m. moradi-shahrbabak

In this study, transcriptome data were used to identify the genes involved in embryo elongation of dairy cattle and the inter-gene interactions to evaluate the important functional modules during this process. The growth, successful development, and survival of the embryo are the most important needs of the dairy industry. The majority of pregnancy loss occurs during the first weeks, especially at the embryonic elongation stage. Thus,in order to better understanding of the molecular basis of this process, we undertook the transcriptome profiling of endometrial cells of pregnant versus non-pregnant cows, during this period. After preprocessing and analysis of microarray and RNA-Seq data and combining the results, gene interactions were investigated using data mining approach. Finally, by comparison of the endometrial profiles, reconstruction of the network and search for important modules, we found four significant functional modules. The most important genes contained ANKRD54, ADAMDEC1, PTN, MT1A, LIMS2, MT1E, CPA3 and MTPN. According to this study, we suggest that identified modules can be used as markers for embryonic growth, elongation, development, secretion of uterine luminal fluid, immune response and embryo survival.

Genetic variation within and between five Iranian sheep populations including Sanjabi (SAN), Kordi Kordistan (KKO), Kordi Khorasan (KKH), Mehraban (MEH) and Moghani (MOG) was assessed using six microsatellite markers (McMA2, McMA26, MAF64, OarAE64, OarCP26 and OarFCB304). The PCR reactions were successfully perfomed with all primers except OarAE64. All locus-population combinations were at Hardy-Weinberg equilibrium except McMA2 in MOG population (P<0.005). Polymorphism criteria showed that the five studied loci were polymorphic in all populations. The lowest DA genetic distance (0.234) was observed between KKH and KKO and the highest (0.388) between SAN and MOG populations. The dendrograms based on DA distances were drawn using unweighted pair-group method using an arithmetic average (UPGMA) and neighbor-joining (NJ) method. KKO, KKH and SAN were grouped together at one cluster and MEH and MOG at another by both methods. The average expected heterozygosity for each populations (as interpopulation variation) ranged from 0.744 to 0.847 for KKH and MEH, respectively. The estimated time of divergence for two Kordi populations (KKO and KKH) was 445 years that complies with historical evidences. The findings of this research confirmed that microsatellite variation could be a useful tool for screening of investigating biodiversity among domestic animals.

This research was carried out to investigate the heterogeneity of milk yield variance components in different production levels of holstein cattles. The first lactation milk yield records of 95945 Holstein cattles, which had calved in 651 herds through years 1991 to 2000, were used in this research. Data was collected by the Animal Breeding Center of Iran and adjusted for two-time milking per day. Records were classified into three classes: low (less than 5275 kg), average (5275-6874 kg), and high (more than 6874 kg) based on the level of production. Variance components and genetic parameters were estimated using single and three-trait animal models for each class and three classes with Derivative Free Restricted Maximum Likelihood methods (DF-REML). Bartlett test showed significant differences for variance components between classes. Milk yield heritability was estimated as 0.205, 0.276, and 0.196 for low, average, and high class, respectively, in both single and three-trait analysis. The gentic correlation coefficient between classes ranged from 0.80 to 0.85, Phenotypic correlation coefficients between classes were low and ranged from 0.17 to 0.19. The highest rank correlation coefficient between estimated breeding value by single and three-trait model was obtained in average class. The average changes in the rank of common animals in the top 1% of cows were greather than the top 5% of bulls. Adjustment for heterogeneity of variance components suggested selecting more top cows from herds with high level of production.

Improvement of feed efficiency in dairy farming economically has a great importance. In this study, the genetic parameters of net energy efficiency and its relationships with milk yield, 3.2% fat corrected milk, body weight, gross income and income over feed costs were investigated, by the 2589 monthly records collected from the 723 lactating cows in the 3 herds. The different requirements of energy were estimated, by the National Research Council (NRC) models. A general linear model was employed for determining significant factors affecting each trait. The genetic parameters were estimated by a multivariate analysis with the derivative free approach of restricted maximum likelihood algorithm. The animal models contained the fixed effects of herd-year-season, parity number and stage of lactation, the regression coefficients of each trait on the dietary levels of rumen undegradable protein and metabolizable energy, and the random effects of animal additive genetic, permanent environment and residuals. The heritability of milk yield, 3.2 percent fat corrected milk, body weight, net energy efficiency, gross income and income over feed cost, were estimates 0.31, 0.32, 0.30, 0.34, 0.24 and 0.29 respectively. The results of this study indicated that the direct selection for net energy efficiency might genetically improve the feed efficiency. It also seems that the selection for fat corrected milk may be effective for the indirect improvement of feed efficiency and economic performance of dairy cows.