| Name | H4 clustered histone 7 |
| Description | Histones are basic nuclear proteins that are responsible for the nucleosome structure of the chromosomal fiber in eukaryotes. Two molecules of each of the four core histones (H2A, H2B, H3, and H4) form an octamer, around which approximately 146 bp of DNA is wrapped in repeating units, called nucleosomes. The linker histone, H1, interacts with linker DNA between nucleosomes and functions in the compaction of chromatin into higher order structures. This gene is intronless and encodes a replication-dependent histone that is a member of the histone H4 family. Transcripts from this gene lack polyA tails but instead contain a palindromic termination element. This gene is found in the large histone gene cluster on chromosome 6. [provided by RefSeq, Aug 2015] |
| Summary |
{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n Studies using H4‐based systems have been instrumental in elucidating the molecular mechanisms that regulate amyloid precursor protein (APP) processing and its pathogenic by‐product, amyloid‐β (Aβ), in Alzheimer’s disease (AD). In human neuroglioma H4 cells engineered to express full‐length APP or its C99 fragment, RNA interference targeting key APP adaptor proteins—such as Dab, Numb, ShcC, and Fe65—resulted in altered APP C‐terminal fragment accumulation and Aβ production. For example, knock‐down of Dab and Numb impaired γ‐secretase processing of APP, leading to increased APP C‐terminal fragments and reduced Aβ generation, suggesting that disruption of APP–adaptor interactions might offer a more selective therapeutic strategy than broad γ‐secretase inhibition."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": " Similarly, silencing ShcC diminished both APP‐CTF and Aβ levels while also lowering BACE expression, and Fe65 knock‐down led to increased APP‐CTFs with concomitant Aβ reduction, underscoring the nuanced role these interactions play in modulating APP catabolism."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "2"}]}, {"type": "t", "text": ""}]}, {"type": "t", "text": "\n \n "}, {"type": "p", "children": [{"type": "t", "text": "\n In parallel, fluorescent reporter constructs derived from H4 domains have been introduced as tools to monitor enzyme–substrate interactions. In one study, reporters such as H4‐FL were employed to track the binding and methylation activities of protein arginine methyltransferase 1 (PRMT1), offering a rapid readout for substrate engagement and providing a platform to evaluate inhibitors that block these events."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "3"}]}, {"type": "t", "text": "\n "}]}, {"type": "t", "text": "\n \n "}, {"type": "p", "children": [{"type": "t", "text": "\n Although other research has also focused on emerging biomarkers—such as microRNAs in AD—and on infectious etiologies implicated in carcinogenesis"}, {"type": "fg", "children": [{"type": "fg_f", "ref": "4"}]}, {"type": "t", "text": ", the H4‐based cellular models and reporters remain pivotal. They not only reveal critical regulatory interactions that influence APP processing and Aβ formation but also provide innovative avenues for screening potential therapeutic agents aimed at modulating these disease‐relevant pathways.\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Zhongcong Xie, Yuanlin Dong, Uta Maeda, et al. "}, {"type": "b", "children": [{"type": "t", "text": "RNAi-mediated knock-down of Dab and Numb attenuate Aβ levels via γ-secretase mediated APP processing."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Transl Neurodegener (2012)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/2047-9158-1-8"}], "href": "https://doi.org/10.1186/2047-9158-1-8"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "23211096"}], "href": "https://pubmed.ncbi.nlm.nih.gov/23211096"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Zhongcong Xie, Yuanlin Dong, Uta Maeda, et al. "}, {"type": "b", "children": [{"type": "t", "text": "RNA interference silencing of the adaptor molecules ShcC and Fe65 differentially affect amyloid precursor protein processing and Abeta generation."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "J Biol Chem (2007)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1074/jbc.M609293200"}], "href": "https://doi.org/10.1074/jbc.M609293200"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "17170108"}], "href": "https://pubmed.ncbi.nlm.nih.gov/17170108"}]}, {"type": "r", "ref": 3, "children": [{"type": "t", "text": "You Feng, Nan Xie, Jiang Wu, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Inhibitory study of protein arginine methyltransferase 1 using a fluorescent approach."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Biochem Biophys Res Commun (2009)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1016/j.bbrc.2008.12.119"}], "href": "https://doi.org/10.1016/j.bbrc.2008.12.119"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "19121292"}], "href": "https://pubmed.ncbi.nlm.nih.gov/19121292"}]}, {"type": "r", "ref": 4, "children": [{"type": "t", "text": "Manasa Basavaraju, Alexandre de Lencastre "}, {"type": "b", "children": [{"type": "t", "text": "Alzheimer's disease: presence and role of microRNAs."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Biomol Concepts (2016)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1515/bmc-2016-0014"}], "href": "https://doi.org/10.1515/bmc-2016-0014"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "27505094"}], "href": "https://pubmed.ncbi.nlm.nih.gov/27505094"}]}, {"type": "r", "ref": 5, "children": [{"type": "t", "text": "Brent A Stanfield, Micah A Luftig "}, {"type": "b", "children": [{"type": "t", "text": "Recent advances in understanding Epstein-Barr virus."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "F1000Res (2017)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.12688/f1000research.10591.1"}], "href": "https://doi.org/10.12688/f1000research.10591.1"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "28408983"}], "href": "https://pubmed.ncbi.nlm.nih.gov/28408983"}]}]}]}
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| NCBI Gene ID | 8369 |
| API | |
| Download Associations | |
| Predicted Functions |
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| Co-expressed Genes |
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| Expression in Tissues and Cell Lines |
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H4C7 has 2,983 functional associations with biological entities spanning 5 categories (chemical, functional term, phrase or reference, disease, phenotype or trait, cell line, cell type or tissue, gene, protein or microRNA) extracted from 17 datasets.
Click the + buttons to view associations for H4C7 from the datasets below.
If available, associations are ranked by standardized value
| Dataset | Summary | |
|---|---|---|
| Allen Brain Atlas Aging Dementia and Traumatic Brain Injury Tissue Sample Gene Expression Profiles | tissue samples with high or low expression of H4C7 gene relative to other tissue samples from the Allen Brain Atlas Aging Dementia and Traumatic Brain Injury Tissue Sample Gene Expression Profiles dataset. | |
| Carcinogenome Chemical Perturbation Carcinogenicity Signatures | small molecule perturbations changing expression of H4C7 gene from the Carcinogenome Chemical Perturbation Carcinogenicity Signatures dataset. | |
| CM4AI KOLF21J CRISPRi Gene Perturbation Atlas | gene perturbations changing expression of H4C7 gene from the CM4AI KOLF21J CRISPRi Gene Perturbation Atlas dataset. | |
| COMPARTMENTS Text-mining Protein Localization Evidence Scores 2025 | cellular components co-occuring with H4C7 protein in abstracts of biomedical publications from the COMPARTMENTS Text-mining Protein Localization Evidence Scores 2025 dataset. | |
| DISEASES Experimental Gene-Disease Association Evidence Scores 2025 | diseases associated with H4C7 gene in GWAS datasets from the DISEASES Experimental Gene-Disease Assocation Evidence Scores 2025 dataset. | |
| DISEASES Text-mining Gene-Disease Association Evidence Scores 2025 | diseases co-occuring with H4C7 gene in abstracts of biomedical publications from the DISEASES Text-mining Gene-Disease Assocation Evidence Scores 2025 dataset. | |
| GO Biological Process Annotations 2025 | biological processes involving H4C7 gene from the curated GO Biological Process Annotations2025 dataset. | |
| GO Cellular Component Annotations 2025 | cellular components containing H4C7 protein from the curated GO Cellular Component Annotations 2025 dataset. | |
| GWAS Catalog SNP-Phenotype Associations 2025 | phenotypes associated with H4C7 gene in GWAS datasets from the GWAS Catalog SNP-Phenotype Associations 2025 dataset. | |
| JASPAR Predicted Human Transcription Factor Targets 2025 | transcription factors regulating expression of H4C7 gene predicted using known transcription factor binding site motifs from the JASPAR Predicted Human Transcription Factor Targets dataset. | |
| KEGG Pathways 2026 | pathways involving H4C7 protein from the KEGG Pathways 2026 dataset. | |
| LINCS L1000 CMAP Chemical Perturbation Consensus Signatures | small molecule perturbations changing expression of H4C7 gene from the LINCS L1000 CMAP Chemical Perturbations Consensus Signatures dataset. | |
| PFOCR Pathway Figure Associations 2024 | pathways involving H4C7 protein from the Wikipathways PFOCR 2024 dataset. | |
| Rummagene Transcription Factor Associations 2026 | transcription factors regulating expression of H4C7 gene from the Rummagene Transcription Factor Associations 2026 dataset. | |
| TISSUES Experimental Tissue Protein Expression Evidence Scores 2025 | tissues with high expression of H4C7 protein in proteomics datasets from the TISSUES Experimental Tissue Protein Expression Evidence Scores 2025 dataset. | |
| TISSUES Text-mining Tissue Protein Expression Evidence Scores 2025 | tissues co-occuring with H4C7 protein in abstracts of biomedical publications from the TISSUES Text-mining Tissue Protein Expression Evidence Scores 2025 dataset. | |
| WikiPathways Pathways 2024 | pathways involving H4C7 protein from the WikiPathways Pathways 2024 dataset. | |