The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Study Gene Interaction Effect Based on Expanded Multifactor Dimensionality Reduction Algorithm

확장된 다중인자 차원축소 (E-MDR) 알고리즘에 기반한 유전자 상호작용 효과 규명

  • Received : 20090600
  • Accepted : 20091000
  • Published : 2009.12.31
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Abstract

Study the gene about economical characteristic of human disease or domestic animal is a matter of grave interest, preserve and elevation of gene of Korea cattle is key subject. Studies have been done on the gene of Korea cattle using EST based SNP map, but it is based on statistical model, therefore there are difference between real position and statistical position. These problems are solved using both EST_based SNP map and Gene on sequence by Lee et al. (2009b). We have used multifactor dimensionality reduction(MDR) method to study interaction effect of statistical model in general. But MDR method cannot be applied in all cases. It can be applied to the only case-control data. So, method is suggested E-MDR method using CART algorithm. Also we identified interaction effects of single nucleotide polymorphisms(SNPs) responsible for average daily gain(ADG) and marbling score(MS) using E-MDR method.

인간의 질병 또는 가축의 경제적인 특성에 관한 유전자의 규명은 매우 중요한 관심사이며, 우리나라 축산업을 대표하는 한우의 유전자원 보존과 능력향상은 매우 중요한 과제이다. 이를 연구하기 위해 기존 EST_based SNP 연관지도를 사용하여 발굴한 유전자로 연구되어왔으나 이는 통계학적 모델에 기반한 연관지도 작성법으로 실제 위치와는 차이가 있을 수 있다. 따라서 Lee (2009)에 의해 EST_based SNP 연관지도와 염기서열 분석으로 작성되어지는 Gene on sequence를 함께 고려하여 한우의 경제형질 연관 후보 DNA marker들이 발견되었다. 한편, 통계모형의 상호작용 효과를 고려할 때, 유전자와 같은 범주형 data에서 범주가 많을 경우 상호작용의 조합이 많아지므로 종종 모수들의 상호작용에 대한 해석과 모형을 결정하는 것이 어려울 수 있다. 그래서 비모수적인 방법으로 다중인자 차원축소방법 (MDR)을 사용해왔으며, 사례_대조 데이터에만 적용가능 MDR방법을 연속형 데이터에도 적용하기 위해 CART알고리즘을 적용한 확장된 다중인자 차원축소방법(E-MDR)이 제안되었다. 본 연구에서는 새롭게 발견된 단일염기다형성 (SNP)으로부터 E-MDR방법을 적용하여 한우의 경제형질(일당중체량, 근내지방도)에 영향을 주는 우수 유전자 단일염기다형성을 규명하였다.

Keywords

References

  1. Barendse, W., Bunch, R., Thomas, M., Armitage, S., Baud, S. and Donaldson, N. (2004). The TG5 thyroglob-ulin 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, Proceedings of the Autumn Conference Korea Statistical Society, 31-36
  3. Culverhouse, R., Klein, T. and Shannon, W. (2004). Detecting epistatic interactions contributing to quanti-tative traits, Genetic Epidemiology, 27, 141-152 https://doi.org/10.1002/gepi.20006
  4. Efron, B. and Tibshirani, R. (1993). An Introduction to the Bootstrap, Chapman & Hall/CRC, New York
  5. Good, P. (2000). Permutation Test: A Practical Guide to Resampling Methods for Testing Hypotheses, Springer, 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 https://doi.org/10.5713/ajas.2003.1402
  7. Lee, Y. S. (2009). Study on the identification of candidate genes and their haplotypes that are associated with growth and carcass traits in the QTL region of BTA6 in a Hanwoo population, Ph. D. Thesis, 1-94
  8. Lee, J. Y., Kwon, J. C. and Kim, J. J. (2008a). Multifactor dimensionality reduction(MDR) analysis to detect single nucleotide polymorphisms associated with a carcass trait in a Hanwoo population, Asian-Australasian Journal of Animal Sciences, 21, 784-788 https://doi.org/10.5713/ajas.2008.70645
  9. Lee, J. Y. and Lee, H. G. (2009). Multifactor dimensionality reduction(MDR) analysis by dummy variables, The Korean Journal of Applied Statistics, 22, 435-442 https://doi.org/10.5351/KJAS.2009.22.2.435
  10. Lee, Y. S., Lee, J. H., Lee, J. Y., Kim, J. J., Park, H. S. and Yeo, J. S. (2008b). Identification of candidate SNP (single nucleotide polymorphism) for growth and carcass traits related to QTL on chromosome 6 in Hanwoo (Korean cattle), Asian-Australasian Journal of Animal Sciences, 21, 1703-1709 https://doi.org/10.5713/ajas.2008.80223
  11. Nelson, M. R., Kardia, S. L. R., 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 https://doi.org/10.1101/gr.172901
  12. 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 CAPN1 gene with meat tenderness in large crossbred populations that sample in uential industry sires, Journal of Animal Science, 82, 3474-3481 https://doi.org/10.2527/2004.82123474x
  13. 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
  14. Snelling, W. M., Casas, E., Stone, R. T., Keele, J. W., Harhay, G. P., Benett, G. L. and Smith, T. P. L. (2005). Linkage mapping bovine EST-based SNP, BMC Genomics, 6, 74-84 https://doi.org/10.1186/1471-2164-6-74