Bayesian inference on genetic parameters for some reproductive traits in sheep using linear and threshold models

This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inference. The data of 1894 animals from three generations of White Leghorn laying hens were analyzed for fertility (FERT), hatchability (HATC), and birth rate measurements at 60 weeks of age (BIRTH), body weight at 16 and 60 weeks of age (BW16 and BW60), age at sexual maturity (ASM), egg height/width ratio, weight, and density at 28, 36, and 40 weeks of age (RHW28, RHW36, RHW40, WEGG28, WEGG36, WEGG40, DENS28, DENS36, and DENS40, respectively) traits. The genetic parameters were estimated by the Bayesian inference method of multi-trait animal model. The model included the additive and residual genetic random effects and the fixed effects of generation. The a posteriori mean distributions of the heritability estimates for reproductive traits ranged from 0.14 ± 0.003 (HATC) to 0.22 ± 0.005 (FERT) and performance from 0.07 ± 0.001 (RHW28) to 0.42 ± 0.001 (WEGG40). The a posteriori mean distributions of the genetic correlation between reproductive traits ranged from 0.18 ± 0.026 (FERT and HACT) to 0.79 ± 0.007 (FERT and BIRTH) and those related to performance ranged from –0.49 ± 0.001 (WEGG36 and DENS36) to 0.75 ± 0.003 (DENS28 and DENS36). Reproductive and performance traits showed enough additive genetic variability to respond to selection, except for RHW28. This trait alone would have little impact on the genetic gain because environmental factors would have a higher impact compared to those from the additive genetic factors. Based on the results of this study, the selection applied on the BIRTH trait can be indicated to improve FERT and HATC of eggs. Furthermore, the use of the WEGG40 could improve egg quality in this population.

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Bayesian estimation of genetic parameters of litter size at birth in crossbred Mule ewes using repeatability and multiple trait threshold models

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200019694 ◽

2007 ◽

Vol 2007 ◽

pp. 66-66

Author(s):

W. Mekkawy ◽

R. Roehe ◽

R. M. Lewis ◽

M. H. Davies ◽

A. M. Van Heelsum ◽

...

Keyword(s):

Litter Size ◽

Reproductive Performance ◽

Genetic Parameters ◽

Reproductive Traits ◽

Threshold Models ◽

Multiple Trait ◽

Repeated Observations ◽

Improvement Programs ◽

Size At Birth ◽

Estimation Of Genetic Parameters

The reproductive performance of ewes is a major factor influencing the economic success of lowland flocks. Even so reproductive traits have not often been included in sheep genetic improvement programs because of their low heritabilities compared with other performance traits like body weight and carcass merit. Litter size is one of the most important traits affecting reproductive performance. There are two important factors to be considered in the genetic analysis of litter size. First, several authors have suggested that litter size in different parities is controlled in part by different genes, and therefore should be treated as different traits. Second, ignoring the categorical nature of litter size and analysing it using a linear model does not account for its non-normal distribution. As a consequence, threshold models are likely to be more appropriate for the analysis of categorical traits (Gianola and Foulley, 1983). Therefore, the objective of the current study was to estimate the genetic parameters for litter size of Mule ewes using both repeatability and a multiple trait threshold models for repeated observations of litter size across four different parities.

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Genotype x Environment Interaction for reproductive traits in brazilian Nellore breed cattle

Revista Brasileira de Saúde e Produção Animal ◽

10.1590/s1519-9940200512019 ◽

2019 ◽

Vol 20 ◽

Cited By ~ 1

Author(s):

Caio Victor Damasceno Carvalho ◽

Raphael Bermal Costa ◽

Gregório Miguel Ferreira de Camargo ◽

Thereza Cristina Calmon Bittencourt

Keyword(s):

Bayesian Inference ◽

Genetic Correlation ◽

Genetic Parameters ◽

Reproductive Traits ◽

Northern Region ◽

Environment Interaction ◽

Genotype X Environment ◽

Scrotal Circumference ◽

Genotype Environment Interaction ◽

Different Ages

SUMMARY The objective of this study was to evaluate the effect of the genotype-environment interaction (GEI) for scrotal circumference traits measured at different ages, 365 (SC365), 450 (SC450) and 550 (SC550) days of age, and age at first calving (AFC) for Nellore animals raised in different regions of Brazil. For the evaluation, the herds were grouped in the following regions of the country: North, Southeast and Central-west, using information from 26,619, 28,730, 14,476, 15,397 for the traits SC365, SC450, SC550 and AFC respectively. Genetic parameters, as well as the assessment of GEI were performed using Bayesian inference, using the programs of the BLUPF90. The estimated heritabilities were: 0.465 ± 0.021, 0.500 ± 0.022, 0.492 ± 0.026, 0.117 ± 0.017 for SC365, SC450, SC550 and AFC respectively. The results obtained in the analysis, indicated that this interaction was not significant for SC at different ages (genetic correlation, rg> 0.8). For AFC, significant effect of GEI was observed for combinations involving the Northern region (rg<0.8), indicating that this interaction should be considered by the genetic evaluation programs in this region.

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