The Accuracy of Marker-Assisted Selection for Quantitative Traits Within Populations in Linkage Equilibrium

Genetics ◽  
1998 ◽  
Vol 148 (3) ◽  
pp. 1367-1372 ◽  
Author(s):  
Louis Ollivier
Keyword(s):  
Quantitative Traits ◽  
Infinite Family ◽  
Best Linear Unbiased Prediction ◽  
Linkage Equilibrium ◽  
Linear Unbiased Prediction ◽  
Selection Scheme ◽  
Sib Families ◽  
Best Linear Unbiased ◽  
Selection For ◽  
Combined Selection

Abstract Using the concept of conditional coancestry, given observed markers, an explicit expression of the accuracy of marker-based selection is derived in situations of linkage equilibrium between markers and quantitative trait loci (QTL), for the general case of full-sib families nested within half-sib families. Such a selection scheme is rather inaccurate for moderate values of family sizes and QTL variance, and the accuracies predicted for linkage disequilibrium can never be reached. The result is used to predict the accuracy of marker-assisted combined selection (MACS) and is shown to agree with previous MACS results obtained by simulation of a best linear unbiased prediction animal model. Low gains in accuracy are generally to be expected compared to standard combined selection. The maximum gain, assuming infinite family size and all QTLs marked, is about 50%.

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.

scholarly journals Genetic evaluation and selection correlated response of growth traits in Japanese quail

2020 ◽  
Vol 50 (2) ◽  
pp. 325-333
Author(s):  
M.M. El-Attrouny ◽  
E.A. Manaa ◽  
S.I. Ramadan
Keyword(s):  
Growth Traits ◽  
Best Linear Unbiased Prediction ◽  
Correlated Response ◽  
Genetic Trend ◽  
Linear Unbiased Prediction ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Best Linear Unbiased ◽  
Selection For ◽  
Genetic Trends

Objectives of the current study were to i) investigate effects of selection for bodyweight at four weeks old on bodyweight (BW) and bodyweight gain (BWG) across four generations; ii) estimate correlated response to selection for BW and BWG at different ages; and iii) document best linear unbiased prediction (BLUP) of genetic trends for BW and BWG across four generations of selection. A total of 3540 chicks from 444 sires and 885 dams were used to estimate heritabilities, and genetic and phenotypic correlations for growth traits, including BW at 0, 2, 4, and 6 weeks, and BWG between 0 and 2, 2 and 4, 4 and 6, and 0 and 6 weeks. The selection effects, correlated responses and genetic trend for BW and BWG across generations were quantified by applying the animal model. Estimates of heritability for BW and BWG ranged from 0.22 to 0.42 and from 0.18 to 0.23, respectively. Ranges of genetic and phenotypic correlations for BW varied from 0.31 to 0.92 and 0.05 to 0.65, respectively. Moreover, estimates of genetic and phenotypic correlations for BWG at different ages were from 0.12 to 0.72 and 0.17 to 0.60, respectively. Bodyweight and BWG estimates after four generations of selection were significantly higher than those of the base generation. Moreover, contrasts of generation means were significant across the four generations. The genetic trends across the generations clarified that BLUP estimates for BW and BWG gradually increased with the advance of generations until the fourth generation. Keywords: best linear unbiased prediction, bodyweight, heritability, selection, genetic trend

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.

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.

COMPARISON OF SINGLE AND MULTIPLE TRAIT BEEF SIRE EVALUATIONS

1981 ◽  
Vol 61 (3) ◽  
pp. 565-573 ◽  
Author(s):  
L. R. SCHAEFFER ◽  
J. W. WILTON
Keyword(s):  
Absolute Magnitude ◽  
Best Linear Unbiased Prediction ◽  
Standard Errors ◽  
Multiple Trait ◽  
Linear Unbiased Prediction ◽  
Weaning Weight ◽  
Calving Ease ◽  
Best Linear Unbiased ◽  
Selection For ◽  
Prediction Techniques

Beef bulls of 13 breeds were evaluated from progeny records for calving ease, weaning weight and yearling weight using single and multiple trait best linear unbiased prediction techniques. Multiple trait procedures allowed more bulls to be evaluated for all traits and gave slightly greater variances to sire evaluations than the single trait method. The correlations of proofs between single and multiple trait methods were above 0.9 for the majority of the breeds for each trait, with the lowest correlations being between yearling weight proofs from the two methods. The correlations of proofs between traits within the multiple trait analysis were greater in absolute magnitude than within the single trait analyses. Multiple-trait procedures seem to be advantageous for lowering the standard errors of prediction for young bulls with their first proof, and for removing the effects of selection for weaning weight from the yearling weight proofs.

scholarly journals Correction: Weighted Genomic Best Linear Unbiased Prediction for Carcass Traits in Hanwoo Cattle. Genes 2019, 10, 1019

Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1013
Author(s):  
Bryan Irvine Lopez ◽  
Seung-Hwan Lee ◽  
Jong-Eun Park ◽  
Dong-Hyun Shin ◽  
Jae-Don Oh ◽  
...  
Keyword(s):  
Carcass Traits ◽  
Best Linear Unbiased Prediction ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Hanwoo Cattle ◽  
Unbiased Prediction

The authors wish to make the following corrections to this paper [...]

scholarly journals Genomic Prediction Using Alternative Strategies of Weighted Single-Step Genomic BLUP for Yearling Weight and Carcass Traits in Hanwoo Beef Cattle

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 266
Author(s):  
Hossein Mehrban ◽  
Masoumeh Naserkheil ◽  
Deuk Hwan Lee ◽  
Chungil Cho ◽  
Taejeong Choi ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Beef Cattle ◽  
Genomic Prediction ◽  
Quantitative Trait ◽  
Carcass Traits ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Linear Unbiased Prediction ◽  
Single Nucleotide ◽  
Best Linear Unbiased

The weighted single-step genomic best linear unbiased prediction (GBLUP) method has been proposed to exploit information from genotyped and non-genotyped relatives, allowing the use of weights for single-nucleotide polymorphism in the construction of the genomic relationship matrix. The purpose of this study was to investigate the accuracy of genetic prediction using the following single-trait best linear unbiased prediction methods in Hanwoo beef cattle: pedigree-based (PBLUP), un-weighted (ssGBLUP), and weighted (WssGBLUP) single-step genomic methods. We also assessed the impact of alternative single and window weighting methods according to their effects on the traits of interest. The data was comprised of 15,796 phenotypic records for yearling weight (YW) and 5622 records for carcass traits (backfat thickness: BFT, carcass weight: CW, eye muscle area: EMA, and marbling score: MS). Also, the genotypic data included 6616 animals for YW and 5134 for carcass traits on the 43,950 single-nucleotide polymorphisms. The ssGBLUP showed significant improvement in genomic prediction accuracy for carcass traits (71%) and yearling weight (99%) compared to the pedigree-based method. The window weighting procedures performed better than single SNP weighting for CW (11%), EMA (11%), MS (3%), and YW (6%), whereas no gain in accuracy was observed for BFT. Besides, the improvement in accuracy between window WssGBLUP and the un-weighted method was low for BFT and MS, while for CW, EMA, and YW resulted in a gain of 22%, 15%, and 20%, respectively, which indicates the presence of relevant quantitative trait loci for these traits. These findings indicate that WssGBLUP is an appropriate method for traits with a large quantitative trait loci effect.

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