{"doi":"10.1126/science.adi5199","title":"Single-cell genomics and regulatory networks for 388 human brains","abstract":"Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. 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Galeev","orcid":"0000-0002-6241-1011","position":14,"is_corresponding":false},{"id":851786,"name":"Ahyeon Hwang","orcid":"0000-0002-4686-3077","position":15,"is_corresponding":false},{"id":1200614,"name":"Yunyang Li","orcid":null,"position":16,"is_corresponding":false},{"id":21455,"name":"Pengyu Ni","orcid":"0000-0001-9878-5480","position":17,"is_corresponding":false},{"id":227468,"name":"Xiao Zhou","orcid":"0000-0002-8933-444X","position":18,"is_corresponding":false},{"id":38316,"name":"Trygve E. Bakken","orcid":"0000-0003-3373-7386","position":19,"is_corresponding":false},{"id":284407,"name":"Jaroslav Bendl","orcid":"0000-0001-9989-2720","position":20,"is_corresponding":false},{"id":21369,"name":"Lucy Bicks","orcid":"0000-0002-9884-0133","position":21,"is_corresponding":false},{"id":1199592,"name":"Tanima Chatterjee","orcid":"0000-0001-8956-6569","position":22,"is_corresponding":false},{"id":12288,"name":"Lijun Cheng","orcid":"0000-0001-7606-9563","position":23,"is_corresponding":false},{"id":21376,"name":"Yuyan Cheng","orcid":"0000-0003-4647-4917","position":24,"is_corresponding":false},{"id":758530,"name":"Yi Dai","orcid":"0000-0003-1219-2436","position":25,"is_corresponding":false},{"id":21388,"name":"Ziheng Duan","orcid":"0000-0003-4696-0042","position":26,"is_corresponding":false},{"id":1199593,"name":"Mary Flaherty","orcid":"0009-0002-9931-7122","position":27,"is_corresponding":false},{"id":284413,"name":"John F. Fullard","orcid":"0000-0001-9874-2907","position":28,"is_corresponding":false},{"id":1200615,"name":"Michael Gancz","orcid":null,"position":29,"is_corresponding":false},{"id":29303,"name":"Diego Garrido-Martín","orcid":"0000-0002-4131-4458","position":30,"is_corresponding":false},{"id":1199594,"name":"Sophia C. Gaynor-Gillett","orcid":"0009-0001-7242-350X","position":31,"is_corresponding":false},{"id":21401,"name":"Jennifer Grundman","orcid":"0000-0003-2266-277X","position":32,"is_corresponding":false},{"id":21407,"name":"Natalie Hawken","orcid":"0000-0002-0473-4373","position":33,"is_corresponding":false},{"id":1200616,"name":"Ella Henry","orcid":null,"position":34,"is_corresponding":false},{"id":1202,"name":"Gabriel E. Hoffman","orcid":"0000-0002-0957-0224","position":35,"is_corresponding":false},{"id":1199595,"name":"Ao Huang","orcid":"0000-0002-8665-4683","position":36,"is_corresponding":false},{"id":19719,"name":"Yunzhe Jiang","orcid":"0000-0001-8768-0050","position":37,"is_corresponding":false},{"id":474874,"name":"Ting Jin","orcid":"0000-0001-5073-0667","position":38,"is_corresponding":false},{"id":38317,"name":"Nikolas L. Jorstad","orcid":"0000-0001-7906-9470","position":39,"is_corresponding":false},{"id":226817,"name":"Riki Kawaguchi","orcid":"0000-0002-2489-4825","position":40,"is_corresponding":false},{"id":640878,"name":"Saniya Khullar","orcid":"0000-0002-4166-874X","position":41,"is_corresponding":false},{"id":1162126,"name":"Jianyin Liu","orcid":null,"position":42,"is_corresponding":false},{"id":1199596,"name":"Junhao Liu","orcid":"0009-0007-3694-7799","position":44,"is_corresponding":false},{"id":291112,"name":"Shuang Liu","orcid":"0000-0001-5548-8494","position":46,"is_corresponding":false},{"id":21437,"name":"Shaojie Ma","orcid":"0000-0002-8782-3047","position":47,"is_corresponding":false},{"id":21439,"name":"Michael Margolis","orcid":"0000-0002-3706-8960","position":48,"is_corresponding":false},{"id":21442,"name":"Samantha Mazariegos","orcid":"0009-0000-1762-6454","position":49,"is_corresponding":false},{"id":21450,"name":"Jill E. 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Riesenmy","orcid":"0009-0006-2048-0744","position":58,"is_corresponding":false},{"id":1199598,"name":"Nicole Shedd","orcid":"0000-0003-2272-5398","position":59,"is_corresponding":false},{"id":1200617,"name":"Manman Shi","orcid":null,"position":60,"is_corresponding":false},{"id":1200618,"name":"Megan Spector","orcid":null,"position":61,"is_corresponding":false},{"id":1200619,"name":"Rosemarie Terwilliger","orcid":null,"position":62,"is_corresponding":false},{"id":12147,"name":"Kyle J. Travaglini","orcid":"0000-0003-3164-6448","position":63,"is_corresponding":false},{"id":21494,"name":"Brie Wamsley","orcid":"0000-0002-4454-9834","position":64,"is_corresponding":false},{"id":1199599,"name":"Gaoyuan Wang","orcid":"0000-0003-4039-748X","position":65,"is_corresponding":false},{"id":415932,"name":"Yan Xia","orcid":"0000-0001-6432-9911","position":66,"is_corresponding":false},{"id":346203,"name":"Shaohua Xiao","orcid":null,"position":67,"is_corresponding":false},{"id":565087,"name":"Andrew C. 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[majority verdict 'no' (4/5 passes agreed)]","anchors":["NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines","NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy'","RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":40.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No file format is named for the released data in the main text.","anchors":["FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co","RDA-R1.3-02D — data is expressed in a machine-understandable community standard","RDA-I1-01D — data uses a knowledge representation expressed in a standardised format"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"BICCN-compatible cell-typing system","grounded":true,"rationale":"The paper names BICCN, a community standard for cell typing. 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A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No version token or date is given for the data snapshot.","gain":4.17,"priority":"useful","scored":true},{"key":"f_discovery_metadata","dimension":"F","label":"Description of the dataset as an object","action":"Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The resource can be summarized at multiple levels: (1) raw data and metadata with a harmonized identifier system for each of the individuals; (2) quantifications of single-cell gene expression (count matrices) with a BICCN-compatible cell-typing system for the PFC; (3) lists of DE genes and differential cell-fractions for various phenotypes; (4) snATAC-seq signal tracks for various cell types and ENCODE-compatible regulatory elements (b-cCREs and scCREs), including lists of validated ones; (5) the variability for each gene and functional category (by individual, cell type, and brain region) and the associated sequence conservation of genes and regulatory elements; (6) a core set of GTEx-compatible scQTLs and other additional sets of QTLs (such as dynamic eQTLs); (7) full GRNs for each cell type, including enhancer-to-gene and TF-to-regulatory element links, and associated files relating each downstream gene to its most significant upstream regulators; (8) cell-to-cell communication networks (expressed as ligand-receptor- by-cell-type matrices); (9) integrative models with code for imputation, perturbation and prioritization of cell-type-specific functional genomics in brain disease; and (10) the resulting prioritized genes, cell types, and cell-to-cell linkages.","why":"The paper provides an itemised inventory of the dataset components in the Discussion section. 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