Volume 13, Issue 35 (3-2022)                   rap 2022, 13(35): 149-157 | Back to browse issues page


XML Persian Abstract Print


Department of Biotechnology Research, Animal Science Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran
Abstract:   (1546 Views)
Extended Abstract
Introduction and Objective: Breeding between Indus cows and Taurus cows in the Sistan region of Iran has been done in recent years through the use of liquid sperm, frozen sperm, or foreign bulls. There are few studies in Iran on the effects of interbreeding programs on Sistani cattle. The present study was performed to identify mononucleotide polymorphisms (SNPs) based on RNA-Seq data in purebred Sistani cows and its crosses with three foreign breeds of Holstein, Simmental, and MonteBilliarde cows.
Material and Methods: In this study, RNA-Seq data were used for pure Sistani, Sistani and Holstein, Sistani and Montebeliarde, Sistani and Simmental cattle. For this purpose, first of the tail vein of purebred cattle mixed with Holstein, Simmental, and MonteBilliarde. (4 treatments and for each treatment two biological replications) in the same environmental, nutritional, and managerial conditions located in the breeding center of Sistani cattle in Zabol. blood was drawn.
Results: SNP discovery analysis was performed on transcriptome using SAMtools software package, which led to the discovery of 152496, 177042, 134285, and 163362 SNPs in pure Sistani breeds and its crosses with three foreign breeds of Holstein, Simmental, and Montebeliarde bulls. In this study, there was no direct relationship between the number of SNPs identified and the length of chromosomes. Also, 12 types of SNPs were identified, of which four types were transition and eight types were transversion. The most common known SNPs were transition which was 71.84% in pure Sistani, 72.65% in Sistani and Holstein, 72.60% in Sistani and Simmental, and 71.94% in Sistani and MonteBilliarde.
Conclusion: Overall, the results of this study confirmed that RNA-Seq technology is an effective, economical, and efficient method for identifying SNP loci. Factors influencing RNA-Seq evaluation are such as the number of samples.


 
Full-Text [PDF 1058 kb]   (449 Downloads)    
Type of Study: Research | Subject: ژنتیک و اصلاح نژاد دام
Received: 2021/08/9 | Revised: 2022/07/17 | Accepted: 2021/09/22 | Published: 2022/03/30

References
1. Asghari, E.B., Gh. Dshab, M.H. Banabazi and M. Rokouei. 2021. Analasis of Genetic Differences in Genes Associated With Immune Response Among Purebred and Crossbreed Sistani and Montebeliarde Cow Population Using RNA-Seq Data. Research on Animal Production, 12(31): 134-145 (In Persian).
2. Banabazi, M.H., A. Nejati, J.I. Imumotin, M. Gaderi and S.R. Miraei. 2017. Genetic Variance explanation of Residual Feed Intake((RFI) by SNPs discovered on transcriptome of Holstein cows. Animal Science Journal, 114: 169-182 (In Persian).
3. Bolger, A.M., M. Lohse and B. Usadel. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data, Bioiformatics, 30(15): 2114-2120. [DOI:10.1093/bioinformatics/btu170]
4. Canovas, A., G. Rincon, A. ‌Islas-Trejo, S. Wickramasinghe and J. Medrano. 2010. SNP discovery in the bovine milk transcriptome using RNA-Seq technology. mammalian Genome, 21: 592-598. [DOI:10.1007/s00335-010-9297-z]
5. Djari, A., D. Esquerre, B. Weiss, F. Martins, L. Koufariotis, Y.‌P. Chen, S. Bolormaa and B. Hayes. 2014. Regulatory and coding genome regions are enriched for trait associated variants in dairy and beef cattle. BMC Genomics, 15: 436. [DOI:10.1186/1471-2164-15-436]
6. Ehsaninia, J., M. Moradi, S.S.H. Haffezian and M.B. Sayad. 2011. Crossbreeding effects on milk fat yields performance of Iran population local cattle. Animal Sciences Journal, 91: 27-33 (In Persian).
7. Flintoft, L. 2008. Transcriptomics: Digging deep with RNA-Seq. Nature Reviews Genetics, 9(8): 568- 568. [DOI:10.1038/nrg2423]
8. Gorbani, A. and M. Behpai. 2020. Association of GDF9 Gene Polymorphism with Sperm Quality and Quantity traits in Iranian Holstein Bulls. Research Animal Production, 11(27): 95-100 (In Persian). [DOI:10.29252/rap.11.27.95]
9. https://github.com/ncbi/sra-tools.
10. Kamalzadeh, A., M. Rajabbaigy and A. Kiasat. 2008. Livestock production systems and trends in livestock industry in Iran. Journal of Agriculture and Social Sciences, 4: 183-188.
11. Li, H., B. Handsaker, A. Wysoker, T. Fennell, J. Ruan, N. Homer, G. Marth, G. Abecasis, R. Durbin and 1000 Genome Project Data Processing Subgroup. 2009. The Sequence Alignment/Map format and SAMtool. Bioinformatics, 25(16): 2078-2079. [DOI:10.1093/bioinformatics/btp352]
12. Meuwissen, T. and M. ‌Goddard. 2010. Accurate prediction of genetic values forcomplex traits by whole-genome resequencing. Genetics, 185: 623-631. [DOI:10.1534/genetics.110.116590]
13. Park, K.D., J. Park, J. Ko, J. Kim, B.‌ Kim and H.S.K. Ahn et al. 2012. Whole transcriptome analyses of six thoroughbred horses before and after exercise using RNA-Seq. BMC Genomics, 13: 437. [DOI:10.1186/1471-2164-13-473]
14. Pennisi, E. 2012. ENCODE Project Writes Eulogy for Junk DNA. Science, 337(6099): 1159-1161. [DOI:10.1126/science.337.6099.1159]
15. Pitt, D., N. Sevane, E.L. Nicolazzi, D.E. MacHugh, S.D.E. Park, L. Colli, R. Martinez, M.W. Bruford and P. Orozco-terWengel. 2019. Domestication of cattle: two or three events? Evolutionary Applications, 12(1): 123-136. doi: 10.1111/eva.12674. [DOI:10.1111/eva.12674]
16. Salimpour, M. and M.H. Banabazi. 2021. The Single Nucleotide Polymorphisms (SNP) discovery and calling on genes differentially expressed between Holstein (Bos taurus) and Cholistani(Bos indicus) cattle populations. Animal Science Journal, 130: 203-2014 (In Persian).
17. Sharma, U., P. Banerjee, J. Joshi and R.K. Vijh. 2012. Identification of SNPs in Goats (Capra hircus) using RNA-Seq Analysis. International Journal of Animal and Veterinary Advances, 4: 904-914.
18. Varkoohi, SH., M.H. Banabazy and M. Ghsemi-shib. 2021. Allele specific Expression (ASE) analysis between Bos Taurus indicus cows using RNA-Seq data at SNP level and gene level. Cellular and Molecular Biology, 93(3). E20191453. [DOI:10.1590/0001-3765202120191453]
19. Wang, L., Y. Zhang, M. Zhao, R. Wang, R. Su and J. Li. 2015. SNP Discovery from Transcriptome of Cashmere Goat Skin. Asian-Australasian Journal of Animal Acencesi, 28(9): 1235-1243. [DOI:10.5713/ajas.15.0172]
20. Wang,‌ Z., M.‌ Gerstein and M.‌ Snyder. 2009. RNA-seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics, 10: 57-63.11. [DOI:10.1038/nrg2484]
21. Zhang, C., G. Wang, J. Wang, Z. Ji, Z. Liu, X. Pi and C. Chen. 2013. Characterization and Comparative Analyses of Muscle Transcriptomes in Dorper and Small-Tailed Han Sheep Using RNA-Seq Technique. PLoS ONE, 8: e72686. [DOI:10.1371/journal.pone.0072686]

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.