پویش ژنومی نشانه‌های انتخاب در گاومیش‌های خوزستانی و مازندرانی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری ژنتیک و اصلاح نژاد، گروه مهندسی علوم دامی دانشگاه تهران، کرج، ایران

2 استاد گروه مهندسی علوم دامی دانشگاه تهران، کرج، ایران

3 استادیار گروه مهندسی علوم دامی دانشگاه تهران، کرج، ایران

4 استاد و مدیر بخش ژنومیک مرکز تحقیقات Padano، ایتالیا

چکیده

شناسایی مناطق ژنومی که هدف انتخاب بوده‌اند، از بحث‌برانگیزترین مباحث در حوزة تحقیقات ژنتیک حیوانی، به‌خصوص در حیوانات اهلی است. در این مطالعه، پویش کل ژنوم برای شناسایی مناطقی از ژنوم که در گاومیش‌های خوزستانی و مازندرانی هدف انتخاب‌های طبیعی یا مصنوعی قرار گرفته‌اند، اجرا شده است. بدین منظور 148 رأس گاومیش رودخانه‌ای شامل جمعیت‌های خوزستانی (121 رأس) و مازندرانی (27 رأس)، به وسیلة آرایه‌های ژنومیکی Axiom® Buffalo Genotyping 90K تعیین ژنوتیپ شدند. جهت جستجوی نشانه‌های انتخاب از برآوردگر نااُریب FST (θ) استفاده شد. در مجموع 23 منطقه که نشانگرهای SNP آن‌ها بالاتر از 1/0 درصد حد بالای توزیع تجربی FST بود، به‌عنوان نشانه‌های انتخاب شناسایی شده و مورد بررسی‌های بیشتر قرار گرفتند. بعد از انطباق مناطق ژنومی انتخاب‌شده با مناطق ژنومی متناظر آن روی ژنوم گاو (UMD3.1 Bos Taurus Genome)، 64 ژن و 27 QTL شناسایی شد. تعدادی از این ژن‌ها در مطالعات قبلی نیز به‌عنوان نشانه‌های انتخاب گزارش شده‌اند. برخی از این ژن‌ها احتمالاً در مسیرهای بیولوژیکی که با اهلی‌شدن حیوانات (توسعة مغز و عملکردهای رفتاری، پیگماسیون و آداپته‌شدن به محیط زندگی و شرایط جغرافیایی) و تولید شیر مرتبط می‌باشند، درگیرند. بررسی‌ها همچنین نشان داد که QTLهای شناسایی‌شده در این تحقیق با صفات مهم اقتصادی از جمله صفات مرتبط با راندمان تبدیل غذایی، وزن بدن، چربی زیرپوستی، افزایش وزن روزانه، تیپ، تردی گوشت، ترکیبات شیر، اتصالات پستانی، اندازة گوساله و گوساله‌زایی آسان ارتباط دارند. به هرحال جهت شناسایی نقش دقیق این ژن‌ها و QTLها لازم است مطالعات پیوستگی و عملکردی بیشتری انجام گیرد.

کلیدواژه‌ها

عنوان مقاله [English]

Genome-Wide Survey of signature of positive selection in Khuzestani and Mazandrani buffalo breeds

نویسندگان [English]

  • Mahdi Mokhber 1
  • Mohammad Moradi Shahrbabak 2
  • Mostafa Sadeghi 3
  • Hossein Moradi Shahrbabak 3
  • John Williams 4
1 Ph.D Student, Department of Animal Science, Faculty of Agricultural Science and Engineering, University College of Agriculture and Natural Resources (UTCAN), University of Tehran, Karaj, Iran
2 Department of Animal Science, Faculty of Agricultural Science and Engineering, University College of Agriculture and Natural Resources (UTCAN), University of Tehran, Karaj, Iran
3 Department of Animal Science, Faculty of Agricultural Science and Engineering, University College of Agriculture and Natural Resources (UTCAN), University of Tehran, Karaj, Iran
4 Parco Tecnologico Padano, Lodi, Italy,
چکیده [English]

Identification of selection targeted genomic regions is one of the most challenging areas of research in animal genetics, particularly in livestock. We carried out a genome-wide scan for signatures of positive selection to identify genomic regions that had been under selection in Iranian Khuzestani and Mazandrani buffalo breeds. A total of 148 water buffalo from Khuzestani (N=121) and Mazandrani (N=27) buffalo breeds were genotyped using Axiom® Buffalo Genotyping 90K Array. Unbiased method of population differentiation index (FST) was applied to detect signatures of selection. In total, 23 regions exceeding the 0.1 percent threshold of the empirical posterior distribution were identified as extremely differentiated. These selected genomic regions were surveyed to find encoding putative candidate genes and 64 genes and 27 QTL were extracted from the corresponding areas in UMD3.1 Bos Taurus Genome Assembly. Some of these genes have previously reported as signature of positive selection in the last studies. Some of these genes were also found to be involved in milk production traits and domestication-related changes include sensory perceptions, brain and neural system development, pigmentation, and geographic adaptation. Also, survey on extracted QTLs was shown that these QTLs involved in some economicl important traits in buffalo such as feed conversion ratio, subcutaneous fat, body weight, average daily gain, type, Meat tenderness, milk production conentent, udder attachment, calf size and calving ease traits. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes.

کلیدواژه‌ها [English]

  • signatures of selection
  • Genome-Wide Survey
  • population differentiation index
  • Khuzestani and Mazandrani buffalo breeds

مراجع

  1. Akey, J. M. (2009). Constructing genomic maps of positive selection in humans: Where do we go from here?. Genome Res, 19, 711-722.
  2. 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 Res, 12(12), 1805–1814.
  3. Alberts, C. C., Ribeiro-Paes, J. T., Aranda-Selverio, G., Cursino-Santos, J. R., Moreno-Cotuli, V. R., Oliveir, A. L. D., Santos Departamento, W.F. & Souza, E. B. (2010). DNA extraction from hair shafts of wild Brazilian felids and canids. Gene and Mol Res, 9 (4), 2429-2435.
  4. Amaral, M. E., Owens, K. E., Elliott, J. S., Fickey, C. & Schaffer, A. A. (2007). Construction of a river buffalo (Bubalus bubalis) whole-genome radiation hybrid panel and preliminary RH mapping of chromosomes 3 and 10. Anim Genet, 38, 311-314
  5. Ashwell, M. S., Heyen, D. W., Weller, J. I., Ron, M., Sonstegard, T. S., Van-Tassell, C. P. & Lewin, H. A. (2005). Detection of quantitative trait loci influencing conformation traits and calvingease in Holstein-Friesian cattle. J Dairy Sci, 88(11), 4111-9.
  6. Bernard, C., Cassar-Malek, I., Le Cunff, M., Dubroeucq, H., Renand, G. & Hocquette, J. F. (2007). New indicators of beef sensory quality revealed by expression of specific genes. J Agric Food Chem, 55, 5229–5237.
  7. Biswas, S. & Akey, J. M. (2006). Genomic insights into positive Selection. Trends in Genetics, 22(8), 437-436.
  8. Borghese, A. (2011). Situation and perspectives of buffalo in the world, Europe and Macedonia. Macedonian J Anim Sci, 1(2), 281–296.
  9. Campbell, A. M., Williamson, J., Padula, D. & Sundby, S. (1997). Use PCR & Single Hair to produce a “DNA Fingerprint”. The American Biol Teach, 59(3), 172-178.
  10. Daetwyler, H. D., Schenkel, F. S., Sargolzaei, M. & Robinson, J. A. B. (2008). A genome scan to detect quantitative trait loci for economically important traits in Holstein cattle using two methods and a dense single nucleotide polymorphism map. J Dairy Sci, 91 (8), 3225-36.
  11. Ensembl BioMart: Ensembl online genome data base BioMart Tool. http:// www.ensembl.org/biomart/martview/.
  12. EntrezGene: NCBI Resources EntrezGene. http://www.ncbi.nlm.nih.gov/.
  13. Fan, B., Du, Z. Q., Gorbach, D. M., & Rothschild, M. F.( 2010). Development and Application of High-density SNP Arrays in Genomic Studies of Domestic Animals. Asian-Aust. J. Anim. Sci, 23(7), 833 – 847.
  14. GeneCards. http://www.genecards.org/cgi-bin/carddisp.pl?gene=STAT
  15. Goddard, M. (2009). Genomic selection: prediction of accuracy and maximization of long term response. Genetics, 136, 245-257.
  16. Gotoh, T., Terada, K., Oyadomari, S. & Mori, M. (2004). Hsp70 DnaJ chaperone pair prevents nitric oxide and CHOP induced apoptosis by inhibiting translocation of Bax to mitochondria. Cell Death Differ, 11, 390–402.
  17. Grimberg, J., Nawoscihik, S., Belluscio, L., McKee, R., Turk, A. & Eisenberg, A. (1989). A simple and efficient non-organic procedure for the isolation of genomic DNA from blood. Nucl Acids Res, 17, 8390.
  18. Grossman, S. R., Shylakhter, I., Karlsson, E. K., Byrne,  E. H., Morales, S. et al. (2010). A composite of multiple signals distinguishes causal variants in regions of positive selection. Science, 327, 883–886.
  19. Gulcher, J. & Stefansson, K. (1998). Population Genomics: Laying the Groundwork for Genetic Disease Modeling and Targeting. Clin Chem Lab Med, 36, 523-527.
  20. 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 Genet, 13, 71.
  21. Khan, M. S., Rehman, M. S. & Hassan, F. (2012). Breeding Buffaloes in Genomics era –Issues of recording and evaluation. J. Anim Plant Sci, 22(3), 174-180.
  22. Kijas, J. W., Lenstra, J. A., Hayes, B., Boitard, S., Porto Neto, L. R., et al. (2012). Genome-Wide Analysis of the World’s Sheep Breeds Reveals High Levels of Historic Mixture and Strong Recent Selection. PLoS Biol, 10(2), e1001258. doi:10.1371/journal.pbio.1001258.
  23. Lamason, R. L., Mohideen, M., Mest, J. R., Wong, A .C., Norton, H. L., et al. (2005). SLC24A5, a putative cation exchanger, affects pigmentation in zebrafish and humans. Science, 310, 1782–1786.
  24. Leutenegger, A. L., Prum, B., Génin, E., Verny, C., Lemainque, A., Clerget-Darpoux, F. and Thompson, E. A. (2003). Estimation of the inbreeding coefficient through use of genomic data. Am J Hum Genet, 73, 516–523.
  25. Li, Z., Xie, J., Li, W., Tang, A., Li, X., Jiang, Z., Han, Y., Ye, J., Jing, J., Gui, Y. & Cai, Z. (2011). Identification and characterization of human PCDH10 gene promoter. Gene, 475, 49–50.
  26. MacEachern, S., Hayes, B., McEwan, J. & Goddard, M. (2009). An examination of positive selection and changing effective population size in Angus and Holstein cattle populations (Bos taurus) using a high density SNP genotyping platform and the contribution of ancient polymorphism to genomic diversity in Domestic cattle. BMC Genomics, 10, 181.
  27. Marcos-Carcavilla et al. (2010). Polymorphisms in the HSP90AA1 5' flanking region are associated with scrapie incubation period in sheep. Cell Stress & Chaperones, 15(4), 343-349.
  28. Marquez, G. C., Enns, R. M., Grosz, M. D., Alexander, L. J. & Macneil, M. D. (2010). Quantitative trait loci with effects on feed efficiency traits in Hereford x composite double backcross populations. Anim Genet, 40(6), 986-8.
  29. Maynard-Smith, J, Haigh, J: (1974). The hitch-hiking effect of a favourable gene. Genet Res, 23, 23-35.
  30. McClure, M. C., Ramey, H. R., Rolf, M. M., McKay, S. D., Decker, J. E., Chapple, R. H., et al. (2012). Genome-wide association analysis for quantitative trait loci influencing Warner-Bratzler shear force in five taurine cattle breeds. Anim Genet, 43 (6), 662-73.
  31. Michelizzi, V.  N., Wu, X., Dodson, M., Michal, J. J., Zambrano-Varon, J., McLean, D. J. & Jiang, Z. (2011). A Global View of 54,001 Single Nucleotide Polymorphisms (SNPs) on the Illumina BovineSNP50 BeadChip and Their Transferability to Water Buffalo, Int. J. Biol. Sci,7(1), 18-27.
  32. Moradi, M. H., Nejati-Javaremi, A., Moradi-Shahrbabak, M., Dodds, K. G. & McEwan, J. C. (2012). Genomic scan of selective sweeps in thin and fat tail sheep breeds for identifying of candidate regions associated with fat deposition. BMC Genetics, 13, 10.
  33. Morris, C. A., Cullen, N. G., Glass, B. C., Hyndman, D. L., Manley, T. R., Hickey, S. M., McEwan, J. C., Pitchford, W. S., Bottema, C. D. K. & Lee, M. A. H. (2007). Fatty acid synthase effects on bovine adipose fat and milk fat. Mammal genome, 18 (1), 64-74.
  34. Nicolazzi, E. L., Iamartino, D. and Williams, J. L. (2014). AffyPipe: an open-source pipeline for Affymetrix Axiom genotyping workflow. Bioinformatics, 30(21), 3118-9. doi: 10.1093/bioinformatics/btu486. Epub 2014 Jul 15.
  35. Nielsen, R. & Yang, Z. (1988). Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics, 148, 929–936.
  36. Nkrumah, J. D., Sherman, E. L.; Li, C., Marques, E., Crews, D. H., Bartusiak, R., Murdoch, B., Wang, Z., Basarab, J. A. & Moore, S. S. (2007). Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle. J Anim Sci, 85 (12), 3170-81.
  37. Ogorevc, J., Kunej, T., Razpet, A. & Dovc, P. (2009). Database of cattle candidate genes and genetic markers for milk production and mastitis. Anim Genet, 40, 832–851.
  38. Oleksyk, T. K., Smith, M. W., & O’Brien, S. J. (2010). Genome-wide scans for footprints of natural selection. Philosophical Transactions of the Royal SocietyB, 365, 185–205.
  39. Othman, O. E. )2006(. Restriction fragment length polymorphism and gene mapping of two genes associated with composition in Egyption river buffalo. J Dairy Sci, 1(1), 84-92.
  40. Pardridge, W. M. (2005). The blood–brain barrier: bottleneck in brain drug development. NeuroRx: J Am Soc Exp NeuroTherapeutics, 2(1), 3–14.
  41. Pérez O’Brien, A. M., Utsunomiya, Y. T., Gábor Mészáros, V. B., Bickhart, D. M., Liu, G. E., Van Tassell, C. P., Sonstegard T. S., Silva, M. D., Garcia, J. F. & Sölkner, J. (2014). Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle. Genet Sel Evol46, 19 .
  42. Peters, S. O., Kizilkaya, K., Garrick, D. J., Fernando, R. L., Reecy, J. M., Weaber, R. L., Silver, G. A. & Thomas, M. G. (2012). Bayesian genome-wide association analysis of growth and yearling ultrasound measures of carcass traits in Brangus heifers. J Anim Sci, 90 (10), 3398-409.
  43. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P .I. W., Daly, M. J. & Sham, P. C. (2007). PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet, 81, 559–575.
  44. Qanbari, S., Pausch, H., Jansen, S., Somel, M., Strom, T. M., et al. (2014). Classic Selective Sweeps Revealed by Massive Sequencing in Cattle. PLoS Genet, 10(2), e1004148. doi:10.1371/journal.pgen.1004148
  45. Qanbari, S., Strom, T. M., Haberer, G., Weigend, S., Gheyas, A. A., et al. (2012) A High Resolution Genome-Wide Scan for Significant Selective Sweeps: An Application to Pooled Sequence Data in Laying Chickens. PLoS ONE, 7(11), e49525. doi:10.1371/journal.pone.0049525.
  46. Rubin, C. J., Zody, M. C., Eriksson, J., Meadows, J. R. S., Sherwood, E., et al. (2010). Whole-genome resequencing reveals loci under selection during chicken domestication. Nature, 464, 587-591.
  47. Sabeti, P. C., Reich, D. E., Higgins, J. M., Levine, H. Z. P., Richter, D. J., Schaffner, S. F., Gabriel, S. B., Platko, J. V., Patterson, N. J., McDonald, G. J., et al. (2002). Detecting recent positive selection in the human genome from Haplotype structure. Nature, 419, 832-837.
  48. Schnabel, R. D., Sonstegard, T. S., Taylor, J. F. & Ashwell, M. S. (2005). Whole-genome scan to detect QTL for milk production, conformation, fertility andfunctional traits in two US Holstein families. Anim Genet, 36(5), 408-16.
  49. Schopen, G. C. B., Koks, P. D., van-Arendonk, J. A. M., Bovenhuis, H. & Visker, M. H. P. W. (2009). Whole genome scan to detect quantitative trait loci for bovine milk protein composition. Anim Genet, 40 (4), 524-37.
  50. Schrooten, C., Bovenhuis, H., Coppieters, W. & Van Arendonk, J. A. (2000). Whole genome scan to detect quantitative trait loci for conformation and functional traits in dairy cattle. J Dairy Sci, 83 (4): 795-806.
  51. Sherman, E. L.; Nkrumah, J. D.; Murdoch, B. M. & Moore, S. S. (2008). Identification of polymorphisms influencing feed intake and efficiency in beef cattle. Anim Genet, 39 (3), 225-31.
  52. Simianer, H., Ma, Y. & Qanbari, S. (2014). Statistical problems in livestock population genomics. Proccedings, 10th Congress of Genetics Applied to Livestock Production, 17-22 August., Vancouver, BC, Canada.
  53. Tajima, F. (1989). Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics, 123(3), 585–595.
  54. Takasuga, A., Watanabe, T., Mizoguchi, Y., Hirano, T., Ihara, N., Takano, A. & Yokouchi, K. F. (2007). Identification of bovine QTL for growth and carcass traits in Japanese Black cattle by replication and identical-by-descent mapping. Mammal Genome, 18 (2), 125-36.
  55. Tellechea, M. L., Steinhardt, A. P., Rodriguez, G., Taverna, M. J., Poskus, E., Frechtel, G. (2013). Common variants in SOCS7 gene predict obesity, disturbances in lipid metabolism and insulin resistance. Nutr Metab Cardiovasc, 23(5), 424–431.
  56. Teo, Y. Y., Fry, A. E., Clark, T. G., Tai, E. S., & Seielstad, M. (2007). On the usage of HWE for identifying genotyping errors. Annal of Hum Genet, 71, 701-703.
  57. The Bovine HapMap Consortium, Gibbs, R. A., Taylor, J. F., Van Tassell, C. P., Barendse, W., et al. (2009) Genome-Wide Survey of SNP Variation Uncovers the Genetic Structure of Cattle Breeds. Science, 324, 528–532. doi:10.1126/ science.1167936.
  58. The R Project for Statistical Computing: Free software environment for statistical computing and graphics. http:// www.r-project.org/.
  59. Utsunomiya, Y. T., Pe ´ rez O’Brien, A. M., Sonstegard, T. S., Van Tassell, C. P., do Carmo, A. S., et al. (2013). Detecting Loci under Recent Positive Selection in Dairy and Beef Cattle by Combining Different Genome-Wide Scan Methods. PLoS ONE, 8(5), e64280. doi:10.1371/journal.pone.0064280.
  60. Voight, B. F., Kudaravalli, S., Wen, X. & Pritchard, J. K. (2006). A Map of Recent Positive Selection in the Human Genome. PLoS Biol, 4 (3), e72.
  61. Weir, B. S. & Cockerham, C. C. (1984). Estimating F-Statistics for the analysis of population structure. Evol, 38(6), 1358–1370.
  62. Zheng, J., Watson, A. D., & Kerr, D. E. (2006). Genome-wide expression analysis of lipopolysaccharide-induced mastitis in a mouse model. Infect and Immu, 74, 1907–15.

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  • تاریخ دریافت: 26 بهمن 1393
  • تاریخ بازنگری: 23 خرداد 1394
  • تاریخ پذیرش: 02 تیر 1394

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