본문 바로가기
KERD
논문KCI 등재

Comparison on genomic prediction using pedigree BLUP and single step GBLUP through the Hanwoo full-sib family

3

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

Objective: When evaluating individuals with the same parent and no phenotype by pedigree best linear unbiased prediction (BLUP), it is difficult to explain carcass grade difference and select individuals because they have the same value in pedigree BLUP (PBLUP). However, single step GBLUP (ssGBLUP), which can estimate the breeding value suitable for the individual by adding genotype, is more accurate than the existing method. Methods: The breeding value and accuracy were estimated with pedigree BLUP and ssGBLUP using pedigree and genotype of 408 Hanwoo cattle from 16 families with the same parent among siblings produced by fertilized egg transplantation. A total of 14,225 Hanwoo cattle with pedigree, genotype and phenotype were used as the reference population. PBLUP obtained estimated breeding value (EBV) using the pedigree of the test and reference populations, and ssGBLUP obtained genomic EBV (GEBV) after constructing and H-matrix by integrating the pedigree and genotype of the test and reference populations. Results: For all traits, the accuracy of GEBV using ssGBLUP is 0.18 to 0.20 higher than the accuracy of EBV obtained with PBLUP. Comparison of EBV and GEBV of individuals without phenotype, since the value of EBV is estimated based on expected values of alleles passed down from common ancestors. It does not take Mendelian sampling into consideration, so the EBV of all individuals within the same family is estimated to be the same value. However, GEBV makes estimating true kinship coefficient based on different genotypes of individuals possible, so GEBV that corresponds to each individual is estimated rather than a uniform GEBV for each individual. Conclusion: Since Hanwoo cows bred through embryo transfer have a high possibility of having the same parent, if ssGBLUP after adding genotype is used, estimating true kinship coefficient corresponding to each individual becomes possible, allowing for more accurate estimation of breeding value.

Abstract

Objective: When evaluating individuals with the same parent and no phenotype by pedigree best linear unbiased prediction (BLUP), it is difficult to explain carcass grade difference and select individuals because they have the same value in pedigree BLUP (PBLUP). However, single step GBLUP (ssGBLUP), which can estimate the breeding value suitable for the individual by adding genotype, is more accurate than the existing method. Methods: The breeding value and accuracy were estimated with pedigree BLUP and ssGBLUP using pedigree and genotype of 408 Hanwoo cattle from 16 families with the same parent among siblings produced by fertilized egg transplantation. A total of 14,225 Hanwoo cattle with pedigree, genotype and phenotype were used as the reference population. PBLUP obtained estimated breeding value (EBV) using the pedigree of the test and reference populations, and ssGBLUP obtained genomic EBV (GEBV) after constructing and H-matrix by integrating the pedigree and genotype of the test and reference populations. Results: For all traits, the accuracy of GEBV using ssGBLUP is 0.18 to 0.20 higher than the accuracy of EBV obtained with PBLUP. Comparison of EBV and GEBV of individuals without phenotype, since the value of EBV is estimated based on expected values of alleles passed down from common ancestors. It does not take Mendelian sampling into consideration, so the EBV of all individuals within the same family is estimated to be the same value. However, GEBV makes estimating true kinship coefficient based on different genotypes of individuals possible, so GEBV that corresponds to each individual is estimated rather than a uniform GEBV for each individual. Conclusion: Since Hanwoo cows bred through embryo transfer have a high possibility of having the same parent, if ssGBLUP after adding genotype is used, estimating true kinship coefficient corresponding to each individual becomes possible, allowing for more accurate estimation of breeding value.

참고문헌 (30)

  1. Henderson CR, "Theoretical basis and computational methods for a number of different animal models", J Dairy Sci (1988)[DOI]
  2. Jil TC, "Viability of bovine opuderived oocytes to honeybee as cryoprotectant", IOP Conf Ser : Earth Environ Sci, 756, pp.012063~ (2021)[DOI]
  3. Hayes BJ, "Increased accuracy of artificial selection by using the realized relationship matrix", Genet Res(Camb), 91, pp.47~60 (2009)[DOI]
  4. Goddard ME, "Using the genomic relationship matrix to predict the accuracy of genomic selection", J Anim Breed Genet, 128, pp.409~421 (2011)[DOI]
  5. Sullivan PG, "Mendelian sampling variance tests with genomic preselection", Proceedings of the 2018 Interbull Technical Workshop (2018)
  6. Ignacy Misztal, "Current status of genomic evaluation", Journal of Animal Science, 98(4) (2020), Oxford University Press (OUP)[DOI]
  7. Meuwissen THE, "Prediction of total genetic value using genome-wide dense marker maps", Genetics, 157, pp.1819~1829 (2001)[DOI]
  8. "Foundation for Statistical Computing", 2022
  9. Purcell S, "PLINK : A toolset for whole-genome association and population-based linkage analysis", Am J Hum Genet, 81, pp.559~575 (2007)[DOI]
  10. Loh P, "Eagle v2.4.1 User manual", Loh Lab, ~ (2022)
  11. Das S, "Next-generation genotype imputation service and methods", Nat Genet, 48, pp.1284~1287 (2016)[DOI]
  12. "Manual for BLUPF90 family programs"[URL]
  13. VanRaden PM, "Efficient methods to compute genomic predictions", J Diary Sci, 91, pp.4414~4423 (2008)[DOI]
  14. Zhang Z, "Software engineering the mixed model for genome-wide association studies on large samples", Brief Bioinform, 10, pp.664~675 (2009)[DOI]
  15. 이광현, "한우 SNP Chip 및 혈통 데이터를 이용한 경기 한우 암소의 유전능력평가 정확도 분석", 생명과학회지, 32(4), pp.279~284 (2022), 한국생명과학회[DOI]
  16. 이창우, "강원도 한우 암소 검정사업 시행지역 한우의 도체형질에 대한 유전능력 예측", 동물자원연구, 31(1), pp.1~12 (2020), 동물생명과학연구소[DOI]
  17. Jang JS, "Animal products grading statistical yearbook" (2022), Korea Institute for Animal Products Quality Evaluation
  18. 최태정, "한우의 성장 및 도체형질에 대한 유전모수 추정", 한국축산학회지, 48(6), pp.759~766 (2006), 한국축산학회
  19. Cesarani A, "Genomic selection of milk fatty acid composition in Sarda dairy sheep : Effect of different phenotypes and relationship matrices on heritability and breeding value accuracy", J Dairy Sci, 102, pp.3189~3203 (2019)[DOI]
  20. Hadi Esfandyari, "Genetic parameters and purebred–crossbred genetic correlations for growth, meat quality, and carcass traits in pigs", Journal of Animal Science, 98(12) (2020), Oxford University Press (OUP)[DOI]
  21. Piush Khanal, "Genetic parameters of meat quality, carcass composition, and growth traits in commercial swine", Journal of Animal Science, 97(9), pp.3669~3683 (2019), Oxford University Press (OUP)[DOI]
  22. Emhimad E. A. Abdalla, "Single-Step Methodology for Genomic Evaluation in Turkeys (Meleagris gallopavo)", Frontiers in Genetics, 10 (2019), Frontiers Media SA[DOI]
  23. Park Mi Na, "Genomic selection through single-step genomic best linear unbiased prediction improves the accuracy of evaluation in Hanwoo cattle", Animal Bioscience, 33(10), pp.1544~1557 (2020), 아세아·태평양축산학회[DOI]
  24. Powell JE, "Reconciling the analysis of IBD and IBS in complex trait studies", Nat Rev Genet, 11, pp.800~805 (2010)[DOI]
  25. Bonk S, "Mendelian sampling covariability of marker effects and genetic values", Genet Sel Evol, 48, pp.36~ (2016)[DOI]
  26. Hill WG, "Variation in actual relationship as a consequence of Mendelian sampling and linkage", Genet Res, 93, pp.47~64 (2011)[DOI]
  27. Lee SH, "Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits", Genet Sel Evol, 42, pp.22~ (2010)[DOI]
  28. Veerkamp RF, "Genomic and pedigree-based genetic parameters for scarcely recorded traits when some animals are genotyped", J Dairy Sci, 94, pp.4189~4197 (2011)[DOI]
  29. Christensen OF, "Singlestep methods for genomic evaluation in pigs", Animal, 6, pp.1565~1571 (2012)[DOI]
  30. 장성봉, "The effect of progeny numbers and pedigree depth on the accuracy of the EBV with the BLUP method", Korean Journal of Agricultural Science, 46(2), pp.293~301 (2019), 농업과학연구소[DOI]

관련 논문AI추천

Genomic selection through single-step genomic best linear unbiased prediction improves the accuracy of evaluation in Hanwoo cattle김시동, 이성수, 이승환, Alam Mahboob, Park Byoungho, Park Mi Na아세아·태평양축산학회 · Animal Bioscience2020 · 제33권 제10호Comparison of accuracy of breeding value for cow from three methods in Hanwoo (Korean cattle) population이승환, ChangHee Do, Dong Jae Lee, Dongwon Seo, Doo Ho Lee, Du-Hak Yoon, Hyo Sang Lee, Kil Hwan Lee, Phuong Thanh N. Dinh, Waruni Ekanayake, Yang Mo Koo, Yeong Kuk Kim한국축산학회 · 한국축산학회지2023 · 제65권 제4호Assessment of genomic prediction accuracy using different selection and evaluation approaches in a simulated Korean beef cattle population김영국, 이승환, 이준헌, Choi Hyunji, Nwogwugwu Chiemela Peter아세아·태평양축산학회 · Animal Bioscience2020 · 제33권 제12호전형매 가계 내 유전체정보량에 따른 유전체육종가 추정 및 정확도 분석강호찬, 김은호, 김지영, 명철현, 선두원, 이두호, 이승환, 임현태농업생명과학연구원 · 농업생명과학연구2022 · 제56권 제6호Accuracy of genomic breeding value prediction for intramuscular fat using different genomic relationship matrices in Hanwoo (Korean cattle)김시동, 김종주, 박병호, 이승환, 임다정, 최태정, Aditi Sharma아세아·태평양축산학회 · Animal Bioscience2017 · 제30권 제7호한우의 유전체 육종가의 정확도 추정김내수, 이승수, 이승환, 이중재, 조광현, 조용민, 최연호, 최유림, 최태정한국축산학회 · 한국축산학회지2013 · 제55권 제1호

이 간행물의 다른 논문 (15건)