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Screening candidate microR-15a- IRAK2 regulatory pairs for predicting the response to Staphylococcus aureus-induced mastitis in dairy cows

Published online by Cambridge University Press:  14 November 2019

Zhi Chen ,
Jingpeng Zhou ,
Xiaolong Wang ,
Yang Zhang ,
Xubin Lu ,
Yongliang Fan ,
Yongjiang Mao ,
Juan J. Loor  and
Zhangping Yang
Zhi Chen
Affiliation:
College of Animal Science and Technology, Yangzhou University, Yangzhou225009, PR China Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou225009, China
Jingpeng Zhou
Affiliation:
College of Animal Science and Technology, Yangzhou University, Yangzhou225009, PR China Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou225009, China
Xiaolong Wang
Affiliation:
College of Animal Science and Technology, Yangzhou University, Yangzhou225009, PR China Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou225009, China
Yang Zhang
Affiliation:
Animal husbandry and veterinary station of Zhiqian, Jintan District, Changzhou, 213200, China
Xubin Lu
Affiliation:
College of Animal Science and Technology, Yangzhou University, Yangzhou225009, PR China Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou225009, China
Yongliang Fan
Affiliation:
College of Animal Science and Technology, Yangzhou University, Yangzhou225009, PR China Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou225009, China
Yongjiang Mao
Affiliation:
College of Animal Science and Technology, Yangzhou University, Yangzhou225009, PR China Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou225009, China
Juan J. Loor
Affiliation:
Mammalian Nutrition Physiology Genomics, Department of Animal Sciences and Division of Nutritional Sciences, University of Illinois, Urbana, IL61801, USA
Zhangping Yang*
Affiliation:
College of Animal Science and Technology, Yangzhou University, Yangzhou225009, PR China Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou225009, China
*
Author for correspondence: Zhangping Yang, Email: yzp@yzu.edu.cn
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Abstract

We established a mastitis model using exogenous infection of the mammary gland of Chinese Holstein cows with Staphylococcus aureus and extracted total RNA from S. aureus-infected and healthy mammary quarters. Differential expression of genes due to mastitis was evaluated using Affymetrix technology and results revealed a total of 1230 differentially expressed mRNAs. A subset of affected genes was verified via Q-PCR and pathway analysis. In addition, Solexa high-throughput sequencing technology was used to analyze profiles of miRNA in infected and healthy quarters. These analyses revealed a total of 52 differentially expressed miRNAs. A subset of those results was verified via Q-PCR. Bioinformatics techniques were used to predict and analyze the correlations among differentially expressed miRNA and mRNA. Results revealed a total of 329 pairs of negatively associated miRNA/mRNA, with 31 upregulated pairs of mRNA and 298 downregulated pairs of mRNA. Differential expression of miR-15a and interleukin-1 receptor-associated kinase-like 2 (IRAK2), were evaluated by western blot and luciferase reporter assays. We conclude that miR-15a and miR-15a target genes (IRAK2) constitute potential miRNA–mRNA regulatory pairs for use as biomarkers to predict a mastitis response.

Keywords

Differential genes and microRNAsIRAK2MastitisMicroRNA-mRNA networkmiR-15aStaphylococcus aureus

Information

Type
Research Article
Information
Journal of Dairy Research , Volume 86 , Issue 4 , November 2019 , pp. 425 - 431
Copyright
Copyright © Hannah Dairy Research Foundation 2019

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