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BRCA1 gene plays an important role in DNA damage repair, cell cycle, and transcription process regulation; hence it's called gate keeper. The current research aims to perform bioinformatics analyzes of the BRCA1 gene of different breeds of domestic and wild sheep from 49 breeds in 14 countries using the NCBI genome database. The desired sequences were aligned using MEGA11 software and a phylogenetic tree was drawn by Neighbor-Joining method. The number of mutations, nucleotide diversity, and haploid diversity were also analyzed using Dnaspv5 software. The analyses showed 296 polymorphisms, which led to the creation of 45 different haplotypes with a haplotype diversity of 0.035. Nucleotide diversity and average nucleotide differences among breeds were estimated as 0.259 and 0.052, respectively. The average genetic distance within the population of countries was calculated as 0.052. The amount of sequence conservation in this research was 0.313 on average, which indicates the high polymorphism of this gene and the emergence of new proteins. Tajima's D value in Tajima's neutrality test was −2.421, which was significant (p < 0.05). One of the reasons for the high genetic diversity in Iran's wild sheep population is the existence of forests and open environments, which prevent genetic drift and reduce inbreeding. [ABSTRACT FROM AUTHOR]

It's well-documented that most economic traits have a complex genetic structure that is controlled by additive and non-additive gene actions. Hence, knowledge of the underlying genetic architecture of such complex traits could aid in understanding how these traits respond to the selection in breeding and mating programs. Computing and having estimates of the non-additive effect for economic traits in sheep using genome-wide information can be important because; non-additive genes play an important role in the prediction accuracy of genomic breeding values and the genetic response to the selection. This study aimed to assess the impact of non-additive effects (dominance and epistasis) on the estimation of genetic parameters for body weight traits in sheep. This study used phenotypic and genotypic belonging to 752 Scottish Blackface lambs. Three live weight traits considered in this study were included in body weight at 16, 20, and 24 weeks). Three genetic models including additive (AM), additive + dominance (ADM), and additive + dominance + epistasis (ADEM), were used. The narrow sense heritability for weight at 16 weeks of age (BW16) were 0.39, 0.35, and 0.23, for 20 weeks of age (BW20) were 0.55, 0.54, and 0.42, and finally for 24 weeks of age (BW24) were 0.16, 0.12, and 0.02, using the AM, ADM, and ADEM models, respectively. The additive genetic model significantly outperformed the non-additive genetic model (p < 0.01). The dominance variance of the BW16, BW20, and BW24 accounted for 38, 6, and 30% of the total phenotypic, respectively. Moreover, the epistatic variance accounted for 39, 0.39, and 47% of the total phenotypic variances of these traits, respectively. In addition, our results indicated that the most important SNPs for live weight traits are on chromosomes 3 (three SNPS including s12606.1, OAR3_221188082.1, and OAR3_4106875.1), 8 (OAR8_16468019.1, OAR8_18067475.1, and OAR8_18043643.1), and 19 (OAR19_18010247.1), according to the genome-wide association analysis using additive and non-additive genetic model. The results emphasized that the non-additive genetic effects play an important role in controlling body weight variation at the age of 16–24 weeks in Scottish Blackface lambs. It is expected that using a high-density SNP panel and the joint modeling of both additive and non-additive effects can lead to better estimation and prediction of genetic parameters. [ABSTRACT FROM AUTHOR]