SELECTION OF SIRES ORIGINATING FROM A NUCLEUS BREEDING UNIT FOR USE IN A COMMERCIAL DAIRY POPULATION

Bulls that originate from breeding schemes with extensive use of multiple ovulation and embryo transfer (MOET) can be selected on pedigree information, the performance of their contemporary female full- and half-sibs or based on a progeny test. Combined selection across groups of bulls with different sources of information is shown to be superior to selection of progeny tested bulls alone. The magnitude of the superiority for a given selection rate is determined by the differences in genetic merit between the groups and ranges from 5 to 65%. Depending on the annual genetic progress the majority of the bulls are selected either on pedigree or progeny information. The proportion of sib-tested bulls ranges from 9 to 23%. When breeding activities are concentrated in nucleus herds, possible genotype by environment interactions between performance in the test herd and in the commercial population have to be considered. Genotype by environment interactions increase the proportion of progeny tested sires that will be selected. However, the proportion of progeny tested sires used is reduced by genotype by environment interactions among the groups of a heterogenous commercial production environment. Key words: Embryo transfer, sire selection, genotype-by-environment interactions

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

Canadian Journal of Plant Science ◽

10.4141/cjps2011-110 ◽

2012 ◽

Vol 92 (3) ◽

pp. 553-562 ◽

Cited By ~ 4

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.

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Selection of Genotypes and Prediction of Performance by Analysing Genotype-by-Environment Interactions

Genotype-by-Environment Interaction ◽

10.1201/9781420049374.ch13 ◽

1996 ◽

pp. 353-371 ◽

Cited By ~ 8

Author(s):

W Weber ◽

T Westermann ◽

G Wricke

Keyword(s):

Genotype By Environment Interactions ◽

Genotype By Environment ◽

Selection Of

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Use of genomic information to exploit genotype-by-environment interactions for body weight of broiler chicken in bio-secure and production environments

Genetics Selection Evolution ◽

10.1186/s12711-019-0493-3 ◽

2019 ◽

Vol 51 (1) ◽

Cited By ~ 1

Author(s):

Thinh T. Chu ◽

John W. M. Bastiaansen ◽

Peer Berg ◽

Hélène Romé ◽

Danye Marois ◽

...

Keyword(s):

Body Weight ◽

Genetic Correlations ◽

Single Step ◽

Pedigree Information ◽

Genomic Information ◽

Genotype By Environment Interactions ◽

Genotype By Environment ◽

Increase In Accuracy ◽

Close Relatives ◽

Estimate Variance

Abstract Background The increase in accuracy of prediction by using genomic information has been well-documented. However, benefits of the use of genomic information and methodology for genetic evaluations are missing when genotype-by-environment interactions (G × E) exist between bio-secure breeding (B) environments and commercial production (C) environments. In this study, we explored (1) G × E interactions for broiler body weight (BW) at weeks 5 and 6, and (2) the benefits of using genomic information for prediction of BW traits when selection candidates were raised and tested in a B environment and close relatives were tested in a C environment. Methods A pedigree-based best linear unbiased prediction (BLUP) multivariate model was used to estimate variance components and predict breeding values (EBV) of BW traits at weeks 5 and 6 measured in B and C environments. A single-step genomic BLUP (ssGBLUP) model that combined pedigree and genomic information was used to predict EBV. Cross-validations were based on correlation, mean difference and regression slope statistics for EBV that were estimated from full and reduced datasets. These statistics are indicators of population accuracy, bias and dispersion of prediction for EBV of traits measured in B and C environments. Validation animals were genotyped and non-genotyped birds in the B environment only. Results Several indications of G × E interactions due to environmental differences were found for BW traits including significant re-ranking, heterogeneous variances and different heritabilities for BW measured in environments B and C. The genetic correlations between BW traits measured in environments B and C ranged from 0.48 to 0.54. The use of combined pedigree and genomic information increased population accuracy of EBV, and reduced bias of EBV prediction for genotyped birds compared to the use of pedigree information only. A slight increase in accuracy of EBV was also observed for non-genotyped birds, but the bias of EBV prediction increased for non-genotyped birds. Conclusions The G × E interaction was strong for BW traits of broilers measured in environments B and C. The use of combined pedigree and genomic information increased population accuracy of EBV substantially for genotyped birds in the B environment compared to the use of pedigree information only.

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Selection for larval growth in Tribolium under two levels of nutrition

Genetics Research ◽

10.1017/s0016672300002871 ◽

1969 ◽

Vol 13 (2) ◽

pp. 175-195 ◽

Cited By ~ 13

Author(s):

Yukio Yamada ◽

A. E. Bell

Keyword(s):

Larval Growth ◽

Direct Selection ◽

Larval Weight ◽

Genotype By Environment Interactions ◽

Genotype By Environment ◽

Physiological Limits ◽

Short Run ◽

Selection For ◽

Current Selection ◽

Selection Of

Selection for large and small 13-day larval weight in Tribolium castaneum was studied for sixteen generations in a replicated experiment to evaluate the effectiveness of various selection methods and the importance of genotype by environment interactions under two levels of nutrition.Direct selection responses generally were larger than correlated ones under both Good and Poor nutritional environments. However, contrary to theoretical expectations, those populations selected on average performance in both environments were not superior for this attribute.Asymmetrical responses were observed to be dependent on the environment of selection. When selection was based on performance in the optimal environment, the asymmetry was observed toward small size. This situation in the sub – optimal environment was completely reversed. This phenomenon was discussed in terms of physiological limits rather than gene frequency and directional dominance.It was proposed that selection of compound traits such as body weight at a fixed age may affect the component characters quite differently. As the latter are differentiated by direction and environment of selection, the compound trait may reflect parametric changes and enhanced genotype by environment interactions. Such changes hamper the precision of current selection theory for predicting response even in the short run.

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Spatial Representations as an Emergent Feature of Perceptual Processing

Journal of Psychophysiology ◽

10.1027/0269-8803/a000007 ◽

2010 ◽

Vol 24 (3) ◽

pp. 161-172 ◽

Cited By ~ 14

Author(s):

Edmund Wascher ◽

C. Beste

Keyword(s):

Common Ground ◽

Event Related Potentials ◽

Vertical Axis ◽

Relevant Information ◽

Sources Of Information ◽

Integrated Network ◽

Perceptual Maps ◽

Emergent Feature ◽

Related Potentials ◽

Selection Of

Spatial selection of relevant information has been proposed to reflect an emergent feature of stimulus processing within an integrated network of perceptual areas. Stimulus-based and intention-based sources of information might converge in a common stage when spatial maps are generated. This approach appears to be inconsistent with the assumption of distinct mechanisms for stimulus-driven and top-down controlled attention. In two experiments, the common ground of stimulus-driven and intention-based attention was tested by means of event-related potentials (ERPs) in the human EEG. In both experiments, the processing of a single transient was compared to the selection of a physically comparable stimulus among distractors. While single transients evoked a spatially sensitive N1, the extraction of relevant information out of a more complex display was reflected in an N2pc. The high similarity of the spatial portion of these two components (Experiment 1), and the replication of this finding for the vertical axis (Experiment 2) indicate that these two ERP components might both reflect the spatial representation of relevant information as derived from the organization of perceptual maps, just at different points in time.

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Evidence for a single mechanism gating perceptual and long-term memory information into working memory

10.31234/osf.io/3m7up ◽

2020 ◽

Author(s):

Sam Verschooren ◽

Yoav Kessler ◽

Tobias Egner

Keyword(s):

Working Memory ◽

Long Term Memory ◽

Sources Of Information ◽

Term Memory ◽

Source Selection ◽

Single Mechanism ◽

Gating Mechanism ◽

Opening And Closing ◽

Selection Of

An influential view of working memory (WM) holds that its’ contents are controlled by a selective gating mechanism that allows for relevant perceptual information to enter WM when opened, but shields WM contents from interference when closed. In support of this idea, prior studies using the reference-back paradigm have established behavioral costs for opening and closing the gate between perception and WM. WM also frequently requires input from long-term memory (LTM), but it is currently unknown whether a similar gate controls the selection of LTM representations into WM, and how WM gating of perceptual vs. LTM sources of information relate to each other. To address these key theoretical questions, we devised a novel version of the reference-back paradigm, where participants switched between gating perceptual and LTM information into WM. We observed clear evidence for gate opening and closing costs in both cases. Moreover, the pattern of costs associated with gating and source-switching indicated that perceptual and LTM information is gated into WM via a single gate, and rely on a shared source-selection mechanism. These findings extend current models of WM gating to encompass LTM information, and outline a new functional WM architecture.

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Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Animals ◽

10.3390/ani11030599 ◽

2021 ◽

Vol 11 (3) ◽

pp. 599

Author(s):

Miguel A. Gutierrez-Reinoso ◽

Pedro M. Aponte ◽

Manuel Garcia-Herreros

Keyword(s):

Dairy Cattle ◽

Production Efficiency ◽

Association Studies ◽

Phenotypic Traits ◽

Progeny Testing ◽

Genome Wide Association Studies ◽

Genetic Progress ◽

Breeding Programs ◽

Increased Risk ◽

Selection Of

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

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