estimated breeding value
Recently Published Documents


TOTAL DOCUMENTS

55
(FIVE YEARS 21)

H-INDEX

9
(FIVE YEARS 2)

Animals ◽  
2022 ◽  
Vol 12 (2) ◽  
pp. 136
Author(s):  
Menghua Zhang ◽  
Hanpeng Luo ◽  
Lei Xu ◽  
Yuangang Shi ◽  
Jinghang Zhou ◽  
...  

One-step genomic selection is a method for improving the reliability of the breeding value estimation. This study aimed to compare the reliability of pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP), single-trait and multitrait models, and the restricted maximum likelihood (REML) and Bayesian methods. Data were collected from the production performance records of 2207 Xinjiang Brown cattle in Xinjiang from 1983 to 2018. A cross test was designed to calculate the genetic parameters and reliability of the breeding value of 305 daily milk yield (305 dMY), milk fat yield (MFY), milk protein yield (MPY), and somatic cell score (SCS) of Xinjiang Brown cattle. The heritability of 305 dMY, MFY, MPY, and SCS estimated using the REML and Bayesian multitrait models was approximately 0.39 (0.02), 0.40 (0.03), 0.49 (0.02), and 0.07 (0.02), respectively. The heritability and estimated breeding value (EBV) and the reliability of milk production traits of these cattle calculated based on PBLUP and ssGBLUP using the multitrait model REML and Bayesian methods were higher than those of the single-trait model REML method; the ssGBLUP method was significantly better than the PBLUP method. The reliability of the estimated breeding value can be improved from 0.9% to 3.6%, and the reliability of the genomic estimated breeding value (GEBV) for the genotyped population can reach 83%. Therefore, the genetic evaluation of the multitrait model is better than that of the single-trait model. Thus, genomic selection can be applied to small population varieties such as Xinjiang Brown cattle, in improving the reliability of the genomic estimated breeding value.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Masayuki Takeda ◽  
Keiichi Inoue ◽  
Hidemi Oyama ◽  
Katsuo Uchiyama ◽  
Kanako Yoshinari ◽  
...  

Abstract Background Size of reference population is a crucial factor affecting the accuracy of prediction of the genomic estimated breeding value (GEBV). There are few studies in beef cattle that have compared accuracies achieved using real data to that achieved with simulated data and deterministic predictions. Thus, extent to which traits of interest affect accuracy of genomic prediction in Japanese Black cattle remains obscure. This study aimed to explore the size of reference population for expected accuracy of genomic prediction for simulated and carcass traits in Japanese Black cattle using a large amount of samples. Results A simulation analysis showed that heritability and size of reference population substantially impacted the accuracy of GEBV, whereas the number of quantitative trait loci did not. The estimated numbers of independent chromosome segments (Me) and the related weighting factor (w) derived from simulation results and a maximum likelihood (ML) approach were 1900–3900 and 1, respectively. The expected accuracy for trait with heritability of 0.1–0.5 fitted well with empirical values when the reference population comprised > 5000 animals. The heritability for carcass traits was estimated to be 0.29–0.41 and the accuracy of GEBVs was relatively consistent with simulation results. When the reference population comprised 7000–11,000 animals, the accuracy of GEBV for carcass traits can range 0.73–0.79, which is comparable to estimated breeding value obtained in the progeny test. Conclusion Our simulation analysis demonstrated that the expected accuracy of GEBV for a polygenic trait with low-to-moderate heritability could be practical in Japanese Black cattle population. For carcass traits, a total of 7000–11,000 animals can be a sufficient size of reference population for genomic prediction.


Author(s):  
C M C van der Peet-Schwering ◽  
L M G Verschuren ◽  
R Bergsma ◽  
M S Hedemann ◽  
G P Binnendijk ◽  
...  

Abstract The effects of birth weight (BiW) (low BiW (LBW) vs high BiW (HBW)) and estimated breeding value for protein deposition (EBV) (low EBV (LBV) vs high EBV (HBV)) on N retention, N efficiency and concentrations of metabolites in plasma and urine related to N efficiency in growing pigs were studied. At an age of 14 weeks, 10 LBW-LBV (BiW: 1.07 + 0.09 (SD) kg; EBV: -2.52 + 3.97 g/d, compared to an average crossbred pig with a protein deposition of 165 g/d), 10 LBW-HBV (BiW: 1.02 + 0.13 kg; EBV: 10.47 + 4.26 g/d), 10 HBW-LBV (BiW: 1.80 + 0.13 kg; EBV: -2.15 + 2.28 g/d), and 10 HBW-HBV (BiW: 1.80 + 0.15 kg; EBV: 11.18 + 3.68 g/d), male growing pigs were allotted to the experiment. The pigs were individually housed in metabolism cages and were subjected to a N balance study in two sequential periods of 5 d, after a 11-d dietary adaptation period. Pigs were assigned to a protein adequate (A) or protein restricted (R, 70% of A) regime in a change-over design. Pigs were fed 2.8 times the energy requirements for maintenance. Non-targeted metabolomics analyses were performed in urine and blood plasma samples. The N retention (in g/d) was higher in the HBW than in the LBW pigs (P < 0.001). The N retention (in g/(kg BW 0.75.d)) and N efficiency, however, were not affected by BiW of the pigs. The N retention (P = 0.04) and N efficiency (P = 0.04) were higher in HBV than in LVB pigs on the A regime, but were not affected by EBV in pigs on the R regime. Restricting the dietary protein supply with 30% decreased the N retention (P < 0.001) but increased the N efficiency (P = 0.003). Non-targeted metabolomics showed that a hexose, free amino acids (AA) and lysophosphatidylcholines were the most important metabolites in plasma for the discrimination between HBV and LBV pigs, whereas metabolites of microbial origin contributed to the discrimination between HBV and LBV pigs in urine. This study shows that BiW does not affect N efficiency in later life of pigs. Nitrogen efficiency and N retention were higher in HBV than in LBV pigs on the A regime, but similar in HBV and LBV pigs on the R regime. In precision feeding concepts aiming to further optimize protein and AA efficiency in pigs, the variation in EBV for protein deposition of pigs should be considered as a factor determining N retention, growth performance and N-efficiency.


2021 ◽  
Vol 48 (2) ◽  
pp. 1-5
Author(s):  
I. Udeh

Animal breeders are interested in the genetic worth or total genetic merit of an animal for a given trait. The value of an animal in a breeding program for a particular trait is called the breeding value. The aim of this study was to predict the breeding values for bodyweight of grasscutters at 4, 6 and 8 months of age using univariate animal model. Four families of grasscutters with five grasscutters per family were used for the study. Families 3 and 4 had higher bodyweight at 4 and 6 months compared with families 1 and 2. Family 4 had the highest bodyweight at 8 month and family 2 had the least. The estimated breeding values (EBV) for bodyweight of grasscutters ranged from -0.06kg to 0.45kg at 4 month, -0.05kg to 0.45 kg at 6 month and -0.04kg to 0.55kg at 8 month. The reliability of the EBV (%) ranged from 51.00 to 62.50, 22.25 to 43.81 and 25.84 to 49.00 at 4, 6 and 8 months of age respectively. This implies that the correlations between estimated breeding value and true genetic merit were medium to high in magnitude. The reliability of the EBV could be improved further through collecting more phenotypic information on the animal and its relatives and by improving the heritability of the trait.     Les éleveurs s'intéressent à la valeur génétique ou au mérite génétique total d'un animal pour un trait donné. La valeur d'un animal dans un programme d'élevage pour un trait particulier est appelée valeur de reproduction. Le but de cette étude était de prédire les valeurs de reproduction du poids corporel des coupe-herbes à l'âge de 4, 6 et 8 mois à l'aide d'un modèle animal univarié. Quatre familles de coupe-herbes avec cinq coupes-herbes par famille ont été utilisées pour l'étude. Les familles 3 et 4 avaient un poids corporel plus élevé à 4 et 6 mois comparativement aux familles 1 et 2. Famille 4 avait le poids corporel le plus élevé à 8 mois et la famille 2 avait le moins. Les valeurs de reproduction estimées (le 'EBV') pour le poids corporel des coupe-herbes allaient de -0.06 kg à 0,45 kg à 4 mois, -0.05 kg à 0.45 kg à 6 mois et -0.04 kg à 0.55 kg à 8 mois. La fiabilité de l'EBV (%) 51.00 à 62.50, 22.25 à 43.81 et 25.84 à 49.00 à 4, 6 et 8 mois respectivement. Cela implique que les corrélations entre la valeur de reproduction estimée et le véritable mérite génétique étaient de taille moyenne à élevée. La fiabilité de l'EBV pourrait être encore améliorée en recueillant plus d'informations phénotypique sur l'animal et ses parents et en améliorant l'hérabilité du trait.


2020 ◽  
Vol 54 (6) ◽  
pp. 73-80
Author(s):  
Ji-Hyun Son ◽  
◽  
Yang-Mo Koo ◽  
Yeoung-Ho Jeoung ◽  
Dae-Hyeop Cha ◽  
...  

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 8-9
Author(s):  
Zahra Karimi ◽  
Brian Sullivan ◽  
Mohsen Jafarikia

Abstract Previous studies have shown that the accuracy of Genomic Estimated Breeding Value (GEBV) as a predictor of future performance is higher than the traditional Estimated Breeding Value (EBV). The purpose of this study was to estimate the potential advantage of selection on GEBV for litter size (LS) compared to selection on EBV in the Canadian swine dam line breeds. The study included 236 Landrace and 210 Yorkshire gilts born in 2017 which had their first farrowing after 2017. GEBV and EBV for LS were calculated with data that was available at the end of 2017 (GEBV2017 and EBV2017, respectively). De-regressed EBV for LS in July 2019 (dEBV2019) was used as an adjusted phenotype. The average dEBV2019 for the top 40% of sows based on GEBV2017 was compared to the average dEBV2019 for the top 40% of sows based on EBV2017. The standard error of the estimated difference for each breed was estimated by comparing the average dEBV2019 for repeated random samples of two sets of 40% of the gilts. In comparison to the top 40% ranked based on EBV2017, ranking based on GEBV2017 resulted in an extra 0.45 (±0.29) and 0.37 (±0.25) piglets born per litter in Landrace and Yorkshire replacement gilts, respectively. The estimated Type I errors of the GEBV2017 gain over EBV2017 were 6% and 7% in Landrace and Yorkshire, respectively. Considering selection of both replacement boars and replacement gilts using GEBV instead of EBV can translate into increased annual genetic gain of 0.3 extra piglets per litter, which would more than double the rate of gain observed from typical EBV based selection. The permutation test for validation used in this study appears effective with relatively small data sets and could be applied to other traits, other species and other prediction methods.


2020 ◽  
Vol 33 (7) ◽  
pp. 1057-1067 ◽  
Author(s):  
Chiemela Peter Nwogwugwu ◽  
Yeongkuk Kim ◽  
Yun Ji Chung ◽  
Sung Bong Jang ◽  
Seung Hee Roh ◽  
...  

Objective: This study evaluated the effect of pedigree errors (PEs) on the accuracy of estimated breeding value (EBV) and genetic gain for carcass traits in Korean Hanwoo cattle.Methods: The raw data set was based on the pedigree records of Korean Hanwoo cattle. The animals’ information was obtained using Hanwoo registration records from Korean animal improvement association database. The record comprised of 46,704 animals, where the number of the sires used was 1,298 and the dams were 38,366 animals. The traits considered were carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS). Errors were introduced in the pedigree dataset through randomly assigning sires to all progenies. The error rates substituted were 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80%, respectively. A simulation was performed to produce a population of 1,650 animals from the pedigree data. A restricted maximum likelihood based animal model was applied to estimate the EBV, accuracy of the EBV, expected genetic gain, variance components, and heritability (h2) estimates for carcass traits. Correlation of the simulated data under PEs was also estimated using Pearson’s method.Results: The results showed that the carcass traits per slaughter year were not consistent. The average CWT, EMA, BFT, and MS were 342.60 kg, 78.76 cm<sup>2, 8.63 mm, and 3.31, respectively. When errors were introduced in the pedigree, the accuracy of EBV, genetic gain and h2 of carcass traits was reduced in this study. In addition, the correlation of the simulation was slightly affected under PEs.Conclusion: This study reveals the effect of PEs on the accuracy of EBV and genetic parameters for carcass traits, which provides valuable information for further study in Korean Hanwoo cattle.


2020 ◽  
Vol 62 (4) ◽  
pp. 429-437
Author(s):  
Eun Ho Kim ◽  
Hyeon Kwon Kim ◽  
Du Won Sun ◽  
Ho Chan Kang ◽  
Doo Ho Lee ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document