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Integrated regulatory network reveals novel candidate regulators in the development of negative energy balance in cattle

Published online by Cambridge University Press:  28 December 2017

Z. Mozduri ,
M. R. Bakhtiarizadeh  and
A. Salehi
Z. Mozduri
Affiliation:
Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, 33916-53775, Tehran, Iran
M. R. Bakhtiarizadeh*
Affiliation:
Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, 33916-53775, Tehran, Iran
A. Salehi
Affiliation:
Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, 33916-53775, Tehran, Iran
*
†E-mail: mrbakhtiari@ut.ac.ir
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Abstract

Negative energy balance (NEB) is an altered metabolic state in modern high-yielding dairy cows. This metabolic state occurs in the early postpartum period when energy demands for milk production and maintenance exceed that of energy intake. Negative energy balance or poor adaptation to this metabolic state has important effects on the liver and can lead to metabolic disorders and reduced fertility. The roles of regulatory factors, including transcription factors (TFs) and micro RNAs (miRNAs) have often been separately studied for evaluating of NEB. However, adaptive response to NEB is controlled by complex gene networks and still not fully understood. In this study, we aimed to discover the integrated gene regulatory networks involved in NEB development in liver tissue. We downloaded data sets including mRNA and miRNA expression profiles related to three and four cows with severe and moderate NEB, respectively. Our method integrated two independent types of information: module inference network by TFs, miRNAs and mRNA expression profiles (RNA-seq data) and computational target predictions. In total, 176 modules were predicted by using gene expression data and 64 miRNAs and 63 TFs were assigned to these modules. By using our integrated computational approach, we identified 13 TF-module and 19 miRNA-module interactions. Most of these modules were associated with liver metabolic processes as well as immune and stress responses, which might play crucial roles in NEB development. Literature survey results also showed that several regulators and gene targets have already been characterized as important factors in liver metabolic processes. These results provided novel insights into regulatory mechanisms at the TF and miRNA levels during NEB. In addition, the method described in this study seems to be applicable to construct integrated regulatory networks for different diseases or disorders.

Keywords

integrated regulatory networkmodule networknegative energy balancesequence-based informationtranscription factor
Type
Research Article
Information
animal , Volume 12 , Issue 6 , June 2018 , pp. 1196 - 1207
Copyright
© The Animal Consortium 2017 

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