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

Author(s):  
Ludmila Zavadilová ◽  
Eva Kašná ◽  
Zuzana Krupová

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.

2019 ◽  
Vol 97 (9) ◽  
pp. 3669-3683 ◽  
Author(s):  
Piush Khanal ◽  
Christian Maltecca ◽  
Clint Schwab ◽  
Kent Gray ◽  
Francesco Tiezzi

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.


2001 ◽  
Vol 73 (3) ◽  
pp. 407-412 ◽  
Author(s):  
A. Legarra ◽  
E. Ugarte

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.


2019 ◽  
Vol 64 (No. 5) ◽  
pp. 199-206 ◽  
Author(s):  
Michaela Brzáková ◽  
Ludmila Zavadilová ◽  
Josef Přibyl ◽  
Petr Pešek ◽  
Eva Kašná ◽  
...  

Genetic parameters for fertility traits in Czech Holstein population were estimated. The database obtained from the Czech-Moravian Breeders Corporation with 6 414 486 insemination records between years 2005–2015 was used. Date of calving of the selected animals was taken from the database of milk records from 2005–2015. Fertility traits were age at first service (AFS), age at first calving (AFC), days open (DO), calving interval (CI) and first service to conception interval in cows (FSC-C) and heifers (FSC-H). The heritability of each trait was estimated using single-trait animal models. The model included fixed effects of herd-year-season of birth, herd-year-month of calving, lactation order, parity, last calving ease, linear and quadratic regressions on age at first insemination in heifers or on age at first calving in cows. Random effects were animal, permanent environmental effect and random residual error. After edits, the final data set included up to 599 901 observations from up to 448 037 animals dependent on traits. The range of heritability estimates was from 0.010 to 0.058. The lowest heritability was for first service to conception interval in heifers, and the highest heritability was for age at first service. Variances of random permanent effects were higher than variance of additive genetic effect in all traits manifested in mature cows. Repeatability ranged from 0.060 to 0.090. Genetic correlations between traits were estimated using a bivariate animal model. High positive genetic correlations were found between AFS–AFC, DO–CI, FSC-C–DO and FSC-C–CI. A moderate genetic correlation was found between AFS–FSC-H and between AFC. A negative correlation was found between AFS–FSC-C. Correlations between other traits were close to zero. The results suggest that the level of these reproductive traits can be improved by selection of animals with high genetic merit.


2008 ◽  
Vol 16 (2) ◽  
pp. 89 ◽  
Author(s):  
M-L. SEVÓN-AIMONEN ◽  
M. HONKAVAARA ◽  
T. SERENIUS

Selection potential for meat quality of economically important loin (longissimus) and ham muscles (adductor, semimembranosus, biceps femoris) has been assessed. Ultimate pH (pHu), meat colour (lightness, redness and yellowness), drip loss and two visually scored colour traits were recorded from 483 Finnish Landrace and 494 Finnish Large White station test pigs in a half-sib design. A univariate restricted maximum likelihood procedure was used to estimate variance components. The statistical model contained age at beginning of test, sex and time lapse from slaughter to dissection as fixed effects and slaughter batch, common environment of littermates and additive genetic effect of the animal as random effects. The average pHu values in adductor and semispinalis were between 5.6 and 6.1. The pHu were on average 5.4 and 5.5 in longissimus and semimembranosus respectively, with the latter two being lower than optimum values of 5.6 to 5.9. Lightness for semimembranosus turned to be clearly lighter (62) than for other muscles. Lightness for longissimus (56) was slightly lighter than optimum (from 48 to 54). The heritability varied from zero to 0.45 for pHu, from 0.02 to 0.34 for lightness, from 0.17 to 0.56 for redness, from zero to 0.28 for yellowness and from 0.05 to 0.16 for drip loss. Heritability for redness values was considerably higher than heritability for other meat quality traits. The heritability of quality traits spoke for possibilities for genetic improvement of meat quality. Genetic correlations between quality traits (pHu and lightness) and average daily gain varied strongly among breeds and muscles. Genetic correlations between meat-% and pHu were in most cases high and unfavourable (rg from –0.36 to –0.68 except in longissimus, where it was 0.11). Genetic correlations between meat-% and lightness were unfavourable in Finnish Large White (from 0.47 to 0.92) but in Finnish Landrace estimates varied among muscles (from –0.40 to 0.47). Due to these results, the ham quality (pHu and lightness for semimembranosus) was included in the selection criteria for pork quality in the Finnish pig improvement programme.;


2021 ◽  
Vol 12 ◽  
Author(s):  
Mojca Simčič ◽  
Barbara Luštrek ◽  
Miran Štepec ◽  
Betka Logar ◽  
Klemen Potočnik

The aim of this study was to estimate genetic parameters of 26 individual and four composite type traits in first parity Cika cows. An analysis of variance was performed with the generalized linear model procedure of the SAS/STAT statistical package, where the fixed effects of year of recording, cow’s age at recording and days after calving as a linear regression were included in the model. The variance components for the direct additive genetic effect and the herd effect in all type traits were estimated using the REML method in the VCE-6 software package. The estimated heritabilities ranged from 0.42 to 0.67 for the measured body frame traits, from 0.36 to 0.80 for the scored autochthonous traits, from 0.11 to 0.61 for the scored body frame traits, and from 0.20 to 0.47 for the scored udder traits. The estimated heritabilities for the composite traits called “autochthonous characteristics”, “muscularity”, “body frame” and “udder” were 0.55, 0.19, 0.19, and 0.26, respectively. The estimated genetic correlations among the measured body frame traits were positive and high, while the majority of them among the scored body frame traits were low to moderate. The estimated proportions of variance explained by the herd effect for the composite traits “autochthonous characteristics,” “muscularity,” “body frame” and “udder” were 0.09, 0.28, 0.14, and 0.10, respectively. The estimated heritabilities for the type traits of first parity Cika cows were similar to those reported for other breeds where breeding values have been routinely predicted for a long time. All estimated genetic parameters are already used for breeding value prediction in the Cika cattle population.


2021 ◽  
Author(s):  
Marisol Londoño-Gil ◽  
Juan Carlos Rincón Flórez ◽  
Albeiro López-Herrera ◽  
Luis Gabriel Gonzalez-Herrera

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.


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 ◽  
...  

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.


2009 ◽  
Vol 89 (2) ◽  
pp. 215-218 ◽  
Author(s):  
A. Wolc ◽  
G. Torzynski ◽  
T. Szwaczkowski

Reproductive efficiency is an important issue in horse breeding. However, almost no estimates of genetic parameters of reproductive traits in horses can be found in the literature. The objective of the study was to estimate heritability and genetic trends of foaling rate and number of reproductive seasons in Warmblood horses. The records of 3965 mares from six studs were analyzed. Mares were on average kept for 7.3 reproductive seasons with a foaling rate of 66%. Models included fixed effects of stud, period of birth, breed and random additive genetic effect. Heritability estimates were 0.12 for foaling rate and 0.17 for number of reproductive seasons. Key words: Heritability, reproduction, horse


2004 ◽  
Vol 84 (3) ◽  
pp. 361-365 ◽  
Author(s):  
T. L. Fernandes ◽  
J. W. Wilton ◽  
J. J. Tosh

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


1999 ◽  
Vol 29 (6) ◽  
pp. 724-736 ◽  
Author(s):  
P X Lu ◽  
D A Huber ◽  
T L White

Potential biases associated with incomplete linear models in the estimation of heritability and the prediction of breeding values have been investigated. Results indicate that estimates of additive genetic variance and heritability as well as predicted parental breeding values from incomplete models will inevitably be biased as long as the true variance components of ignored effects are not zero. While models ignoring the interaction effect of males and females (SCA) × environment (E) interaction downwardly biased the estimates of additive genetic variance and heritability, models ignoring SCA and (or) the additive genetic effect (GCA) × E interaction yielded upward biases. The magnitudes of biases are functions of population genetic architecture, mating design, and field experimental design and can be precisely assessed with formulae derived for balanced data. Numerical simulations using unbalanced data of different mating and field experimental designs suggest that the formulae from balanced data can be used to approximate the minimum biases associated with unbalanced data. Because of the magnitudes of biases for some typical forest genetic scenarios, it is suggested that models ignoring SCA and (or) GCA × E should be avoided when the numbers of test sites and crosses per parent are small. However, incomplete model ignoring SCA × E interaction may be used to reduce computational demand with only negligible consequences.


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