In silico Methods for Modeling of Genomic Regions for Immunological and Metabolic Gene Modulating to Stress Response in Chicken: Where We Are?
الموضوعات :M.S. Ekhtiyari 1 , A.S. Sadr 2 , M. Shirali 3 , A. Javanmard 4
1 - Department of Biochemistry, Faculty of Veterinary Medicine, University of Tabriz, Tabriz, Iran
2 - Aquaculture Research Center-South of Iran, Iranian Fisheries Science Research Institute, Agricultural Research Education and Extension Organization (AREEO), Ahvaz, Iran
3 - Agri-Food and Biosciences Institute, Hillsborough, BT26 6DR, United Kingdom
4 - Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
الکلمات المفتاحية: genomics, controlling homeostasis, gene networking, stress response,
ملخص المقالة :
Traditionally, commercial broilers are not well adapted and currently subjected to a variety of environmental challenges. In recent years, researchers have shown an increased interest in stress as one of the greatest environmental challenges to the profitability of sustainable intensive poultry production. In this scenario, understanding the complexity of the molecular basis and genomics of the stress response is critical to successful breeding programs for climate-adapted chickens. Recently, numerous popular studies have attempted to identify candidate genes that control stress responses in chickens. However, a number of questions regarding the choice of stress response remain unanswered or inadequately answered regarding the number of lead candidate genes that control components of the non-infectious and infectious stress response. With this motivation, 89 journal articles were collected for the primary investigation and those with low validity were excluded from further analysis. In short, we used three types of information sources, namely: text-based systematic review, in silico modeling, and both network and pathway approaches, to introduce more effective and bio-indicators of gene-controlling stress responses in chickens through older literature. Gene ontology (GO) and pathway networking of candidate gene associated with stress was loaded into Cytoscape for analysis. The result provides additional evidence and highlights, including nearly 9 candidate genes. According to published studies, CRYAB, HSP90AA1, IL6, HSPA2, HSF2, HSPB1, HSF3, PLK1, BAG3 are mostly associated with non-infectious and infectious stressors and may deserve further attention. String database analysis illustrated role of highlighted gene in multiple cellular task and functionally such as ATPase activity, cellular processes, including protection of the proteome from stress, folding and transport of newly synthesized polypeptides, activation of proteolysis of misfold proteins and the formation and dissociation of protein complexes. Obtained information from Animal QTL database indicated important role of chromosomes numbers 2, 3, 4, 5, 12, 14 and 24 associated with stress resistance and susceptibility. On this basis, this report attempts to find out which genomic regions control homeostasis and promote cell survival, molecular transport and cell signaling.
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