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7q11.23 dosage-dependent dysregulation in human pluripotent stem cells affects transcriptional programs in disease-relevant lineages

Nature Genetics volume 47, pages 132–141 (2015)Cite this article

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Abstract

Cell reprogramming promises to make characterization of the impact of human genetic variation on health and disease experimentally tractable by enabling the bridging of genotypes to phenotypes in developmentally relevant human cell lineages. Here we apply this paradigm to two disorders caused by symmetrical copy number variations of 7q11.23, which display a striking combination of shared and symmetrically opposite phenotypes—Williams-Beuren syndrome and 7q-microduplication syndrome. Through analysis of transgene-free patient-derived induced pluripotent stem cells and their differentiated derivatives, we find that 7q11.23 dosage imbalance disrupts transcriptional circuits in disease-relevant pathways beginning in the pluripotent state. These alterations are then selectively amplified upon differentiation of the pluripotent cells into disease-relevant lineages. A considerable proportion of this transcriptional dysregulation is specifically caused by dosage imbalances in GTF2I, which encodes a key transcription factor at 7q11.23 that is associated with the LSD1 repressive chromatin complex and silences its dosage-sensitive targets.

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Figure 1: Patient cohort and expression of WBS chromosome region (WBSCR) genes according to genotype.
Figure 2: 7q11.23 CNV-dependent and GTF2I-specific transcriptional dysregulation.
Figure 3: GTF2I protein complex and genome-wide occupancy.
Figure 4: GTF2I represses BEND4 in a dosage- and LSD1-dependent manner.
Figure 5: Transcriptional dysregulation in iPSC-derived disease-relevant lineages.
Figure 6: Lineage-specific retention of iPSC transcriptional dysregulation.

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Change history

  • 09 January 2015

    In the version of this article initially published online, GTF1I knockdown was incorrectly referred to in the legend for Figure 4c. GTF2I is the correct shRNA target in this experiment. The error has been corrected for the print, PDF and HTML versions of this article.

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Acknowledgements

We thank the AFSW (Associazione Famiglie Sindrome di Williams) and AISW (Associazione Italiana Sindrome di Williams) for agreeing to participate and making this study possible and the Genomic and Genetic Disorder Biobank, Galliera Genetic Bank and members of the Telethon Network of Genetic Biobanks (project numbers GTB12001G and GTB12001A), along with the EuroBioBank network, for providing us with specimens. We also thank scientists at the Drug Discovery Unit, Drug Development Program (DDU-DDP) of the European Institute of Oncology (IEO) for sharing with us the two LSD1 inhibitors used in this study; A. Bachi, A. Cattaneo and P. Soffiantini from the Mass Spectrometry service of the FIRC (Fondazione Italiana per la Ricerca sul Cancro) Institute of Molecular Oncology (IFOM); F. Pisati for processing of the teratomas; P. Andrews (University of Sheffield) for sharing two control iPSC lines (CTL2-C1 and CTL2-C2; reprogrammed from CRL-2429 fibroblasts); G. Mostoslavsky and the Center for Regenerative Medicine of Boston University for sharing the BU1Cr3-1 line; G. Barbagiovanni for help with FACS profiling and analysis; and L. Marelli along with all other members of the Testa laboratory for discussion. This work was funded by the European Research Council (consolidator grant number 616441-DISEASEAVATARS to G.T.), the Italian Ministry of Health (Ricerca Corrente to G.T. and G.M. and Bando Giovani Ricercatori 2008 and 2009 to G.T.), the EPIGEN Flagship Project of the Italian National Research Council (G.T.), the Jerome-Lejeune Foundation (G.T. and G.M.), the ERA-NET Neuron Program (G.T.), the Umberto Veronesi Foundation (S.A. and G.D.) and the Federation of European Biochemical Societies (FEBS; fellowship awarded to A.A. to work in the laboratory of G.T.).

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Author notes

  1. Antonio Adamo, Sina Atashpaz and Pierre-Luc Germain: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Experimental Oncology, European Institute of Oncology (Istituto di Ricovero e Cura a Carattere Scientifico, IRCCS), Milan, Italy

    Antonio Adamo, Sina Atashpaz, Pierre-Luc Germain, Matteo Zanella, Giuseppe D'Agostino, Veronica Albertin, Giancarlo Pruneri & Giuseppe Testa

  2. Lieber Institute for Brain Development, Baltimore, Maryland, USA

    Josh Chenoweth & Ronald McKay

  3. Medical Genetics Unit, IRCCS Casa Sollievo della Sofferenza Hospital, San Giovanni Rotondo, Italy

    Lucia Micale, Carmela Fusco, Bartolomeo Augello, Orazio Palumbo, Massimo Carella & Giuseppe Merla

  4. Department of Biomedical Sciences, University of Sheffield, Sheffield, UK

    Christian Unger

  5. Stemgent, Cambridge, Massachusetts, USA

    Brad Hamilton

  6. Medical Genetics Unit, Hospital Santa Maria della Misericordia, University of Perugia, Perugia, Italy

    Emilio Donti & Paolo Prontera

  7. Unità Operativa Semplice (UOS) Genetica Clinica Pediatrica, Fondazione Monza e Brianza per il Bambino e la sua Mamma (Fondazione MBBM), Azienda Ospedaliera San Gerardo, Monza, Italy

    Angelo Selicorni

  8. Department of Pediatrics, University of Turin, Turin, Italy

    Elisa Biamino

  9. Department of Health Sciences, University of Milan, Milan, Italy

    Giuseppe Testa

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  1. Antonio Adamo
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Contributions

S.A. initiated this project and set up human iPSC reprogramming and culture, including mRNA-based reprogramming. S.A. and A.A. reprogrammed the lines presented in this study. A.A., S.A., G.D. and M.Z. cultured and characterized iPSC lines and profiled transcriptomes. A.A. performed the biochemical characterization of the GTF2I complex and GTF2I and LSD1 ChIP-seq. A.A. performed the Nanostring experiment. A.A. and V.A. generated the GTF2I RNAi lines. S.A. established human iPSC differentiation into the cortical neural and neural crest lineages. S.A. and A.A. differentiated human iPSCs into cortical neural progenitors. S.A. analyzed NPCs and NCSCs by microarray. S.A. and M.Z. differentiated human iPSCs into NCSCs and MSCs. P.-L.G. performed the computational analysis for the microarray, Nanostring, RNA-seq and ChIP-seq data sets. P.-L.G. created the WikiWilliams-7qGeneBase web platform. G.M. organized the recruitment of patients, including molecular diagnostics and derivation of fibroblast cultures (with L.M., C.F. and B.A.). O.P., M.C. and G.M. performed aCGH analysis. G.P. performed histopathological analysis of teratomas. A.S. diagnosed and recruited patient AtWBS1, E.B. diagnosed and recruited patient WBS4, and P.P. and E.D. diagnosed and recruited patient 7dupASD1. R.M. and J.C. performed RNA-seq on a subset of samples. C.U. provided two control iPSC lines. B.H. provided mRNA reprogramming kits and expertise. P.-L.G., S.A., A.A. and G.T. wrote the manuscript. G.T. conceived, designed and supervised the study.

Corresponding author

Correspondence to Giuseppe Testa.

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Competing interests

B.H. is the director of research and development for Stemgent and Asterand. All other authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 iPSC line derivation.

(a) Schematic representation of mRNA-mediated reprogramming. The scale bar represents 400 μm. (b) GFP tracking of the mesenchymal-to-epithelial transition during reprogramming. The scale bar represents 50 μm. (c) For each genetic condition, expression of ALP by immunohistochemistry, immunofluorescence for pluripotency markers and staining of three iPSC-derived teratomas expressing markers specific for the three germ layers (right) are shown. The scale bar represents 400 μm. (d) Nanostring measurements for pluripotency markers. (e) Principal-component analysis of the published data comparing iPSCs, IVF-derived hESCs and somatic cell nuclear transfer–derived hESCs (SCNT-hESCs)18. Plotted are the first components able to distinguish, in the published data (after trimmed mean of M values normalization with ours), between iPSCs and SCNT-hESCs. Although our lines span the spectrum of variation on these components, most of them side with SCNT-hESCs and IVF-hESCs.

ALP, alkaline phosphatase; H&E, hematoxylin and eosin; DES, desmin; CK, cytokeratin.

Supplementary Figure 2 Expression of genes of the WBSCR in iPSCs.

(a) Expression of genes included in and directly flanking the WBSCR rearrangement as measured by RNA-seq (see Nanostring validation in Fig. 1c). The order of genes reflects their relative chromosomal position, and the horizontal colored bars indicate which genes are included in the CNVs. (b–d) Protein blot (b) and densitometry analyses (c,d) of BAZ1B and GTF2I protein levels in a representative subset of iPSC lines. Changes in GTF2I protein levels are statistically significant according to a two-tailed t test (*p<0.05, **P < 0.01); differences in BAZ1B protein levels, although showing a clear trend, are not statistically significant in this assay.

Supplementary Figure 3 Transcriptional profiling of patient-derived and control iPSCs.

(a–c) Top most-specific GO biological processes enriched among DEGs between control versus 7dupASD (a), control versus WBS (b), and WBS versus 7dupASD (c). (d) Top most-specific enrichments for GO biological processes among the union of DEGs when excluding the external control lines from the analysis.

Supplementary Figure 4 Genes differentially expressed in a symmetrical manner in WBS and 7dupASD iPSCs.

Supplementary Figure 5 Comparison of different antibodies assessed by ChIP-seq and immunoprecipitation assays.

(a) Protein blot validation of the immunoprecipitation efficiency of two different GTF2I antibodies in a control iPSC line. (b) Enrichment plot showing the distribution of reads across the genome; the samples using the Bethyl antibodies have a distinctively greater degree of enrichment compared with the other samples. (c) Most gene targets identified with the Bethyl antibody are also identified with the other antibodies. Importantly, nearly all core targets (i.e., genes with a high-confidence peak across all control and 7dupASD samples) are identified by all three antibodies. (d) ChIP-qPCR validation of GTF2I targets shown as enrichment over 0.05% total input. EOMES and SNAP25 promoters have been used as negative controls.

Supplementary Figure 6 Characterization of NCSC and MSC lines derived from WBS, AtWBS, 7dupASD and control iPSC lines.

NCSC (a) and MSC (b) phase-contrast microscopy shows a similar morphology across the four genotypes. The scale bar represents 400 μm. (c) Immunofluorescence analysis indicates positivity for two NCSC markers (HNK1 and NGFR) in a representative iPSC-derived NCSC line. The scale bar represents 50 μm. (d,e) Flow cytometry analysis indicates a high percentage of HNK1-NGFR and CD73-CD44 double-positive cells in, respectively, NCSC (d) and MSC (e) lines. (f) Plot of RNA-seq expression levels of genes included in the WBSCR at the MSC stage. For better visualization, genes were separated into low/medium (left) and high (right) expression.

Supplementary Figure 7 Characterization of DEGs found in both iPSCs and MSCs.

(a) MSC DEGs that are also DEGs in iPSCs have higher expression. (b) The proportion of overlapping DEGs in MSCs does not correlate with expression levels in iPSCs. (c) The vast majority of DEGs in iPSCs are downregulated in differentiated MSCs, and the overlap between iPSC and MSC DEGs increases with greater fold changes from iPSCs to MSCs.

Supplementary Figure 8 Grafical representation of the core results of the study and their integration into the WikiWilliams/7q11GB database.

(a) Graphical representation of the lineage-specific retention of DEGs. (b) Schematic representation of the data gathered in the open-access WikiWilliams/7qGB.

Supplementary Figure 9 The WikiWilliams/7q11GB web platform.

Representative screenshot of the WikiWilliams/7q11GB database as it appears to users searching for a specific gene of interest. All transcriptomic and genomic data presented in this paper as well as previously published data sets can be easily interrogated in a multilayered format integrated with several biological databases.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–9 and Supplementary Tables 1 and 10 (PDF 3864 kb)

Supplementary Table 2

Summary of the copy number variations (CNVs) identified through aCGH. (XLS 34 kb)

Supplementary Table 3

GO biological processes enriched among linear DEGs, defined as mean (control) within a 20–80% range between mean (WBS) and mean (7dupASD), and abs(Pearson correlation) > 0.5 with WBS copy number. (XLSX 117 kb)

Supplementary Table 4

Proportion of DEGs, in each comparison between genotypes, attributable to GTF2I. (XLSX 10 kb)

Supplementary Table 5

GTF2I interactors identified through mass spectrometry analysis. (XLSX 9 kb)

Supplementary Table 6

GTF2I target classification according to ChIP analysis. (XLSX 48 kb)

Supplementary Table 7

GO biological processes enriched among the union of NCSC DEGs. (XLSX 164 kb)

Supplementary Table 8

Comparison of GO biological processes enriched among MSC DEGs and in MSC shuffling. (XLSX 124 kb)

Supplementary Table 9

List of performed experiments (Nat. Biotechnol. 25, 681–686, 2007). (XLSX 13 kb)

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Adamo, A., Atashpaz, S., Germain, PL. et al. 7q11.23 dosage-dependent dysregulation in human pluripotent stem cells affects transcriptional programs in disease-relevant lineages. Nat Genet 47, 132–141 (2015). https://doi.org/10.1038/ng.3169

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