一种适用于单胎动物多品种选择的基因组关系矩阵

doi:10.11843/j.issn.0366-6964.2021.011.012

Abstract

Abstract: This study aimed to propose a new genomic relationship matrix and validate its simulated application efficacy for an across-breeds population. The bovine phenotypic and genotypic data were simulated by QMsim software; General G matrix was constructed by Gmatrix software; The new G matrix was constructed by R language. Compared with the general G matrix, the new G matrix took into account the Hardy-Weinberg disequilibrium loci in combined population; The ssGBLUP method in DMU software was used to calculate the estimated genomic breeding values; The GEBV accuracies predicted by two G matrixes were compared for different situations. The results indicated that under different heritabilities and QTL numbers, the GEBV accuracy of the general G matrix using A₂₂ matrix weighting could be achieved without using the A₂₂ matrix weighting for the new G matrix. When the partial pedigree information missed, the GEBV accuracy of new G matrix without weighting outperformed general G matrix with weighting. In conclusion, new G matrix could perform better on GEBV prediction for across-breeds population when the partial pedigree information missed.

Key words: genomic selection, simulated research, ssGBLUP, genomic relationship matrix, across-breeds

CLC Number:

S811

ZHANG Hongzhi, REN Duanyang, AN Lixia, QIAO Liying, LIU Wenzhong. A Novel Genomic Relationship Matrix Applied to Single Birth Animals for Across-breeds Genomic Selection[J]. Acta Veterinaria et Zootechnica Sinica, 2021, 52(11): 3108-3117.

References 42

[1]	HENDERSON C R.Best linear unbiased estimation and prediction under a selection model[J].Biometrics, 1975, 31(2):423-447.
[2]	COWLING W A, STEFANOVA K T, BEECK C P, et al. Using the animal model to accelerate response to selection in a self-pollinating crop[J].G3(Bethesda), 2015, 5(7):1419-1428.
[3]	DEKKERS J C M.Application of genomics tools to animal breeding[J].Curr Genomics, 2012, 13(3):207-212.
[4]	CALUS M P L, DE HAAS Y, PSZCZOLA M, et al. Predicted accuracy of and response to genomic selection for new traits in dairy cattle[J].Animal, 2013, 7(2):183-191.
[5]	PARK M N, ALAM M, KIM S, et al. Genomic selection through single-step genomic best linear unbiased prediction improves the accuracy of evaluation in Hanwoo cattle[J].Asian-Australas J Anim Sci, 2020, 33(10):1544-1557.
[6]	MOSER D W, MILLER S P, RETALLICK K J, et al. Genomic selection in the beef industry:current achievements and future directions[J].J Anim Sci, 2019, 97(S3):54-55.
[7]	ZHANG H H, YIN L L, WANG M Y, et al. Factors affecting the accuracy of genomic selection for agricultural economic traits in maize, cattle, and pig populations[J].Front Genet, 2019, 10:189.
[8]	TSAIRIDOU S, HAMILTON A, ROBLEDO D, et al. Optimizing low-cost genotyping and imputation strategies for genomic selection in Atlantic salmon[J].G3(Bethesda), 2020, 10(2):581-590.
[9]	MEUWISSEN T H E, HAYES B J, GODDARD M E.Prediction of total genetic value using genome-wide dense marker maps[J].Genetics, 2001, 157(4):1819-1829.
[10]	MISZTAL I, LOURENCO D, LEGARRA A.Current status of genomic evaluation[J].J Anim Sci, 2020, 98(4):skaa101.
[11]	WANG X Q, MIAO J, CHANG T P, et al. Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle[J].PLoS One, 2019, 14(2):e0210442.
[12]	DUARTE J L G, GORI A S, HUBIN X, et al. Performances of Adaptive MultiBLUP, Bayesian regressions, and weighted-GBLUP approaches for genomic predictions in Belgian Blue beef cattle[J].BMC Genomics, 2020, 21(1):545.
[13]	VANRADEN P M, WIGGANS G R.Derivation, calculation, and use of national animal model information[J].J Dairy Sci, 1991, 74(8):2737-2746.
[14]	GARRICK D J, TAYLOR J F, FERNANDO R L.Deregressing estimated breeding values and weighting information for genomic regression analyses[J].Genet Sel Evol, 2009, 41(1):55.
[15]	RICARD A, DANVY S, LEGARRA A.Computation of deregressed proofs for genomic selection when own phenotypes exist with an application in French show-jumping horses[J].J Anim Sci, 2013, 91(3):1076-1085.
[16]	VANRADEN P M.Efficient methods to compute genomic predictions[J].J Dairy Sci, 2008, 91(11):4414-4423.
[17]	LEGARRA A, CHRISTENSEN O F, AGUILAR I, et al. Single Step, a general approach for genomic selection[J].Livest Sci, 2014, 166:54-65.
[18]	SILVA R P, ESPIGOLAN R, BERTON M P, et al. Genomic prediction ability for carcass composition indicator traits in Nellore cattle[J].Livest Sci, 2021, 245:104421.
[19]	AGUILAR I, MISZTAL I, JOHNSON D L, et al. Hot topic:a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score[J].J Dairy Sci, 2010, 93(2):743-752.
[20]	AGUILAR I, FERNANDEZ E N, BLASCO A, et al. Effects of ignoring inbreeding in model-based accuracy for BLUP and SSGBLUP[J].J Anim Breed Genet, 2020, 137(4):356-364.
[21]	VAN DEN BERG I, MEUWISSEN T H E, MACLEOD I M, et al. Predicting the effect of reference population on the accuracy of within, across, and multibreed genomic prediction[J].J Dairy Sci, 2019, 102(4):3155-3174.
[22]	MRODE R, OJANGO J M K, OKEYO A M, et al. Genomic selection and use of molecular tools in breeding programs for indigenous and crossbred cattle in developing countries:current status and future prospects[J].Front Genet, 2019, 9:694.
[23]	BOICHARD D, DUCROCQ V, CROISEAU P, et al. Genomic selection in domestic animals:principles, applications and perspectives[J].C R Biol, 2016, 339(7-8):274-277.
[24]	HOZÉ C, FRITZ S, PHOCAS F, et al. Efficiency of multi-breed genomic selection for dairy cattle breeds with different sizes of reference population[J].J Dairy Sci, 2014, 97(6):3918-3929.
[25]	MEUWISSEN T, HAYES B, GODDARD M.Genomic selection:a paradigm shift in animal breeding[J].Anim Front, 2016, 6(1):6-14.
[26]	SARGOLZAEI M, SCHENKEL F S.QMSim:a large-scale genome simulator for livestock[J].Bioinformatics, 2009, 25(5):680-681.
[27]	ANDONOV S, LOURENCO D A L, FRAGOMENI B O, et al. Accuracy of breeding values in small genotyped populations using different sources of external information-A simulation study[J].J Dairy Sci, 2017, 100(1):395-401.
[28]	HENDERSON C R.Best linear unbiased estimation and prediction under a selection model[J].Biometrics, 1975, 31(2):423-447.
[29]	SNELLING W M, CHIU R, SCHEIN J E, et al. A physical map of the bovine genome[J].Genome Biol, 2007, 8(8):R165.
[30]	BRITO F V, NETO J B, SARGOLZAEI M, et al. Accuracy of genomic selection in simulated populations mimicking the extent of linkage disequilibrium in beef cattle[J].BMC Genet, 2011, 12(1):80.
[31]	CHRISTENSEN O F, MADSEN P, NIELSEN B, et al. Single-step methods for genomic evaluation in pigs[J].Animal, 2012, 6(10):1565-1571.
[32]	SU G, MADSEN P.User's guide for Gmatrix:a program for computing Genomic relationship matrix[J].AU Tjele Dk, 2011.
[33]	MADSEN P, SØRENSEN P, SU G S, et al. DMU-a package for analyzing multivariate mixed models[C]//Proceedings of the 8th World Congr.Geneti.Appl.to Livest Prod Belo Horizonte.2006:247.
[34]	MEUWISSEN T, GODDARD M.Accurate prediction of genetic values for complex traits by whole-genome resequencing[J]. Genetics, 2010, 185(2):623-631.
[35]	ERBE M, HAYES B J, MATUKUMALLI L K, et al. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels[J].J Dairy Sci, 2012, 95(7):4114-4129.
[36]	LUAN T, WOOLLIAMS J A, LIEN S, et al. The accuracy of genomic selection in Norwegian red cattle assessed by cross-validation[J]. Genetics, 2009, 183(3):1119-1126.
[37]	DAETWYLER H D, PONG-WONG R, VILLANUEVA B, et al. The impact of genetic architecture on genome-wide evaluation methods[J].Genetics, 2010, 185(3):1021-1031.
[38]	VITEZICA Z G, AGUILAR I, MISZTAL I, et al. Bias in genomic predictions for populations under selection[J].Genet Res, 2011, 93(5):357-366.
[39]	GAO H D, MADSEN P, AAMAND G P, et al. Bias in estimates of variance components in populations undergoing genomic selection:a simulation study[J].BMC Genomics, 2019, 20(1):956.
[40]	MARJANOVIC J, HULSEGGE B, CALUS M P L.Relatedness between numerically small Dutch Red dairy cattle populations and possibilities for multibreed genomic prediction[J].J Dairy Sci, 2021, 104(4):4498-4506.
[41]	IBTISHAM F, ZHANG L, XIAO M, et al. Genomic selection and its application in animal breeding[J].Thai J Vet Med, 2017, 47(3):301-310.
[42]	MISZTAL I, AGUILAR I, LOURENCO D, et al. Emerging issues in genomic selection[J].J Anim Sci, 2021, 99(6):skab092.

A Novel Genomic Relationship Matrix Applied to Single Birth Animals for Across-breeds Genomic Selection

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