body weight

The identification of selection targeted genomic regions is one of the main aims of biological research. Domestication and selection have significantly changed the behavioral and phenotypic traits in modern domestic animals. The selection of animals by humans has left detectable signatures on the genome of modern cattle. The identification of these signals can help us to improve the genetic characteristics of economically important traits in cattle. The interest in the detection of genes or genomic regions that are targeted by selection has been growing over the last decade. Identifying the signatures of selection can provide valuable insights about the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. This study aimed to identify effective genes and genomic regions on positive signatures of selection in Beetal goats using selection signature and gene ontology methods.

In this study, data from 631 Beetal goats genotyped using the Caprine 50 K Bead Chip were used to identify genomic regions under selection associated with important traits in Beetal goats. Quality control measures were performed in Plink by setting an animal call rate of 0.90, SNP call rate of 0.95, and SNPs with minor allele frequencies (MAF) lower than 0.05 or that do not conform to the Hardy–Weinberg expectation (p-value ≤ 0.000001) and unknown positions. After quality control of the initial data using Plink software (v1.90; http://pngu.mgh.harvard.edu/purcell/plink), 36,861 SNP markers in 594 animals of cattle were finally entered for further analysis. To identify the signatures of selection, the statistical method iHS was used under REHH software packages. Candidate genes were identified by SNPs located at 1% upper the range of iHS using Plink v1.9 software and the gene list of Illumina in R. Additionally, the latest published version of Animal Genome Database was used for defining QTLs associated with economically important traits in identified locations. In addition, the DAVID database (http://david.abcc.ncifcrf.gov) was used to determine biological routes. At this stage, it is assumed that genes belonging to a functional class can be considered a group of genes that have some specific and common characteristics. GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes. Moreover, gene ontology analysis for identified genes was performed using the DAVID online database.

After quality control filters, 36,861 SNPs were left while 9761 SNPs were removed due to Hardy-Weinberg Equilibrium, 1342 SNPs were removed due to unknown positions, 3963 were removed due to a minor allele threshold, and 1342 were removed due to missing genotypes. Besides 37 individuals were removed after quality control measures. Using the iHS approach, 10 genomic regions were identified on chromosomes 4, 6, 7, 11 (two regions per chromosome), 13, 14, 15, 17, and 18. Some of the genes located in identified regions under selection were associated with body size (SPP1, SCN9A, and TNPO2), fat metabolism (SDCBP), skeletal development (IBSP and MEPE), and energy metabolism (UCP2, TRPC3, and FBP1). Some of the genes under selection were found to be consistent with some previous studies. Results of the gene ontology analysis identified two biological pathways, namely skeletal system development and a calcium channel complex, with two important KEGG pathways, including the glucagon signaling pathway and the AMPK signaling pathway, which play an important role in glucose metabolism, homeostasis, and skeletal system development.

Overall, various genes found within these regions can be considered the candidates under selection based on function. Most of the genes under selection were found to be consistent with some previous studies and to be involved in several processes, such as growth, body weight, metabolic pathways, and domestication-related changes, including system development and immune systems. Furthermore, a survey on extracted QTLs showed that these QTLs were involved in some important economic traits in goats, such as feed conversion ratio, subcutaneous fat, Marbling score, meat tenderness, body weight, average daily gain, conformation traits, the length of productive life, carcass traits, and composition carcass traits. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes and surveys on QTLs related to selected regions. However, will be necessary to carry out more association and functional studies to demonstrate the implication of genes obtained from association analyses. Using these findings can accelerate genetic progress in breeding programs and can be used to understand the genetic mechanism controlling this trait. The results of our research can be used to understand the genetic mechanism controlling growth traits. Since this study supported previous results from the genome scan of production traits and revealed additional regions, using these findings could potentially be useful for genetic selection in goats for a better body weight.

In many countries of the world, the camel has played an important role in the lives of people in arid and semi-arid regions in terms of providing milk and meat products. Based on phenotypic characteristics, the camel has been adapted to the deserts from physiological, anatomical, and behavioral points of view. Due to limited water resources, the south Khorasan province of Iran has not been an appropriate geographical region for a great number of agricultural products. Weighing plays an important role in the management of camel breeding to adjust the nutritional needs and also the annual evaluation of the animals. One of the main challenges of camel breeding is the difficulty of recording and the lack of records due to the wild nature and also the large size, especially in adults. Due to the many difficulties and risks, camel breeders usually use various potential alternative tools such as apparent estimation or weighing tape to estimate the weight of camels at different ages. For farm animals, significant correlations between body measurements and body weight can be used as a tool to estimate the weight of animals through a mathematical equation. The main objective of this study was to compare the accuracy of artificial neural network (ANN) and multiple linear regression model (MLR) in estimating the body weight of a humped camel.
In the present study, the data of a total number of 177 one-humped camels in four groups  (including 1. 63 adult female Pakistani camels aged between 9 and 12 years, 2. 21 adult female Baluchi camels aged between 9 and 12 years, 3. 93 male and female camels less than 2 years of age of Pakistani and Baluchi breeds, and 4. total camels) collected at the South Khorasan camel breeding station in 2019 were used. Morphological characteristics of camels include: neck length, neck girth, hand length, foot length, shoulder height to the ground, hump height to the ground, hip height to the ground, chest girth, chest width, abdomen girth, hip width, tail length, breast height, and breast girth were measured. After measuring the body dimensions, the evaluated camels were weighed using a 1000 kg digital scale. To estimate the weight of camels from their body dimensions, the data were analyzed using the MLR model and ANN with the nnet package in R software. For ANN analysis, 80% of the data were considered for network training and 20% for testing. The accuracy of MLR and ANN for camel body weight estimation was compared using the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE).
The results of the MLR model showed that body dimensions of shoulder height to the ground, chest girth, abdominal girth, neck girth, and hand length had a significant effect on body weight (P<0.05). In the ANN model, chest girth, abdominal girth, and shoulder height to the ground were the most important variables in estimating the body weight of camels of the whole population. The MLR and ANN models had acceptable accuracy in weight estimation. However, compared to the MLR model, the ANN model had a higher R2 and a lower error in estimating the weight of camels. In the first group, R2 and RMSE were found to be 0.996 and 6.852, respectively, for ANN while the corresponding values were 0.979 and 22.955, respectively, for MLR.  In the second group, R2 and RMSE were found to be 0.995 and 3.525, respectively, for ANN while the corresponding values were 0.989 and 5.377, respectively, for MLR.  In the third group, R2 and RMSE were found to be 0.896 and 13.959, respectively, for ANN while the corresponding values were 0.849 and 17.549, respectively, for MLR. In the fourth group, R2 and RMSE were found to be 0.929 and 20.248, respectively, for ANN while the corresponding values were 0.903 and 38.505, respectively, for MLR. The results showed that ANN is more accurate compared to MLR in predicting the body weight of camels. 
In terms of goodness of fit (including R2 and RMSE), the results of the present research suggest that both MLR and ANN methods have high acceptable accuracy for predicting body weight in camels. ANN was more suitable compared to MLR, suggesting that it could be used to predict camel body weight. Furthermore, grouping the camels by age and breed could also lead to higher precision and lower prediction error.

The aim of this study was to evaluate the effect of removing iron from mineral premix before calving on the productive performance and health status of Holstein dairy cows during transition period. The ninety multiparous Holstein dairy cows entered the experiment -21 days before the expected calving and were randomly assigned to 3 experimental treatments. Treatments included: 1) control treatment: recipient of mineral supplement with iron (to supply iron requirement in the amount of 15 mg/kg; n = 30); 2) treatment without iron: recipient of mineral supplement without iron (n=30); 3) without supplemental iron treatment with cottonseed: recipient of mineral supplement without iron and 4.6% of cottonseed in the diet (n=30). Removing iron from mineral supplements with and without cottonseed had no significant effect on milk production, percentage and amount of milk fat, as well as the amount of milk protein. The somatic cell count (SCC) in the control treatments, without supplemental iron and without supplemental iron with cottonseed, were 471.48, 338.80 and 155.77 (103 per ml), respectively, which significantly decreased in the treatment without supplemental iron with cottonseed. Body weight changes after calving were also affected by experimental treatments. Removing iron from the mineral supplement along with cottonseed reduces the incidence of hypocalcemia. Total birth weight of both male and female calves, body length, hearth girth and days of diarrhea showed a significant difference between the treatments. Overall, the removal of supplemental iron along with cottonseed reduced the SCC and also improved the health status of cows and their calves.

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.

Compared to other poultry, geese are more resistant to adverse environmental factors, so they are less likely to get sick. Geese are fast-growing poultry, and they are easy to raise. Due to the importance of goose meat due to its high calorie content compared to the meat of other poultry species and its high palatability, as well as its resistance to many diseases, it is necessary to raise this bird on an economic scale. In industrial goose breeding, there arises a need to develop strains tailored for specific purposes such as meat, egg, and dual-purpose. This allows breeders to align breeding objectives with associated costs and optimize productivity for the industry's requirements. Consequently, the economic coefficients of breeding, coupled with the relative selection of products, necessitate consideration in four primary aspects: achieving high weight gain, reducing the food conversion ratio, increasing the egg count, and enhancing egg fertility. It is crucial to acknowledge the negative correlation coefficient with the egg production trait within the realms of management and breeding sciences. This is because an improvement in one trait may inversely impact the values of another trait. Among the effective strategies in breeding, the selection is based on genetic markers that lead to the reduction of the generation gap and increase in production. Due to the ever-increasing growth of the population, a lot of effort is needed to overcome unfavorable environmental conditions, including biological and non-biological factors, and to increase the quantity and quality of the product. In recent years, many advances have been made in the field of molecular biology and biotechnology, which has provided a powerful tool for the genetic study of animals. Considering that the growth hormone gene (GH indicator) is one of the candidate genes for various traits, especially weight gain, but it has not been used in goose breeding programs so far. Therefore, in order to determine the contribution of this gene in goose breeding, its relationship with the weight gain trait of chickens should be determined, which is actually the purpose of designing and implementing this study. In order to implement this research, 300 gosling hatched from eggs of Malekan research station geese and reared for 5 months. The hatched goose chicks were kept and fed according to breeding standards Gosling weighted monthly and blood samples was collected from them in vacuum tubes containing EDTA at end of raising period. Genomic DNA was extracted by Pronase procedure. A spectrophotometer was used to determine the quality of the extracted DNA, and for this purpose, a wavelength of 260 nm was used to determine the amount and concentration of DNA, and a wavelength ratio of 260/280 was used to determine the purity and quality of the extracted DNA. Amplification of the desired region from exon 2 of the growth hormone gene was done by thermocycler using the designed primers GH-G F and GH-G R to amplify 162 base pairs. 2% agarose gel with ethidium bromide staining was used to identify PCR products. The SSCP technique was used to determine the genotypes of the growth hormone gene. Denatured SSCP products was electrophoresed on 10% polyacrylamide gel and stained by silver nitrate. Effects of GH gene on growth performance were analyzed by SPSS software version 23 in CRD design. Genotypes pattern of 1, 2 and 3 were recognized. Frequencies of 1, 2 and 3 patterns resulted 48.15, 44.44 and 7.15 percent, respectively. Results indicated that GH genotypes affected live weight of gosling in 1 and 2 month of age, the 3th pattern had heavier live weight in these periods. Despite of heavier live weight in pattern 3, for months of 3, 4 and 5 no significant differences observed among them. Low frequency of pattern 3, that affected live weight in gosling, can be increased in study population in favor of this pattern. The results of this research showed that the growth hormone gene and especially exon 2 of this gene can be considered as a genetic marker in the selection of geese for the weight gain trait. Given the considerable importance of the economic coefficient of egg production in geese, which outweighs the emphasis on increasing the weight of breeding geese, and considering that the economic activities of the station align more closely with augmenting the number of chicks produced per breeding goose, the observed negative correlation between egg production and weight gain in geese suggests a lower prevalence of the effective genotype influencing the weight gain of geese in this station. The selection focus at Malekan station has predominantly aimed at enhancing the egg laying rate, in stark contrast to the growth rate of geese. Consequently, this deliberate selection has led to an increase in the frequency of the effective genotype impacting egg laying and concurrently a reduction in the frequency of genotypes influencing the weight gain of goose chicks.

The majority of selection and breeding programs for sheep focus on improving weight and growth traits. Body weight uniformity is a crucial economic characteristic within the industry of sheep breeding. Birth weight is an important trait that has an optimal limit, and extremely high or extremely low birth weight can cause difficulties during birth, stillbirth, and problems such as dystocia, stillbirths, and diminished growth of lambs. The existence of genetic variability for the residual variance is a necessary condition for improving this trait through breeding. Recent studies have demonstrated that the residual variance is governed by additive genetic influences. The enhancement of uniformity in body weight traits can be achieved as an economic advantage by employing selection strategies that take into account the genetic variability of the residual variance. The present study was undertaken to ascertain variance components and genetic parameters pertaining to the residual variance of birth weight and weaning weight traits in Sangsari sheep. Also, the genetic correlation between these traits and their residual variance was calculated.

To carry out this study, the phenotypic data of 5986 lambs obtained between 1986 and 2016 from the Sangsari sheep breeding station were utilized. The traits examined comprised birth weight, weaning weight, and the residual variance associated with them. To incorporate fixed factors into the model and assess their impact on the examined traits, a least-squares analysis was conducted utilizing the GLM procedure of SAS software. The estimation of variance components and genetic parameters was conducted using the average information restricted maximum likelihood (AI-REML) algorithm implemented in the DMU software, employing the DHGLM method. Firstly, an animal model was applied to estimate the residual variance of birth weight and weaning weight traits. Following that, a bivariate model was employed to examine the influence of additive genetic effects on the residual variance.

The additive genetic standard deviations for the residual variance of birth weight and weaning weight were determined to be 7.74 and 17.90, respectively, consequently, a decrease of one standard deviation in the breeding value of residual variance resulted in a reduction of 7.74 and 17.90% in the uniformity of the respective traits. The heritability estimates for the mean and residual variance of birth weight and weaning weight were found to be 0.26 ± 0.09, 0.059 ± 0.003, 0.23 ± 0.06, and 0.037 ± 0.001, respectively. The genetic coefficient of variation was determined to be 0.58 for birth weight and 0.48 for weaning weight. The genetic correlation ranged from -0.16 for birth weight and residual variance to 0.11 for weaning weight and residual variance.

The results of the current study offer crucial information regarding the presence of additive genetic variation for the residual variance of birth weight and weaning weight within Sangsari sheep herds, which can be utilized to enhance uniformity by selecting for reduced residual variance. The selection for increasing birth weight resulted in a reduction of the breeding value of residual variance and an enhancement of herd uniformity, owing to the favorable genetic correlation observed between birth weight and its residual variance. The genetic correlation for weaning weight was found to be unfavorable, indicating that selecting for higher weaning weights led to increased heterogeneity within the herd.

Lipids (fat and oil) are the most concentrated sources of energy for animals, which are usually added to poultry diets to meet energy requirements for better performance (Abudabos 2014). However, there are problems with dietary lipid levels and digestibility in poultry, especially in young birds due to low bile secretion (Ravindran et al 2016). This physiological limitation of the poultry digestive system can be solved by using exogenous emulsifiers. Emulsifier can help increase the active level of lipids, stimulate the formation of micelles, and then increase the digestibility of dietary lipids and other nutrients in broilers (Siyal et al 2017). Upadhaya et al (2017) showed that 1, 3-diacylglycerol as an exogenous emulsifier can improve growth performance and increase nutrient digestibility in broilers. In addition, a large number of studies have also shown that exogenous emulsifier can improve meat quality and regulate fat metabolism of broilers (Zhao and Kim 2017). Bile acids are the main pathway of cholesterol catabolism in mammals. Cholesterol is converted into bile acids by changes in ring structure, oxidation and side chain shortening (Li and Chiang 2019). The chemistry of bile acids is complex due to the large variety of chemical structures in natural compounds such as cholic acid, kenodeoxycholic acid, deoxycholic acid, and lithocholic acid. Bile acids of birds are mainly composed of kenodeoxycholic acid and cholic acid (Hoffman and Hagee 2018). Recently, bile acids have been considered as an emulsifier to increase digestibility (Upadhaya et al 2019) and improve the performance of broiler chickens (Parsai et al 2007). Supplementation of bile acids in the diet of broilers significantly improves fat digestibility (Lammasak et al 2019). The effect of bile salts on performance, carcass characteristics and blood parameters of broiler chickens were investaigeted.

Three hundered one-day-old broilers (Ross 308) were divided into 5 treatments and 6 replications with 10 birds in each replication. Five experimental treatments included the control diet (corn soybean based diet), emulsifier (added to control diet) and three levels of 0.05%, 0.1% and 0.2% of poultry bile salts (added to control diet). All the dietary treatment were fed to the birds from day one to day 42 of age. The experiment lasted for 42 days and were performed during the starter (1-10 days), grower (11-24 days) and finisher (25-42 days). Performnce indices were measured during the difeferned periods and carcass characteristics and blood parameters were determined on day 42 of age. The data obtained from the present study were statistically analyzed using SAS statistical software and GLM procedure. To compare the means, Tukey's test was used.

The results showed that consumption of different levels of bile salts had no significant effect on feed consumption (P<0.05). However, consumption of 0.1% bile salts improved body weight gain and feed conversion ratio during the starter period (P<0.05). Previous studies have shown that the consumption of 0.05% commercial emulsifier can improve the growth performance of broiler chickens (Wang et al 2016). In addition, in the present study, 0.05% poultry bile acids supplement significantly improved daily weight gain and feed conversion ratio during 1 to 10 days, which is consistent with the results of Alzawqari et al (2011) regarding bile. These researchers observed improvement in daily weight gain with 0.05% bovine bile acid supplementation. Arshad et al (2020) reported that feed intake was not affected by bile acid supplementation in the initial, growth, finisher and overall periods. In the newly hatched chick, the ability to digest and absorb dietary fat is poor as a result of limited bile secretion (Tancharonrat et al 2013). For this reason, artificial bile acid and bile salts have shown the greatest effect in young broiler chickens to improve fat digestion, and the improvement in the performance of birds receiving bile in the initial period of recent research was for this reason. The results of Maisonnier et al (2016) showed that 0.5% of pig bile acids can increase fat digestibility and body weight in broilers. These results may imply that the supplementation of bile acids in diets improved the growth performance of broiler chickens by increasing the solubility and digestibility of dietary fat and fat-soluble nutrients in this study. Abdominal fat decreased significantly by consumption of 0.1% bile salts (P<0.05). Subcutaneous fat and abdominal fat are considered as the main factors influencing the performance of poultry carcasses (Tůmová and Teimouri 2010). In agreement with our results, many researchers have pointed out the positive effects of emulsifier on reducing fat status and improving carcass quality in broiler chickens (Zhao and Kim 2017). Blood triglyceride concentration was decreased in 0.05% bile salts fed birds wherease cholesterol and uric acid concentrations decreased in the birds fed emulsifier (P<0.05). Triglyceride, cholesterol, HDL and LDL blood are key indicators of lipid metabolism balance (Helkin et al 2017). In agreement with our results, researchers reported that bile acids increased hepatic AST and ALT activity in broilers and reduced serum triglyceride levels, which could be due to the participation of these enzymes in the lipogenesis process (Ge et al 2019). In addition, Siyal et al (2017) showed that feed emulsifier can reduce serum triglyceride concentration in broilers. It can also be stated that bile acids may enhance fat catabolism and inhibit fat synthesis by regulating the expression of genes related to lipid metabolism which may play a pivotal role in improving serum lipid profile and reducing fat deposition in broiler chickens (Ge et al 2019).

Totally, it was found that dietary bile salts supplementation improves the performance of, carcass characteristics and blood lipids in broiler chcikens.

In the management of camel breeding, weightlifting plays a decisive role in grouping livestock, regulating nutritional needs and also annual evaluation of animals. Due to the many difficulties and risks, camel owners usually prefer alternative methods such as using apparent estimates or weight -meter to estimate the weight of camels. Since the accuracy of mathematical models in estimating the weight of camels is not equal, so the present research was conducted to compare the accuracy of estimating artificial neural network and multiple linear regression model in estimating the weight of dromedary camels from their body dimensions. For this purpose, 26 camels with 203 records were used from a private farm for one year. Weighing and determining the body dimensions of camels (body length, shoulder height, back height, hump height to the ground, chest and abdomen girth) were measured monthly. To estimate the weight of camels from their body dimensions, the data were analyzed using multiple linear regression model and artificial neural network. The weight of camels on their body dimensions was estimated with accuracy of 0.94 and 0.99, respectively, using multivariate linear regression model and artificial neural network model. The weight of camels on their body dimensions was estimated with accuracy of 0.94 and 0.99, respectively, using multivariate linear regression model and artificial neural network model. The results of this research showed that the artificial neural network has the proper ability to estimate the weight of camels based on their body dimensions and can replace conventional regression methods.

The aim of the present study was to evaluate the genetic architecture, genomic regions and candidate genes associated with body weight gain, feed intake and feed conversion ratio in Japanese quails. For detection the informative genomic windows, genotyping data on 920 quails was used in a single-step genome-wide association study. The BLUPf90 family software was used to perform related analyses. Theresults was calculated based on the proportion of additive genetic variance (agv) explained by genomic region with an average size of 1.5-Mb of adjacent SNPs. Windows with accounting for more than 1% of the agv were used to identify genomic regions and to search for candidate genes. A total of 13 significant windows over 8 chromosomes were explained 23% of the agv for the body weight gain and including SMYD1, ADGRG6 and CFL2 candidate genes. A peak on CJA2 explained the largest proportion of variance. For feed intake, we identified 20 informative windows across 8 chromosomes and including ACSL, PPA2, FGF2 and RBL2 candidate genes. These regions explained 38% of the agv and a peak on CJA4 explained of agv. Also, for the feed conversion ratio, 12 significant windows were identified on 7 chromosomes and explained 23.7% of agv, contained ATRNL1 and PTPN4 candidate genes. Four genomic regions had a pleiotropic effect. Considering the identification of new genome regions and the key role of the mentioned genes related to feed intake, the single step method can be validated for GWAS in feed efficiency traits.

The purpose of this study was to fit different nonlinear models to describe growth curve and selection the best model to describe a growth curve forcalves of Sistani calves. Body weight records of 241 calves (118 males and 123 females) collected by the Sistani Dairy Cattle Research Station ofZahak from year 2010 to 2017 were used. Four nonlinear models (Gompertz, Logistic, Richards, and Weibull) were fitted to the body weight recordsand the best model was selected by the goodness-of-fit criteria (Mean square error, Bayesian information criterion, Akaike information criterion andcorrected coefficient of determination). According to goodness-of-fit criteria, Richards model was the most appropriate model to describe the growthcurve in male and female calves. The effect of sex on curve parameters was significant in many functions (P <0.05). Logistic and Richards models hadthe highest and the lowest initial weight parameter, respectively. Male calves reached to the inflection point in a higher age and weight compared tofemale calves. According to the results of this study, a proper model can be used to study the growth pattern of this breed in order to better nutritionalmanagement and selection for rapid growth with high accuracy.

Microbial products or probiotics can be added to animal feed and can have a positive effect on improving animal performance and enhancing the growth of young ruminants by maintaining a microbial balance in the intestinal flora and preventing gastrointestinal infections (Noori et al. 2016). The use of bacterial probiotics in replacing milk of suckling animals has improved the feed conversion ratio (Noori et al. 2016) and increased daily weight gain (Kawakami et al. 2010). Improving animal weight gain by feeding probiotic-containing treatments may be due to improvements in microbial ecology (Lascano et al. 2009) and increased nutrient uptake (Khutia and Chayyaderi 2002) and improved feed conversion ratio. The effects of bacterial probiotic use on different performance, health status, and blood counts have been reported, and differences in results may be due to the type of probiotic used, the type of food consumed, the level of management, the method of probiotic use, and environmental conditions (Agarvall 2002). The results of a study showed that the production of growth factors (organic acids, B vitamins and amino acids), creating anaerobic conditions and increasing the growth of cellulosic bacteria and lactate consumption are among the mechanisms of probiotics in increasing the digestibility of food nutrients (Riedel et al. 2010).Considering the benefits of using probiotics in feeding young ruminants and suckling calves to improve growth performance as well as reduce antibiotic use and most importantly healthy growth and breeding of lambs that can in the future replace herds of mature ewes and rams, and ensure the economic future and Herd health of the herd. And also because of the lack of study on the use of these microbial additives orally in lambs and lactating Bakhtiari ewes, so this study investigates the probiotic effects of protexin on blood hematological parameters of lactating Bakhtiari lambs.

In this experiment, 28 ewes with one to multiparous were used. The ewes were divided into two groups. One group (14 head) received no probiotics and the other group (14 head) received 2% (v / w) solution (one gram of probiotic dissolved in five ml of water) per day of probiotics through oral and syringe one month until parturition. Probiotics were discontinued at parturition. The lambs born of these ewes were 28 (male and female). Treatments included 1) Control treatment (non-reception of probiotics by lambs and ewes), 2) Receive 1 g of probiotic by ewes, 3) Receive 0.2 g of probiotic by lambs 4) Receive 0.2 g of probiotics by lambs and 1 g of probiotics by ewes. The lambs were weighed weekly at birth and up to five weeks after birth. In order to measure hematologic and hematological parameters on 3, 14 and 21 days after the morning and by applying food restriction for 2 to 4 hours, blood was taken through the vein from all lambs. Blood samples were taken at 3, 14 and 21 days to measure hematological and blood parameters. Hematological parameters included eosinophils, lymphocytes, monocytes, neutrophils, hematocrits and white blood cells. Blood parameters included glucose, albumin, total protein, globulin, triglycerides, alkaline phosphatase, gamma glutamine transferase, acute phase proteins, oxaloallastic transaminase glutamate, and iron oxalate, including copper and iron, including calcium, iron, phosphorus, zinc. Hematology supplements and blood suppositories were determined using an autoanalyzer (model BT 1500, made in Italy).

The effect of protexin probiotic on body weight in lambs was not significant (p>0.05). Consistent with this result, the use of probiotic supplementation in lamb feeding during the experiment did not have any significant effect on daily weight gain (Baranowski et al. 2007). The effectiveness of compounds such as probiotics, which have different microorganisms, varies and depends on the composition of the animal's diet and nutritional needs, and may be ineffective with the slightest change. Therefore, animal feed management includes feed supply (completely mixed feed, separate forage and concentrate feed), number of feed times and physical shape of feed, chemical composition of feed including forage to concentrate ratio, dietary nutrient percentage, dietary effective fiber percentage and forage type. And the concentrate used in this study can be considered as a possible cause of differences in results. The effect of treatment on hematological data including eosinophil, lymphocyte, monocyte, neutrophil, hematocrit and white blood cell concentration in lambs was not significant (p>0.05). Hematological parameters are important in determining the functional status of animals. Consistent with this, in a report with the addition of biofeedback probiotics in the last month of gestation and by the end of lactation, lambs' red blood cell counts, neutrophils, lymphocytes, basophils, and isosophils percentages were significantly affected at the start and end of the experiment. Regarding the blood parameters, the effect of treatment on the concentration of albumin, alkaline phosphatase, total protein, triglyceride, globulin, gamma glutamine transferase, glutamic oxalacetic transaminase, glucose, albumin to globulin ratio, and Acute phase proteins was not significant lambs (p>0.05). Supplementation of lambs with probiotic had no statistically significant effect on total protein, albumin, globulin, and glucose concentrations in the pre-weaning period (Salim et al. 2017). Also, the addition of probiotics protexin to blood minerals (calcium, zinc, iron, copper) in lambs was not significant (p>0.05). Consistent with our results, no significant effect on blood phosphorus and calcium concentrations was observed with probiotic supplementation of zovitis (Dimova et al. 2013)..

Probiotic supplementation of protexin had no significant effect on lamb weight, hematological parameters and blood parameters. This indicates that this probiotic had no positive effect on lambs. Amounts and more levels of this probiotic are needed to achieve a rational response in lambs.Keywords: Acute phase proteins, albumin to globulin ratio, blood minerals, body weight, hematocrit, white blood cells

Understanding the genetic control of growth traits is one of the most important breeding goals in poultry industry. Genomic selection has provided the poultry industry with a powerful tool to increase genetic gains on economically important traits such as meat production. One way to identify new loci and confirm existing QTL is through genome-wide association analysis (GWAA). In addition identifying of genes loci with large effects on economically important traits, has been one of the important goal to poultry breeding. QTL assisted selection and genomic regions affecting the production traits have been considered to increase the efficiency of selection and improve production performance. Genome wide association studies typically focus on genetic markers with the strongest evidence of association. However, single markers often explain only a small component of the genetic variance and hence offer a limited understanding of the trait under study. A solution to tackle the aforementioned problems, and deepen the understanding of the genetic background of complex traits, is to move up the analysis from the SNP to the gene and gene-set levels. In a gene-set analysis, a group of related genes that harbor significant SNP previously identified in GWAS, is tested for over-representation in a specific pathway.

The aim of the present study genome wide association studies (GWAS) based on Gene set enrichment analysis for identifying the loci associated with related to body weight and shank length and diameter traits in advanced intercross line (AIL) using the high-confidence SNPs that enable us to study 161376 SNP markers simultaneously. For this purpose, the 599 advanced intercross line and 161376 markers were performed with mixed linear model (MLM) approach was used for the GWAS of the F9 generation, as implemented in the GCTA package (v1.92) (Yang et al., 2011) and no any correction to adjust the error rate. The gene set analysis consists basically in three different steps: (1) the assignment of SNPs to genes, (2) the assignment of genes to functional categories, and finally (3) the association analysis between each functional category and the phenotype of interest. In brief, for each trait, nominal P-values < 0.005 from the GWAS analyses were used to identify significant SNP. Using the biomaRt R package the SNP were assigned to genes if they were within the genomic sequence of the gene or within a flanking region of 15 kb up- and downstream of the gene, to include SNP located in regulatory regions. For the assignment of the genes to functional categories, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases were used. The GO database designates biological descriptors to genes based on attributes of their encoded products and it is further partitioned into 3 components: biological process, molecular function, and cellular component. The KEGG pathway database contains metabolic and regulatory pathways, representing the actual knowledge on molecular interactions and reaction networks. Finally, a Fisher’s exact test was performed to test for overrepresentation of the significant genes for each gene-set. The gene enrichment analysis was performed with the goseq R package. In the next step, a bioinformatics analysis was implemented to identify the biological pathways performed in BioMart, Panther, DAVID and GeneCards databases.

Gene set enrichment analysis has proven to be a great complement of genome-wide association analysis (Abdalla et al., 2016). Among available gene set databases, GO is probably the most popular, whereas KEGG is a relatively new tool that is gaining ground in livestock genomics (Morota et al., 2015, 2016). We had hypothesized that the use of gene set information could improve prediction. However, neither of the gene set SNP classes outperformed the standard whole-genome approach. Gene sets have been primarily developed using data from model organisms, such as mice and flies, so it is possible that some of the genes included in these terms are irrelevant for meat production. It is likely that a better understanding of the biology underlying meat production specifically, plus an advance in the annotation of the chicken genome, can provide new opportunities for predicting production using gene set information.11 SNP markers on chromosomes 1, 2, 4, 5, 7, 8, 10, 11, and 27 located in MSTN, CAPN3, PNPLA3, ANXA2, IGF1, LDB2, LEPR, FN1, ‌TMEM135, MC4R, EDN1, and ADAMTS18 genes were identified. Some of the genes were found are consistent with some previous studies and to be involved biological pathways related to muscle skeletal growth, energy metabolism and bone growth and development. According to pathway analysis, 19 pathways from gene ontology and KEGG pathway were associated with the body weight and shank length and diameter trait (P˂0.05). Among those pathways, the regulation of muscle organ development, regulation of cell growth and anatomical structure homeostasis biological pathway has an important role in the growth and skeletal muscle development. Also, the anatomical structure formation involved in morphogenesis, positive regulation of ossification and calcium signaling pathway significant association with body weight and shank length and diameter traits. Some of these regulatory regions, such as enhancers, are located far from the genes. Therefore, although the gene might be part of the analysis, the relevant variant would probably not be included in the gene set SNP class. Finally, linkage disequilibrium interferes with the use of biological information in prediction because irrelevant regions (regions without any biological role) capture part of the information encoded in relevant regions, causing both regions to exhibit similar predictive abilities. The use of very high density SNP data or even whole genome sequence data could alleviate some of these issues. Finally, it is worth noting that our gene-set enrichment analysis was conducted using a panel of SNP obtained from a single marker regression GWAS, which relies on a simplified theory of the genomic background of traits, without considering for instance the joint effect of SNP. Hence, other approaches (e.g., GWAS exploring SNP by SNP interactions) might provide a better basis for biological pathway analysis.

Considering, this study supported previous results from GWAS of body weight and shank length and diameter traits, also revealed additional regions in the chicken genome associated with these economically important traits, presented here should be contribute to a better understanding of the genetic control of growth traits in broiler chicken and using these findings can accelerate the genetic progress in poultry breeding programs.

In order to take advantage of breeding programs and productivity of poultry and other domesticated animals, it is essential to assess genetic variability and study the strategies to preserve genetic diversity. The Japanese quail is widely used as a model for animal research purposes in laboratory studies because of its small body size, short intergeneration interval, high growth rate, production of more eggs and meat. Although, Japanese quail has various benefits as a laboratory bird, but its genome sequence is not accessible now. The genome sequence of Japanese quail will deliver important genomic resources to accelerate different studies and to authenticate divergent lines of Japanese quail. Growth is a complex physiological pathway that occurs from fertilization until maturity in birds. Insulin-like growth factor I (IGF-I) gene is one of the most important candidate genes in different species which can affect the performance traits because of its function in metabolism and growth. IGF-I is a 70 amino acid polypeptide hormone with endocrine, paracrine, and autocrine effects. It has been reported that there is association of genetic polymorphisms of the IGF-I gene with growth traits in the poultry. There are relatively few reported studies about the relation between genetic markers of the IGF-I gene and body weights in quails. The objective of this study was undertaken to identify polymorphisms of the IGF-I gene using PCR single-strand conformational polymorphism (PCR–SSCP) analysis and to evaluate association of these polymorphisms with body weight in the Japanese quail.

For doing this research, body weight of the 110 quails under study (46 males and 64 females) in different ages were collected. All data were collected from the Natural Resources Research Center of East Azerbaijan. The data included the identification of the animal, year of birth, sex, body weights at 15, 30, 45 and 60 days. Genomic DNA was extracted from 10 μl of blood in presence of Pronase (Bailes et al., 2007) and stored in EDTA-coated tubes and placed immediately inside an ice box and transferred to the laboratory. The samples were stored at -20 until DNA has been extracted. The quality and quantity of extracted DNA were measured by %0/8 agarose gel electrophoresis. PCR was done for amplifying a fragment in size of 465 bp of IGF-I gene. The PCR primers for the IGF1 gene were designed based on GenBank. PCR primers of IGF-I gene was mentioned in Table 1. The PCRs were carried out in 25 μl volumes containing 1 unit Taq DNA Polymerase, reaction buffer 1X (Sina Gene, Tehran, Iran), 1/5 mM MgCl2, 0/2 μM each of dNTPs, 10 μM of each primer (Sina Gene, Tehran, Iran) and 30 ng of genomic extracted DNA as template. PCR was performed using the T-professional thermal cycler. The thermal profile consisted of 3 min at 95°C, followed by 35 cycles of 40 s at 95°C, 30 s at 58°C and 40 s at 72°C, with a final extension of 5 min at 72°C. Amplification was carried out in Mastercycler (Bailes et al.,2007). PCR products were detected by electrophoresis on %1/5 agarose gel containing ethidium bromide and were visualized in a gel documentation system with a UV transilluminator. PCR products were mixed with 20 μl of denaturing loading dye [95% deionized formamide, %0/35 xylene cyanol, %0/25 bromophenol blue and 10 mM EDTA] in a total volume of 10 μl. The mixture was denatured at 95°C for 15 min and was snap chilled on ice. The electrophoresis was performed in 0.5X TBE buffer (Tris 100 mM, boric acid 9 mM, EDTA 1 mM) at room temperature (18°C) and constant 110 V for 16 h. Polyacrylamide gels were stained with silver according to the protocol described (Benbouza et al.,2006). A statistical model included the mean of population, fixed effect of the sex, random effect of the genotype patterns and residual random term was done by using GLM of SAS software to find the association between the SSCP genotype patterns of PCR products with the body weights. Significant differences among means of different genotypes were calculated using Duncan method in the GLM program and P values of 0.05 were considered statistically significant.

The investigation of candidate genes is one of the foremost techniques to reveal whether definite genes are associated with the economic traits in animals. We successfully amplified the exon 4 of the IGF-I gene. All extracted DNAs from quail blood samples yielded a specific single band PCR product without any nonspecific band. Therefore, the PCR products were directly used for SSCP analysis. The results of SSCP showed that this population was polymorphic at the studied loci and three different genotypes with frequencies of 7.27%, 50.91% and 41.82%, respectively were observed in the examined quails (Figure 3). The results indicated that the exon-4 of IGF-1 gene is polymorph and there was a significant difference (P<0.05) between the genotype patterns and body weight on 30 days. However, for association of gender effect on body weight, there was a significant difference (P<0.05) in the age of 60 days. Also the average daily gain in females is more than males in different ages.

The goal of this study was to determine genetic polymorphism of IGF-I gene in Japanese quail. According to this research, the selected locus for investigating of IGF-I gene in quail can be considered as a locus that effects on body weight and growth rate of quails. It can be also measured as the factor that cause of difference of body weight in different periods.

Growth and reproductive traits are well-known characteristics of living organisms because of their direct relationship with economic benefits. Genetic description of the growth curve and the correlation of its parameters with growth and reproductive traits can be useful in determining selection strategies. For this purpose, 2035 quail data, which were collected during the years 1398-1396 in the Agricultural Research and Training Center and Natural Resources of Khorasan Razavi, were used. To identify the fixed factors affecting the traits, the linear model of GLM procedure of SAS software was used and to estimate the parameters of the growth curve, the nonlinear regression model of Gampertz was used. Genetic components variance (co) of growth curve and reproduction traits was estimated using maximum likelihood multi-trait analysis by DMU software. Heritability of body weight at 35 days (BW35), asymptotic weight (a), maturity rate (k), age at inflection point (IPT), absolute growth rate (AGR), relative growth rate (RGR), number of eggs (EN) and fertility percentage (FR) were estimated respectively 0.222, 0.238, 0.416, 0.283, 168 to be 0.22, 0.222, 0.283 and 0.071. Growth curve parameters with AGR and RGR and BW35 days had high genetic correlations (0.434 - 0.924). The strongest correlation was obtained between IPT and RGR (0.924). Except for genetic correlations between EN and FR percentage with other traits, most of the genetic correlations were positive. Based on this results, management of environmental factors are effective in increasing growth and reproductive performance, and genetic selection for growth trait using growth curve parameters can improve the genetic potential of the animals.

This study was conducted to investigate the effects of toxin binders and prebiotics on growth performance, intestinal microbial population, stress andantioxidant indexes of broiler chicks fed diets contaminated with aflatoxin B1. In this study, 600 1-d-old mixed broiler chicks (Ross 308) wereinvestigated in 10 treatments with 6 replications and 10 chicks per replication. Experimental treatments included: Negative controls un-supplementedand supplemented with ASRI1 and ASRI2 toxin binders and prebiotic and positive groups un-supplemented and supplemented with ASRI1 andASRI2 toxin binders and prebiotic, ASRI1 +prebiotic and ASRI2 +prebiotic. Growth performance, stress indexes of heterophile, lymphocyte,bacterial population and stress indexes of super oxide dismutase (SOD), glutathione peroxidase (GPx) and malondialdehyde (MDA) wereinvestigated. Dietary inclusion of aflatoxin into diet increased heterophile, heterophile:lymphocyte ratio and decreased lymphocyte (P<0.05), but toxinbinders and prebiotic alleviated effects of aflatoxin on heterophile and lymphpocyte. Thepopulation of E. coli and lactobacilli were significantlyhigher and lower in positive control compared to negative control (P < 0.05). The results also showed that the serum concentrations of antioxidantenzymes were significantly lower in negative control compared to positive control (P < 0.05). In sum, aflatoxin showed negative effects on growthperformance, intestinal microbial populations, stress and antioxidant indexes but toxin binders and prebiotic decreased its negative effects andinclusion of ASRI1(3kg/ton) was better than other toxin binders.