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Stories and Challenges of Genome Wide Association Studies in Livestock - A Review

  • Sharma, Aditi (Hanwoo Experiment Station) ;
  • Lee, Jun Seop (Hanwoo Experiment Station) ;
  • Dang, Chang Gwon (Hanwoo Experiment Station) ;
  • Sudrajad, Pita (Hanwoo Experiment Station) ;
  • Kim, Hyeong Cheol (Hanwoo Experiment Station) ;
  • Yeon, Seong Heum (Hanwoo Experiment Station) ;
  • Kang, Hee Seol (Hanwoo Experiment Station) ;
  • Lee, Seung-Hwan (Department of Animal Science and Biotechnology, Chung Nam National University)
  • Received : 2014.09.15
  • Accepted : 2015.01.30
  • Published : 2015.10.01

Abstract

Undoubtedly livestock is one of the major contributors to the economy of any country. The economic value of livestock includes meat, dairy products, fiber, fertilizer etc. Understanding and identifying the associations of quantitative trait loci (QTL) with the economically important traits is believed to substantially benefit the livestock industry. The past two decades have seen a flurry of interest in mapping the QTL associated with traits of economic importance on the genome. With the availability of single nucleotide polymorphism chip of various densities it is possible to identify regions, QTL and genes on the genome that explain the association and its effect on the phenotype under consideration. Remarkable advancement has been seen in genome wide association studies (GWAS) since its inception till the present day. In this review we describe the progress and challenges of GWAS in various livestock species.

Keywords

QTL;Livestock;Genome-wide Association

Acknowledgement

Supported by : National Institute of Animal Science

References

  1. Arya, R., R. Duggirala, C. P. Jenkinson, L. Almasy, J. Blangero, P. O'Connell, M. P. Stern. 2004. Evidence of a novel quantitative-trait locus for obesity on chromosome 4p in Mexican Americans. Am. J. Hum. Genet. 74:272-282. https://doi.org/10.1086/381717
  2. Becker, D., K. Wimmers, H. Luther, A. Hofer, and T. Leeb. 2013. A genome-wide association study to detect QTL for commercially important traits in Swiss Large White Boars. PLoS ONE. 8(2):e55951. https://doi.org/10.1371/journal.pone.0055951
  3. Beckmann, J. S. and M. Soller. 1986. Restriction fragment length polymorphisms and genetic improvement of agricultural species. Euphytica 35:111-124. https://doi.org/10.1007/BF00028548
  4. Bolorma, S., B. J. Hayes, K. Savin, R. Hawken, W. Barendse, P. F. Arthur, R. M. Herd, and M. E. Goddard. 2011. Genome-wide association studies for feedlot and growth traits in cattle. J. Anim. Sci. 89:1684-1697. https://doi.org/10.2527/jas.2010-3079
  5. Casas, E., S. D. Shackelford, J. W. Keele, R. T. Stone, S. M. Kappes, and M. Koohmaraie. 2000. Quantitative trait loci affecting growth and carcass composition of cattle segregating alternate forms of myostatin. J. Anim. Sci. 78:560-569. https://doi.org/10.2527/2000.783560x
  6. Cole, J. B., B. Waurich, M. Wensch-Dorendorf, D. M. Bickhart, and H. H. Swalve. 2014. A genome-wide association study of calf birth weight in Holstein cattle using single nucleotide polymorphisms and phenotypes predicted from auxiliary traits. J. Dairy Sci. 97:3156-3172. https://doi.org/10.3168/jds.2013-7409
  7. Dikmen, S., J. B. Cole, D. J. Null, and P. J. Hansen. 2013. Genome-wide association mapping for identification of quantitative trait loci for rectal temperature during heat stress in Holstein cattle. PLoS ONE 8(7):e69202. https://doi.org/10.1371/journal.pone.0069202
  8. Do, D. N., A. B. Strathe, T. Ostersen, J. Jensen, T. Mark, and H. N. Kadarmideen. 2013. Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping. PLoS ONE 8(8):e71509. https://doi.org/10.1371/journal.pone.0071509
  9. Duijvesteijn, N., E. F. Knol, J. W. M. Merks, R. P. M. A. Crooijmans, M. A. M. Groenen, H. Bovenhuis, and B. Harlizius. 2010. A genome-wide association study on androstenone levels in pigs reveals a cluster of candidate genes on chromosome 6. BMC Genetics 11:42.
  10. Fernandez-Gonzalez, A., A. R. La Spada, J. Treadaway, J. C. Higdon, B. S. Harris, R. L. Sidman, J. I. Morgan, and J. Zuo. 2002. Purkinje cell degeneration (pcd) phenotypes caused by mutations in the axotomy-induced gene, Nna1. Science 295(5561):1904-1906. https://doi.org/10.1126/science.1068912
  11. Go, Y. Y., E. Bailey, D. G. Cook, S. J. Coleman, J. N. MacLeod, K.-C. Chen, P. J. Timoney, and U. B. R. Balasuriya. 2011. Genome-wide association study among four horse breeds identifies a common haplotype associated with in vitro $CD3^+$ T cell susceptibility/resistance to equine arteritis virus infection. J. Virol. 85:13174-13184. https://doi.org/10.1128/JVI.06068-11
  12. Gu, X., C. Feng, L. Ma, C. Song, Y. Wang, Y. Da, H. Li, K. Chen, S. Ye, C. Ge, X. Hu, and N. Li. 2011. Genome-wide association study of body weight in chicken F2 resource population. PLoS ONE 6(7):e21872. https://doi.org/10.1371/journal.pone.0021872
  13. Gutierrez-Gil, B., J. L. Williams, D. Homer, D. Burton, C. S. Haley, and P. Wiener. 2009. Search for quantitative trait loci affecting growth and carcass traits in a cross population of beef and dairy cattle. J. Anim. Sci. 87:24-36. https://doi.org/10.2527/jas.2008-0922
  14. Ishii, A., K. Yamaji, Y. Uemoto, N. Sasago, E. Kobayashi, N. Kobayashi, T. Matsuhashi, S. Maruyama, H. Matsumoto, S. Sasazaki, and H. Mannen. 2013. Genome-wide association study for fatty acid composition in Japanese Black cattle. Anim. Sci. J. 84:675-682.
  15. Johansson, A. M., M. E. Pettersson, P. B. Siegel, and O. Carlborg. 2010. Genome-wide effects of long-term divergent selection. PLoS Genet. 6(11):e1001188. https://doi.org/10.1371/journal.pgen.1001188
  16. Kim, J. W., S. I. Park, and J. S. Yeo. 2003. Linkage mapping and QTL on chromosome 6 in Hanwoo (Korean Cattle). Asian Australas. J. Anim. Sci. 16:1402-1405. https://doi.org/10.5713/ajas.2003.1402
  17. Klein, R. J., C. Zeiss, E. Y. Chew, J. Y. Tsai, R. S. Sackler, C. Haynes, A. K. Henning, J. P. SanGiovanni, S. M. Mane, S. T. Mayne, M. B. Bracken, F. L. Ferris, J. Ott, C. Barnstable, and J. Hoh. 2005. Complement factor H polymorphism in age-related macular degeneration. Science 308(5720):385-389. https://doi.org/10.1126/science.1109557
  18. Kluge, R., K. Giesen, G. Bahrenberg, L. Plum, J. R. Ortlepp, and H. -G. Joost. 2000. Quantitative trait loci for obesity and insulin resistance (Nob1, Nob2) and their interaction with the leptin receptor allele (LeprA720T/T1044I) in New Zealand obese mice. Diabetologia 43:1565-1572. https://doi.org/10.1007/s001250051570
  19. Kneeland, J., C. Li, J. Basarab, W. M. Snelling, B. Benkel, B. Murdoch, C. Hansen, and S. S. Moore. 2004. Identification and fine mapping of quantitative trait loci for growth traits on bovine chromosomes 2, 6, 14, 19, 21, and 23 within one commercial line of Bos Taurus. J. Anim. Sci. 82:3405-3414. https://doi.org/10.2527/2004.82123405x
  20. Lee, S. H., B. H. Choi, D. Lim, C. Gondro, Y. M. Cho, C. G. Dang, A. Sharma, G. W. Jang, K. T. Lee, D. Yoon, H. K. Lee, S. H. Yeon, B. S. Yang, H. S. Kang, and S. K. Hong. 2013. Genome-wide association study identifies major loci for carcass weight on BTA14 in Hanwoo (Korean cattle). PLoS ONE 8(10): e74677. https://doi.org/10.1371/journal.pone.0074677
  21. Lillehammer, M., M. Arnyasi, S. Lien, H. G. Olsen, E. Sehested, J. Odegard, and T. H. E. Meuwissen. 2007. A genome scan for quantitative trait locus by environment interactions for production traits. J. Dairy Sci. 90:3482-3489. https://doi.org/10.3168/jds.2006-834
  22. Lillehammer, M., M. E. Goddard, H. Nilsen, E. Sehested, H. G. Olsen, S. Lien, and T. H. E. Meuwissen. 2008. Quantitative trait locus-by-environment interaction for milk yield traits on Bos taurus autosome 6. Genetics 179:1539-1546. https://doi.org/10.1534/genetics.107.084483
  23. Lipkin, E., M. O. Mosig, A. Darvasi, E. Ezra, A. Shalom, A. Friedmann, and M. Soller. 1988. Quantitative trait locus mapping in dairy cattle by means of selective milk DNA pooling using dinucleotide microsatellite markers: Analysis of milk protein percentage. Genetics 149:1557-1567.
  24. Liu, R., Y. Sun, G. Zhao, F. Wang, D. Wu, M. Zheng, J. Chen, L. Zhang, Y. Hu, and J. Wen. 2013. Genome-wide association study identifies loci and candidate genes for body composition and meat quality traits in Beijing-You chickens. PLoS ONE 8(4):e61172. https://doi.org/10.1371/journal.pone.0061172
  25. Liu, W., D. Li, J. Liu, S. Chen, L. Qu, J. Zheng, G. Xu, and N. Yang. 2011. A genome-wide SNP scan reveals novel loci for egg production and quality traits in White Leghorn and Brown-Egg Dwarf layers. PLoS ONE 6(12):e28600. https://doi.org/10.1371/journal.pone.0028600
  26. Luo, C., H. Qu, J. Ma, J. Wang, C. Li, C. Yang, X. Hu, N. Li, and D. Shu. 2013. Genome-wide association study of antibody response to Newcastle disease virus in chicken. BMC Genetics 14:42.
  27. Luo, W., S. Chen, D. Cheng, L. Wang, Y. Li, X. Ma, X. Song, X. Liu, W. Li, J. Liang, H. Yan, K. Zhao, C. Wang, L. Wang, and L. Zhang. 2012. Genome-wide association study of porcine hematological parameters in a Large White $\times$ Minzhu F2 resource population. Int. J. Biol. Sci. 8:870-881. https://doi.org/10.7150/ijbs.4027
  28. Matukumalli, L. K., C. T. Lawley, R. D. Schnabel. J. F. Taylor, M. F. Allan, M. P. Heaton, J. O'Connell, S. S. Moore, T. P. L. Smith, T. S. Sonstegard, and C. P. Van Tassell. 2009. Development and characterization of a high density SNP genotyping assay for cattle. PLoS ONE 4(4):e5350. https://doi.org/10.1371/journal.pone.0005350
  29. McCarthy, M. I., G. R. Abecasis, L. R. Cardon, D. B. Goldstein, J. Little, J. P. A. Ioannidis, and J. N. Hirschhorn. 2008. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet. 9:356-369. https://doi.org/10.1038/nrg2344
  30. Meredith, B. K., F. J. Kearney, E. K. Finlay, D. G. Bradley, A. G. Fahey, D. P. Berry, and D. J. Lynn. 2012. Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland. BMC Genetics 13:21.
  31. Murdoch, B. M., M. L. Clawson, W. W. Laegreid, P. Stothard, M. Settles, S. McKay, A. Prasad, Z. Wang, S. S. Moore, and J. L. Williams. 2010. A 2cM genome-wide scan of European Holstein cattle affected by classical BSE. BMC Genetics 11:20.
  32. Nkrumah, J. D., E. L. Sherman, C. Li, E. Marques, D. H. Crews Jr., R. Bartusiak, B. Murdoch, Z. Wang, J. A. Basarab, and S. S. Moore. 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. 85:3170-3181. https://doi.org/10.2527/jas.2007-0234
  33. Norman, R. A., D. B. Thompson, T. Foroud, W. T. Garvey, P. H. Bennett, C. Bogardus, and E. Ravussin. 1997. Genowide search for genes influencing percent body fat in Pima Indians: suggestive linkage at chromosome 11q21-q22. Am. J. Hum. Genet. 60:166-173.
  34. Olsen, H. G., B. J. Hayes, M. P. Kent, T. Nome, M. Svendsen, A. G. Larsgard, and S. Lien. 2011. Genome-wide association mapping in Norwegian Red cattle identifies quantitative trait loci for fertility and milk production on BTA12. Anim. Genet. 42:466-474. https://doi.org/10.1111/j.1365-2052.2011.02179.x
  35. Perusse, L., T. Rice, Y. C. Chagnon, J.-P. Despres, S. Lemieux, S. Roy, M. Lacaille, M.-A. Ho-Kim, M. Chagnon, M. A. Province, D. C. Rao, and C. Bouchard. 2001. A genome-wide scan for abdominal fat assessed by computed tomography in the quebec family study. Diabetes 50:614-621. https://doi.org/10.2337/diabetes.50.3.614
  36. Schneider, J. F., L. A. Rempel, W. M. Snelling, R. T. Wiedmann, D. J. Nonneman, and G. A. Rohrer. 2012. Genome-wide association study of swine farrowing traits. Part II: Bayesian analysis of marker data. J. Anim. Sci. 90:3360-3367. https://doi.org/10.2527/jas.2011-4759
  37. Schook, L. B., J. E. Beever, J. Rogers, S. Humphray, A. Archibald, P. Chardon, D. Milan, G. Rohrer, and K. Eversole. 2005. Swine Genome Sequencing Consortium (SGSC): A strategic roadmap for sequencing the pig genome. Comp. Funct. Genomics 6: 251-255. https://doi.org/10.1002/cfg.479
  38. Schurink, A., A. Wolc, B. J. Ducro, K. Frankena, D. J. Garrick, J. C. M. Dekkers, and J. A. M. van Arendonk. 2012a. Genome-wide association study of insect bite hypersensitivity in two horse populations in the Netherlands. Genet. Sel. Evol. 44:31. https://doi.org/10.1186/1297-9686-44-31
  39. Sherman, E. L., J. D. Nkrumah, C. Li, R. Bartusiak, B. Murdoch, and S. S. Moore. 2009. Fine mapping quantitative trait loci for feed intake and feed efficiency in beef cattle. J. Anim. Sci. 87:37-45. https://doi.org/10.2527/jas.2008-0876
  40. Snelling, W. M., M. F. Allan, J. W. Keele, L. A. Kuehn, T. McDaneld, T. P. L. Smith, T. S. Sonstegard, R. M. Thallman, and G. L. Bennett. 2010. Genome-wide association study of growth in crossbred beef cattle. J. Anim. Sci. 88:837-848. https://doi.org/10.2527/jas.2009-2257
  41. Soller, M. and J. S. Beckmann. 1983. Genetic polymorphism in varietal identification and genetic improvement. Theor. Appl. Genet. 67:25-33. https://doi.org/10.1007/BF00303917
  42. Stone, S., V. Abkevich, S. C. Hunt, A. Gutin, D. L. Russell, C. D. Neff, R. Riley, G. C. Frech, C. H. Hensel, S. Jammulapati, J. Potter, D. Sexton, T. Tran, D. Gibbs, D. Iliev, R. Gress, B. Bloomquist, J. Amatruda, M. M. P. Rae, D. T. Adams, H. M. Skolnick, and D. Shattuck. 2002. A major predisposition locus for severe obesity, at 4p15-p14. Am. J. Hum. Genet. 70:1459-1468. https://doi.org/10.1086/340670
  43. Streit, M., F. Reinhardt, G. Thaller, and J. Bennewitz. 2013. Genome-wide association analysis to identify genotype$\times$environment interaction for milk protein yield and level of somatic cell score as environmental descriptors in German Holsteins. J. Dairy Sci. 96:7318-7324. https://doi.org/10.3168/jds.2013-7133
  44. Sugimoto, M., S. Sasakia, Y. Gotohb, Y. Nakamurac, Y. Aoyagic, T. Kawaharab, and Y. Sugimoto. 2013. Genetic variants related to gap junctions and hormone secretion influence conception rates in cows. Proc. Natl. Acad. Sci. USA. 110:19495-19500. https://doi.org/10.1073/pnas.1309307110
  45. Sun, Y., G. Zhao, R. Liu, M. Zheng, Y. Hu, D. Wu, L. Zhang, P. Li and J. Wen. 2013. The identification of 14 new genes for meat quality traits in chicken using a genome-wide association study. BMC Genomics 14:458. https://doi.org/10.1186/1471-2164-14-458
  46. Tan, M. E. 2013. Genome-Wide Association Study for Stature in New Zealand Dairy Cattle. M.Sc. Thesis, Massey University, Palmerston North, New Zealand.
  47. Utsunomiya, Y. T., A. S. do Carmo, R. Carvalheiro, H. H. R. Neves, M. C. Matos, L. B. Zavarez, A. M. P. O'Brien, J. Solkner, J. C. McEwan, J. B. Cole, C. P. van Tassell, F. S. Schenkel, M. V. G. B. da Silva, L. R. P. Neto, T. S. Sonstegard, and J. F. Garcia. 2013. Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height. BMC Genetics 14:52.
  48. Wolc, A., J. Arango, T. Jankowski, P. Settar, J. E. Fulton, N. P. O'Sullivan, R. Fernando, D. J. Garrick, and J. C. M. Dekkers. 2013. Genome-wide association study for Marek's disease mortality in layer chickens. Avian Diseases. 57(2s1) (Suppl.1):395(Abstr.). https://doi.org/10.1637/10409-100312-Reg.1
  49. Zimin, A. V., A. L. Delcher, L. Florea, D. R. Kelley, M. C. Schatz, D. Puiu, F. Hanrahan, G. Pertea, C. P. Van Tassell, T. S. Sonstegard, G. Marcais, M. Roberts, P. Subramanian, J. A. Yorke, and S. L. Salzberg. 2009. A whole-genome assembly of the domestic cow, Bos taurus. Genome Biol. 10: R42. http://dx.doi.org/10.1186/gb-2009-10-4-r42. https://doi.org/10.1186/gb-2009-10-4-r42

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