Multiple-trait BLUP: a suitable strategy for genetic selection of Eucalyptus

Alves, Rodrigo Silva; Rocha, João Romero do Amaral Santos de Carvalho; Teodoro, Paulo Eduardo; Resende, Marcos Deon Vilela de; Henriques, Eduardo Pinheiro; Silva, Lidiane Aparecida; Carneiro, Pedro Crescêncio Souza; Bhering, Leonardo Lopes

doi:10.1007/s11295-018-1292-7

Cited by 24 publications

(13 citation statements)

References 21 publications

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“…Ulloa (2006) also observed heritability estimates for micronaire higher than the estimates observed for fiber fineness and maturity traits. In general, the results indicate that the phenotypic variance for most traits is mostly composed of residual effects and reinforces the need for using more accurate statistical methods, such as multiple-trait BLUP, to obtain unbiased genetic correlations (1).…”

Section: Discussionsupporting

confidence: 53%

Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length

et al. 2021

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Multi-trait best linear unbiased prediction (BLUP) is, generally, the most appropriate method to genetic evaluation because it considers the genetic and residual correlations among traits and conduct to higher selection accuracy. Thus, the present study aimed to identify traits correlated to the fiber length via path analysis under multi-trait BLUP for the cotton breeding. To this end, thirty-six elite lines were evaluated in three environments and phenotyped for many traits related to fiber quality and agronomic traits. Variance components were estimated via residual maximum likelihood (REML). The genetic correlation coefficients among traits were obtained through mixed model output, and to graphically express these results a correlation network was built. Subsequently, we performed path analysis considering fiber length as a principal dependent variable. Genetic parameters obtained by multi-trait BLUP model indicate that the phenotypic variance for most traits is mostly composed of residual effects, which reinforces the need for using more accurate statistical methods such as multi-trait BLUP. The results found for genetic correlations and path analysis under multi-trait BLUP reveal the difficulty of selection based on important fiber quality traits, especially fiber length, since most traits show very low cause-and-effect relationship, and other important traits present undesirable cause-and-effect relationship. Highlights Multiple-trait BLUP is the most appropriate method to predict genetic values. This is the first study in cotton to perform path analysis under multiple-trait BLUP. The findings of this study indicate that there is no genotype presenting all desirable traits.

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Section: Discussionsupporting

confidence: 53%

Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length

et al. 2021

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“…This analytical method, known as best linear prediction (BLP) or best linear unbiased prediction (BLUP), allows the maximization of the precision or the correlation between the predicted and real values for genetic merits, which includes the pedigree information of the individuals evaluated [ 63 ]. In this sense, the use of the Henderson mixed-model method (based on BLUP) has traditionally been used to determine the genetic merit of trees and it is considered a standard prediction method [ 8 , 9 ]. The genetic merit is predicted according to the degree of kinship between the trees of a breeding population under the assumption that individuals with a common ancestor are phenotypically similar and share loci of interest.…”

Section: Conventional Forest Tree Breeding and Marker-assisted Selection (Mas)mentioning

confidence: 99%

“…The authors summarized the recent progress in GWAS-based functional genomics of these traits and concluded that the emerging high-throughput phenotyping technology will be broadly used in the future to collect data for quantitative studies of complex traits related to tree growth, adaptation, morphological and physiological traits. 8…”

Section: Genome-wide Association Studies (Gwas)mentioning

confidence: 99%

“…Conventional forest tree breeding considers phenotypic evaluations based on kinship relationships between individuals to identify trees that are superior in a trait of interest. The Henderson mixed-model method has been traditionally used to determine the genetic merit of trees and best linear unbiased prediction (BLUP) has been the standard prediction method [ 8 , 9 ]. The genetic merit is predicted according to the degree of kinship between the trees of a breeding population under the assumption that individuals with a common ancestor are phenotypically similar and share loci of interest.…”

Section: Introductionmentioning

confidence: 99%

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Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Ahmar

Ballesta²,

Ali

et al. 2021

IJMS

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Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

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“…In diallel analyses, the REML/BLUP procedure allows the estimation of additive and dominance genetic variances, as well as the narrow- and broad-sense heritabilities [ 24 – 26 ]. In addition, it allows the prediction of additive and dominance genetic effects and the gains with selection, derived directly from parents and hybrid selection [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Accounting for spatial trends in multi-environment diallel analysis in maize breeding

et al. 2021

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Spatial trends represent an obstacle to genetic evaluation in maize breeding. Spatial analyses can correct spatial trends, which allow for an increase in selective accuracy. The objective of this study was to compare the spatial (SPA) and non-spatial (NSPA) models in diallel multi-environment trial analyses in maize breeding. The trials consisted of 78 inter-populational maize hybrids, tested in four environments (E1, E2, E3, and E4), with three replications, under a randomized complete block design. The SPA models accounted for autocorrelation among rows and columns by the inclusion of first-order autoregressive matrices (AR1 ⊗ AR1). Then, the rows and columns factors were included in the fixed and random parts of the model. Based on the Bayesian information criteria, the SPA models were used to analyze trials E3 and E4, while the NSPA model was used for analyzing trials E1 and E2. In the joint analysis, the compound symmetry structure for the genotypic effects presented the best fit. The likelihood ratio test showed that some effects changed regarding significance when the SPA and NSPA models were used. In addition, the heritability, selective accuracy, and selection gain were higher when the SPA models were used. This indicates the power of the SPA model in dealing with spatial trends. The SPA model exhibits higher reliability values and is recommended to be incorporated in the standard procedure of genetic evaluation in maize breeding. The analyses bring the parents 2, 10 and 12, as potential parents in this microregion.

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Multiple-trait BLUP: a suitable strategy for genetic selection of Eucalyptus

Cited by 24 publications

References 21 publications

Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length

Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Accounting for spatial trends in multi-environment diallel analysis in maize breeding

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