بررسی ساختار جمعیت و شناسایی نواحی تحت انتخاب در ژنگان اسب‌های کرد و عرب ایرانی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج

2 دانشیار، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج

3 استاد، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج

4 دانشجوی سابق کارشناسی ارشد، گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج

چکیده

اسب عرب از قدیمی­ترین نژادهای اسب جهان است. این نژاد عملکرد بسیار خوبی در مسابقات استقامتی و به‌طورکلی عملکرد ورزشی داشته و در تشکیل برخی نژادهای مهم جهان نقش داشته است. در مقابل، اسب کرد که بیشتر در زمین‌های ناهموار و مناطق کوهستانی زندگی می­کند، مناسب سواری در مناطق کوهستانی و مسابقات چوگان است. برای بررسی ساختار جمعیت و شناسایی قطعه‌های کروموزمی تحت انتخاب در این دو جمعیت، از 38 اسب عرب و 58 اسب کرد نمونۀ خون و مو گرفته شد. نمونه­ها پس از استخراج DNA، توسط 670K Axiom Equine Genotyping Array تعیین نژادگان (ژنوتیپ) شدند. تحلیل مؤلفه­های اصلی (PCA) روی داده‌های به‌دست‌آمده از تعیین نژادگان انجام شد؛ سپس آمارۀ Fst برای هر SNP محاسبه و برای جلوگیری از اثر تنوع تصادفی ذاتی Fst محاسبه‌شده برای تک SNP، آن­ها در طول هر کروموزوم همگن شدند. نتایج به‌دست‌آمده از تحلیل مؤلفه­های اصلی این دو جمعیت نشان داد اسب­های عرب ایرانی نسبت به اسب­های کرد تنوع ژنتیکی بالاتری دارند. در این تحقیق، نشانه­های انتخاب در شش جایگاه ژنگانی (ژنومی) شناسایی شد که بالاترین میزان آمارۀ Fst در کروموزم شماره 8 مشاهده شد. حاشیه­نویسی جایگاه­های تحت انتخاب منجر به شناسایی ژن­هایی همانند ژن­های CaMKK2، ATP2A2 و MLXIP شد، که به‌احتمال با عملکرد در مسابقات استقامتی و­ به‌طورکلی عملکرد ورزشی در اسب­ها مرتبط هستند و برای بررسی‌های بیشتر پیشنهاد می­شوند.

کلیدواژه‌ها

عنوان مقاله [English]

Investigating population structure and identifying signatures of selection in Iranian Kurdish and Arabian horses

نویسندگان [English]

  • Saber Mohammad Maghsoodi 1
  • Hassan Mehrabani Yeganheh 2
  • Ardeshir Nejati Javaremi 3
  • Navid Yousefi Mashouf 4
1 Ph.D. Candidate, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
2 Associate Professor, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
3 Professor, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
4 Former M.Sc. Student, Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
چکیده [English]

The Arab horse breed is one of the most ancient horse breeds. Arabian horses are famous for endurance riding and flat racing. Moreover, this breed has contributed to the formation of some of the most important horse breeds in the world. Kurdish horses are found in rough terrain and hilly regions and they are suitable for riding in hilly areas and Polo tournament. To investigate the population structure and to find the signatures of  selection in the genome of Arabian and Kurdish horses, blood and hair samples from 38 Arabian and 58 Kurdish horses were taken and genotyped using the 670K Axiom Equine Genotyping Array. Principal component analysis (PCA) was carried out on the genotypic data and Fst statistic for each SNP was calculated. Fst values were smoothed over each chromosome. PCA showed that the Arabian horse population is more genetically diverse than the Kurdish horses. We identified six genomic regions showing signatures of selection. The strongest signal of selection was found in ECA8. Annotation of the regions of the genome that showed selection signatures revealed candidate genese.g. CaMKK2, MLXIP and ATP2A2 that may involve in endurance riding and racing. These genes for further studies are proposed.

کلیدواژه‌ها [English]

  • Arabian horse breed
  • Genetic diversity
  • Kurdish horse breed
  • selection signatures

مراجع

  1. Akey, J. M., Zhang, G., Zhang, K., Jin, L. & Shriver, M. D. (2002). Interrogating a high-density SNP map for signatures of natural selection. Genome Research, 12(12), 1805-1814.
  2. Aulchenko, Y. S., Ripke, S., Isaacs, A. & van Duijn, C. M. (2007). GenABEL: an R library for genome-wide association analysis. Bioinformatics, 23(10), 1294-1296.
  3. Barendse, W., Harrison, B. E., Bunch, R. J., Thomas, M. B. & Turner, L. B. (2009). Genome wide signatures of positive selection: the comparison of independent samples and the identification of regions associated to traits. BMC Genomics, 10, 178.
  4. Bolcun-Filas, E., Hall, E., Speed, R., Taggart, M., Grey, C., de Massy, B., Benavente, R. & Cooke, H. J. (2009). Mutation of the mouse Syce1 gene disrupts synapsis and suggests a link between synaptonemal complex structural components and DNA repair. PLoS Genetics, 5(2), e1000393.
  5. Bowling, A. T., Del Valle, A. & Bowling, M. (2000). A pedigree-based study of mitochondrial D-loop DNA sequence variation among Arabian horses. Animal Genetics, 31(1), 1-7.
  6. Brito, L. F., Kijas, J. W., Ventura, R. V., Sargolzaei, M., Porto-Neto, L. R., Canovas, A., Feng, Z., Jafarikia, M. & Schenkel, F. S. (2017). Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers. BMC Genomics. 18(1). 229.
  7. Cadzow, M., Boocock, J., Nguyen, H. T., Wilcox, P., Merriman, T. R. & Black, M. A. (2014). A bioinformatics workflow for detecting signatures of selection in genomic data. Frontiers in Genetics, 5, 293.
  8. Casey, J. P., Magalhaes, T., Conroy, J. M., Regan, R., Shah, N., Anney, R., Shields, D. C., Abrahams, B. S., Almeida, J., Bacchelli, E., Bailey, A. J., Baird, G., Battaglia, A., Berney, T., Bolshakova, N., Bolton, P. F., Bourgeron, T., Brennan, S., Cali, P., Correia, C., Corsello, C., Coutanche, M., Dawson, G., de Jonge, M., Delorme, R., Duketis, E., Duque, F., Estes, A., Farrar, P., Fernandez, B. A., Folstein, S. E., Foley, S., Fombonne, E., Freitag, C. M., Gilbert, J., Gillberg, C., Glessner, J. T., Green, J., Guter, S. J., Hakonarson, H., Holt, R., Hughes, G., Hus, V., Igliozzi, R., Kim, C., Klauck, S. M., Kolevzon, A., Lamb, J. A., Leboyer, M., Le Couteur, A., Leventhal, B. L., Lord, C., Lund, S. C., Maestrini, E., Mantoulan, C., Marshall, C. R., McConachie, H., McDougle, C. J., McGrath, J., McMahon, W. M., Merikangas, A., Miller, J., Minopoli, F., Mirza, G. K., Munson, J., Nelson, S. F., Nygren, G., Oliveira, G., Pagnamenta, A. T., Papanikolaou, K., Parr, J. R., Parrini, B., Pickles, A., Pinto, D., Piven, J., Posey, D. J., Poustka, A., Poustka, F., Ragoussis, J., Roge, B., Rutter, M. L., Sequeira, A. F., Soorya, L., Sousa, I., Sykes, N., Stoppioni, V., Tancredi, R., Tauber, M., Thompson, A. P., Thomson, S., Tsiantis, J., Van Engeland, H., Vincent, J. B., Volkmar, F., Vorstman, J. A., Wallace, S., Wang, K., Wassink, T. H., White, K., Wing, K., Wittemeyer, K., Yaspan, B. L., Zwaigenbaum, L., Betancur, C., Buxbaum, J. D., Cantor, R. M., Cook, E. H., Coon, H., Cuccaro, M. L., Geschwind, D. H., Haines, J. L., Hallmayer, J., Monaco, A. P., Nurnberger, J. I., Jr., Pericak-Vance, M. A., Schellenberg, G. D., Scherer, S. W., Sutcliffe, J. S., Szatmari, P., Vieland, V. J., Wijsman, E. M., Green, A., Gill, M., Gallagher, L., Vicente, A. & Ennis, S. (2012). A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder. Human Genetics, 131(4), 565-579.
  9. Chen, G., Yuan, A., Shriner, D., Tekola-Ayele, F., Zhou, J., Bentley, A. R., Zhou, Y., Wang, C., Newport, M. J., Adeyemo, A. & Rotimi, C. N. (2015). An Improved F(st) Estimator. PLoS One, 10(8), e0135368.
  10. Colomer, J. & Means, A. R. (2007). Physiological roles of the Ca2+/CaM-dependent protein kinase cascade in health and disease. Subcell Biochem, 45, 169-214.
  11. De Simoni Gouveia, J. J., da Silva, M. V., Paiva, S. R. & de Oliveira, S. M. (2014). Identification of selection signatures in livestock species. Genetics and Molecular Biology, 37(2), 330-342.
  12. DeGiorgio, M., Lohmueller, K. E. & Nielsen, R. (2014). A model-based approach for identifying signatures of ancient balancing selection in genetic data. PLoS Genetics, 10(8), e1004561.
  13. Dennis, G., Jr., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C.&  Lempicki, R. A. (2003). DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biology, 4(5), P3.
  14. Freedman, A. H., Schweizer, R. M., Ortega-Del Vecchyo, D., Han, E., Davis, B. W., Gronau, I., Silva, P. M., Galaverni, M., Fan, Z., Marx, P., Lorente-Galdos, B., Ramirez, O., Hormozdiari, F., Alkan, C., Vila, C., Squire, K., Geffen, E., Kusak, J., Boyko, A. R., Parker, H. G., Lee, C., Tadigotla, V., Siepel, A., Bustamante, C. D., Harkins, T. T., Nelson, S. F., Marques-Bonet, T., Ostrander, E. A., Wayne, R. K. & Novembre, J. (2016). Demographically-Based Evaluation of Genomic Regions under Selection in Domestic Dogs. PLoS Genetics, 12(3), e1005851.
  15. Głażewska, I. (2010). Speculations on the origin of the Arabian horse breed. Livestock Science, 129(1), 49-55.
  16. Gu, J., Orr, N., Park, S. D., Katz, L. M., Sulimova, G., MacHugh, D. E. & Hill, E. W. (2009). A genome scan for positive selection in thoroughbred horses. PLoS One, 4(6), e5767.
  17. Herrmann, E. (1997). Local bandwidth choice in kernel regression estimation. Journal of Computational and Graphical Statistics, 6(1), 35-54.
  18. Hill, E. W., Gu, J., McGivney, B. A. & MacHugh, D. E. (2010). Targets of selection in the Thoroughbred genome contain exercise-relevant gene SNPs associated with elite racecourse performance. Animal Genetics, 41 Suppl 2, 56-63.
  19. Holsinger, K. E. & Weir, B. S. (2009). Genetics in geographically structured populations: defining, estimating and interpreting F(ST). Nature Reviews Genetics, 10(9), 639-650.
  20. Hunt, L. C., Xu, B., Finkelstein, D., Fan, Y., Carroll, P. A., Cheng, P. F., Eisenman, R. N. & Demontis, F. (2015). The glucose-sensing transcription factor MLX promotes myogenesis via myokine signaling. Genes & Development, 29(23), 2475-2489.
  21. Imamura, M., Chang, B. H., Kohjima, M., Li, M., Hwang, B., Taegtmeyer, H., Harris, R. A. & Chan, L. (2014). MondoA deficiency enhances sprint performance in mice. Biochemical Journal, 464(1), 35-48.
  22. Kelley, B. P. (2002). Horse breeds of the world. Philadelphia: Chelsea House Publishers.
  23. Khanshour, A., Conant, E., Juras, R. & Cothran, E. G. (2013). Microsatellite analysis of genetic diversity and population structure of Arabian horse populations. Journal of Heredity, 104(3), 386-398.
  24. Kijas, J. W., Lenstra, J. A., Hayes, B., Boitard, S., Porto Neto, L. R., San Cristobal, M., Servin, B., McCulloch, R., Whan, V., Gietzen, K., Paiva, S., Barendse, W., Ciani, E., Raadsma, H., McEwan, J., Dalrymple, B. & International Sheep Genomics Consortium, M. (2012). Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection. PLoS Biology, 10(2), e1001258.
  25. Kim, E. S., Cole, J. B., Huson, H., Wiggans, G. R., Van Tassell, C. P., Crooker, B. A., Liu, G., Da, Y. & Sonstegard, T. S. (2013). Effect of artificial selection on runs of homozygosity in U.S. Holstein cattle. PLoS One, 8(11), e80813.
  26. Kullo, I. J. & Ding, K. (2007). Patterns of population differentiation of candidate genes for cardiovascular disease. BMC Genetics, 8, 48.
  27. Li, X., Yang, S., Tang, Z., Li, K., Rothschild, M. F., Liu, B. & Fan, B. (2014). Genome-wide scans to detect positive selection in Large White and Tongcheng pigs. Animal Genetics, 45(3), 329-339.
  28. Makvandi-Nejad, S., Hoffman, G. E., Allen, J. J., Chu, E., Gu, E., Chandler, A. M., Loredo, A. I., Bellone, R. R., Mezey, J. G., Brooks, S. A. & Sutter, N. B. (2012). Four loci explain 83% of size variation in the horse. PLoS One, 7(7), e39929.
  29. Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., Shafer, A., Neri, F., Lee, K., Kutyavin, T., Stehling-Sun, S., Johnson, A. K., Canfield, T. K., Giste, E., Diegel, M., Bates, D., Hansen, R. S., Neph, S., Sabo, P. J., Heimfeld, S., Raubitschek, A., Ziegler, S., Cotsapas, C., Sotoodehnia, N., Glass, I., Sunyaev, S. R., Kaul, R. & Stamatoyannopoulos, J. A. (2012). Systematic localization of common disease-associated variation in regulatory DNA. Science, 337(6099), 1190-1195.
  30. Mokhber, M., Moradi Shahrbabak, M., Sadeghi, M., Moradi Shahrbabak, H. & Williams, J. (2015). Genome-Wide Survey of signature of positive selection in Khuzestani and Mazandrani buffalo breeds. Iranian Journal of Animal Science, 46(2), 119-131. (in Farsi)
  31. Momke, S. & Distl, O. (2007a). Molecular characterization of the equine ATP2A2 gene. Cytogenet Genome Research, 116(4), 256-262.
  32. Momke, S. & Distl, O. (2007b). Molecular genetic analysis of the ATP2A2 gene as candidate for chronic pastern dermatitis in German draft horses. Journal of Heredity, 98(3), 267-271.
  33. Moon, S., Lee, J. W., Shin, D., Shin, K. Y., Kim, J., Choi, I. Y., Kim, J. & Kim, H. (2015). A Genome-wide Scan for Selective Sweeps in Racing Horses. Asian-Australasian Journal of Animal Sciences, 28(11), 1525-1531.
  34. Moridi, M., Masoudi, A. A., Vaez Torshizi, R. & Hill, E. W. (2013). Mitochondrial DNA D-loop sequence variation in maternal lineages of Iranian native horses. Animal Genetics, 44(2), 209-213.
  35. Mosapour Kaleibar, P., Aghazade, A. M., Hassanpour, A., Mahpeikar, H. A. & Ebrahimi Hamed, M. (2007). A study on some phenotypic characteristics of the Karabakh horse in comparison with the Kurdish and Arabian horses. J. Spe. Vet. Sci. Islam. Azad. Uni. Tabriz., 1(1), 27-33. (in Farsi)
  36. Pérez O’Brien, A. M., Utsunomiya, Y. T., Mészáros, G., Bickhart, D. M., Liu, G. E., Van Tassell, C. P., Sonstegard, T. S., Da Silva, M. V., Garcia, J. F. & Sölkner, J. (2014). Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle. Genetics Selection Evolution, 46(1), 19.
  37. Petersen, J. L., Mickelson, J. R., Rendahl, A. K., Valberg, S. J., Andersson, L. S., Axelsson, J., Bailey, E., Bannasch, D., Binns, M. M., Borges, A. S., Brama, P., da Camara Machado, A., Capomaccio, S., Cappelli, K., Cothran, E. G., Distl, O., Fox-Clipsham, L., Graves, K. T., Guerin, G., Haase, B., Hasegawa, T., Hemmann, K., Hill, E. W., Leeb, T., Lindgren, G., Lohi, H., Lopes, M. S., McGivney, B. A., Mikko, S., Orr, N., Penedo, M. C., Piercy, R. J., Raekallio, M., Rieder, S., Roed, K. H., Swinburne, J., Tozaki, T., Vaudin, M., Wade, C. M. & McCue, M. E. (2013). Genome-wide analysis reveals selection for important traits in domestic horse breeds. PLoS Genetics, 9(1), e1003211.
  38. Rafeie, F., Amirinia, C., Nejati Javaremi, A., Mirhoseini, S. Z. & Amirmozafari, N. (2011). A study of patrilineal genetic diversity in Iranian indigenous horse breeds. African Journal of Biotechnology, 10(75), 17347-17352.
  39. Ricard, A., Robert, C., Blouin, C., Baste, F., Torquet, G., Morgenthaler, C., Riviere, J., Mach, N., Mata, X., Schibler, L. & Barrey, E. (2017). Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism. Frontiers in Genetics, 8, 89.
  40. Ricard, A. & Touvais, M. (2007). Genetic parameters of performance traits in horse endurance races. Livestock Science, 110(1), 118-125.
  41. Ropka-Molik, K., Stefaniuk-Szmukier, M., Zukowski, K., Piorkowska, K., Gurgul, A. & Bugno-Poniewierska, M. (2017). Transcriptome profiling of Arabian horse blood during training regimens. BMC Genetics, 18(1), 31.
  42. Rothammer, S., Seichter, D., Forster, M. & Medugorac, I. (2013). A genome-wide scan for signatures of differential artificial selection in ten cattle breeds. BMC Genomics, 14, 908.
  43. Sabeti, P. C., Schaffner, S. F., Fry, B., Lohmueller, J., Varilly, P., Shamovsky, O., Palma, A., Mikkelsen, T. S., Altshuler, D. & Lander, E. S. (2006). Positive natural selection in the human lineage. Science, 312(5780), 1614-1620.
  44. Schroder, W., Klostermann, A., Stock, K. F. & Distl, O. (2012). A genome-wide association study for quantitative trait loci of show-jumping in Hanoverian warmblood horses. Animal Genetics, 43(4), 392-400.
  45. Sobczyńska, M. (2010). Genetic parameters of racing performance indices in Polish Arabian horses. Livestock Science, 131(2), 245-249.
  46. Vafaei Sayah, G. & Mehrannezhad, R. (2005). Cytogenetical study of Kurd horse. Pajouhesh & Sazandegi, 66, 75-79. (in Farsi)
  47. Vernot, B., Stergachis, A. B., Maurano, M. T., Vierstra, J., Neph, S., Thurman, R. E., Stamatoyannopoulos, J. A. & Akey, J. M. (2012). Personal and population genomics of human regulatory variation. Genome Research, 22(9), 1689-1697.
  48. Weir, B. S. & Cockerham, C. C. (1984). Estimating F-statistics for the analysis of population structure. Evolution, 38, 1358-1370.
  49. Ye, C., Zhang, D., Zhao, L., Li, Y., Yao, X., Wang, H., Zhang, S., Liu, W., Cao, H., Yu, S., Wang, Y., Jiang, J., Wang, H., Li, X. & Ying, H. (2016). CaMKK2 Suppresses Muscle Regeneration through the Inhibition of Myoblast Proliferation and Differentiation. International Journal of Molecular Sciences, 17(10): 1695.
  50. Yousefi Mashouf, N. (2016). Phenotypic and genetic characterization of the Iranian Kurdish horse. MSc Thesis, College of Agriculture & Natural Resources, University of Tehran, Iran.
  51. Zhao, F., McParland, S., Kearney, F., Du, L. & Berry, D. P. (2015). Detection of selection signatures in dairy and beef cattle using high-density genomic information. Genetics Selection Evolution, 47(1), 49.

فایل ها

سابقه مقاله

  • تاریخ دریافت: 14 آبان 1396
  • تاریخ بازنگری: 24 آذر 1396
  • تاریخ پذیرش: 29 آذر 1396

هم رسانی

ارجاع به این مقاله

آمار