expression against the log₂-fold change of the microarray data obtained from XM001 iPSCs and PPs. Genes with significantly different expression (log₂ fold change ≥ 1 and adjusted p-value ≤ 0.1) are drawn in color. Yellow depicts increased expression in PPs, whereas brown depicts increased expression in iPSCs. (B) Bar graph of p-values from pathway enrichment analysis, showing selected GO terms and KEGG and Reactome pathways from differentially expressed genes. (C) Heatmap of differentially expressed genes between patient-derived *PDX1*^P33T/+ and XM001 control PPs. (D) Heat map and clustering showing consistently deregulated genes in patients *PDX1*^P33T/+ and isogenic *PDX1*^P33T/P33T PPs.

**figs1**
**Suppl. Figure 1. Generation of patient-derived iPSC lines.** (A) An overview of the PDX1 protein structure. (B) The PDX1 protein alignment in different species. (C) Scheme shows the reprogramming factors for the generation of iPSCs.

**figs2**
Suppl. Figure 2. Characterization of *PDX1*^P33T/+and *PDX1*^C18R/+**mutant iPSCs differentiated towards the endoderm stage.** (A) Representative immunofluorescence staining for SOX17 in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the endoderm stage. Scale bar indicates 100 μm. (B) Representative FACS plots for SOX17⁺ cells in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the endoderm stage. (C) FACS quantification of the percentage of total SOX17⁺ cells in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the endoderm stage (n = 3).

**figs3**
Suppl. Figure 3. Characterization of *PDX1*^P33T/+and *PDX1*^C18R/+**mutant iPSCs differentiated towards the early pancreatic progenitors (PP1).** (A) Representative immunofluorescence staining for PDX1 in the XM001, *PDX1*^P33T/+ and *PDX1*^C18R/+ cells at the PP1 stage. Scale bar indicates 75 μm. (B) Representative FACS plots for PDX1⁺ cells in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the PP1 stage. (C) FACS quantification of the percentage of PDX1⁺ cells in XM001, *PDX1*^P33T/+ and *PDX1*^C18R/+ cells at PP1 stage (n = 3). (D) Representative immunoblot of PDX1 expression from XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the PP1 stage. (E) Median Fluorescence Intensity (MFI) quantification for XM001 and *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the PP1 stage stained with PDX1 antibody (n = 3).

**figs4**
Suppl. Figure 4. Characterization of *PDX1*^P33T/+and *PDX1*^C18R/+**mutant iPSCs differentiated towards the late pancreatic progenitors (PP2).** (A) Representative immunofluorescence staining for PDX1 and NKX6.1 in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the PP2 stage. Scale bars indicate 250 μm. (B) Representative FACS plots for PDX1⁺ and NKX6.1⁺cells in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the PP2 stage. (C) FACS quantification of the percentage of total PDX1⁺ and NKX6.1⁺cells in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the PP2 stage (n = 3).

**figs5**
Suppl. Figure 5. Cells carrying *PDX1*^P33T/+and *PDX1*^C18R/+**mutations are able to differentiate into β-like cells.** (A) Representative immunofluorescence staining for CPEP and SST in the XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the S7 stage. Scale bar indicates 50 μm. (B) Insulin secretion assay for XM001, *PDX1*^P33T/+, and *PDX1*^C18R/+ cells at the S7 stage (n = 3).

**figs6**
Suppl. Figure 6. Generation of the *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18Risogenic iPSC lines using CRISPR/Cas9 system. (A) Schematics of gene targeting strategy for creating *PDX1* mutations. Exons and introns are represented by boxes and lines, respectively, and sequences corresponding to the transactivation domain are indicated in blue. (B) Schematic of sgRNA targeting for the *PDX1*^+/− iPSC line. Top: sgRNA targeting site is highlighted in green. PAM is highlighted in red. The sequencing analysis shows the desired mutation. (C) Schematic of sgRNA targeting for the *PDX1*^P33T/P33T iPSC line. Top: sgRNA targeting site is highlighted in green. PAM is highlighted in red. ssODN sequence carrying mutation site A is highlighted in blue. The silent mutation is highlighted in yellow. The sequencing analysis shows the desired mutation. The black asterisk indicates the C>A switch. (D) Schematic of sgRNA targeting for the *PDX1*^C18R/C18R iPSC line. Top: sgRNA targeting site is highlighted in green. PAM is highlighted in red. ssODN sequence carrying mutation site C is highlighted in blue. The sequencing analysis shows the desired mutation. The black asterisk indicates the T>C switch.

**figs7**
Suppl. Figure 7. The *PDX1*^+/−, *PDX1*^P33T/P33Tand *PDX1*^C18R/C18Rmutant iPSCs are pluripotent *in vitro*. (A) *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R iPSCs have normal karyotype. (B) *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R iPSCs display typical morphological ESC-like characteristics and uniformly express several pluripotency markers. Scale bar indicates 75 μm.

**figs8**
Suppl. Figure 8. Characterization of *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18Rmutant iPSCs differentiated towards the endoderm stage. (A) Representative immunofluorescence staining for FOXA2 and SOX17 in XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the endoderm stage. Scale bar indicates 50 μm. (B) Representative FACS plots for FOXA2⁺ and SOX17⁺ cells in the XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the endoderm stage. (C) FACS quantification of the percentage of total FOXA2⁺ and SOX17⁺ cells in the XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the endoderm stage (n = 3).

**figs9**
**Suppl. Figure 9. PDX1 is important for the generation of glucose-responsive β-like cells**. (A) Representative immunofluorescence staining for CPEP and SST in the XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage. Scale bar indicates 50 μm. (B) C-peptide secretion assay for XM001, *PDX1*^+/−, *PDX1*^P33T/P33T, and *PDX1*^C18R/C18R cells at the S7 stage (n = 3).

**figs10**
**Suppl. Figure 10. Principal component analysis of PP1 cells.** (A) Principal component analysis PCA) of PPs derived from isogenic PDX1 mutant and control iPSCs. (B-C) Top 20 genes ranked by their contribution to PC1 and PC2, respectively.

**figs11**
Suppl. Figure 11. The PDX1 binding patterns are similar in patient-derived *PDX1*^P33T/+**and control PPs**. (A) Comparison of the distribution of accessible sites in XM001 and *PDX1*^P33T/+ PPs. (B) Comparison of the distances to the nearest TSSs of PDX1 binding sites in XM001 and *PDX1*^P33T/+ PPs. (C) Read count of H3K27ac at the 8970 and 8288 PDX1 binding sites in *PDX1*^P33T/+, XM001 PPs, respectively, and at three sets of 8970 and 8288 random sites of the same length distribution. H3K27ac is enriched >5 × at PDX1-bound sites compared to the random sites. P-value for all comparisons <2.2 × 10⁻¹⁶. (D) The comparison of the enrichment of PDX1 at the transcriptional start sites (TSS) of its target genes displayed as binding sites per base pair (bp) per gene over the genomic regions of all RefSeq genes in XM001 and *PDX1*^P33T/+ PPs. (E, H, K) ChIP-seq data tracks showing the enrichment of H3K27ac and PDX1 at the loci of important pancreatic genes in XM001 and *PDX1*^P33T/+ PPs. (F) The comparison of top motifs identified in PDX1 peaks. (G) The comparison of the H3K27ac signal around PDX1 binding sites. (I) Scatter plot comparing the log₂ read counts from PDX1 ChIP-seq in *PDX1*^P33T/+ and XM001. (J) Scatter plot comparing the log₂ read counts from H3K27ac ChIP-seq in *PDX1*^P33T/+ and XM001.

See this image and copyright information in PMC

Cited by

Transcriptome-Powered Pluripotent Stem Cell Differentiation for Regenerative Medicine.
Ogi DA, Jin S. Ogi DA, et al. Cells. 2023 May 22;12(10):1442. doi: 10.3390/cells12101442. Cells. 2023. PMID: 37408278 Free PMC article. Review.
What Do We Know about Neonatal Diabetes caused by PDX1 Mutations?
de Souza RB, Cabello PH, Rosado EL, Junior MC, de Medeiros Abreu G. de Souza RB, et al. Curr Diabetes Rev. 2024;21(1):e290124226471. doi: 10.2174/0115733998265866231204070606. Curr Diabetes Rev. 2024. PMID: 38299270 Review.
The Role of ER Stress in Diabetes: Exploring Pathological Mechanisms Using Wolfram Syndrome.
Morikawa S, Urano F. Morikawa S, et al. Int J Mol Sci. 2022 Dec 23;24(1):230. doi: 10.3390/ijms24010230. Int J Mol Sci. 2022. PMID: 36613674 Free PMC article. Review.
Dynamic regulation of pancreatic β cell function and gene expression by the SND1 coregulator in vitro.
Kanojia S, Davidson RK, Conley JM, Xu J, Osmulski M, Sims EK, Ren H, Spaeth JM. Kanojia S, et al. Islets. 2023 Dec 31;15(1):2267725. doi: 10.1080/19382014.2023.2267725. Epub 2023 Oct 15. Islets. 2023. PMID: 37838950 Free PMC article.
Gene-edited human stem cell-derived β cells from a patient with monogenic diabetes reverse preexisting diabetes in mice.
Maxwell KG, Augsornworawat P, Velazco-Cruz L, Kim MH, Asada R, Hogrebe NJ, Morikawa S, Urano F, Millman JR. Maxwell KG, et al. Sci Transl Med. 2020 Apr 22;12(540):eaax9106. doi: 10.1126/scitranslmed.aax9106. Sci Transl Med. 2020. PMID: 32321868 Free PMC article.

See all "Cited by" articles

References

1. Ahlqvist E., Storm P., Käräjämäki A., Martinell M., Dorkhan M., Carlsson A. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. The Lancet Diabetes and Endocrinology. 2018;6(5):361–369. - PubMed
1. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37(Supplement_1):S81–S90. - PubMed
1. Hattersley A.T., Patel K.A. Precision diabetes: learning from monogenic diabetes. Diabetologia. 2017:769–777. - PMC - PubMed
1. Staffers D.A., Ferrer J., Clarke W.L., Habener J.F. Early-onset type-ll diabetes mellitus (MODY4) linked to IPF1. Nature Genetics. 1997;17(2):138–139. - PubMed
1. Heuvel-Borsboom H., de Valk H.W., Losekoot M., Westerink J. Maturity onset diabetes of the young: seek and you will find. The Netherlands Journal of Medicine. 2016:193–200. - PubMed

Publication types

Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Substances

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

LinkOut - more resources

Full Text Sources
Medical
- MedlinePlus Health Information
Molecular Biology Databases
- NIAID Data Ecosystem - Find datasets on Infectious and Immune-mediated Diseases
Miscellaneous
- NCI CPTAC Assay Portal

[1] Ahlqvist E., Storm P., Käräjämäki A., Martinell M., Dorkhan M., Carlsson A. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. The Lancet Diabetes and Endocrinology. 2018;6(5):361–369. - PubMed

[2] Ahlqvist E., Storm P., Käräjämäki A., Martinell M., Dorkhan M., Carlsson A. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. The Lancet Diabetes and Endocrinology. 2018;6(5):361–369. - PubMed

[3] Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37(Supplement_1):S81–S90. - PubMed

[4] Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37(Supplement_1):S81–S90. - PubMed

[5] Hattersley A.T., Patel K.A. Precision diabetes: learning from monogenic diabetes. Diabetologia. 2017:769–777. - PMC - PubMed

[6] Hattersley A.T., Patel K.A. Precision diabetes: learning from monogenic diabetes. Diabetologia. 2017:769–777. - PMC - PubMed

[7] Staffers D.A., Ferrer J., Clarke W.L., Habener J.F. Early-onset type-ll diabetes mellitus (MODY4) linked to IPF1. Nature Genetics. 1997;17(2):138–139. - PubMed

[8] Staffers D.A., Ferrer J., Clarke W.L., Habener J.F. Early-onset type-ll diabetes mellitus (MODY4) linked to IPF1. Nature Genetics. 1997;17(2):138–139. - PubMed

[9] Heuvel-Borsboom H., de Valk H.W., Losekoot M., Westerink J. Maturity onset diabetes of the young: seek and you will find. The Netherlands Journal of Medicine. 2016:193–200. - PubMed

[10] Heuvel-Borsboom H., de Valk H.W., Losekoot M., Westerink J. Maturity onset diabetes of the young: seek and you will find. The Netherlands Journal of Medicine. 2016:193–200. - PubMed

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Point mutations in the PDX1 transactivation domain impair human β-cell development and function

Affiliations

Point mutations in the PDX1 transactivation domain impair human β-cell development and function

Authors

Affiliations

Abstract

Figures

Similar articles

Cited by

References

Publication types

MeSH terms

Substances

LinkOut - more resources

Full Text Sources

Medical

Molecular Biology Databases

Miscellaneous

Abstract

Figures

Similar articles

Cited by

References

Publication types

MeSH terms

Substances

Related information

LinkOut - more resources

Full Text Sources

Medical

Molecular Biology Databases

Miscellaneous