The genome contributes to the uniqueness of an individual breed, and enables distinctive characteristics to be passed from one generation to the next. The allelic heterogeneity of a certain breed results in a different response to a pathogen with different genomic expression. Disease resistance in chicken is a polygenic trait that involves different genes that confer resistance against pathogens. Such resistance also involves major histocompatibility (MHC) molecules, immunoglobulins, cytokines, interleukins, T and B cells, and CD4+ and CD8+ T lymphocytes, which are involved in host protection. The MHC is associated with antigen presentation, antibody production, and cytokine stimulation, which highlight its role in disease resistance. The natural resistance-associated macrophage protein 1 (Nramp-1), interferon (IFN), myxovirus-resistance gene, myeloid differentiation primary response 88 (MyD88), receptor-interacting serine/threonine kinase 2 (RIP2), and heterophile cells are involved in disease resistance and susceptibility of chicken. Studies related to disease resistance genetics, epigenetics, and quantitative trait loci would enable the identification of resistance markers and the development of disease resistance breeds. Microbial infections are responsible for significant outbreaks and have blighted the poultry industry. Breeding disease-resistant chicken strains may be helpful in tackling pathogens and increasing the current understanding on host genetics in the fight against communicable diseases. Advanced technologies, such as the CRISPR/Cas9 system, whole genome sequencing, RNA sequencing, and high-density single nucleotide polymorphism (SNP) genotyping, aid the development of resistant breeds, which would significantly decrease the use of antibiotics and vaccination in poultry. In this review, we aimed to reveal the recent genetic basis of infection and genomic modification that increase resistance against different pathogens in chickens.
The present study was designed to evaluate the association of polymorphisms in bovine trafficking protein particle complex subunit 9 (TRAPPC9) and cluster of differentiation 4 (CD4) genes with milk production and mastitis resistance phenotypic traits in a different cattle population. Three single nucleotide polymorphisms (SNPs) (SNP1 Position: Chr14:2484891, SNP2 (rs110017379), SNP3 Position: Chr14:2525852) in bovine TRAPPC9 and one SNP (Position: Chr5:104010752) in CD4 were screened through Chinese Cow's SNPs Chip-I (CCSC-I) and genotyped in a population of 312 Chinese Holsteins (156: Mastitis, 156: Healthy). The results were analyzed using the general linear model in SAS 9.4. Our analysis revealed that milk protein percentage, somatic cell count (SCC), somatic cell score (SCS), serum cytokines interleukin 6 (IL-6) and interferon-gamma (IFN-γ) were significantly (P < 0.05) associated with at least one or more identified SNPs of TRAPPC9 and CD4 genes. Furthermore, the expression status of SNPs in CD4 and TRAPPC9 genes were verified through RT-qPCR. The expression analysis showed that genotypes GG in SNP3 of TRAPPC9 and TT genotype in SNP4 of CD4 showed higher expression level compared to other genotypes. The GG genotype in SNP2 and TT genotype in SNP3 of TRAPPC9 were associated with higher bovine milk SCC and lower IL6. Altogether, our findings suggested that the SNPs of TRAPPC9 and CD4 genes could be useful genetic markers in selection for milk protein improvement and mastitis resistance phenotypic traits in dairy cattle. The CCSC-I used in current study is proposed to be validate in different and large population of dairy cattle not only in China but also in other countries. Moreover, our analyses recommended that besides SCC and SCS, the association of genetic markers could also be considered with the serum cytokines (IL-6, IFN-γ) while selecting genetically mastitis resistance dairy cattle.
In the current study, we investigated dairy cows’ circulating microRNA (miRNA) expression signature during several key time points around calving, to get insights into different aspects of metabolic adaptation. In a trial with 32 dairy cows, plasma samples were collected on days −21, 1, 28, and 63 relative to calving. Individually extracted total RNA was subjected to RNA sequencing using NovaSeq 6,000 (Illumina, CA) on the respective platform of IGA Technology Services, Udine, Italy. MiRDeep2 was used to identify known and novel miRNA according to the miRbase collection. Differentially expressed miRNA (DEM) were assessed at a threshold of fold-change > 1.5 and false discovery rate < 0.05 using the edgeR package. The MiRWalk database was used to predict DEM targets and their associated KEGG pathways. Among a total of 1,692 identified miRNA, 445 known miRNA were included for statistical analysis, of which 84, 59, and 61 DEM were found between days −21 to 1, 1 to 28, and 28 to 63, respectively. These miRNA were annotated to KEGG pathways targeting the insulin, MAPK, Ras, Wnt, Hippo, sphingolipid, T cell receptor, and mTOR signaling pathways. MiRNA-mRNA network analysis identified miRNA as master regulators of the biological process including miR-138, miR-149-5p, miR-2466-3p, miR-214, miR-504, and miR-6523a. This study provided new insights into the miRNA signatures of transition to the lactation period. Calving emerged as a critical time point when miRNA were most affected, while the following period appeared to be recovering from massive parturition changes. The primarily affected pathways were key signaling pathways related to establishing metabolic and immune adaptations.
Frontiers in Public Health
Emerging Infectious and Vector-Borne Diseases: A Global Challenge