Identification of genetic variants in Arian line and investigation of their performance using whole genome sequencing

Document Type : Research Paper

Authors

1 Ph.D student, Institute of Biotechnology, School of Agriculture, Shiraz University, Shiraz, Iran.

2 Associate professor, Institute of Biotechnology, School of Agriculture, Shiraz University, Shiraz, Iran.

3 Associate professor, Department of Animal science, School of Agriculture, Shiraz University, Shiraz, Iran.

4 Professor, Institute of Biotechnology, School of Agriculture, Shiraz University, Shiraz, Iran..

5 Professor, Department of Animal science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran.

Abstract

Objective
This is the first study for discovering genetic variants in Arian line by whole genome sequencing data. The study of Arian line features at genomic level can unravel the genetic background of economic traits such as growth.
 
Materials and methods
In this study, the information of three whole genomes of Arian chickens was used.
 
Results
The results of this study indicated that, there were 63866 common variants among samples. 17604 variants Out of 63866 variants were reported as novel variants in this study. Also 604 variants are located in coding regions, which 204 out of them lead to change in the amino acid sequence of the proteins. Considering the importance of dietary protein quality for growth and weight gain for poultry, the results of gene ontology analysis indicated that the pathways of protein catabolism and post-translational modification of proteins, related to growth are considerable. Also candidate genes such as, SMURF2 and SUMO1 was suggested for these biological pathways. Another interesting result of gene ontology was the significance of response to stress pathways.
 
Conclusions
In the Arian line due to intense selection, the existence of stress is inevitable. Therefore, the significance of stress response can indicate the importance of these pathways in relation to the desired performance.

Keywords


References
Alkan C, Coe BP, Eichler EE (2011). Genome structural variation discovery and genotyping. Nature Reviews Genetics 12: 363-376.
Axelsson E, Ratnakumar A, Arendt M, Maqbool K, Webster M, Perloski M, Liberg O, Arnemo J, Hedhammar A, Lindblad-Toh K (2013). The genomic signature of dog domestication reveals adaptation to a starch-rich diet. Nature 495: 360-365.
Buysse K, Delle Chiaie B, Van Coster R, Loeys B, De Paepe A, Mo111rtier G, Speleman F, Menten B (2009). Challenges for CNV interpretation in clinical molecular karyotyping: lessons learned from a 1001 sample experience. European Journal of Medical Genetics 52: 398-403.
Connerly PL (2010). How do proteins move through the golgi apparatus? Nature Education 3: 60.
Craig TJ, Henley JM (2012). Protein SUMOylation in spine structure and function. Current Opinion in Neurobiology 22: 480–487.
Dharmasiri S, Dharmasiri N, Hellmann H, Estelle M (2003). The RUB/Nedd8 conjugation pathway is required for early development in Arabidopsis. EMBO Journal 22: 1762–1770.
Dias, M. Cánovas AMantilla-Rojas CRiley DGLuna-Nevarez PColeman SJSpeidel SEEnns RM5, Islas-Trejo AMedrano JFMoore SSFortes MR,  Venus BDiaz ISSouza FRFonseca LFBaldi FAlbuquerque LGThomas MGOliveira HN (2017). SNP detection using RNA-sequences of candidate genes associated with puberty in cattle. Genetics Molecular Research 16, DOI: 10.4238/gmr16019522.
 Doan R, Cohen ND, Sawyer J, Ghaffari N, Johnson DC, Dindot SV (2012). Whole-genome sequencing and genetic variant analysis of a Quarter Horse mare. BMC genomics 13, DOI: 10.1186/1471-2164-13-78.
Elferink MG, Megens HJ, Vereijken A, Hu X, Crooijmans RPMA, Groenen MAM (2012). signatures of selection in the genomes of commercial and non-commercial chicken breeds. Plos one 7: e32720.
 Fleming DS, Koltes JE, Markey AD, Schmidt CJ, Ashwell CM, Rothchild MF, Reecy MJ, Lamont SJ (2016). Genomic analysis of Ugandan and Rwandan chicken ecotypes using a 600K genotyping array. BMC Genomics. DOI:10.1186/s12864-016-2711-5.
Gholami M, Erbe M, Garke C, Preisinger R, Weigend A, Weigend S, Simianer H (2014). Population Genomic Analyses Based on 1 Million SNPs in Commercial Egg Layers. Plos one 9: e94509.
Giaever G, Chu AM, Ni L, Connelly C, Riles L, Veronneau S, Dow S, Lucau-Danila A, Anderson K, Andre B, et al (2002). Functional profiling of the Saccharomyces cerevisiae genome. Nature 418: 387–391.
Groen AJ, Sancho-Andrés G, Breckels LM, Gatto L, Aniento F, Kathryn S. Lilley KS (2014). Identification of trans-golgi network proteins in Arabidopsis thaliana root tissue. Journal dharof Proteome Research 13: 763–776.
Kharrati-Koopaee H, Esmailizadeh AK (2014). SNPs Genotyping Technologies and Their Applications in Farm Animals Breeding Programs: Review. Brazilian Archives of Biology and Technology 57: 87-95.
Lander ES, Waterman MS (1988). Genomic mapping by fingerprinting random clones: a mathematical analysis. Genomics 2: 231-239.
Mergner J, Kuster B, Schwechheimer C (2017). DENEDDYLASE1 Protein counters auto-modification of neddylating enzymes to maintain NEDD8 protein homeostasis in arabidopsis. Journal of Biological Chemistry 292: 3854-3865.
Metzker ML (2010). Sequencing technologies - the next generation. Nature Reviews Genetics 11:31-46.
Miller SA, Dykes DD, Polesky HF (1988). A simple salting-out procedure for extracting DNA from human nucleated cells. Nucleic Acids Researches 16: 1215.
Moazeni S, Mohammadabadi MR, Sadeghi M, Shahrbabak H, Koshkoieh A, Bordbar F (2016a). Association between UCP Gene Polymorphisms and Growth, Breeding Value of Growth and Reproductive Traits in Mazandaran Indigenous Chicken. Open Journal of Animal Sciences 6: 1-8.
Moazeni SM, Mohammadabadi MR, Sadeghi M, Moradi Shahrbabak H, Esmailizadeh AK (2016b). Association of the melanocortin-3(MC3R) receptor gene with growth and reproductive traits in Mazandaran indigenous chicken. Journal of Livestock Science and Technologies 4: 51-56. 
Mohammadabadi MR., Nikbakhti M, Mirzaee HR, Shandi A, Saghi DA, Romanov MN, Moiseyeva IG (2010). Genetic variability in three native Iranian chicken populations of the Khorasan province based on microsatellite markers. Russian Journal of Genetics 46: 505-509.    
Mudalal S, Babini E, Cavani C, Petracci M (2014). Quantity and functionality of protein fractions in chicken breast fillets affected by white striping. Poultry Science 93: 2108–2116.
Mukhopadhyay D, Riezman H (2007). Proteasome-independent functions of ubiquitin in endocytosis and signaling. Science 315: 201–205. 
Rubin C, Zody M, Erikson J, Meadows J, Sherwood E, Webster M, Jiang l, Ingman M, Sharpe T, Ka S, Hallbook F, Besnier F, Carlborg O, Bedhom B, Jensen P (2010). Whole genome resequencing reveals loci under selection during chicken domestication. Nature Letters 464: 587-593.
 Shahdadnejad N, Mohammadabadi MR, Shamsadini M (2016). Typing of Clostridium Perfringens Isolated from Broiler Chickens Using Multiplex PCR. Genetics in the 3rd millennium 14: 4368-4374.
Tibbles LAWoodgett JR (1999). The stress-activated protein kinase pathways. Cellular Molecular Life Science 55: 1230-1254.
Xirodimas DP (2008). Novel substrates and functions for the ubiquitin-like molecule NEDD8. Biochemical Society Transactions 36: 802-806.
Zandi E, Mohammadabadi MR, Ezzatkhah M, Esmailizadeh AK (2014). Typing of Toxigenic Isolates of Clostridium Perfringens by Multiplex PCR in Ostrich. Iranian Journal of Applied Animal Science 4: 509-514.
Zhang H, Wang SZ, Wang ZP, Da Y, Wang N, Hu XX, Zhang YD, Wang YX, Leng L, Tang ZQ, Li h (2012). A genome-wide scan of selective sweeps in two broiler chicken lines divergently selected for abdominal fat content. BMC Genetics 13: 704-720.
Zhu JY, Fu Y, Nettleton M, Richman A, Han Z (2017). High throughput in vivo functional validation of candidate congenital heart disease genes in Drosophila. Developmental Biology, Human Biology and Medicine DOI: 10.7554/eLife.22617.