Co-regulation and Crosstalk of MicroRNA and Transcription Factor in Human Protein Interaction Network
Date Issued
2011
Date
2011
Author(s)
Chen, Ya-Jen
Abstract
Systems biology is a rising field of biomedical research. It uses systematic analysis to characterize or discover the mechanism of biological systems. Biological processes involve numerous genes and proteins, which interact with each other to form complicated molecular networks. Thus, finding and conducting a complete module of gene regulatory network is important for understanding mechanisms of cellular physiologies or diseases.
In recent years, microRNAs (miRNAs, small RNA molecules with ~22 bps) have been widely discovered in plants, animals and viruses. MicroRNAs will not be translated to proteins but can recognize target genes based on complementary sequence similarity and then suppress the translations of target genes. Previous studies found that microRNAs are involved in growth development, differentiation and metabolism through down-regulating target genes. Furthermore, there exist some characteristic correlations between microRNAs and transcription factors (TFs). Although many studies have uncovered the mechanism of microRNA biogenesis and functions, their corporation with transcription factors remains unclear. One of the reasons is that microRNAs usually have numerous target genes, which made functional prediction or classification difficult and complicated.
Here we build a model of microRNAs and transcription factors regulating human protein-protein interaction networks from experimental results and computational predictions. Using computational analysis finds out possible existing regulatory motifs and relations between protein-protein interaction networks.
Our results show that protein-protein interaction networks might be regulated by microRNAs and/or transcription factors through their co-regulation and crosstalk regulatory motifs. In other words, more than two microRNAs or transcription factors might be involved in specific biological processes together. Most interestingly, we have identified crosstalk motifs for the first time and found that microRNAs or transcription factors might indirectly regulate protein-protein interactions through regulating a third gene. More than half of all the genes participate in crosstalk motifs (P-value < 0.001).
Subjects
System Biology
Bioinformatics
MicroRNA
Transcription Factors
Gene Regulatory Network
Protein Interaction Network
SDGs
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-100-R98945025-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):50a840008828fd96b631a264a3992b78