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Disease & heat resistance

Investigating the Genomic Architecture of Avian Influenza Resistance in Asian chickens

Authors
  • Ankit Hinsu (The Royal Veterinary College)
  • Tairrie Bremner (Royal Veterinary College)
  • Md Ahasanul Hoque (Chattogram Veterinary and Animal Sciences University)
  • Hoa Pham (CIRAD)
  • Guillaume Fournie (French National Institute for Agricultural Research (INRAE))
  • Damer Blake (Royal Veterinary College)
  • Fiona Tomley (Royal Veterinary College)
  • Androniki Psifidi (The Royal Veterinary College)

Abstract

Poultry are a major global source of animal protein, essential for food security and economic growth. Rising demand for affordable meat and eggs has spurred rapid industry growth, but infectious diseases remain a significant challenge. Avian influenza virus (AIV) is a major threat to poultry with outbreaks of disease disrupting food supply, causing economic losses and creating significant public health concerns, including the risk that new strains will emerge which have pandemic potential. Due to AIV's rapid evolution, endemic nature, and fast transmission, traditional controls like vaccination, biosecurity, movement limits, and culling are less effective, underscoring the need for new strategies. This study estimated the heritability and investigated the genetic architecture of resistance to AIV in different chicken populations using genome-wide association studies (GWAS). Samples were collected in Bangladesh and Vietnam from fast- and slow-growing broilers and indigenous chicken types as part of the UKRI-funded GCRF One Health Poultry Hub (https://www.onehealthpoultry.org/). A first cross-sectional round of sampling targeted farms, markets, and slaughterhouses, while a second round comprised longitudinal sampling on farms. Chickens with natural AIV infection were identified by qRT-PCR. Genomic DNA was extracted from individual blood samples preserved on FTA cards and processed for skim-genome sequencing. The resulting data were imputed to approximately 28 million variants, enabling high-resolution genomic analysis. Heritability was estimated using GCTA, and GWAS were conducted using GCTA and GEMMA for AIV infection status (cases vs controls) phenotype. Statistical models accounted for population structure and environmental covariates to ensure robust detection of genetic associations and provide a comprehensive framework to identify candidate loci linked to AIV resistance in these diverse chicken populations. For population level data from 1436 birds, a significant heritability of 0.39 (SE=0.1, p-value< 0.001) was observed, and from GWAS, three SNPs reached genome-wide suggestive (1/nSNPs) significance. Within 100 kb of these SNPs, we identified genes associated with cell-cell signalling and stress response pathways. Chicken type-specific GWAS revealed many additional significant SNPs at the genome-wide level with minimal overlaps between types. However, the implicated genomic regions consistently showed enrichment for pathways related to cytokine response and neutrophil chemotaxis, suggesting a potential link between genetic variants and AIV resistance. These findings provide compelling evidence that supports a genetic basis of resilience to AIV in chickens and establishes a foundation for incorporating genetic markers into breeding strategies aimed at enhancing disease resilience. Ongoing studies integrating gene expression (RNA-seq) profiling from the same birds will further refine understanding of host resistance mechanisms. By identifying genetic markers linked to disease resistance, our work aims to inform selective breeding programs that will enhance poultry health and reduce the risk of outbreaks. These findings have the potential to support sustainable poultry production systems, safeguard food security, and minimize zoonotic threats.

Keywords: 2026

How to Cite:

Hinsu, A., Bremner, T., Hoque, M., Pham, H., Fournie, G., Blake, D., Tomley, F. & Psifidi, A., (2026) “Investigating the Genomic Architecture of Avian Influenza Resistance in Asian chickens”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2285633. doi: https://doi.org/10.31274/wcgalp.23761

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Published on
2026-02-25

Peer Reviewed