biostudies-arrayexpressKatarzyna KoltowskaDanio reriohttps://www.ebi.ac.uk/biostudies/studies/E-MTAB-16797This dataset contains single-cell RNA sequencing (scRNA-seq) profiles of zebrafish venous and lymphatic endothelial cells across development. Endothelial cells were isolated by FACS from transgenic zebrafish embryos and larvae at 36 hpf, 48 hpf, 5 dpf (120 hpf), and 7 dpf (168 hpf) using endothelial reporters labeling fli1a-positive and lyve1b-positive endothelial populations, enriching for venous endothelial cells (VECs) and lymphatic endothelial cells (LECs). Transcriptomes were generated using Smart-Seq2. The dataset captures transcriptional heterogeneity across endothelial populations and developmental stages, including proliferating, differentiating, and mature LEC and VEC states during vascular development. These data were used in two studies. In Gloger et al., the dataset was used to identify transcriptional programs regulating spatio-temporal lymphatic endothelial cell proliferation, revealing a lineage-enriched LEC proliferation signature. In Panara, Arnold, Gloger et al., the scRNA-seq data were integrated with ATAC-seq and Hi-C datasets to define regulatory programs and chromatin organisation underlying lymphatic endothelial cell differentiation and gene regulation.biostudies-arrayexpressNucleic Acid Extraction - Single-cell cDNA libraries were prepared according to the previously described Smart Seq2 protocol (Vanlandewijck, M. & Betsholtz, C. Single-Cell mRNA Sequencing of the Mouse Brain Vasculature. Methods Mol. Biol. Clifton NJ 1846, 309–324 (2018)). In brief, mRNA was transcribed into cDNA using oligo(dT) primer and SuperScript II reverse transcriptase (ThermoFisher Scientific). Second strand cDNA was synthetized using a template switching oligo. The synthetized cDNA was then amplified by polymerase chain reaction (PCR) for 23–26 cycles, depending on the tissue-origin of the respective mRNA sample. Purified cDNA was quality controlled (QC) by analyzing on a TapeStation 4200 or 2100 Bioanalyzer with a DNA High Sensitivity chip (Agilent Biotechnologies).Sample Collection - Tg(-5.2lyve1b:Venus)uu1kk;Tg(fli1a:H2B-mCherry)uq37bh embryos were harvested at 36 hpf, 48 hpf, 5 dpf and 7 dpf. Heads were dissected by making an incision posterior of the otolithic lymph vessel. Trunks were dissected by making an incision posterior of the yolk and an incision posterior of the yolk extension. Isolation of cells was performed by dissociation of the whole embryos, heads and trunks. For the dissociation of zebrafish, we followed and optimized the protocol described by Kartopawiro et al., 2014 (Kartopawiro, J. et al. Arap3 is dysregulated in a mouse model of hypotrichosis-lymphedema-telangiectasia and regulates lymphatic vascular development. Hum. Mol. Genet. 23, 1286–1297 (2014)). Briefly, at the desired developmental stage, we deyolked embryos by pipetting up and down and rinsing in calcium-free ringer’s solution. Then, we centrifuged at 2000 rpm for 5 min at 4 °C and removed the supernatant. Following, we dissociated the cells by incubating whole embryos, heads and trunks in 2.5 mg/ml liberase (Sigma-Aldrich) diluted at a 1:35 ratio in DPBS at 28.5 °C. Thereby, whole embryos of 36 hpf and 48 hpf were incubated 7-8 min while 5 dpf and 7 dpf zebrafish were incubated 9-10 min, whereas heads and trunks of 36 hpf and 48 hpf embryos were incubated for 5 min while heads and trunks of 5 dpf and 7 dpf embryos were incubated for 7-8 min, homogenizing the samples during and after the incubation. To stop the reaction, we added CaCl2 to a final concentration of 1-2 mM and FBS to a final concentration of 5-10 %. We centrifuged at 2000 rpm for 5 min at 4 °C, discarded the supernatant. To assess live vs. dead cells, we resuspend the cell solution in 1 uM SytoxTM (Thermo Fisher Scientific) in DPBS/EDTA plus 0.5 % FBS. Cell suspension was filtered through a strainer and taken to the FACS sorting facility. The dissociated cells were sorted using a FACS Aria III (BD Biosciences) directly into buffered 384-well plates prepared by the Single Cell Core Facility of Flemingsberg Campus (SICOF) on a cold block. We based the selection for the desired populations on FSC and SCC, singlets, and alive cells based on their SytoxTM (Thermo Fisher Scientific) profile. Double-positive cells were sorted for both transgenes Tg(-5.2lyve1b:Venus)uu1kk and Tg(fli1a:H2B-mCherry)uq37bh (LECs and VECs). After sorting, the 384-well plates were snap-frozen on dry ice, stored at -80 °C before being shipped to the Single Cell Core Facility of Flemingsberg Campus (SICOF).Sequencing - Single-cell cDNA libraries were prepared according to the previously described Smart Seq2 protocol (Vanlandewijck, M. & Betsholtz, C. Single-Cell mRNA Sequencing of the Mouse Brain Vasculature. Methods Mol. Biol. Clifton NJ 1846, 309–324 (2018)). In brief, the uniquely indexed cDNA libraries from one 384-well plate were pooled into one sample to be sequenced on one lane of a HiSeq3000 sequencer (Illumina), one lane per plate, using dual indexing and single 50 base-pair reads.Library Construction - Single-cell cDNA libraries were prepared according to the previously described Smart Seq2 protocol (Vanlandewijck, M. & Betsholtz, C. Single-Cell mRNA Sequencing of the Mouse Brain Vasculature. Methods Mol. Biol. Clifton NJ 1846, 309–324 (2018)). In brief, when the sample passed the QC, the cDNA was fragmented and tagged (tagmented) using Tn5 transposase, and each single well was uniquely indexed using the Illumina Nextera XT index kits (Set A-D).OrganizationMINSEQE ScoreAssays and DataMAGE-TAB FilesData Transformation - The reads were aligned to the zebrafish genome (GRCz11) and spike-in sequences (from the External RNA Controls Consortium, ERCC92) using STAR v2.5.3a (Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinforma. Oxf. Engl. 29, 15–21 (2013)), and filtered for uniquely mapping reads. Counts per gene were calculated for each transcript in Ensembl release 97 using rpkmforgenes (Ramsköld, D., Wang, E. T., Burge, C. B. & Sandberg, R. An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput. Biol. 5, e1000598 (2009)). Various QC metrics were generated with RSeQC 2.6.1 (Wang, L., Wang, S. & Li, W. RSeQC: quality control of RNA-seq experiments. Bioinforma. Oxf. Engl. 28, 2184–2185 (2012)).MetabolomicsUnknownTranscriptomicsGenomicsProteomicsAria III (BD Biosciences)oligo(dT) primer and SuperScript II reverse transcriptase (ThermoFisher Scientific), TapeStation 4200 or 2100 Bioanalyzer with a DNA High Sensitivity chip (Agilent Biotechnologies)STAR v2.5.3a, rpkmforgenes, RSeQC 2.6.1Illumina Nextera XT index kits (Set A–D)Illumina HiSeq 3000<title>Abstract</title> <p>Cell proliferation is central to the proper formation of functional and healthy organs. Although cells divide in all tissues during embryogenesis, how the spatio-temporal control of lymphatic endothelial cell (LEC) number expansion is achieved, remains to be determined. Our comprehensive whole organism time-course analysis has uncovered that spatially restricted LEC proliferation bursts contribute to the morphogenesis of distinct lymphatic vascular beds in zebrafish during embryonic and larval development. Mechanistically, Vegfc-Vegfr3 signalling is necessary and sufficient for LEC proliferation and regulates cell cycle length. Using single-cell transcriptomics, we discover a cohort of genes that generate the unique LEC proliferation code, which is lineage-enriched during the cell proliferation bursts. We confirmed that FKBP1A and LBR are required for endothelial cell proliferation in human primary cell lines. Similarly, the conservation of the lineage-enriched cell proliferation code is present in mouse endothelial cells, whereas in Pik3ca-driven endothelial cell pathologies the cell proliferation code loses its cell type specificity. Thus, our data uncover promising new candidates behind the mechanisms regulating lineage cell number expansion, which could be relevant to future strategies for modulating lymphatic cell proliferation in homeostasis or disease.</p>The activation and repression of genes is a fundamental part of proper embryonic development and functional tissue formation, ensuring that unique molecular codes are set up to orchestrate cell differentiation. Changes in chromatin organisation dictate accessibility to gene regulatory elements and control gene expression. Several molecular factors regulating lymphatic endothelial cell (LEC) specification and differentiation have been identified. However, it remains to be defined how chromatin is organised in lymphatic endothelium and how it orchestrates lymphatic vessel network formation. In this study, we combined Hi-C and ATAC-sequencing to characterise 3D chromatin architecture and accessibility in LECs and blood endothelial cells (BECs). We have identified cell type-specific topologically associated domains (TADs) in LECs and BECs. Specifically, our data revealed changes in the TAD boundaries and differentially segregating enhancers regions in lymphatic-associated loci, such as prox1a and tbx1 . This multi-omic approach also defined the regulatory logic for nine genes whose expression is enriched in LECs. In vivo validation of their short- and long-range enhancers confirmed their LEC-confined activity. Leveraging these datasets, we reconstructed mafba tissue-specific regulatory networks and identified a genetic interaction with tfe3a in vivo necessary to limit ectopic vessel formation. Overall, our work provides a powerful resource of multi-omic datasets that can be used to systematically determine the regulatory networks governing LEC identity and genes linked to lymphatic disease.RNA-seq of coding RNA from single cellsDanio rerioDistinct topologically associated domains underlie regulatory logic in lymphatic endothelial cells contributing to proper cell differentiationLineage-enriched cell proliferation code underlies spatio-temporal regulation of cell cycle dynamics in lymphatic vesselsKatarzyna KoltowskaMarleen GlogerVirginia Panara*, Hannah Arnold*, Marleen Gloger*, Renae Skoczylas, Victoria Vidal Gutierrez, Anna Johansson, Agata Smialowska, Katarzyna Koltowska#.Marleen Gloger*, Claudia Carlantoni, Marle Kraft, Di Peng, Alicja Ebert, Renae Skoczylas, Anna Johansson, Agata Smialowska, Ross Smith, Armand Stoe, Beata Filipek-Gorniok, Thomas Juan, Taija Mäkinen, Maike Frye, Katarzyna Koltowska#falseSingle-cell RNA sequencing data of zebrafish lymphatic and venous endothelial cells at different developmental stages (36 hpf, 48 hpf, 120 hpf (5 dpf) and 168 hpf (7 dpf))This dataset contains single-cell RNA sequencing (scRNA-seq) profiles of zebrafish venous and lymphatic endothelial cells across development. Endothelial cells were isolated by FACS from transgenic zebrafish embryos and larvae at 36 hpf, 48 hpf, 5 dpf (120 hpf), and 7 dpf (168 hpf) using endothelial reporters labeling fli1a-positive and lyve1b-positive endothelial populations, enriching for venous endothelial cells (VECs) and lymphatic endothelial cells (LECs). Transcriptomes were generated using Smart-Seq2. The dataset captures transcriptional heterogeneity across endothelial populations and developmental stages, including proliferating, differentiating, and mature LEC and VEC states during vascular development. These data were used in two studies. In Gloger et al., the dataset was used to identify transcriptional programs regulating spatio-temporal lymphatic endothelial cell proliferation, revealing a lineage-enriched LEC proliferation signature. In Panara, Arnold, Gloger et al., the scRNA-seq data were integrated with ATAC-seq and Hi-C datasets to define regulatory programs and chromatin organisation underlying lymphatic endothelial cell differentiation and gene regulation.2026-09-28T00:00:00Z2026-09-28T06:57:41.685Z2026-04-10T11:41:51.16ZE-MTAB-16797ERP191979EFO_0002944EFO_0004170EFO_0005684EFO_0005518EFO_0003816EFO_000418410.21203/rs.3.rs-5333191/v110.1101/2025.06.16.659849