Identifying the genetic basis for resistance to avian influenza in commercial egg layer chickens

Genetic Variation in Natural and Induced Antibody Responses in Layer Chickens

Selection of livestock for disease resistance is challenging due to the difficulty in obtaining reliable phenotypes. Antibodies are immunological molecules that provide direct and indirect defenses against infection and link the activities of both the innate and adaptive compartments of the immune system. As a result, antibodies have been used as a trait in selection for immune defense. The goal of this study was to identify genomic regions associated with natural and induced antibodies in chickens using low-pass sequencing. Enzyme-linked immunosorbent assays were used to quantify innate (natural) antibodies binding KLH, OVA, and PHA and induced (adaptive) antibodies binding IBD, IBV, NDV, and REO. We collected plasma from four White Leghorn (WL), two White Plymouth Rock (WPR), and two Rhode Island Red (RIR) lines. Samples numbers ranged between 198 and 785 per breed. GWAS was performed within breed on data pre-adjusted for Line-Hatch-Sex effects using GCTA. A threshold of p = 10-6 was used to select genes for downstream annotation and enrichment analysis with SNPEff and Panther. Significant enrichment was found for the defense/immunity protein, immunoglobulin receptor superfamily, and the antimicrobial response protein in RIR; and the immunoglobulin receptor superfamily, defense/immunity protein, and protein modifying enzyme in WL. However, none were present in WPR, but some of the selected SNP were annotated in immune pathways. This study provides new insights regarding the genetics of the antibody response in layer chickens.

Divergent Selection in Low Recombination Regions Shapes the Genomic Islands in Two Incipient Shorebird Species

Speciation in the face of gene flow is usually associated with a heterogeneous genomic landscape of divergence in nascent species pairs. However, multiple factors, such as divergent selection and local recombination rate variation, can influence the formation of these genomic islands. Examination of the genomic landscapes of species pairs that are still in the early stages of speciation provides an insight into this conundrum. In this study, population genomic analyses were undertaken using a wide range of sampling and whole-genome resequencing data from 96 unrelated individuals of Kentish plover (Charadrius alexandrinus) and white-faced plover (Charadrius dealbatus). We suggest that the two species exhibit varying levels of population admixture along the Chinese coast and on the Taiwan Island. Genome-wide analyses for introgression indicate that ancient introgression had occurred in Taiwan population, and gene flow is still ongoing in mainland coastal populations. Furthermore, we identified a few genomic regions with significant levels of interspecific differentiation and local recombination suppression, which contain several genes potentially associated with disease resistance, coloration, and regulation of plumage molting and thus may be relevant to the phenotypic and ecological divergence of the two nascent species. Overall, our findings suggest that divergent selection in low recombination regions may be a main force in shaping the genomic islands in two incipient shorebird species.

A pangenome graph reference of 30 chicken genomes allows genotyping of large and complex structural variants

BACKGROUND

The red junglefowl, the wild outgroup of domestic chickens, has historically served as a reference for genomic studies of domestic chickens. These studies have provided insight into the etiology of traits of commercial importance. However, the use of a single reference genome does not capture diversity present among modern breeds, many of which have accumulated molecular changes due to drift and selection. While reference-based resequencing is well-suited to cataloging simple variants such as single-nucleotide changes and short insertions and deletions, it is mostly inadequate to discover more complex structural variation in the genome.

METHODS

We present a pangenome for the domestic chicken consisting of thirty assemblies of chickens from different breeds and research lines.

RESULTS

We demonstrate how this pangenome can be used to catalog structural variants present in modern breeds and untangle complex nested variation. We show that alignment of short reads from 100 diverse wild and domestic chickens to this pangenome reduces reference bias by 38%, which affects downstream genotyping results. This approach also allows for the accurate genotyping of a large and complex pair of structural variants at the K feathering locus using short reads, which would not be possible using a linear reference.

CONCLUSIONS

We expect that this new paradigm of genomic reference will allow better pinpointing of exact mutations responsible for specific phenotypes, which will in turn be necessary for breeding chickens that meet new sustainability criteria and are resilient to quickly evolving pathogen threats.

Comparative Investigation of Coincident Single Nucleotide Polymorphisms Underlying Avian Influenza Viruses in Chickens and Ducks

Avian influenza is a severe viral infection that has the potential to cause human pandemics. In particular, chickens are susceptible to many highly pathogenic strains of the virus, resulting in significant losses. In contrast, ducks have been reported to exhibit rapid and effective innate immune responses to most avian influenza virus (AIV) infections. To explore the distinct genetic programs that potentially distinguish the susceptibility/resistance of both species to AIV, the investigation of coincident SNPs (coSNPs) and their differing causal effects on gene functions in both species is important to gain novel insight into the varying immune-related responses of chickens and ducks. By conducting a pairwise genome alignment between these species, we identified coSNPs and their respective effect on AIV-related differentially expressed genes (DEGs) in this study. The examination of these genes (e.g., CD74, RUBCN, and SHTN1 for chickens and ABCA3, MAP2K6, and VIPR2 for ducks) reveals their high relevance to AIV. Further analysis of these genes provides promising effector molecules (such as IκBα, STAT1/STAT3, GSK-3β, or p53) and related key signaling pathways (such as NF-κB, JAK/STAT, or Wnt) to elucidate the complex mechanisms of immune responses to AIV infections in both chickens and ducks.

Dual Host and Pathogen RNA-Seq Analysis Unravels Chicken Genes Potentially Involved in Resistance to Highly Pathogenic Avian Influenza Virus Infection

Highly pathogenic avian influenza viruses (HPAIVs) cause severe systemic disease and high mortality rates in chickens, leading to a huge economic impact in the poultry sector. However, some chickens are resistant to the disease. This study aimed at evaluating the mechanisms behind HPAIV disease resistance. Chickens of different breeds were challenged with H7N1 HPAIV or clade 2.3.4.4b H5N8 HPAIV, euthanized at 3 days post-inoculation (dpi), and classified as resistant or susceptible depending on the following criteria: chickens that presented i) clinical signs, ii) histopathological lesions, and iii) presence of HPAIV antigen in tissues were classified as susceptible, while chickens lacking all these criteria were classified as resistant. Once classified, we performed RNA-Seq from lung and spleen samples in order to compare the transcriptomic signatures between resistant and susceptible chickens. We identified minor transcriptomic changes in resistant chickens in contrast with huge alterations observed in susceptible chickens. Interestingly, six differentially expressed genes were downregulated in resistant birds and upregulated in susceptible birds. Some of these genes belong to the NF-kappa B and/or mitogen-activated protein kinase signaling pathways. Among these six genes, the serine protease-encoding gene PLAU was of particular interest, being the most significantly downregulated gene in resistant chickens. Expression levels of this protease were further validated by RT-qPCR in a larger number of experimentally infected chickens. Furthermore, HPAIV quasi-species populations were constructed using 3 dpi oral swabs. No substantial changes were found in the viral segments that interact with the innate immune response and with the host cell receptors, reinforcing the role of the immune system of the host in the clinical outcome. Altogether, our results suggest that an early inactivation of important host genes could prevent an exaggerated immune response and/or viral replication, conferring resistance to HPAIV in chickens.

Direct and indirect contributions of molecular genetics to farm animal welfare: a review

Since domestication, farm animals have played a key role to increase the prosperity of humankind, while animal welfare (AW) is debated even today. This paper aims to comprehensively review the contributions of developing molecular genetics to farm animal welfare (FAW) and to raise awareness among both scientists and farmers about AW. Welfare is a complex trait affected by genetic structure and environmental factors. Therefore, the best welfare status can be achieved not only to enhance environmental factors such as management and feeding practices, but also the genetic structure of animals must be improved. In this regard, advances in molecular genetics have made great contributions to improve the genetic structure of farm animals, which has increased AW. Today, by sequencing and/or molecular markers, genetic diseases may be detected and eliminated in local herds. Additionally, genes related to diseases or adaptations are investigated by molecular techniques, and the frequencies of desired genotypes are increased in farm animals to keep welfare at an optimized level. Furthermore, stress on animals can be reduced with DNA extraction from stool and feather samples which reduces physical contact between animals and veterinarians. Together with molecular genetics, advances in genome editing tools and biotechnology are promising to improve FAW in the future.

Genetic determinants of resistance to highly pathogenic avian influenza in chickens

Highly pathogenic avian influenza (HPAI) poses a huge threat to poultry production and also introduces an epidemiological risk in the human population. Thus far, HPAI has been controlled mainly through widespread implementation of biosecurity, and in the case of an outbreak, liquidation of flocks and establishment of protection zones. Alternative strategies for combating HPAI include the use of vaccines, genetic modification, and genetic selection for increased general and specific immunity in birds. These kinds of strategies often require identification of the genes involved in the immune response to the pathogen. Many genes have been identified as potentially associated with differences in the response to HPAI between poultry species and between individuals. Thus far, the most attention has been focused on genes taking part in regulating the innate immune response, which is responsible for preventing infection and limiting the replication and spread of the virus. The most commonly mentioned candidates for layer chickens include interferon-stimulated genes (ISGs) and RIG-I-like receptors. Proteins encoded by genes of the BTLN family, defensins, and proteins involved in apoptosis have also been associated with differences in the response to HPAI. Recent years have seen an increasing number of studies on the genetic determinants of individual differences in the response to HPAI in chickens. Data from HPAI outbreaks in the US in the spring of 2015 and Mexico in the years 2012-2016 have enabled a more precise analysis of this problem. A number of genes have been identified as associated with the immune response, but their specific role in determining the survival of birds requires further study. Preliminary results indicate that genetic determinants of resistance to HPAI are highly complex and can vary depending on the virus strain and the genetic line of birds.

Creating Disease Resistant Chickens: A Viable Solution to Avian Influenza?

Influenza A virus (IAV) represents an ongoing threat to human and animal health worldwide. The generation of IAV-resistant chickens through genetic modification and/or selective breeding may help prevent viral spread. The feasibility of creating genetically modified birds has already been demonstrated with the insertion of transgenes that target IAV into the genomes of chickens. This approach has been met with some success in minimising the spread of IAV but has limitations in terms of its ability to prevent the emergence of disease. An alternate approach is the use of genetic engineering to improve host resistance by targeting the antiviral immune responses of poultry to IAV. Harnessing such resistance mechanisms in a “genetic restoration” approach may hold the greatest promise yet for generating disease resistant chickens. Continuing to identify genes associated with natural resistance in poultry provides the opportunity to identify new targets for genetic modification and/or selective breeding. However, as with any new technology, economic, societal, and legislative barriers will need to be overcome before we are likely to see commercialisation of genetically modified birds.

Genomic prediction of avian influenza infection outcome in layer chickens

Avian influenza (AI) is a devastating poultry disease that currently can be controlled only by liquidation of affected flocks. In spite of typically very high mortality rates, a group of survivors was identified and genotyped on a 600K single nucleotide polymorphism (SNP) chip to identify genetic differences between survivors, and age- and genetics-matched controls from unaffected flocks. In a previous analysis of this dataset, a heritable component was identified and several regions that are associated with outcome of the infection were localized but none with a large effect. For complex traits that are determined by many genes, genomic prediction models using all SNPs across the genome simultaneously are expected to optimally exploit genomic information. In this study, we evaluated the diagnostic value of genomic estimated breeding values for predicting AI infection outcome within and across two highly pathogenic avian influenza viral strains and two genetic lines of layer chickens using receiver operating curves. We show that genomic prediction based on the 600K SNP chip has the potential to predict disease outcome especially within the same strain of virus (area under receiver operating curve above 0.7), but did not predict well across genetic varieties (area under receiver operating curve of 0.43).