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Aguilar I, Misztal I, Johnson DL, Legarra A, Tsuruta S, Lawlor TJ (2010) Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score1. J Dairy Sci 93:743–752
Google Scholar
Alanoshahr F, Rafat SA, Imany-Nabiyyi R, Alijani S, Robert-Granie C (2018) The impact of different genetic architectures on accuracy of genomic selection using three Bayesian methods. Iran J Appl Anim Sci 8:53–59
Google Scholar
Andrews DF, Mallows CL (1974) Scale mixtures of normal distributions. J R Stat Soc Ser B 36:99–102
Bassi FM, Bentley AR, Charmet G, Ortiz R, Crossa J (2016) Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.). Plant Sci 242:23–36
Google Scholar
Bhat JA, Ali S, Salgotra RK, Mir ZA, Dutta S, Jadon V et al. (2016) Genomic selection in the era of next generation sequencing for complex traits in plant breeding. Front Genet 7:221
Google Scholar
Bhering LL, Barrera CF, Ortega D, Laviola BG, Alves AA, Rosado TB et al. (2013) Differential response of Jatropha genotypes to different selection methods indicates that combined selection is more suited than other methods for rapid improvement of the species. Ind Crops Products 41:260–265
Google Scholar
Bhering LL, Junqueira VS, Peixoto LA, Cruz CD, Laviola BG (2015) Comparison of methods used to identify superior individuals in genomic selection in plant breeding. Genet Mol Res 14:10888–10896
Google Scholar
de los Campos G, Vazquez AI, Fernando R, Klimentidis YC, Sorensen D (2013) Prediction of complex human traits using the genomic best linear unbiased predictor. PLOS Genet 9:e1003608
Google Scholar
Crossa J, Campos G, de L, Pérez P, Gianola D, Burgueño J, Araus JL et al. (2010) Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186:713–724
Google Scholar
Crossa J, Pérez P, Hickey J, Burgueño J, Ornella L, Cerón-Rojas J et al. (2014) Genomic prediction in CIMMYT maize and wheat breeding programs. Heredity 112:48–60
Google Scholar
Cui Z, Dong H, Zhang A, Ruan Y, He Y, Zhang Z (2020) Assessment of the potential for genomic selection to improve husk traits in maize. G3 10:3741–3749
Google Scholar
Daetwyler HD, Pong-Wong R, Villanueva B, Woolliams JA (2010) The impact of genetic architecture on genome-wide evaluation methods. Genetics 185:1021–1031
Google Scholar
de Los Campos G, Hickey JM, Pong-Wong R, Daetwyler HD, Calus MPL (2013) Whole-genome regression and prediction methods applied to plant and animal breeding. Genetics 193:327–345
Google Scholar
Dekkers JCM (2007) Prediction of response to marker-assisted and genomic selection using selection index theory. J Anim Breed Genet 124:331–341
Google Scholar
Desta ZA, Ortiz R (2014) Genomic selection: genome-wide prediction in plant improvement. Trends Plant Sci 19:592–601
Google Scholar
Diaz S, Ariza-Suarez D, Ramdeen R, Aparicio J, Arunachalam N, Hernandez C, Diaz H et al. (2021) Genetic architecture and genomic prediction of cooking time in common bean (Phaseolus vulgaris L.). Front Plant Sci 11:2257
Google Scholar
Echeverri J, Zambrano J, Herrera AL (2014) Genomic evaluation of Holstein cattle in Antioquia (Colombia): a case study. Rev Colomb Cienc Pecu 27:306–314
Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES et al. (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLOS ONE 6:e19379
Google Scholar
Endelman JB (2011) Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4, https://doi.org/10.3835/plantgenome2011.08.0024
Fristche-Neto R, Akdemir D, Jannink JL (2018) Accuracy of genomic selection to predict maize single-crosses obtained through different mating designs. Theor Appl Genet 131:1153–1162
Google Scholar
Ganal MW, Durstewitz G, Polley A, Bérard A, Buckler ES, Charcosset A et al. (2011) A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PLOS ONE 6:e28334
Google Scholar
Gianola D, Fernando RL, Stella A (2006) Genomic-assisted prediction of genetic value with semiparametric procedures. Genetics 173:1761–1776
Google Scholar
Gianola D, Weigel KA, Krämer N, Stella A, Schön C-C (2014) Enhancing genome-enabled prediction by bagging genomic BLUP. PLOS ONE 9:e91693
Google Scholar
Goddard M (2009) Genomic selection: prediction of accuracy and maximisation of long term response. Genetica 136:245–257
Google Scholar
González-Camacho JM, de Los Campos G, Pérez P, Gianola D, Cairns JE, Mahuku G et al. (2012) Genome-enabled prediction of genetic values using radial basis function neural networks. Theor Appl Genet 125:759–771
Google Scholar
Guo G, Zhou Z, Wang Y, Zhao K, Zhu L, Lust G et al. (2011) Canine hip dysplasia is predictable by genotyping. Osteoarthr Cartil 19:420–429
Google Scholar
Habier D, Fernando RL, Dekkers JCM (2007) The impact of genetic relationship information on genome-assisted breeding values. Genetics 177:2389–2397
Google Scholar
Habier D, Fernando RL, Kizilkaya K, Garrick DJ (2011) Extension of the bayesian alphabet for genomic selection. BMC Bioinforma 12:186
Google Scholar
Haile TA, Heidecker T, Wright D, Neupane S, Ramsay L, Vandenberg A et al. (2020) Genomic selection for lentil breeding: empirical evidence. Plant Genome 13:e20002
Google Scholar
Hayes B, Goddard M (2010) Genome-wide association and genomic selection in animal breeding. Genome 53:876–883
Google Scholar
Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME (2009) Invited review: genomic selection in dairy cattle: Progress and challenges. J Dairy Sci 92:433–443
Google Scholar
Heffner EL, Jannink JL, Sorrells ME (2011) Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Genome 4, https://doi.org/10.3835/plantgenome2010.12.0029
Heffner EL, Sorrells ME, Jannink J-L (2009) Genomic selection for crop improvement. Crop Sci 49:1–12
Google Scholar
Hoffstetter A, Cabrera A, Huang M, Sneller C (2016) Optimizing training population data and validation of genomic selection for economic traits in soft winter wheat. G3 6:2919–2928
Google Scholar
Hong JP, Ro N, Lee HY, Kim GW, Kwon JK, Yamamoto E et al. (2020) Genomic selection for prediction of fruit-related traits in pepper (Capsicum spp.). Front Plant Sci 11:570871
Google Scholar
Howard R, Carriquiry AL, Beavis WD (2014) Parametric and nonparametric statistical methods for genomic selection of traits with additive and epistatic genetic architectures. G3 4:1027–1046
Google Scholar
Hu Z, Yang R-C (2014) Marker-based estimation of genetic parameters in genomics. PLOS ONE 9:e102715
Google Scholar
Juliana P, Poland J, Huerta-Espino J, Shrestha S, Crossa J, Crespo-Herrera L et al. (2019) Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics. Nat Genet 51:1530–1539
Google Scholar
Kramer M, Erbe M, Seefried FR, Gredler B, Bapst B, Bieber A et al. (2014) Accuracy of direct genomic values for functional traits in Brown Swiss cattle. J Dairy Sci 97:1774–1781
Google Scholar
Legarra A, Robert-Granié C, Manfredi E, Elsen J-M (2008) Performance of genomic selection in mice. Genetics 180:611–618
Google Scholar
Li B, Zhang N, Wang Y-G, George AW, Reverter A, Li Y (2018) Genomic prediction of breeding values using a subset of SNPs identified by three machine learning methods. Front Genet 9:237
Makowsky R, Pajewski NM, Klimentidis YC, Vazquez AI, Duarte CW, Allison DB et al. (2011) Beyond missing heritability: prediction of complex traits. PLOS Genet 7:e1002051
Google Scholar
Meuwissen TH, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829
Google Scholar
Michel S, Löschenberger F, Ametz C, Pachler B, Sparry E, Bürstmayr H (2019) Combining grain yield, protein content and protein quality by multi-trait genomic selection in bread wheat. Theor Appl Genet 132:2767–2780
Google Scholar
Neves HH, Carvalheiro R, O’Brien AMP, Utsunomiya YT, do Carmo AS, Schenkel FS et al. (2014) Accuracy of genomic predictions in Bos indicus (Nellore) cattle. Genet Sel Evol 46:17
Google Scholar
Nielsen NH, Jahoor A, Jensen JD, Orabi J, Cericola F, Edriss V et al. (2016) Genomic prediction of seed quality traits using advanced barley breeding lines. PLOS ONE 11:e0164494
Google Scholar
Noshahr FA, Rafat SA, Imany-Nabiyyi R, Alijani S, Robert-Granie C (2017) Genomic accuracy in different genetic architecture and genomic structure. Ind J Anim Sci 87:324–328
Nsibi M, Gouble B, Bureau S, Flutre T, Sauvage C, Audergon JM et al. (2020) Adoption and optimization of genomic selection to sustain breeding for apricot fruit quality. G3 10:4513–4529
Google Scholar
Ordas B, Butron A, Alvarez A, Revilla P, Malvar RA (2012) Comparison of two methods of reciprocal recurrent selection in maize (Zea mays L.). Theor Appl Genet 124:1183–1191
Google Scholar
Pais de Arruda M, Lipka A, Brown P, Krill A, Thurber C, Brown-Guedira G et al. (2016) Comparing genomic selection and marker-assisted selection for Fusarium head blight resistance in wheat (Triticum aestivum L.). Mol Breed 36:84
Google Scholar
Park T, Casella G (2008) The Bayesian Lasso. J Am Stat Assoc 103:681–686
Google Scholar
Pérez P, de los Campos G (2014) Genome-wide regression and prediction with the BGLR statistical package. Genetics 198:483–495
Google Scholar
Pérez-Cabal MA, Vazquez AI, Gianola D, Rosa GJM, Weigel KA (2012) Accuracy of genome-enabled prediction in a dairy cattle population using different cross-validation layouts. Front Genet 3:27
Google Scholar
Pérez-Rodríguez P, Gianola D, González-Camacho JM, Crossa J, Manès Y, Dreisigacker S (2012) Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat. G3 2:1595–1605
Google Scholar
Piepho HP (2009) Ridge regression and extensions for genomewide selection in maize. Crop Sci 49:1165–1176
Google Scholar
Poland J, Endelman J, Dawson J, Rutkoski J, Wu S, Manes Y et al. (2012) Genomic selection in wheat breeding using genotyping-by-sequencing. Plant Genome 5, https://doi.org/10.3835/plantgenome2012.05.0005
Resende MFR, Muñoz P, Resende MDV, Garrick DJ, Fernando RL, Davis JM et al. (2012) Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.). Genetics 190:1503–1510
Google Scholar
Rio S, Mary-Huard T, Moreau L, Charcosset A (2019) Genomic selection efficiency and a priori estimation of accuracy in a structured dent maize panel. Theor Appl Genet 132:81–96
Google Scholar
Sayfzadeh S, Honarvar M, Taheri F, Afshari K (2013) Accuracy of genomic prediction using random regression BLUP: a simulation study. Agrochimica Pisa 57:27–31
Tang Y, Liu X, Wang J, Li M, Wang Q, Tian F et al. (2016) GAPIT version 2: an enhanced integrated tool for genomic association and prediction. Plant Genome 9:plantgenome2015.11.0120
Google Scholar
Tempelman RJ (2015) Statistical and computational challenges in whole genome prediction and genome-wide association analyses for plant and animal breeding. JABES 20:442–466
Google Scholar
Tiede T, Smith KP (2018) Evaluation and retrospective optimization of genomic selection for yield and disease resistance in spring barley. Mol Breed 38:1–16
Google Scholar
VanRaden PM (2008) Efficient methods to compute genomic predictions. J Dairy Sci 91:4414–4423
Google Scholar
Viana JMS, Faria VR, Silva FFE, de Resende MDV (2011) Best linear unbiased prediction and family selection in crop species. Crop Sci 51:2371–2381
Google Scholar
Wang J, Zhou Z, Zhang Z, Li H, Liu D, Zhang Q et al. (2018) Expanding the BLUP alphabet for genomic prediction adaptable to the genetic architectures of complex traits. Heredity 121:648–662
Google Scholar
Wang Q, Tian F, Pan Y, Buckler ES, Zhang Z (2014) A SUPER powerful method for genome wide association study. PLOS ONE 9:e107684
Google Scholar
Wang X, Miao J, Chang T, Xia J, An B, Li Y et al. (2019) Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle. PLOS ONE 14:e0210442
Google Scholar
Wolc A, Kranis A, Arango J, Settar P, Fulton JE, O’Sullivan NP et al. (2016) Implementation of genomic selection in the poultry industry. Anim Front 6:23–31
Google Scholar
Wray NR, Goddard ME, Visscher PM (2007) Prediction of individual genetic risk to disease from genome-wide association studies. Genome Res 17:1520–1528
Google Scholar
Xu Y, Crouch JH (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48:391–407
Google Scholar
Yabe S, Yoshida H, Kajiya-Kanegae H, Yamasaki M, Iwata H, Ebana K et al. (2018) Description of grain weight distribution leading to genomic selection for grain-filling characteristics in rice. PLOS ONE 13:e0207627
Google Scholar
Yáñez JM, Houston RD, Newman S (2014) Genetics and genomics of disease resistance in salmonid species. Front Genet 5:415
Google Scholar
Yi N, Xu S (2008) Bayesian LASSO for quantitative trait loci mapping. Genetics 179:1045–1055
Google Scholar
Yoshida GM, Bangera R, Carvalheiro R, Correa K, Figueroa R, Lhorente JP et al. (2018) Genomic prediction accuracy for resistance against Piscirickettsia salmonis in farmed rainbow trout. G3 8:719–726
Google Scholar
Yu X, Li X, Guo T, Zhu C, Wu Y, Mitchell SE et al. (2016) Genomic prediction contributing to a promising global strategy to turbocharge gene banks. Nat Plant 2:16150
Google Scholar
Zhang H, Yin L, Wang M, Yuan X, Liu X (2019) Factors affecting the accuracy of genomic selection for agricultural economic traits in maize, cattle, and pig populations. Front Genet 10:189
Google Scholar
Zhang X, Pérez-Rodríguez P, Semagn K, Beyene Y, Babu R, López-Cruz MA et al. (2015) Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs. Heredity 114:291–299
Google Scholar
Zhao Y, Zeng J, Fernando R, Reif JC (2013) Genomic prediction of hybrid wheat performance. Crop Sci 53:802–810
Google Scholar
Zhong S, Dekkers JCM, Fernando RL, Jannink J-L (2009) Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a Barley case study. Genetics 182:355–364
Google Scholar
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