Genomic prediction in a multi-generation Eucalyptus globulus breeding population

被引:0
作者
Geoffrey Haristoy
Laurent Bouffier
Luis Fontes
Luis Leal
Jorge A. P. Paiva
João-Pedro Pina
Jean-Marc Gion
机构
[1] AGAP,CIRAD
[2] Univ. Bordeaux,INRAE
[3] BIOGECO,undefined
[4] Altri Florestal,undefined
[5] Associação CECOLAB - Collaborative Laboratory Towards Circular Economy,undefined
[6] iBET,undefined
来源
Tree Genetics & Genomes | 2023年 / 19卷
关键词
Genomic selection; GBLUP; Progeny validation; Pedigree error; Breeding programme;
D O I
暂无
中图分类号
学科分类号
摘要
Genomic selection is a promising approach for reducing the length of the selection cycle in forest tree breeding. Its efficiency must be evaluated across generations for this purpose, but such studies have been performed for multi-generational breeding programmes in only a few forest tree species to date. We analysed a subset of the Eucalyptus globulus breeding population from the Portuguese company Altri Florestal. In total, 412 genotypes from three successive breeding generations were genotyped with 14,716 SNP markers. A comparison of pedigree-based and marker-based relationship coefficients allowed to correct several documented pedigree errors. Deregressed breeding values were estimated from phenotypic records for growth traits (height and diameter) and survival for 31 field trials distributed in one breeding zone in Portugal and used as pseudo-phenotypes for genomic prediction models. Accuracy was assessed by cross-validation according to two main scenarios: (i) a scenario based on a five random fold number, not taking generation into account, and (ii) scenarios investigating progeny validation using parental generations to predict the progenies. Accuracy was highest after pedigree correction and ranged from 0.46 to 0.60 for the first scenario, from − 0.56 to 0.72 for parent/progeny scenarios and from 0.33 to 0.79 when progenies were added to the calibration population. This genomic selection study provides promising insight for the Altri Florestal Eucalyptus breeding programme.
引用
收藏
相关论文
共 179 条
[31]  
Bradshaw BP(1975)Implementation of the realized genomic relationship matrix to open-pollinated white spruce family testing for disentangling additive from nonadditive genetic effects Biometrics 31 423-59
[32]  
Elms S(2011)Deregressing estimated breeding values and weighting information for genomic regression analyses Genet Res 93 47-231
[33]  
Chambers PGS(2012)Genomic selection in forest tree breeding BMC Genom 13 240-1829
[34]  
Borralho NMG(2014)Complex heatmaps reveal patterns and correlations in multidimensional genomic data New for 45 379-719
[35]  
Potts BM(2016)Genetic control of Plant Sci 242 108-1123
[36]  
Costa e Silva F(2006) harvest traits For Ecol Manage 234 78-362
[37]  
Shvaleva A(1994)Genetic correlations between pulpwood and solid-wood selection and objective traits in Theor Appl Genet 89 442-805
[38]  
Broetto F(2014)Invited review: genomic selection in dairy cattle: progress and challenges Tree Genet Genomes 10 241-46
[39]  
Costa J(2005)Increased accuracy of artificial selection by using the realized relationship matrix Mol Breed 15 55-531
[40]  
Vaillancourt RE(2020)Best linear unbiased estimation and prediction under a selection model Forests 11 1190-128