Competition effects in breeding value prediction of forest trees

2020 ◽  
Author(s):  
Gunnar Jansson ◽  
Richard Kerr ◽  
Gregory Dutkowski ◽  
Johan Kroon
Keyword(s):  
Indirect Effects ◽  
Genetic Parameter ◽  
Genetic Effect ◽  
Tree Breeding ◽  
Breeding Value ◽  
Additive Genetic Effect ◽  
Analytic Structure ◽  
Additive Variance ◽  
Value Prediction ◽  
Genetic Level

Competition is a concern to tree breeding because of its potential to reduce the genetic gain. Competition, if not accounted for in the analytical model, can potentially introduce a source of bias in genetic parameter estimation and breeding value prediction. This study modelled competition between trees in 20 Swedish progeny trials of Norway spruce, Scots pine and lodgepole pine. The competition model assumed a tree has a direct additive genetic effect, which affects the tree’s own phenotype, and an indirect additive effect, which affects the phenotypes of its neighbours. Genetic parameters were estimated via a factor analytic structure (FA) where separate indirect effects were considered for each neighbour, or via a combined indirect effect approach (CIE). We analysed diameter, as it is the trait that can be expected to be affected most by competition. Competition at the genetic level was detected in 17 of the 20 trials analysed. In most cases the ratio of indirect to direct additive variance was less than five percent and no major changes in ranking resulted. At this stage there is little incentive to incorporate indirect effects into program-wide genetic evaluation models. The added complexity is not commensurate with the benefit that would be gained.

Potential biases of incomplete linear models in heritability estimation and breeding value prediction

1999 ◽  
Vol 29 (6) ◽  
pp. 724-736 ◽  
Author(s):  
P X Lu ◽  
D A Huber ◽  
T L White
Keyword(s):  
Genetic Variance ◽  
Linear Models ◽  
Additive Genetic Variance ◽  
Genetic Effect ◽  
Breeding Value ◽  
Additive Genetic Effect ◽  
Unbalanced Data ◽  
Breeding Values ◽  
Incomplete Model ◽  
Heritability Estimation

Potential biases associated with incomplete linear models in the estimation of heritability and the prediction of breeding values have been investigated. Results indicate that estimates of additive genetic variance and heritability as well as predicted parental breeding values from incomplete models will inevitably be biased as long as the true variance components of ignored effects are not zero. While models ignoring the interaction effect of males and females (SCA) × environment (E) interaction downwardly biased the estimates of additive genetic variance and heritability, models ignoring SCA and (or) the additive genetic effect (GCA) × E interaction yielded upward biases. The magnitudes of biases are functions of population genetic architecture, mating design, and field experimental design and can be precisely assessed with formulae derived for balanced data. Numerical simulations using unbalanced data of different mating and field experimental designs suggest that the formulae from balanced data can be used to approximate the minimum biases associated with unbalanced data. Because of the magnitudes of biases for some typical forest genetic scenarios, it is suggested that models ignoring SCA and (or) GCA × E should be avoided when the numbers of test sites and crosses per parent are small. However, incomplete model ignoring SCA × E interaction may be used to reduce computational demand with only negligible consequences.

Combining the genetic and clonal responses in a closed dairy cattle nucleus scheme

1994 ◽  
Vol 59 (3) ◽  
pp. 345-358 ◽  
Author(s):  
I. J. M. de Boer ◽  
T. H. E. Meuwissen ◽  
J. A. M. van Arendonk
Keyword(s):  
Gene Action ◽  
Clonal Selection ◽  
Dominant Gene ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Genetic Response ◽  
Reference Design ◽  
Female Genotype ◽  
Additive Gene ◽  
Genetic Level

AbstractDesigns testing clones in a closed nucleus, in which 1024 cows are tested each year, were compared for their additive genetic response to selection (genetic response) and their genetic superiority of female genotype(s) selected for commercial cloning (clonal response), using stochastic simulation. Clones were tested at the expense of dam or sire families, matings per dam (sire), or full-sibs per family. The reference design maximized the genetic response corrected for inbreeding in the absence of cloning. The trait considered was overall economic merit for milk production, which was simulated assuming an approximate infinitesimal model with both additive and dominant gene action. Bulls and cows eligible for breeding were selected on their animal model estimated additive genetic effect at either 15 or 27 months of age. Female genotypes eligible for commercial cloning were selected on their estimated total genetic effect at 27 months of age. All (fe)male full-sibs were available for selection. With only additive gene action, testing clones at the expense of sire families, matings per dam or full-sibs per family reduced genetic response, while it increased clonal response and inbreeding. Testing clones at the expense of dam families, however, added to both the genetic and clonal response without increasing inbreeding. When eight clones were tested at the expense of dam families, the genetic response and the final genetic level of commercially available cloned embryos were maximal. Accuracy of clonal selection equalled 0·83. With dominant gene action, however, testing two clones at the expense of dam families maximized the final genetic level of cloned embryos, irrespective of the level of inbreeding depression (accuracy of 0·72). Reliable commercial clone lines can be produced now and in future generations by testing clones at the expense of dam families.

scholarly journals Genetic evaluations of traits recorded in British young horse tests

2011 ◽  
Vol 54 (5) ◽  
pp. 439-455
Author(s):  
I. D. Stewart ◽  
J. A. Woolliams ◽  
S. Brotherstone
Keyword(s):  
Variance Components ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Breeding Value ◽  
Value Prediction ◽  
Data Source ◽  
The Uk ◽  
Genetic Evaluations ◽  
Show Jumping ◽  
Prediction Evaluation

Abstract. Tests for young sport horses were recently introduced in Great Britain. This study characterises the young horse data, examines their suitability for genetic analysis and estimates the genetic parameters needed for breeding value prediction. Evaluation data from 2006–2009 were used. This included 1 887 evaluations of 1 323 horses, which were evaluated for competing in dressage, show jumping, eventing, endurance or as sport ponies. Traits assessed were conformation, correctness of paces, type and temperament, athleticism and veterinary. The distributions of traits were examined and correlations of traits between disciplines, for the effect of the horse, were estimated. These indicated that traits could be assumed to be genetically identical across disciplines. Variance components were estimated for each of the 5 traits, using an animal model, where random effects were the genetic effect of the horse and the permanent environment of the horse. Bivariate analyses were performed between pairs of traits. Mean scores for each trait in each discipline were between 8.02 and 8.24, and standard deviations were between 0.54 and 0.83. Heritabilities ranged between 20.3 % for athleticism and 42.2 % for type and temperament. The variance due to the horse’s permanent environment ranged from approximately 25 % for correctness of paces and athleticism to 51.6 % for veterinary. The genetic correlations between traits were generally high. The young horse tests (»Futurity«) recently introduced in the UK are a valuable data source for genetic evaluations. The most appropriate measure will be to combine young horse data with adult competition data to routinely estimate breeding values.

scholarly journals Inheritance of soybean resistance to Corynespora cassiicola

2020 ◽  
Vol 46 (2) ◽  
pp. 85-91
Author(s):  
Rafael Moreira Soares ◽  
Carlos Alberto Arrabal Arias
Keyword(s):  
Continuous Distribution ◽  
Genetic Effect ◽  
Lesion Size ◽  
Genetic Models ◽  
Additive Genetic Effect ◽  
Corynespora Cassiicola ◽  
Additive Variance ◽  
Target Spot ◽  
Soybean Resistance ◽  
Soybean Diseases

ABSTRACT The incidence of target spot, caused by Corynespora cassiicola, has gained increasing importance among the main soybean diseases in Brazil, and using susceptible cultivars can cause yield losses. Different susceptibility/resistance levels have been observed among cultivars in commercial crops but the genetics of the resistance to this pathogen is still unknown. To study the inheritance of soybean resistance to C. cassiicola, crosses were developed between cultivars including one cultivar resistant to target spot, BRS 316RR, one moderately resistant cultivar, BRS 184, and one susceptible cultivar BMX Potência RR. Parental generations, as well as F2 and F2:3 derived from their crosses, were evaluated as to severity and lesion size after inoculation with the pathogen. Quantitative analysis was applied to the data, and genetic models were adjusted for means and variances. Predominance of additive genetic effects controlling soybean resistance to C. cassiicola is suggested for the different crosses. The genetic models adjusted for the means detected an additive genetic effect more frequently. The additive variance D was detected only for the trait lesion size and had low heritability, indicating high environmental effect influencing the reaction. Based on mean and variance genetic models, further genetic gains are expected in the cross BRS 316RR x BMX Potência RR. The effect of genetic dominance was not important. The presence of significant epistasis in crosses between susceptible cultivars indicates the existence of at least two genes affecting resistance and that are interacting. The normal continuous distribution of the frequency of the number of individuals in different classes of resistance indicates that the resistance to C. cassiicola is quantitatively inherited and there is predominance of an additive genetic effect and low heritability.

scholarly journals Development of optimal genetic evaluations for teat and udder structure in Canadian Angus cattle

2019 ◽  
Vol 97 (11) ◽  
pp. 4445-4452 ◽  
Author(s):  
Kajal Devani ◽  
Tiago S Valente ◽  
John J Crowley ◽  
Karin Orsel
Keyword(s):  
Fixed Effects ◽  
Genetic Effect ◽  
Information Criteria ◽  
Breeding Value ◽  
Additive Genetic Effect ◽  
Multiple Trait ◽  
Angus Cattle ◽  
Genotypic Correlations ◽  
Genetic Evaluations ◽  
The Impact

Abstract Despite their heritability and influence on female productivity, there are currently no genetic evaluations for teat and udder structure in Canadian Angus cattle. The objective of this study was to develop optimal genetic evaluations for these traits in the Canadian Angus population. Guidelines recommended by Beef Improvement Federation (BIF) were used to score teat and udder structure in 1,735 Canadian Angus cows from 10 representative herds. Cows scored ranged in parity from 1 to 13; however, >70% of cows were parity ≤4. Scores ranged from 1 (large, bottle shaped) to 9 (very small) for teats and from 1 (very pendulous) to 9 (very tight) for udders. Consistent with parity distribution, >70% of teat and udder scores were ≥6. Teat and udder scores (TS9 and US9, respectively) were modeled using a multiple trait animal model with random effects of contemporary group (herd-year-season) and additive genetic effect, and fixed effects of breed, parity group, and days between calving and scoring. To test good versus poor structure, a binary classification of 1 or 2 (TS2, US2) [comprised of scores 1 to 5 = 1 (poor structure) and scores 6 to 9 = 2 (good structure)] was created. Further, to assess the impact of grouping less frequently observed poor scores, a 1 to 7 scale (TS7, US7) was created by combining teat and udder scores 1 to 3. Analyses for teat and udder scores on scales TS9, US9, TS7, US7, and TS2, US2 were compared. In addition, both threshold and linear animal models were used to estimate variance components for the traits. Data treatment and models were evaluated based on correlation of resulting estimated breeding value (EBV) with corrected phenotypes, Spearman’s rank correlation coefficient, average EBV accuracies (r), and deviance information criteria (DIC). TS9, US9 scales for teat and udder scores and linear models performed best. Estimates of heritability (SE) for teat and udder score were 0.32 (0.06) and 0.15 (0.04), respectively, indicating these traits were moderately heritable and that genetic improvement for teat and udder scores was possible. Estimates of phenotypic and genotypic correlations for teat and udder score were 0.46 (0.02) and 0.71 (0.09), respectively. Estimates of genotypic correlations with birth weight (BW), weaning weight (WW), and yearling weight (YW), ranged from −0.04 (0.10) to −0.20 (0.12), verifying the importance of selecting for improved teat and udder score as individual traits, alongside performance traits.

scholarly journals Estimation of Genetic Parameters of Type Traits in First Parity Cows of the Autochthonous Cika Cattle in Slovenia

2021 ◽  
Vol 12 ◽  
Author(s):  
Mojca Simčič ◽  
Barbara Luštrek ◽  
Miran Štepec ◽  
Betka Logar ◽  
Klemen Potočnik
Keyword(s):  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Breeding Value ◽  
Additive Genetic Effect ◽  
Body Frame ◽  
Herd Effect ◽  
Long Time ◽  
Type Traits

The aim of this study was to estimate genetic parameters of 26 individual and four composite type traits in first parity Cika cows. An analysis of variance was performed with the generalized linear model procedure of the SAS/STAT statistical package, where the fixed effects of year of recording, cow’s age at recording and days after calving as a linear regression were included in the model. The variance components for the direct additive genetic effect and the herd effect in all type traits were estimated using the REML method in the VCE-6 software package. The estimated heritabilities ranged from 0.42 to 0.67 for the measured body frame traits, from 0.36 to 0.80 for the scored autochthonous traits, from 0.11 to 0.61 for the scored body frame traits, and from 0.20 to 0.47 for the scored udder traits. The estimated heritabilities for the composite traits called “autochthonous characteristics”, “muscularity”, “body frame” and “udder” were 0.55, 0.19, 0.19, and 0.26, respectively. The estimated genetic correlations among the measured body frame traits were positive and high, while the majority of them among the scored body frame traits were low to moderate. The estimated proportions of variance explained by the herd effect for the composite traits “autochthonous characteristics,” “muscularity,” “body frame” and “udder” were 0.09, 0.28, 0.14, and 0.10, respectively. The estimated heritabilities for the type traits of first parity Cika cows were similar to those reported for other breeds where breeding values have been routinely predicted for a long time. All estimated genetic parameters are already used for breeding value prediction in the Cika cattle population.

scholarly journals Weighting genomic and genealogical information for genetic parameter estimation and breeding value prediction in tropical beef cattle

2018 ◽  
Vol 96 (2) ◽  
pp. 612-617 ◽  
Author(s):  
Fernanda S S Raidan ◽  
Laercio R Porto-Neto ◽  
Yutao Li ◽  
Sigrid A Lehnert ◽  
Antonio Reverter
Keyword(s):  
Parameter Estimation ◽  
Beef Cattle ◽  
Genetic Parameter ◽  
Breeding Value ◽  
Value Prediction ◽  
Genealogical Information

Personal Goals of Older Female Twins

2009 ◽  
Vol 14 (2) ◽  
pp. 160-167 ◽  
Author(s):  
Katariina Salmela-Aro ◽  
Sanna Read ◽  
Jari-Erik Nurmi ◽  
Markku Koskenvuo ◽  
Jaakko Kaprio ◽  
...  
Keyword(s):  
Physical Exercise ◽  
Independent Living ◽  
Environmental Effect ◽  
Close Relationships ◽  
Environmental Influence ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Personal Goals ◽  
Cultural Activities ◽  
The Individual

This study examined genetic and environmental influences on older women’s personal goals by using data from the Finnish Twin Study on Aging. The interview for the personal goals was completed by 67 monozygotic (MZ) pairs and 75 dizygotic (DZ) pairs. The tetrachoric correlations for personal goals related to health and functioning, close relationships, and independent living were higher in MZ than DZ twins, indicating possible genetic influence. The pattern of tetrachoric correlations for personal goals related to cultural activities, care of others, and physical exercise indicated environmental influence. For goals concerning health and functioning, independent living, and close relationships, additive genetic effect accounted for about half of the individual variation. The rest was the result of a unique environmental effect. Goals concerning physical exercise and care of others showed moderate common environmental effect, while the rest of the variance was the result of a unique environmental effect. Personal goals concerning cultural activities showed unique environmental effects only.

Impact of maternal genetic effect on genetic parameter estimation of production traits for Qinghai fine-wool sheep

2012 ◽  
Vol 34 (5) ◽  
pp. 584-590
Author(s):  
Peng-Yu WANG ◽  
Zha-Xi GUANQUE ◽  
Quan-Qing QI ◽  
Mao DE ◽  
Wen-Guang ZHANG ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Genetic Parameter ◽  
Genetic Effect ◽  
Production Traits ◽  
Maternal Genetic Effect

scholarly journals Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Akio Onogi ◽  
Toshio Watanabe ◽  
Atsushi Ogino ◽  
Kazuhito Kurogi ◽  
Kenji Togashi
Keyword(s):  
Population Size ◽  
Genomic Prediction ◽  
Variance Components ◽  
Variance Component ◽  
Predictive Accuracy ◽  
Genetic Effect ◽  
Genetic Effects ◽  
Additive Effects ◽  
Additive Variance ◽  
Additive Genetic Effects

Abstract Background Genomic prediction is now an essential technology for genetic improvement in animal and plant breeding. Whereas emphasis has been placed on predicting the breeding values, the prediction of non-additive genetic effects has also been of interest. In this study, we assessed the potential of genomic prediction using non-additive effects for phenotypic prediction in Japanese Black, a beef cattle breed. In addition, we examined the stability of variance component and genetic effect estimates against population size by subsampling with different sample sizes. Results Records of six carcass traits, namely, carcass weight, rib eye area, rib thickness, subcutaneous fat thickness, yield rate and beef marbling score, for 9850 animals were used for analyses. As the non-additive genetic effects, dominance, additive-by-additive, additive-by-dominance and dominance-by-dominance effects were considered. The covariance structures of these genetic effects were defined using genome-wide SNPs. Using single-trait animal models with different combinations of genetic effects, it was found that 12.6–19.5 % of phenotypic variance were occupied by the additive-by-additive variance, whereas little dominance variance was observed. In cross-validation, adding the additive-by-additive effects had little influence on predictive accuracy and bias. Subsampling analyses showed that estimation of the additive-by-additive effects was highly variable when phenotypes were not available. On the other hand, the estimates of the additive-by-additive variance components were less affected by reduction of the population size. Conclusions The six carcass traits of Japanese Black cattle showed moderate or relatively high levels of additive-by-additive variance components, although incorporating the additive-by-additive effects did not improve the predictive accuracy. Subsampling analysis suggested that estimation of the additive-by-additive effects was highly reliant on the phenotypic values of the animals to be estimated, as supported by low off-diagonal values of the relationship matrix. On the other hand, estimates of the additive-by-additive variance components were relatively stable against reduction of the population size compared with the estimates of the corresponding genetic effects.

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