Akademik Veri Yönetim Sistemi
7th International Molecular Biology and Biotechnology Congress, Konya, Türkiye, 25 - 27 Nisan 2018, ss.401
MicroRNAs negatively regulate expression of many genes, efficiency of which de-
pends on concentration of targets, content and structure of seed region. Current
models consider one microRNA and its targets, or one mRNA and microRNAs
targeting that mRNA. In this study, a network-based model was developed in-
corporating factors that are important in microRNA activity such as free energy,
microRNA expression and gene expression levels, seed structure and position of
target region on mRNA. The gene and microRNA expression data were downloa-
ded from The Cancer Genome Atlas (TCGA), microRNA:target pairing data was
obtained from previously performed high-throughput sequencing studies using
CLASH and CLEAR-CLIP. In this regard, microRNA expression, gene expressi-
on and microRNA:target databases were combined and the initial network created
from the dataset was accepted as steady-state. The model was used to calculate
how the expression of other genes will change in the network upon perturbation of
single gene expression. As an example, in a microRNA:target network extracted
from a breast cancer patient with 61 microRNAs and 186 genes, two-fold increase
in one of the genes resulted in 15% of targets being up-regulated and 81% being
constant . When gene expression changes calculated for the genes two genes node
away from initial perturbed gene, we observed increase in 53% and decrease in
18% of all genes in the network. Our model can help understand gene expressi-
on changes in context of complex microRNA:target network and pave the way
for gene expression analysis in context of ceRNAs such as circRNAs, lncRNAs.
Keywords: MicroRNA, Network, Gene expression regulation