Identification of new major histocompatibility complex-B Haplotypes in Bangladesh native chickens.

OBJECTIVE: The major histocompatibility complex in chicken demonstrates a great range of variations within varities, breeds, populations and that can eventually influence their immuneresponses. The preset study was conducted to understand the major histocompatibility complex-B (MHC-B) variability in five major populations of Bangladesh native chicken: Aseel, Hilly, Junglefowl, Non-descript Deshi, and Naked Neck. METHODS: These five major populations of Bangladesh native chicken were analyzed with a subset of 89 single nucleotide polymorphisms (SNPs) in the high-density MHC-B SNP panel and Kompetitive Allele-Specific polymerase chain reaction genotyping was applied. To explore haplotype diversity within these populations, the results were analyzed both manually and computationally using PHASE 2.1 program. The phylogenetic investigations were also performed using MrBayes program. RESULTS: A total of 136 unique haplotypes were identified within these five Bangladesh chicken populations, and only one was shared (between Hilly and Naked Neck). Phylogenetic analysis showed no distinct haplotype clustering among the five populations, although they were shared in distinct clades; notably, the first clade lacked Naked Neck haplotypes. CONCLUSION: The present study discovered a set of unique MHC-B haplotypes in Bangladesh chickens that could possibly cause varied immune reponses. However, further investigations are required to evaluate their relationships with global chicken populations.

Major histocompatibility complex genes exhibit a potential immunological role in mixed Eimeria-infected broiler cecum analyzed using RNA sequencing.

OBJECTIVE: This study was conducted to investigate the differential expression of the major histocompatibility complex (MHC) gene region in Eimeria-infected broiler. METHODS: We profiled gene expression of Eimeria-infected and uninfected ceca of broilers sampled at 4, 7, and 21 days post-infection (dpi) using RNA sequencing. Differentially expressed genes (DEGs) between two sample groups were identified at each time point. DEGs located on chicken chromosome 16 were used for further analysis. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis was conducted for the functional annotation of DEGs. RESULTS: Fourteen significant (false discovery rate <0.1) DEGs were identified at 4 and 7 dpi and categorized into three groups: MHC-Y class I genes, MHC-B region genes, and non-MHC genes. In Eimeria-infected broilers, MHC-Y class I genes were upregulated at 4 dpi but downregulated at 7 dpi. This result implies that MHC-Y class I genes initially activated an immune response, which was then suppressed by Eimeria. Of the MHC-B region genes, the DMB1 gene was upregulated, and TAP-related genes significantly implemented antigen processing for MHC class I at 4 dpi, which was supported by KEGG pathway analysis. CONCLUSION: This study is the first to investigate MHC gene responses to coccidia infection in chickens using RNA sequencing. MHC-B and MHC-Y genes showed their immune responses in reaction to Eimeria infection. These findings are valuable for understanding chicken MHC gene function.

Genome-wide association study for the free amino acid and nucleotide components of breast meat in an F2 crossbred chicken population.

Flavor is an important sensory trait of chicken meat. The free amino acid (FAA) and nucleotide (NT) components of meat are major factors affecting meat flavor during the cooking process. As a genetic approach to improve meat flavor, we performed a genome-wide association study (GWAS) to identify the potential candidate genes related to the FAA and NT components of chicken breast meat. Measurements of FAA and NT components were recorded at the age of 10 weeks from 764 and 767 birds, respectively, using a White leghorn and Yeonsan ogye crossbred F2 chicken population. For genotyping, we used 60K Illumina single-nucleotide polymorphism (SNP) chips. We found a total of nine significant SNPs for five FAA traits (arginine, glycine, lysine, threonine content, and the essential FAAs and one NT trait (inosine content), and six significant genomic regions were identified, including three regions shared among the essential FAAs, arginine, and inosine content traits. A list of potential candidate genes in significant genomic regions was detected, including the KCNRG, KCNIP4, HOXA3, THSD7B, and MMUT genes. The essential FAAs had significant gene regions the same as arginine. The genes related to arginine content were involved in nitric oxide metabolism, while the inosine content was possibly affected by insulin activity. Moreover, the threonine content could be related to methylmalonyl-CoA mutase. The genes and SNPs identified in this study might be useful markers in chicken selection and breeding for chicken meat flavor.

Application of next-generation sequencing for the high-resolution typing of MHC-B in Korean native chicken.

The major histocompatibility complex-B (MHC-B) region of chicken is crucially important in their immunogenesis and highly diverse among different breeds, lines, and even populations. Because it determines the resistance/susceptibility to numerous infectious diseases, it is important to analyze this genomic region, particularly classical class I and II genes, to determine the variation and diversity that ultimately affect antigen presentation. This study investigated five lines of indigenous Korean native chicken (KNC) and the Ogye breed using next-generation sequencing (NGS) data with Geneious Prime-based assembly and variant calling with the Genome Analysis Toolkit (GATK) best practices pipeline. The consensus sequences of MHC-B (BG1-BF2) were obtained for each chicken line/breed and their variants were analyzed. All of the Korean native chicken lines possessed an excessive number of variants, including an ample amount of high-impact variants that provided useful information regarding modified major histocompatibility complex molecules. The study confirmed that next-generation sequencing techniques can effectively be used to detect MHC variabilities and the KNC lines are highly diverse for the MHC-B region, suggesting a substantial divergence from red junglefowl.

Single nucleotide polymorphism marker combinations for classifying Yeonsan Ogye chicken using a machine learning approach.

Genetic analysis has great potential as a tool to differentiate between different species and breeds of livestock. In this study, the optimal combinations of single nucleotide polymorphism (SNP) markers for discriminating the Yeonsan Ogye chicken (Gallus gallus domesticus) breed were identified using high-density 600K SNP array data. In 3,904 individuals from 198 chicken breeds, SNP markers specific to the target population were discovered through a case-control genome-wide association study (GWAS) and filtered out based on the linkage disequilibrium blocks. Significant SNP markers were selected by feature selection applying two machine learning algorithms: Random Forest (RF) and AdaBoost (AB). Using a machine learning approach, the 38 (RF) and 43 (AB) optimal SNP marker combinations for the Yeonsan Ogye chicken population demonstrated 100% accuracy. Hence, the GWAS and machine learning models used in this study can be efficiently utilized to identify the optimal combination of markers for discriminating target populations using multiple SNP markers.

Time-series transcriptome analysis identified differentially expressed genes in broiler chicken infected with mixed Eimeria species.

Coccidiosis caused by the Eimeria species is a highly problematic disease in the chicken industry. Here, we used RNA sequencing to observe the time-dependent host responses of Eimeria-infected chickens to examine the genes and biological functions associated with immunity to the parasite. Transcriptome analysis was performed at three time points: 4, 7, and 21 days post-infection (dpi). Based on the changes in gene expression patterns, we defined three groups of genes that showed differential expression. This enabled us to capture evidence of endoplasmic reticulum stress at the initial stage of Eimeria infection. Furthermore, we found that innate immune responses against the parasite were activated at the first exposure; they then showed gradual normalization. Although the cytokine-cytokine receptor interaction pathway was significantly operative at 4 dpi, its downregulation led to an anti-inflammatory effect. Additionally, the construction of gene co-expression networks enabled identification of immunoregulation hub genes and critical pattern recognition receptors after Eimeria infection. Our results provide a detailed understanding of the host-pathogen interaction between chicken and Eimeria. The clusters of genes defined in this study can be utilized to improve chickens for coccidiosis control.