» Articles » PMID: 26459852

Integrated Ordination of MiRNA and MRNA Expression Profiles

Overview
Journal BMC Genomics
Publisher Biomed Central
Specialty Genetics
Date 2015 Oct 14
PMID 26459852
Citations 31
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Several studies have investigated miRNA and mRNA co-expression to identify regulatory networks at the transcriptional level. A typical finding of these studies is the presence of both negative and positive miRNA-mRNA correlations. Negative correlations are consistent with the expected, faster degradation of target mRNAs, whereas positive correlations denote the existence of feed-forward regulations mediated by transcription factors. Both mechanisms have been characterized at the molecular level, although comprehensive methods to represent miRNA-mRNA correlations are lacking. At present, genome-wide studies are able to assess the expression of more than 1000 mature miRNAs and more than 35,000 well-characterized human genes. Even if studies are generally restricted to a small subset of genes differentially expressed in specific diseases or experimental conditions, the number of potential correlations remains very high, and needs robust multivariate methods to be conveniently summarized by a small set of data.

Results: Nonparametric Kendall correlations were calculated between miRNAs and mRNAs differentially expressed in livers of patients with acute liver failure (ALF) using normal livers as controls. Spurious correlations due to the histopathological composition of samples were removed by partial correlations. Correlations were then transformed into distances and processed by multidimensional scaling (MDS) to map the miRNA and mRNA relationships. These showed: (a) a prominent displacement of miRNA and mRNA clusters in ALF livers, as compared to control livers, indicative of gene expression dysregulation; (b) a clustering of mRNAs consistent with their functional annotations [CYP450, transcription factors, complement, proliferation, HLA class II, monocytes/macrophages, T cells, T-NK cells and B cells], as well as a clustering of miRNAs with the same seed sequence; and (c) a tendency of miRNAs and mRNAs to populate distinct regions of the MDS plot. MDS also allowed to visualize the network of miRNA-mRNA target pairs.

Conclusions: Different features of miRNA and mRNA relationships can be represented as thematic maps within the framework of MDS obtained from pairwise correlations. The symmetric distribution of positive and negative correlations between miRNA and mRNA expression suggests that miRNAs are involved in a complex bidirectional molecular network, including, but not limited to, the inhibitory regulation of miRNA targets.

Citing Articles

Competition effects regulating the composition of the microRNA pool.

Raak S, Hanley J, ODonnell C J R Soc Interface. 2025; 22(223):20240870.

PMID: 39965642 PMC: 11835486. DOI: 10.1098/rsif.2024.0870.


Dysregulation of Inflammation, Oxidative Stress, and Glucose Metabolism-Related Genes and miRNAs in Visceral Adipose Tissue of Women with Type 2 Diabetes Mellitus.

Wroblewski A, Strycharz J, Oszajca K, Czarny P, Swiderska E, Matyjas T Med Sci Monit. 2023; 29:e939299.

PMID: 37422695 PMC: 10340125. DOI: 10.12659/MSM.939299.


Bone marrow mesenchymal stem cell-derived small extracellular vesicles promote liver regeneration via miR-20a-5p/PTEN.

Zhang J, Gao J, Li X, Lin D, Li Z, Wang J Front Pharmacol. 2023; 14:1168545.

PMID: 37305542 PMC: 10248071. DOI: 10.3389/fphar.2023.1168545.


Stress induced dynamic adjustment of conserved miR164:NAC module.

Hernandez Y, Goswami K, Sanan-Mishra N Plant Environ Interact. 2023; 1(2):134-151.

PMID: 37283725 PMC: 10168063. DOI: 10.1002/pei3.10027.


Clinicopathological Significances and Prognostic Value of in Colorectal Cancer.

Fu F, Niu R, Zheng M, Yang X, Fan L, Fu W J Cancer. 2023; 14(1):24-34.

PMID: 36605492 PMC: 9809326. DOI: 10.7150/jca.78634.


References
1.
Lai E, Posakony J . Regulation of Drosophila neurogenesis by RNA:RNA duplexes?. Cell. 1998; 93(7):1103-4. DOI: 10.1016/s0092-8674(00)81454-3. View

2.
Guo L, Zhao Y, Yang S, Zhang H, Chen F . Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions. Biomed Res Int. 2014; 2014:907420. PMC: 3945032. DOI: 10.1155/2014/907420. View

3.
Subramanian A, Tamayo P, Mootha V, Mukherjee S, Ebert B, Gillette M . Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005; 102(43):15545-50. PMC: 1239896. DOI: 10.1073/pnas.0506580102. View

4.
Nissim O, Melis M, Diaz G, Kleiner D, Tice A, Fantola G . Liver regeneration signature in hepatitis B virus (HBV)-associated acute liver failure identified by gene expression profiling. PLoS One. 2012; 7(11):e49611. PMC: 3504149. DOI: 10.1371/journal.pone.0049611. View

5.
Zhou L, Pupo G, Gupta P, Liu B, Tran S, Rahme R . A parallel genome-wide mRNA and microRNA profiling of the frontal cortex of HIV patients with and without HIV-associated dementia shows the role of axon guidance and downstream pathways in HIV-mediated neurodegeneration. BMC Genomics. 2012; 13:677. PMC: 3560210. DOI: 10.1186/1471-2164-13-677. View