miRBase entry: hsa-mir-379

Stem-loop hsa-mir-379


Accession
MI0000787
Symbol
HGNC: MIR379
Description
Homo sapiens hsa-mir-379 precursor miRNA mir-379
Gene
family?
RF04292; mir-379

Summary
Caution, this is an AI generated summary based on literature. This may have errors. ?

MIR379 is an imprinted microRNA that is part of the DLK1-DIO3 genomic region and is implicated in various biological processes and diseases [PMC3743905]. It is activated during the epithelial to mesenchymal transition in prostate cancer cells [PMC5195822]. MIR379, along with other miRNAs, forms a cluster that has been associated with sensitivity to certain chemotherapeutic agents in cancer cell lines [PMC9716673]. This miRNA has been shown to maintain stable levels during induced long-term potentiation, suggesting a potential role in synaptic plasticity [PMC7486624]. MIR379 has also been implicated in skeletal muscle differentiation and has been correlated with various lipid levels in early-stage non-alcoholic fatty liver disease (NAFLD) patients, suggesting its potential as a biomarker for early detection of NAFLD [PMC8111742], [PMC9738374]. Furthermore, MIR379 expression levels were found to be significantly higher in patients with early-stage NAFLD compared to controls [PMC9738374]'>PMC9738374], and its serum levels were increased in a Japanese population of NAFLD patients [PMC9738374]. It targets numerous genes involved in different biological processes and diseases such as diabetic nephropathy (DN) and may have therapeutic implications for conditions like obesity and type 2 diabetes when inhibited by specific modalities like GapmeRs [PMC9535382], [PMC8255808].

Literature search
48 open access papers mention hsa-mir-379
(227 sentences)

Sequence

93096 reads, 331 reads per million, 119 experiments
agagaUGGUAGACUAUGGAACGUAGGcguuaugauuucugaccUAUGUAACAUGGUCCACUAACUcu
((((.((((.(((((((..(((((((((..........)).)))))))..))))))).)))).))))

Structure
    a    A       GA       -  uuau 
agag UGGU GACUAUG  ACGUAGG cg    g
|||| |||| |||||||  ||||||| ||     
ucUC AUCA CUGGUAC  UGUAUcc gu    a
    A    C       AA       a  cuuu 


Annotation confidence High
Do you think this miRNA is real?
Comments
The mature sequence shown here represents the most commonly cloned form from large-scale cloning studies [4].

Genome context
chr14: 101022066-101022132 [+]
Clustered miRNAs
11 other miRNAs are < 10 kb from hsa-mir-379
Name Accession Chromosome Start End Strand Confidence




Disease association
hsa-mir-379 is associated with one or more human diseases in the Human microRNA Disease Database
Disease Description Category PubMed ID


Database links

Mature hsa-miR-379-5p

Accession MIMAT0000733
Description Homo sapiens hsa-miR-379-5p mature miRNA
Sequence 6 - UGGUAGACUAUGGAACGUAGG - 26
Evidence experimental
cloned [2-4]
Database links
Predicted targets

Mature hsa-miR-379-3p

Accession MIMAT0004690
Description Homo sapiens hsa-miR-379-3p mature miRNA
Sequence 44 - UAUGUAACAUGGUCCACUAACU - 65
Evidence experimental
cloned [4]
Database links
Predicted targets

References

  1. PubMed ID: 17604727
    A mammalian microRNA expression atlas based on small RNA library sequencing
    "Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, Pfeffer S, Rice A, Kamphorst AO, Landthaler M, Lin C, Socci ND, Hermida L, Fulci V, Chiaretti S, Foa R, Schliwka J, Fuchs U, Novosel A, Muller RU, Schermer B, Bissels U, Inman J, Phan Q, Chien M"
    "Cell (2007) 129:1401-1414

  2. PubMed ID: 15538371
    A pancreatic islet-specific microRNA regulates insulin secretion
    "Poy MN, Eliasson L, Krutzfeldt J, Kuwajima S, Ma X, Macdonald PE, Pfeffer S, Tuschl T, Rajewsky N, Rorsman P, Stoffel M"
    "Nature (2004) 432:226-230

  3. PubMed ID: 15891114
    Clustering and conservation patterns of human microRNAs
    "Altuvia Y, Landgraf P, Lithwick G, Elefant N, Pfeffer S, Aravin A, Brownstein MJ, Tuschl T, Margalit H"
    "Nucleic Acids Res (2005) 33:2697-2706

  4. PubMed ID: 16274478
    Identification of clustered microRNAs using an ab initio prediction method
    Sewer A, Paul N, Landgraf P, Aravin A, Pfeffer S, Brownstein MJ, Tuschl T, van Nimwegen E, Zavolan M
    BMC Bioinformatics (2005) 6:267