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Prioritizing genes responsible for host resistance to influenza using network approaches

Suying Bao1, Xueya Zhou2, Liangcai Zhang3, Jie Zhou4, Kelvin Kai-Wang To45, Binbin Wang6, Liqiu Wang78, Xuegong Zhang2 and You-Qiang Song19*

  • * Corresponding author: You-Qiang Song

  • † Equal contributors

Author Affiliations

1 Department of Biochemistry, The University of Hong Kong, Hong Kong, China

2 Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST, MOE Key Lab of Bioinformatics / Department of Automation, Tsinghua University, Beijing, China

3 Department of Biophysics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China

4 Department of Microbiology, The University of Hong Kong, Hong Kong, China

5 Carol Yu Centre for Infection, The University of Hong Kong, Hong Kong, China

6 National Research Institute for Family Planning, Beijing, China

7 Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China

8 HKU-Zhejiang Institute of Research and Innovation (HKU-ZIRI), Linan, Zhejiang, 311100, China

9 Center for Genome Science, The University of Hong Kong, Hong Kong, China

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BMC Genomics 2013, 14:816  doi:10.1186/1471-2164-14-816

Published: 21 November 2013



The genetic make-up of humans and other mammals (such as mice) affects their resistance to influenza virus infection. Considering the complexity and moral issues associated with experiments on human subjects, we have only acquired partial knowledge regarding the underlying molecular mechanisms. Although influenza resistance in inbred mice has been mapped to several quantitative trait loci (QTLs), which have greatly narrowed down the search for host resistance genes, only few underlying genes have been identified.


To prioritize a list of promising candidates for future functional investigation, we applied network-based approaches to leverage the information of known resistance genes and the expression profiles contrasting susceptible and resistant mouse strains. The significance of top-ranked genes was supported by different lines of evidence from independent genetic associations, QTL studies, RNA interference (RNAi) screenings, and gene expression analysis. Further data mining on the prioritized genes revealed the functions of two pathways mediated by tumor necrosis factor (TNF): apoptosis and TNF receptor-2 signaling pathways. We suggested that the delicate balance between TNF’s pro-survival and apoptotic effects may affect hosts’ conditions after influenza virus infection.


This study considerably cuts down the list of candidate genes responsible for host resistance to influenza and proposed novel pathways and mechanisms. Our study also demonstrated the efficacy of network-based methods in prioritizing genes for complex traits.