DOI QR코드

DOI QR Code

Genome-wide analysis of Hanwoo and Chikso populations using the BovineSNP50 genotyping array

  • Song, Jun?Seok (College of Animal Life Science, Kangwon National University) ;
  • Seong, Ha?Seung (College of Animal Life Science, Kangwon National University) ;
  • Choi, Bong?Hwan (Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, RDA) ;
  • Lee, Chang?Woo (Gangwon Province Livestock Technology Research Institute) ;
  • Hwang, Nam?Hyun (College of Animal Life Science, Kangwon National University) ;
  • Lim, Dajeong (Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, RDA) ;
  • Lee, Joon?Hee (Institute of Agriculture & Life Science, College of Agriculture and Life Sciences, Gyeongsang National University) ;
  • Kim, Jin Soo (College of Animal Life Science, Kangwon National University) ;
  • Kim, Jeong?Dae (College of Animal Life Science, Kangwon National University) ;
  • Park, Yeon?Soo (Gangwon Province Livestock Technology Research Institute) ;
  • Choi, Jung?Woo (College of Animal Life Science, Kangwon National University) ;
  • Kim, Jong?Bok (College of Animal Life Science, Kangwon National University)
  • Received : 2018.01.08
  • Accepted : 2018.08.22
  • Published : 2018.12.31

Abstract

Hanwoo and Chikso are classified as Korean native cattle breeds that are currently registered with the Food and Agriculture Organization. However, there is still a lack of genomic studies to compare Hanwoo to Chikso populations. The objective of this study was to perform genome-wide analysis of Hanwoo and Chikso populations, investigating the genetic relationships between these two populations. We genotyped a total of 319 cattle including 214 Hanwoo and 105 Chikso sampled from Gangwon Province Livestock Technology Research Institute, using the Illumina Bovine SNP50K Beadchip. After performing quality control on the initially generated datasets, we assessed linkage disequilibrium patterns for all the possible SNP pairs within 1 Mb apart. Overall, average $r^2$ values in Hanwoo (0.048) were lower than Chikso (0.074) population. The genetic relationship between the populations was further assured by the principal component analysis, exhibiting clear clusters in each of the Hanwoo and Chikso populations, respectively. Overall heterozygosity for Hanwoo (0.359) was slightly higher than Chikso (0.345) and inbreeding coefficient was also a bit higher in Hanwoo (-0.015) than Chikso (-0.035). The average $F_{ST}$ value was 0.036 between Hanwoo and Chikso, indicating little genetic differentiation between those two breeds. Furthermore, we found potential selection signatures including LRP1B and NTRK2 genes that might be implicated with meat and reproductive traits in cattle. In this study, the results showed that both Hanwoo and Chikso populations were not under severe level of inbreeding. Although the principal component analysis exhibited clear clusters in each of the populations, we did not see any clear evidence that those two populations are highly differentiated each other.

Keywords

Acknowledgement

Grant : Comparative genome analysis of Hanwoo to identify heat tolerance and tenderness traits related genes under different selection pressure

Supported by : Kangwon National University, Rural Development Administration

References

  1. Choi JW, Liao X, Park S, Jeon HJ, Chung WH, Stothard P, Park YS, Lee JK, Lee KT, Kim SH, Oh JD, Kim N, Kim TH, Lee HK, Lee SJ (2013) Massively parallel sequencing of Chikso (Korean brindle cattle) to discover genome-wide SNPs and InDels. Mol Cells 36:203-211 https://doi.org/10.1007/s10059-013-2347-0
  2. Choi JW, Liao X, Stothard P, Chung WH, Jeon HJ, Miller SP, Choi SY, Lee JK, Yang B, Lee KT, Han KJ, Kim HC, Jeong D, Oh JD, Kim N, Kim TH, Lee HK, Lee SJ (2014) Whole-genome analyses of Korean native and Holstein cattle breeds by massively parallel sequencing. PLoS ONE 9:e101127 https://doi.org/10.1371/journal.pone.0101127
  3. Choi JW, Choi BH, Lee SH, Lee SS, Kim HC, Yu D, Chung WH, Lee KT, Chai HH, Cho YM, Lim D (2015) Whole-genome resequencing analysis of Hanwoo and Yanbian cattle to identify genomewide SNPs and signatures of selection. Mol Cells 38:466-473 https://doi.org/10.14348/molcells.2015.0019
  4. Cole JB, Wiggans GR, Ma L, Sonstegard TS, Lawlor TJ, Crooker BA, Tassell CPV, Yang J, Wang S, Matukumalli LK, Da Y (2011) Genome-wide association analysis of thirty one production, health, reproduction and body conformation traits in contemporary US Holstein cows. BMC Genom 12:408 https://doi.org/10.1186/1471-2164-12-408
  5. Devlin B, Risch N (1995) A comparison of linkage disequilibrium measures for fine-scale mapping. Genomics 29:311-322 https://doi.org/10.1006/geno.1995.9003
  6. Du FX, Clutter AC, Lohuis MM (2007) Characterizing linkage disequilibrium in pig populations. Int J Biol Sci 3:166-178
  7. Han Y, Penagaricano F (2016) Unravelling the genomic architecture of bull fertility in Holstein cattle. BMC Genet 17:143
  8. Herz J, Chen Y, Masiulis I, Zhou L (2009) Expanding functions of lipoprotein receptors. J Lipid Res 50(Supplement):S287-S292 https://doi.org/10.1194/jlr.R800077-JLR200
  9. Hyeong KE, Lee YM, Kim YS, Nam KC, Jo C, Lee KH, Lee JE, Kim JJ (2014) A whole genome association study on meat palatability in Hanwoo. Asian Australas J Anim Sci 27:1219 https://doi.org/10.5713/ajas.2014.14258
  10. Jaeger S, Pietrzik CU (2008) Functional role of lipoprotein receptors in Alzheimer's disease. Curr Alzheimer Res 5:15-25 https://doi.org/10.2174/156720508783884675
  11. Jo C, Cho SH, Chang J, Nam KC (2012) Keys to production and processing of Hanwoo beef: a perspective of tradition and science. Anim Front 2:32-38
  12. Kee HJ, Park EW, Lee CK (2008) Characterization of beef transcripts correlated with tenderness and moisture. Mol Cells 25:428-437
  13. Kim JH, Byun MJ, Kim MJ, Suh SW, Ko YG, Lee CW, Jung KS, Kim ES, Yu DJ, Kim WH, Choi SB (2013) mtDNA diversity and phylogenetic state of Korean cattle breed, Chikso. Asian Australas J Anim Sci 26:163 https://doi.org/10.5713/ajas.2012.12499
  14. Lee C, Pollak EJ (2002) Genetic antagonism between body weight and milk production in beef cattle. J Anim Sci 80:316-321 https://doi.org/10.2527/2002.802316x
  15. Lee SH, Park BH, Sharma A, Dang CG, Lee SS, Choi TJ, Choy YH, Kim HC, Jeon KJ, Kim SD, Yeon SH, Park SB, Kang HS (2014) Hanwoo cattle: origin, domestication, breeding strategies and genomic selection. J Anim Sci Technol 56:2 https://doi.org/10.1186/2055-0391-56-2
  16. Li Y, Kim JJ (2015) Effective population size and signatures of selection using bovine 50K SNP chips in Korean native cattle (Hanwoo). Evol Bioinform Online 11:143-153
  17. Li Y, Cam J, Bu G (2001) Low-density lipoprotein receptor family. Mol Neurobiol 23:53-67 https://doi.org/10.1385/MN:23:1:53
  18. Lim D, Strucken EM, Choi BH, Chai HH, Cho YM, Jang GW, Kim TH, Gondro C, Lee SH (2016) Genomic footprints in selected and unselected beef cattle breeds in Korea. PLoS ONE 11:e0151324 https://doi.org/10.1371/journal.pone.0151324
  19. Lu D, Sargolzaei M, Kelly M, Li C, Vander Voort G, Wang Z, Plastow G, Moore S, Miller SP (2012) Linkage disequilibrium in Angus, Charolais, and Crossbred beef cattle. Front Genet 3:152
  20. Matukumalli LK, Lawley CT, Schnabel RD, Taylor JF, Allan MF, Heaton MP, O'Connell J, Moore SS, Smith TPL, Sonstegard TS, Tassell CPV (2009) Development and characterization of a high density SNP genotyping assay for cattle. PLoS ONE 4:e5350 https://doi.org/10.1371/journal.pone.0005350
  21. May P, Woldt E, Matz RL, Boucher P (2007) The LDL receptor-related protein (LRP) family: an old family of proteins with new physiological functions. Ann Med 39:219-228 https://doi.org/10.1080/07853890701214881
  22. Meszaros G, Eaglen S, Waldmann P, Solkner J (2014) A genome wide association study for longevity in Cattle. Open J Genet 4:46-55 https://doi.org/10.4236/ojgen.2014.41007
  23. Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819-1829
  24. O'Brien AMP, Utsunomiya YT, Meszaros G, Bickhart DM, Liu GE, Van Tassell CP, Sonstegard TS, Da Silva MVB, Garcia JF, Solkner J (2014) Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle. Genet Sel Evol 46:19 https://doi.org/10.1186/1297-9686-46-19
  25. Park JH, Lee CW, Lee HL, Choi JW, Choy YH, Kwon AN, Ji YH, Kim JG (2014) Sires' MC1R genotypes and coat color of the offspring of the Chikso (Korean Brindle Cattle). J Emb Trans 29:21-27 https://doi.org/10.12750/JET.2014.29.1.21
  26. Park MN, Choi TJ, Park B, Lee SS, Choi JG, Cho KH, Yang CB, Lee JG, Choo HJ, Mahboob A, Kim SH, Park YS, Lee CW, Choi JW, Jung KS, Kim SB, Kim ES, Choi YS, Jung DJ, Lee KT, Shin NH, Park YS, Lee HJ, Shin SK, Choy YH (2016) Distribution of Chikso (Korean Brindle Cattle) in south Korea and their coat color expression. Korean J Int Agric 28:407-413 https://doi.org/10.12719/KSIA.2016.28.3.407
  27. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38:904-909 https://doi.org/10.1038/ng1847
  28. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC (2007) PLINK: a tool set for whole-genome association and populationbased linkage analyses. Am J Hum Genet 81:559-575 https://doi.org/10.1086/519795
  29. Randhawa IAS, Khatkar MS, Thomson PC, Raadsma HW (2014) Composite selection signals can localize the trait specific genomic regions in multi-breed populations of cattle and sheep. BMC Genet 15:34
  30. Sharma A, Lim DJ, Chai HH, Choi BH, Cho YM (2016a) Demographic trends in Korean native cattle explained using bovine SNP50 beadchip. Genom Inform 14:230-233 https://doi.org/10.5808/GI.2016.14.4.230
  31. Sharma A, Lee SH, Lim DJ, Chai HH, Choi BH, Cho Y (2016b) A genome-wide assessment of genetic diversity and population structure of Korean native cattle breeds. BMC Genet 17:139
  32. Strucken EM, Lee SH, Jang GW, Porto-Neto LR, Gondro C (2015) Towards breed formation by island model divergence in Korean cattle. BMC Evol Biol 15:284 https://doi.org/10.1186/s12862-015-0563-2
  33. Sudrajad P, Seo DW, Choi TJ, Park BH, Roh SH, Jung WY, Lee SS, Lee JH, Kim S, Lee SH (2017) Genome-wide linkage disequilibrium and past effective population size in three Korean cattle breeds. Anim Genet 48:85-89 https://doi.org/10.1111/age.12488
  34. Sved JA (1971) Linkage disequilibrium and homozygosity of chromosome segments in finite populations. Theor Popul Biol 2:125-141 https://doi.org/10.1016/0040-5809(71)90011-6
  35. Venkata Reddy B, Sivakumar AS, Jeong DW, Woo YB, Park SJ, Lee SY, Byun JY, Kim CH, Cho SH, Hwang I (2015) Beef quality traits of heifer in comparison with steer, bull and cow at various feeding environments. Anim Sci J 86:1-16 https://doi.org/10.1111/asj.12266
  36. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358-1370
  37. Wright S (1951) The genetical structure of populations. Ann Eugenics 15:323-354
  38. Wright S (1978) Evolution and the genetics of populations, volume 4. Variability within and among populations. University of Chicago Press, Chicago

Cited by

  1. Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds vol.113, pp.3, 2018, https://doi.org/10.1016/j.ygeno.2021.02.009
  2. Genome‐wide association study and pathway analysis for fat deposition traits in nellore cattle raised in pasture–based systems vol.138, pp.3, 2018, https://doi.org/10.1111/jbg.12525