The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values

It is widely known that the environment influences phenotypic expression and that its effects must be accounted for in genetic evaluation programs. The most used method to account for environmental effects is to add herd and contemporary group to the model. Although generally informative, the herd effect treats different farms as independent units. However, if two farms are located physically close to each other, they potentially share correlated environmental factors. We introduce a method to model herd effects that uses the physical distances between farms based on the Global Positioning System (GPS) coordinates as a proxy for the correlation matrix of these effects that aims to account for similarities and differences between farms due to environmental factors. A population of Hanwoo Korean cattle was used to evaluate the impact of modelling herd effects as correlated, in comparison to assuming the farms as completely independent units, on the variance components and genomic prediction. The main result was an increase in the reliabilities of the predicted genomic breeding values compared to reliabilities obtained with traditional models (across four traits evaluated, reliabilities of prediction presented increases that ranged from 0.05 ± 0.01 to 0.33 ± 0.03), suggesting that these models may overestimate heritabilities. Although little to no significant gain was obtained in phenotypic prediction, the increased reliability of the predicted genomic breeding values is of practical relevance for genetic evaluation programs.

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Effect of unfavourable population structure on estimates of heritability, systematic effects and breeding values

Archives Animal Breeding ◽

10.5194/aab-51-601-2008 ◽

2008 ◽

Vol 51 (6) ◽

pp. 601-610

Author(s):

A. P. Kominakis

Keyword(s):

Population Structure ◽

Mean Squared Error ◽

Heritability Estimate ◽

Breeding Values ◽

Parameter Estimations ◽

Squared Error ◽

Heritability Estimation ◽

Population Structures ◽

Systematic Effects ◽

The Impact

Abstract. Empirical estimations of heritability, systematic effects and predictions of sires’ breeding values (BVs) were obtained under various population structures for simulated populations consisted of n = 400 animals in 5 herds for a trait of medium heritability (h2 = 0.30). An infinitesimal additive genetic animal model was assumed while simulating data. Population structure was varied to allow for good and poor connectedness across herds and (non)random association between the genetic and the environmental effects. The impact of the various population structures on the parameter estimation(s) was assessed using Mean Squared Error (MSE) and Pearson’s correlations. Allowing sires to have progenies in more than one herd (good herd connectedness) and random use of sires across herds generally resulted in good parameter estimations. Poor connectedness significantly affected herd effects estimation and BV prediction but not heritability estimation as long as random usage of sires across environments was guaranteed. Selective use of the best sires in the best herds along with poor connectedness resulted in poorest estimations of all parameters examined. In the latter case, heritability was seriously underestimated (h2 = 0.06) while highest error, lowest accuracies for the BVs and a remarkable underestimation of the genetic gain were observed. Use of reference sires on a natural mating basis to create genetic links between herds has served a good solution for both heritability and BVs estimation under unfavorable structure. Mating 0.25 of the herd ewes with reference sires resulted in a heritability estimate close to the simulated one. Significantly better estimates of systematic effects and BVs were, however, obtained when 0.5 of the herd ewes were mated by reference sires.

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The Earth-Moon Connection

Zeitschrift für Naturforschung A ◽

10.1515/zna-1989-1004 ◽

1989 ◽

Vol 44 (10) ◽

pp. 891-923 ◽

Cited By ~ 2

Author(s):

A. E. Ringwood

Keyword(s):

Genetic Relationship ◽

The Moon ◽

Core Formation ◽

Earth’S Mantle ◽

Terrestrial Atmosphere ◽

The Earth ◽

Wide Range ◽

Siderophile Elements ◽

The Impact ◽

Close Genetic Relationship

Abstract The early thermal state of the Earth provides important constraints on hypotheses relating to its origin and its connection with the Moon. The currently popular giant impact hypothesis of lunar origin requires the Earth’s mantle to have been completely melted during the impact. Differentiation of a molten mantle would have produced strong chemical and mineralogical stratification, causing the mantle to become gravitationally stable and resistant to convective rehomogenization. The resulting composition and mineralogy of the upper mantle and primitive crust would have been dramatically different from those which have existed during the past 3.8 b. y. It is concluded that the Earth’s mantle was not extensively melted at the conclusion of accretion of the planet and therefore the hypothesis that the Moon was formed by the impact of a martian-sized planetesimal on the proto-Earth is probably incorrect. Nevertheless, a wide range of geochemical evidence demonstrates the existence of a close genetic relationship between the Moon and the Earth’s mantle. The key evidence relates to the processes of core formation in planetary bodies and resultant abundance patterns of siderophile elements which remain in their silicate mantles. Because of the complexity of the core formation process within a given body and the multiplicity of chemical and physical processes involved, the mantle siderophile signature is expected to be a unique characteristic. Thus, the siderophile signatures of Mars and of the eucrite parent body are quite distinct from that of the Earth’s mantle. Lunar siderophile geochemistry is reviewed in detail. It is demonstrated that a large group of siderophile elements display similar abundances in the terrestrial and lunar mantles. The similarity implies that a major proportion of the material now in the Moon was derived from the Earth’s mantle after core formation. This implication, however, does not require that the bulk compositions of the lunar and terrestrial mantles should be essentially identical, as is often assumed. Factors which may contribute to significant compositional differences between the two bodies within the context of a close genetic relationship are reviewed. The most promising mechanism for removing terrestrial material from the Earth’s mantle arises from the impacts of a number of large (0.001 to 0.01 ME) but not giant (≥ 0.1 ME) planetesimals after core formation and at the terminal stage of the Earth’s accretion. These impacts evaporated several times their own masses of mantle material and shock-melted considerably more. However, they did not lead to complete or extensive (e.g. > 50%) melting of the entire mantle. Impact-generated clouds of shock-melted spray and vapours were accelerated to high velocities in the presence of a primitive terrestrial atmosphere that co-rotated with the Earth. This provided an effective means of transferring angular momentum from the Earth to the ejected material which condensed to form a ring of Earth-orbiting planetesimals and moonlets. The Moon was formed by coagulation from material derived from the outer regions of this ring. Accretion of the Earth in the presence of the gases of the solar nebula and the co-rotating primitive terrestrial atmosphere may also have provided a mechanism for generating the rapid prograde spin of the proto-Earth.

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Impact of liveweight, fat and muscle sire breeding values on ewe reproduction is minimal but variable across Australian grazing systems

Animal Production Science ◽

10.1071/an15574 ◽

2017 ◽

Vol 57 (9) ◽

pp. 1952 ◽

Cited By ~ 1

Author(s):

S. F. Walkom ◽

D. J. Brown

Keyword(s):

Body Condition ◽

Reproductive Performance ◽

Breeding Value ◽

Production Cycle ◽

Eye Muscle ◽

Breeding Values ◽

Reproduction Traits ◽

Reproductive Rates ◽

Supplementary Feed ◽

The Impact

Australian sheep producers have the potential to improve reproductive rates through optimising ewe body condition across the production cycle. Managing ewe body condition can become costly when supplementary feeding is required due to poor pasture growth or rainfall and by using appropriate genetics, producers can theoretically reduce the flock’s dependency on supplementary feed and improve reproductive rates. Reproductive records from the Information Nucleus Flock and Sheep Genetics Merino and maternal breed datasets were analysed to examine the influence of sire breeding values for liveweight (post-weaning, yearling and adult assessments), fat and eye muscle depths (post-weaning and yearling assessments) and number of lambs weaned on reproductive performance (fertility, litter size and number of lambs born) across a variety of production environments. To determine the impact of environmental conditions on the relationship between weight, ultrasound body composition, and reproduction traits the daughters’ adjusted reproductive performances were regressed on the sire’s breeding value across flocks, within flocks and within flock × year. Irrespective of age at assessment, sire breeding values for liveweight, fat and eye muscle depths had very little association with the reproductive performance of their daughters, on average. The regressions of reproduction on weight, and fat and eye muscle depth traits varied across flocks from unfavourable to favourable estimates. The very small overall impact of weight, and fat and eye muscle depth traits, on average suggests that using sire breeding values for number of lambs weaned, which had a large impact on reproduction, will provide the most viable method to genetically improve reproductive performance within the production system in question.

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Quantitative traits under selection: derivations of distributions, higher moments, and the effects of recombination

10.1101/2021.07.30.454547 ◽

2021 ◽

Author(s):

Reginald D Smith

Keyword(s):

Quantitative Traits ◽

Exact Formula ◽

Breeding Value ◽

Breeding Values ◽

Mean And Variance ◽

The Mean ◽

The Impact ◽

First Four Moments ◽

First Time ◽

Fertile Area

The mathematical theory of quantitative traits is over one hundred years old but it is still a fertile area for research and analysis. However, the effects of selection on a quantitative trait, while well understood for the effects on the mean and variance, have traditionally been difficult to attack from the perspective of analyzing the probability density of the breeding values and deriving higher (third and fourth) moments as well as analyzing the impact of recombination. In this paper, the exact formula for the breeding value distribution after selection is derived and, using new integral tables, the first four moments are given exact expressions for the first time. In addition, the effects of recombination on the full distribution of breeding values are demonstrated. Finally, the changes of GXE covariance in the selected parent population caused by factors similar to the Bulmer Effect are also investigated in detail.

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61 The impact of selective phenotyping and genotyping over generations in beef cattle

Journal of Animal Science ◽

10.1093/jas/skz122.068 ◽

2019 ◽

Vol 97 (Supplement_2) ◽

pp. 37-39

Author(s):

Andrea Plotzki Reis ◽

Rodrigo Fagundes da Costa ◽

Fabyano Fonseca e Silva ◽

Fernando Flores Cardoso ◽

Matthew L Spangler

Keyword(s):

Beef Cattle ◽

Prediction Accuracy ◽

Cost Benefit ◽

Single Step ◽

Breeding Values ◽

Additional Information ◽

Economic Framework ◽

Estimated Breeding Values ◽

The Cost ◽

The Impact

Abstract The aim of this study was to investigate selective phenotyping to maintain adequate prediction accuracy. A simulation was conducted, with 10 replicates, using QMSim to mimic the structure and size of a Braford population. A population with 50 generations, 500 animals per generation, was created with phenotyping and genotyping beginning in generation 11. The scenarios investigated were: 1) Randomly phenotype and genotype 10, 25, 50, 75, and 100% of individuals each generation and; 2) Randomly phenotype and genotype 10, 25, 50, 75, and 100% of individuals in every-other generation. Estimated breeding values (EBV) were obtained using single-step GBLUP and accuracy was determined as the correlation between true BV from simulation and those estimated from the blupf90 family of programs. For scenarios where phenotyping and genotyping occurred every generation, EBV accuracies in generation 11 and 50 ranged from 0.32 to 0.32, 0.42 to 0.43, 0.49 to 0.51, 0.53 to 0.56 and 0.57 to 0.59 when 10, 25, 50, 75, and 100% of animals were chosen, respectively. The highest accuracies were 0.40 and 0.50 in generation 38 for scenarios 10 and 25%; 0.56, 0.61 and 0.64 in generation 40 for scenarios 50, 75 and 100%, respectively. When animals were selected every-other generation, EBV accuracy in generation 11 and 50 ranged from 0.24 to 0.26, 0.36 to 0.36, 0.43 to 0.42, 0.48 to 0.44 and 0.53 to 0.48 for 10, 25, 50, 75 and 100% of selected animals, respectively. The highest accuracies were in generation 23 for scenario 10% (0.31), in generation 37 for scenarios 25 (0.43), 50 (0.50) and 75% (0.55) and in generation 39 for 100% (0.59). Although increasing the density of phenotyped and genotyped animals increased prediction accuracy, some gains were marginal. These differences in accuracy must be contemplated in an economic framework to determine the cost-benefit of additional information.

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PSXV-1 Genetic evaluation of longevity of cows culled due to fertility-related problems using random regression models and censored data

Journal of Animal Science ◽

10.1093/jas/skab235.477 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 261-261

Author(s):

Hinayah R Oliveira ◽

Stephen P Miller ◽

Luiz F Brito ◽

Flavio S Schenkel

Keyword(s):

Censored Data ◽

Regression Models ◽

Genetic Evaluation ◽

Random Regression ◽

Breeding Values ◽

Structural Problems ◽

Time Period ◽

And Performance ◽

Genetic Evaluations ◽

The Impact

Abstract A recent study showed that longevity based on different culling reasons should be considered as different traits in genetic evaluations. However, it is still necessary to create a pipeline that avoid including/excluding animals culled for different reasons in every genetic evaluation run. This study aimed to: 1) perform a genetic evaluation of the longevity of cows culled due to fertility-related problems including records of animals culled for other reasons (i.e., age, structural problems, disease, and performance) as censored records; and, 2) identify the impact of censored data in the genetic parameters and breeding values estimated. Two longevity indicators were evaluated: traditional (TL; time from first calving to culling) and functional (FL; time period in which the cow was alive and also calving after its first calving) longevity. Both TL and FL were evaluated from 2 to 15 years-old, and codified as binary traits for each age (0 = culled and 1 = alive/calved). Both trait definitions were analyzed using a Bayesian random regression linear model. Animals culled for reasons other than fertility were either excluded from the data (standard) or had their records censored after the culling date reported in the dataset (censored). After the quality control, 154,419 and 450,124 animals had uncensored and censored records, respectively. Heritabilities estimated for TL over the ages ranged from 0.02 to 0.13 for standard, and from 0.01 to 0.12 for censored datasets. Heritabilities estimated for FL ranged from 0.01 to 0.14 (standard), and from 0.01 to 0.13 (censored). Average (SD) correlation of breeding values predicted over all ages, using the standard and censored datasets, was 0.77 (0.16) for TL, and 0.83 (0.11) for FL. Our findings suggest that including censored data in the analyses might impact the genomic evaluations and further work is need to determine the optimal predictive approach.

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Understanding the plant-pathogen interaction associated with Septoria nodorum blotch of wheat

10.19103/as.2021.0092.14 ◽

2021 ◽

pp. 359-392

Author(s):

Gayan K. Kariyawasam ◽

◽

Timothy L. Friesen ◽

Keyword(s):

Genome Sequencing ◽

Genetic Relationship ◽

Plant Pathogen ◽

Gene Interactions ◽

Septoria Nodorum ◽

Septoria Nodorum Blotch ◽

Plant Pathogen Interaction ◽

Necrotrophic Effector ◽

The Impact ◽

Sensitivity Gene

This chapter discusses understanding the plant-pathogen interaction associated with septorium nodorum blotch of wheat. It begins by reviewing the necrotrophic effector-host sensitivity gene interactions in the wheat-P. nodorum system. It then reviews the genetic relationship between NE-sensitivity gene interactions and the importance of these interactions in the field. Additional QTL associated with susceptibility/resistance to P. nodorum is also discussed, followed by a section on the impact of genome sequencing in characterizing NE-sensitivity gene interactions.

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