Document Type : Research Paper
Authors
1 Assistant Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran.
2 Associate Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran.
3 Assistant Professor, Department of Agriculture, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran.
Abstract
Introduction: Identifying signatures of selection can provide valuable insights about the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. In the last decade, most selection programs in meat type chicken had been mainly focused on fast growing and optimal feed efficiency. This selection for rapid growth has been resulted an accumulation of fatty tissue and decrease of chicken meat quality, it has been new challenges in poultry breeding due to genetic correlation between rapid growing and fat deposition. Understanding the genomic features of poultry is essential for successful breeding programs and conservation. This study aimed to identify effective genes and genomic regions on positive signature of selection in broiler at seven weeks by linkage disequilibrium-based method.
Materials and Methods: In the present study, a total 475 chickens from two chicken lines divergently selected were obtained using the Illumina chicken 60 K SNP chip. The broilers used in this study were from two Chinese broiler lines. In the first step, for the detected regions of the genome were evaluated using the XP-EHH method based on linkage disequilibrium using Selscan software v.2.0. Candidate genomic regions and genes were identified by SNPs located at 1% upper range of XP-EHH values in ten creeping windows. Finally, GeneCards and DAVID databases were also used to interpret the function of the obtained genes. Additionally, the latest published version of Animal genome database was used for defining QTLs associated with fat deposition traits in identified locations.
Results and Discussion: Candidate genes STAB2, TAPT1, JDP2, FNDC3B, PTPN11, ADIPOR1 and SLC44A3 obtained these regions. Further investigation using bioinformatics tools showed these genomic regions overlapped with lipid metabolism, fatty acid transport, lipoprotein receptors, glucose metabolism and homeostasis. Various genes that were founded within these regions can be considered as candidates under selection based on function. Also, a survey on extracted QTLs showed that these QTLs involved in some economically important traits in chicken such as abdominal fat weight and carcass fat weight traits.
Conclusion: However, will be necessary to carry out more association and functional studies to demonstrate the implication of genes obtained from association analyses. Identifying important economic traits and locating parts of the genome that have changed as a result of selection could be used in poultry breeding programs. The results of our research can be used to understand the genetic mechanism controlling fat deposition trait and using these findings could potentially be useful for genetic selection in chicken for increasing body weight while reducing body fat deposition during a broiler breeding.
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