Pluripotent stem cells are increasingly used to model different aspects of embryogenesis and organ formation1. Despite recent advances in in vitro induction of major mesodermal lineages and cell types2,3, experimental model systems that can recapitulate more complex features of human mesoderm development and patterning are largely missing. Here we used induced pluripotent stem cells for the stepwise in vitro induction of presomitic mesoderm and its derivatives to model distinct aspects of human somitogenesis. We focused initially on modelling the human segmentation clock, a major biological concept believed to underlie the rhythmic and controlled emergence of somites, which give rise to the segmental pattern of the vertebrate axial skeleton. We observed oscillatory expression of core segmentation clock genes, including HES7 and DKK1, determined the period of the human segmentation clock to be around five hours, and demonstrated the presence of dynamic travelling-wave-like gene expression in in vitro-induced human presomitic mesoderm. Furthermore, we identified and compared oscillatory genes in human and mouse presomitic mesoderm derived from pluripotent stem cells, which revealed species-specific and shared molecular components and pathways associated with the putative mouse and human segmentation clocks. Using CRISPR–Cas9-based genome editing technology, we then targeted genes for which mutations in patients with segmentation defects of the vertebrae, such as spondylocostal dysostosis, have been reported (HES7, LFNG, DLL3 and MESP2). Subsequent analysis of patient-like and patient-derived induced pluripotent stem cells revealed gene-specific alterations in oscillation, synchronization or differentiation properties. Our findings provide insights into the human segmentation clock as well as diseases associated with human axial skeletogenesis.
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All RNA sequencing data used for this study have been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE116935. SNP array data in the current publication have been deposited in and are available upon application from the dbGaP database under accession number phs001975.v1.p1 and their use is limited to health, medical and biomedical purposes. Source Data for Figs. 1–4 and Extended Data Figs. 1, 2, 5–12 are available in the online version of the paper.
Computational codes and scripts used in this study are available at GitHub (https://github.com/mebisuya/SegmentationClock) and upon request from the corresponding authors.
McCauley, H. A. & Wells, J. M. Pluripotent stem cell-derived organoids: using principles of developmental biology to grow human tissues in a dish. Development 144, 958–962 (2017).
Chal, J. et al. Differentiation of pluripotent stem cells to muscle fiber to model Duchenne muscular dystrophy. Nat. Biotechnol. 33, 962–969 (2015).
Lee, J. H., Protze, S. I., Laksman, Z., Backx, P. H. & Keller, G. M. Human pluripotent stem cell-derived atrial and ventricular cardiomyocytes develop from distinct mesoderm populations. Cell Stem Cell 21, 179–194 (2017).
Loh, K. M. et al. Mapping the pairwise choices leading from pluripotency to human bone, heart, and other mesoderm cell types. Cell 166, 451–467 (2016).
Xi, H. et al. In vivo human somitogenesis guides somite development from hPSCs. Cell Rep. 18, 1573–1585 (2017).
Pourquié, O. Vertebrate somitogenesis. Annu. Rev. Cell Dev. Biol. 17, 311–350 (2001).
Hofmann, M. et al. WNT signaling, in synergy with T/TBX6, controls Notch signaling by regulating Dll1 expression in the presomitic mesoderm of mouse embryos. Genes Dev. 18, 2712–2717 (2004).
Bessho, Y. et al. Dynamic expression and essential functions of Hes7 in somite segmentation. Genes Dev. 15, 2642–2647 (2001).
Turnpenny, P. D. et al. Abnormal vertebral segmentation and the notch signaling pathway in man. Dev. Dyn. 236, 1456–1474 (2007).
Hubaud, A. & Pourquié, O. Signalling dynamics in vertebrate segmentation. Nat. Rev. Mol. Cell Biol. 15, 709–721 (2014).
William, D. A. et al. Identification of oscillatory genes in somitogenesis from functional genomic analysis of a human mesenchymal stem cell model. Dev. Biol. 305, 172–186 (2007).
Lauschke, V. M., Tsiairis, C. D., François, P. & Aulehla, A. Scaling of embryonic patterning based on phase-gradient encoding. Nature 493, 101–105 (2013).
Matsumiya, M., Tomita, T., Yoshioka-Kobayashi, K., Isomura, A. & Kageyama, R. ES cell-derived presomitic mesoderm-like tissues for analysis of synchronized oscillations in the segmentation clock. Development 145, dev156836 (2018).
Wahl, M. B., Deng, C., Lewandoski, M. & Pourquié, O. FGF signaling acts upstream of the NOTCH and WNT signaling pathways to control segmentation clock oscillations in mouse somitogenesis. Development 134, 4033–4041 (2007).
Burgess, R., Rawls, A., Brown, D., Bradley, A. & Olson, E. N. Requirement of the paraxis gene for somite formation and musculoskeletal patterning. Nature 384, 570–573 (1996).
Fleming, A., Kishida, M. G., Kimmel, C. B. & Keynes, R. J. Building the backbone: the development and evolution of vertebral patterning. Development 142, 1733–1744 (2015).
Dequéant, M. L. et al. A complex oscillating network of signaling genes underlies the mouse segmentation clock. Science 314, 1595–1598 (2006).
Hubaud, A., Regev, I., Mahadevan, L. & Pourquie, O. Excitable dynamics and Yap-dependent mechanical cues drive the segmentation clock. Cell 171, 668–682 (2017).
Aulehla, A. et al. A β-catenin gradient links the clock and wavefront systems in mouse embryo segmentation. Nat. Cell Biol. 10, 186–193 (2008).
Sparrow, D. B. et al. Mutation of the LUNATIC FRINGE gene in humans causes spondylocostal dysostosis with a severe vertebral phenotype. Am. J. Hum. Genet. 78, 28–37 (2006).
Okubo, Y. et al. Lfng regulates the synchronized oscillation of the mouse segmentation clock via trans-repression of Notch signalling. Nat. Commun. 3, 1141 (2012).
Huggins, I. J. et al. The WNT target SP5 negatively regulates WNT transcriptional programs in human pluripotent stem cells. Nat. Commun. 8, 1034 (2017).
Pedersen, L., Jensen, M. H. & Krishna, S. Dickkopf1—a new player in modelling the Wnt pathway. PLoS ONE 6, e25550 (2011).
Sonnen, K. F. et al. Modulation of phase shift between Wnt and Notch signaling oscillations controls mesoderm segmentation. PLoS ONE 172, 1079–1090 (2018).
Bulman, M. P. et al. Mutations in the human Delta homologue, DLL3, cause axial skeletal defects in spondylocostal dysostosis. Nat. Genet. 24, 438–441 (2000).
Sparrow, D. B., Guillén-Navarro, E., Fatkin, D. & Dunwoodie, S. L. Mutation of HAIRY-AND-ENHANCER-OF-SPLIT-7 in humans causes spondylocostal dysostosis. Hum. Mol. Genet. 17, 3761–3766 (2008).
Whittock, N. V. et al. Mutated MESP2 causes spondylocostal dysostosis in humans. Am. J. Hum. Genet. 74, 1249–1254 (2004).
Niwa, Y. et al. The initiation and propagation of Hes7 oscillation are cooperatively regulated by Fgf and Notch signaling in the somite segmentation clock. Dev. Cell 13, 298–304 (2007).
Kusumi, K. et al. Dll3 pudgy mutation differentially disrupts dynamic expression of somite genes. Genesis 39, 115–121 (2004).
Chen, J., Kang, L. & Zhang, N. Negative feedback loop formed by Lunatic fringe and Hes7 controls their oscillatory expression during somitogenesis. Genesis 43, 196–204 (2005).
Cornier, A. S. et al. Mutations in the MESP2 gene cause spondylothoracic dysostosis/Jarcho–Levin syndrome. Am. J. Hum. Genet. 82, 1334–1341 (2008).
Kim, S. I. et al. Microhomology-assisted scarless genome editing in human iPSCs. Nat. Commun. 9, 939 (2018).
Lackmann, M. et al. Distinct subdomains of the EphA3 receptor mediate ligand binding and receptor dimerization. J. Biol. Chem. 273, 20228–20237 (1998).
McInerney-Leo, A. M. et al. Compound heterozygous mutations in RIPPLY2 associated with vertebral segmentation defects. Hum. Mol. Genet. 24, 1234–1242 (2015).
Bouman, A. et al. Homozygous DMRT2 variant associates with severe rib malformations in a newborn. Am. J. Med. Genet. A. 176, 1216–1221 (2018).
Turnpenny, P. D. et al. Novel mutations in DLL3, a somitogenesis gene encoding a ligand for the Notch signalling pathway, cause a consistent pattern of abnormal vertebral segmentation in spondylocostal dysostosis. J. Med. Genet. 40, 333–339 (2003).
Nakagawa, M. et al. A novel efficient feeder-free culture system for the derivation of human induced pluripotent stem cells. Sci. Rep. 4, 3594 (2015).
Takahashi, K. et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131, 861–872 (2007).
Wataya, T. et al. Minimization of exogenous signals in ES cell culture induces rostral hypothalamic differentiation. Proc. Natl Acad. Sci. USA 105, 11796–11801 (2008).
Yamanaka, Y., Uemura, M. & Alev, C. Stepwise in vitro induction of human somitic mesoderm and its derivatives. Protoc. Exch. https://doi.org/10.21203/rs.2.22919/v1 (2020).
Zhao, J. et al. Small molecule-directed specification of sclerotome-like chondroprogenitors and induction of a somitic chondrogenesis program from embryonic stem cells. Development 141, 3848–3858 (2014).
Yamashita, A. et al. Generation of scaffoldless hyaline cartilaginous tissue from human iPSCs. Stem Cell Reports 4, 404–418 (2015).
Chal, J. et al. Generation of human muscle fibers and satellite-like cells from human pluripotent stem cells in vitro. Nat. Protoc. 11, 1833–1850 (2016).
Mandegar, M. A. et al. CRISPR interference efficiently induces specific and reversible gene silencing in human iPSCs. Cell Stem Cell 18, 541–553 (2016).
Li, X. et al. Generation of destabilized green fluorescent protein as a transcription reporter. J. Biol. Chem. 273, 34970–34975 (1998).
Niwa, Y. et al. Different types of oscillations in Notch and Fgf signaling regulate the spatiotemporal periodicity of somitogenesis. Genes Dev. 25, 1115–1120 (2011).
Nakajima, T. et al. Modeling human somite development and fibrodysplasia ossificans progressiva with induced pluripotent stem cells. Development 145, dev165431 (2018).
Isomura, A., Ogushi, F., Kori, H. & Kageyama, R. Optogenetic perturbation and bioluminescence imaging to analyze cell-to-cell transfer of oscillatory information. Genes Dev. 31, 524–535 (2017).
Sugimoto, M. et al. A simple and robust method for establishing homogeneous mouse epiblast stem cell lines by Wnt inhibition. Stem Cell Reports 4, 744–757 (2015).
Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).
Trapnell, C. et al. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat. Biotechnol. 31, 46–53 (2013).
Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).
McCarthy, D. J., Chen, Y. & Smyth, G. K. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 40, 4288–4297 (2012).
Yang, R. & Su, Z. Analyzing circadian expression data by harmonic regression based on autoregressive spectral estimation. Bioinformatics 26, i168–i174 (2010).
Huang, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protocols 4, 44–57 (2009).
Ran, F. A. et al. Genome engineering using the CRISPR–Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).
Guo, L. et al. Novel and recurrent XYLT1 mutations in two Turkish families with Desbuquois dysplasia, type 2. J. Hum. Genet. 62, 447–451 (2017).
Guo, L. et al. Identification of a novel LRRK1 mutation in a family with osteosclerotic metaphyseal dysplasia. J. Hum. Genet. 62, 437–441 (2017).
McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).
Bock, C. et al. Reference maps of human ES and iPS cell variation enable high-throughput characterization of pluripotent cell lines. Cell 144, 439–452 (2011).
Gogarten, S. M. et al. GWASTools: an R/Bioconductor package for quality control and analysis of genome-wide association studies. Bioinformatics 28, 3329–3331 (2012).
The authors thank B. McIntyre and P. O’Neill for critical reading of the manuscript; K. Mitsunaga for help with FACS analysis; Y. Ashida for help with development of human spheroid PSM-induction protocol; H. Hayashi for help with development of mouse PSM protocol; J. Asahira for help with RNA-seq experiments; A. Yamashita for help with 3D chondrogenic induction experiments; M. Shibata and T. Nakajima for help with development of one-step PSM-induction protocol; M. Ohno and S. Nishimura for help with iPS cell quality control and validation; members of the Kageyama laboratory, K. Yoshioka-Kobayashi and A. Isomura for help with Hilbert transformation and M. Matsumiya for help with removing spike noise from images; the CiRA Genome Evaluation Group, in particular H. Dohi, F. Kitaoka, M. Nomura, T. Takahashi, M. Umekage and N. Takasu for performing SNP array analysis. This work was supported by the CiRA Fellowship Program of Challenge to C.A.; Naito Foundation Research Grant to C.A.; Grant-in-Aid for Challenging Exploratory Research (KAKENHI Number 16K15664) to C.A.; Grant-in-Aid for Scientific Research on Innovative Areas (KAKENHI Number 17H05777) to M.M.; Takeda Science Foundation Grant to M.E.; Japan Agency for Medical Research and Development (AMED) Grants Number 12103610 and 17935423 to M.K.S. for iPS cell generation and qualification, grant number JP19bm0804001 to K.W. for iPS cell gene editing and grant numbers JP18ek0109212 and 18ek0109280 to S.I. for genomic and exome studies of spondylocostal dysostosis, respectively; the Core Center for iPS Cell Research (AMED) to T.Y., K.W. and J.T. and the Acceleration Program for Intractable Disease Research Using Disease Specific iPS Cells (AMED) to K.W., J.T. and M.K.S.; the Kyoto University Hakubi Project to K.W.; the Cooperative Research Program (Joint Usage/Research Center Program) of the Institute for Frontier Life and Medical Sciences, Kyoto University to J.T., L.G and S.I.. ASHBi is supported by the World Premier International Research Center Initiative (WPI), MEXT, Japan.
The authors declare no competing interests.
Peer review information Nature thanks Helen M. Blau, Duncan Sparrow and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Heat map of gene expression levels in stepwise-induced human PSM and its derivatives (using iPS cell line 1231A3). FPKM values of each gene were normalized to the mean of all samples. The gene order is the same as in Fig. 1b. b, PCA plot of transcript expression levels in human PSM and derivatives of three independent experiments (1231A3), n = 3. Proposed RNA-seq-based developmental trajectory is shown in pink. c, RT–qPCR-based validation of RNA-seq results; data of four independent experiments with three technical replicates each using 201B7 are shown. Data are mean ± s.d., n = 4. Similar results were obtained for 1231A3 (data not shown). Open circles in some conditions indicate that there are less than four experiments because no Ct values for these samples were obtained after 45 cycles of PCR to calculate expression values. d, Representative flow cytometric evaluation of DLL1 and TBX6 (left) and DLL1 and brachyury (BRA) (right) expression at PSM stage (1231A3), n = 3. e, Representative expression of DLL1 at transcript level during in vitro differentiation (201B7). Data are mean ± s.d., n = 4. f, Representative expression of DLL1 at protein level, n = 3. Correlation of FACS data with RT–qPCR results (201B7) shown in e.
a, HES7 reporter activity in a 2D culture (the oscillation assay condition) and 3D spreading spheroid (the synchronization assay condition). Raw, detrended (± 100 min window) and phase signals are shown. For spheroids, the signal was averaged over all area or ROIs indicated by the red line. 2D culture data are same as Fig. 1g and part of 3D-spheroid culture data are same as Fig. 1h. Data of three independent experiments are shown. Schematic depiction of reporter construct is shown on top. b, Human segmentation clock period quantification based on detrended and instantaneous phase signals. The period was calculated as the average peak-to-peak interval using the 1st to 5th peaks. The measure of centre is mean, n = 3. c, Instantaneous phase-based kymograph of travelling-wave-like HES7 reporter activity in spheroid spreading assay shown in Fig. 1h. Representative data of three independent experiments are shown.
Extended Data Fig. 3 Characterization of induced human PSM-derivatives, somitic mesoderm, sclerotome and dermomyotome.
a, Representative immunofluorescence staining of PSM markers TBX6 and brachyury (BRA) and somitic mesoderm marker TCF15 at PSM stage, n = 3; entire wells (left) and magnified views of selected areas. b, Representative immunofluorescence staining of PSM markers TBX6 and BRA and somitic mesoderm marker TCF15 at stage, n = 3; entire wells (left) and magnified views of selected areas. Bottom, staining of segmentation marker MESP2 (alone or co-staining with TBX6). Scale bar, 100 μm. c, Representative immunofluorescence of dermomyotome markers (PAX7 and PRRX1) and sclerotome marker (FOXC2) at dermomyotome and sclerotome stages (201B7), n = 3; entire wells (left) and magnified views of selected areas (right). Staining of PAX7 (epithelial colonies) at dermomyotome and FOXC2 (mesenchymal colonies) at sclerotome stage. PRRX1 staining surrounding PAX7+ areas is specific to dermomyotome stage. Scale bar, 100 μm.
a, Assessment of in vivo bone- and cartilage-forming ability of human induced sclerotome. Subcutaneous transplantation of PSC-derived sclerotome stepwise-induced from healthy control or wild-type (1231A3) and luciferase-reporter iPS cell lines (625-D4 and 625-A4). Evaluation of transplanted cells using IVIS at two months after transplantation; injection sides are marked with dashed or coloured circles. Cartilage and bone-forming areas of wild-type iPS cell line (1231A3) marked by white arrows. b, Whole-mount images of wild-type sclerotome-derived in vivo cartilage and bone tissues isolated from transplanted mice 1 and 3. Explant isolated from mouse 2 is shown in d. Scale bar, 4 mm. c, Representative staining of in vitro human sclerotome-derived cartilage (from 3D chondrogenic induction) sections. Observed safranin O and type II collagen (COL2) signals are indicative of in vitro cartilage formation, n = 3. d, Representative whole-mount (top left) and histological staining of section (bottom left) of human induced sclerotome-derived in vivo cartilage and bone. Scale bar, 100 μm. Representative pentachrome staining of marked area reminiscent of in vivo human endochondral bone formation; n = 3. I, proliferative human cartilage; II, hypertrophic cartilage; III, ossifying cartilage and forming human bone. Scale bar, 100 μm. e, Representative sections and staining of area shown in d. Safranin O and COL2 staining in human in vivo sclerotome-derived cartilage areas; von Kossa and COL1 staining in ossifying cartilage and forming bone areas. Majority of cells contributing to cartilage or bone formation are HNA-positive and of human origin (right bottom); n = 3. Scale bar, 100 μm.
a, Evaluation of in vitro muscle induction from human induced dermomyotome. Myosin and sarcomeric α-actinin (SAA) staining of in vitro dermomyotome-derived skeletal muscle; representative images of entire well (left) and magnified areas (right); n = 3. Scale bar, 100 μm. b, Comparison of skeletal muscle induction of human iPS cell, and iPS cell-derived sclerotome and dermomyotome. Representative myosin heavy chain (MYH), myosin and sarcomeric α-actinin staining only apparent in dermomyotome-based skeletal muscle differentiation. Right, magnified areas; n = 3. c, Quantification of contracting colonies and GFP-positive foci of iPS cell-, sclerotome- and dermomyotome-derived human skeletal muscle. Calcium-reporter iPS cell line (Gen1C) was used in all cases. Measurements of total 18 view fields in 6 independent experiments. In box-and-whisker plots, the middle line represents median value, box edges represent 25th and 75th quartiles and error bars show extreme values. d, Representative quantification of calcium GFP-reporter activity in iPS cell, sclerotome and dermomyotome as readout of spontaneous contraction-mediated GFP signal in induced human skeletal muscle cells; n = 3.
a, Sampling of human oscillating PSM samples for RNA-seq. HES7 reporter activity was continuously monitored with one sample, and the other samples were frozen at each time point indicated in the graph. b, Three-dimensional synchronization (spheroid-spreading) assay following inhibition of FGF (PD173074, 100 nM), Notch (DAPT, 10 mM), and Wnt (XAV939, 10 mM) signalling pathways. The HES7 reporter signal was first averaged over all area, the background was subtracted and the signal was normalized to time 0. The background was defined as the average signal at time 0 over the 15 × 15-pixel area of the top left corner of the image. Representative graph of three independent experiments is shown. See also Supplementary Video 3. c, Average HES7 reporter intensity during 36–41 h (2,160–2,440 min) of inhibitor treatment. Data are mean ± s.d., n = 3; two-sided Dunnett’s test. *P < 0.05, **P < 0.01, ***P < 0.001. d, Additional validation of RNA-seq results by RT–qPCR for phase and antiphase oscillating genes showing specific oscillatory expression in human iPS cell-derived PSM but not in mouse EpiSC-derived PSM. Data are shown for two independent biological datasets with 16 samples each. See also Fig. 2c. e, RT–qPCR validation of phase and antiphase oscillating murine genes found to oscillate in mouse EpiSC-derived PSM. Same genes show oscillation in human in vitro PSM. f, RT–qPCR validation of phase and antiphase oscillating genes identified by RNA-seq in human induced PSM. These genes were also validated to show clear oscillation in mouse EpiSC-derived PSM. See also Fig. 2d. In e, f, mean values of three technical replicas of two independent experiments (Ex1 and Ex2) for each time point and sample set are shown.
a, Heat map of normalized gene expression levels for oscillating genes in mouse in vitro-derived PSM. RNA-seq results shown for two independent biological datasets with 16 samples each. Examples of identified phase and antiphase oscillating genes are highlighted on the right. Oscillating mouse genes marked in red and blue match with high- and low-stringency cut-off setting identified oscillating human induced-PSM genes, respectively. Unambiguously phase- or antiphase oscillating genes are highlighted on the left; solid and dotted black lines indicate unambiguous and ambiguous genes, respectively. See Supplementary Table 4 for complete list of identified high-stringency cut-off oscillating genes in mouse in vitro-derived PSM. See also Fig. 2 and Supplementary Table 2 for RNA-seq results of oscillating human segmentation clock genes identified in human iPS cell-derived PSM. b, Sampling of mouse oscillating PSM samples for RNA-seq. Hes7 reporter activity was continuously monitored with one sample, and the other samples were frozen at each time point indicated in the graph. c, RT–qPCR validation of identified mouse phase and antiphase oscillating genes. See also Fig. 2d and Extended Data Fig. 6e for validation of additional mouse oscillating genes. Mean values of three technical replicas of two independent experiments (Ex1 and Ex2) for each time point and sample set are shown. d, Results obtained for dual luciferase-reporter assay of HES7 reporter (NanoLuc) and DKK1 reporter (Luciferase2) in human PSC-derived PSM. The signal was detrended (± 2-h window) and normalized to the maximum oscillation peak. Representative graph of three independent experiments is shown. Top, schematic overview of reporter constructs. e, Schematic overview of 2D-oscillation and 3D-synchronization assays.
a, Overview of knockout reporter cell line generation for HES7, DLL3, LFNG and MESP2 genes. Positions of the sgRNAs used in this study are shown. sgRNAs were designed to target at or near regions of known pathogenic mutations, particularly those resulting in frameshifts and premature termination. Sequence analysis of iPS cell clones used in this study indicating insertion or deletion mutations generated by Cas9. Predicted effects on the protein sequence are listed below the sequence alignments. b, Damping rate of oscillation amplitude in knockout human PSMs. The signal of all area was averaged and detrended (± 100-min window). See also Fig. 3d for quantification of shown data, n = 3. c, Summary of results of oscillation and synchronization assays. See Fig. 3a–d for details. d, Flow cytometric evaluation of DLL1 expression at PSM stage of healthy control and knockout human iPS cell lines. Blue, isotype control; red, DLL1-APC. PSM induction efficiency is high in all analysed samples; slight reduction of DLL1 induction efficiency in LFNG-knockout cell lines. Representative results of three independent experiments of two different knockout lines for each gene are shown (HES7 KO #1 and #8, DLL3 KO #2 and #6, LFNG KO #2 and #12, and MESP2 KO #7 and #11); n = 3. e, Scatter plot of transcriptome analysis of wild-type and knockout cell lines at iPS cell and PSM stages. Positions of expression values for MESP2, DLL3, LFNG and HES7 are highlighted with coloured arrows. Data are averages of two biological replicates, n = 2.
Extended Data Fig. 9 Overview of HES7R25W mutant cell line generation and initial characterization of patient iPS cell lines SCDP1 and SCDP2.
a, Schematic overview of the stepwise HES7-targeting approach for ssODN-mediated recreation of HES7R25W mutant cell lines. The first round of CRISPR–Cas9 targeting with ssODN resulted in a compound heterozygous line with the desired c.73C>T base modification and a 5-bp deletion (c.70_74delCGCCG). The c.70_74delCGCCG deletion creates a new PAM site. In the second targeting step, the c.70_74delCGCCG allele was retargeted with a sgRNA specific to the deletion, and correction with the same ssODN resulted in a homozygous c.73C>T iPS cell line. b, Representative bright-field views of SCDP1 (SCDP1-A and SCDP1-F) and SCDP2 (SCDP2-A and SCDP2-E) iPS cell clones. Representative data of five independent experiments are shown. Scale bar, 500 μm. c, Normal karyotype (46, XX) in both clones of SCDP1 patient iPS cell line by chromosomal G-banding analysis. The data of passage 10 is shown. d, Expression of pluripotency markers OCT3/4 and NANOG in SCDP1 and SCDP2 clones compared with iPS cell line (201B7). Quantification of residual plasmid levels in SCDP1 and SCDP2 clones (right); mean value (horizontal bar) of three technical replicas for each of the four analysed clones are shown. e, FACS-based evaluation of differentiation capacity into three germ layers of healthy control (H9 hESC) and patient cell lines (SCDP1-A and SCDP1-F, SCDP2-A and SCDP2-E). Representative data of three independent experiments are shown; n = 3. f, Quantification of differentiation capacity of healthy control and patient cell lines into ectoderm, mesoderm and endoderm at the transcript level by TaqMan hPSC scorecard panel. Top, SCDP1-A and SCDP1-F; bottom, SCDP2-A and SCDP2-E. Same H9 hESC control data shown in both panels. Data of three independent experiments are shown; n = 3. g, X-ray and MRI images of a patient with SDV with a DLL3 mutation (donor of SCDP2 iPS cell clones). Radiological images were obtained at Meijo Hospital, Nagoya, Japan with patient consent. Black bars were added to anonymize the image. See Supplementary Note 1 for details of clinical and radiological features of the patient.
Extended Data Fig. 10 Analysis of patient and rescue iPS cell line-derived PSM and allele-specific gene correction of SCDP1 patient iPS cell lines.
a, Representative DLL1 expression in iPS cells (grey) and PSMs (red) derived from a patient with SCD with a compound mutation in MESP2 (SCDP1-A and SCDP1-F), a patient with SCD with a mutation in DLL3 (SCDP2-A and SCDP2-E) and corresponding isogenic rescue cell lines (SCDP1-resA1, SCDP1-resF3, SCDP2-resA12 and SCDP2-resE17). n = 3; data for SCDP1-A and SCDP2-E are also used for Fig. 4b. b, Three-dimensional synchronization assay of SCDP1 patient PSM. Representative kymograph of three independent experiments is shown. c, Representative measurement of HES7 reporter activity in PSM derived from SCDP1 patient cell line. After the spike noise was removed, the signal of the entire area was averaged. The signal was further detrended and normalized to the average (±100-min window). d, Top, representative genotype of patients with SCD and iPS cells (SCDP1) with compound heterozygous mutations in MESP2. Bottom, sequence of each haplotype from patient genomic DNA. Red triangle indicates a deletion. Black triangle indicates a single nucleotide variation. e, Schematic of the gene-targeting procedure for allele-specific correction of MESP2 mutations using MhAX. Details of the targeting and genotyping procedures are provided in g. f, Genotype of heterozygously corrected iPS cell subclones. 201B7 is included as a reference. Red triangle indicates a deletion. Black triangle indicates a single nucleotide variation. DNA sequencing was performed twice for each clone; n = 2. g, Detailed schematic of gene-correction strategy of SCDP1 patient iPS cell clones. Depicted are two mutant or corrected MESP2 alleles with coding and non-coding exons (grey and white), overlapping donor vector homology arms (HA-L and HA-R), engineered 51-bp microhomology (μ51, blue), inverted protospacers for cassette excision (ps1, green), genotyping primers (red arrows) and Southern blotting probes (black bars). Sequences of mutation-specific sgRNAs are shown below each mutant allele. The gene-targeted intermediate shows details of the CAG::mCherry-IRES-puro cassette used for enrichment. h, Southern blot analysis of targeted iPS cell clones. Samples marked with an asterisk were selected for cassette excision. i, Southern blot analysis of gene-corrected iPS cell clones following selection marker removal. Samples marked with an asterisk were selected for phenotyping (067-1-3, SCDP1-resA1; 067-2-5, SCDP1-resF2; 067-3-4 and SCDP1-resF3). Southern blots shown in h and i were performed once for two patient and rescue clones each. For gel source data of h and i see Supplementary Fig. 1. j, k, Resulting karyograms from SNP array analysis of SCDP1 patient iPS cell clone A (SCDP1-A) and corresponding rescued iPS cell line (SCDP1-resA1). l–n, Karyograms from SNP array analysis of iPS cell clone F (SCDP1-F) from a patient with SDV and corresponding rescued iPS cell lines (SCDP1-resF2/F3). No de novo CNVs were detected following gene editing and subcloning. These figures were created with Illumina Genome Viewer (v.1.9.0) on Illumina GenomeStudio v.2011.1 with Human:Build 37 genome.
a, Heat map of gene expression levels of transcripts differentially expressed in patient cell lines SCDP1-A and SCDP1-F, when compared to wild-type (201B7) and corrected rescue clones (SCDP1-resA (A1) and SCDP1-resF (F2 and F3)). Analysis covers all stages of stepwise PSM induction and differentiation and for MESP2-knockout cell lines all stages except primitive streak. For somitic mesoderm-stage data see Fig. 4d. b, RT–qPCR-based validation of additional candidates found via RNA-seq to be upregulated in SCDP1 patient cell lines at the somitic mesoderm stage. Data are mean ± s.d. from three independent experiments.
a, Representative genotype of cells from patients with SCD and iPS cells (SCDP2) with mutation in DLL3—201B7 is included as a reference. Red triangle indicates insertion. b, Schematic of the gene-targeting procedure for allele-specific correction of DLL3 mutation using MhAX. Details for the targeting and genotyping procedures are provided in d. The synonymous c.615C>G PAM blocking mutation is present only in the 3′ microhomology. c, Genotype of homozygously corrected iPS cell subclones (SCDP2-resA and SCDP2-resE). Black triangle indicates the synonymous blocking mutation. DNA sequencing performed twice for each clone; n = 2. d, Detailed schematic of gene-correction strategy of SCDP2 patient iPS cell clones. Depicted are mutant or corrected DLL3 alleles with coding and non-coding exons (grey and white), overlapping donor vector homology arms (HA-L and HA-R), engineered 30-bp microhomology (μ30, blue), inverted protospacers for cassette excision (ps1, green), genotyping primers (red arrows), and Southern blotting probes (black bars). The same sgRNA used to generate DLL3-knockout iPS cell lines was used for gene targeting. The gene-targeted intermediate shows details of the CAG::mCherry-IRES-puro cassette used for enrichment and FACS sorting of targeted cells as a population. Excision was performed without intermediate cloning. Owing to the c.615C/G mismatch between flanking microhomologies, two repair outcomes are possible. e, Southern blot analysis of gene-corrected iPS cell clones following selection marker removal. Samples marked with an asterisk were selected for further characterization, with SCDP2-resE17 and SCDP2-resE43 used for analysis of oscillation phenotypes (Fig. 4f, g). For gel source data for e, see Supplementary Fig. 1. f, HES7 reporter activity in 3D synchronization assay of PSM derived from SCDP2 patient and isogenic rescue cell lines (SCDP2-resE17 and SCDP2-resE43). After the spike noise was removed, the signal of the entire area was averaged. The signal was further detrended and normalized to the average (±100-min window). Representative graphs of three independent experiments are shown. See also Fig. 4g.
This file contains: Supplementary Figure 1, Source Data for gels and Southern blots in Extended Data Fig. 10h, Extended Data Fig. 10i and Extended Data Fig. 12e; Supplementary Notes 1-2 and Supplementary Discussions 1-2.
Expressed genes arranged into six major expression clusters/groups corresponding to the six distinct differentiation and developmental stages analyzed. The FPKM values were used for expression values. Data (n = 3) for two WT iPSC lines (201B7 and 1231A3) are shown.
Complete list of all phase and anti-phase oscillating genes identified by ARSER algorithm for hiPSC-PSM (for details see Methods section). The cpm values were used for expression values. RNA-seq data of two independent experiments with 16 samples each were used for applied analysis.
Complete results of pathway and GO analyses for phase and anti-phase oscillating human genes identified via RNA-seq of hiPSC-PSM. Statistical analysis was performed by the method implemented in DAVID and IPA (for details see Methods section). RNA-seq data of two independent experiments with 16 samples each were used for applied analysis.
Complete list of all phase and anti-phase oscillating genes identified by ARSER algorithm for mEpiSC-PSM (for details see Methods section). The cpm values were used for expression values. RNA-seq data of two independent experiments with 16 samples each were used for applied analysis.
Complete results of pathway and GO analyses for phase and anti-phase oscillating murine genes identified via RNA-seq of mEpiSC-PSM. Statistical analysis was performed by the method implemented in DAVID and IPA (for details see Methods section). RNA-seq data of two independent experiments with 16 samples each were used for applied analysis.
List of utilized recombinant human proteins (6.1), small molecule agonists and inhibitors (6.2).
List of utilized human RT-qPCR primers for differentiation and oscillation assays (7.1), mouse RT-qPCR primers for oscillation assays (7.2), RT-qPCR primers for iPSC quality control (7.3), exon-specific primers for genotyping (7.4), oligos for sgRNA cloning (7.5), InFusion primers for MhAX targeting vectors (7.6), PCR genotyping for MhAX targeting and excision (7.7) and ssODN templates used for gene editing (7.8).
List of utilized primary antibodies for immunocytochemistry (8.1), secondary antibodies for immuno-cytochemistry (8.2), primary antibodies for flow cytometry (8.3), secondary antibodies and isotype controls for flow cytometry (8.4).
Bright field view (left) and HES7 luciferase reporter images of healthy control iPSC-derived PSM (right). Representative data of three independent experiments are shown. Scale bar: 500 µm.
Representative videos of in vitro dermomyotome (DM) derived human skeletal muscle. GCaMP reporter line activity (green fluorescence) indicating calcium influx into contracting induced muscle cells. Magnified view of contracting skeletal muscle cells showing concomitant calcium activity (right side of video panel). Representative data of three independent experiments are shown. Scale bar: 100 µm.
HES7 reporter activity is shown for human in vitro derived PSM treated with inhibitors of the FGF, Wnt and Notch signalling pathways. Representative data of three independent experiments are shown.
HES7 reporter activity is shown for WT and DLL3, LFNG, MESP2 knock-out PSMs. Representative data of three independent experiments are shown. Scale bar: 500 µm.
HES7 reporter activity is shown for patient (SCDP2-E) PSM and two isogenic rescue line-derived (SCDP2-resE17 and SCDP2-resE43) PSMs. Representative data of three independent experiments are shown. Scale bar: 500 µm.
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Matsuda, M., Yamanaka, Y., Uemura, M. et al. Recapitulating the human segmentation clock with pluripotent stem cells. Nature 580, 124–129 (2020). https://doi.org/10.1038/s41586-020-2144-9
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