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Effect of Dynamic Interaction between microRNA and Transcription Factor on Gene Expression

View Article: PubMed Central - PubMed

ABSTRACT

MicroRNAs (miRNAs) are endogenous noncoding RNAs which participate in diverse biological processes in animals and plants. They are known to join together with transcription factors and downstream gene, forming a complex and highly interconnected regulatory network. To recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions, we constructed a computational model of miRNA-mediated feedforward loops (FFLs) in which a transcription factor (TF) regulates miRNA and targets gene. Based on the different dynamic interactions between miRNA and TF on gene expression, four possible structural topologies of FFLs with two gate functions (AND gate and OR gate) are introduced. We studied the dynamic behaviors of these different motifs. Furthermore, the relationship between the response time and maximal activation velocity of miRNA was investigated. We found that the curve of response time shows nonmonotonic behavior in Co1 loop with OR gate. This may help us to infer the mechanism of miRNA binding to the promoter region. At last we investigated the influence of important parameters on the dynamic response of system. We identified that the stationary levels of target gene in all loops were insensitive to the initial value of miRNA.

No MeSH data available.


The time evolutions of Z in various FFLs with different gate functions in response to variation of v2. Types 1-2 coherent FFLs are shown in (a)-(b), while types 1-2 incoherent FFLs are given in (c)-(d). The red line corresponds to AND gate function, and the green line represents OR gate function. Here we fix k1 = 0.25.
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fig5: The time evolutions of Z in various FFLs with different gate functions in response to variation of v2. Types 1-2 coherent FFLs are shown in (a)-(b), while types 1-2 incoherent FFLs are given in (c)-(d). The red line corresponds to AND gate function, and the green line represents OR gate function. Here we fix k1 = 0.25.

Mentions: Figure 5 shows the time course of Z in various FFLs with different gate functions in response to variation of v2. We choose three typical values of v2: the original value, 10-fold, and 0.1-fold of v2. We find that bigger v2 induces less expression of target gene when Z reaches the steady state. We can understand this from the interaction relationship in Figure 1. Larger v2 results in more miRNA generation which further represses target gene synthesis, so at last less target gene was observed. Parameter d2 is the degradation rate of miRNA. For the influence of d2, the situation is opposite, in which bigger d2 results in higher level of gene expression after it gets to the stationary level (Figure 6). This is because that larger d2 induces less miRNA generation, which results in less inhibition of miRNA on Z synthesis.


Effect of Dynamic Interaction between microRNA and Transcription Factor on Gene Expression
The time evolutions of Z in various FFLs with different gate functions in response to variation of v2. Types 1-2 coherent FFLs are shown in (a)-(b), while types 1-2 incoherent FFLs are given in (c)-(d). The red line corresponds to AND gate function, and the green line represents OR gate function. Here we fix k1 = 0.25.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5121577&req=5

fig5: The time evolutions of Z in various FFLs with different gate functions in response to variation of v2. Types 1-2 coherent FFLs are shown in (a)-(b), while types 1-2 incoherent FFLs are given in (c)-(d). The red line corresponds to AND gate function, and the green line represents OR gate function. Here we fix k1 = 0.25.
Mentions: Figure 5 shows the time course of Z in various FFLs with different gate functions in response to variation of v2. We choose three typical values of v2: the original value, 10-fold, and 0.1-fold of v2. We find that bigger v2 induces less expression of target gene when Z reaches the steady state. We can understand this from the interaction relationship in Figure 1. Larger v2 results in more miRNA generation which further represses target gene synthesis, so at last less target gene was observed. Parameter d2 is the degradation rate of miRNA. For the influence of d2, the situation is opposite, in which bigger d2 results in higher level of gene expression after it gets to the stationary level (Figure 6). This is because that larger d2 induces less miRNA generation, which results in less inhibition of miRNA on Z synthesis.

View Article: PubMed Central - PubMed

ABSTRACT

MicroRNAs (miRNAs) are endogenous noncoding RNAs which participate in diverse biological processes in animals and plants. They are known to join together with transcription factors and downstream gene, forming a complex and highly interconnected regulatory network. To recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions, we constructed a computational model of miRNA-mediated feedforward loops (FFLs) in which a transcription factor (TF) regulates miRNA and targets gene. Based on the different dynamic interactions between miRNA and TF on gene expression, four possible structural topologies of FFLs with two gate functions (AND gate and OR gate) are introduced. We studied the dynamic behaviors of these different motifs. Furthermore, the relationship between the response time and maximal activation velocity of miRNA was investigated. We found that the curve of response time shows nonmonotonic behavior in Co1 loop with OR gate. This may help us to infer the mechanism of miRNA binding to the promoter region. At last we investigated the influence of important parameters on the dynamic response of system. We identified that the stationary levels of target gene in all loops were insensitive to the initial value of miRNA.

No MeSH data available.