| Abstrakt: |
Background: To date, one of the main areas of research is the creation of breeds with inherent resistance to digestive nematodes in sheep. In this context, resistance to digestive nematodes has exhibited significant phenotypic differences within and between sheep breeds, suggesting a genetic basis for these differences. According to the list of effective candidate genes and the identified gene network for parasite resistance in sheep, there are genes involved in the immune system, such as the interferon-γ gene (IFN-γ). Cytokinin is involved in biochemical immune system signaling pathways, parasite resistance, and immunological responses. In addition, certain mutations in this gene impair the ability of specialized cells of the immune system to fight off parasite invasion. One of the most popular approaches to generating gene expression data for genome function studies is DNA microarray technology, which allows the simultaneous expression of thousands of genes. Proteomics and genomics are two application areas of microarray technology. This research aims to identify and categorize some of the genes involved in the relative genetic resistance of sheep to nematode infection using microarray data. Methods: In this context, the GEO-Bank, part of the NCBI, was searched for access to open- access databases. Downloaded microarray data corresponded to infection with parasitic nematodes with the best replication (e.g., data in two resistant and sensitive groups), and the set of genes with differential expression was identified using R -based appropriate software packages (Biobase, GEOquery, limma, affy, Genfilter, Pheatmap, Plyr, Reshape2, and Ggplot2). Raw data were measured on a logarithmic scale, and the P-value fit statistics were used for expression comparisons between gene groups. Results: The main analysis was performed after precorrection and processing of the raw data because of the high intragroup variance of the data, as evidenced by the observed quality control results of the raw data and the quality control-related results of the integrated data. After pre- processing of the raw data, correlation analysis revealed a strong relationship between genes in the pre-Inf group (Pre-Inf) and the infected group (Inf) compared to the control group. Three heatmap reference charts, a PCA chart, and a volcano plot were used to verify data quality, and by verifying these charts, samples of unfavorable quality were removed from the next stages of analysis. After a bioinformatics analysis, the results showed significantly increased expression patterns (NACA, RPL4, NAGS, CTCF, GBP1, BHLHE, YTHDF3, PDHA1, and MXI1) and diminished expression patterns of PDHA1 and MXI1 genes. According to the results of this study, these genes play a role in the cellular metabolism process, molecular function, the formation of genetic connections, and cell life. Therefore, they were significant (p-value < 0.05) according to the magnitude of the change. The N-acryl glutamate synthetase (NAGS) gene is the cofactor of the first enzyme involved in the urea cycle in mammals. The functional role of this gene has been identified in many neurological diseases. The CTCF gene has a positive effect on the cells of the immune system and plays a special role in defending against viruses and pathogens that invade the host body. The guanylate binding protein 1 (GBP1) gene plays a role in the body's defense against many infectious pathogens. This gene causes oxidative reactions and autophagy of the host immune system as a barrier to invading pathogens. The methyl adenosine RNA binding 3 gene is more effective in antiviral immunity and is closely linked to the GBP1 gene, which plays a role in the body's resistance to many infectious agents. This gene causes oxidative responses and autophagy of the host immune system against invading pathogens. The PDHA1 pyruvate dehydrogenase gene is involved in immune system metabolism. This gene plays a role in allosteric factor-induced regulation, repair of covalent bonds, and relatively rapid changes in the level of expressed proteins, either through altered gene expression or proteolytic degradation. The MXI1 gene helps control the entry of invading pathogens into the host's body and promotes recovery and healing from infections. The results can be explained by several reasons, including the use of different sample breeds and laboratory techniques, the level of parasite contamination, the age of the test material, the variety of tested nematodes, and inconsistent techniques and tools of the current study with those of previous studies. Other reasons include the climatic differences between the test region and its physical location as well as the use of different RNA and microarray methods. However, the results of the study may be helpful under the related circumstances. Conclusion: The results of microarrays and differential expression patterns can be of great help to molecularly modify livestock to resist internal parasites. Using more advanced tools, such as next-gene sequencing, will provide more accurate and relevant information. [ABSTRACT FROM AUTHOR] |
