نشریه اصلاح و به نژادی دام
سال سوم شماره 1 (پیاپی 7، بهار 1402)

Microarray technology is a powerful technique to measure the expression levels of large numbers of genes simultaneously. Microarray data contains many noise sources; therefore, several preprocessing steps are necessary to convert the raw data to achieve accurate analyzing results. Preprocessing of microarray data includes background correction, data normalization, and summarization steps each can be performed by a large variety of methods. However, the relative impact of these methods on the detection of differentially expressed genes remains to be determined. The aim of this study was to compare the effects of different methods of preprocessing on the results of differentially expressed gene detection. The used data was downloaded from the NCBI GEO database. The series (GSE) accession number, platform (GPL) accession number, and platform name of the data were GSE56589, GPL18534, and Affymetrix Bovine Genome Array, respectively. Two background correction methods (MAS.5 and RMA.2), two normalization methods (Scaling normalization and Quantile normalization), and two summarization methods (Tukey biweight and Medianpolish) were evaluated. The results showed that the number and types of differentially expressed genes could be mainly affected by background correction and normalization methods, but the summarization method showed a small impact.

Pedigree and weight trait records belonging to 13633 Baluchi lambs descendent from 308 ram and 3747 dam which were collected in North-east animal breeding center from years 1989 to 2021 were used. Six univariate animal models with fixed (birth year, month, type, sex of lamb and age of dam) and different random effects were fitted to data. Effects of non-genetic factors on weight traits were investigated by Proc GLM of SAS software, and to estimate the variance components the Wombat software was used. All fixed effects had significant effect on the studied traits (P<0.001). Model with additive autosomal, sex linked, and additive maternal random with covariance between direct additive genetic and maternal genetic effect had the lowest AIC and was used for genetic analysis. For birth, weaning, 6, 9 month and yearling weight respectively additive autosomal heritability were 0.16, 0.34, 0.41, 0.49 and 0.56, additive sex-linked heritability were 0.004, 0, 0, 0.007 and 0.005 and maternal heritability were 0.34, 0.38, 0.32, 0.32 and 0.36. Results showed that sex-linked genes possibly have negligible and close to zero additive genetic effects on body weights at initial ages and in comparison, more noticeable effects on body weights at higher ages. In general, it is recommended to use an animal model for genetic analysis of growth traits in sheep, which is able to separate the total genetic variance into three autosomal, sex-dependent and maternal components in order to be more effective in genetic selection.

The purpose of this research was to determine the population structure and effective population size of Najdi, Holstein and their hybrids in the herds of Khuzestan province. For this purpose, the genomic information of 329 cattle samples including 141, 60 and 128 samples from Holstein, mixed and Najdi breeds were used. The samples were genotyped with Illumina SNP30K genomic arrays. Population analysis was done using PCA and plotNJ, and in both methods the populations were somewhat separated. The range of r2 is from 0.150 ± 0.359 in chromosome 26 to 0.244 ± 0.450 in chromosome 20 for the Holstein breed and 0.130 ± 0.319 in chromosome 28 to 0.271 ± 0.462 in chromosome 20 in were mixed livestock, while the highest value of r2 was observed in the Najdi breed from the range of 0.120 ± 0.311 in chromosome 28 to 0.271 ± 0.483 in chromosome 20. The effective size of the populations in the fifth generation for the populations of this study was 45 Najdi heads, 101 mixed heads and 110 Holstein heads. These numbers for Najdi cattle are far from the recommended values for the protection of populations, and this indicates a serious risk of eliminating native Najdi cattle in the near future. Reducing the effective size will increase the sensitivity of this population to the upcoming environmental changes.

The present research aims to construct the latent variable of growth in Kermani sheep, and to evaluate the measurement model and genetic evaluation by applying pedigree and data information collected from 1993 to 2013 in the Breeding Station of Kermani sheep, Shahre Babak, Kerman Province. The records of body weights at birth (BWT), weaning (WWT), six months (SIXWT), nine months (NINEWT), and twelve months (YWT) of age were used to construct a growth latent variable. Fitting the measurement model considered for constructing the latent variable of growth was done by applying confirmatory factor analysis and was evaluated by using goodness of fit statistical measures including root mean square error of approximation (RMSEA), Tuker-Lewis index (TLI), and confirmatory fit index (CFI). The values of RMSEA, TLI, and CFI were obtained at 0.05, 0.99, and 0.99, respectively, implying the construct adequacy for assessing the latent variable of growth in Kermani sheep. An estimate of 0.34 was obtained for latent variable of growth. Positive estimates of genetic, phenotypic, and environmental correlations between the latent variable of growth and any of the investigated body weight traits were obtained. Furthermore, Spearman's rank correlations between estimated breeding values of the latent variable of growth with any of the investigated body weights were positive and high, implying the selection of superior animals for the latent variable of growth may result in the selection of superior animals for investigated body weights except for BWT.

Several cross breeding experiments have been performed in sheep. These researches have focused mainly on traits of lamb production or meat production. The aim of the present study was to compare the expression of Calpastatin gene in lambs of Arabi and its cross-breed with Romanov. For this purpose, 16 Arabi and hybrid lambs were used in a completely randomized design with 2 treatments and 8 replicates. Hybrid lambs were born from similar ewes which artificially inseminated with Romanove ram sperm by laparoscopy method after estrous synchronization. The lambs were reared after birth in the same conditions and slaughtered at the age of 6 months. Immediately after slaughter, sampling of the muscle portion of longissimus lumborum was performed from the right side of the animal. After extraction of total RNA, its quality and quantity were evaluated and used for cDNA production. Glyceraldehyde 3 phosphate dehydrogenase gene was used as housekeeping gene to normalize the data. Finally, expression of calpastatin gene was evaluated by Real-time qPCR. SAS and REST software were used for analysis of gene expression data. The results of this study showed that the Calpastatin gene expression was 1.3 times higher in crossbred lambs comparing to Arabi (P˂0.05). These results may confirm that cross-breeding can have a significant effect on calpastatin gene function over the pure group. Further studies should be performed to determine the role of calpastatin in muscle physiology.

associated with milk related traits and somatic cell scores through genome-wide association study based on gene-set enrichment analysis in Valle del Belice sheep breed. To this end, the genotypic information of 476 sheep of this breed along with phenotypic records related to production traits including milk yield and milk composition were evaluated using PLINK v. 1.9. After performing various quality control steps, finally 42285 SNP markers in 426 animals were used for follow-up analysis. The results of the genome wide association study (GWAS) showed that 1830, 1577, 2186, 793, 710 and 1063 SNP markers are associated with milk yield, amount and percentage of fat, amount and percentage of protein and somatic cell score in Valle del Belice sheep, respectively (P-value ≤ 0.05). The results of the analysis based on gene-set enrichment led to the identification of pathways (candidate genes) of lipid phosphorylation (including TTC7B candidate gene), lipoprotein transport (ZDHHC17 gene), regulation of calcium ion transport (ATP2B2 gene) and pathway of peptide hormone processing (PCSK6 gene) associated with milk yield; regulation of fatty acid metabolic process (IRS1 and SLC45A3 genes) related to milk fat; the signal transduction by protein phosphorylation (ERCC6 gene) and the pathway of sulfur amino acid metabolic process (NOX4 gene) in relationship with milk protein; and finally the pathways of positive regulation of response to biotic stimulus (PRKCA gene), response pathway to external stimuli (CACNA2D1 gene), regulation of response to stress (EGFR and HSP90B1 genes) and response to bacterium (candidate gene ANXA3) related to somatic cell score.