In forest tree breeding programs, open-pollinated families are frequently used to estimate genetic parameters and evaluate genetic merit of individuals. However, the presence of selfing events not documented in the pedigree affects the estimation of these parameters. In this study, 194 open-pollinated families of Eucalyptus globulus Labill. trees were used to compare the precision of estimated genetic parameters and accuracies of predicted breeding values with the conventional pedigree-based model (ABLUP) and the pedigree-genomic single-step model (ssGBLUP). The available genetic information for pairwise parent-offspring allows us to estimate an actual populational selfing rate of 5.4%. For all the growth and disease resistance traits evaluated, the inclusion of selfing rate was effective in reducing the upward bias, between 7 and 30%, in heritability estimates. The predictive abilities for ssGBLUP models were always higher than those for ABLUP models. In both cases, a considerable reduction of predictive abilities was observed when relatedness between training and validation populations was removed. We proposed a straightforward approach for the estimation of the actual selfing rate in a breeding population. The incorporation of this parameter allows for more reliable estimation of genetic parameters. Furthermore, our results proved that ssGBLUP was effective for the accurate estimation of genetic parameters and to improve the prediction of breeding values in presence of selfing events, thus a valuable tool for genomic evaluations in Eucalyptus breeding programs.
Acca sellowiana, known as feijoa or pineapple guava, is a diploid, (2n = 2x = 22) outcrossing fruit tree species native to Uruguay and Brazil. The species stands out for its highly aromatic fruits, with nutraceutical and therapeutic value. Despite its promising agronomical value, genetic studies on this species are limited. Linkage genetic maps are valuable tools for genetic and genomic studies, and constitute essential tools in breeding programs to support the development of molecular breeding strategies. A high-density composite genetic linkage map of A. sellowiana was constructed using two genetically connected populations: H5 (TCO × BR, N = 160) and H6 (TCO × DP, N = 184). Genotyping by sequencing (GBS) approach was successfully applied for developing single nucleotide polymorphism (SNP) markers. A total of 4,921 SNP markers were identified using the reference genome of the closely related species Eucalyptus grandis, whereas other 4,656 SNPs were discovered using a de novo pipeline. The individual H5 and H6 maps comprised 1,236 and 1,302 markers distributed over the expected 11 linkage groups, respectively. These two maps spanned a map length of 1,593 and 1,572 cM, with an average inter-marker distance of 1.29 and 1.21 cM, respectively. A large proportion of markers were common to both maps and showed a high degree of collinearity. The composite map consisted of 1,897 SNPs markers with a total map length of 1,314 cM and an average inter-marker distance of 0.69. A novel approach for the construction of composite maps where the meiosis information of individuals of two connected populations is captured in a single estimator is described. A high-density, accurate composite map based on a consensus ordering of markers provides a valuable contribution for future genetic research and breeding efforts in A. sellowiana. A novel mapping approach based on an estimation of multipopulation recombination fraction described here may be applied in the construction of dense composite genetic maps for any other outcrossing diploid species.
Mycosphaerella leaf disease (MLD) is one of the most prevalent foliar diseases of E. globulus plantations around the world. Since resistance management strategies have not been effective in commercial plantations, breeding to develop more resistant genotypes is the most promising strategy. Available genomic information can be used to detect genomic regions associated with resistance to MLD, which could significantly speed up the process of genetic improvement. In this study, we investigated the genetic basis of MLD resistance in a breeding population of E. globulus which was genotyped with the EUChip60K SNP array. Resistance to MLD was evaluated for resistance of the juvenile foliage, as defoliation and leaf spot severity, and for precocity of change to resistant adult foliage. Genome-wide association studies (GWAS) were carried out applying four Single-SNP models, a Genomic Best Linear Unbiased Prediction (GBLUP-GWAS) approach, and a Single step genome-wide association study (ssGWAS). The Single-SNP and GBLUP- GWAS models detected 13 and 16 SNP-trait associations in chromosomes 2, 3 y 11; whereas the ssGWAS detected 66 SNP trait associations in the same chromosomes, and additional significant SNP-trait associations in chromosomes 5 to 9 for the precocity of phase change (proportion of adult foliage). For this trait, the two main regions in chromosomes 3 and 11 were identified for the three approaches. The SNPs identified in these regions were positioned near the key miRNA genes, miR156.5 and miR157.4, which have a main role in the regulation of the timing of vegetative change, and also in the response to environmental stresses in plants. Our results outlined that ssGWAS was more powerful in detecting regions that affect resistance than conventional GWAS approaches. Additionally, suggest a polygenic genetic architecture for the heteroblastic transition in E. globulus and identified useful SNP markers for the development of marker-assisted selection strategies for resistance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.