Genetic changes in Canadian performance-tested pigs for fat depth and growth rate

1996 ◽  
Vol 76 (1) ◽  
pp. 41-48 ◽  
Author(s):  
B. W. Kennedy ◽  
V. M. Quinton ◽  
C. Smith
Keyword(s):  
Growth Rate ◽  
Performance Testing ◽  
Economic Benefits ◽  
Breeding Value ◽  
Improvement Program ◽  
Linear Unbiased Prediction ◽  
Genetic Changes ◽  
Best Linear Unbiased ◽  
The Mean ◽  
Genetic Trends

Data on more than 1.3 million pigs of four breeds in four regions of Canada were used to estimate genetic changes in fat depth and growth rate from 1976 to 1993. Analysis was by a multi (two)-trait best linear unbiased prediction (BLUP) animal model within breed and across regions. The genetic changes were measured as the changes in average estimated breeding value (EBV) over years.The across-breed average total phenotypic changes from 1976 to 1993 were− 3.9 mm in fat depth (26% of the mean) and− 17 d in age at 100 kg (9% of the mean). The multi-trait BLUP estimates of the genetic trends were similar to single-trait BLUP estimates. The mean EBV and the changes were similar for the four regions. The changes were larger in the Landrace and Yorkshire breeds than in the Duroc and Hampshire. The overall genetic trends were − 1.44% of the mean yr−1 in fat depth and − 0.36% of the mean yr−1 in age at 100 kg. The trend for age at 100 kg increased over time as better methods of deriving the EBV were implemented. The current rates of pig improvement in Canada are good and yield large economic benefits. However, they could be improved to recoup the full gains possible through the Canadian Swine Improvement Program. Key words: Canadian pigs, performance testing, genetic trends

Genetic changes generated within the Katanning Merino Resource flocks

2006 ◽  
Vol 46 (7) ◽  
pp. 803 ◽  
Author(s):  
J. C. Greeff ◽  
G. Cox
Keyword(s):  
Body Weight ◽  
Phase 1 ◽  
Fibre Diameter ◽  
Linear Unbiased Prediction ◽  
Genetic Changes ◽  
Breeding Values ◽  
Best Linear Unbiased ◽  
Fleece Weight ◽  
Estimated Breeding Values ◽  
Genetic Trends

Genetic changes for clean fleece weight, fibre diameter and hogget body weight were determined in the Katanning Merino Resource flocks from 1982 to 2004. From 1982 to 1992 genetic trends are presented for individual studs that used mainly subjective classing selection methods (Phase 1) and the genetic trends from 1997 to 2004 demonstrate the genetic changes that can be achieved from using estimated breeding values calculated from best linear unbiased prediction (BLUP) mixed methodology (Phase 2). The results during the first phase show that very few genetic changes occurred in most studs, except for the 4 studs of the Performance Sheep Breeding strain which showed genetic increases in hogget body weight. The genetic trends show that some studs generated change towards their breeding objective, while others show no changes or changes in the opposite direction. In contrast, the use of BLUP estimated breeding values resulted in positive changes in clean fleece weight, fibre diameter and body weight in accordance with the defined breeding objectives.

Estimation of genetic and phenotypic trends for litter size in canadian yorkshire and landrace swine

1990 ◽  
Vol 1990 ◽  
pp. 12-12
Author(s):  
O. I. Southwood
Keyword(s):  
Litter Size ◽  
Computer Programs ◽  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Canadian Province ◽  
Linear Unbiased Prediction ◽  
Genetic Changes ◽  
Genetic Merit ◽  
Best Linear Unbiased ◽  
Over Time

Litter size in swine, although lowly heritable, has been receiving increasing interest especially with the availability of computer programs to allow estimation of genetic merit for this trait using family information. Genetic changes in a trait over time can be monitored by estimating best linear unbiased prediction (BLUP) of breeding value for individuals exhibiting the trait. Data from a recording programme within a Canadian province allowed estimation of genetic and phenotypic trends for three measures of litter size.Data from purebred Yorkshire and Landrace litters were obtained from the Quebec Record of Performance Sow Productivity Program. First parity litters born between 1977 and 1987 were analysed for total numbers born, numbers born alive and numbers weaned. Data were edited to include only herds with ten or more litters in Yorkshire and 40 or more litters in Landrace. Also, in order to reduce the number of records further, due to computing limitations, a sow was only allowed one daughter per full-sib family. A total of 2024 Yorkshire gilts (from 467 sires and 1539 dams) and 1920 Landrace gilts (from 421 sires and 1436 dams) provided records.

Best linear unbiased prediction of clonal breeding values and genetic values from full-sib mating designs

2003 ◽  
Vol 33 (10) ◽  
pp. 2036-2043 ◽  
Author(s):  
Bin Xiang ◽  
Bailian Li
Keyword(s):  
Genetic Gain ◽  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Improvement Program ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Sib Mating ◽  
Best Linear Unbiased ◽  
Progeny Tests ◽  
Unbiased Prediction

Full-sib progeny tests with clonal replicates may provide better breeding value estimates and the greatest genetic gain in a tree improvement program. Clonal breeding values (CBV) that combine the family and within-family breeding values due to additive genetic effects can maximize the genetic gain for advanced generation breeding. Clonal genetic values (CGV) that further incorporate full-sib family specific combining ability due to nonadditive genetic effect can maximize gain for a deployment program with clonal propagation techniques. The best linear unbiased prediction (BLUP) is the best statistical method for estimating both CBV and CGV because of its desirable statistical properties compared with the heritability-based gain calculation. A BLUP method for determining both the CBV and CGV for full-sib clonal progeny tests was proposed in this paper. The formulas for CBV and CGV were derived using general BLUP methodology, and formulas were derived for the calculations of their standard errors. An analytical method by using a standard statistical package (SAS PROC MIXED) was presented for CBV and CGV calculations from any full-sib mating designs.

A method for reducing inbreeding with Best Linear Unbiased Prediction

1993 ◽  
Vol 1993 ◽  
pp. 33-33
Author(s):  
B Grundy ◽  
WG Hill
Keyword(s):  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Best Linear Unbiased Predictor ◽  
Linear Unbiased Prediction ◽  
Genetic Merit ◽  
Selection Decisions ◽  
Best Linear Unbiased ◽  
Estimated Breeding Value ◽  
Commercial Environment ◽  
Unbiased Prediction

An optimum way of selecting animals is through a prediction of their genetic merit (estimated breeding value, EBV), which can be achieved using a best linear unbiased predictor (BLUP) (Henderson, 1975). Selection decisions in a commercial environment, however, are rarely made solely on genetic merit but also on additional factors, an important example of which is to limit the accumulation of inbreeding. Comparison of rates of inbreeding under BLUP for a range of hentabilities highlights a trend of increasing inbreeding with decreasing heritability. It is therefore proposed that selection using a heritability which is artificially raised would yield lower rates of inbreeding than would otherwise be the case.

A simulation study of open nucleus and closed nucleus breeding systems in a sheep population

1995 ◽  
Vol 60 (1) ◽  
pp. 117-124 ◽  
Author(s):  
J. A. Roden
Keyword(s):  
Genetic Gain ◽  
Live Weight ◽  
Breeding Systems ◽  
Breeding Value ◽  
Linear Unbiased Prediction ◽  
Sheep Population ◽  
Best Linear Unbiased ◽  
Nucleus Breeding ◽  
Open Nucleus ◽  
Selection Of

AbstractStochastic simulation was used to compare the results of alternative breeding systems in a sheep population divided into 10 flocks of 120 ewes. The breeding systems compared were selection within closed flocks (CF), a closed nucleus system (CNS), an open nucleus system (ONS) and open nucleus systems with the selection of nucleus replacements being restricted to either nucleus born males (ONSRm) or nucleus born females (ONSRf). Selection was for a best linear unbiased prediction of breeding value for lamb live weight which had a heritability of 0·17. The open nucleus breeding systems (ONS, ONSRm, ONSRf) resulted in higher rates of genetic gain, more predictable selection responses and lower rates of inbreeding than either the closed nucleus system (CNS) or selection within closed flocks (CF). Initial genetic differences between flocks resulted in higher rates of genetic gain in the nucleus breeding systems due to the use of between flock genetic variance. In the ONS system up to 25% of nucleus sires and approximately 50% of nucleus dams were born in base flocks. Nevertheless if selection of either nucleus sires or dams was restricted to nucleus born animals there was very little change in genetic gain or rate of inbreeding.

scholarly journals Genetic evaluation and selection correlated response of growth traits in Japanese quail

2020 ◽  
Vol 50 (2) ◽  
pp. 325-333
Author(s):  
M.M. El-Attrouny ◽  
E.A. Manaa ◽  
S.I. Ramadan
Keyword(s):  
Growth Traits ◽  
Best Linear Unbiased Prediction ◽  
Correlated Response ◽  
Genetic Trend ◽  
Linear Unbiased Prediction ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Best Linear Unbiased ◽  
Selection For ◽  
Genetic Trends

Objectives of the current study were to i) investigate effects of selection for bodyweight at four weeks old on bodyweight (BW) and bodyweight gain (BWG) across four generations; ii) estimate correlated response to selection for BW and BWG at different ages; and iii) document best linear unbiased prediction (BLUP) of genetic trends for BW and BWG across four generations of selection. A total of 3540 chicks from 444 sires and 885 dams were used to estimate heritabilities, and genetic and phenotypic correlations for growth traits, including BW at 0, 2, 4, and 6 weeks, and BWG between 0 and 2, 2 and 4, 4 and 6, and 0 and 6 weeks. The selection effects, correlated responses and genetic trend for BW and BWG across generations were quantified by applying the animal model. Estimates of heritability for BW and BWG ranged from 0.22 to 0.42 and from 0.18 to 0.23, respectively. Ranges of genetic and phenotypic correlations for BW varied from 0.31 to 0.92 and 0.05 to 0.65, respectively. Moreover, estimates of genetic and phenotypic correlations for BWG at different ages were from 0.12 to 0.72 and 0.17 to 0.60, respectively. Bodyweight and BWG estimates after four generations of selection were significantly higher than those of the base generation. Moreover, contrasts of generation means were significant across the four generations. The genetic trends across the generations clarified that BLUP estimates for BW and BWG gradually increased with the advance of generations until the fourth generation. Keywords: best linear unbiased prediction, bodyweight, heritability, selection, genetic trend

scholarly journals Prediction of Rates of Inbreeding in Populations Selected on Best Linear Unbiased Prediction of Breeding Value

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 361-373
Author(s):  
Piter Bijma ◽  
John A Woolliams
Keyword(s):  
Linear Model ◽  
Goodness Of Fit ◽  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Quadratic Model ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Wide Range ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Abstract Predictions for the rate of inbreeding (ΔF) in populations with discrete generations undergoing selection on best linear unbiased prediction (BLUP) of breeding value were developed. Predictions were based on the concept of long-term genetic contributions using a recently established relationship between expected contributions and rates of inbreeding and a known procedure for predicting expected contributions. Expected contributions of individuals were predicted using a linear model, μi(x) = α βsi, where si denotes the selective advantage as a deviation from the contemporaries, which was the sum of the breeding values of the individual and the breeding values of its mates. The accuracy of predictions was evaluated for a wide range of population and genetic parameters. Accurate predictions were obtained for populations of 5–20 sires. For 20–80 sires, systematic underprediction of on average 11% was found, which was shown to be related to the goodness of fit of the linear model. Using simulation, it was shown that a quadratic model would give accurate predictions for those schemes. Furthermore, it was shown that, contrary to random selection, ΔF less than halved when the number of parents was doubled and that in specific cases ΔF may increase with the number of dams.

scholarly journals The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

Animals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 569
Author(s):  
Chen Wei ◽  
Hanpeng Luo ◽  
Bingru Zhao ◽  
Kechuan Tian ◽  
Xixia Huang ◽  
...  
Keyword(s):  
Rank Correlation ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Breeding Value ◽  
Genomic Information ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
Merino Sheep ◽  
Best Linear Unbiased ◽  
Unbiased Prediction

Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992–2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h2 values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

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