scholarly journals Using Random Regression Models to Genetically Evaluate Functional Longevity Traits in North American Angus Cattle

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2410
Author(s):  
Hinayah R. Oliveira ◽  
Luiz F. Brito ◽  
Stephen P. Miller ◽  
Flavio S. Schenkel
Keyword(s):  
North American ◽  
Regression Models ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Random Regression ◽  
Pedigree Information ◽  
Residual Variance ◽  
Multiple Trait ◽  
Structural Problems ◽  
Angus Cattle

This study aimed to propose novel longevity indicators by comparing genetic parameters for traditional (TL; i.e., the cow’s lifespan after the first calving) and functional (FL; i.e., how long the cow stayed in the herd while also calving; assuming no missing (FLa) or missing (FLb) records for unknown calving) longevity, considering different culling reasons (natural death, structural problems, disease, fertility, performance, and miscellaneous). Longevity definitions were evaluated from 2 to 15 years of age, using single- and multiple-trait Bayesian random regression models (RRM). The RRM fitting heterogenous residual variance and fourth order Legendre polynomials were considered as the optimal models for the majority of longevity indicators. The average heritability estimates over ages for FLb (from 0.08 to 0.25) were always higher than those for FLa (from 0.07 to 0.19), and higher or equal to the ones estimated for TL (from 0.07 to 0.23), considering the different culling reasons. The average genetic correlations estimated between ages were low to moderate (~0.40), for all longevity definitions and culling reasons. However, removing the extreme ages (i.e., 2 and >12 years) increased the average correlation between ages (from ~0.40 to >0.70). The genetic correlations estimated between culling reasons were low (0.12 and 0.20 on average, considering all ages and ages between 3 and 12 years old, respectively), indicating that longevity based on different culling reasons should be considered as different traits in the genetic evaluations. Higher average genetic correlations (estimated from 3 to 12 years old) were observed between TL and FLb (0.73) in comparison to TL and FLa (0.64), or FLa and FLb (0.65). Consequently, a higher average proportion of commonly-selected sires, for the top 1% sires, was also observed between TL and FLb (91.74%), compared to TL and FLa (59.68%), or FLa and FLb (61.01%). Higher prediction accuracies for the expected daughter performances (calculated based on the pedigree information) were obtained for FLb in comparison to TL and FLa. Our findings indicate that FLb is preferred for the genetic evaluation of longevity. In addition, it is recommended including multiple longevity traits based on different groups of culling reasons in a selection sub-index, as they are genetically-different traits. Genetic selection based on breeding values at the age of four years is expected to result in greater selection responses for increased longevity in North American Angus cattle.

scholarly journals Components of (co)variance of the days open in Siboney dairy cows

2010 ◽  
Vol 62 (1) ◽  
pp. 136-143 ◽  
Author(s):  
D. González-Peña ◽  
J.L. Espinoza-Villavicencio ◽  
D. Guerra ◽  
A. Palacios ◽  
J.C. Évora ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Legendre Polynomials ◽  
Regression Models ◽  
Genetic Correlations ◽  
Random Regression ◽  
Residual Variance ◽  
Parity Number ◽  
Days Open ◽  
Univariate Model

The records of 63,406 calvings of Siboney dairy cows (5/8 Holstein 3/8 Cuban Zebu) were used to estimate the components of covariance of the days open (DO). Five models were used: of repeatability; univariate; bivariate; of random regression with Legendre polynomials and the parity number as predicting variable; and a model of random regression with Legendre polynomials and heterogeneity of the residual variance. The heritability obtained with the univariate model was 0.09 in the first calving and decreased to 0.05 in the fifth. A higher estimate of heritability (0.12) was obtained with the repeatability model. When the model of random regression with heterogeneity of the residual variance was used, the heritability was higher than the values estimated with the previous models. The genetic correlations among the DO in different calvings, estimated with the models of random regression with and without heterogeneity of the residual variance, were close to 1.0. It is concluded that the estimates of heritability increased with the use of the random regression models. The genetic correlations among the DO of different calvings indicated that in the first three, the DO are regulated for the most part by the same genes.

scholarly journals Genetic parameters for test-day model with random regressions for production traits of Czech Holstein cattle

2011 ◽  
Vol 50 (No. 4) ◽  
pp. 142-154 ◽  
Author(s):  
L. Zavadilová ◽  
J. Jamrozik ◽  
Schaeffer LR
Keyword(s):  
Milk Fat ◽  
Sampling Method ◽  
Random Regression ◽  
Model Parameters ◽  
Residual Variance ◽  
Posterior Distributions ◽  
Production Traits ◽  
Multiple Trait ◽  
Holstein Breed ◽  
Random Regression Model

Multiple-lactation random regression model was applied to test-day records of milk, fat and protein yields in the first three lactations of the Czech Holstein breed. Data included 9 583 cows, 89 584, 44 207 and 11 266 test-day records in the first, second and third lactation, respectively. Milk, fat and protein in the first three lactations were analysed separately and in a multiple-trait analysis. Linear model included herd-test date, fixed regressions within age-season class and two random effects: animal genetic and permanent environment modelled by regressions. Gibbs sampling method was used to generate samples from marginal posterior distributions of the model parameters. The single- and multiple-trait models provided similar results. Genetic and permanent environmental variances and heritability for particular days in milk were high at the beginning and at the end of lactation. The residual variance decreased throughout the lactation. The resulting heritability ranged from 0.13 to 0.52 and increased with parity.  

scholarly journals Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians

2016 ◽  
Vol 46 (9) ◽  
pp. 1649-1655
Author(s):  
Mariana de Almeida Dornelles ◽  
Paulo Roberto Nogara Rorato ◽  
Luis Telo Lavadinho da Gama ◽  
Fernanda Cristina Breda ◽  
Carlos Bondan ◽  
...  
Keyword(s):  
Milk Production ◽  
Legendre Polynomials ◽  
Fixed Effects ◽  
Regression Models ◽  
Genetic Parameters ◽  
Random Regression ◽  
Residual Variance ◽  
Lower Estimation ◽  
The One ◽  
Residual Variances

ABSTRACT: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the first lactation in the Holstein Friesian breed. Five thousand eight hundred and eighty biweekly records of test-day milk production were used. The models included the fixed effects of group of contemporaries and cow age at calving as covariable. Statistical criteria indicated that the WF.33_HE2, LEG.33_HE2, and LEG.55_HE4 functions best described the changes in the variances that occur throughout lactation. Heritability estimates using WF.33_HE2 and LEG.33_HE2 models were similar, ranging from 0.31 to 0.50. The LEG.55_HE4 model diverged from these models, with higher estimates at the beginning of lactation and lower estimates after the 16th fortnight. The LEG55_HE4, among the three better models indicated by the index, is the one with highest number of parameters (14 vs 34) and resulted in lower estimation of residual variance at the beginning and at the end of lactation, but overestimated heritability in the first fortnight and presented a greater difficulty to model genetic and permanent environment correlations among controls. Random regression models that used the Wilmink and Legendre polynomials functions with two residual variance classes appropriately described the genetic variation during lactation of Holstein Friesians reared in Rio Grande do Sul.

scholarly journals PSI-1 Evaluating genetic parameters and trends of weight traits for the Hays Converter beef breed by multiple-trait and random regression models.

2018 ◽  
Vol 96 (suppl_3) ◽  
pp. 60-61
Author(s):  
R Khorshidi ◽  
M MacNeil ◽  
D Hays ◽  
M Abo-Ismail ◽  
J Crowley ◽  
...  
Keyword(s):  
Regression Models ◽  
Genetic Parameters ◽  
Random Regression ◽  
Multiple Trait ◽  
Beef Breed

scholarly journals Genetic parameters for test day milk yield of first lactation Holstein cows estimated by random regression using Legendre polynomials

2008 ◽  
Vol 37 (4) ◽  
pp. 602-608 ◽  
Author(s):  
Claudio Napolis Costa ◽  
Claudio Manoel Rodrigues de Melo ◽  
Irineu Umberto Packer ◽  
Ary Ferreira de Freitas ◽  
Nilson Milagres Teixeira ◽  
...  
Keyword(s):  
Variance Components ◽  
Legendre Polynomials ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Holstein Cows ◽  
Residual Variance ◽  
Environmental Variance ◽  
Environmental Correlations ◽  
Lp Estimates

Data comprising 263,390 test-day (TD) records of 32,448 first parity cows calving in 467 herds between 1991 and 2001 from the Brazilian Holstein Association were used to estimate genetic and permanent environmental variance components in a random regression animal model using Legendre polynomials (LP) of order three to five by REML. Residual variance was assumed to be constant in all or in some classes of lactation periods for each LP. Estimates of genetic and permanent environmental variances did not show any trend due to the increase in the LP order. Residual variance decreased as the order of LP increased when it was assumed constant, and it was highest at the beginning of lactation and relatively constant in mid lactation when assumed to vary between classes. The range for the estimates of heritability (0.27 - 0.42) was similar for all models and was higher in mid lactation. There were only slight differences between the models in both genetic and permanent environmental correlations. Genetic correlations decreased for near unity between adjacent days to values as low as 0.24 between early and late lactation. A five parameter LP to model both genetic and permanent environmental effects and assuming a homogeneous residual variance would be a parsimonious option to fit TD yields of Holstein cows in Brazil.

scholarly journals Unraveling the genetic variability of host resilience to endo and ectoparasites under natural infestation, in Nellore cattle

2021 ◽  
Author(s):  
Gabriela Canabrava Gouveia ◽  
Virgínia Mara Pereira Ribeiro ◽  
Marina Rufino Salinas Fortes ◽  
Fernanda Santos Silva Raidan ◽  
Antonio Reverter-Gomez ◽  
...  
Keyword(s):  
Association Studies ◽  
Genetic Correlations ◽  
Parasite Burden ◽  
Random Regression ◽  
Economic Losses ◽  
Control Analysis ◽  
Genome Wide Association Studies ◽  
Multiple Trait ◽  
Eimeria Spp ◽  
Natural Infestation

Abstract Background: Host resilience (HR) to parasites can affect growth in pastured raised cattle. This study is a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) under natural infestation. HR was defined as the slope coefficient of random regression models of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients. The BW was evaluated in five measurement events (ME): when animals were 331, 385, 443, 498, and 555 days old on average. 7307 BW records were available from 1712 animals weighted at least in one ME. Out of those, 1075 animals had valid genotypic information after quality control analysis that were used in genome-wide association studies (GWAS) and GWAS meta-analyses to identify genomic regions associated with HR. Results: Both the genetic correlations between intercept and HR to each parasite, and the genetic correlations between BW measured in animals submitted to different parasite burden indicated that there was genotype x parasite burden interaction for BW, and selection for BW under environment with controlled parasite burden might be an efficient strategy to improve both, BW and HR. Furthermore, there was no impact of age of measurement on genetic variance estimates for HR to different parasites. However, genetic correlation between HR to the same parasite measured in different ages ranged from low to moderate in magnitude, with a posteriori means (high posterior density interval with 90% of samples) varying from 0.13 (-0.05; 0.35) to 0.40 (0.15; 0.63) for TICK, from 0.11 (-0.06; 0.29) to 0.52 (0.37; 0.67) for GIN and from 0.25 (0.07; 0.43) to 0.56 (0.34; 0.77) for EIM. These results indicate the importance of age of measurement in studies on HR. Conclusions: HR to GIN and EIM can be used as a complementary tool to parasitic control management, and a multiple trait selection method that combine BW and HR to parasites should be used in parasitic endemic areas to avoid economic losses due parasitic diseases.

Genetic parameters for faecal worm egg count at different ages in Australian sheep under natural challenge

2019 ◽  
Vol 59 (7) ◽  
pp. 1201 ◽  
Author(s):  
L. Li ◽  
D. J. Brown ◽  
A. A. Swan ◽  
J. H. J. van der Werf
Keyword(s):  
Genetic Correlations ◽  
Random Regression ◽  
Research Centre ◽  
Steady Increase ◽  
Cooperative Research ◽  
Multiple Trait ◽  
Full Data ◽  
Different Ages ◽  
Australian Sheep ◽  
Univariate Analyses

The data used in the present study consisted of 24535 worm egg count records on sheep observed from 63 to 560 days of age under conditions of the natural challenge of trichostrongylid species. Records were extracted from the Information Nucleus Flock database of the Australia Sheep Cooperative Research Centre program from 2007 to 2011. Records were observed at various ages and subdivided into weaning (W, ~3 months), post-weaning (P, ~4 months), yearling (Y, ~12 months) and hogget (H, ~18 months) age stages and were used to investigate genetic variation at different age stages in univariate analyses and estimate genetic correlations between age stages in multi-trait analyses. The full data were also analysed by random regression models to study how heritability and genetic correlations varied with age. Heritability estimates from univariate analyses were 0.20 ± 0.05, 0.15 ± 0.02, 0.36 ± 0.09, 0.22 ± 0.06 for W, P, Y and H age stages respectively. A similar trend of heritability over ages was found from random regression analyses, which decreased from 0.16 at 90 days to 0.09 at 120 days, following a steady increase to 0.32 at ~410 days, and then decreased afterwards to 0.24 at 520 days. Strong genetic correlations (>0.8) were found between W and P age stages, along with Y and H age stages. Sire by flock interaction effects were significant, and accounted for the reduced estimates of heritability and increased genetic correlations between age stages. The results indicated that a multiple-trait approach is required for genetic evaluation of worm egg count when measurements are at different ages, and the accuracy of evaluations would benefit from recording at least two separate age stages.

PSXV-1 Genetic evaluation of longevity of cows culled due to fertility-related problems using random regression models and censored data

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 261-261
Author(s):  
Hinayah R Oliveira ◽  
Stephen P Miller ◽  
Luiz F Brito ◽  
Flavio S Schenkel
Keyword(s):  
Censored Data ◽  
Regression Models ◽  
Genetic Evaluation ◽  
Random Regression ◽  
Breeding Values ◽  
Structural Problems ◽  
Time Period ◽  
And Performance ◽  
Genetic Evaluations ◽  
The Impact

Abstract A recent study showed that longevity based on different culling reasons should be considered as different traits in genetic evaluations. However, it is still necessary to create a pipeline that avoid including/excluding animals culled for different reasons in every genetic evaluation run. This study aimed to: 1) perform a genetic evaluation of the longevity of cows culled due to fertility-related problems including records of animals culled for other reasons (i.e., age, structural problems, disease, and performance) as censored records; and, 2) identify the impact of censored data in the genetic parameters and breeding values estimated. Two longevity indicators were evaluated: traditional (TL; time from first calving to culling) and functional (FL; time period in which the cow was alive and also calving after its first calving) longevity. Both TL and FL were evaluated from 2 to 15 years-old, and codified as binary traits for each age (0 = culled and 1 = alive/calved). Both trait definitions were analyzed using a Bayesian random regression linear model. Animals culled for reasons other than fertility were either excluded from the data (standard) or had their records censored after the culling date reported in the dataset (censored). After the quality control, 154,419 and 450,124 animals had uncensored and censored records, respectively. Heritabilities estimated for TL over the ages ranged from 0.02 to 0.13 for standard, and from 0.01 to 0.12 for censored datasets. Heritabilities estimated for FL ranged from 0.01 to 0.14 (standard), and from 0.01 to 0.13 (censored). Average (SD) correlation of breeding values predicted over all ages, using the standard and censored datasets, was 0.77 (0.16) for TL, and 0.83 (0.11) for FL. Our findings suggest that including censored data in the analyses might impact the genomic evaluations and further work is need to determine the optimal predictive approach.

scholarly journals Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

2013 ◽  
Vol 96 (9) ◽  
pp. 5923-5932 ◽  
Author(s):  
Rusbel Raul Aspilcueta Borquis ◽  
Francisco Ribeiro de Araujo Neto ◽  
Fernando Baldi ◽  
Naudin Hurtado-Lugo ◽  
Gregório M.F. de Camargo ◽  
...  
Keyword(s):  
Milk Fat ◽  
Regression Models ◽  
Genetic Parameters ◽  
Protein Yield ◽  
Random Regression ◽  
Multiple Trait ◽  
Estimation Of Genetic Parameters
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