Genomic scan for selection signatures in native (Sarabi, Najdi and Taleshi) and ‎Holstein cattle breeds using hapFLK method

Document Type : Research Paper

Authors

1 M.Sc. Student,, Department of Animal Science, College of Agriculture & Natural Resources, ‎University of Tehran, Karaj, Iran

2 Professor, Department of Animal Science, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

3 Assistant Professor, Department of Animal Science, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

4 Assistant Professor, Department of Animal Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran

Abstract

In order to identify the signatures of selection in three Iranian native cattle and Holstein breeds, genomic information of 153 native cattle (including 63 Sarabi, 44 Najdi and 46 Taleshi) and 60 Holstein cattle and 46 Brahma cattle (as an outgroup breed) were used. In order to determine the genotype of the samples, Illumina Bead Chip 40K (for native breeds) and Illumina Bead Chip 770K (for Holstein and Brahman breeds) were used. The genomic information of foreign breeds was extracted from the WIDDE database. After the quality control of the data, hapFLK statistical method with hapFLK v1.4 software was used to identify selection signatures. Considering the high hapFLK value of 0.1%, selection signatures were identified using the Ensmble Biomart tool, which included 57 genes on chromosome 25. Then, using the PANTHER database, the general biological function of the genes was checked, and the QTLs in the selected region were extracted using the Animalgenome database, and the genes were compared with other researches.The results showed that these genes were associated with different biological pathways such as ATP-dependent activity, binding, catalytic activity, molecular adapter activity, molecular function regulator, molecular transducer activity, transcription regulator activity and transporter activity.The QTLs reported in these areas were also related to the traits of stature and withers hight, milk yield and contents, muscle iron content, body weight and calving ease traits.

Keywords

References

  1. Boitard, S., Boussaha, M., Capitan, A., Rocha, D., & Servin, B. (2016). Uncovering adaptation from sequence data: lessons from genome resequencing of four cattle breeds. Genetics, 203(1), 433-450.
  2. Bonhomme, M., Chevalet, C., Servin, B., Boitard, S., Abdallah, J., Blott, S., & SanCristobal, M. (2010). Detecting selection in population trees: the Lewontin and Krakauer test extended. Genetics, 186(1), 241-262.
  3. Brito, L. F., Kijas, J. W., Ventura, R. V., Sargolzaei, M., Porto-Neto, L. R., Cánovas, A., Schenkel, F. S. (2017). Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers. BMC genomics, 18(1), 1-20.
  4. Caetano, A. R. (2009). Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Embrapa Recursos Genéticos e Biotecnologia-Artigo em Periódico Indexado (ALICE).
  5. Carvalheira, J., Salem, M., Thompson, G., Chen, S., & Beja-Pereira, A. (2014). Genome-wide association study for milk and protein yields in Portuguese Holstein cattle. MARS, 131(131.83), 131-183.
  6. Cassar-Malek, I., Boby, C., Picard, B., Reverter, A., & Hudson, N. J. (2017). Molecular regulation of high muscle mass in developing Blonde d'Aquitaine cattle foetuses. Biology Open, 6(10), 1483-1492.
  7. Chen, K.-L., Wang, H.-L., Jiang, L.-Z., Qian, Y., Yang, C.-X., Chang, W.-W., & Xing, G.-D. (2020). Heat stress induces apoptosis through disruption of dynamic mitochondrial networks in dairy cow mammary epithelial cells. In Vitro Cellular & Developmental Biology-Animal, 56(4), 322-331.
  8. Decker, J. E., McKay, S. D., Rolf, M. M., Kim, J., Alcalá, A. M., Sonstegard, T. S., & Praharani, L. (2014). Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle. PLoS Genet, 10(3), e1004254.
  9. Fariello, M. I., Boitard, S., Naya, H., SanCristobal, M., & Servin, B. (2013). Detecting signatures of selection through haplotype differentiation among hierarchically structured populations. Genetics, 193(3), 929-941.
  10. Gondro, C. (2015). Primer to analysis of genomic data using R: Springer.
  11. Höglund, J. K., Guldbrandtsen, B., Lund, M. S., & Sahana, G. (2012). Analyzes of genome-wide association follow-up study for calving traits in dairy cattle. BMC Genetics, 13(1), 1-9.
  12. Kijas, J. W. (2014). Haplotype-based analysis of selective sweeps in sheep. Genome, 57(8), 433-437.
  13. Kuehn, L., Keele, J., Bennett, G., McDaneld, T., Smith, T., Snelling, W., & Thallman, R. (2011). Predicting breed composition using breed frequencies of 50,000 markers from the US Meat Animal Research Center 2,000 Bull Project. Journal of Animal Science, 89(6), 1742-1750.
  14. Maniatis, T. (1989). Molecular Cloning: Decontamination of Dilute Solutions of Ethidium Bromide. Cold Spring Harbor Laboratory Press.
  15. Meade, K. G., Gormley, E., O'Farrelly, C., Park, S. D., Costello, E., Keane, J., MacHugh, D. E. (2008). Antigen stimulation of peripheral blood mononuclear cells from Mycobacterium bovis infected cattle yields evidence for a novel gene expression program. BMC Genomics, 9(1), 1-17.
  16. Miles, A. M., Posbergh, C. J., & Huson, H. J. (2021). Direct Phenotyping and Principal Component Analysis of Type Traits Implicate Novel QTL in Bovine Mastitis through Genome-Wide Association. Animals, 11(4), 1147.
  17. Mokhber, M., Moradi-Shahrbabak, M., Sadeghi, M., Moradi-Shahrbabak, H., Stella, A., Nicolzzi, E., ... & Williams, J. L. (2018). A genome-wide scan for signatures of selection in Azeri and Khuzestani buffalo breeds. BMC Genomics, 19(1), 449.
  18. Mosavi kashani, M., Rahimi Mianji, Gh., & Moradi Shahrbabak, H. (2018). Genome-Wide Scan for Selection Signatures in Iranian Sarabi and Taleshi Indigenous Breed. Research on Animal Production, 9, 88-99
  19. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A., Bender, D., Daly, M. J. (2007). PLINK: a tool set for whole-genome association and population-based linkage analyses. The American Journal of Human Genetics, 81(3), 559-575.
  20. Sabeti, P. C., Schaffner, S. F., Fry, B., Lohmueller, J., Varilly, P., Shamovsky, O., Lander, E. (2006). Positive natural selection in the human lineage. Science, 312(5780), 1614-1620.
  21. Sempéré, G., Moazami-Goudarzi, K., Eggen, A., Laloë, D., Gautier, M., & Flori, L. (2015). WIDDE: a Web-Interfaced next generation database for genetic diversity exploration, with a first application in cattle. BMC Genomics, 16(1), 1-8.
  22. Stella, A., Ajmone-Marsan, P., Lazzari, B., & Boettcher, P. (2010). Identification of selection signatures in cattle breeds selected for dairy production. Genetics, 185(4), 1451-1461.
  23. Vatsiou, A. I., Bazin, E., & Gaggiotti, O. E. (2016). Detection of selective sweeps in structured populations: a comparison of recent methods. Molecular Ecology, 25(1), 89-103.
  24. Winter, A., Van Eckeveld, M., Bininda-Emonds, O., Habermann, F. A., & Fries, R. (2003). Genomic organization of the DGAT2/MOGAT gene family in cattle (Bos taurus) and other mammals. Cytogenetic and Genome Research, 102(1-4), 42-47.
  25. Yan, Z., Wang, Z., Zhang, Q., Yue, S., Yin, B., Jiang, Y., & Shi, K. (2020). Identification of whole‐genome significant single nucleotide polymorphisms in candidate genes associated with body conformation traits in Chinese Holstein cattle. Animal Genetics, 51(1), 141.
Iranian Journal of animal Science
Volume 53, Issue 3
December 2022
Pages 203-209

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History

  • Receive Date: 11 April 2022
  • Revise Date: 03 August 2022
  • Accept Date: 05 August 2022

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