{"paper_id":"bcff350f-4deb-41c6-ab8f-b074689a6134","body_text":"1 \nSingle-cell and spatial transcriptomics of the avian embryo tailbud  \nMok GF1*, Turner S2,3, Smith E1, Mincarelli L2,4, Lister A2, Lipscombe J2, Uzun V2,4, Haerty W2, Macaulay \nIC2*, Münsterberg A1* \n1 School of Biological Sciences, University of East Anglia, Norwich Research Park, Norfolk NR4 7TJ, \nUnited Kingdom \n2 Earlham Institute, Norwich Research Park, Norfolk, NR4 7UZ, United Kingdom \n*Correspondence to: g.mok@uea.ac.uk; iain.macaulay@earlham.ac.uk; a.munsterberg@uea.ac.uk \n3 Present address: Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 \n3EJ, UK \n4 Present address: Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Saffron \nWalden CB10 1RQ, UK \n  \n  \n  \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 2 \nAbstract \nVertebrate body axis formation initiates during gastrulation and continues within the tail bud at the \nposterior end of the embryo. Major structures in the trunk are paired somites, which generate the \nmusculoskeletal system, the spinal cord - forming part of the central nervous system, and the notochord, \nwith important patterning functions. The specification of these different cell lineages by key signalling \npathways and transcription factors is essential, however, a global map of cell types and expressed \ngenes in the avian trunk is missing. Here we use single-cell RNA sequencing and RNA tomography to \ngenerate a molecular map of the emerging trunk and tailbud in the chick embryo. Single cell RNA -\nsequencing (scRNA-seq) identifies discrete cell lineages includi ng somites, neural tube, neural crest, \nlateral plate mesoderm, ectoderm, endothelial and blood progenitors. In addition, high-throughput RNA-\nseq of sequential tissue sections provides a spatially resolved, genome-wide expression dataset for the \navian tailbud and emerging body, comparable to other model systems. Combining the single -cell and \nspatial datasets, we identify spatially restricted genes, focusing on somites and early myoblasts. Thus, \nthis high -resolution transcriptome map incorporating cell types in the embryonic trunk can expose \nmolecular pathways involved in body axis development. \nKey words: development; axis extension, somites, single -cell RNA sequencing, RNA tomography, \nchick embryo \n  \n  \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 3 \nIntroduction \nThe generation of somites, which arise in a regular sequence during embryogenesis, is fundamental for \ncreating the vertebrate segmented body plan (Benazeraf and Pourquie, 2013). Pairs of somites form on \neither side of the neural tube from unsegmented, paraxial mesoderm, and the process of somitogenesis, \nwhich involves waves of cycling gene expression, has been studied extensively in chick embryos \n(Pourquie, 2004). Prospective paraxial mesoderm cells emerge from the primitive streak during \ngastrulation (Psychoyos and Stern, 1996) and follow a stereotypical migration trajectory towards their \ndestination (Iimura et al., 2007; Yang et al., 2002). As the body axis elongates, bi -potential neuro-\nmesodermal progenitors (NMP) located in the tailbud continue to generate paraxial mesoderm and cells \nof the neural tube (Henrique et al., 2015; Wilson et al., 2009; Wymeersch et al., 2021).  The dynamics \nof this specialised cell population has been mapped in detail in chick embryos (Guillot et al., 2021) and \nit has been shown that the extension of neural and paraxial mesoderm tissues in the embryonic body is \ncoordinated by mechanical interactions (Xiong et al., 2020). \nSomite differentiation proceeds along the posterior -to-anterior axis and serves as a paradigm for the \nstudy of cell fate specification. Multiple signals from surrounding tissues are integrated by somite cells \nto produce the lineages of the musculoskeletal system, including chondrocytes of the axial skeleton and \nskeletal muscles of the trunk and limbs (Brent and Tabin, 2002; Christ et al., 2007; Christ and Scaal, \n2008). Cell fate specification is intimately linked to stereotypic morphological changes resulting in somite \ncompartmentalisation. Tracking of GFP-labelled cells showed that the dorsal dermomyotome produces \nthe myotome layer in multiple waves, with the first myocytes specified adjacent to the neural tube (Gros \net al., 2004). Live -imaging of cellular rearrangements examined the morphological transformations of \nsomites from epithelial structures to somites with a mesenchymal sclerotome, located ventrally, and an \nepaxial myotome abutting the neural tube (McColl et al., 2018). This uncovered differential cell sizes \nand regions of proliferation as well as a directed movement of dermomyotomal progenitor cells towards \nthe rostro-medial domain of the dermomyotome, where skeletal muscle formation initiates. \nTo better characterise the regulation of these morphogenetic events and their integration with cell \nspecification and differentiation, we previously assessed the dynamic changes of the transcriptome and \nof chromatin accessibility across presegmented mesode rm and early somites (Mok et al., 2021). \nAssociating differentially accessible chromatin with nearby genes differentially expressed along the axis \nidentified candidate cis -regulatory elements (CREs) involved in expression of transcription factors \nimportant for somite formation and differentiation. Time-lapse microscopy in accessible chick embryos \nof fluorescent CRE-reporters revealed their spatio -temporal activity and mutation analysis uncovered \nsome upstream regulators. Similarly in mice, we examined match ed gene expression and open \nchromatin profiles for newly formed somite pairs across a developmental time series. This provided a \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 4 \nhigh-resolution view of the molecular signatures underlying the conserved maturation programme \nfollowed by all somites after segmentation (Ibarra-Soria et al., 2023). \nHere we focus on the initial phase of trunk development in chick embryos. Recent in vitro organoid \nmodels of axis elongation based on the differentiation of mouse or human pluripotent stem cells use \npharmacological activation or inhibition of crucial signalling pathways (Veenvliet and Herrmann, 2021). \nThese self-organising structures include gastruloids (Moris et al., 2020; Turner et al., 2017), trunk -like \nstructures (Veenvliet et al., 2020), or somitoids (Sanaki-Matsumiya et al., 2022), or axioloids (Yamanaka \net al., 2023). These often comprise mesoderm, including somites, although the notochord, which is \ninvolved in patterning of trunk tissues,  is missing. Thus, it is important to reconstruct the molecular \nprofiles and cellular composition in the native tissues. \nHere, we use single -cell transcriptomics combined with an RNA -tomography based approach, \nanalogous to Tomo-seq (Junker et al., 2014; Kruse et al., 2016) but using a modified G&T-seq approach \n(Macaulay et al. 2015). This generated a spatio-temporal map of the emerging trunk and identified genes \nnot previously known to be involved in presomitic mesoderm (psm) and somite maturation.  Our study \ncomplements data in chick embryos, from earlier developmental stages (HH4-HH11) (Rito et al., 2023; \nVermillion et al.,  2018; Williams et al., 2022), from tailbud (Guillot et al., 2021) and from prospective \nneural plate, neural plate border and non-neural ectoderm (Trevers et al., 2023). The dataset is relevant \nfor cell -type specification during early body formation and ma y provide insights into the molecular \ngenetics that underlie diseases of the musculoskeletal system. \nResults \nSingle cell profiling of the developing chick embryonic body \nTo investigate the molecular basis underpinning somitogenesis and axis elongation of the growing chick \nbody, we mapped the transcriptomes of individual cells at embryonic stage HH14 (Hamburger and \nHamilton, 1992). This stage embryo has 22 somites, including cervical level somites (6-19) and thoracic \nlevel somites (20-22). The unsegmented paraxial mesoderm and tailbud comprise prospective somites \nof the thoracic, lumbar and sacral regions (Weldon and Munsterberg, 2022). Single cell suspensions \nfrom the posterior part of five pooled embryos included the extraembryonic region, tailbud, pre -somitic \nmesoderm and the most recently formed six somites. Following enzymatic digestion and mechanical \ndissociation the suspension was processed using the 10X Genomics Chromium (Fig. 1). A total of 6158 \ncells were sequenced with a median of 517 genes and 900 UMIs per cell. \nUnsupervised clustering was used to classify cell populations (Butler et al., 2018). Projection onto UMAP \nplots revealed 10 separate clusters (Fig. 2). Classic marker genes assigned cluster identity and tissues: \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 5 \nlateral plate mesoderm ( Prrx1 and Krt18), neural ( Wnt4 and Olig2), epithelial somites ( Meox1 and \nTcf15), maturing somite ( Nkx3-2 and Twist1), ectoderm ( Fabp3 and Wnt6), blood ( Hbm and Hba1), \ntailbud (Cdx4 and Msgn1), endothelial (Lmo2 and Sox18), notochord (Tf and Shh) and neural crest cells \n(FoxD3 and Sox10) (Fig. 2A-C). Seurat cell cycle scoring determined cell cycle activity. This showed \ncell clustering was not due to cell cycle phase, although neural cells were predominantly in S phase and \nG2M phase (Fig. 2D).  \nSpatial transcriptomics profiling of the developing chick embryonic trunk \nSpatial information is lost in single cell sequencing data following tissue dissociation (Griffiths et al., \n2018). To address this, we next used a spatial transcriptomics approach to quantify the transcriptomes \nof a series of individual cryogenic sections along the HH14 embryonic trunk. This enabled a systematic \ninvestigation of spatial RNA profiles along the axis. Libraries were generated from 20 micron \nconsecutive cryosections of a HH14 chick embryo. Each section was collected into lysis buffer and \nmRNA captured and amplified using a modification of the G&T -seq protocol (Macaulay et al., 2016). \nThe resulting cDNA libraries had high complexity and enabled us to confidently determine spatial gene \nexpression (Fig. 3). \nUsing the same markers as in the previous scRNA-seq analysis, we identified 10 different clusters and \nestablished profiles of the lateral plate mesoderm, neural tissue, early somite, maturing somite, \nectoderm, blood, endothelial, tailbud, notochord and neu ral crest cells (Fig. 3). Spatial patterns of \nlocalised anterior-to-posterior restricted gene expression were evident for all tissue types, with exception \nof the ectoderm, suggesting that this tissue has few distinguishing markers along the A -P axis. In th e \nmost posterior samples, we identified blood (Hbm, Hba1) and endothelial marker genes (Lmo2, Ramp2), \nconsistent with this region comprising extra-embryonic tissue. Subsequent sections showed the onset \nof tailbud genes (T (= brachyury) and Fgf8). Some notochord markers were more highly expressed in \nposterior sections (Shh), while transferrin (Tf) was expressed along the axis, with lower levels around \nthe tailbud region. Across neural tissue (Ckb, Pax6), early somites (Meox1, Tcf15) and maturing somites \n(Cnmd, Shisa2), gene expression profiles showed a gradual increase towards the anterior. Neural crest \ncells are beginning to migrate and become distinguishable in the more anterior sections with discreet \nprofiles detected for Foxd3 and Sox10 (Fig. 3C). \nSpatial transcriptomics resolves mRNA localisation patterns \nTo identify gene expression patterns systematically, we clustered our spatial gene expression data \nbased on a self-organising heatmap. This sorted the cumulative gene expression traces along a linear \naxis of 180 profiles and identified 3 major groups of localised mRNA (Fig. 4A). The first group localised \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 6 \nto the most posterior, the second group displayed an increase in the tailbud region and across the pre-\nsomitic mesoderm, and the third group of transcripts was most highly expressed in the anterior sections \ncomprising epithelial and maturing somites (Fig. 4B). Transcripts enriched posteriorly (e.g. Hbm, Epas1, \nLmo2) were related to hematopoiesis, erythrocyte differentiation and myeloid homeostasis, consistent \nwith the presence of extraembryonic blood islands. The second profile showed genes enriched for Gene \nOntology (GO) processes such as anterior-posterior pattern specification, embryo morphogenesis and \ntissue morphogenesis. This overlaps spatially with tailbud and pre -somitic regions. Markers with \nenriched expression included Wnt5a, Msgn1, Tbx6 and Fgf8. The third profile, which overlaps with the \nformation of somites but also neural tube development, included genes enriched for pattern \nspecification, neurogenesis and animal organ morphogenesis, such as Meox1 and Shisa2. Interestingly, \nthe profiles for somites and neural tube are very similar and genes were clustered together, suggesting \nthese tissues mature at a similar rate. However, GO analysis did separate genes associated with either \nsomitogenesis or neurogenesis (Fig. 4C). Spatial transcriptomics also detected the opposing gradients \nacross the psm and somites of Wnt5a, FGF8 and Aldh1a2, encoding an enzyme involved in retinoid \nacid synthesis. The transcripts for Meox1 and Tcf15 become upregulated in anterior psm and epithelial \nsomites, whereas Mesp1 transcripts are restricted to an anterior region in the psm, comprising the next \nbut one prospective somite. Transcripts for Hoxd11, Hoxc9 and Hoxb1 show the expected expression \nboundaries along the anterior-posterior axis (Fig. 4D). Analysis of expression l evels of components of \nimportant signalling pathways, including WNT, FGF, NOTCH and BMP pathways, shows high levels of \nWnt5a and Fgf8 in tailbud population, high levels of Wnt6 in the ectoderm, Notch1/2 in neural and neural \ncrest cells and Bmp4 in the lateral plate (Fig. 4E).  \nCorrelation of single cell RNA sequencing with spatial transcriptomics   \nAxis patterning is characterized by the progressive differentiation of cell types with anterior-to-posterior \nidentity. To validate genes identified in specific clusters obtained from the single-cell RNA-sequencing, \nwe correlated spatial patterns and confir med gene expression by in situ hybridisation. Expression of \nHbm, a haemoglobin gene, is representative for the most posterior group of transcripts, which is \nenriched for genes involved in hematopoietic differentiation. We show that Hbm transcripts are restricted \nto blood islands in posterior extraembryonic tissue (Fig. 5A). The second spatial cluster values correlate \nwith the tailbud and pre -somitic mesoderm. We validated this data using Wnt5a, a known regulator of \ncell movement behaviour during axis elongation (Sweetman et al., 2008). In situ hybridisation showed \nWnt5a expression was restricted to the tailbud region (Fig. 5B), where neuromesodermal progenitor \n(NMP) cells are located. The third spatial cluster, where gene expression increased towards the anterior, \nwas validated using Tbx22 - a key gene for somite boundary formation. Expression of Tbx22 was \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 7 \nrestricted to caudal somite domains. The periodicity visualised in situ correlates with the distribution in \nthe UMAP and in the spatial line plots (Fig. 5C). \nIdentification of new genes in paraxial mesoderm and somites \nNext, we investigated previously unexplored genes uncovered by our approach. We focused on \ncandidates with restricted expression in the pre -somitic mesoderm and somites. Using the subset \nfeature in Seurat, we profiled three clusters from the single-cell RNA seq dataset – tailbud, early somite \nand maturing somite (Fig. 6A). We re-ran the clustering, findneighbours and pca tests on this new Seurat \nobject. Classic markers for each cluster were re-plotted on UMAPs, such as Msgn1 for the pre-somitic \nmesoderm, Meox1 and Tcf15 for early somites and Tbx22 for maturing somites (Fig. 6A). Sub-clustering \nalso revealed restricted expression of follistatin ( Fst), in a group of cells potentially representing early \nmyoblasts located adjacent to the neural tube. We identified three genes for further analysis. UMAP plot \nof Olfml3 and Foxd1 gene expression suggested they are likely to be expressed in maturing somites, \nwhereas Lrig3 was predicted to be expressed in some pre -somitic mesoderm cells, early somites and \nless in maturing somites (Fig. 6A). \nInterrogation of the profiles for these genes in the spatial data showed that expression of Foxd1 and \nOlfml3 increased towards the anterior regions. Foxd1 and Olfml3 were also identified in spatial  cluster \n3 (Fig. 4). For Lrig3, the spatial data showed increasing expression from the most posterior to the \nanterior embryonic regions, suggesting that it is expressed from the tailbud to maturing somites. Spatial \nvalidation for all three genes in situ confirmed these observations: Foxd1 and Olfml3 are restricted to \nsomites whilst Lrig3 is expressed in the tailbud, pre -somitic mesoderm and in somites. In epithelial \nsomites, all three genes are restricted medially. In maturing somites Foxd1 is broadly expressed, Olfml3 \nremains medially restricted and Lrig3 is downregulated (Fig. 6B-D). \nDiscussion \nThe chick embryo is a classic model for developmental biology studies due to the versatility of in vivo \nexperimental approaches (Gandhi and Bronner, 2018; Sauka-Spengler and Barembaum, 2008; Stern, \n2005). For example, it has served to better understand the processes of body axis formation, \nsegmentation/somitogenesis and differentiation (Benazeraf and Pourqu ie, 2013).  Here we use single \ncell transcriptomics and spatial transcriptomics to map cells that arise in the emerging trunk as it \nextends. This adds to the growing body of literature, which includes scRNA-seq data of the chick embryo \nfrom primitive streak to neurula stages (Vermillion et al., 2018; Williams et al., 2022). Previous work \ncharacterised the molecular signature of neuromesodermal progenitors (NMP) in detail by micro -\ndissecting anterior PS in stage HH5 and in 6-somite embryos (HH9-) as well as the tail bud of 35-somite \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 8 \nembryos (~HH18) (Guillot et al., 2021). A recent report examined the anterior most part of the main \nbody axis, including occipital and cervical somites at several stages of development, 4 -somites, 7 -\nsomites, 10 -somites and 13 -somites (Rito et al., 2023). T his work is in agreement with our data \npresented here. We identified similar cell populations when the body extends and the cervical-thoracic \nregion forms (HH14, 22-somite embryo) (Weldon and Munsterberg, 2022). \nFurthermore, we show that combining scRNA-seq with spatial transcriptomics can reveal novel genes \ninvolved in specific aspects of axis extension. As an example, we focused on paraxial mesoderm and \ndiscovered the previously unknown relevance of Foxd1, Olfml3 and Lrig3 in developing somites. All \nthree genes showed restricted expression in the medial somite domain suggesting a possible role in \nearly myoblasts. It is noteworthy that Foxd1, a member of the fork-head family of transcription factors, \nis associated with pluripotency and seems to be required for successful reprogramming (Koga et al., \n2014). In addition, Foxd1 protects senescence in human mesenchymal stem cells (hMSC) and is \nregulated by YAP (Fu et al., 2019). Not much is known about Olfml3 function in development. It is a \nsecreted glycoprotein of the Olfactomedin-family, which organises the extracellular matrix and has pro-\nangiogenic properties. Olfml3 deficient mice exhibit abnormalities in the vasculature causing lethality \n(Imhof et al., 2020). Olfml3 has also been implicated in pre-natal muscle development in pig (Jin and Li, \n2019) and in Xenopus it is involved in dorso -ventral patterning by enhancing chordin degradation \n(Inomata et al., 2008). Finally, Leucine-rich repeats and immunoglobulin-like domains 3 (Lrig3) plays a \nrole in neural crest development (Zhao et al., 2008) in Xenopus. This is consistent with studies in mice, \nwhich showed Lrig3 is involved in inner ear morphogenesis by restricting the expression of Ntn1 (Abraira \net al., 2008). However, the roles of these genes in developing somites have not yet been investigated. \nTomo-seq is a spatial transcriptomics approach first used in zebrafish embryos (Junker et al., 2014; \nKruse et al., 2016). We modified and automated this approach using the G&T -seq protocol (Macaulay \net al. 20015) and applied it to the posterior half of a HH14 whole embryo. As reported previously in the \nzebrafish heart (Burkhard and Bakkers, 2018; Wu et al., 2016), we obtained high spatial resolution and \nsensitivity as shown by hierarchical cluster analysis. Known marker genes were expressed in the \nanticipated spatio-temporal patterns and identified the appropriate regions along the body axis. The \nextraembryonic tissue was characterized by Hbm, Hbz, Lmo2 and Epas1, the tailbud region by Hoxa13, \nWnt5A, the presegemented mesoderm by Msgn1, Tbx6 and epithelial somites by Meox1 and genes \ninvolved in retinoic acid (RA) signalling. \nOverall, this study integrates scRNA-seq with spatial transcriptomics improving our understanding and \nvalidating the gene expression patterns within the avian tailbud. While the scRNA -seq provides \ninformation on gene expression at the single -cell level, combining it with spatial transcriptomics using \nthe G&T method allows preservation of the spatial context of gene activity along the anterior-to-posterior \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 9 \naxis. Although other technologies are now available for obtaining high-resolution spatial transcriptional \nprofiles of tissues, such as MERFISH, 10X Genomics Visium and Xenium, these would be costly to \nimplement to understand gene dynamics along the anterior-to-posterior axis with multiple samples. Our \nresults illustrate the advantage of combining different approaches to address fundamental questions in \ndevelopmental biology. \nMaterials and Methods \nChicken embryos \nFertilised chicken eggs (Henry Stewart & Co.) were incubated at 37 °C with humidity. Embryos were \nstaged according to (Hamburger and Hamilton, 1992). All experiments were performed on chicken \nembryos younger than two thirds of gestation and therefore were not regulated by the Animal Scientific \nProcedures Act 1986. \nPreparation of single cells from chicken embryos \nThe trunk of HH14 embryos were dissected into Ringer’s solution in silicon lined petri dishes and pinned \ndown using the extra-embryonic membranes. Embryonic tissue was transferred into low binding tubes \nand Ringer’s solution was replaced with Dispase (1.5  mg/ml) in DMEM 10 mM HEPES pH7.5 at 37 °C \nfor 7 min prior to treatment with Trypsin (0.05%) at 37 °C for 7 min. The reaction was stopped with \nRinger’s solution with 0.25% BSA. Cells were spun down and resuspended in Hank’s solution prior to \npassing through 40 μm cell strainer to obtain single cell suspension. \nscRNA-seq library preparation \nA suspension of approximately 10,000 single cells was loaded onto the 10X Genomics Single Cell 3’ \nChip. cDNA synthesis and library construction were performed according to the manufacturer’s protocol \nfor the Chromium Single Cell 3’ v2 protocol (PN-12033, 10X Genomics). Samples were sequenced on \nIllumina HiSeq 4000 100 bp paired-end runs. \nscRNA-seq data analysis \nCell Ranger 3.0.2 (10X Genomics) was used to de-multiplex Illumina BCL output, create fastq files and \ngenerate single cell feature counts for the library using  the Gallus gallus  transcriptome (Ensembl \nrelease 94) with 82.4% reads mapped to the genome. Subsequent processing was performed using the \nSeurat v3.1.0 (Butler et al., 2018) package within R (v3.6.1). Cell quality was assessed using simple QC \nmetrics: total number of expressed genes, mitochondrial RNA content and ribosomal RNA content. \nIdentification of chicken mitochondrial RNA content and ribosomal RNA content. Outlier cells  were \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 10 \nidentified if they were above or below three median absolute deviations (MADs) from the median for any \nmetric in the dataset. Data was normalised across all cells using the ‘LogNormalize’ function with a scale \nfactor of 1e4. A set of genes highly variable across the cells was identified using the ‘FindVariableGenes’ \nfunction (using ‘vst’ and 2000 features) before being centred and scaled using the ‘ScaleData’ function \nwith default parameters. PCA analysis was performed on scaled data using variant genes and significant \nprincipal components were identified by plotting the standard deviation of the top 50 components. The \nfirst 2 principal components showed high enrichment for mitochondrial genes and were subsequently \nregressed and only principal components 3:25 were used to create a Shared Nearest Neighbour (SNN) \ngraph using the ‘FindNeighbours’ function with k.param set to 10. This was used to identify clusters of \ncells showing similar expression profiles using the FindClusters function with a resolution set to 0.6. The \nUniform Manifold Approximation and Projection (UMAP) dimensional reduction technique was used to \nvisualise data from principal components 3:26 in two -dimensional space (‘RunUMAP’ function). \nGraphing of the output enabled visualisation of cell cl uster identity and marker gene expression. \nBiomarkers of each cluster were identified using Wilcoxon rank sum tests using Seurat's \n‘FindAllMarkers’ function. It was stipulated that genes must show a logFC of at least 0.01 to be \nconsidered for testing. Only  positive markers were reported. The expression profile of top markers \nranked by average logFC were visualised as heatmaps and dotplots of the scaled data. Cluster identity \nwas determined using visual inspection focussing on the expression of known marker genes. For cells \nidentified in tailbud and somite clusters, the ‘Subset’ function was used to create a new Seurat object \nwhich narrowed down to 1359 cells. Using the ‘FindNeighbors’ feature with dimensions set to 3:20, \n‘FindClusters’ resolution of 0.4 and ‘RunUMAP’ set with dimensions 3:16. \nSpatial RNA sequencing from sections \nEmbryos were embedded in Jung tissue freezing medium (Leica), orientated and rapidly frozen on dry \nice, and stored at -80° C prior to cryosectioning. Embedded embryos were cryosectioned at 20 μm \nthickness, collected into 96 -well plates (on ice) prior to th e addition of 10 μL of RLT plus lysis buffer \n(Qiagen, Hilden, Germany). All instruments and surfaces were cleaned with 80% v/v ethanol, RNAse -\nfree water and lastly RNAse -out solution after each sample to reduce cross -contamination and RNA \ndegradation. Samples were stored at -80° C until cDNA preparation using the G&T -seq method as \npreviously described (Macaulay et al. 2015) with minor modifications to accommodate the larger volume \nof lysis buffer. cDNA was normalised to 0.2 ng/μL before Nextera (Illumina, San Diego, CA, USA) library \npreparation in a total reaction volume of 4 μL. Libraries were pooled by volume and sequenced on a \nsingle lane on the Illumina HiSeq 2500 (150-bp paired-end reads).  \nLow-input RNA sequencing analysis For RNA-seq analysis, we used Refseq version GRCg6a for \ngenome assembly and gene annotation. Reads were trimmed and adapters were removed using tim -\n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 11 \ngalore version 0.4.2. Heatmap based on hierarchical clustering was generated in R -Studio version \n1.2.1335 and plotted as a heatmap using the R package DeSeq2 (Love et al. 2014).  \nWholemount in situ hybridisation \nWholemount in situ hybridisation using DIG -UP labelled antisense RNA probes was carried out using \nstandard methods. Probes were generated from amplific ons of chicken cDNA using the following \nprimers: Wnt5a (GCAGCACTGTGGACAACAAC/CACCGTCTTGAACTGGTCGT), Olfml3 \n(GGGAGTTCACGCTCTTCTCG/GATGATCTGGTAGCCGTCGT) Hbm (CATCACACATTGCCACCAG \nC/GCAGCAATGGTGTCTTTATTGA), Tbx22 (GGATGTTCCCATCGGTCAGG/AGACTTAGCGCTCTT \nCAGGC), Lrig3 (GTCCTGACGCCTGGGAATTT/AATCTGTGGGACAGGATGCC). Briefly, following \nfixation in 4% PFA embryos were treated with Proteinase K, hybridised with the probe over night at \n65°C. After post-hybridisation washed and blocking with BMB (Roche), embryos were treated with anti-\nDIG antibody coupled to alkaline phosphatase (Merck) and signal developed using NBT/BCIP (Melfords \nLaboratories). \nData availability \nFor scRNA-seq the raw sequencing data can be accessed on the NCBI -SRA archive under accession \nnumber tbc. Raw spatial transcriptomics data are available under NCBI-SRA accession number tbc. \nACKNOWLEDGEMENTS \nThe authors acknowledge support from the Biotechnology and Biological Sciences Research Council \n(BBSRC), part of UK Research and Innovation, Core Capability Grant BB/CCG1720/1 and the National \nCapability BBS/E/T/000PR9816 (NC1 - Supporting EI’s ISPs and th e UK Community with Genomics \nand Single Cell Analysis). ICM was supported by a BBSRC New Investigator Grant BB/P022073/1. AM \nacknowledges funding from BBSRC to support GM ( BB/N007034/1) and a NRPDTP studentship to \nsupport ES. ST was supported by a Summer internship held at EI. \nAUTHOR CONTRIBUTIONS \nConceptualization: GM, AM, WH and IM. Funding acquisition, Project administration and supervision: \nAM, WH and IM. Investigation, validation and visualisation: GM, ST and ES. Formal analysis and Data \ncuration: GM, WH and VU. LM and AL made libraries with assistance from JL. Writing original draft: AM \nand GM. Writing review and editing: all authors.  \n  \nCompeting Interests statement \nThe authors declare no competing interests. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 12 \nFigure legends \nFigure 1: High -throughput scRNA-seq of the embryonic trunk.  (A) Trunk regions, indicated by \nstippled lines, of five stage HH14 chicken embryos were collected for scRNA-seq. (B) Illustration of the \ndeveloping structures captured:  pre -somitic mesoderm (psm), epithelial somites, maturing somites, \nlateral plate mesoderm (lpm), surface ectoderm, neural crest cells and notochord. (C) Schematic of the \n10X Genomics Chromium workflow. \nFigure 2: Cell population composition and signatures of the HH14 chicken embryo trunk.  (A) \nUnsupervised UMAP subdivides cells within the trunk into 10 clusters – lateral plate mesoderm, neural \nprogenitors, early somite, maturing somite, pre -somitic mesoderm, ectoderm, blood progenitors, \nendothelial progenitors and neural crest. (B) Heatmap of the top 10 genes significantly enriched in each \ncluster; representative genes are shown. (C) UMAPs show log normalised counts of representative \ngenes for each cluster. Colour intensity is proportional to expression level of each gene. (D) Distribution \nof cell cycle phases visualised using Seurat cell cycle scoring. \nFigure 3: Spatial sequencing reveals distinct gene expression profiles along the embryonic axis. \n(A) Stage HH14 chick embryo trunk was sectioned along the anterior -to-posterior axis, from \nextraembryonic tissue at the posterior end, through the tailbud and pre -somitic mesoderm towards \nmaturing somites. Individual sections were collected in wells follow ed by RNA isolation and cDNA \npreparation using section specific barcodes. After that, samples were pooled for linear amplification and \nsequence library prepara tion. (B) Spatial expression traces for representative genes in each \ncorresponding tissue type identified from the scRNA-seq clustering. \nFigure 4. K -means clustering identifies biological components along the posterior -to-anterior \naxis. (A) Hierarchical cluster analysis of gene expression per section (total 180). Distinct gene \nexpression clusters correspond to different regions along the axis, characterised by extraembryonic \ntissue, tailbud, pre -somitic mesoderm and epithelial somites – indicated by boxed areas. RNA \nsequencing reads per gene were normalised against the total read count per section. (B) Spatial \nexpression traces for representative genes in each corresponding cluster. (C) Gene ontology on genes \nenriched in the extraembryonic tissue, tailbud and pre -somitic mesoderm, and epithelial somites and \nneural tube. (D) Spatial expression traces for signalling pathways associated with ant erior-posterior \npatterning such as WNT ( Wnt5A), FGF (Fgf8) and  retinoic acid ( Aldh1A2); for genes associated with \nparaxial mesoderm differentiation (Meox1, Tcf15 and Mesp1); and for Hox genes involved in anterior-\nposterior patterning (Hoxd11, Hoxc9 and Hoxb1). (E) Dot plot showing average expression of genes \nand percentage expressed in each cell cluster associated with the WNT, FGF, NOTCH and BMP \nsignalling pathways. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 13 \nFigure 5: Transcriptome map of the embryonic trunk with high spatial resolution.  (A-C) UMAP \nplot and violin plot of representative genes for different tissues, with comparison to Spatial expression \ntrace along the posterior-to-anterior axis. The corresponding in situ hybridisation is shown for (A) Hbm \n– blood islands, (B) Wnt5A - tailbud, (C) Tbx22 – caudal somite halves. \nFigure 6: Differentially expressed genes in pre-somitic mesoderm and somites. (A) Sub-clustering \nidentifies specific genes within the psm, early somites and maturing somites. Psm is characterised by \nMSGN1 expression while Tcf15, Meox1 and Tbx22 markers represent somites. Restricted Fst \nexpression may correlate with epaxial myoblasts. (B-D) UMAP, violin plots and spatial expression traces \nshow expression for Foxd1, Olfml3 and Lrig3, not previously identified in somites.  Whole-mount in situ \nhybridisation confirmed the spatially restricted expression of Foxd1 and Olfml3 in epithelial and maturing \nsomites and of Lrig3 in the psm and somites. \n \n \n \n \n \n \n  \n  \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 14 \nReferences \nAbraira, V.E., Del Rio, T., Tucker, A.F., Slonimsky, J., Keirnes, H.L., Goodrich, L.V., 2008. Cross -\nrepressive interactions between Lrig3 and netrin 1 shape the architecture of the inner ear. Development \n135, 4091-4099. \nBenazeraf, B., Pourquie, O., 2013. Formation and segmentation of the vertebrate body axis. Annu Rev \nCell Dev Biol 29, 1-26. \nBrent, A.E., Tabin, C.J., 2002. Developmental regulation of somite derivatives: muscle, cartilage and \ntendon. Curr Opin Genet Dev 12, 548-557. \nBurkhard, S.B., Bakkers, J., 2018. Spatially resolved RNA-sequencing of the embryonic heart identifies \na role for Wnt/beta-catenin signaling in autonomic control of heart rate. Elife 7. \nButler, A., Hoffman, P., Smibert, P., Papalexi, E., Satija, R., 2018. Integrating single-cell transcriptomic \ndata across different conditions, technologies, and species. Nat Biotechnol 36, 411-420. \nChrist, B., Huang, R., Scaal, M., 2007. Amniote somite derivatives. Dev Dyn 236, 2382-2396. \nChrist, B., Scaal, M., 2008. Formation and differentiation of avian somite derivatives. Adv Exp Med Biol \n638, 1-41. \nFu, L., Hu, Y., Song, M., Liu, Z., Zhang, W., Yu, F.X., Wu, J., Wang, S., Izpisua Belmonte, J.C., Chan, \nP., Qu, J., Tang, F., Liu, G.H., 2019. Up -regulation of FOXD1 by YAP alleviates senescence and \nosteoarthritis. PLoS Biol 17, e3000201. \nGandhi, S., Bronner, M.E., 2018. Insights into neural crest development from studies of avian embryos. \nInt J Dev Biol 62, 183-194. \nGriffiths, J.A., Scialdone, A., Marioni, J.C., 2018. Using single -cell genomics to understand \ndevelopmental processes and cell fate decisions. Mol Syst Biol 14, e8046. \nGros, J., Scaal, M., Marcelle, C., 2004. A two-step mechanism for myotome formation in chick. Dev Cell \n6, 875-882. \nGuillot, C., Djeffal, Y., Michaut, A., Rabe, B., Pourquie, O., 2021. Dynamics of primitive streak regression \ncontrols the fate of neuromesodermal progenitors in the chicken embryo. Elife 10. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 15 \nHamburger, V., Hamilton, H.L., 1992. A series of normal stages in the development of the chick embryo. \n1951. Dev Dyn 195, 231-272. \nHenrique, D., Abranches, E., Verrier, L., Storey, K.G., 2015. Neuromesodermal progenitors and the \nmaking of the spinal cord. Development 142, 2864-2875. \nIbarra-Soria, X., Thierion, E., Mok, G.F., Munsterberg, A.E., Odom, D.T., Marioni, J.C., 2023. A \ntranscriptional and regulatory map of mouse somitogenesis. \nIimura, T., Yang, X., Weijer, C.J., Pourquie, O., 2007. Dual mode of paraxial mesoderm formation during \nchick gastrulation. Proc Natl Acad Sci U S A 104, 2744-2749. \nImhof, B.A., Ballet, R., Hammel, P., Jemelin, S., Garrido -Urbani, S., Ikeya, M., Matthes, T., Miljkovic -\nLicina, M., 2020. Olfactomedin -like 3 promotes PDGF -dependent pericyte proliferation and migration \nduring embryonic blood vessel formation. FASEB J 34, 15559-15576. \nInomata, H., Haraguchi, T., Sasai, Y., 2008. Robust stability of the embryonic axial pattern requires a \nsecreted scaffold for chordin degradation. Cell 134, 854-865. \nJin, Y., Li, J.L., 2019. Olfactomedin -like 3: possible functions in embryonic development and \ntumorigenesis. Chin Med J (Engl) 132, 1733-1738. \nJunker, J.P., Noel, E.S., Guryev, V., Peterson, K.A., Shah, G., Huisken, J., McMahon, A.P., Berezikov, \nE., Bakkers, J., van Oudenaarden, A., 2014. Genome-wide RNA Tomography in the zebrafish embryo. \nCell 159, 662-675. \nKoga, M., Matsuda, M., Kawamura, T., Sogo, T., Shigeno, A., Nishida, E., Ebisuya, M., 2014. Foxd1 is \na mediator and indicator of the cell reprogramming process. Nat Commun 5, 3197. \nKruse, F., Junker, J.P., van Oudenaarden, A., Bakkers, J., 2016. Tomo -seq: A method to obtain \ngenome-wide expression data with spatial resolution. Methods Cell Biol 135, 299-307. \nMacaulay, I.C., Teng, M.J., Haerty, W., Kumar, P., Ponting, C.P., Voet, T., 2016. Separation and parallel \nsequencing of the genomes and transcriptomes of single cells using G&T -seq. Nat Protoc 11, 2081 -\n2103. \nMcColl, J., Mok, G.F., Lippert, A.H., Ponjavic, A., Muresan, L., Munsterberg, A., 2018. 4D imaging \nreveals stage dependent random and directed cell motion during somite morphogenesis. Sci Rep 8, \n12644. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 16 \nMok, G.F., Folkes, L., Weldon, S.A., Maniou, E., Martinez -Heredia, V., Godden, A.M., Williams, R.M., \nSauka-Spengler, T., Wheeler, G.N., Moxon, S., Munsterberg, A.E., 2021. Characterising open \nchromatin in chick embryos identifies cis -regulatory elements im portant for paraxial mesoderm \nformation and axis extension. Nat Commun 12, 1157. \nMoris, N., Anlas, K., van den Brink, S.C., Alemany, A., Schroder, J., Ghimire, S., Balayo, T., van \nOudenaarden, A., Martinez Arias, A., 2020. An in vitro model of early anteroposterior organization during \nhuman development. Nature 582, 410-415. \nPourquie, O., 2004. The chick embryo: a leading model in somitogenesis studies. Mech Dev 121, 1069-\n1079. \nPsychoyos, D., Stern, C.D., 1996. Fates and migratory routes of primitive streak cells in the chick \nembryo. Development 122, 1523-1534. \nRito, T., Libby, A.R.G., Demuth, M., Briscoe, J., 2023. Notochord and axial progenitor generation by \ntimely BMP and NODAL inhibition during vertebrate trunk formation. bioRxiv. \nSanaki-Matsumiya, M., Matsuda, M., Gritti, N., Nakaki, F., Sharpe, J., Trivedi, V., Ebisuya, M., 2022. \nPeriodic formation of epithelial somites from human pluripotent stem cells. Nat Commun 13, 2325. \nSauka-Spengler, T., Barembaum, M., 2008. Gain- and loss-of-function approaches in the chick embryo. \nMethods Cell Biol 87, 237-256. \nStern, C.D., 2005. The chick; a great model system becomes even greater. Dev Cell 8, 9-17. \nSweetman, D., Wagstaff, L., Cooper, O., Weijer, C., Munsterberg, A., 2008. The migration of paraxial \nand lateral plate mesoderm cells emerging from the late primitive streak is controlled by different Wnt \nsignals. BMC Dev Biol 8, 63. \nTrevers, K.E., Lu, H.C., Yang, Y., Thiery, A.P., Strobl, A.C., Anderson, C., Palinkasova, B., de Oliveira, \nN.M.M., de Almeida, I.M., Khan, M.A.F., Moncaut, N., Luscombe, N.M., Dale, L., Streit, A., Stern, C.D., \n2023. A gene regulatory network for neural induction. Elife 12. \nTurner, D.A., Girgin, M., Alonso -Crisostomo, L., Trivedi, V., Baillie -Johnson, P., Glodowski, C.R., \nHayward, P.C., Collignon, J., Gustavsen, C., Serup, P., Steventon, B., M, P.L., Arias, A.M., 2017. \nAnteroposterior polarity and elongation in the absence of  extra-embryonic tissues and of spatially \nlocalised signalling in gastruloids: mammalian embryonic organoids. Development 144, 3894-3906. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 17 \nVeenvliet, J.V., Bolondi, A., Kretzmer, H., Haut, L., Scholze-Wittler, M., Schifferl, D., Koch, F., Guignard, \nL., Kumar, A.S., Pustet, M., Heimann, S., Buschow, R., Wittler, L., Timmermann, B., Meissner, A., \nHerrmann, B.G., 2020. Mouse embryonic stem cells self-organize into trunk-like structures with neural \ntube and somites. Science 370. \nVeenvliet, J.V., Herrmann, B.G., 2021. Modeling mammalian trunk development in a dish. Dev Biol 474, \n5-15. \nVermillion, K.L., Bacher, R., Tannenbaum, A.P., Swanson, S., Jiang, P., Chu, L.F., Stewart, R., \nThomson, J.A., Vereide, D.T., 2018. Spatial patterns of gene expression are unveiled in the chick \nprimitive streak by ordering single-cell transcriptomes. Dev Biol 439, 30-41. \nWeldon, S.A., Munsterberg, A.E., 2022. Somite development and regionalisation of the vertebral axial \nskeleton. Semin Cell Dev Biol 127, 10-16. \nWilliams, R.M., Lukoseviciute, M., Sauka -Spengler, T., Bronner, M.E., 2022. Single -cell atlas of early \nchick development reveals gradual segregation of neural crest lineage from the neural plate border \nduring neurulation. Elife 11. \nWilson, V., Olivera -Martinez, I., Storey, K.G., 2009. Stem cells, signals and vertebrate body axis \nextension. Development 136, 1591-1604. \nWu, C.C., Kruse, F., Vasudevarao, M.D., Junker, J.P., Zebrowski, D.C., Fischer, K., Noel, E.S., Grun, \nD., Berezikov, E., Engel, F.B., van Oudenaarden, A., Weidinger, G., Bakkers, J., 2016. Spatially \nResolved Genome-wide Transcriptional Profiling Identifies  BMP Signaling as Essential Regulator of \nZebrafish Cardiomyocyte Regeneration. Dev Cell 36, 36-49. \nWymeersch, F.J., Wilson, V., Tsakiridis, A., 2021. Understanding axial progenitor biology in vivo and in \nvitro. Development 148. \nXiong, F., Ma, W., Benazeraf, B., Mahadevan, L., Pourquie, O., 2020. Mechanical Coupling Coordinates \nthe Co-elongation of Axial and Paraxial Tissues in Avian Embryos. Dev Cell 55, 354-366 e355. \nYamanaka, Y., Hamidi, S., Yoshioka-Kobayashi, K., Munira, S., Sunadome, K., Zhang, Y., Kurokawa, \nY., Ericsson, R., Mieda, A., Thompson, J.L., Kerwin, J., Lisgo, S., Yamamoto, T., Moris, N., Martinez -\nArias, A., Tsujimura, T., Alev, C., 2023. Reconstituting human somitogenesis in vitro. Nature 614, 509-\n520. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 18 \nYang, X., Dormann, D., Munsterberg, A.E., Weijer, C.J., 2002. Cell movement patterns during \ngastrulation in the chick are controlled by positive and negative chemotaxis mediated by FGF4 and \nFGF8. Dev Cell 3, 425-437. \nZhao, H., Tanegashima, K., Ro, H., Dawid, I.B., 2008. Lrig3 regulates neural crest formation in Xenopus \nby modulating Fgf and Wnt signaling pathways. Development 135, 1283-1293. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 19 \n \n \nFigure 1: High -throughput scRNA-seq of the embryonic trunk.  (A) Trunk regions, indicated by \nstippled lines, of five stage HH14 chicken embryos were collected for scRNA-seq. (B) Illustration of the \ndeveloping structures captured:  pre -somitic mesoderm (psm), epithelial somites, maturing somites, \nlateral plate mesoderm (lpm), surface ectoderm, neural crest cells and notochord. (C) Schematic of the \n10X Genomics Chromium workflow. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 20 \n \nFigure 2: Cell population composition and signatures of the HH14 chicken embryo trunk.  (A) \nUnsupervised UMAP subdivides cells within the trunk into 10 clusters – lateral plate mesoderm, neural \nprogenitors, early somite, maturing somite, pre -somitic mesoderm, ectoderm, blood progenitors, \nendothelial progenitors and neural crest. (B) Heatmap of the top 10 genes significantly enriched in each \ncluster; representative genes are shown. (C) UMAPs show log normalised counts of representative \ngenes for each cluster. Colour intensity is proportional to expression level of each gene. (D) Distribution \nof cell cycle phases visualised using Seurat cell cycle scoring. \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 21 \n \nFigure 3: Spatial sequencing reveals distinct gene expression profiles along the embryonic axis. \n(A) Stage HH14 chick embryo trunk was sectioned along the anterior -to-posterior axis, from \nextraembryonic tissue at the posterior end, through the tailbud and pre -somitic mesoderm towards \nmaturing somites. Individual sections were collected in wells follow ed by RNA isolation and cDNA \npreparation using section specific barcodes. After that, samples were pooled for linear amplification and \nsequence library prepara tion. (B) Spatial expression traces for representative genes in each \ncorresponding tissue type identified from the scRNA-seq clustering. \n \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 22 \n \nFigure 4. K -means clustering identifies biological components along the posterior -to-anterior \naxis. (A) Hierarchical cluster analysis of gene expression per section (total 180). Distinct gene \nexpression clusters correspond to different regions along the axis, characterised by extraembryonic \ntissue, tailbud, pre -somitic mesoderm and epithelial somites – indicated by boxed areas. RNA \nsequencing reads per gene were normalised against the total read count per section. (B) Spatial \nexpression traces for representative genes in each corresponding cluster. (C) Gene ontology on genes \nenriched in the extraembryonic tissue, tailbud and pre -somitic mesoderm, and epithelial somites and \nneural tube. (D) Spatial expression traces for signalling pathways associated with ant erior-posterior \npatterning such as WNT ( Wnt5A), FGF (Fgf8) and retinoic acid (Aldh1A2); for genes associated with \nparaxial mesoderm differentiation (Meox1, Tcf15 and Mesp1); and for Hox genes involved in anterior-\nposterior patterning (Hoxd11, Hoxc9 and Hoxb1). (E) Dot plot showing average expression of genes \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 23 \nand percentage expressed in each cell cluster associated with the WNT, FGF, NOTCH and BMP \nsignalling pathways. \n \n \nFigure 5: Transcriptome map of the embryonic trunk with high spatial resolution.  (A-C) UMAP \nplot and violin plot of representative genes for different tissues, with comparison to Spatial expression \ntrace along the posterior-to-anterior axis. The corresponding in situ hybridisation is shown for (A) Hbm \n– blood islands, (B) Wnt5A - tailbud, (C) Tbx22 – caudal somite halves. \n \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint \n\n \n 24 \n \nFigure 6: Differentially expressed genes in pre-somitic mesoderm and somites. (A) Sub-clustering \nidentifies specific genes within the psm, early somites and maturing somites. Psm is characterised by \nMSGN1 expression while Tcf15, Meox1 and Tbx22 markers represent somites. Restricted Fst \nexpression may correlate with epaxial myoblasts. (B-D) UMAP, violin plots and spatial expression traces \nshow expression for Foxd1, Olfml3 and Lrig3, not previously identified in somites.  Whole-mount in situ \nhybridisation confirmed the spatially restricted expression of Foxd1 and Olfml3 in epithelial and maturing \nsomites and of Lrig3 in the psm and somites. \n \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted February 5, 2024. ; https://doi.org/10.1101/2024.02.05.578917doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}