Bayesian and REML analysis of twinning and fertility in Thoroughbred horses

Mucha, Sebastian; Wolc, Anna; Szwaczkowski, T.

doi:10.1016/j.livsci.2011.10.015

Cited by 12 publications

(9 citation statements)

References 14 publications

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“…Given the limited amount of information available in our study to estimate genetic parameters and the nature of the data used (semi-continuous distribution in a narrow scale), the use of a Bayesian approach to estimate genetic parameters is expected to outperform the REML methods used until now, given its good properties (Blasco, 2001) and good performance when applied to binary traits in horses, among other applications (Mucha et al, 2012) but especially when data are not in full agreement with normality (Van Tassel and Van Vleck, 1996;Faria et al, 2007). In our study, estimates of genetic parameters and their precision were similar with both methods, and the corresponding breeding values were highly correlated.…”

Section: Bayesian Estimations Vs Remlmentioning

confidence: 99%

Genetic parameters for harmony and gaits in Hispano-Arabe horses estimated by Bayesian methods and Restricted Maximum Likelihood

et al. 2016

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Section: Bayesian Estimations Vs Remlmentioning

confidence: 99%

Genetic parameters for harmony and gaits in Hispano-Arabe horses estimated by Bayesian methods and Restricted Maximum Likelihood

et al. 2016

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“…A low fertility with respect to other livestock species is well known in horses and may have a negative impact on the profitability of breeding [ 18 , 19 ]. A major weakness in reproduction is the strong impact of management decisions such as the time or the method on insemination on the measured traits [ 2 , 18 ].…”

Section: Discussionmentioning

confidence: 99%

“…Sperm quality, e.g., can be very variable due to stallion-specific genetic and non-genetic effects [ 36 ]. It is well known that inbreeding depression mainly occur on fitness traits like fertility and longevity [ 2 , 18 , 19 ], and for this reason, genetic analyses on fertility traits generally include the inbreeding effect [ 18 ]. Finally, both additive and non-additive effects may affect fertility, depending on the population structure, and considering a dominance relationship matrix within the genetic analysis may prevent an inflated estimation of the heritability of the trait [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

“…As examples of the few studies in horses, genetic components for foaling rates were studied in Polish Warmblood horses [ 17 ], in Standardbred trotters and Finnhorses [ 18 ], also considering the effect of the inbreeding on fertility. The liability of being pregnant was studied in Thoroughbred horses [ 19 ] and the lifetime reproductive efficiency in Arabian broodmares [ 20 ]. Beef cattle shares with horses the common characteristics of a strong seasonality, in spite of a different reproductive efficiency, timing of ovulation, insemination protocols, and gestation length [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

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Genetics of Lifetime Reproductive Performance in Italian Heavy Draught Horse Mares

Mantovani

Folla

Pigozzi³

et al. 2020

Animals

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Our aims were to find a phenotypic variable to express mares’ lifetime reproductive performance after 6 breeding seasons (BS) in Italian Heavy Draught Horse breed (IHDH), and to estimate its heritability. At first, 1487 mares in a training dataset were used to implement and validate a set of predictive coefficients (LFR-C) or equations (LFR-E) to estimate a lifetime foaling rate (LFR) after 6 BS, i.e., the number of foals generated divided by the opportunities to do so. Then, 3033 mares in a dataset with at least 3 registered BS, was used to estimate LFR for mares with 3, 4, or 5 registered RS. This dataset contained actual (n = 1950) and estimated (n = 1443) LFR, obtained by LFR-C, and LFR-E; Arcsine transformation of LFR-C and LFR-E were also analyzed in single trait animal models to estimate heritability. Overall, the LFR showed a moderate but significant genetic variation, and the heritability of the trait was high (0.24) considering it is a fitness trait. The arcsine transformation of LFR did not show any improvement of heritability. The present study indicates the possible use of a linear LFR variable for breeding purposes in IHDH breed considering both complete and incomplete reproductive careers.

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“…Various studies have compared heritability estimates from sire or animal models based on REML and MCMC methods using real and simulated data [ 44 , 48 – 50 ]. Studies on real data have reported that REML estimates are more conservative than the corresponding MCMC estimates [ 48 , 49 ].…”

Section: Discussionmentioning

confidence: 99%

A Bayesian generalized random regression model for estimating heritability using overdispersed count data

et al. 2015

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BackgroundFaecal egg counts are a common indicator of nematode infection and since it is a heritable trait, it provides a marker for selective breeding. However, since resistance to disease changes as the adaptive immune system develops, quantifying temporal changes in heritability could help improve selective breeding programs. Faecal egg counts can be extremely skewed and difficult to handle statistically. Therefore, previous heritability analyses have log transformed faecal egg counts to estimate heritability on a latent scale. However, such transformations may not always be appropriate. In addition, analyses of faecal egg counts have typically used univariate rather than multivariate analyses such as random regression that are appropriate when traits are correlated. We present a method for estimating the heritability of untransformed faecal egg counts over the grazing season using random regression.ResultsReplicating standard univariate analyses, we showed the dependence of heritability estimates on choice of transformation. Then, using a multitrait model, we exposed temporal correlations, highlighting the need for a random regression approach. Since random regression can sometimes involve the estimation of more parameters than observations or result in computationally intractable problems, we chose to investigate reduced rank random regression. Using standard software (WOMBAT), we discuss the estimation of variance components for log transformed data using both full and reduced rank analyses. Then, we modelled the untransformed data assuming it to be negative binomially distributed and used Metropolis Hastings to fit a generalized reduced rank random regression model with an additive genetic, permanent environmental and maternal effect. These three variance components explained more than 80 % of the total phenotypic variation, whereas the variance components for the log transformed data accounted for considerably less. The heritability, on a link scale, increased from around 0.25 at the beginning of the grazing season to around 0.4 at the end.ConclusionsRandom regressions are a useful tool for quantifying sources of variation across time. Our MCMC (Markov chain Monte Carlo) algorithm provides a flexible approach to fitting random regression models to non-normal data. Here we applied the algorithm to negative binomially distributed faecal egg count data, but this method is readily applicable to other types of overdispersed data.

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Bayesian and REML analysis of twinning and fertility in Thoroughbred horses

Cited by 12 publications

References 14 publications

Genetic parameters for harmony and gaits in Hispano-Arabe horses estimated by Bayesian methods and Restricted Maximum Likelihood

Genetic parameters for harmony and gaits in Hispano-Arabe horses estimated by Bayesian methods and Restricted Maximum Likelihood

Genetics of Lifetime Reproductive Performance in Italian Heavy Draught Horse Mares

A Bayesian generalized random regression model for estimating heritability using overdispersed count data

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