Acta Veterinaria et Zootechnica Sinica ›› 2021, Vol. 52 ›› Issue (12): 3323-3334.doi: 10.11843/j.issn.0366-6964.2021.012.001
• REVIEW • Previous Articles Next Articles
YUAN Zehu1,2, GE Ling3, LI Fadi2, YUE Xiangpeng2*, SUN Wei1,3*
Received:
2021-04-06
Online:
2021-12-25
Published:
2021-12-22
CLC Number:
YUAN Zehu, GE Ling, LI Fadi, YUE Xiangpeng, SUN Wei. The Method of Genomic Selection by Integrating Biological Prior Information and Its Application in Livestock Breeding[J]. Acta Veterinaria et Zootechnica Sinica, 2021, 52(12): 3323-3334.
[1] | 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. |
[2] | GEORGES M, CHARLIER C, HAYES B.Harnessing genomic information for livestock improvement[J].Nat Rev Genet, 2019, 20(3):135-156. |
[3] | HICKEY J M.Sequencing millions of animals for genomic selection 2.0[J].J Anim Breed Genet, 2013, 130(5):331-332. |
[4] | PÉREZ-ENCISO M, RINCON J C, LEGARRA A.Sequence-vs. chip-assisted genomic selection:accurate biological information is advised[J].Genet Sel Evol, 2015, 47(1):43. |
[5] | HEIDARITABAR M, CALUS M P L, MEGENS H J, et al.Accuracy of genomic prediction using imputed whole-genome sequence data in white layers[J].J Anim Breed Genet, 2016, 133(3):167-179. |
[6] | VAN BINSBERGEN R, CALUS M P L, BINK M C A M, et al.Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle[J].Genet Sel Evol, 2015, 47(1):71. |
[7] | ABDOLLAHI-ARPANAHI R, MOROTA G, PENAGARICANO F.Predicting bull fertility using genomic data and biological information[J].J Dairy Sci, 2017, 100(12):9656-9666. |
[8] | YE S P, LI J Q, ZHANG Z.Multi-omics-data-assisted genomic feature markers preselection improves the accuracy of genomic prediction[J].J Anim Sci Biotechno, 2020, 11(1):109. |
[9] | DE LAS HERAS-SALDANA S, LOPEZ B I, MOGHADDAR N, et al.Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle[J].Genet Sel Evol, 2020, 52(1):54. |
[10] | GEBREYESUS G, BOVENHUIS H, LUND M S, et al.Reliability of genomic prediction for milk fatty acid composition by using a multi-population reference and incorporating GWAS results[J].Genet Sel Evol, 2019, 51(1):16. |
[11] | 袁泽湖.整合GWAS和eQTL先验的绵羊部分肉用性状全基因组选择研究[D].兰州:兰州大学, 2020.YUAN Z H.The prior information from GWAS and eQTL increase the accuracy of genomic selection in several sheep meat traits[D]. Lanzhou:Lanzhou University, 2020.(in Chinese) |
[12] | BOTELHO M E, LOPES M S, MATHUR P K, et al.Applying an association weight matrix in weighted genomic prediction of boar taint compounds[J].J Anim Breed Genet, 2021, 138(4):442-453. |
[13] | MOGHADDAR N, KHANSEFID M, VAN DER WERF J H J, et al.Genomic prediction based on selected variants from imputed whole-genome sequence data in Australian sheep populations[J].Genet Sel Evol, 2019, 51(1):72. |
[14] | MACLEOD I M, BOWMAN P J, JAGT C J V, et al.Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits[J].BMC Genomics, 2016, 17(1):144. |
[15] | HOFF J L, DECKER J E, SCHNABEL R D, et al.QTL-mapping and genomic prediction for bovine respiratory disease in U.S. Holsteins using sequence imputation and feature selection[J].BMC Genomics, 2019, 20(1):555. |
[16] | NANI J P, REZENDE F M, PEÑAGARICANO F.Predicting male fertility in dairy cattle using markers with large effect and functional annotation data[J].BMC Genomics, 2019, 20(1):258. |
[17] | LIU A X, LUND M S, BOICHARD D, et al.Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data[J].Heredity, 2020, 124(1):37-49. |
[18] | SU G, CHRISTENSEN O F, JANSS L, et al.Comparison of genomic predictions using genomic relationship matrices built with different weighting factors to account for locus-specific variances[J].J Dairy Sci, 2014, 97(10):6547-6559. |
[19] | ZHANG Z, LIU J F, DING X D, et al.Best linear unbiased prediction of genomic breeding values using a trait-specific marker-derived relationship matrix[J].PLoS One, 2010, 5(9):e12648. |
[20] | FRAGOMENI B O, LOURENCO D A L, MASUDA Y, et al.Incorporation of causative quantitative trait nucleotides in single-step GBLUP[J].Genet Sel Evol, 2017, 49(1):59. |
[21] | MA P P, LUND M S, AAMAND G P, et al.Use of a Bayesian model including QTL markers increases prediction reliability when test animals are distant from the reference population[J].J Dairy Sci, 2019, 102(8):7237-7247. |
[22] | CHANG L Y, TOGHIANI S, LING A, et al.High density marker panels, SNPs prioritizing and accuracy of genomic selection[J]. BMC Genet, 2018, 19(1):4. |
[23] | TOGHIANI S, CHANG L Y, LING A, et al.Genomic differentiation as a tool for single nucleotide polymorphism prioritization for genome wide association and phenotype prediction in livestock[J].Livest Sci, 2017, 205:24-30. |
[24] | BOUWMAN A C, DAETWYLER H D, CHAMBERLAIN A J, et al.Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals[J].Nat Genet, 2018, 50(3):362-367. |
[25] | XIANG R D, VAN DEN BERG I, MACLEOD I M, et al.Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits[J].Proc Natl Acad Sci U S A, 2019, 116(39):19398-19408. |
[26] | FANG L Z, SAHANA G, MA P P, et al.Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds[J].BMC Genomics, 2017, 18(1):604. |
[27] | EDWARDS S M, SØRENSEN I F, SARUP P, et al.Genomic prediction for quantitative traits is improved by mapping variants to gene ontology categories in Drosophila melanogaster[J].Genetics, 2016, 203(4):1871-1883. |
[28] | SARUP P, JENSEN J, OSTERSEN T, et al.Increased prediction accuracy using a genomic feature model including prior information on quantitative trait locus regions in purebred Danish Duroc pigs[J].BMC Genet, 2016, 17:11. |
[29] | SONG H L, YE S P, JIANG Y F, et al.Using imputation-based whole-genome sequencing data to improve the accuracy of genomic prediction for combined populations in pigs[J].Genet Sel Evol, 2019, 51(1):58. |
[30] | 郝兴杰.整合功能注释的全基因组选择和关联分析方法研究[D].武汉:华中农业大学, 2018.HAO X J.Incorporating functional annotation to develop genomic selection and genome-wide association study method[D].Wuhan:Huazhong Agricultural University, 2018.(in Chinese) |
[31] | XIANG R D, MACLEOD I M, DAETWYLER H D, et al.Genome-wide fine-mapping identifies pleiotropic and functional variants that predict many traits across global cattle populations[J].Nat Commun, 2021, 12(1):860. |
[32] | ZHANG Q Q, SAHANA G, SU G S, et al.Impact of rare and low-frequency sequence variants on reliability of genomic prediction in dairy cattle[J].Genet Sel Evol, 2018, 50(1):62. |
[33] | XU L, GAO N, WANG Z Z, et al.Incorporating genome annotation into genomic prediction for carcass traits in Chinese Simmental beef cattle[J].Front Genet, 2020, 11:481. |
[34] | GAO N, MARTINI J W R, ZHANG Z, et al.Incorporating gene annotation into genomic prediction of complex phenotypes[J]. Genetics, 2017, 207(2):489-501. |
[35] | LEE H J, CHUNG Y J, JANG S, et al.Genome-wide identification of major genes and genomic prediction using high-density and text-mined gene-based SNP panels in Hanwoo (Korean cattle)[J].PLoS One, 2020, 15(12):e0241848. |
[36] | VEERKAMP R F, BOUWMAN A C, SCHROOTEN C, et al.Genomic prediction using preselected DNA variants from a GWAS with whole-genome sequence data in Holstein-Friesian cattle[J].Genet Sel Evol, 2016, 48(1):95. |
[37] | VANRADEN P M.Efficient methods to compute genomic predictions[J].J Dairy Sci, 2008, 91(11):4414-4423. |
[38] | LEGARRA A, AGUILAR I, MISZTAL I.A relationship matrix including full pedigree and genomic information[J].J Dairy Sci, 2009, 92(9):4656-4663. |
[39] | ZHANG X Y, LOURENCO D, AGUILAR I, et al.Weighting strategies for single-step genomic BLUP:An iterative approach for accurate calculation of GEBV and GWAS[J].Front Genet, 2016, 7:151. |
[40] | REN D Y, AN L X, LI B J, et al.Efficient weighting methods for genomic best linear-unbiased prediction (BLUP) adapted to the genetic architectures of quantitative traits[J].Heredity, 2021, 126(2):320-334. |
[41] | GIANOLA D, FERNANDO R L, SCHÖN C C.Inferring trait-specific similarity among individuals from molecular markers and phenotypes with Bayesian regression[J].Theor Popul Biol, 2020, 132:47-59. |
[42] | ZHANG Z, OBER U, ERBE M, et al.Improving the accuracy of whole genome prediction for complex traits using the results of genome wide association studies[J].PLoS One, 2014, 9(3):e93017. |
[43] | ZHANG Z, ERBE M, HE J L, et al.Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix[J].G3 Genes Genom Genet, 2015, 5(4):615-627. |
[44] | MOURESAN E F, SELLE M, RÖNNEGÅRD L.Genomic prediction including SNP-specific variance predictors[J].G3 Genes Genom Genet, 2019, 9(10):3333-3343. |
[45] | GAO N, TENG J Y, YE S P, et al.Genomic prediction of complex phenotypes using genic similarity based relatedness matrix[J]. Front Genet, 2018, 9:364 |
[46] | 朱波, 王延晖, 牛红等.畜禽基因组选择中贝叶斯方法及其参数优化策略[J].中国农业科学, 2014, 47(22):4495-4505.ZHU B, WANG Y H, NIU H, et al.The strategy of parameter optimization of Bayesian methods for genomic selection in livestock[J]. Scientia Agricultura Sinica, 2014, 47(22):4495-4505.(in Chinese) |
[47] | 尹立林, 马云龙, 项韬, 等.全基因组选择模型研究进展及展望[J].畜牧兽医学报, 2019, 50(2):233-242.YIN L L, MA Y L, XIANG T, et al.The progress and prospect of genomic selection models[J].Acta Veterinaria et Zootechnica Sinica, 2019, 50(2):233-242.(in Chinese) |
[48] | GIANOLA D.Priors in whole-genome regression:the Bayesian alphabet returns[J].Genetics, 2013, 194(3):573-596. |
[49] | GAO N, LI J Q, HE J L, et al.Improving accuracy of genomic prediction by genetic architecture based priors in a Bayesian model[J].BMC Genet, 2015, 16:120. |
[50] | KADARMIDEEN H N.Genomics to systems biology in animal and veterinary sciences:progress, lessons and opportunities[J]. Livest Sci, 2014, 166:232-248. |
[51] | SPEED D, BALDING D J.MultiBLUP:improved SNP-based prediction for complex traits[J].Genome Res, 2014, 24(9):1550-1557. |
[52] | LLOYD-JONES L R, ZENG J, SIDORENKO J, et al.Improved polygenic prediction by Bayesian multiple regression on summary statistics[J].Nat Commun, 2019, 10(1):5086. |
[53] | BRØNDUM R F, SU G S, LUND M S, et al.Genome position specific priors for genomic prediction[J].BMC Genomics, 2012, 13:543. |
[54] | MOORE J K, MANMATHAN H K, ANDERSON V A, et al.Improving genomic prediction for pre-harvest sprouting tolerance in wheat by weighting large-effect quantitative trait loci[J].Crop Sci, 2017, 57(3):1315-1324. |
[55] | YIN L L, ZHANG H H, ZHOU X, et al.KAML:improving genomic prediction accuracy of complex traits using machine learning determined parameters[J].Genome Biol, 2020, 21(1):146. |
[56] | MOURESAN E F, SELLE M, RÖNNEGÅRD L.Genomic prediction including SNP-specific variance predictors[J].G3 Genes Genom Genet, 2019, 9(10):3333-3343. |
[57] | FANG L Z, SAHANA G, MA P P, et al.Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection[J].Genet Sel Evol, 2017, 49(1):44. |
[58] | 房灵昭.奶牛复杂性状基因组特征模型分析及基因组选择研究[D].北京:中国农业大学, 2017.FANG L Z.Genomic feature model analysis of complex traits in dairy cattle[D].Beijing:China Agricultural University, 2017.(in Chinese) |
[59] | MA P P, LUND M S, AAMAND G P, et al.Use of a Bayesian model including QTL markers increases prediction reliability when test animals are distant from the reference population[J].J Dairy Sci, 2019, 102(8):7237-7247. |
[60] | MEHRBAN H, NASERKHEIL M, LEE D H, et al.Genomic prediction using alternative strategies of weighted single-step genomic BLUP for yearling weight and carcass traits in Hanwoo beef cattle[J].Genes, 2021, 12(2):266. |
[61] | 谈成, 边成, 杨达, 等.基因组选择技术在农业动物育种中的应用[J].遗传, 2017, 39(11):1033-1045.TAN C, BIAN C, YANG D, et al.Application of genomic selection in farm animal breeding[J].Hereditas (Beijing), 2017, 39(11):1033-1045.(in Chinese) |
[62] | 周磊, 杨华威, 赵祖凯, 等.基因组选择在我国种猪育种中应用的探讨[J].中国畜牧杂志, 2018, 54(3):4-8.ZHOU L, YANG H W, ZHAO Z K, et al.The application of genomic selection in Chinese pig breeding industry[J].Chinese Journal of Animal Science, 2018, 54(3):4-8.(in Chinese) |
[63] | ZHANG C, KEMP R A, STOTHARD P, et al.Genomic evaluation of feed efficiency component traits in duroc pigs using 80k, 650k and whole-genome sequence variants[J].Genet Sel Evol, 2018, 50(1):14. |
[64] | CLARK E L, ARCHIBALD A L, DAETWYLER H D, et al.From FAANG to fork:application of highly annotated genomes to improve farmed animal production[J].Genome Biol, 2020, 21(1):285. |
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