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.

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 parameters and trends in a selection experiment for increased clean fleece weight involving South African Merinos

1998 ◽  
Vol 38 (5) ◽  
pp. 427 ◽  
Author(s):  
S. W. P. Cloete ◽  
J. J. Olivier ◽  
M. A. Snyman ◽  
E. du Toit
Keyword(s):  
Fibre Diameter ◽  
Control Group ◽  
Selection Line ◽  
Additive Effects ◽  
Genetic And Phenotypic Correlations ◽  
Estimate Heritability ◽  
Fleece Weight ◽  
Estimated Breeding Values ◽  
Change In Mean ◽  
Genetic Trends

Summary. Data of 3603 to 7385 progeny of a Merino line selected for an increased clean fleece weight with a limitation on fibre diameter in sires and an unselected control group were used to estimate heritability for liveweight and wool traits. Estimated breeding values were obtained by backsolution and averaged within birth years to obtain genetic trends. Direct additive heritability (± s.e.) estimates were 0.29 ± 0.02 for clean fleece weight, 0.52 ± 0.03 for liveweight, 0.68 ± 0.02 for clean yield, 0.35 ± 0.02 for staple length, 0.63 ± 0.02 for fibre diameter and 0.42 ± 0.03 for total fold score. Fitting maternal additive effects to the model of analysis resulted in an improvement (P≤0.05) in the log likelihood ratio for clean fleece weight and liveweight. These effects were relatively small in magnitude, resulting in maternal additive effects (± s.e.) of 0.04 ± 0.01 for both traits. Genetic and phenotypic correlations of clean fleece weight with the other traits were positive. Genetic trends for fleece traits in the control group were less than 0.1% of the overall phenotypic mean per year. A substantial increase, depicted by a regression (± s.e.b) amounting to 0.14 ± 0.01 kg/year (0.28% of the phenotypic mean) was, however, found for liveweight (r = 0.91). The direct response in clean fleece weight in the selection line amounted to 0.039 ± 0.001 kg/year (r = 0.99), or 0.97% of the overall phenotypic mean. Correlated responses ranged from 0.78% of the overall phenotypic mean (r = 0.97) for liveweight to 0.17% per year (r = 0.51) for clean yield. The genetic change in mean fibre diameter (the trait under observation because an increase was unwanted) amounted to 0.020 ± 0.002 m/year (r = 0.69) or 0.10% of the overall phenotypic mean. The relaxation of the limitation on fibre diameter in sires used during 1986–90 probably contributed to this trend. A substantial increase in clean fleece weight was thus possible while unwanted increases in fibre diameter were limited.

scholarly journals Domestic and Interbull information in the single step genomic evaluation of Holstein milk production

2014 ◽  
Vol 59 (No. 9) ◽  
pp. 409-415 ◽  
Author(s):  
J. Přibyl ◽  
J. Bauer ◽  
P. Pešek ◽  
J. Přibylová ◽  
L. Vostrý ◽  
...  
Keyword(s):  
Animal Model ◽  
Milk Production ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Linear Unbiased Prediction ◽  
Breeding Values ◽  
One Step ◽  
Best Linear Unbiased ◽  
Estimated Breeding Values ◽  
Unbiased Prediction

Estimated breeding values and genomic enhanced breeding values for milk production of young genotyped Holstein bulls were predicted using a conventional animal model, ridge regression genomic prediction procedure, genomic best linear unbiased prediction, single-step genomic best linear unbiased prediction, and one-step blending procedures. For prediction, the nation-wide database of domestic Czech production records was combined with deregressed proofs from Interbull files through 2008, which had been transformed by multiple across country evaluation to reflect domestic production conditions. 1259 genotyped bulls had already been proven in 2008. Analyses were run that used Interbull values only for these genotyped bulls and used Interbull values for all available sires. Predictions were validated by comparing correlations of breeding value predictions with estimated breeding values and daughter-yield-deviations after progeny test in 2012 of 140 young genotyped bulls and their associated reliabilities. Combining domestic data with Interbull estimated breeding values improved prediction of both estimated breeding values and genomic enhanced breeding values. Prediction by animal model (traditional estimated breeding values) using only the domestic database had 0.29 validated reliability of prediction; whereas combining the nation-wide domestic database with all available deregressed proofs for genotyped and non-genotyped sires from Interbull resulted in reliability of 0.34, compared to 0.36 when using Interbull data only. The highest reliabilities were for predictions from the single-step genomic best linear unbiased prediction procedure using combined data, or with all available deregressed proofs from Interbull only (one-step blending approach), which reached validated reliabilities for genomic enhanced breeding values predictions 0.53 and 0.54, respectively.  

scholarly journals Genomic selection in French dairy cattle

2012 ◽  
Vol 52 (3) ◽  
pp. 115 ◽  
Author(s):  
D. Boichard ◽  
F. Guillaume ◽  
A. Baur ◽  
P. Croiseau ◽  
M. N. Rossignol ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Genomic Selection ◽  
Reference Population ◽  
Specific Reference ◽  
Nucleotide Polymorphisms ◽  
Genomic Evaluation ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Estimated Breeding Values ◽  
Restricted Use

Genomic selection is implemented in French Holstein, Montbéliarde, and Normande breeds (70%, 16% and 12% of French dairy cows). A characteristic of the model for genomic evaluation is the use of haplotypes instead of single-nucleotide polymorphisms (SNPs), so as to maximise linkage disequilibrium between markers and quantitative trait loci (QTLs). For each trait, a QTL-BLUP model (i.e. a best linear unbiased prediction model including QTL random effects) includes 300–700 trait-dependent chromosomal regions selected either by linkage disequilibrium and linkage analysis or by elastic net. This model requires an important effort to phase genotypes, detect QTLs, select SNPs, but was found to be the most efficient one among all tested ones. QTLs are defined within breed and many of them were found to be breed specific. Reference populations include 1800 and 1400 bulls in Montbéliarde and Normande breeds. In Holstein, the very large reference population of 18 300 bulls originates from the EuroGenomics consortium. Since 2008, ~65 000 animals have been genotyped for selection by Labogena with the 50k chip. Bulls genomic estimated breeding values (GEBVs) were made official in June 2009. In 2010, the market share of the young bulls reached 30% and is expected to increase rapidly. Advertising actions have been undertaken to recommend a time-restricted use of young bulls with a limited number of doses. In January 2011, genomic selection was opened to all farmers for females. Current developments focus on the extension of the method to a multi-breed context, to use all reference populations simultaneously in genomic evaluation.

Genetic and phenotypic trends and parameters in reproduction, greasy fleece weight and liveweight in Merino lines divergently selected for multiple rearing ability

2004 ◽  
Vol 44 (8) ◽  
pp. 745 ◽  
Author(s):  
S. W. P. Cloete ◽  
A. R. Gilmour ◽  
J. J. Olivier ◽  
J. B. van Wyk
Keyword(s):  
Genetic Correlations ◽  
Annual Production ◽  
Production Traits ◽  
Genetic Progress ◽  
Additive Variance ◽  
Genetic Changes ◽  
Environmental Correlations ◽  
Breeding Values ◽  
Reproduction Traits ◽  
Fleece Weight

Genetic and phenotypic trends and parameters were estimated for reproduction, fleece weight and liveweight in a South African Merino population, divergently selected from 1986, either for (H line) or against (L line) maternal multiple rearing ability. Annual reproduction, ewe greasy fleece weight and pre-joining liveweight data were recorded on 809 Merino ewes, from 1986 to 2002. Phenotypic trends indicated divergence in reproduction traits between the H and L lines. The direct additive variance ratio (h2 ± s.e.) for day of lambing was 0.08 ± 0.02. Estimates of h2 for reproduction traits were: 0.10 ± 0.02 for number of lambs born per ewe; 0.04 ± 0.02 for number of lambs weaned per ewe; and 0.04 ± 0.02 for weight of lamb weaned per ewe, corrected for the gender of the lamb. Corresponding h2 estimates for annual production were 0.57 ± 0.06 for greasy fleece weight and 0.48 ± 0.06 for ewe liveweight at joining. Service sire only exerted a significant (P<0.05) effect on day of lambing, but it accounted for merely 2% of the overall phenotypic variation. Ewe permanent environment variance ratios (c2ewe) for the reproduction traits were: 0.07 ± 0.03 for number of lambs born per ewe; 0.11 ± 0.03 for number of lambs weaned per ewe; and 0.11 ± 0.03 for total weight of lamb weaned per ewe. Corresponding c2ewe estimates for annual production traits were 0.14 ± 0.05 for greasy fleece weight and 0.27 ± 0.06 for ewe joining weight. Genetic and ewe permanent environmental correlations between measures of reproduction exceeded 0.7. Genetic correlations of reproduction traits with greasy fleece weight were low and variable in sign. Genetic correlations of reproduction traits with ewe joining weight were positive and particularly high for weight of lamb weaned. Permanent environmental correlations of reproduction traits with greasy fleece weight and joining weight were generally low to moderate. Genetic trends for the H and L lines (derived from averaged direct breeding values within birth years) were divergent (P<0.01) for all reproduction traits. Expressed as percentage of the overall least squares means of the respective traits, breeding values in the H line increased annually, with 1.3% for lambs born per ewe, 1.5% for lambs weaned per ewe and by 1.8% for weight of lamb weaned per ewe. Corresponding trends in the L line were, respectively, –0.6%, –1.0% and –1.2% per year. Substantial genetic progress in annual lamb output was attainable, despite relatively small h2 estimates. This response was achieved without unfavourable genetic changes in wool and liveweight.

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 Indirect predictions with a large number of genotyped animals using the algorithm for proven and young

2020 ◽  
Vol 98 (6) ◽  
Author(s):  
Andre L S Garcia ◽  
Yutaka Masuda ◽  
Shogo Tsuruta ◽  
Stephen Miller ◽  
Ignacy Misztal ◽  
...  
Keyword(s):  
Random Sample ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Nucleotide Polymorphisms ◽  
Linear Unbiased Prediction ◽  
Single Nucleotide ◽  
Large Numbers ◽  
Minimum Number ◽  
Best Linear Unbiased ◽  
Estimated Breeding Values

Abstract Reliable single-nucleotide polymorphisms (SNP) effects from genomic best linear unbiased prediction BLUP (GBLUP) and single-step GBLUP (ssGBLUP) are needed to calculate indirect predictions (IP) for young genotyped animals and animals not included in official evaluations. Obtaining reliable SNP effects and IP requires a minimum number of animals and when a large number of genotyped animals are available, the algorithm for proven and young (APY) may be needed. Thus, the objectives of this study were to evaluate IP with an increasingly larger number of genotyped animals and to determine the minimum number of animals needed to compute reliable SNP effects and IP. Genotypes and phenotypes for birth weight, weaning weight, and postweaning gain were provided by the American Angus Association. The number of animals with phenotypes was more than 3.8 million. Genotyped animals were assigned to three cumulative year-classes: born until 2013 (N = 114,937), born until 2014 (N = 183,847), and born until 2015 (N = 280,506). A three-trait model was fitted using the APY algorithm with 19,021 core animals under two scenarios: 1) core 2013 (random sample of animals born until 2013) used for all year-classes and 2) core 2014 (random sample of animals born until 2014) used for year-class 2014 and core 2015 (random sample of animals born until 2015) used for year-class 2015. GBLUP used phenotypes from genotyped animals only, whereas ssGBLUP used all available phenotypes. SNP effects were predicted using genomic estimated breeding values (GEBV) from either all genotyped animals or only core animals. The correlations between GEBV from GBLUP and IP obtained using SNP effects from core 2013 were ≥0.99 for animals born in 2013 but as low as 0.07 for animals born in 2014 and 2015. Conversely, the correlations between GEBV from ssGBLUP and IP were ≥0.99 for animals born in all years. IP predictive abilities computed with GEBV from ssGBLUP and SNP predictions based on only core animals were as high as those based on all genotyped animals. The correlations between GEBV and IP from ssGBLUP were ≥0.76, ≥0.90, and ≥0.98 when SNP effects were computed using 2k, 5k, and 15k core animals. Suitable IP based on GEBV from GBLUP can be obtained when SNP predictions are based on an appropriate number of core animals, but a considerable decline in IP accuracy can occur in subsequent years. Conversely, IP from ssGBLUP based on large numbers of phenotypes from non-genotyped animals have persistent accuracy over time.

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