Assessment of maternal and parent of origin effects in genetic variation of economic traits in Iranian native fowl

Karami, Keyvan; Zerehdaran, Saeed; Javadmanesh, Ali; Shariati, Mohammad Mahdi

doi:10.1080/00071668.2019.1621987

Cited by 6 publications

(11 citation statements)

References 55 publications

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“…Maternally imprinted genes have important roles in placenta development, whereas paternally imprinted genes have important roles in embryonic tissue development. In Iranian native fowl, significant effects of paternally imprinted effect was detected for body weight at 8 weeks of age and estimated value of was 0.04 (Karami et al ., 2019). Where the effects of maternal and paternal imprinting effects are significant, they can be included in the selection procedure, by considering the breeding values of the maternal and paternal imprinting effects when selecting ewes and sires for the next generation.…”

Section: Discussionmentioning

confidence: 99%

“…In recent years, by developing suitable computer software such as WOMBAT (Meyer, 2020), estimating imprinting effects in livestock has attracted lots of attention. By considering imprinting from both parents, the importance of imprinting effects on performance traits of pigs, beef cattle, sheep and chicken has been studied by Neugebauer et al (2010), Meyer and Tier (2012), Amiri Roudbar et al (2017) and Karami et al (2019), respectively.…”

Section: Introductionmentioning

confidence: 99%

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Parental imprinting effects on growth traits and Kleiber ratio in sheep

et al. 2022

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The goal was to study imprinting effects on birth weight (BW), weaning weight (WW), six months weight (W6), pre- and post-weaning growth rate (GRa and GRb), and pre- and post-weaning Kleiber ratio (KRa and KRb) in Baluchi and Makuie sheep breeds. Analyses were done in a two steps process. In the first step, each trait was analysed with a series of 12 univariate animal models, including different combinations of direct and maternal effects and the best model was selected by the AIC criterion. In the second step, three new models were fitted by adding either maternal imprinting effect, paternal imprinting effect, or both of them, respectively, to the best model already selected in the first step, and changes in AIC were monitored. (Co)variances between traits were estimated using bivariate analyses. In Baluchi sheep, for BW, WW and W6, estimates of maternal imprinting heritability ( ${\boldsymbol h}_{{\boldsymbol mi}}^2$ ) were 0.12 ± 0.02, 0.08 ± 0.01 and 0.09 ± 0.01, respectively. In Makuie sheep, paternal imprinting heritability ( ${\boldsymbol h}_{{\boldsymbol pi}}^2$ ) for BW, WW, W6, GRb and KRb were 0.17 ± 0.05, 0.8 ± 0.05, 0.38 ± 0.10, 0.71 ± 0.15 and 0.65 ± 0.13, respectively. In Baluchi sheep, strong maternal imprinting correlations were observed between BW and WW (0.93 ± 0.05), BW and W6 (0.80 ± 0.07) and WW and W6 (0.91 ± 0.02). In Makuie sheep, paternal imprinting correlations ranged from −0.97 ± 0.33 (BW-GRb) to 0.99 ± 0.47 (GRb-KRb). It was concluded that imprinting effects need to be included in the statistical model to increase the accuracy of genetic evaluation. However, to have accurate and reliable estimates of imprinting effects, the availability of large data sets and deep pedigrees are necessary.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parental imprinting effects on growth traits and Kleiber ratio in sheep

et al. 2022

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“…Corresponding estimates for paternal imprinting heritability were 0.05 and 0.07 for birth and weaning weights and 0.00 and 0.01 for yearling weight and final weight, respectively. In addition, in Iranian native fowl, the estimated value of paternally imprinting heritability for body weight at 8 weeks of age was 0.04, and the estimated value of maternally imprinting heritability for 12‐week weight was 0.05 (Karami et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…The paucity of appropriate computer programs implementing efficient algorithms able to disentangle imprinting from additive genetic variance has slowed research on this topic, which were postponed until the 2010s. From 2010 onwards, by considering imprinting from both parents, imprinting effects were quantified on the economic traits of pigs (Neugebauer et al, 2010), beef cattle (Meyer & Tier, 2012; Tier & Meyer, 2012), sheep (Amiri Roudbar et al, 2017) and chicken (Karami et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Relative contribution of Imprinting, X chromosome and Litter effects to phenotypic variation in economic traits of sheep

Ghafouri‐Kesbi

Zamani

Mokhtari

2022

J Animal Breeding Genetics

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Data on Zandi sheep were analysed to quantify maternal and paternal imprinting, X chromosome and litter effects' contribution to phenotypic variation in birth weight (BW), weaning weight (WW), growth rate (GR), Kleiber ratio (KR), efficiency of growth (EF) and relative growth rate (RGR). To this end, a two‐step approach was adopted. In the first step, each trait was analysed with a series of 16 animal models, which were identical for fixed and autosomal additive genetic effects but differed for combinations of maternal permanent environmental, maternal genetic, X chromosome and litter effects. For each trait, the best model was selected by the Akaike information criterion (AIC) and likelihood ratio tests (LRTs). In the second step, three additional models were fitted by adding maternal imprinting, paternal imprinting or both (models 17, 18 and 19) to the best model selected in the first step. Estimators of bias, dispersion and accuracy of breeding values estimated within 19 models with whole, and partial data were used to evaluate how well were the 19 models in estimating breeding values for the animals when their records were masked. For all traits studied, fitting the litter effect led to a better data fit. Also, it resulted in noticeable decreases in residual variance and other maternal variances. For growth traits, models containing the X‐linked effects fitted the data substantially better than corresponding models without the X‐linked effects. For BW, WW and GR, estimates of X‐linked heritability (hs2) ranged between 0.09 (GR) and 0.14 (BW). Ignoring X‐linked effects from the genetic evaluation model resulted in significant inflated autosomal additive genetic variance. For BW, WW, EF and RGR, models containing the imprinting effects provided a better fit of the data than otherwise identical models. Imprinting effects contributed significantly to the phenotypic variation of these traits in a range between 5% (RGR) and 8% (BW, WW). A sharp decline was observed in autosomal additive genetic variance following including imprinting effects in the model (27% to 40% depending on the trait). The least bias and dispersion, as well as greater accuracies for breeding values of focal animals, were for a model which included imprinting, X‐linked and litter effects. It was concluded that imprinting, X‐linked and litter effects need to be included in the genetic evaluation models for growth and efficiency‐related traits of Zandi lambs.

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“…Several studies have been published describing the pattern of growth in poultry. Karami et al (2019) T A B L E 2 Nonexhaustive list of applications of nonlinear functions to describe the growth pattern in chicken…”

Section: Introductionmentioning

confidence: 99%

Estimation of genetic parameters for production, reproduction, and growth curve of Fars indigenous chicken

Neysi

Ghaderi–Zefrehei

Rafeie

et al. 2023

Animal Science Journal

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Iranian native chicken, including Fars indigenous chicken, is an important genetic resource due to its adaptation to stressful environmental conditions, good endurance and resistance to disease. The aim of this research was to determine the genetic infrastructure of Fars indigenous chicken using several nonlinear functions. The dataset included body weight at hatch (BW1), body weight at the 8th week (BW8), body weight at the 12th week (BW12), weight at sexual maturity (WSM), age at sexual maturity (ASM), number of eggs in the first 12 weeks of laying period (EN), egg weight at the first day of laying (EW1), average egg weight at the 28thday of laying (EW28), and average egg weight at weeks 28, 30, and 32 of the laying period (AEW). Growth models were fitted using the NLIN procedure and WOMBAT software was used to predict variance components for the best fit model parameters. Results suggested three‐parameter models, for example, Gompertz, fitted better to the data than others. The maturity weight (A), initial weight (B), and maturity rate (K) parameters in the Gompertz model were 1996.8 ± 6.63, 4.11 ± 0.03, and 0.021 ± 0.0001, respectively. The heritability of A, B, and K parameters were 0.03, 0.05, and 0.12, respectively.

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Assessment of maternal and parent of origin effects in genetic variation of economic traits in Iranian native fowl

Cited by 6 publications

References 55 publications

Parental imprinting effects on growth traits and Kleiber ratio in sheep

Parental imprinting effects on growth traits and Kleiber ratio in sheep

Relative contribution of Imprinting, X chromosome and Litter effects to phenotypic variation in economic traits of sheep

Estimation of genetic parameters for production, reproduction, and growth curve of Fars indigenous chicken

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