<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Gaja Matassa</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-17185</full_dataset_link><description>Bulk RNA sequencing (bulk RNA-seq) data of the Neural Organoid Hormonal Atlas (NOHA). To investigate the impact of hormonal modulation on neurodevelopmental processes, we used neural organoids derived from two genetically validated human induced pluripotent stem cell (hiPSC) control lines (CTL08, male; CTL04, female). Organoids were chronically exposed to agonists and inhibitors targeting seven hormone signaling pathways known to regulate human brain development: androgen, estrogen, glucocorticoid, thyroid, retinoic acid, liver X, and aryl hydrocarbon. Appropriate negative controls were included, consisting of vehicle-treated (DMSO) and untreated samples (CTL).  GitHub: https://github.com/GiuseppeTestaLab/noha</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - Neural organoids were harvested at DIV 50 into 2ml Eppendorf tubes and washed three times with 1.5 ml PBS to remove medium residues before being snap-frozen and stored at -80 °C for a maximum of 1 month before RNA extraction. For each of the replicates, 1 organoid was collected unless size constraints required the pooling of multiple organoids</sample_protocol><sample_protocol>Nucleic Acid Extraction - After thawing the pellets on ice, RNA was extracted using the PureLink RNA Mini kit (Thermofisher, 12183025) and eluted in 30ul of RNAse free water. On-column DNAse I treatment was performed with RNAse-free DNase set (Qiagen, 79265) according to protocol recommendations. Purified RNA was quantified with Nanodrop One (Thermofisher) to estimate the concentration range, while the RNA Integrity Index (RIN) was measured by TapeStation analysis. A RIN >7.5 (scale 1-10) was chosen as a cutoff for further sample processing. Samples with RIN &lt;7.5 were discarded and RNA was re-extracted from backup pellets.</sample_protocol><sample_protocol>Sequencing - Samples were sequenced in paired-end configuration with a target coverage of 35 million reads/sample.</sample_protocol><sample_protocol>Library Construction - RNA concentration was then normalized, and cDNA libraries were prepared using Illumina Stranded mRNA Prep with polyA-capture technology with an initial RNA input of 100 ng/sample</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - FASTQ files for the CTL08 line are partially processed. Due to legal constraints associated with this human cell line, read pairs mapping to chromosome Y were removed prior to public submission. Reads were aligned to the human reference genome to identify chromosome Y-associated reads, and the remaining mapped reads were exported back to FASTQ format.</data_protocol><data_protocol>Data Transformation - Gene-level count matrices were generated using Salmon v1.3.0 with Human GENCODE Release 35 (GRCh38.p13) as the reference. Count matrices were subsequently filtered to retain only protein-coding genes.</data_protocol><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq 6000</instrument_platform><pubmed_abstract>Hormonal signalling shapes the development of the human brain and its disruption is implicated in various neuropsychiatric conditions. However, a comprehensive and mechanistic understanding of how hormonal pathways orchestrate human neurodevelopment remains elusive. Here we present a multi-scale high resolution atlas of endocrine signalling in human neural organoids through systematic perturbations with agonists and inhibitors of seven key hormonal pathways: androgen (AND), estrogen (EST), glucocorticoid (GC), thyroid (THY), retinoic acid (RA), liver X (LX), and aryl hydrocarbon (AH). By integrating bulk and single-cell transcriptomics, high-throughput imaging and targeted steroidomics, we mapped the molecular and cellular consequences of their physiologically relevant perturbations. Retinoic acid exerted the most profound effect, promoting neuronal differentiation and maturation, consistent with its established role as a patterning factor. Our analysis further benchmarked neural organoids for in vitro endocrinology and neurotoxicology by confirming previously reported  in vivo effects, such as induction of mTOR signalling by AND, alteration of disease relevant genes by GC and enhanced differentiation by TH. Furthermore, we observed that LX activation upregulates genes involved in cholesterol metabolism while AH inhibition promotes neuronal differentiation. We next uncovered extensive crosstalks between these endocrine pathways, as in the paradigmatic convergence induced by AND agonist and inhibitors of GC, TH, and LX, affecting genes related to protein folding and metabolic regulation, as also highlighted by weighted gene co-expression network analysis. Single-cell analyses pinpointed cell-type-specific responses to hormonal challenges, such as the caudalization of progenitors and neurons upon RA activation and the depletion of specific neurodevelopmental states upon AH activation. Finally, we dissected the cytoarchitectural and morphometric impact of hormonal perturbations and demonstrated that neural organoids possess active steroidogenic pathways that are functionally modulated by the tested compounds. This atlas provides a systematic quantification of the hormonal impact on human neurodevelopment, enabling the investigation of uncharted aspects in the developmental origins of neuropsychiatric traits. Through the empowering architecture of its knowledge base for iterative adoption by the community, this resource will thus be key to probe how environmental factors and genetic endocrine vulnerabilities contribute to neurodevelopmental outcomes, as well as to train advanced generative models for improving their predictive power on gene environment interactions in human neurodevelopment.</pubmed_abstract><study_type>RNA-seq of coding RNA</study_type><species>Homo sapiens</species><pubmed_title>A molecular cell atlas of endocrine signalling in human neural organoids</pubmed_title><pubmed_authors>Gaja Matassa</pubmed_authors><pubmed_authors>Gaja Matassa, Marco Tullio Rigoli, Davide Castaldi, Alessia Valenti, Manuel Lessi, Nicolò Caporale, Sarah Stucchi, Benedetta Muda, Riccardo Nagni, Lisa Mainardi, Alessandro Melon, Amaia Tintori, Davide Bulgheresi, Michal Kubacki, Sebastiano Trattaro, Sara Evangelista, Pim Leonards, Human Cell Atlas Organoid Biological Network, Carlo Emanuele Villa, Cristina Cheroni, Giuseppe Testa</pubmed_authors></additional><is_claimable>false</is_claimable><name>bulk RNA-seq NOHA</name><description>Bulk RNA sequencing (bulk RNA-seq) data of the Neural Organoid Hormonal Atlas (NOHA). To investigate the impact of hormonal modulation on neurodevelopmental processes, we used neural organoids derived from two genetically validated human induced pluripotent stem cell (hiPSC) control lines (CTL08, male; CTL04, female). Organoids were chronically exposed to agonists and inhibitors targeting seven hormone signaling pathways known to regulate human brain development: androgen, estrogen, glucocorticoid, thyroid, retinoic acid, liver X, and aryl hydrocarbon. Appropriate negative controls were included, consisting of vehicle-treated (DMSO) and untreated samples (CTL).  GitHub: https://github.com/GiuseppeTestaLab/noha</description><dates><release>2026-07-22T00:00:00Z</release><modification>2026-07-22T01:01:05.469Z</modification><creation>2026-06-18T14:38:47.642Z</creation></dates><accession>E-MTAB-17185</accession><cross_references><ENA>ERP195330</ENA><doi>10.1101/2025.08.14.669814</doi><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>