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What do all the (human) micro-RNAs do?

Ultsch A, Lötsch J - BMC Genomics (2014)

Bottom Line: The present analysis transferred this knowledge to a systems-biology level.A comprehensible and precise description of the biological processes in which the genes that are influenced by miRNAs are notably involved could be made.The analysis also suggests that miRNAs especially control the expression of genes that control the expression of genes.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Pharmacology, Goethe - University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany. j.loetsch@em.uni-frankfurt.de.

ABSTRACT

Background: Micro-RNAs (miRNA) are attributed to the systems biological role of a regulatory mechanism of the expression of protein coding genes. Research has identified miRNAs dysregulations in several but distinct pathophysiological processes, which hints at distinct systems-biology functions of miRNAs. The present analysis approached the role of miRNAs from a genomics perspective and assessed the biological roles of 2954 genes and 788 human miRNAs, which can be considered to interact, based on empirical evidence and computational predictions of miRNA versus gene interactions.

Results: From a genomics perspective, the biological processes in which the genes that are influenced by miRNAs are involved comprise of six major topics comprising biological regulation, cellular metabolism, information processing, development, gene expression and tissue homeostasis. The usage of this knowledge as a guidance for further research is sketched for two genetically defined functional areas: cell death and gene expression. Results suggest that the latter points to a fundamental role of miRNAs consisting of hyper-regulation of gene expression, i.e., the control of the expression of such genes which control specifically the expression of genes.

Conclusions: Laboratory research identified contributions of miRNA regulation to several distinct biological processes. The present analysis transferred this knowledge to a systems-biology level. A comprehensible and precise description of the biological processes in which the genes that are influenced by miRNAs are notably involved could be made. This knowledge can be employed to guide future research concerning the biological role of miRNA (dys-) regulations. The analysis also suggests that miRNAs especially control the expression of genes that control the expression of genes.

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Related in: MedlinePlus

Directed acyclic graphs (DAG [32]) representing the nested Gene Ontology (GO) classification showing the polyhierarchy of functional annotations (GO terms) assigned in the GO categories “cellular component” and “molecular function” (right) to the 2954 genes (Figure1) that supported by empirical evidence from the miRTarBase [18] or TarBase [19] databases or computationally predicted using the TargetScan Human [20] software interact with miRNAs. The figure is based on the GeneTrail web-based analysis tool [24] and represents the results of an over-representation analysis with parameters p-value threshold, tp = 1.0 10−5 and Bonferroni α correction. Significant terms are shown as red colored or framed ellipses, with the number of member genes indicated in line three, the expected number of genes in line five and the significance of the deviation between the two numbers given as minus log10 p. The GO category is indicated in yellow, and the leaves of this polyhierarchy at the select p-value threshold are shown in blue indicating the most specific significant GO terms.
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Fig4: Directed acyclic graphs (DAG [32]) representing the nested Gene Ontology (GO) classification showing the polyhierarchy of functional annotations (GO terms) assigned in the GO categories “cellular component” and “molecular function” (right) to the 2954 genes (Figure1) that supported by empirical evidence from the miRTarBase [18] or TarBase [19] databases or computationally predicted using the TargetScan Human [20] software interact with miRNAs. The figure is based on the GeneTrail web-based analysis tool [24] and represents the results of an over-representation analysis with parameters p-value threshold, tp = 1.0 10−5 and Bonferroni α correction. Significant terms are shown as red colored or framed ellipses, with the number of member genes indicated in line three, the expected number of genes in line five and the significance of the deviation between the two numbers given as minus log10 p. The GO category is indicated in yellow, and the leaves of this polyhierarchy at the select p-value threshold are shown in blue indicating the most specific significant GO terms.

Mentions: Following functional abstractions of the further GO categories (Table 3) the GO category “cellular component” (Figure 4) indicated 2.5 times more miRNA-interacting genes annotated to the nucleus (n = 688 genes) than to the cytoplasm (n = 274). This significantly (p <10−20) exceeded the n = 504 genes that were expected to be annotated to the nucleus. Finally, the analysis of “molecular function” (Figure 4) indicated a particular role of miRNAs in selective, non-covalent interaction of a molecule with one or more specific sites on another molecule, i.e., “binding” (GO:0005488, p <10−33), including DNA binding (GO:0003677, p <10−15), and the regulation of “transcription factor activity” (GO:0003700, p <10−10) or “transcription factor binding” (GO:0008134, p <10−23).Table 3


What do all the (human) micro-RNAs do?

Ultsch A, Lötsch J - BMC Genomics (2014)

Directed acyclic graphs (DAG [32]) representing the nested Gene Ontology (GO) classification showing the polyhierarchy of functional annotations (GO terms) assigned in the GO categories “cellular component” and “molecular function” (right) to the 2954 genes (Figure1) that supported by empirical evidence from the miRTarBase [18] or TarBase [19] databases or computationally predicted using the TargetScan Human [20] software interact with miRNAs. The figure is based on the GeneTrail web-based analysis tool [24] and represents the results of an over-representation analysis with parameters p-value threshold, tp = 1.0 10−5 and Bonferroni α correction. Significant terms are shown as red colored or framed ellipses, with the number of member genes indicated in line three, the expected number of genes in line five and the significance of the deviation between the two numbers given as minus log10 p. The GO category is indicated in yellow, and the leaves of this polyhierarchy at the select p-value threshold are shown in blue indicating the most specific significant GO terms.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4289375&req=5

Fig4: Directed acyclic graphs (DAG [32]) representing the nested Gene Ontology (GO) classification showing the polyhierarchy of functional annotations (GO terms) assigned in the GO categories “cellular component” and “molecular function” (right) to the 2954 genes (Figure1) that supported by empirical evidence from the miRTarBase [18] or TarBase [19] databases or computationally predicted using the TargetScan Human [20] software interact with miRNAs. The figure is based on the GeneTrail web-based analysis tool [24] and represents the results of an over-representation analysis with parameters p-value threshold, tp = 1.0 10−5 and Bonferroni α correction. Significant terms are shown as red colored or framed ellipses, with the number of member genes indicated in line three, the expected number of genes in line five and the significance of the deviation between the two numbers given as minus log10 p. The GO category is indicated in yellow, and the leaves of this polyhierarchy at the select p-value threshold are shown in blue indicating the most specific significant GO terms.
Mentions: Following functional abstractions of the further GO categories (Table 3) the GO category “cellular component” (Figure 4) indicated 2.5 times more miRNA-interacting genes annotated to the nucleus (n = 688 genes) than to the cytoplasm (n = 274). This significantly (p <10−20) exceeded the n = 504 genes that were expected to be annotated to the nucleus. Finally, the analysis of “molecular function” (Figure 4) indicated a particular role of miRNAs in selective, non-covalent interaction of a molecule with one or more specific sites on another molecule, i.e., “binding” (GO:0005488, p <10−33), including DNA binding (GO:0003677, p <10−15), and the regulation of “transcription factor activity” (GO:0003700, p <10−10) or “transcription factor binding” (GO:0008134, p <10−23).Table 3

Bottom Line: The present analysis transferred this knowledge to a systems-biology level.A comprehensible and precise description of the biological processes in which the genes that are influenced by miRNAs are notably involved could be made.The analysis also suggests that miRNAs especially control the expression of genes that control the expression of genes.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Pharmacology, Goethe - University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany. j.loetsch@em.uni-frankfurt.de.

ABSTRACT

Background: Micro-RNAs (miRNA) are attributed to the systems biological role of a regulatory mechanism of the expression of protein coding genes. Research has identified miRNAs dysregulations in several but distinct pathophysiological processes, which hints at distinct systems-biology functions of miRNAs. The present analysis approached the role of miRNAs from a genomics perspective and assessed the biological roles of 2954 genes and 788 human miRNAs, which can be considered to interact, based on empirical evidence and computational predictions of miRNA versus gene interactions.

Results: From a genomics perspective, the biological processes in which the genes that are influenced by miRNAs are involved comprise of six major topics comprising biological regulation, cellular metabolism, information processing, development, gene expression and tissue homeostasis. The usage of this knowledge as a guidance for further research is sketched for two genetically defined functional areas: cell death and gene expression. Results suggest that the latter points to a fundamental role of miRNAs consisting of hyper-regulation of gene expression, i.e., the control of the expression of such genes which control specifically the expression of genes.

Conclusions: Laboratory research identified contributions of miRNA regulation to several distinct biological processes. The present analysis transferred this knowledge to a systems-biology level. A comprehensible and precise description of the biological processes in which the genes that are influenced by miRNAs are notably involved could be made. This knowledge can be employed to guide future research concerning the biological role of miRNA (dys-) regulations. The analysis also suggests that miRNAs especially control the expression of genes that control the expression of genes.

Show MeSH
Related in: MedlinePlus