scholarly journals Comparison of International Dairy Sire Evaluations from Meta-Analysis of National Estimated Breeding Values and Direct Analysis of Individual Animal Performance Records

2004 ◽  
Vol 87 (8) ◽  
pp. 2599-2605 ◽  
Author(s):  
C. Maltecca ◽  
A. Bagnato ◽  
K.A. Weigel
Keyword(s):  
Meta Analysis ◽  
Direct Analysis ◽  
Individual Animal ◽  
Animal Performance ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Dairy Sire

scholarly journals Effective Use of Genomics in Commercial Dairy Farms

EDIS ◽  
2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Francisco Peñagaricano
Keyword(s):  
Cattle Breeding ◽  
Entire Genome ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Selection Decisions ◽  
Dairy Cattle Breeding ◽  
Estimated Breeding Values ◽  
Effective Use ◽  
Animal Sciences ◽  
Dairy Sire

Genomic selection refers to selection decisions based on genomic-estimated breeding values. These genomic breeding values are calculated using genetic markers across the entire genome. This technology has revolutionized dairy cattle breeding globally. This new 4-page fact sheet discusses the effects of genomics on dairy sire selection. Written by Francisco Peñagaricano, and published by the UF/IFAS Department of Animal Sciences, February 2018.  http://edis.ifas.ufl.edu/an340

scholarly journals A note on genetic parameters and accuracy of estimated breeding values in honey bees

2019 ◽  
Vol 51 (1) ◽  
Author(s):  
Evert W. Brascamp ◽  
Piter Bijma
Keyword(s):  
Honey Bees ◽  
Variance Components ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Breeding Value ◽  
Phenotypic Variance ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Additive Genetic Relationship ◽  
The Relationship

Abstract Background In honey bees, observations are usually made on colonies. The phenotype of a colony is affected by the average breeding value for the worker effect of the thousands of workers in the colony (the worker group) and by the breeding value for the queen effect of the queen of the colony. Because the worker group consists of multiple individuals, interpretation of the variance components and heritabilities of phenotypes observed on the colony and of the accuracy of selection is not straightforward. The additive genetic variance among worker groups depends on the additive genetic relationship between the drone-producing queens (DPQ) that produce the drones that mate with the queen. Results Here, we clarify how the relatedness between DPQ affects phenotypic variance, heritability and accuracy of the estimated breeding values of replacement queens. Second, we use simulation to investigate the effect of assumptions about the relatedness between DPQ in the base population on estimates of genetic parameters. Relatedness between DPQ in the base generation may differ considerably between populations because of their history. Conclusions Our results show that estimates of (co)variance components and derived genetic parameters were seriously biased (25% too high or too low) when assumptions on the relationship between DPQ in the statistical analysis did not agree with reality.

scholarly journals Relationships of a Detailed Mineral Profile of Meat with Animal Performance and Beef Quality

2019 ◽  
Author(s):  
Nageshvar Patel ◽  
Matteo Bergamaschi ◽  
Luciano Magro ◽  
Andrea Petrini ◽  
Giovanni Bittante
Keyword(s):  
Meat Quality ◽  
Quality Traits ◽  
Meat Color ◽  
Individual Animal ◽  
Animal Performance ◽  
Latent Factors ◽  
Mineral Contents ◽  
Meat Quality Traits ◽  
Mineral Profile ◽  
Color Traits

Mineral profile of beef interests human health, but also animal performance and meat quality. This study analyzes the relationships of 20 minerals in beef (ICP-OES) with 3 animal performance and 13 meat quality traits analyzed on 182 samples of Longissimus thoracis. Animals’ breed and sex showed limited effects. The major sources of variation (farm/date of slaughter, individual animal within group and side/sample within animal) differed greatly from trait to trait. Mineral contents were correlated to animal performance and meat quality being significant 52 out of the 320 correlations at the farm/date level, and 101 out of the 320 at the individual animal level. Five latent factors explained 69% of mineral co-variation. The most important, “Mineral quantity” factor correlated with age at slaughter and with the meat color traits. Two latent factors (“Na+Fe+Cu” and “Fe+Mn”) correlated with performance and meat color traits. Two other (“K-B-Pb” and “Zn”) correlated with meat chemical composition and the latter also with carcass weight and daily gain, and meat color traits. Meat cooking losses correlated with “K-B-Pb”. Latent factor analysis appears be a useful means of disentangling the very complex relationships that the minerals in meat have with animal performance and meat quality traits.

scholarly journals Prediction of breeding values for group-recorded traits including genomic information and an individually recorded correlated trait

Heredity ◽  
2020 ◽  
Vol 126 (1) ◽  
pp. 206-217
Author(s):  
Xiang Ma ◽  
Ole F. Christensen ◽  
Hongding Gao ◽  
Ruihua Huang ◽  
Bjarne Nielsen ◽  
...  
Keyword(s):  
Egg Production ◽  
Quantitative Traits ◽  
Group Structure ◽  
Genetic Evaluation ◽  
Genomic Information ◽  
Bivariate Model ◽  
Breeding Values ◽  
Lower Accuracy ◽  
Small Group Size ◽  
Estimated Breeding Values

AbstractRecords on groups of individuals could be valuable for predicting breeding values when a trait is difficult or costly to measure on single individuals, such as feed intake and egg production. Adding genomic information has shown improvement in the accuracy of genetic evaluation of quantitative traits with individual records. Here, we investigated the value of genomic information for traits with group records. Besides, we investigated the improvement in accuracy of genetic evaluation for group-recorded traits when including information on a correlated trait with individual records. The study was based on a simulated pig population, including three scenarios of group structure and size. The results showed that both the genomic information and a correlated trait increased the accuracy of estimated breeding values (EBVs) for traits with group records. The accuracies of EBV obtained from group records with a size 24 were much lower than those with a size 12. Random assignment of animals to pens led to lower accuracy due to the weaker relationship between individuals within each group. It suggests that group records are valuable for genetic evaluation of a trait that is difficult to record on individuals, and the accuracy of genetic evaluation can be considerably increased using genomic information. Moreover, the genetic evaluation for a trait with group records can be greatly improved using a bivariate model, including correlated traits that are recorded individually. For efficient use of group records in genetic evaluation, relatively small group size and close relationships between individuals within one group are recommended.

scholarly journals Genomic Analysis Using Bayesian Methods under Different Genotyping Platforms in Korean Duroc Pigs

Animals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 752 ◽  
Author(s):  
Jungjae Lee ◽  
Yongmin Kim ◽  
Eunseok Cho ◽  
Kyuho Cho ◽  
Soojin Sa ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Genome Wide Association Study ◽  
Genomic Analysis ◽  
Snp Markers ◽  
Snp Genotyping ◽  
Muscle Area ◽  
Bayesian Approaches ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Response Variables

Genomic evaluation has been widely applied to several species using commercial single nucleotide polymorphism (SNP) genotyping platforms. This study investigated the informative genomic regions and the efficiency of genomic prediction by using two Bayesian approaches (BayesB and BayesC) under two moderate-density SNP genotyping panels in Korean Duroc pigs. Growth and production records of 1026 individuals were genotyped using two medium-density, SNP genotyping platforms: Illumina60K and GeneSeek80K. These platforms consisted of 61,565 and 68,528 SNP markers, respectively. The deregressed estimated breeding values (DEBVs) derived from estimated breeding values (EBVs) and their reliabilities were taken as response variables. Two Bayesian approaches were implemented to perform the genome-wide association study (GWAS) and genomic prediction. Multiple significant regions for days to 90 kg (DAYS), lean muscle area (LMA), and lean percent (PCL) were detected. The most significant SNP marker, located near the MC4R gene, was detected using GeneSeek80K. Accuracy of genomic predictions was higher using the GeneSeek80K SNP panel for DAYS (Δ2%) and LMA (Δ2–3%) with two response variables, with no gains in accuracy by the Bayesian approaches in four growth and production-related traits. Genomic prediction is best derived from DEBVs including parental information as a response variable between two DEBVs regardless of the genotyping platform and the Bayesian method for genomic prediction accuracy in Korean Duroc pig breeding.

scholarly journals Integration of external estimated breeding values and associated reliabilities using correlations among traits and effects

2015 ◽  
Vol 98 (12) ◽  
pp. 9044-9050 ◽  
Author(s):  
J. Vandenplas ◽  
F.G. Colinet ◽  
G. Glorieux ◽  
C. Bertozzi ◽  
N. Gengler
Keyword(s):  
Breeding Values ◽  
Estimated Breeding Values

Practical aspects of a genetic evaluation system using parentage assigned from genetic markers

2005 ◽  
Vol 45 (8) ◽  
pp. 935 ◽  
Author(s):  
K. G. Dodds ◽  
J. A. Sise ◽  
M. L. Tate
Keyword(s):  
Genetic Markers ◽  
Evaluation System ◽  
Fixed Effects ◽  
Genetic Evaluation ◽  
Diagnostic Systems ◽  
Breeding Values ◽  
Mating Group ◽  
Animal Management ◽  
The Mean ◽  
Estimated Breeding Values

Animal breeding values can be calculated when genetic markers have been used to help determine the parentage of some of the animals, but their parentage has been incompletely determined. The pedigree sampling method is 1 computing strategy for calculating these breeding values. This paper describes and discusses methods for dealing with a number of practical issues that arise when implementing such a system for industry use. In particular, diagnostic systems for detecting inadequacies or possible errors in the genotyping systems and the recording of animal management are developed. Also, characteristics of the best assigned pedigrees are calculated according to mating group and used to check for sires missing from these groups. The correlation between breeding values estimated from a single sampled pedigree (using parentage probabilities) and those estimated as the mean from many sampled pedigrees gives a diagnostic to indicate which estimated breeding values are more influenced by uncertainties in relationships. For the analysis of survival traits, a method to enumerate and assign likely parentage to dead offspring which have not been DNA sampled and genotyped is described. When embryo transfer technology is used, the genetic dam needs to be included as a possible dam when considering parentage. If some fixed effects which depend on the parent are missing, these can be sampled similarly to parentage, and this may improve the evaluation if certain assumptions are met. A method to provide a likely list of parents, the ‘fitted pedigree’, which is based on the most likely parents, but modified to reduce the occurrence of unlikely family sets (e.g. very large litters) is also presented. The use of these methods will enhance the practical application of DNA parenting when used in conjunction with genetic evaluation.

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