scholarly journals Genetic Variation in Drought-Tolerance Traits and Their Relationships to Growth in Pinus radiata D. Don Under Water Stress

2022 ◽  
Vol 12 ◽  
Author(s):  
Ahmed Ismael ◽  
Jianming Xue ◽  
Dean Francis Meason ◽  
Jaroslav Klápště ◽  
Marta Gallart ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Water Stress ◽  
Genetic Correlations ◽  
Best Linear Unbiased Prediction ◽  
Linear Unbiased Prediction ◽  
Breeding Programs ◽  
Water Stress Tolerance ◽  
Drought Tolerant ◽  
Best Linear Unbiased ◽  
Selection Of

The selection of drought-tolerant genotypes is globally recognized as an effective strategy to maintain the growth and survival of commercial tree species exposed to future drought periods. New genomic selection tools that reduce the time of progeny trials are required to substitute traditional tree breeding programs. We investigated the genetic variation of water stress tolerance in New Zealand-grown Pinus radiata D. Don using 622 commercially-used genotypes from 63 families. We used quantitative pedigree-based (Genomic Best Linear Unbiased Prediction or ABLUP) and genomic-based (Genomic Best Linear Unbiased Prediction or GBLUP) approaches to examine the heritability estimates associated with water stress tolerance in P. radiata. Tree seedling growth traits, foliar carbon isotope composition (δ13C), and dark-adapted chlorophyll fluorescence (Y) were monitored before, during and after 10 months of water stress. Height growth showed a constant and moderate heritability level, while the heritability estimate for diameter growth and δ13C decreased with water stress. In contrast, chlorophyll fluorescence exhibited low heritability after 5 and 10 months of water stress. The GBLUP approach provided less breeding value accuracy than ABLUP, however, the relative selection efficiency of GBLUP was greater compared with ABLUP selection techniques. Although there was no significant relationship directly between δ13C and Y, the genetic correlations were significant and stronger for GBLUP. The positive genetic correlations between δ13C and tree biomass traits under water stress indicated that intraspecific variation in δ13C was likely driven by differences in the genotype’s photosynthetic capacity. The results show that foliar δ13C can predict P. radiata genotype tolerance to water stress using ABLUP and GBLUP approaches and that such approaches can provide a faster screening and selection of drought-tolerant genotypes for forestry breeding programs.

Genetic Parameters and Selection in Full-Sib Families of Tall Fescue Using Best Linear Unbiased Prediction (BLUP) Analysis of Animal Breeding and Genetic

2021 ◽  
Author(s):  
Fatemeh Pirnajmedin ◽  
Mohammad Mahdi Majidi ◽  
Mohammad Hadi Taleb ◽  
Davoud Rostami
Keyword(s):  
Ssr Markers ◽  
Tall Fescue ◽  
Genetic Parameters ◽  
Best Linear Unbiased Prediction ◽  
Forage Yield ◽  
Linear Unbiased Prediction ◽  
Breeding Programs ◽  
Sib Families ◽  
Best Linear Unbiased ◽  
Selection Of

Abstract Background: Better understanding of genetic structure of economic traits is crucial for identification and selection of superior genotypes in specific breeding programs. Best linear unbiased prediction (BLUP) is the most efficient method in this regards, which is poorly used in forage plant breeding. The present study aimed to assess genetic variation, estimate genetic parameters, and predict breeding values of five essential traits in full sib families (recognized by EST-SSR markers) of tall fescue using REML/BLUP procedure. Method: Forty-two full-sib families of tall fescue (included of 120 individual genotypes), recognized by EST-SSR markers’ along with twenty-one their corresponding parental genotypes were assessed for biomass production and agro-morphological traits at three harvests (spring, summer, and autumn) in the field during 4 years (2017-2020). Results: Considerable genotypic variability was observed for all traits. Low narrow-sense heritability (h2n) for dry forage yield (DFY) at three harvest indicates that non-additive gene actions may play an important role in the inheritance of this trait. Higher h2n of yield related traits and flowering time and also significant genetic correlation of these traits with forage yield, suggests that selection based on these traits via developing an index may lead to indirect genetic improvement of DFY. Conclusion: Our results showed the adequacy of REML/BLUP procedure for identification and selection of preferable parental genotypes and progenies with higher breeding values for future breeding programs such as variety development in tall fescue. Parental genotypes 21M, 1M, and 20L were identified as superior and stable genotypes and could also produce the best hybrid combinations when they were mostly used as maternal parent.

Combined selection of progeny in crop breeding using best linear unbiased prediction

2012 ◽  
Vol 92 (3) ◽  
pp. 553-562 ◽  
Author(s):  
José Marcelo Soriano Viana ◽  
Vinícius Ribeiro Faria ◽  
Fabyano Fonseca e Silva ◽  
Marcos Deon Vilela de Resende
Keyword(s):  
Least Squares ◽  
Best Linear Unbiased Prediction ◽  
Pedigree Information ◽  
Crop Breeding ◽  
Additive Variance ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Combined Selection ◽  
Selection Of ◽  
Unbiased Prediction

Viana, J. M. S., Faria, V. R., Fonseca e Silva, F. and Vilela de Resende, M. D. 2012. Combined selection of progeny in crop breeding using best linear unbiased prediction. Can. J. Plant Sci. 92: 553–562. Combined selection is an important strategy in crop breeding. As the classical index does not consider pedigree information, the objective of this study was to evaluate the efficiency of the best linear unbiased prediction (BLUP) methodology for combined selection of progeny. We analyzed expansion volume (EV) and grain yield of parents and inbred and non-inbred progeny from the popcorn population Viçosa. The BLUP analyses, single-trait and of the same character measured in parents and progeny (combined parent-family) were performed using the ASReml software. Because the experiments were balanced, the estimates of the additive variance from the BLUP and least squares analyses were generally equivalent. The accuracies of the BLUP analyses do not clearly establish the superior technique. The accuracy of the classical index tended to be higher than that obtained from BLUP analyses. There was equivalence between BLUP and least squares analyses relative to half-sib and inbred progeny selection, and superiority of the combined parent-family BLUP index for full-sib selection. The BLUP analyses also differed from the least squares analysis on the coincidence of selected parents. The populations obtained by selection based on BLUP of breeding values presented a lower effective size.

A comparison of alternative nucleus breeding systems and a sire referencing scheme for sheep improvement

1996 ◽  
Vol 62 (2) ◽  
pp. 265-270 ◽  
Author(s):  
J. A. Roden
Keyword(s):  
Selection Response ◽  
Best Linear Unbiased Prediction ◽  
Breeding Systems ◽  
Linear Unbiased Prediction ◽  
Sequential Selection ◽  
Best Linear Unbiased ◽  
The Mean ◽  
Nucleus Breeding ◽  
Open Nucleus ◽  
Selection Of

AbstractStochastic simulation was used to compare selection response and rate of inbreeding in four nucleus breeding systems and a sire referencing scheme for sheep: an open nucleus system (ONS), an open nucleus system with sequential selection of the nucleus (ONS-S), a sire referencing scheme (SRS) and a dispersed open nucleus system (DONS). Selection was based on best linear unbiased prediction of breeding values for a single trait measurable on all individuals prior to selection. Selection in a population of 1200 ewes equally divided into 10 flocks was simulated over a 15-year period. The mean rate of genetic gain was proportionately about 0-15 higher in ONS-S and DONS compared with ONS and SRS. The rate of inbreeding in SRS was considerably lower and in ONS-S, considerably higher, than in the other systems. The level of prolificacy in the population did not influence the relative ranking of the breeding systems but may have implications for their optimal structure.

scholarly journals Selection of forage oat genotypes through GGE Biplot and BLUP

2020 ◽  
Author(s):  
Franklin Santos ◽  
y Félix Marza
Keyword(s):  
Statistical Methods ◽  
Dry Matter ◽  
Best Linear Unbiased Prediction ◽  
Dry Matter Yield ◽  
Gge Biplot ◽  
Average Yield ◽  
Phenotypic Stability ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Selection Of

AbstractIn Bolivia, there is a low predominance of forage oat productivity. Therefore, it was proposed to select more productive and stable genotypes through statistical methods of GGE Biplot and BLUP. The research was conducted in three environments in Bolivia and six commercial varieties of forage oats were evaluated; three of them correspond to INIA Peru and the rest of Bolivia. Data were analyzed through GGE Biplot and BLUP (Best Linear Unbiased Prediction) and an average yield of 10.29 ±3.51 t ha−1 of dry matter was obtained. BLUP accumulated greater variance than GGE Biplot in the first two components. In terms of productivity and stability values, both models have the same selection trend. Thus, Tayco and Texas were selected for their outstanding characteristic in dry matter yield and phenotypic stability.

scholarly journals A Bayesian Genomic Multi-output Regressor Stacking Model for Predicting Multi-trait Multi-environment Plant Breeding Data

2019 ◽  
Vol 9 (10) ◽  
pp. 3381-3393 ◽  
Author(s):  
Osval A. Montesinos-López ◽  
Abelardo Montesinos-López ◽  
José Crossa ◽  
Jaime Cuevas ◽  
José C. Montesinos-López ◽  
...  
Keyword(s):  
Ridge Regression ◽  
Prediction Accuracy ◽  
Best Linear Unbiased Prediction ◽  
Environment Interaction ◽  
Linear Unbiased Prediction ◽  
Breeding Programs ◽  
Second Stage ◽  
Genotype Environment Interaction ◽  
Best Linear Unbiased ◽  
Two Stages

In this paper we propose a Bayesian multi-output regressor stacking (BMORS) model that is a generalization of the multi-trait regressor stacking method. The proposed BMORS model consists of two stages: in the first stage, a univariate genomic best linear unbiased prediction (GBLUP including genotype × environment interaction GE) model is implemented for each of the L traits under study; then the predictions of all traits are included as covariates in the second stage, by implementing a Ridge regression model. The main objectives of this research were to study alternative models to the existing multi-trait multi-environment (BMTME) model with respect to (1) genomic-enabled prediction accuracy, and (2) potential advantages in terms of computing resources and implementation. We compared the predictions of the BMORS model to those of the univariate GBLUP model using 7 maize and wheat datasets. We found that the proposed BMORS produced similar predictions to the univariate GBLUP model and to the BMTME model in terms of prediction accuracy; however, the best predictions were obtained under the BMTME model. In terms of computing resources, we found that the BMORS is at least 9 times faster than the BMTME method. Based on our empirical findings, the proposed BMORS model is an alternative for predicting multi-trait and multi-environment data, which are very common in genomic-enabled prediction in plant and animal breeding programs.

scholarly journals ESTIMATES OF GENETIC PARAMETERS USING RELM/BLUP FOR INTRA-POPULATIONAL GENETIC BREEDING OF Platonia insignis Mart.

2016 ◽  
Vol 40 (3) ◽  
pp. 561-573 ◽  
Author(s):  
Maria Clideana Cabral Maia ◽  
Luciano Medina Macedo ◽  
Lúcio Flavo Lopes Vasconcelos ◽  
João Pedro Alves Aquino ◽  
Luís Cláudio Oliveira ◽  
...  
Keyword(s):  
Variance Components ◽  
Genetic Parameters ◽  
Recurrent Selection ◽  
Indirect Selection ◽  
Best Linear Unbiased Prediction ◽  
Selection Differential ◽  
Linear Unbiased Prediction ◽  
Genetic Breeding ◽  
Best Linear Unbiased ◽  
Selection Of

ABSTRACT The aim of this study was to estimate genetic parameters to support the selection of bacuri progenies for a first cycle of recurrent selection, using the REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure to estimate the variance components and genotypic values. Were evaluated twelve variables in a total of 210 fruits from 39 different seed trees, from a field trial with an experimental design of incomplete blocks with clonal replies among subplots. The three variables related with the fruit development (weight, diameter, length) showed strong correlation, and where fruit length showed higher heritability and potential to be used for indirect selection. Among the 39 progenies evaluated in this study, five present potential to compose the next cycle of recurrent selection, due they hold good selection differential either to agrotechnological variables as to development of bacuri fruit.

scholarly journals Genetic association among feeding behavior, feed efficiency, and growth traits in growing indicine cattle

2020 ◽  
Vol 98 (11) ◽  
Author(s):  
Lorena Ferreira Benfica ◽  
Leandro Sannomiya Sakamoto ◽  
Ana Fabrícia Braga Magalhães ◽  
Matheus Henrique Vargas de Oliveira ◽  
Lúcia Galvão de Albuquerque ◽  
...  
Keyword(s):  
Feeding Behavior ◽  
Genetic Gain ◽  
Feed Efficiency ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Best Linear Unbiased Prediction ◽  
Likelihood Method ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Abstract This study aimed to estimate genetic parameters, including genomic data, for feeding behavior, feed efficiency, and growth traits in Nellore cattle. The following feeding behavior traits were studied (861 animals with records): time spent at the feed bunk (TF), duration of one feeding event (FD), frequency of visits to the bunk (FF), feeding rate (FR), and dry matter intake (DMI) per visit (DMIv). The feed efficiency traits (1,543 animals with records) included residual feed intake (RFI), residual weight gain (RWG), and feed conversion (FC). The growth traits studied were average daily gain (ADG, n = 1,543 animals) and selection (postweaning) weight (WSel, n = 9,549 animals). The (co)variance components were estimated by the maximum restricted likelihood method, fitting animal models that did (single-step genomic best linear unbiased prediction) or did not include (best linear unbiased prediction) genomic information in two-trait analyses. The direct responses to selection were calculated for the feed efficiency traits, ADG, and WSel, as well as the correlated responses in feed efficiency and growth by direct selection for shorter TF. The estimated heritabilities were 0.51 ± 0.06, 0.35 ± 0.06, 0.27 ± 0.07, 0.34 ± 0.06, and 0.33 ± 0.06 for TF, FD, FF, FR, and DMIv, respectively. In general, TF and FD showed positive genetic correlations with all feed efficiency traits (RFI, RWG, and FC), ADG, DMI, and WSel. Additionally, TF showed high and positive genetic and phenotypic correlations with RFI (0.71 ± 0.10 and 0.46 ± 0.02, respectively) and DMI (0.56 ± 0.09 and 0.48 ± 0.03), and medium to weak genetic correlations with growth (0.32 ± 0.11 with ADG and 0.14 ± 0.09 with WSel). The results suggest that TF is a strong indicator trait of feed efficiency, which exhibits high heritability and a weak positive genetic correlation with growth. In a context of a selection index, the inclusion of TF to select animals for shorter TF may accelerate the genetic gain in feed efficiency by reducing RFI but with zero or slightly negative genetic gain in growth traits.

scholarly journals Quantitative genetic analysis of methylxanthines and phenolic compounds in mate progenies

2010 ◽  
Vol 45 (2) ◽  
pp. 171-177 ◽  
Author(s):  
Euclides Lara Cardozo Junior ◽  
Carmen Maria Donaduzzi ◽  
Osvaldo Ferrarese-Filho ◽  
Juliana Cristhina Friedrich ◽  
Adriana Gonela ◽  
...  
Keyword(s):  
Phenolic Compounds ◽  
High Performance ◽  
Genetic Parameters ◽  
Best Linear Unbiased Prediction ◽  
Region Of Origin ◽  
Linear Unbiased Prediction ◽  
Breeding Programs ◽  
Quantitative Genetic ◽  
Sib Families ◽  
Best Linear Unbiased

The objective of this work was to determine the contents of methylxanthines, caffeine and theobromine, and phenolic compounds, chlorogenic and caffeic acids, in 51 mate progenies (half-sib families) and estimate the heritability of genetic parameters. Mate progenies were from five Brazilian municipalities: Pinhão, Ivaí, Barão de Cotegipe, Quedas do Iguaçu, and Cascavel. The progenies were grown in the Ivaí locality. The contents of the compounds were obtained by high performance liquid chromatography (HPLC). The estimation of genetic parameters by the restricted maximum likelihood (REML) and the prediction of genotypic values via best linear unbiased prediction (BLUP) were obtained by the Selegen - REML/BLUP software. Caffeine (0.248-1.663%) and theobromine (0.106-0.807%) contents were significantly different (p<0.05) depending on the region of origin, with high individual heritability (ĥ²>0.5). The two different progeny groups determined for chlorogenic (1.365-2.281%) and caffeic (0.027-0.037%) acid contents were not significantly different (p<0.05) depending on the locality of origin. Individual heritability values were low to medium for chlorogenic (ĥ²<0.4) and caffeic acid (ĥ²<0.3). The content of the compounds and the values of genetic parameters could support breeding programs for mate.

scholarly journals Prediction of genotypic values and estimation of genetic parameters in common bean

2008 ◽  
Vol 51 (3) ◽  
pp. 465-472 ◽  
Author(s):  
Alisson Fernando Chiorato ◽  
Sérgio Augusto Morais Carbonell ◽  
Luiz Antônio dos Santos Dias ◽  
Marcos Deon Vilela de Resende
Keyword(s):  
Common Bean ◽  
Genetic Parameters ◽  
High Accuracy ◽  
Best Linear Unbiased Prediction ◽  
Broad Sense Heritability ◽  
Phaseolus Vulgaris L ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Estimation Of Genetic Parameters ◽  
Selection Of

Eighteen common bean (Phaseolus vulgaris L.) genotypes were evaluated in 25 environments of the state of São Paulo in 2001 and 2002. The estimation of genetic parameters by the Restricted Maximum Likelihood (REML) and the prediction of genotypic values via Best Linear Unbiased Prediction (BLUP) were obtained by software Selegen-REML/BLUP. The estimate of the broad-sense heritability was low for the grain yield (0.03), since it took individual plots into consideration and was free of the effects of interaction with years, cultivation periods and site. Nevertheless, the heritability at the level of line means across the various environments was high (0.75), allowing a high accuracy (0.87) in the selection of lines for planting in the environment mean. Among the 18 genotypes, the predicted genotypic values of nine were higher than the general mean. The genetic gain predicted with the selection of the best line, in this case line Gen 96A31 of the IAC, was 16.25%.

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