biostudies-arrayexpressNadezhda AzbukinaHomo sapienshttps://www.ebi.ac.uk/biostudies/studies/E-MTAB-15659Here, we generated multiome (coupled scRNA-seq and scATAC-seq) data over a time course of mid- and hindbrain organoid development to map cell composition and explore the regulatory mechanisms underlying cell type maturation. The dataset incorporates 5 time points from day 7 to day 120 from 3 human induced pluripotent stem cell (iPSC) lines using 2 previously established protocols. The protocols differentially generate ventral and dorsal cell types, and together cover regions such as floor-plate, dorsal and ventral midbrain, cerebellum, and additional parts of hindbrain. Comparing the data to a reference atlas of the developing human brain and to an integrated neural organoid cell atlas, we find that the gene regulatory architecture in organoid cells is predictive of primary counterparts and also that multiple regions are under-represented in existing organoid models.biostudies-arrayexpressSequencing - Libraries were sequenced according to 10x Multiome ATAC + Gene Expression kit protocol recommendations.Nucleic Acid Extraction - Single-nuclei suspension- generation and library preparation were performed according to the 10x Chromium Single Cell Multiome ATAC + Gene Expression kit protocol.Library Construction - Single-nuclei suspension- generation and library preparation were performed according to the 10x Chromium Single Cell Multiome ATAC + Gene Expression kit protocol.Sample Collection - Organoids of the three different cell lines were pooled on the basis of size and dissociated together, and the cell lines were later demultiplexed on the basis of the single-nucleotide polymorphism information. Multiple organoids of each line were pooled together to obtain a sufficient number of cells. If needed, on the later time points organoids were cut in halves and washed three times with HBSS without Ca2+ and Mg2+ (STEMCELL Technologies, 37250). Tissue dissociation to single cell suspension was done with a papain-based dissociation kit (Miltenyi Biotec, 130-092-628). Prewarmed papain solution (2 ml) was added to the organoids and incubated for 15 min at 37 °C. This was followed by enzyme mix A addition and then tissue pieces were triturated 5–10 times with 1,000 μl wide-bore and P1000 pipette tips. After that the tissue pieces were incubated twice for 10 min at 37 °C with trituration steps with P1000 and P200 pipette tips. After dissociation cells were filtered with 30 um filters and centrifuged. Before nuclei isolation, 100,000 cells were washed twice with 50 μL PBS containing 0.04% BSA. To isolate nuclei from the ready single-cell suspension, cells were resuspended in 50 μL lysis buffer (10 mM Tris-Cl pH7.4, 10 mM NaCl, 3 mM MgCl2, 1% BSA, 0.1% Tween-20, 1 mM DTT, 1U/μL RNase inhibitor (Roche Protector RNase-Inhibitor), 0.1% NP-40, 0.01% Digitonin (Invitrogen, BN2006)) and incubated for 3 minutes on ice, neutralized by adding 50 uL wash buffer (10 mM Tris-Cl pH7.4, 3 mM NaCl, 10 mM MgCl2, 1% BSA, 0.1% Tween-20, 1 mM DTT, 1U/μL RNase inhibitor).Growth Protocol - Brain organoids were generated from three different stem cell lines (WTC, WIBJ2, HOIK1) simultaneously. Brain organoids of the same batch were dissociated at multiple time points of the course of brain organoids development: neural induction (day 7) and neural differentiation and maturation (days 15, 30, 60, 90, 120).OrganizationMINSEQE ScoreAssays and DataProcessed DataMAGE-TAB FilesData Transformation - We used Cell Ranger ARC (v.2.0.0 with the default parameters to map the RNA-seq and ATAC-seq portion of the data to the human reference genome and gene annotation provided by 10x Genomics (GRCh38-2020-A-2.0.0). All samples were aggregated using the aggr command in Cell Ranger ARC to have the same list of accessible peaks being quantified for all cells. Both data modalities were read and further processed in R using Seurat (v.4.4.0)54 and Signac (v.1.1.1). As quality control, only cells satisfying the following criterias were remained: detected gene number between 1000 and 7500, percentage of mitochondrial transcripts less than 30%, detected ATAC-seq fragment number between 1000 and 30000, nucleosome signal less than 2.5 and TSS enrichment higher than 1. Nuclei from different stem cell lines were demultiplexed using the demuxlet55 tool. Genotyping information was downloaded from the HipSci (WIBJ2, HOIK1) or Allen Institute (WTC) website. Bcftools were used to merge all vcf files and sites with the same genotypes in all samples were filtered out. Demuxlet was run with default settings on transcriptomic and genomic reads. Cells with ambiguous assignments were classified as “Unknown”. For all other cells, the best singlet assignment was considered. To analyze the scRNA-seq modality, the standard log-normalization was firstly applied, and the top 3000 highly variable genes were identified. Subsequently, truncated principal component analysis (PCA) was performed with the scaled expression levels (across all cells) of highly variable genes as the input, using the RunPCA() function from the Seurat package. The first 20 principal components (PCs) were used to integrate different samples in the dataset (time point and protocol) using the CSS method51 (cluster_resolution=1.2). We performed UMAP56 to obtain a two-dimensional representation of data. We used the RunUMAP() function with default parameters using all components of the CSS matrix. For the scATAC-seq modality, the tf-idf (term frequency times inverse document frequency) normalization, implemented as the default normalization method in the Signac package for scATAC- seq data, was firstly applied. Singular value decomposition (SVD) was then performed using the RunSVD() function from the Signac package, to the normalized counts of the top peaks. The first 50 latent semantic indexes, except for the first one for its high correlation with numbers of fragments per cell, were used for scATAC-seq data integration using CSS method (cluster_resolution=0.8), followed by performing UMAP for low-dimensional data representation.MetabolomicsUnknownTranscriptomicsGenomicsProteomicsIllumina NovaSeq 6000Patterning of the neural tube establishes midbrain and hindbrain structures that coordinate motor movement, process sensory input, and integrate cognitive functions. Cellular impairment within these structures underlie diverse neurological disorders, and in vitro organoid models promise inroads to understand development, model disease, and assess therapeutics. Here, we use paired single-cell transcriptome and accessible chromatin sequencing to map cell composition and regulatory mechanisms in organoid models of midbrain and hindbrain. We find that existing midbrain organoid protocols generate ventral and dorsal cell types, and cover regions including floor plate, dorsal and ventral midbrain, as well as adjacent hindbrain regions, such as cerebellum. Gene regulatory network (GRN) inference and transcription factor perturbation resolve mechanisms underlying neuronal differentiation. A single-cell multiplexed patterning screen identifies morphogen concentration and combinations that expand existing organoid models, including conditions that generate medulla glycinergic neurons and cerebellum glutamatergic subtypes. Differential abundance of cell states across screen conditions enables differentiation trajectory reconstruction from region-specific progenitors towards diverse neuron types of mid- and hindbrain, which reveals morphogen-regulon regulatory relationships underlying neuronal fate specification. Altogether, we present a single-cell multi-omic atlas and morphogen screen of human neural organoid models of the posterior brain, advancing our understanding of the co-developmental dynamics of regions within the developing human brain.RNA-seq of coding RNA from single cellsHomo sapiensMulti-omic human neural organoid cell atlas of the posterior brainHsiu-Chuan LinZhisong HeNadezhda Azbukina, Zhisong He, Hsiu-Chuan Lin, Malgorzata Santel, Bijan Kashanian , Ashley Maynard, Tivadar Török, Ryoko Okamoto, Marina Nikolova, Sabina Kanton, Valentin Brösamle, Rene Holtackers, J. Gray Camp, Barbara TreutleinBarbara TreutleinNadezhda AzbukinafalsePosterior brain organoids multi-omics atlasHere, we generated multiome (coupled scRNA-seq and scATAC-seq) data over a time course of mid- and hindbrain organoid development to map cell composition and explore the regulatory mechanisms underlying cell type maturation. The dataset incorporates 5 time points from day 7 to day 120 from 3 human induced pluripotent stem cell (iPSC) lines using 2 previously established protocols. The protocols differentially generate ventral and dorsal cell types, and together cover regions such as floor-plate, dorsal and ventral midbrain, cerebellum, and additional parts of hindbrain. Comparing the data to a reference atlas of the developing human brain and to an integrated neural organoid cell atlas, we find that the gene regulatory architecture in organoid cells is predictive of primary counterparts and also that multiple regions are under-represented in existing organoid models.2026-03-17T00:00:00Z2026-03-17T02:03:49.313Z2025-10-06T11:50:58.201ZE-MTAB-15659ERP181055EFO_0002944EFO_0004170EFO_0003789EFO_0005684EFO_0005518EFO_0003816EFO_000418410.1101/2025.03.20.644368