Bright AR , van Genesen S , Li Q , Grasso A , Frölich S , van der Sande M , van Heeringen SJ , Veenstra GJC .

607142 European Commission (EC), 016.Vidi.189.081 NWO | Aard- en Levenswetenschappen, Nederlandse Organisatie voor Wetenschappelijk Onderzoek (ALW-NOW)

	SYNOPSIS Mesoderm induction, dorsal‐ventral patterning, and establishment of the dorsal axis involve transcriptional heterogeneity at the gastrula stage of vertebrate embryogenesis. Single‐cell chromatin‐accessibility and transcriptomic analyses identify the contribution and cooperation of key transcription factors in zygotic gene expression. The extent of chromatin opening closely reflects lineage potential. Integration of single cell chromatin‐accessibility and transcriptomic data allows identification of developmental key regulators. Bipotent neuromesodermal, head‐organizer and trunk‐organizer cells are found as early as the early gastrula. Transcription factors Foxb1, Eomes, Irx3 and Otx2 cooperate in a combinatorial fashion in zygotic gene regulation.
	Figure 1.Chromatin accessibility during early development Genome browser view showing chromatin accessibility (ATAC‐seq) and ChIP‐seq (p300 and H3K4me3) profiles at stage 9, 10½, 12, and 16 at sox2 gene locus. The number at the left (black line) indicates the Y‐axis scale of the profile. ATAC‐seq peaks were found at promoter (H3K4me3) and enhancer (p300‐bound) regulatory regions. Chromatin accessibility and p300 binding at differential ATAC‐seq peaks visualized using K‐means clustering. Boxplots showing pair‐wise sequential‐stage comparisons of fold change in accessibility (ATAC‐seq) and corresponding changes in gene expression (RNA‐seq data set; Owens et al, 2016). The data represents two biological replicates. The central band within the boxplot represents the median (50th percentile), the box represents the range between the first and third quartile (25th–75th percentile), and the whiskers show 1.5× the interquartile range (IQR).
	Figure EV1.Chromatin accessibility at promoters and enhancers Clustering of ATAC‐seq signal at ATAC‐seq peaks (center of heatmap, ±5 kb) along with p300 and H3K4me3 ChIP‐seq signals at stage 9 (blastula), 10½ (early gastrula), 12 (late gastrula), and 16 (neurula). Clustering (k 8) on all peaks. Clustering (k 6) on differential ATAC‐seq peaks. H3K4me3 marked promoter regions have mostly stable accessibility across the stages, whereas differential accessibility seems restricted to enhancers (p300‐bound). Expression profiles of genes associated to cluster Fig 1B. In the graph, the dots represent median expression values (transcripts per million) of genes. The solid lines connect these expression values across each stage.
	Figure 2.Chromatin accessibility in animal cap (AC) and dorsal marginal zone (DMZ) Genome browser view of AC and DMZ accessibility profiles for ectoderm‐expressed (tfap2a and grhl3) and organizer‐expressed (gsc and chrd) marker genes. Boxplots showing differential gene expression (AC versus DMZ) and associated ATAC‐seq signals (Two biological replicates). The central band within the boxplot represents the median and the whiskers show 1.5 times the range between the first and third quartile (IQR). Hierarchical clustering of AC and DMZ ATAC‐seq data on H3K4me3‐positive (top) and p300‐positive (bottom) ATAC‐seq peaks. Heatmap showing accessibility signal (log1p of fold over background) at p300‐positive ATAC‐seq peaks surrounding pluripotency genes (ventx1/ventx2, pou5f3 and sox2). The row labeled “random” shows accessibility signals at random genomic loci. Single‐cell ATAC‐seq UMAP projection of cells derived from gastrula stage embryos (stage 10½), colored by cluster. Genomic tracks showing aggregated accessibility of single‐cell ATAC‐seq clusters at the t (tbxt), tfap2a, gsc, ctcf, lhx1 and sox11 loci.
	Figure EV2.Region‐specific chromatin accessibility A. Genome browser view of AC and DMZ ATAC‐seq at regulatory regions of key pluripotency genes (pou5f3.3, ventx1.2, sox2, and ventx1.1). Most of the genes show relatively higher accessibility for animal cap cells and lower signals in DMZ. B, C. Sample statistics for single‐cell ATAC‐seq clusters A1‐A3. The ridge plots display the distribution of transcription start site (TSS) enrichment (B) and unique nuclear fragments (log10 of nFrags; C) over the cells in clusters A1‐A3. The TSS enrichment is determined by the peak signal (centered at the TSS of annotated genes) relative to the flanking regions (± 1,900–2,000 bp). Unique nuclear fragments represent those fragments that do not map to mitochondrial genome.
	Figure 3.Cellular heterogeneity and developmental trajectories in blastula and gastrula stages A, B. UMAP visualization of whole embryo scRNA‐seq for stages 8, 10, and 12 colored by stage (A) and cell type annotations (B).
	Figure EV3.Single‐cell transcriptome analysis of early development Analysis of single‐cell RNA‐seq data (Briggs et al, 2018). Panels depict 7,705 filtered cells of stage 8, 10 and 12 embryos, shown in Uniform Manifold Approximation and Projection (dimensionality reduction). Cell type annotation based on marker gene expression (Briggs et al, 2018). Cell clusters (Louvain clusters L0–L20) based on hypervariable genes, labeled with predominant cell type annotation. Cluster labels contain cluster number, followed by predominant cell annotations and the stage it was derived from in brackets. Abbreviations: NoNEct, non‐neural ectoderm; Neur, neural plate; O, organizer; End, endoderm; Not, notochord; VMes, ventral mesoderm; Ect, ectoderm; Blas, blastula; NEct, neural ectoderm; InvDMes, involuted dorsal mesoderm; MZ, marginal zone; Tlbd, tailbud; Cil, ciliated epidermal progenitor; Misc, miscellaneous.
	Figure 4.scRNA‐seq of hand‐picked cells from stage 10½ dissected AC and DMZ explants Dimensionality reduction using UMAP. Each dot represents a cell. Colors indicate AC and DMZ. As panel (A), colors indicate clusters (C0‐C6). Feature maps, showing the expression of selected genes in single cells (cf. Appendix Fig S2). Color scale represents the gene expression value (log1p‐transformed counts per 10,000 unique reads) for each cell for a given gene, from low (gray) to high (orange). Heatmap depicting top 100 hypervariable genes in each cluster (cf. Dataset EV5). Color scale represents scaled gene expression (z‐score values). The z‐score values are ranging from −2 to 2. Spatially restricted AC and DMZ cell clusters embedded in UMAP of whole embryo scRNA‐seq data (cf. Fig 3).
	Figure EV4.Correlations of region‐specific and whole embryo single cell clusters Correlation of AC and DMZ single cell clusters (C0‐C6) with whole embryo single cell clusters of whole embryos of stage 8, 10 and 12.
	Figure 5.Integration of single‐cell transcriptomics and chromatin accessibility, for identifying regulators driving cluster‐specific gene expression Heatmap showing motif activity inferred from differential chromatin accessibility of stage 10½‐AC‐DMZ. Heatmap showing motifs identified based on regulatory regions closest to cluster‐specific genes, and regression to cluster gene expression. Heatmap of transcription factor (TF)‐motif combinations showing cluster‐specific motif activity (z‐score, color) and gene expression (size of dot). Motifs and the Motif‐TF combinations were hierarchically clustered.
	Figure EV5.Transcription factor motifs and expression of single cell clusters A. Heatmap showing motif activity inferred from differential chromatin accessibility of single‐cell ATAC‐seq. B. Schematic overview, outlining the steps involved in the integrative analysis: (1) Identifying transcription factor motifs associated with regulatory regions closest to cluster‐specific genes, and regression to cluster gene expression; (2) Prioritizing transcription factors based on their gene expression and the corresponding motif activity in specific clusters. Combining the information (lower right panel) on motif activity (color of dots) and corresponding transcription factor expression (size of dots) allows prediction of factors that may play a role in cell cluster‐specific gene expression. C, D. Heatmaps of transcription factor‐motif combinations showing cluster‐specific motif activity (z‐score, color) and transcription factor expression (size of dot) for animal cap (panel C) and dorsal marginal zone (panel D) peak sets.
	Figure 6.Induction of organizer gene expression in AC cells Heatmap showing log2 fold expression changes of differentially expressed genes in AC tissues overexpressing Foxb1, Foxb1‐Eomes, Eomes, Irx3, Irx3‐Otx2, Otx2, and Lhx8. Correlation heatmap of overexpression RNA‐seq samples and single‐cell clusters. Fold enrichment of genes with zygotically defined (ZyD) H3K4me3 at their promoter in AC with transcription factor overexpression. Asterisk indicates hypergeometric P‐value ≤ 0.01.

Agius, Endodermal Nodal-related signals and mesoderm induction in Xenopus. 2000, Pubmed, Xenbase

Agius, Endodermal Nodal-related signals and mesoderm induction in Xenopus. 2000, Pubmed , Xenbase
Angerilli, The Xenopus animal cap transcriptome: building a mucociliary epithelium. 2018, Pubmed , Xenbase
Balwierz, ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs. 2014, Pubmed
Blitz, A catalog of Xenopus tropicalis transcription factors and their regional expression in the early gastrula stage embryo. 2017, Pubmed , Xenbase
Bogdanović, The epigenome in early vertebrate development. 2012, Pubmed , Xenbase
Borchers, Programming pluripotent precursor cells derived from Xenopus embryos to generate specific tissues and organs. 2010, Pubmed , Xenbase
Briggs, The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. 2018, Pubmed , Xenbase
Bright, Combinatorial transcription factor activities on open chromatin induce embryonic heterogeneity in vertebrates. 2021, Pubmed , Xenbase
Bright, Assay for Transposase-Accessible Chromatin-Sequencing Using Xenopus Embryos. 2019, Pubmed , Xenbase
Chalmers, Intrinsic differences between the superficial and deep layers of the Xenopus ectoderm control primary neuronal differentiation. 2002, Pubmed , Xenbase
Chalmers, Grainyhead-like 3, a transcription factor identified in a microarray screen, promotes the specification of the superficial layer of the embryonic epidermis. 2006, Pubmed , Xenbase
Charney, A gene regulatory program controlling early Xenopus mesendoderm formation: Network conservation and motifs. 2017, Pubmed , Xenbase
Chen, fastp: an ultra-fast all-in-one FASTQ preprocessor. 2018, Pubmed
Chung, Screening of FGF target genes in Xenopus by microarray: temporal dissection of the signalling pathway using a chemical inhibitor. 2004, Pubmed , Xenbase
Dong, Single-cell RNA-seq analysis unveils a prevalent epithelial/mesenchymal hybrid state during mouse organogenesis. 2018, Pubmed
Esmaeili, Chromatin accessibility and histone acetylation in the regulation of competence in early development. 2020, Pubmed , Xenbase
Gamse, Early anteroposterior division of the presumptive neurectoderm in Xenopus. 2001, Pubmed , Xenbase
Gao, Kruppel-like factor family genes are expressed during Xenopus embryogenesis and involved in germ layer formation and body axis patterning. 2015, Pubmed , Xenbase
Gentsch, In vivo T-box transcription factor profiling reveals joint regulation of embryonic neuromesodermal bipotency. 2013, Pubmed , Xenbase
Gentsch, Maternal pluripotency factors initiate extensive chromatin remodelling to predefine first response to inductive signals. 2019, Pubmed , Xenbase
Georgiou, fluff: exploratory analysis and visualization of high-throughput sequencing data. 2016, Pubmed
Hontelez, Embryonic transcription is controlled by maternally defined chromatin state. 2015, Pubmed , Xenbase
Islam, Highly multiplexed and strand-specific single-cell RNA 5' end sequencing. 2012, Pubmed
Jambhekar, Roles and regulation of histone methylation in animal development. 2019, Pubmed
Karimi, Xenbase: a genomic, epigenomic and transcriptomic model organism database. 2018, Pubmed , Xenbase
Kinoshita, Antagonistic role of XESR1 and XESR5 in mesoderm formation in Xenopus laevis. 2011, Pubmed , Xenbase
Koch, Antagonistic Activities of Sox2 and Brachyury Control the Fate Choice of Neuro-Mesodermal Progenitors. 2017, Pubmed
Kudoh, Role of the iroquois3 homeobox gene in organizer formation. 2001, Pubmed
Langmead, Fast gapped-read alignment with Bowtie 2. 2012, Pubmed
Love, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. 2014, Pubmed
Luo, Regulatory targets for transcription factor AP2 in Xenopus embryos. 2005, Pubmed , Xenbase
Madsen, Integrated analysis of motif activity and gene expression changes of transcription factors. 2018, Pubmed
MARIANO, THE ISOLATION OF NUCLEI FROM XENOPUS LAEVIS EMBRYONIC CELLS. 1964, Pubmed , Xenbase
McCarthy, Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R. 2017, Pubmed
McLean, GREAT improves functional interpretation of cis-regulatory regions. 2010, Pubmed
Nakamura, Tissue- and stage-specific Wnt target gene expression is controlled subsequent to β-catenin recruitment to cis-regulatory modules. 2016, Pubmed , Xenbase
Niehrs, Head in the WNT: the molecular nature of Spemann's head organizer. 1999, Pubmed
Owens, Measuring Absolute RNA Copy Numbers at High Temporal Resolution Reveals Transcriptome Kinetics in Development. 2016, Pubmed , Xenbase
Paraiso, Endodermal Maternal Transcription Factors Establish Super-Enhancers during Zygotic Genome Activation. 2019, Pubmed , Xenbase
Paranjpe, Establishing pluripotency in early development. 2015, Pubmed , Xenbase
Pera, Active signals, gradient formation and regional specificity in neural induction. 2014, Pubmed , Xenbase
Perino, Chromatin Control of Developmental Dynamics and Plasticity. 2016, Pubmed
Quinlan, BEDTools: a flexible suite of utilities for comparing genomic features. 2010, Pubmed
Satija, Spatial reconstruction of single-cell gene expression data. 2015, Pubmed
Scerbo, Ventx factors function as Nanog-like guardians of developmental potential in Xenopus. 2012, Pubmed , Xenbase
Schlesinger, Open Chromatin, Epigenetic Plasticity, and Nuclear Organization in Pluripotency. 2019, Pubmed
Schneider, A dual function of FGF signaling in Xenopus left-right axis formation. 2019, Pubmed , Xenbase
Sive, Dissociation and Reaggregation of Xenopus laevis Animal Caps. 2007, Pubmed , Xenbase
Steiner, FoxD3 regulation of Nodal in the Spemann organizer is essential for Xenopus dorsal mesoderm development. 2006, Pubmed , Xenbase
Suzuki, The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. 2009, Pubmed
Takebayashi-Suzuki, The forkhead transcription factor FoxB1 regulates the dorsal-ventral and anterior-posterior patterning of the ectoderm during early Xenopus embryogenesis. 2011, Pubmed , Xenbase
Tao, BMP4-dependent expression of Xenopus Grainyhead-like 1 is essential for epidermal differentiation. 2005, Pubmed , Xenbase
Vastenhouw, The maternal-to-zygotic transition revisited. 2019, Pubmed
Walentek, Wnt11b is involved in cilia-mediated symmetry breakage during Xenopus left-right development. 2013, Pubmed , Xenbase
Wolf, SCANPY: large-scale single-cell gene expression data analysis. 2018, Pubmed
Zhang, Model-based analysis of ChIP-Seq (MACS). 2008, Pubmed