scholarly journals Genetic improvement of hip-extended scores in 3 breeds of guide dogs using estimated breeding values: Notable progress but more improvement is needed

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0212544 ◽  
Author(s):  
Eldin A. Leighton ◽  
Dolores Holle ◽  
Darryl N. Biery ◽  
Thomas P. Gregor ◽  
Mischa B. McDonald-Lynch ◽  
...  
Keyword(s):  
Genetic Improvement ◽  
Breeding Values ◽  
Guide Dogs ◽  
Estimated Breeding Values

Relations between first and second lactation characters of progeny groups and effects of tandem selection on yield improvement

1975 ◽  
Vol 21 (2) ◽  
pp. 121-125 ◽  
Author(s):  
Reuven Bar-Anan
Keyword(s):  
Standard Deviation ◽  
Genetic Improvement ◽  
Genetic Correlations ◽  
Selection Criterion ◽  
Yield Improvement ◽  
Selection Models ◽  
Breeding Values ◽  
Additional Costs ◽  
Estimated Breeding Values ◽  
Sire Selection

SUMMARYCorrelations and regressions between estimated breeding values for 122 day part-lactation, 1st and 2nd lactation yield (part, 1st, 2nd) were estimated from 106 sire progeny groups, each with at least 60 effective daughters.The genetic correlations between part, 1st and 2nd kg milk were 1·0 and 0·84 respectively, and the regressions of 1st on part and of 2nd on 1st test were 2·40 and 0·82 kg/kg milk, respectively. Selection by one standard deviation between sires on part-lactation tests would improve 1st lactation yields by an average of 204 kg milk with a standard deviation of 84 kg. Selection on 1st lactation yields by one standard deviation would increase 2nd lactation yields by an average of 183 kg milk with a standard deviation of 156 kg, indicating that some bulls so selected could have below average 2nd lactation yields.Two sire selection models were simulated differing in the selection criterion; 1 st yield in model 1, and 1 st followed by 2nd yields in model 2. The contribution of proven sires to the rate of genetic improvement in lifetime production was greater from model 2 than from model 1 by about 15% without any additional costs for bull maintenance.

Preliminary genetic analysis of beef carcass data

2009 ◽  
Vol 2009 ◽  
pp. 58-58
Author(s):  
M P Coffey ◽  
E Wall ◽  
G Banos ◽  
R Roehe
Keyword(s):  
Genetic Analysis ◽  
Beef Cattle ◽  
Genetic Improvement ◽  
Selective Breeding ◽  
Cost Effective ◽  
Genetic Evaluation ◽  
Carcass Weight ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Farm Livestock

Selective breeding of farm livestock is one of the most cost-effective ways of improving the performance and efficiency of livestock enterprises. Genetic improvement of British beef cattle over a ten year period was recently estimated to be worth approximately £23, and the benefits continue to rise (Amer et al., 2007). While these returns are impressive, they could be improved by increasing the rate of improvement in the purebred population, for example by increasing the relevance of estimated breeding values (EBVs) to beef production by using final carcass weight and grading information. This study will examine the feasibility carcass weights and classifications from UK commercial abattoirs for the genetic evaluation of cattle for carcass weight, carcass fatness class, and carcass conformation class.

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 Genomic selection for white spot syndrome virus resistance in whiteleg shrimp boosts survival under an experimental challenge test

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Marie Lillehammer ◽  
Rama Bangera ◽  
Marcela Salazar ◽  
Sergio Vela ◽  
Edna C. Erazo ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Genetic Improvement ◽  
White Spot Syndrome Virus ◽  
Random Mating ◽  
Challenge Test ◽  
White Spot ◽  
Breeding Value ◽  
Genomic Breeding ◽  
Breeding Values ◽  
White Spot Syndrome

AbstractWhite spot syndrome virus (WSSV) causes major worldwide losses in shrimp aquaculture. The development of resistant shrimp populations is an attractive option for management of the disease. However, heritability for WSSV resistance is generally low and genetic improvement by conventional selection has been slow. This study was designed to determine the power and accuracy of genomic selection to improve WSSV resistance in Litopenaeus vannamei. Shrimp were experimentally challenged with WSSV and resistance was evaluated as dead or alive (DOA) 23 days after infestation. All shrimp in the challenge test were genotyped for 18,643 single nucleotide polymorphisms. Breeding candidates (G0) were ranked on genomic breeding values for WSSV resistance. Two G1 populations were produced, one from G0 breeders with high and the other with low estimated breeding values. A third population was produced from “random” mating of parent stock. The average survival was 25% in the low, 38% in the random and 51% in the high-genomic breeding value groups. Genomic heritability for DOA (0.41 in G1) was high for this type of trait. The realised genetic gain and high heritability clearly demonstrates large potential for further genetic improvement of WSSV resistance in the evaluated L. vannamei population using genomic selection.

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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