ژن عمده

The purpose of this study was to evaluate traditional, genomic, gene-assisted traditional selection and gene-assisted genomic selection methods for introgression a major gene in sheep population to improve the litter size trait using computer simulation. In this regard, a trait with heritability of 0.1, including two chromosomes each with a length of 100 cM, was simulated. On chromosome 1, a single QTL as the major gene was created that accounted for 40% of the total genetic variance. This QTL was located in the position of 25.7 cM. In breed A and B, animals were selected based for favorable and unfavorable to create two breeds that has been fixed for opposite alleles. Using the gene introgression approach, the favorable allele in breed A was insert to breed B and the new population was evaluated for genetic gain, accuracy of evaluation, frequencies of favorable allele and inbreeding rate. After five backcrossing generations, genetic gain in GasGenomic and Genomic methods was 26 and 62 percent higher than GasClassic and Classic methods, respectively. The frequency of favorable allele after five generations in Classic, Genomic, GasClassic and GasClassic was 0.387, 0.778, 0.965 and 0.975, respectively. The results of this study showed that if the goal is only introgression a major gene into an indigenous breed, by using gene-assisted classic selection, the frequency of a major gene can also be increased as much as obtain by the gene-assisted genomic selection.

The objective of this study was to compare introgression and synthetic breed strategies for litter size trait improvement in sheep using computer simulation. For this purpose, a trait with heritability of 0.1, consisting of two chromosomes was simulated. On chromosome 1, a single QTL as the major gene was created that accounted for 40% of the total genetic variance. The effect of favorable and unfavorable alleles for the QTL was fixed after seven generations in both A and B breeds, respectively. The introgression and synthetic breed strategies were compared using Classical and Classical with gene-assisted selection (GasClassical) methods. The genetic gain in introgression and synthetic breed strategies using GasClassical method was 39% and 16% higher than that of Classical method, respectively. The mean of inbreeding coefficient in the fifth generation in introgression strategy was 0.049 and 0.077 using the Classical and GasClassical methods, respectively, and in synthetic breed strategy was 0.11 and 0.008, respectively. The results of this study showed that the GasClassical method in comparison with the Classical method led to an increasing frequency of favorable allele (major gene) and genetic gain in both introgression and synthetic breed strategies. However, the genetic gain for one percent increase in inbreeding in the synthetic breed strategy was greater than that of introgression strategy, and as a result, the synthetic breed strategy performs better than introgression strategy.

At the present study in order to detect major genes in a commercial broiler line Bayesian method as the most powerful statistical method in detection of major genes was used. After preliminary data editing, data of body weight (BW) at birth and six weeks of age of 14 and 35 generations respectively were analyzed using iBay software. The results verified segregation of major gene for two economical traits investigated at the current study. Compared to the effect of major genes, the polygenic effect on BW at birth which is highly biased by maternal genetic factors was proved to be stronger. However, our results confirmed that the role of major genes in determining BW at six weeks of age was more impactful than that of polygenic part, which highlights the importance of direct genetic effect on the trait. In this study, results of Bayesian segregation analysis confirm the segregation of major genes for the two traits, BW at birth and six weeks of age, which potentially paves the way for future studies to detect major genes.

In the current study, major gene segregation for body weight at 8 weeks of age (BW8), age at sexual maturity (ASM), average egg weight during 84 days of laying (EW) and number of eggs laid during egg production period (EN) traits were evaluated using data which was collected from Fars Native Breeding Center. Cox Box transformation was applied for all traits except for EN. Major gene detection was achieved by using highest posterior density region for genetic variance of major gene in the population. Therefore, a Bayesian segregation analysis model including non-genetic effects (generation-hatch, sex as fixed and laying period as covariate) and genetic effects (polygenic and biallelic major gene locus as random and fixed ones, respectively) was fitted on the data. The marginal posterior distribution of the model parameters were obtained by Gibbs sampling using iBay software. Based on diagnostic tests for each trait, two large chains were considered. For each chain, the number of Gibbs samples, burn in, and thining interval were equal to 500000, 50000 and 50, respectively. The Bayesian segregation analysis revealed the evidence for major gene segregation for ASM. For other traits there were not the same results. It is also recommended that the laboratory methods should be applied to verify the present results as well as additional methods for major gene detection for variety of traits in the same population.

In this research performance records of the Fars province native chickens that were recorded in breeding station during 1988 to 2002 were used. Segregation of major genes for four economically important traits including sexual maturity, egg weight, egg number and body weight were tested. For segregation testing different statistical methods including normality test, Fain test, variance homogeneity test within families (Bartlett and Leven test) and major gene index test were applied. In first step for estimation of genetic parameters a single trait animal model genetic evaluation using REML method was used. Therefore, heritabilitis of traits and breeding values of all animal's were calculated. In the second step a multiple trait genetic evaluation method for four studied traits were used and multiple traits genetic and phenotype parameters were estimated. Then by predicted BLUP breeding values of all animals (offspring and parents), major gene indices for all of traits were calculated. In conclusion, based on appropriate criteria, segregation of major genes for above mentioned traits in this population were not verified. Heritability values that were calculated with univariate model for sexual maturity, egg weight, egg number and body weight traits were 0.53±0.014, 0.63±0.014, 0.33±0.014 and 0.53±0.016, respectively. Their multiple traits estimations were 0.51±0.014, 0.64±0.013, 0.33±0.014 and 0.54±0.014, respectively. It was concluded although different statistical methods are initial recognition methods of major genes, but these methods did not show high precise and it is better to use another precise methods.