| Name | HLA complex group 4B (non-protein coding) |
| Summary |
{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n HCG4B is a long noncoding RNA located within a genomic region of the major histocompatibility complex that appears to contribute to the regulation of immune‐related gene expression. In a study investigating copy number variations associated with chronic obstructive pulmonary disease (COPD), a common CNV (nsv823469) overlapping both HCG4B and the neighboring HLA‐A gene was shown to affect pulmonary gene expression. Specifically, individuals carrying a copy number loss of this region exhibited lower expression levels of HCG4B and HLA‐A in normal lung tissue, a change that was associated with improved forced expiratory volume in 1 second (FEV1) and a decreased risk of COPD."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": " Although the precise molecular mechanisms remain to be fully elucidated, these findings suggest that HCG4B may be involved in modulating local immune responses in lung tissue—potentially through a regulatory axis that includes HLA‐A—and could influence airway inflammation and pulmonary function. Such insights into gene dosage effects and epigenetic regulation are consistent with broader investigations into how structural and regulatory genomic variations contribute to disease pathogenesis."}, {"type": "fg", "children": [{"type": "fg_fs", "start_ref": "2", "end_ref": "5"}]}, {"type": "t", "text": "\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Xiaoliang Chen, Xiaoxiao Lu, Jiansong Chen, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Association of nsv823469 copy number loss with decreased risk of chronic obstructive pulmonary disease and pulmonary function in Chinese."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Sci Rep (2017)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1038/srep40060"}], "href": "https://doi.org/10.1038/srep40060"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "28079130"}], "href": "https://pubmed.ncbi.nlm.nih.gov/28079130"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Vicki E Maltby, Rodney A Lea, Katherine A Sanders, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Differential methylation at "}, {"type": "a", "children": [{"type": "t", "text": "i"}], "href": "i"}, {"type": "t", "text": "MHC"}, {"type": "a", "children": [{"type": "t", "text": "/i"}], "href": "/i"}, {"type": "t", "text": " in CD4"}, {"type": "a", "children": [{"type": "t", "text": "sup"}], "href": "sup"}, {"type": "t", "text": "+"}, {"type": "a", "children": [{"type": "t", "text": "/sup"}], "href": "/sup"}, {"type": "t", "text": " T cells is associated with multiple sclerosis independently of "}, {"type": "a", "children": [{"type": "t", "text": "i"}], "href": "i"}, {"type": "t", "text": "HLA-DRB1"}, {"type": "a", "children": [{"type": "t", "text": "/i"}], "href": "/i"}, {"type": "t", "text": "."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Clin Epigenetics (2017)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/s13148-017-0371-1"}], "href": "https://doi.org/10.1186/s13148-017-0371-1"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "28729889"}], "href": "https://pubmed.ncbi.nlm.nih.gov/28729889"}]}, {"type": "r", "ref": 3, "children": [{"type": "t", "text": "Eric Chater-Diehl, Resham Ejaz, Cheryl Cytrynbaum, et al. "}, {"type": "b", "children": [{"type": "t", "text": "New insights into DNA methylation signatures: SMARCA2 variants in Nicolaides-Baraitser syndrome."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "BMC Med Genomics (2019)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/s12920-019-0555-y"}], "href": "https://doi.org/10.1186/s12920-019-0555-y"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "31288860"}], "href": "https://pubmed.ncbi.nlm.nih.gov/31288860"}]}, {"type": "r", "ref": 4, "children": [{"type": "t", "text": "Federico Carlini, Virginia Ferreira, Stéphane Buhler, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Association of HLA-A and Non-Classical HLA Class I Alleles."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "PLoS One (2016)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1371/journal.pone.0163570"}], "href": "https://doi.org/10.1371/journal.pone.0163570"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "27701438"}], "href": "https://pubmed.ncbi.nlm.nih.gov/27701438"}]}, {"type": "r", "ref": 5, "children": [{"type": "t", "text": "Noémie Gensous, Claudio Franceschi, Bonnie B Blomberg, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Responders and non-responders to influenza vaccination: A DNA methylation approach on blood cells."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Exp Gerontol (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1016/j.exger.2018.01.019"}], "href": "https://doi.org/10.1016/j.exger.2018.01.019"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "29360511"}], "href": "https://pubmed.ncbi.nlm.nih.gov/29360511"}]}]}]}
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| Synonyms | BPG309N1.1, HCGIV-06, HCGIV.5, HCG4P6, BQB90C11.3, HCGIV-6, BCX67J3.3 |
| NCBI Gene ID | 80868 |
| 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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HCG4B has 705 functional associations with biological entities spanning 7 categories (molecular profile, organism, chemical, disease, phenotype or trait, functional term, phrase or reference, cell line, cell type or tissue, gene, protein or microRNA) extracted from 20 datasets.
Click the + buttons to view associations for HCG4B from the datasets below.
If available, associations are ranked by standardized value
| Dataset | Summary | |
|---|---|---|
| Allen Brain Atlas Adult Human Brain Tissue Gene Expression Profiles | tissues with high or low expression of HCG4B gene relative to other tissues from the Allen Brain Atlas Adult Human Brain Tissue Gene Expression Profiles dataset. | |
| BioGPS Cell Line Gene Expression Profiles | cell lines with high or low expression of HCG4B gene relative to other cell lines from the BioGPS Cell Line Gene Expression Profiles dataset. | |
| BioGPS Human Cell Type and Tissue Gene Expression Profiles | cell types and tissues with high or low expression of HCG4B gene relative to other cell types and tissues from the BioGPS Human Cell Type and Tissue Gene Expression Profiles dataset. | |
| CCLE Cell Line Gene CNV Profiles | cell lines with high or low copy number of HCG4B gene relative to other cell lines from the CCLE Cell Line Gene CNV Profiles dataset. | |
| CCLE Cell Line Gene Expression Profiles | cell lines with high or low expression of HCG4B gene relative to other cell lines from the CCLE Cell Line Gene Expression Profiles dataset. | |
| ChEA Transcription Factor Binding Site Profiles | transcription factor binding site profiles with transcription factor binding evidence at the promoter of HCG4B gene from the CHEA Transcription Factor Binding Site Profiles dataset. | |
| ChEA Transcription Factor Targets | transcription factors binding the promoter of HCG4B gene in low- or high-throughput transcription factor functional studies from the CHEA Transcription Factor Targets dataset. | |
| CMAP Signatures of Differentially Expressed Genes for Small Molecules | small molecule perturbations changing expression of HCG4B gene from the CMAP Signatures of Differentially Expressed Genes for Small Molecules dataset. | |
| COSMIC Cell Line Gene CNV Profiles | cell lines with high or low copy number of HCG4B gene relative to other cell lines from the COSMIC Cell Line Gene CNV Profiles dataset. | |
| GDSC Cell Line Gene Expression Profiles | cell lines with high or low expression of HCG4B gene relative to other cell lines from the GDSC Cell Line Gene Expression Profiles dataset. | |
| GEO Signatures of Differentially Expressed Genes for Diseases | disease perturbations changing expression of HCG4B gene from the GEO Signatures of Differentially Expressed Genes for Diseases dataset. | |
| GEO Signatures of Differentially Expressed Genes for Gene Perturbations | gene perturbations changing expression of HCG4B gene from the GEO Signatures of Differentially Expressed Genes for Gene Perturbations dataset. | |
| GEO Signatures of Differentially Expressed Genes for Small Molecules | small molecule perturbations changing expression of HCG4B gene from the GEO Signatures of Differentially Expressed Genes for Small Molecules dataset. | |
| GEO Signatures of Differentially Expressed Genes for Viral Infections | virus perturbations changing expression of HCG4B gene from the GEO Signatures of Differentially Expressed Genes for Viral Infections dataset. | |
| JASPAR Predicted Transcription Factor Targets | transcription factors regulating expression of HCG4B gene predicted using known transcription factor binding site motifs from the JASPAR Predicted Transcription Factor Targets dataset. | |
| Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles | cell lines with high or low copy number of HCG4B gene relative to other cell lines from the Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles dataset. | |
| LOCATE Predicted Protein Localization Annotations | cellular components predicted to contain HCG4B protein from the LOCATE Predicted Protein Localization Annotations dataset. | |
| MotifMap Predicted Transcription Factor Targets | transcription factors regulating expression of HCG4B gene predicted using known transcription factor binding site motifs from the MotifMap Predicted Transcription Factor Targets dataset. | |
| MSigDB Signatures of Differentially Expressed Genes for Cancer Gene Perturbations | gene perturbations changing expression of HCG4B gene from the MSigDB Signatures of Differentially Expressed Genes for Cancer Gene Perturbations dataset. | |
| TCGA Signatures of Differentially Expressed Genes for Tumors | tissue samples with high or low expression of HCG4B gene relative to other tissue samples from the TCGA Signatures of Differentially Expressed Genes for Tumors dataset. | |