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Updated: Aug 5, 2026

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
Published on: July 18, 2013
Deciphering host-virus interaction networks in ALV infection: an integrative multi-omics perspective
Junliang Xia1,2,3, Weiding Chen1,2,3, Xiaoli Zhou1,2,3
1College of Animal Science, Department of Animal Genetics, Breeding and Reproduction, South China Agricultural University, Guangzhou, China.
Abstract:
Avian leukosis virus (ALV) remains a major threat to the poultry industry due to its ability to establish persistent infection, induce immunosuppression, and promote tumorigenesis. Despite progress in eradication programs, effective control is hindered by subclinical infection, vertical transmission, and rapid viral evolution. A key limitation lies in the complexity of host-virus interactions, which are governed by multi-layered regulatory processes that cannot be fully resolved by studies focusing on single genes, pathways, or omics layers. In addition, the lack of robust and dynamic phenotypic indicators further constrains the dissection of resistance mechanisms. Recent advances in multi-omics technologies provide an opportunity to overcome these challenges by capturing coordinated changes across genomic, transcriptional, proteomic, and epigenetic levels. Integrating these data with molecular phenotypes, such as expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs), enables the linking of genetic variation to functional immune responses. Furthermore, CRISPR-based functional screening offers a systematic approach for validating candidate host factors and identifying key regulators of viral replication and immune modulation. In this review, we summarize the epidemiology and molecular biology of ALV, outline current understanding of host-virus interaction networks with an emphasis on innate immune responses, and highlight how integrative multi-omics combined with functional genomics can advance the identification of critical host determinants. This framework provides a systems-level perspective for deciphering ALV-host interactions and supports the development of more effective antiviral strategies.
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