Communications for Statistical Applications and Methods

  • 제16권6호
  • /
  • Pages.915-923
  • /
  • 2009
  • /
  • 2287-7843(pISSN)
  • /
  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지
DOI QR코드

DOI QR Code

SNPHarvester를 활용한 주요 유전자 상호작용 효과 감명

Identify Major Gene-Gene Interaction Effects Using SNPHarvester

  • 투고 : 20091000
  • 심사 : 20091100
  • 발행 : 2009.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

광범위 유전자 연관(genome-wide association) 연구에서는 무수히 많은 유전자들 중에 인간의 질병에 관련된 유전자를 찾아왔다. 기존의 인간 질병에 관련된 유전자를 찾는 방법에서 이렇게 많은 유전자들 중에서 우수한 유전자를 찾는데 직접 이용할 시에는 계산이 복잡해지고 비용이 많이 들어가며 시간이 오래 걸린다는 단점이 생긴다. 따라서 이번 수많은 유전자들 중 주요 유전자 그룹을 찾는 방법으로 SNPHarvester가 개발되였다. 본 연구에서는 인간의 질병이 아닌 한우의 여러 경제형질에 관련된 우수 유전자를 SNPHarvester를 이용하여 17 개의 SNP들 중에서 우수한 유전자 그룹을 찾았고 의사결정나무(decision tree)를 이용하여 한우의 여러 경제형질을 높일 수 있는 SNP 그룹 내의 우수 유전자형도 함께 규명할 수 있었다.

The gene which is related in the disease of the human has been searched among numerous genes in GWA(Genome-Wide Association) research. However, most current statistical methods used to detect gene-gene interactions in disease association studies cannot be easily applied to handle the whole genome association study(GWAS) due to heavy computing. Therefore SNPHarvester is developed to find the main gene group among numerous genes. This research finds the superior gene groups which are related with the economic traits of the Korean beef cattle, not that of human, among sets of SNPs by using SNPHarvester, and also finds the superior genotypes which can enhance various qualities of Korean beef among SNP groups.

키워드

참고문헌

  1. Barendse, W., Bunch, R., Thomas M., Armitage, S., Baud, S. and Donaldson, N. (2004). The TG5 thyroglobulin gene test for a marbling quantitative trait loci evaluated in feedlot cattle, Australian Journal of Experimental Agriculture, 44, 669–674 https://doi.org/10.1071/EA02156
  2. Chung, Y.-J., Lee, S.-Y. and Park, T.-S. (2005). Multifactor dimensionality reduction in the presence of missing observations, Journal of Korea Statistical Society, Proceedings of the Autumn Conference, 31–36
  3. Culverhouse, R., Klein, T. and Shannon, W. (2004). Detecting epistatic interactions contributing to quantitative traits, Genetic Epidemiology, 27, 141–152 https://doi.org/10.1002/gepi.20006
  4. Hahn, L. W., Ritchie, M. D. and Moore, J. H. (2003). Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions, Bioinformatics, 19, 376–382
  5. Hosmer, D. W. and Lemeshow, S. (2000). Applied logistic regression, John Wiley & Sons, New York
  6. Kim, J. W., Park, S. I. and Yeo, J. S. (2003). Linkage mapping and QTL on chromosome 6 in Hanwoo(Korean Cattle), Asian-Australasian Journal of Animal Sciences, 16, 1402–1405
  7. Lee, J. Y., Kwon, J. C. and Kim, J. J. (2008). Multifactor dimensionality reduction(MDR) analysis to detect single nucleotide polymorphisms associated with a carcass trait in a Hanwoo population, Asian-Australasian. Journal of Animal Science, 6, 784–788
  8. Nelson, M. R., Kardia, S. L., Ferrell R. E. and Sing C. F. (2001). A combinatorial partitioning method to identify multilocus genotypic partitions that predict quantitative trait variation, Genome Research, 11, 458–470
  9. Page, B. T., Casas, E., Quaas, R. L., Thallman, R. M., Wheeler, T. L., Shackelford, S. D., Koohmaraie, M., White, S. N., Bennett, G. L., Keele, J. W., Dikeman, M. E. and Smith, T. P. L. (2004). Association of markers in the bovine CAPNI gene with meat tenderness in large crossbred populations that sample influential industry sires, Journal of Animal Science, 82, 3474–3481
  10. Ritchie, M. D., Hahn, L. W. and Moore, J. H. (2003). Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing Data, phenocopy, and genetic heterogeneity, Genetic Epidemiology, 24,150–157 https://doi.org/10.1002/gepi.10218
  11. Ritchie, M. D., Hahn, L. W., Roodi, N., Bailey, L. R., Dupont, W. D., Parl, F. F. and Moore, J. H. (2001). Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer, American Journal of Human Genetics, 69, 138–147 https://doi.org/10.1086/321276
  12. Yang, C., He, Z., Wan, X., Yang, Q., Xue, H. and Yu. W. (2009). SNPHarvester: A filtering-based approach for detecting epistatic interactions in genome-wide association studies, Bioinformatics, 25, 504–511 https://doi.org/10.1093/bioinformatics/btn652
  13. Snelling, W. M., Casas, E., Stone, R. T., Keele, J. W., Harhay, G. P., Benett, G. L. and Smith, T. P. (2005). Linkage mapping bovine EST-based SNP, BMC Genomics, 6, 74–84

피인용 문헌

  1. Major gene identification for SREBPs and FABP4 gene which are associated with fatty acid composition of Korean cattle vol.26, pp.3, 2015, https://doi.org/10.7465/jkdi.2015.26.3.677
  2. Main Gene Combinations and Genotype Identification of Hanwoo Quality with SNPHarvester vol.19, pp.6, 2012, https://doi.org/10.5351/CKSS.2012.19.6.799