Parvaneh Deimi Ghias Abadi, Sadegh Alijani, Jalil Shodja Ghias, Nasrolla Pirani,
Volume 3, Issue 5 (Research on Animal Production 2013)
Abstract
In the present research, performance records of Fars native chicken from years 1988 to 2002 were used. Studied traits were body weight at 12 weeks (BW12), age at sexual maturity (ASM) egg weight (EW) and egg number (EN). Variance Components and genetic, phenotype and environmental correlations were estimated using restriction maximum likelihood (REML) and Bayesian analysis method based on Gibbs sampling technique under univariate and multivariate animal model. Univariate estimation of heritabilities with REML for ASM, EW, EN and BW12 were 0.53, 0.63, 0.33 and 0.53, while, with multivariate model these values were 0.51, 0.64, 0.33 and 0.53, respectively. Heritabilities estimates with Bayesian analysis in univariate model for ASM, EW, EN and BW12 were 0.53, 0.63, 0.34 and 0.55, respectively, while with multivariate model were these values 0.56, 0.58, 0.33 and 0.55, respectively. Genetic and environmental correlations between BW12 and ASM using both methods were negative but phenotypic correlation was positive. Genetic, environmental and phenotypic correlations between BW12 and EW and EN with both methods were positive. The estimates between W12 and EW with REML were 0.5, 0.15 and 0.36, whereas with Bayesian were 0.43, 0.26 and 0.28, respectively. Those estimates between BW12 and EN with REML were 0.03, 0.15 and 0.1, respectively, whereas with Bayesian were 0.19, 0.23 and 0.19, respectively. The above mentioned correlations between ASM and EN were high and negative using both methods. It can be concluded that the estimation of the parameters evalvated using with these two methods are close together.
Parvaneh Raufian, Jalil Shodja Ghyas, Raziallah Jafari, Gholamali Moghaddam, Arash Javanmard,
Volume 8, Issue 18 (3-2018)
Abstract
Mastitis is one of the most common diseases in dairy cattle, which has imposed therapy heavy costs to farmers through significant reduction in total milk production. Identification of nucleotide polymorphism of two candidate immunity response genes and its effects on SCS as a mastitis incidence indicator was carried out in this research. The genes were exons 1 and 2 of TLR2 and 3 and 4 of TNFα. For this purpose, a hundred Holstein lactating cows were selected based on their breeding values for milk production, fat and somatic cell scores. Then cows based on their residual values for somatic cell scores were divided into two resistant and susceptible groups and 5 ml blood samples were collected from each animal. Selective genotyping of two target groups of susceptible and resistant animals to mastitis was done using PCR-RFLP approach. The association between genetic polymorphisms with corrected records of somatic cell scores (residual values for somatic cell score) were analyzed using the Generalized Linear Model (GLM) procedure of SAS statistical package (version 9.2) followed by means comparison with Tukey-Kramer test. There was a significant direct relationship between TLR2 and TNFα gene polymorphisms and somatic cell score residual values (P<0.001). Furthermore, For TNFα gene the most genotypic frequencies in resistant and susceptible groups were related to genotypes AA and BB, respectively. Also, KK genotype frequency within TLR2 candidate gene showed a higher frequency within susceptible group versus the resistant group. As a conclusion, the obtained results may be used to monitor and design
breeding strategy to prevent mastitis.
Mostafa Madad, Jalil Shodja, Sadegh Alijani, Sayed Abbas Rafat, Jack Dekkers,
Volume 10, Issue 26 (12-2019)
Abstract
The purpose of this study was to compare the accuracy of genomic evaluation for Bayes A, Bayes B, Bayes C and Bayes L multi-step methods and SSBR-C and SSBR-A single-step methods in the different values of π for predicting genomic breeding values of the genotyped and non-genotyped animals. A genome with 40000 SNPs on the 20 chromosom was simulated with the same distance (100cM). The π values that maximized the prediction accuracies in BayesC were 0.980 and 0.995 for the normal and gamma distributions of QTL, respectively, and were also used in SSBR-C method. Genomic prediction accuracy in the SSBR-C (π = 0.99) method was higher than multi step methods from 0.02 to 0.09 for gamma distribution. Results showed that considering mixture distribution and use of phenotype, genotype and pedigree information simultaneously, the SSBR-C (π = 0.99) method had higher accuracy than other methods and is considered a better choice in this scenario. Moreover, both single and multi-step methods showed similar prediction accuracy when the genetic architecture appeared to approach the normal distribution. Furthermore, SSBR-C (π = 0) method appeared to be more reliable choice that was due to regressions of true breeding value on estimated breeding value close to one in normal distribution. Generally, GEBV accuracy decreased as the distance increased between validations and training set, which was more sensitive for non-genotyped individuals compared to genotyped individuals.
Mrs Afsaneh Jahedi, Dr Jalil Shodja, Dr Sadegh Alijani, Dr Majid Olyayee,
Volume 11, Issue 30 (12-2020)
Abstract
The egg quality is one of the most important economic factors for layers that are crucial for hatchability and marketing. Given the low number of egg quality traits records, one of the approaches in estimating phenotypic and genetic parameters is multi trait analysis. The aim of this study was to estimate the phenotypic and genetic parameters of west Azerbaijan native hens egg quality traits by multi-trait analysis. For this purpose, 2000 eggs of 14th and 15th generation of pedigree hens were purchased from west Azerbaijan native fowl breeding station and for measuring egg quality traits were transferred to laboratory. The genetic and phenotypic parameters of egg quality traits were estimated by multi-trait analysis using SAS and WOMBAT softwares. The generation-hatching time and storage duration in refrigerator had significant effect on egg quality traits. The mean of some egg quality traits were: egg weight 55.306 g±3.94, egg shape index 75.192±2.9, egg shell percentage 9.389 %±0.73, albumin percentage 60.160 %±2.49, yolk percentage 30.466%±2.35, yolk index 35.928±3.13 and yolk pH 6.442±0.13. The highest and the lowest coefficient of variance were calculated in air cell height and albumin pH, as 16.947 % and 1.366 %, respectively. The highest positive phenotypic correlation was observed between egg weight and egg volume (0.644), and the lowest one was observed between pH of albumen and yolk weight (0.004). The highest positive genetic correlation was observed between egg weight and egg shell surface area (0.999), the highest negative genetic correlation was observed between albumen percentage and yolk to albumen ratio (-0.994). The lowest positive genetic correlation was estimated between yolk index and yolk weight (0.002) and the lowest negative genetic correlation was evaluated between yolk index and dry matter of yolk (-0.005). The range of estimated heritability of studied egg quality traits were 0.212 (albumen percentage) and 0.015 (pH of albumen). Generally, the results indicated that the egg quality traits of Azarbaijan indigenous hens have relatively high phenotypic and genetic correlation, which in order to decreasing the cost of data recording, the number of recorded traits could be decreased. The heritabilities of egg quality traits were moderate to low that indicated the low progress with direct selection.
