Detecting Positive Selection of Korean Native Goat Populations Using Next-Generation Sequencing

  • Lee, Wonseok (Department of Agricultural Biotechnology, Animal Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University) ;
  • Ahn, Sojin (Department of Natural Science, Interdisciplinary Program in Bioinformatics, Seoul National University) ;
  • Taye, Mengistie (Department of Agricultural Biotechnology, Animal Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University) ;
  • Sung, Samsun (C&K genomics, Seoul National University Research Park) ;
  • Lee, Hyun-Jeong (Division of Animal Genomics and Bioinformatics, National Institute of Animal science, Rural Development Administration) ;
  • Cho, Seoae (C&K genomics, Seoul National University Research Park) ;
  • Kim, Heebal (Department of Agricultural Biotechnology, Animal Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University)
  • Received : 2016.09.08
  • Accepted : 2016.11.14
  • Published : 2016.12.31


Goats (Capra hircus) are one of the oldest species of domesticated animals. Native Korean goats are a particularly interesting group, as they are indigenous to the area and were raised in the Korean peninsula almost 2,000 years ago. Although they have a small body size and produce low volumes of milk and meat, they are quite resistant to lumbar paralysis. Our study aimed to reveal the distinct genetic features and patterns of selection in native Korean goats by comparing the genomes of native Korean goat and crossbred goat populations. We sequenced the whole genome of 15 native Korean goats and 11 crossbred goats using next-generation sequencing (Illumina platform) to compare the genomes of the two populations. We found decreased nucleotide diversity in the native Korean goats compared to the crossbred goats. Genetic structural analysis demonstrated that the native Korean goat and cross-bred goat populations shared a common ancestry, but were clearly distinct. Finally, to reveal the native Korean goat's selective sweep region, selective sweep signals were identified in the native Korean goat genome using cross-population extended haplotype homozygosity (XP-EHH) and a cross-population composite likelihood ratio test (XP-CLR). As a result, we were able to identify candidate genes for recent selection, such as the CCR3 gene, which is related to lumbar paralysis resistance. Combined with future studies and recent goat genome information, this study will contribute to a thorough understanding of the native Korean goat genome.


genomic comparison;native Korean goat;NGS;population analysis;XP-CLR;XP-EHH


Supported by : Rural Development Administration


  1. Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Royal Statistical Society. Series B (Methodological), 289-300.
  2. Browning, S.R., and Browning, B.L. (2007). Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am. J. Hum. Genet. 81, 1084-1097.
  3. Chen, H., Patterson, N., and Reich, D. (2010). Population differentiation as a test for selective sweeps. Genome Res. 20, 393-402.
  4. Choi, S., Choy, Y., Kim, Y., and Hur, S. (2006). Effects of feeding browses on growth and meat quality of Korean Black Goats. Small Ruminant Res. 65, 193-199.
  5. Cingolani, P., Platts, A., Coon, M., Nguyen, T., Wang, L., Land, S.J., Lu, X., and Ruden, D.M. (2012). A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6, 80-92.
  6. Crigler, L., Robey, R.C., Asawachaicharn, A., Gaupp, D., and Phinney, D.G. (2006). Human mesenchymal stem cell subpopulations express a variety of neuro-regulatory molecules and promote neuronal cell survival and neuritogenesis. Exp. Neurol. 198, 54-64.
  7. Dalai, S.K., Das, D., and Kar, S.K. (1998). Setaria digitataAdult 14-to 20-kDa antigens induce differential Thl/Th2 cytokine responses in the lymphocytes of endemic normals and asymptomatic microfilariae carriers in Bancroftian Filariasis. J. Clin. Immunol. 18, 114-123.
  8. Danecek, P., Auton, A., Abecasis, G., Albers, C.A., Banks, E., DePristo, M.A., Handsaker, R.E., Lunter, G., Marth, G.T., and Sherry, S.T. (2011). The variant call format and VCFtools. Bioinformatics 27, 2156-2158.
  9. Dennis Jr, G., Sherman, B.T., Hosack, D.A., Yang, J., Gao, W., Lane, H.C., and Lempicki, R.A. (2003). DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 4, P3.
  10. Dong, Y., Xie, M., Jiang, Y., Xiao, N., Du, X., Zhang, W., Tosser-Klopp, G., Wang, J., Yang, S., and Liang, J. (2013). Sequencing and automated whole-genome optical mapping of the genome of a domestic goat (Capra hircus). Nat. Biotechnol. 31, 135-141.
  11. Dybkaer, K., Iqbal, J., Zhou, G., Geng, H., Xiao, L., Schmitz, A., d'Amore, F., and Chan, W.C. (2007). Genome wide transcriptional analysis of resting and IL2 activated human natural killer cells: gene expression signatures indicative of novel molecular signaling pathways. BMC Genomics 8, 1.
  12. Emmons, D., and Lister, E. (1976). Quality of protein in milk replacers for young calves. I. Factors affecting in vitro curd formation by rennet (chymosin, rennin) from reconstituted skim milk powder. Canadian J. Animal Sci. 56, 317-325.
  13. Evanno, G., Regnaut, S., and Goudet, J. (2005). Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14, 2611-2620.
  14. Hivert, B., Liu, Z., Chuang, C.-Y., Doherty, P., and Sundaresan, V. (2002). Robo1 and Robo2 are homophilic binding molecules that promote axonal growth. Mol. Cell. Neurosci. 21, 534-545.
  15. Huang, D.W., Sherman, B.T., and Lempicki, R.A. (2009). Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1-13.
  16. Hubbard, T., Barker, D., Birney, E., Cameron, G., Chen, Y., Clark, L., Cox, T., Cuff, J., Curwen, V., and Down, T. (2002). The Ensembl genome database project. Nucleic Acids Res. 30, 38-41.
  17. Jackson, J.E. (2005). A user's guide to principal components (
  18. Kim, S.W., Park, S.B., Kim, M.J., Kim, D.H. and Yim, D.-G. (2014). Effects of different levels of concentrate in the diet on physicochemical traits of Korean native black goat meats. Korean J. Food Sci. Animal Res. 34, 457.
  19. Lee, H.-J., Kim, J., Lee, T., Son, J.K., Yoon, H.-B., Baek, K.-S., Jeong, J.Y., Cho, Y.-M., Lee, K.-T., and Yang, B.-C. (2014). Deciphering the genetic blueprint behind Holstein milk proteins and production. Genome Biol. Evol. 6, 1366-1374.
  20. Leo, A. and Schraven, B. (2001). Adapters in lymphocyte signalling. Curr. Opin. Immunol. 13, 307-316.
  21. Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., and Durbin, R. (2009). The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078-2079.
  22. McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., and Daly, M. (2010). The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297-1303.
  23. Mombaerts, P. (2004). Genes and ligands for odorant, vomeronasal and taste receptors. Nat. Rev. Neurosci. 5, 263-278.
  24. Nachman, M.W. (2001). Single nucleotide polymorphisms and recombination rate in humans. Trend Genet. 17, 481-485.
  25. Niimura, Y. (2009). Evolutionary dynamics of olfactory receptor genes in chordates: interaction between environments and genomic contents. Hum. Genomics 4, 107-118.
  26. Odahara, S., Chung, H., Choi, S., Yu, S., Sasazaki, S., Mannen, H., Park, C., and Lee, J. (2006). Mitochondrial DNA diversity of Korean native goats. Asian Australasian J. Animal Sci. 19, 482.
  27. Price, A.L., Patterson, N.J., Plenge, R.M., Weinblatt, M.E., Shadick, N.A., and Reich, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904-909.
  28. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A., Bender, D., Maller, J., Sklar, P., De Bakker, P.I., and Daly, M.J. (2007). PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559-575.
  29. Quinlan, A.R. and Hall, I.M. (2010). BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842.
  30. Sabeti, P.C., Reich, D.E., Higgins, J.M., Levine, H.Z., Richter, D.J., Schaffner, S.F., Gabriel, S.B., Platko, J.V., Patterson, N.J., and McDonald, G.J. (2002). Detecting recent positive selection in the human genome from haplotype structure. Nature 419, 832-837.
  31. Sabeti, P.C., Varilly, P., Fry, B., Lohmueller, J., Hostetter, E., Cotsapas, C., Xie, X., Byrne, E.H., McCarroll, S.A., and Gaudet, R. (2007). Genome-wide detection and characterization of positive selection in human populations. Nature 449, 913-918.
  32. Sallusto, F., Mackay, C.R., and Lanzavecchia, A. (1997). Selective expression of the eotaxin receptor CCR3 by human T helper 2 cells. Science 277, 2005-2007.
  33. Severino, P., Silva, E., Baggio-Zappia, G.L., Brunialti, M.K.C., Nucci, L.A., Rigato Jr, O., da Silva, I.D.C.G., Machado, F.R., and Salomao, R. (2014). Patterns of gene expression in peripheral blood mononuclear cells and outcomes from patients with sepsis secondary to community acquired pneumonia. PloS One 9, e91886.
  34. Sirko-Osadsa, D.A., Murray, M.A., Scott, J.A., Lavery, M.A., Warman, M.L., and Robin, N.H. (1998). Stickler syndrome without eye involvement is caused by mutations in COL11A2, the gene encoding the ${\alpha}2$(XI) chain of type XI collagen. J. Pediatr. 132, 368-371.
  35. Son, Y. (1999). Production and uses of Korean native Black goat. Small Ruminant Res. 34, 303-308.
  36. Uccelli, A., Benvenuto, F., Laroni, A., and Giunti, D. (2011). Neuroprotective features of mesenchymal stem cells. Best practice & research Clin. Haematol. 24, 59-64.
  37. Vikkula, M., Madman, E., Lui, V.C., Zhidkova, N.I., Tiller, G.E., Goldring, M.B., van Beersum, S.E., de Waal Malefijt, M.C., van den Hoogen, F.H. and Ropers, H.-H. (1995). Autosomal dominant and recessive osteochondrodysplasias associated with the COL11A2 locus. Cell 80, 431-437.
  38. Wright, K.T., Masri, W.E., Osman, A., Chowdhury, J., and Johnson, W.E. (2011). Concise review: bone marrow for the treatment of spinal cord injury: mechanisms and clinical applications. Stem Cells 29, 169-178.
  39. Yang, J., Lee, S.H., Goddard, M.E., and Visscher, P.M. (2011). GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76-82.
  40. Yu, B., Qian, T., Wang, Y., Zhou, S., Ding, G., Ding, F., and Gu, X. (2012). miR-182 inhibits Schwann cell proliferation and migration by targeting FGF9 and NTM, respectively at an early stage following sciatic nerve injury. Nucleic Acids Res. 40, 10356-10365.

Cited by

  1. Goat domestication and breeding: a jigsaw of historical, biological and molecular data with missing pieces 2017,