{"doi":"10.1126/sciadv.adf3411","title":"A genome scale transcriptional regulatory model of the human placenta","abstract":"Gene regulation is essential to placental function and fetal development. We built a genome-scale transcriptional regulatory network (TRN) of the human placenta using digital genomic footprinting and transcriptomic data. We integrated 475 transcriptomes and 12 DNase hypersensitivity datasets from placental samples to globally and quantitatively map transcription factor (TF)–target gene interactions. In an independent dataset, the TRN model predicted target gene expression with an out-of-sample R 2 greater than 0.25 for 73% of target genes. We performed siRNA knockdowns of four TFs and achieved concordance between the predicted gene targets in our TRN and differences in expression of knockdowns with an accuracy of >0.7 for three of the four TFs. Our final model contained 113,158 interactions across 391 TFs and 7712 target genes and is publicly available. We identified 29 TFs which were significantly enriched as regulators for genes previously associated with preterm birth, and eight of these TFs were decreased in preterm placentas.","journal":"Science Advances","year":2024,"id":430760,"datarank":0.48883733970031645,"base_score":2.9444389791664403,"endowment":2.9444389791664403,"self_citation_contribution":0.44166584687496613,"citation_network_contribution":0.047171492825350346,"self_endowment_contribution":0.44166584687496613,"citer_contribution":0.047171492825350346,"corpus_percentile":60.87259224878162,"corpus_rank":5059,"citation_count":18,"citer_count":11,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9046,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":41.6667,"fair_percentile":54.173035768878016,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":707511,"name":"Kylia Ahuna","orcid":"0009-0001-5395-1091","position":1,"is_corresponding":false},{"id":993440,"name":"Yeon Mi Hwang","orcid":"0000-0002-4193-8623","position":2,"is_corresponding":false},{"id":242360,"name":"Jocelynn R. 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Bammler","orcid":null,"position":12,"is_corresponding":false},{"id":245211,"name":"Priyanka Baloni","orcid":"0000-0002-3382-4941","position":13,"is_corresponding":false},{"id":820400,"name":"Heather Brockway","orcid":"0000-0001-5690-7910","position":14,"is_corresponding":false},{"id":664615,"name":"W. Alex Mason","orcid":"0000-0002-8132-8045","position":15,"is_corresponding":false},{"id":275836,"name":"Nicole R. Bush","orcid":"0000-0003-0217-9975","position":16,"is_corresponding":false},{"id":275838,"name":"Kaja Z. LeWinn","orcid":"0000-0002-8245-7279","position":17,"is_corresponding":false},{"id":325491,"name":"Catherine J. Karr","orcid":"0000-0002-4683-2270","position":18,"is_corresponding":false},{"id":18775,"name":"J Stamatoyannopoulos","orcid":"0000-0002-2664-5769","position":19,"is_corresponding":false},{"id":40923,"name":"Louis J. Muglia","orcid":"0000-0002-0301-8770","position":20,"is_corresponding":false},{"id":332207,"name":"Helen Jones","orcid":"0000-0001-7356-8420","position":21,"is_corresponding":false},{"id":461892,"name":"Yoel Sadovsky","orcid":"0000-0003-2969-6737","position":22,"is_corresponding":false},{"id":302313,"name":"Leslie Myatt","orcid":"0000-0002-2569-7807","position":23,"is_corresponding":false},{"id":325493,"name":"Sheela Sathyanarayana","orcid":"0000-0002-1480-0397","position":24,"is_corresponding":false},{"id":33002,"name":"Nathan D. Price","orcid":"0000-0002-4157-0267","position":25,"is_corresponding":false},{"id":664613,"name":"Alison G. Paquette","orcid":"0000-0002-6065-9398","position":0,"is_corresponding":true}],"reference_count":103,"raw_metadata":null,"created_at":"2026-07-19T01:59:20.861374Z","pmid":"38941464","pmcid":"PMC11212735","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":38.8889,"fair_a":62.5,"fair_i":0.0,"fair_r":50.0,"fair_zscore":0.2857,"fair_rationale":{"fair_score":41.67,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":38.89,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"The RNA-seq data from MWRI are available on GEO (GSE245395).","grounded":false,"rationale":"The sentence gives a GEO accession (GSE245395), which is a persistent identifier scheme accepted by the FAIR criteria. 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DNase-seq data are available from the ENCODE consortium (GEO IDs: GEO: GSE170432 , GEO: GSE170970 , GEO: GSE170355 , GEO: GSE170943 , GEO: GSE170767 , GEO: GSE170640 , GEO: GSE170752 , GEO: GSE170385 , GEO: GSE170238 , GEO: GSE170099 , GEO: GSE16979 , and GEO: GSE170978 ). The RNA-seq data from MWRI are available on GEO (GSE245395). RNA-seq data from the siRNA knockdown experiments are available on GEO (GSE245394). RNA-seq data for the CANDLE cohort are available on dbGAP (dbGAP ID phs003619.v1).","grounded":false,"rationale":"The data availability statement points to multiple repositories (Zenodo, GEO, dbGaP) with accessions, placing it in Colavizza category 3 (link to archived data in public repository). 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Our final model was composed of 113,158 interactions between 391 TFs and 7712 target genes, including 75,014 positively correlated interactions and 38,144 negatively correlated interactions (Fig. 3A).","grounded":false,"rationale":"The dataset's content is described in running prose, not in an itemised inventory (section, table, or list). [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/5 passes agreed)]","anchors":["RDA-F2-01M — 'Rich metadata is provided to allow discovery' (priority Essential)","FsF-F2-01M — F-UJI: 'Metadata includes descriptive core elements to support data findability'","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'"],"scored":false,"signal":null},{"key":"f_dataset_cited","label":"Dataset formally cited","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"A. 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'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No licence is named for the data; the CC BY-NC license applies only to the article. [majority verdict 'no' (4/5 passes agreed)]","gain":16.67,"priority":"essential","scored":true},{"key":"f_dataset_pid","dimension":"F","label":"Persistent identifier for the data","action":"Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For genomics / sequencing data, deposit in GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The RNA-seq data from MWRI are available on GEO (GSE245395).","why":"The sentence gives a GEO accession (GSE245395), which is a persistent identifier scheme accepted by the FAIR criteria. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"f_repository_named","dimension":"F","label":"Named repository","action":"Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. 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Prefer open genomics / sequencing formats such as FASTQ, BAM or VCF.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No file format token is named for the released data.","gain":8.33,"priority":"important","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the genomics / sequencing repository accession (e.g. from GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA)) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"A. 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[majority verdict 'no' (2/5 passes agreed)]","gain":4.17,"priority":"useful","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All data needed to evaluate the conclusions in the paper are present in the Supplementary Materials and in data repositories. Specifically, the code has been published in Zenodo (103). 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Our final model was composed of 113,158 interactions between 391 TFs and 7712 target genes, including 75,014 positively correlated interactions and 38,144 negatively correlated interactions (Fig. 3A).","why":"The dataset's content is described in running prose, not in an itemised inventory (section, table, or list). [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In genomics / sequencing, describe the data with MIAME, MINSEQE or MIxS.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data or metadata community standard (e.g., MIAME, MINSEQE, GO) is named in the paper.","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Table 1. Covariate data from cohorts used for RNA-seq and DNase-seq data.","why":"Variable definitions are provided inside the article (Table 1) rather than in a separate documentation object shipped with the data. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No identifier for an external resource (other than the study's own data) is given in the text.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence in the paper states when the data become available or how long they persist; only current availability is mentioned. [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For genomics / sequencing data, deposit in GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA).","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For genomics / sequencing data, deposit in GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA).","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For genomics / sequencing data, deposit in GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA).","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open genomics / sequencing formats such as FASTQ, BAM or VCF."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T11:59:35.544885Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}