Age-regulated expression of genetic and environmental variation in fitness traits. 1. Genetic effects and variances for egg production in a factorial mating of six selected Leghorn strains

1999 ◽  
Vol 79 (3) ◽  
pp. 253-267 ◽  
Author(s):  
L.-E. Liljedahl ◽  
R. W. Fairfull ◽  
R. S. Gowe
Keyword(s):  
Egg Production ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Genetic Effects ◽  
The Other ◽  
Additive Genetic Effect ◽  
Phenotypic Variance ◽  
Age Changes ◽  
Genotypic Variance ◽  
Factorial Mating

White Leghorn strains were crossed reciprocally in a complete factorial mating system producing 6 pure strains and 30 strain-crosses, which were kept in individual cages for two laying cycles, 133–496 and 547–909 d of age. The egg production in the second cycle (C2) of the various genotypes started about 10 – 20% lower and had a more linear and less persistent course than in the first cycle (C1). Strains exhibited very different patterns of age changes in both additive and non-additive genetic effects as well as in cytoplasmic effects. The additive autosomal and sex-linked genes (Ai and Zi) active in one laying cycle were quite different from those active in the other laying cycle as shown by low strain genetic correlations between their effects in C1 and C2. Further, the sets of Ai and Zi genes responded with effects quite opposite to each other in both C1 and C2 as indicated by highly negative strain genetic correlations between the Ai and Zi effects. The average non-additive genetic effect of sire strain i or dam strain j over all its crosses with other strains (hi) and the non-additive genetic effect due to the specific combination of genes occurring in each of the two reciprocal crosses between strain i and strain j (sij), showed very divergent patterns of age changes with a conspicuously greater divergence as age advanced. The overall non-additive genetic effect (mean heterosis) increased significantly with age across the two cycles. The strain crosses that most successfully maintained their rate of lay until the end of C2, also most successfully developed a rising age trend for total heterosis. The non-additive genes active in one laying cycle were significantly different from those active in the other laying cycle as shown by the moderately low strain genetic correlations between their effects in C1 and C2. The genotypic variance and its various components increased markedly with age, however, with a tendency to reach a plateau towards the end of both the first and the second laying cycle. The environmental variance increased parallel to the genotypic variance. Consequently, the phenotypic variance followed the same pattern of age changes. The results are discussed in relation to the theoretical aspects of ageing genetics. A model compatible with all the age trends of the genetic and environmental effects and variances is set up, assuming that ageing is composed of two main opposing forces. Finally, the results are briefly discussed from the animal breeding point of view. Key words: Ageing, fitness, laying hens, genetic effects, variation, expression

scholarly journals Genetic and nongenetic factors influencing ewe prolificacy and lamb body weight in a closed Romanov flock

2020 ◽  
Vol 98 (9) ◽  
Author(s):  
Thomas W Murphy ◽  
John W Keele ◽  
Brad A Freking
Keyword(s):  
Body Weight ◽  
Maternal Effects ◽  
Effective Means ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
The United States ◽  
Additive Genetic Effect ◽  
Parameter Estimates ◽  
Phenotypic Variance ◽  
Inbreeding Coefficients

Abstract The U.S. Meat Animal Research Center was the first entity in the United States to import the Romanov breed and it has been maintained as a closed flock for over 30 yr. Incorporating this super-prolific breed into crossbred and composite populations has resulted in large improvements in ewe productivity. However, few have quantified factors contributing to genetic and nongenetic variation in ewe reproduction and lamb growth within purebred Romanov populations, which were the objectives of this study. The pedigree contained a total of 8,683 lambs born to 218 and 1,600 unique sires and dams, respectively. Number of lambs born on a per ewe exposed (NLBE) and lambing (NLBL) basis were analyzed in univariate repeatability animal models. As expected, the proportion of phenotypic variance (σP2) in litter size attributable to additive genetic (0.06 to 0.08) and permanent environmental (0.05 to 0.07) effects of the ewe was low. The service sire permanent environmental effect contributed to a small but significant amount of σP2 in NLBE (0.03) but not NLBL. However, the service sire additive genetic effect did not influence σP2 in NLBE or NLBL. Lamb body weight was recorded at birth (BWB) and upon weaning from either milk replacer (~30 d; BWW-N) or their dam (~60 d; BWW-D) and were analyzed in a three-trait model with random additive direct and maternal effects. Estimated direct heritabilities were low for all body weight (BW) traits (0.07 to 0.10). Maternal heritability was moderate for BWB (0.34) but low for weaning BW (0.11 to 0.18). This was the first to report direct and maternal genetic correlations between BW of nursery- and dam-reared lambs, and both were estimated to be moderate (0.43 to 0.47). Additionally, the direct and maternal effects of BWB were more strongly correlated with BWW-N (0.74 to 0.82) than BWW-D (0.17 to 0.33). Despite inbreeding coefficients having increased at a rate of 0.33% per birth year (1986 to 2019) in this flock, they were not consistently associated with reductions in ewe or lamb performance. Parameter estimates generally agreed with those from less-prolific breeds, and results indicate that selection can be an effective means of improving subcomponents of ewe productivity.

scholarly journals Genetic Parameters for Clinical Mastitis, Fertility and Somatic Cell Score in Czech Holstein Cattle

2017 ◽  
Vol 17 (4) ◽  
pp. 1007-1018
Author(s):  
Ludmila Zavadilová ◽  
Miloslava Štípková ◽  
Alena Svitáková ◽  
Zuzana Krupová ◽  
Eva Kašná
Keyword(s):  
Somatic Cell ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Clinical Mastitis ◽  
Somatic Cell Score ◽  
Additive Genetic Effect ◽  
Phenotypic Variance ◽  
Quadratic Regression ◽  
The Czech Republic ◽  
Calving Season

AbstractCases of mastitis (CM) from 38,236 lactations belonging to 16,497 cows were recorded on seven farms in the Czech Republic from 1996 to 2014. Clinical mastitis was analyzed with linear animal model as an all-or-none trait for each recorded lactation (CM305) and separately for each trimester of lactation (CM1, CM2, and CM3). Bivariate linear animal models were used to estimate the genetic correlation between these CM traits and lactation means for somatic cell score (SCS305), the interval between calving and first insemination (INT) and days open (DO). Factors included in the linear model were parity, herd, year of calving, calving season, fixed linear and quadratic regression on age at first calving, fixed linear and quadratic regression on milk production in the corresponding parity, permanent environmental effect of the cow, and additive genetic effect of the cow. Estimated heritabilities of the CM traits ranged from 0.01 to 0.03. Permanent environmental effects accounted for approximately two-thirds of the phenotypic variance. Genetic correlations of SCS305 with CM traits were 0.85±0.029, 0.81±0.086, 0.82±0.087, and 0.67±0.088 for CM305, CM1, CM2, and CM3, respectively. Genetic correlations of INT with CM305, CM1, CM2, and CM3, respectively, were 0.22±0.065, 0.19±0.084, 0.20±0.121 and 0.15±0.121: and genetic correlations of DO and the four CM traits were 0.28±0.079, 0.26±0.101, 0.43±0.134, and 0.15±0.131. For the 140 sires in the dataset, Spearman rank correlations among breeding values for the four CM traits and for SCS305 were uniformly high at 0.99±0.001.

scholarly journals Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

2019 ◽  
Vol 67 (5) ◽  
pp. 1245-1251
Author(s):  
Ludmila Zavadilová ◽  
Eva Kašná ◽  
Zuzana Krupová
Keyword(s):  
Infectious Diseases ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Holstein Cows ◽  
Additive Genetic Effect ◽  
Genomic Information ◽  
White Line ◽  
Genomic Breeding ◽  
Breeding Values

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.

scholarly journals Genetic-Quantitative Uni- and Bi-Trait Analysis for Growth Traits in the Colombian Creole Breed Blanco Orejinegro (BON)

2021 ◽  
Author(s):  
Marisol Londoño-Gil ◽  
Juan Carlos Rincón Flórez ◽  
Albeiro López-Herrera ◽  
Luis Gabriel Gonzalez-Herrera
Keyword(s):  
Growth Traits ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Cattle Breed ◽  
Live Weight ◽  
Daily Weight Gain ◽  
Additive Genetic Effect ◽  
Selection Processes ◽  
Heritability Estimates ◽  
Maternal Heritability

Abstract The Blanco Orejinegro (BON) is a Colombian creole cattle breed that is not genetically well characterized for growth traits. The aim of this work was to estimate genetic parameters for birth weight (BW), weaning weight (WW), yearling weight (YW), daily weight gain between birth and weaning (DWG), time to reach 120 kg of live weight (T120), and time to reach 60% of adult weight (T60%), and establish the selection criteria for growth traits in the BON population of Colombia. Genealogical and phenotypic information for BW, WW, YW, DWG, T120, and T60% traits of BON animals from 14 Colombian herds were used. These traits were analyzed with the AIREML method in a uni- and bi-trait animal model including the maternal effect for BW, WW, DWG, and T120. The direct heritability estimates values were 0.22 ± 0.059 (BW), 0.20 ± 0.057 (WW), 0.20 ± 0.153 (YW), 0.17 ± 0.07 (DWG), 0.26 (T120), and 0.44 ± 0.03 (T60%). The maternal heritability estimates values were 0.14 ± 0.040 (BW), 0.15 ± 0.039 (WW), 0.25 ± 0.06 (DWG), and 0.16 (T120). The direct genetic correlations were high (>|0.60|) among all the traits, except between T60% with BW, WW, YW, and DWG (ranged from -0.02 to -0.51), all in a favorable direction. The results showed that there is genetic variation in the growth traits associated with the additive genetic effect and they might respond to selection processes. Furthermore, genetic gains would improve through selection, especially for YW and T60% when WW is used as criterion.

scholarly journals Heritability of egg production in laying hens under cumulative, multitrait and repeated measurement animal models

2008 ◽  
Vol 52 (No. 8) ◽  
pp. 254-260 ◽  
Author(s):  
A. Wolc ◽  
M. Lisowski ◽  
T. Szwaczkowski
Keyword(s):  
Animal Models ◽  
Variance Components ◽  
Egg Production ◽  
Genetic Parameters ◽  
Laying Hens ◽  
Genetic Effects ◽  
Repeated Measurement ◽  
Repeated Measurements ◽  
The Other ◽  
Highly Correlated

Six generations of three layer lines (13 770 recorded individuals of A22 line, 13 950 of A88, 9 351 of K66) were used to estimate genetic effects on egg production under cumulative, multitrait and repeatability models. Variance components were estimated by the AI-REML algorithm. The heritability of cumulative records ranged from 0.08 to 0.1. For the repeated measurements model the following genetic parameters were obtained: heritability 0.02–0.03, repeatability 0.04–0.38. The first two months of egg production were found to differ from the other periods: heritability was relatively high (<i>h</i><sup>2</sup> > 0.35) and low or negative correlations with the other periods were found. Heritability was low (<i>h</i><sup>2</sup> < 0.1) from the peak production until the end of recording and the consecutive periods were highly correlated. Further studies on monthly records are suggested.

scholarly journals Genetic parameters of meat quality, carcass composition, and growth traits in commercial swine

2019 ◽  
Vol 97 (9) ◽  
pp. 3669-3683 ◽  
Author(s):  
Piush Khanal ◽  
Christian Maltecca ◽  
Clint Schwab ◽  
Kent Gray ◽  
Francesco Tiezzi
Keyword(s):  
Meat Quality ◽  
Fixed Effects ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Carcass Composition ◽  
Additive Genetic Effect ◽  
Yield Traits ◽  
Data Set ◽  
Crossbred Pigs

Abstract Swine industry breeding goals are mostly directed towards meat quality and carcass traits due to their high economic value. Yet, studies on meat quality and carcass traits including both phenotypic and genotypic information remain limited, particularly in commercial crossbred swine. The objectives of this study were to estimate the heritabilities for different carcass composition traits and meat quality traits and to estimate the genetic and phenotypic correlations between meat quality, carcass composition, and growth traits in 2 large commercial swine populations: The Maschhoffs LLC (TML) and Smithfield Premium Genetics (SPG), using genotypes and phenotypes data. The TML data set consists of 1,254 crossbred pigs genotyped with 60K SNP chip and phenotyped for meat quality, carcass composition, and growth traits. The SPG population included over 35,000 crossbred pigs phenotyped for meat quality, carcass composition, and growth traits. For TML data sets, the model included fixed effects of dam line, contemporary group (CG), gender, as well as random additive genetic effect and pen nested within CG. For the SPG data set, fixed effects included parity, gender, and CG, as well as random additive genetic effect and harvest group. Analyses were conducted using BLUPF90 suite of programs. Univariate and bivariate analyses were implemented to estimate heritabilities and correlations among traits. Primal yield traits were uniquely created in this study. Heritabilities [high posterior density interval] of meat quality traits ranged from 0.08 [0.03, 0.16] for pH and 0.08 [0.03, 0.1] for Minolta b* to 0.27 [0.22, 0.32] for marbling score, except intramuscular fat with the highest estimate of 0.52 [0.40, 0.62]. Heritabilities of primal yield traits were higher than that of primal weight traits and ranged from 0.17 [0.13, 0.25] for butt yield to 0.45 [0.36, 0.55] for ham yield. The genetic correlations of meat quality and carcass composition traits with growth traits ranged from moderate to high in both directions. High genetic correlations were observed for male and female for all traits except pH. The genetic parameter estimates of this study indicate that a multitrait approach should be considered for selection programs aimed at meat quality and carcass composition in commercial swine populations.

Genetic parameters for calving difficulty using complex genetic models in five beef breeds in Australia

2016 ◽  
Vol 56 (5) ◽  
pp. 927 ◽  
Author(s):  
M. G. Jeyaruban ◽  
D. J. Johnston ◽  
B. Tier ◽  
H.-U. Graser
Keyword(s):  
Genetic Parameters ◽  
Linear Models ◽  
Random Effect ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Genetic Effects ◽  
Gestation Length ◽  
Calving Ease ◽  
Direct Genetic Effect ◽  
Calving Difficulty

Data on Angus (ANG), Charolais (CHA), Hereford (HER), Limousin (LIM) and Simmental (SIM) cattle were used to estimate genetic parameters for calving difficulty (CD), birthweight (BWT) and gestation length (GL) using threshold-linear models and to examine the effect of inclusion of random effect of sire × herd interaction (SxH) in the models. For models without SxH, estimated heritabilities for direct genetic effect of CD were 0.24 (±0.02), 0.22 (±0.04), 0.31 (±0.02), 0.22 (±0.04) and 0.17 (±0.01) for ANG, CHA, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.13 to 0.20. Estimated heritabilities for direct genetic effect of BWT were 0.38 (±0.01), 0.37 (±0.03), 0.46 (±0.01), 0.35 (±0.02) and 0.36 (±0.01) for ANG, CHR, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.08 to 0.11. Estimated heritabilities for direct genetic effect of GL were 0.59 (±0.02), 0.42 (±0.04), 0.50 (±0.03), 0.45 (±0.04) and 0.42 (±0.03) for ANG, CHR, HER, LIM and SIM, respectively, whereas maternal heritabilities ranged from 0.03 to 0.09. Genetic correlations between direct genetic effects of CD with BWT were highly positive and with GL were moderately positive for all five breeds. Estimated genetic correlations between direct genetic effects and maternal genetic effects (rdm) ranged across the five breeds from –0.40 (±0.05) to –0.16 (±0.02), –0.41 (±0.03) to –0.27 (±0.08) and –0.47 (±0.10) to –0.06 (±0.12) for BWT, GL and CD, respectively. Fitting SxH interaction as additional random effect significantly increased the log-likelihood for analyses of BWT, GL and CD of all breeds, except for GL of CHA. The estimated heritabilities were less than or equal to the estimates obtained with models omitting SxH. The rdm increased (i.e. became less negative) for BWT, GL and CD of all five breeds. However, the increase for GL was not substantially high in comparison to the increase observed for BWT and CD. Genetic parameters obtained for BWT, GL and CD, by fitting SxH as an additional random effect, are more appropriate to use in the genetic evaluation of calving ease in BREEDPLAN.

Estimates of genetic parameters for ultrasound-measured carcass traits in sheep

2004 ◽  
Vol 84 (3) ◽  
pp. 361-365 ◽  
Author(s):  
T. L. Fernandes ◽  
J. W. Wilton ◽  
J. J. Tosh
Keyword(s):  
Genetic Improvement ◽  
Variance Component ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Backfat Thickness ◽  
Additive Genetic Effect ◽  
Multiple Trait ◽  
Breed Group ◽  
Variance Component Estimates

Data on ultrasound traits (loin depth, average backfat thickness, and loin width) were collected from lambs (n = 3483) across Ontario, born between 1997 and 1999. The data were analysed with a REML procedure in a multiple-trait mixed-animal model to obtain (co)variance component estimates. Analyses of all traits included the additive genetic effect of the lamb, sex of the lamb, contemporary group, and breed group effects. Weight or age was included as a covariate in two separate analyses. Estimates of direct additive heritabilities for loin depth, average backfat thickness, and loin width were 0.29, 0.29 and 0.26 respectively, with genetic correlations of -0.17 between loin depth and average backfat thickness, 0.43 between loin depth and loin width, and 0.23 between loin width and average backfat thickness for the weight constant analysis. When the data were analysed using age in the regression analysis, corresponding estimates of direct additive heritabilities were 0.38, 0.35 and 0.30, and genetic correlations between traits were all positive, 0.29 between loin depth and average backfat thickness, 0.61 between loin depth and loin width, and 0.44 between loin width and average backfat thickness. Results indicate that it is possible to make genetic improvement if selection is based on ultrasound information. Key words: Sheep, genetic parameters, heritability, ultrasound

Genetic parameters of milk traits in Latxa dairy sheep

2001 ◽  
Vol 73 (3) ◽  
pp. 407-412 ◽  
Author(s):  
A. Legarra ◽  
E. Ugarte
Keyword(s):  
Milk Fat ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Selection Criterion ◽  
Genetic Effect ◽  
Milk Composition ◽  
Additive Genetic Effect ◽  
Dairy Sheep ◽  
Milk Traits

AbstractA total of 7444 lactation records which include milk, fat and protein yields (MY, FY, PY) and fat and protein content (F%, P%) from 6429 Black-Faced Latxa ewes were employed to estimate genetic parameters for milk traits. Traits were standardized to 120 days of lactation. For the calculation of composition traits, not all test-days had their composition measured and therefore a correction taking this into account was included in the analysis. A first-derivative restricted maximum likelihood algorithm was used on an animal model with repeatability analysis, using models including fixed effects (flock-year-season of lambing, age-parity at lambing, number of lambs, interval between lambing and first milk recording and the combination of sampled test-days) and random effects (the additive genetic effect and the permanent environmental effect). The resulting heritabilities were 0·20, 0·16, 0·18, 0·14 and 0·38 for MY, FY, PY, F% and P% respectively. Heritability of F% was much lower than expected, probably due to problems derived from the recording method. Genetic correlations were high and positive between yields and moderately positive between F% and P%, and negative or null between yields and composition, as has been reported for other European dairy sheep breeds. As most of the milk produced by Latxa dairy sheep is processed into cheese, the inclusion of milk sampling in official milk recording and a change in the selection criterion are recommended to avoid a long-term worsening in milk composition.

scholarly journals Genetic evaluation of eggshell color based on additive and dominance models in laying hens

2020 ◽  
Vol 33 (8) ◽  
pp. 1217-1223
Author(s):  
Jun Guo ◽  
Kehua Wang ◽  
Liang Qu ◽  
Taocun Dou ◽  
Meng Ma ◽  
...  
Keyword(s):  
Animal Model ◽  
Egg Production ◽  
Genetic Correlations ◽  
Phenotypic Variance ◽  
Dominance Model ◽  
Shell Color ◽  
Inbreeding Coefficients ◽  
L Value ◽  
Eggshell Color

Objective: Eggshells with a uniform color and intensity are important for egg production because many consumers assess the quality of an egg according to the shell color. In the present study, we evaluated the influence of dominant effects on the variations in eggshell color after 32 weeks in a crossbred population.Methods: This study was conducted using 7,878 eggshell records from 2,626 hens. Heritability was estimated using a univariate animal model, which included inbreeding coefficients as a fixed effect and animal additive genetic, dominant genetic, and residuals as random effects. Genetic correlations were obtained using a bivariate animal model. The optimal diagnostic criteria identified in this study were: L* value (lightness) using a dominance model, and a* (redness), and b* (yellowness) value using an additive model.Results: The estimated heritabilities were 0.65 for shell lightness, 0.42 for redness, and 0.60 for yellowness. The dominance heritability was 0.23 for lightness. The estimated genetic correlations were 0.61 between lightness and redness, –0.84 between lightness and yellowness, and –0.39 between redness and yellowness.Conclusion: These results indicate that dominant genetic effects could help to explain the phenotypic variance in eggshell color, especially based on data from blue-shelled chickens. Considering the dominant genetic variation identified for shell color, this variation should be employed to produce blue eggs for commercial purposes using a planned mating system.

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