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 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.

scholarly journals Estimates of (co)variance components and genetic parameters for growth traits in Suffolk lambs

2013 ◽  
Vol 43 (12) ◽  
pp. 2215-2220 ◽  
Author(s):  
Priscilla Regina Tamioso ◽  
Jaime Luiz Alberti Filho ◽  
Laila Talarico Dias ◽  
Rodrigo de Almeida Teixeira
Keyword(s):  
Maternal Effects ◽  
Variance Components ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Ratio Test ◽  
Effect Model ◽  
Estimate Heritability ◽  
Heritability Estimates

The study aimed to estimate the components of (co)variance and heritability for weights at birth (BW), weaning (WW) and 180 days of age (W180), as well as the average daily gains from birth to weaning (ADG1), birth to 180 days of age (ADG2) and weaning to 180 days of age (ADG3) in Suffolk sheep. Thus, three different single-trait animal models were fitted, considering the direct additive genetic effect (Model 1), the direct additive genetic and maternal permanent environmental effects (Model 2), and in Model 3, in addition to those in Model 2, the maternal additive genetic effect was included. After comparing models through the likelihood ratio test (LRT), model 3 was chosen as the most appropriate to estimate heritability for BW, WW and ADG1. Model 2 was considered as the best to estimate the coefficient of heritability for W180 and ADG2, and model 1 for ADG3. Direct heritability estimates were inflated when maternal effects were ignored. According to the most suitable models, the heritability estimates for BW, WW, W180, ADG1, ADG2 and ADG3 were 0.06, 0.08, 0.09, 0.07, 0.08 and 0.07, respectively, indicating low possibility of genetic gain through individual selection. The results show the importance of including maternal effects in the models to properly estimate genetic parameters even at post-weaning ages.

Genetic association between cows’ stayability to three years of age and juvenile growth traits in Canadian Angus herds

2005 ◽  
Vol 85 (2) ◽  
pp. 139-143 ◽  
Author(s):  
D. P. Rasali ◽  
G. H. Crow ◽  
J. N. B. Shrestha ◽  
A. D. Kennedy ◽  
A. Brûlé-Babel
Keyword(s):  
Fixed Effects ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Genetic Effects ◽  
Birth Season ◽  
Angus Cattle ◽  
Body Weights ◽  
Direct Genetic Effect ◽  
Maternal Heritability

Bivariate linear animal models were fit using MTDFREML programs for the analysis of cows’ stayability to 3 yr (STAY3, n = 1, 703) as a binary scored trait paired with body weights at birth (BW, n = 6,116), 205-d weaning (WW, n = 5,360,) and 1 yr of age (YW, n = 5250) in Angus cattle. For STAY3, the model included a fixed effect due to herd ×year of cow’s birth along with a random direct genetic effect. For each of BW, WW and YW, the model included fixed effects due to herd ×birth year, birth season, birth type, calf’s sex and the age of dam (as linear and quadratic covariates), while the random effects were direct and maternal genetic effects and permanent maternal environmental effects. Survival analysis revealed that the risk of cows, 10 yr or less in age, being culled from five Canadian Angus herds was highest between 2 and 3 yr of age. The direct heritability (h2) estimates for BW, WW and YW were 0.54, 0.73 and 0.47, respectively, and corresponding maternal heritability estimates were 0.14, 0.33 and 0.13, respectively. Furthermore, the direct h2 estimate for STAY3 from three bivariate analyses was 0.23–0.24. Estimates of direct-maternal genetic correlations of BW, WW and YW were -0.18, -0.70 and -0.39, respectively. The direct genetic correlations of STAY3 with BW, WW and YW were -0.15 to -0.09 indicating that selection for growth would have less detrimental influence on the stayability trait of cows. The correlations of direct genetic effects of STAY3 with maternal genetic effects of BW, WW and YW were between 0.20 and 0.25, indicating their favorable relationships as correlated traits. Key words: Stayability, growth traits, heritability, genetic correlations, beef cattle

Effects of dietary energy planes on growth and heritability estimates for postweaning growth traits in young beef bulls

1995 ◽  
Vol 75 (3) ◽  
pp. 469-472
Author(s):  
D. R. C. Bailey ◽  
M. F. Liu ◽  
N. H. Shannon
Keyword(s):  
Growth Rate ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Dietary Energy ◽  
Relative Growth ◽  
Heritability Estimates ◽  
Energy Plane ◽  
Maternal Heritability ◽  
Daily Gain

Records of young AN and young HE bulls were analyzed to evaluate the influences of dietary energy planes on growth and heritability estimates of growth traits during 168-d postweaning test. Estimates of h2a for end of test weight (WT168), average daily gain on test (ADG 0–168) and relative growth rate on test (RGR 0–168) were much higher in the MED line than in the HED line. Between lines, maternal heritability estimates (h2m) for WT0 and ADG 0–168 were similar. Estimates of h2m for WT168 was much higher in the HED line than in the MED line. All direct-maternal genetic correlations (ram) were negative. These results may indicate that the antagonism between direct and maternal genetic effects for postweaning growth traits in the MED line was much less than that in the HED line. Key words: Beef cattle, energy plane, growth, heritability

scholarly journals Estimation of genetic parameters for growth and carcass traits in turbot (<i>Scophthalmus maximus</i>)

2019 ◽  
Vol 62 (1) ◽  
pp. 265-273 ◽  
Author(s):  
Kristina Schlicht ◽  
Nina Krattenmacher ◽  
Vincent Lugert ◽  
Carsten Schulz ◽  
Georg Thaller ◽  
...  
Keyword(s):  
Body Weight ◽  
Growth Traits ◽  
Carcass Traits ◽  
Genetic Correlations ◽  
Daily Weight Gain ◽  
Separate Analysis ◽  
Production Traits ◽  
Long Term Study ◽  
Heritability Estimates ◽  
Fillet Yield

Abstract. Information on phenotypic and genetic (co)variance for production traits in turbot is required to improve breeding programs. So far, information on morphometric growth traits is sparse and completely lacking on quality carcass traits like fillet weight or fillet yield for turbot. As part of a long-term study we explored the phenotypic and genetic (co)variance of 16 biometrical and carcass traits of three different European turbot strains. Fish were reared under commercial grow-out conditions, including size grading. We used molecular relatedness (MR) methods based on genotyping with 96 microsatellite markers and animal models. We included an adapted condition factor for Pleuronectiformes (FCIPLN) and average daily weight gain (ADG) between the ages of 300 and 500 d post-hatch (dph) for their potential correlation with body weight at harvest. Heritability estimates for all traits were low to medium (0.04–0.29) when strains were jointly analyzed. Separate analysis of strains yielded higher heritability estimates (0.12–0.43). Genetic correlations between weight-related traits were highly positive (0.70–0.99), while runs with yield and ratio traits often resulted in unreliable estimates of genetic correlation due to high standard errors. Body weight (h2=0.19), fillet yield (h2=0.15), and dressing percentage (h2=0.17) are particularly promising selection traits for turbot breeding.

scholarly journals Genetic evaluation of body weight traits in Iranian native Ghezel sheep

Genetika ◽  
2018 ◽  
Vol 50 (1) ◽  
pp. 275-284 ◽  
Author(s):  
H. Baneh ◽  
J. Ahmadpanah
Keyword(s):  
Body Weight ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Univariate Analysis ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Pedigree Information ◽  
Breeding Values ◽  
Maternal Heritability ◽  
Genetic Trends

The aim of the current study was to estimate genetic parameters and trends for body weight traits at different ages in Ghezel lambs. Traits included were birth weight (BW), 3-month weight (3MW), 6-month weight (6MW), 9-month weight (9MW), and yearling weight (YW). Data and pedigree information used in the present study were collected at the Breeding Station of Ghezel sheep during 1986-2009. (Co) variance components were estimated using REML procedure and breeding values of animals were predicted with Best Linear Unbiased Prediction (BLUP) methodology under univariate analysis. Three different animal models were fitted. The models consisted of the direct additive genetic effect but differed in combinations of maternal additive genetic and maternal permanent environmental effects. Genetic trends for each trait were obtained by regressing the means of predicted breeding values on year of birth. The estimates of direct heritability were 0.285, 0.371, 0.388, 0.450 and 0.179, respectively. Also, the maternal heritability was estimated 0.113, 0.031, 0.021 and 0.030 for BW, WW, 6MW and 9MW, respectively. Direct genetic trends were positive and significant for BW, WW, 6MW (p<0.01), 9MW and YW (p<0.05) and were obtained 2.34, 46.20, 55.11, 33.40 and 24.01 (g/year), respectively. Also, maternal trends for BW, WW, 6MW and YW were positive and highly significant (p<0.01) and were 3.37, 17.05, 12.56 and 16.30 (g/year), respectively. The results indicated that considering maternal effects in the statistical model make accurate estimates of genetic parameters. Also, improvement of growth traits in Ghezel sheep seems to be likely in selection programs.

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 Estimates of (co)variance components and genetic parameters for body weights and growth efficiency traits in the New Zealand white rabbit

2017 ◽  
Vol 25 (4) ◽  
pp. 329 ◽  
Author(s):  
M. Sakthivel ◽  
D. Balasubramanyam ◽  
P. Kumarasamy ◽  
H. Gopi ◽  
A. Raja ◽  
...  
Keyword(s):  
Body Weight ◽  
New Zealand ◽  
Variance Components ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Effect ◽  
Growth Efficiency ◽  
Body Weights ◽  
Heritability Estimates

The genetic parameters of growth traits in the New Zealand White rabbits kept at Sheep Breeding and Research Station, Sandynallah, The Nilgiris, India were estimated by partitioning the variance and covariance components. The (co)variance components of body weights at weaning (W42), post-weaning (W70) and marketing (W135) age and growth efficiency traits viz., average daily gain (ADG), relative growth rate (RGR) and Kleiber ratio (KR) estimated on a daily basis at different age intervals (42 to 70 d; 70 to 135 d and 42 to 135 d) from weaning to marketing were estimated by restricted maximum likelihood, fitting 6 animal models with various combinations of direct and maternal effects. Data were collected over a period of 15 yr (1998 to 2012). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for W42, W70 and W135 were 0.42±0.07, 0.40±0.08 and 0.27±0.07, respectively. Heritability estimates of growth efficiency traits were moderate to high (0.18 to 0.42). Of the total phenotypic variation, maternal genetic effect contributed 14 to 32% for early body weight traits (W42 and W70) and ADG1. The contribution of maternal permanent environmental effect varied from 6 to 18% for W42 and for all the growth efficiency traits except for KR2. Maternal permanent environmental effect on most of the growth efficiency traits was a carryover effect of maternal care during weaning. Direct maternal genetic correlations, for the traits in which maternal genetic effect was significant, were moderate to high in magnitude and negative in direction. Maternal effect declined as the age of the animal increased. The estimates of total heritability and maternal across year repeatability for growth traits were moderate and an optimum rate of genetic progress seems possible in the herd by mass selection. The genetic and phenotypic correlations among body weights and between growth efficiency traits were also estimated. Moderate to high heritability and higher genetic correlation in body weight traits promise good scope for genetic improvement provided measures are taken to keep the inbreeding at the lowest level.

Genetic parameters for daily live-weight gain, live fleshiness and bone thinness in station-tested Piemontese young bulls

2001 ◽  
Vol 72 (3) ◽  
pp. 449-456 ◽  
Author(s):  
A. Albera ◽  
R. Mantovani ◽  
G. Bittante ◽  
A. F. Groen ◽  
P. Carnier
Keyword(s):  
Weight Gain ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Live Weight ◽  
Adaptation Period ◽  
Production Traits ◽  
Multiple Trait ◽  
Live Weight Gain ◽  
Total Gain

AbstractEstimates of genetic parameters for beef production traits were obtained for Piemontese cattle. Data were from 988 young bulls station-tested from 1989 till 1998. Bulls entered the station at 6 to 8 weeks of age and, after an adaptation period of 3 months, were tested for growth, live fleshiness and bone thinness. Length of test was 196 days. Growth traits considered were gain at farm, gain during the adaptation period, gain on test and total gain at the station. Six different fleshiness traits and bone thinness were scored on live animals at the end of the test using a linear system. Live evaluations of fleshiness were adjusted for the weight at scoring in order to provide an assessment of conformation independent of body size. Genetic parameters were estimated using animal models. Heritability of live-weight gain ranged from 0·20 in the adaptation period to 0·60 for total gain at the station. Genetic correlations between gains at station in different periods were high (from 0·63 to 0·97). Residual correlation between gain during the adaptation period and gain during test was negative, probably due to the occurrence of compensatory growth of the animals.Live fleshiness traits and bone thinness were of moderate to high heritability (from 0·34 to 0·55) and highly correlated indicating that heavy muscled bulls also have thin bones. Accuracy of breeding values and therefore response to selection were improved by multiple trait analysis of the live fleshiness traits and bone thinness. Overall weight gain at the station had a moderate negative genetic correlation with all live fleshiness traits and bone thinness (from –0·11 to –0·39).

Efecto de dos estrategias de agrupación de padres fantasmas en la evaluación genética de rasgos de crecimiento en el ganado Braunvieh mexicano

2021 ◽  
Vol 12 (3) ◽  
pp. 878-892
Author(s):  
Luis Antonio Saavedra-Jiménez ◽  
Rodolfo Ramírez-Valverde ◽  
Rafael Núñez-Domínguez ◽  
Agustín Ruíz-Flores ◽  
José Guadalupe García-Muñiz ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Growth Traits ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Genetic Trend ◽  
Phenotypic Data ◽  
Genetic Groups ◽  
Grouping Strategies ◽  
Parent Groups ◽  
Different Sources

The study aimed to compare two grouping strategies for unknown parents or phantom parent groups (PPG) on the genetic evaluation of growth traits for Mexican Braunvieh cattle. Phenotypic data included birth (BW), weaning (WW) and yearling (YW) weights. Pedigree included 57,341 animals. The first strategy involved 12 PPG (G12) based on the birth year of the unknown parent’s progeny and the sex of the unknown parent, while the second involved 24 PPG (G24) based on the birth year of the unknown parent’s progeny and 4-selection pathways. The animal models included fixed effects and the random direct additive genetic effect; WW also included random maternal genetic and maternal permanent environmental effects. Product-moment correlations between EBV from G0 (no PPG) and G12 were 0.96, 0.77 and 0.69 for BW, WW and YW, respectively, and between EBV from G0 and G24 were 0.91, 0.54, and 0.53, respectively. Corresponding rank correlations between G0 and G12 were 0.94, 0.77, and 0.72, and between G0 and G24 were 0.89, 0.61, and 0.60. Genetic trends showed a base deviation from the genetic trend of G0, except for BW of G12. The results did not support the use of the two grouping strategies on the studied population and traits, and further research is required. Introducing PPG to the model, enough phenotype contribution from descendants to PPG, and avoiding collinearity between PPG and fixed effects are important. Genetic groups should reflect changes in the genetic structure of the population to the unknown parents, including different sources of genetic materials, and changes made by selection over time.

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