محمد مرادی شهربابک

Nowadays, with the progress obtained in molecular genetic techniques and bioinformatics, alternative methods have been invented to increase the speed and efficiency of DNA sequencing and their roles in genome level.  In the whole-genome sequencing method, the whole genome sequence of organism (nuclear-genome with mitochondrial DNA) is sequenced. One of the important topics in genomics is genome differences, including single-nucleotide polymorphisms and INDELs for the relationship between genotype and phenotype. Polymorphisms are powerful tools for molecular analysis of economic traits and are important in breeding programs. For this purpose, whole-genome variations of Mazandarani buffaloes were identified and classified. In this study, the whole-genome of 4 Mazandarani buffaloes was sequenced with the Illumina platform. Data quality was measured by FastQC software. BWA-MEM was used for alignment with reference genome. Finally, the variants were obtained using freebayes and the SnpEff was used to calculate the effects of the variants. The result of aligning led us to identification of 56537534 SNPs, and 6128529 indels with an average coverage of x4 to x13. The most number of variants were observed on 1 and X chromosomes, and the least number were in 23 and mitochondrial chromosomes. The transition, transversion and rate of transition/transversion mutations were 236549743, 108015966 and 2/19 respectively. Also, the mutations was calculated. The frequency of variants in intergenic regions was estimated to be 52746727, intron 23560994, downstream 3713594, upstream 3571409 and exon 574093. Considering that this research is the only one that carried out to identify the genomic variations of Mazandarani buffalo, the identified genomic variations can be used for the development of SNP-arrays for Iranian breeds.

Bovine Leukemia Virus (BLV) infection is more common in dairy cattle herds. The main cause of leukosis is the disease that leads to the creation of cancerous lymphocytes in different organisms of the body and affects different species, including cattle. This disease reduces milk production and causes reproductive diseases, and finally the removal of infected animals. Due to trade restrictions and deaths caused by lymphosarcoma, it causes direct economic losses, which is also related to the decrease in milk production and the increase in the elimination rate. No treatment or vaccine is known for this disease so far. Therfore, studying the genomic regions related to susceptibility to BLV infection can be effective in controlling and treating this disease and genetic improvement of animals. This research aimed to perform a whole genom-wide association study (GWAS) study of cattle to identify genomic regions and candidate genes associated with BLV infection.

Material and Methods:

 This study was conducted using Holstein cows that were naturally infected with BLV. For this purpose, blood samples of 150 Holstein cows in an industrial dairy cattle farm in Isfahan were collected, and DNA and serum of them were extracted. The prepared DNA samples were genotyped using k30 microarrays (SNPchip30k) (by Illumina). Quality control of sequences for rare allele frequency components (PMAF < 0.05), missing genotype (PMIND > 0.05), genotyping rate (PGENO > 0.05), and Hardy-Weinberg equilibrium (PH-W < 1×10-6) and significance test was performed by PLINK software. Analysis of the ontology of genes was done by the online database https://www.Uniprot.org and finally, the ontology diagram of genes was drawn and analyzed by the online database PANTHER.

After control analyzing, 145 cows (77 cases and 68 controls) and 22868 markers were left for further analysis, finally 8 markers higher than the significant threshold were identified, and most significant markers were located on chromosomes 17 and 21. Using ensemble sites and genecards, genes associated with significant selected markers were identified. The most important of them were GRK4, TP53BP1, SCAPER, GLRB, PDGFC, TNIP2, PSTPIP1, CEP350, MR1, TOM1L2, SREBF1, COPS and TNFRS13B. Gene Ontology (GO) analysis showed that these genes are more involved in protein-coding and play a role in regulating enzyme activities, intercellular exchanges, DNA stability, calcium activity, nervous system, and lipid activity. Also, according to other research, these genes played a role in cases such as infectious poison lesions, subclinical ketosis disease, BCS of cattle, fatty acid metabolism and fat deposition, various infections such as mastitis, and in meat traits and muscle stiffness in beef cattle. It should be noted that some of these genes were related to the pathways of innate immunity, humoral immunity, and cancer tumors.

Therefore, it can be concluded that whole genome wide association study analysis as well as gene ontology analysis to identify genomic regions related to viral infections such as leukemia can be effective in designing treatment methods and prevention methods and in choosing Genomics and breeding programs in Iranian dairy cows.

Paratuberculosis  known as Johne's disease, is a contagious, chronic, intestinal disease in ruminants, which is caused by Mycobacterium avium paratuberculosis subspecies (MAP) and causes a huge economic damage to the livestock industry. There is no effective treatment nor vaccine for MAP infection. Thus, investigating the genetic regions associated with susceptibility to MAP infection can provide a better understanding of paratuberculosis mechanisms and contribute to the genetic improvement of animals. The aim of this study was to identify genomic regions and candidate genes associated with susceptibility to MAP infection in Holstein dairy cattle using a genome-wide association study (GWAS). For this purpose, blood samples of 150 cows were collected, and DNA and serum of them were extracted.The prepared DNA samples were genotyped using bovine SNPchip30k (Illumina). Quality control of genotypes was performed based on the minor allele frequency (PMAF < 0.05), missing genotype (PMIND > 0.05), genotyping rate (PGENO > 0.05), and Hardy-Weinberg equilibrium (PH-W < 1) 10-6) using PLINK software. The association was performed using a mixed linear model in PLINK software. After quality control, 28749 markers on 142 cows (99 cases and 43 controls) were remained for the further analysis. Associations analysis showed that 16 markers located in chromosomes 30 and 6, were associated with  Johne's disease. Positional candidate genes for Johne's disease were identified. The most important identified genes were LMX1A, THSD7A, ELMOD2, ATP6AP2, RNF150, SLIT3, SDE2, PARP1, PBX1, TFB2M, SMYD3 and PYCR2. Gene ontology analysis showed that most of the identified genes are involved in the nervous system, cytoskeleton system, regulation of cytokines, Golgi apparatus, catalytic activity, calcium ion transport, and resistance to diseases. Whole genome-wide association study (GWAS) and ontology analysis (GO) can help to identify candidate genes and regions related to sensitivity to MAP in dairy cows, which can play an important role in the treatment and prevention of Johne's disease.

The aim of this study was to investigate the effects of dietry cation-anion difference (DCAD) levels and crossbreeding on carcass characteristics of lambs. In this study, 30 Lori Bakhtiari and  first generation Lori Bakhtiari × Romanov × Pakistani lambs (50% Lori Bakhtiari, 25% Romanov, 25% Pakistani)  with an average age of 90±10 days and an average weight of 33±1.5 kg were divided into two groups of 15 lambs, each group was fed with a different level of DCAD. Carcass weight, carcass yield, viscera weight, cross-sectional area of Longissimus muscle and carcass length did not show any significant difference between purebred and crossbreds and also between diets. Crossbreeding also significantly increased the weight of valuable and salable carcass parts (P<0.05). However, according to our findings, no difference was observed in terms of weight of salable carcass parts between anionic and cationic treatmentsgenotype and DCAD did not have any significant effect on the composition of carcass fatty acids. The meat shear force of Lori Bakhtiari × Romanov × Pakistani lambs compare to Lori Bakhtiari  lambs and anionic diet compare to cationinc diet was lower (P<0.05). Lori Bakhtiari lambs had a higher mean in brightness index and Longissimus muscle redness than Lori Bakhtiari × Romanov × Pakistani lambs (P<0.05). Therefore, anionic diets and Crossbreeding can be considered as effective ways to increase the quality and crispiness of sheep meat.

Crossbreeding is a common method for exploiting genetic differences between different breeds of a species, during which offspring are usually obtained from two pure breeds through mating, which are expected to have parental traits. to improve, which includes productive traits and traits related to the health and survival of the animal that each of the parents may have superiority in one of these traits, therefore, hybridization with the aim of combining the superiority of parental traits and improving them in the results It takes place. In sheep, cross-breeding is a well-known method to improve production, including meat, milk, wool, and reproduction. Depending on the parent breeds and their purity percentage, different results may be observed in the offspring. On the other hand, food ration is a determining factor in the manifestation of the genetic power of livestock, and in the meantime, the anion-cation balance of the diet (DCAB) plays an important role by affecting the acid-base balance and homeostasis of the body. Since maintaining the acid and base balance of the body is related to the maintenance of the animal and is preferable to reproduction, lactation and growth, therefore the performance of the animal is significantly affected by the change in the acid and base balance. Therefore, the purpose of this research is to investigate the difference of diet anion-cation on performance, blood and digestion parameters and rumen parameters.

In this study, 30 Lori Bakhtiari and Lori Bakhtiari × Romanov × Pakistani lambs with an average age of 90 ± 10 days and an average weight of 32.9 ± 1.5 and 32.25 ± 1.5 kg respectively used. The lambs were placed in two racial groups in the form of a 2x2 factorial design and with two levels of anion-cation difference (DCAD) of -100 and 100 milliequivalents per kilogram of dry matter for 90 days. The whole fattening period was 84 days and anionic diet was used in the last 14 days of the period.

Based on the results of this study, dry matter consumption, weight gain and feed conversion ratio were not affected by breed. However, dry matter consumption decreased in lambs that consumed anionic diet (P<0.003). Also, blood parameters, apparent nutrient digestibility, ammonia nitrogen concentration and rumen fluid pH were not affected by diet and breed.

The results of this study indicate that the mixing of Lori Bakhtiari breed with foreign breeds has no effect on its fattening characteristics, and the use of anionic ration, along with its potential benefits, can lead to a reduction in dry matter consumption, so according to the results This research suggests that anionic or cationic rations can be used for fattening animals with various purposes without significant effect on growth performance and digestibility of nutrients as well as parameters related to rumen fluid

Advances in next generation sequencing technologies have created the ability to efficiently and economically sequence the whole genome more than ever and provide the opportunity to discover and introduce multiple polymorphisms throughout the genome of organisms. Azeri buffalo is one of the most important breeds of Iran and it is scattered in the north to the northwest of the country and is completely adapted to the environmental conditions of this geographical region. The main purpose of this study is to introduce the genomic diversity of Iranian buffaloes and categorize them. Also, introducing the effects of these variations on different genomic regions of Azeri buffaloes have potential applications in breeding programs.

In this study, whole genome sequencing of 5 heads of Azeri buffaloes native to Iran was done by Illumina sequencing platform. Data quality was measured by FastQC software. BWA-MEM software was used for alignment with the reference genome. Finally, the variants were identified using freebayes and the SnpEff program was used to calculate the effects of the variants by mentioning their type, location and number. The alignment result of high quality reads with the reference genome showed that the alignment percentage for all 5 samples was over 97.5%, which indicates the high quality of short reads.The coverage in the sequenced samples was determined between 4x and 12.8x.

finally, 76,298,858 million variants were identified, including 57,921,822 SNPs, 6,162,328 indels, 10,534,042 MNPs, and 1,680,666 MIXEDs. Small deletions and insertions with a minimum length of 1 bp, a maximum length of 28 bp and an average of 1.39 bp were identified. From the total number of variants, the highest frequency of variants was observed in intergenic regions, 53,789,879 (62.022 percent), intron 24,003,682 (27.677 percent), respectively, and the variants detected in exons had the lowest number.

Identification of genome-level variations such as snps, small insertions and deletions, and multi-nucleotide polymorphisms in different populations are a valuable resource in genetic research and can be useful in locating genomic segments responsible for important economic traits. Also, the large volume of SNPs enables genome-wide association studies in animals. In addition, the genomic variations identified in the present study can be used to develop high-density SNP arrays in Iranian breeds for genetic and breeding applications.

The rapid development of sequencing technologies and bioinformatic tools has made it possible to sequence the entire genome of many species, providing a starting point for exploring the genome-wide genetic diversity of organisms. The buffalo is one of the most important domesticated animals in the world and has great economic value for humans, being used for milk, meat, leather and most importantly as labor. Khuzestani buffalo are among the most important buffalo in Iran. These animals are scattered in western and southwestern Iran. The largest population of this breed is in the Khuzestan province and they are fully adapted to the geographical features of this region

In this study, whole genome sequencing of the Khuzestan buffalo was performed in paired-end format using Illumina technology. Quality control of the readings obtained met all quality parameters and processing of the readings showed that all samples were of high quality. The BWA-MEM software package was then used to match the data to the reference genome. Genome variants were obtained with the Freebayes software. The final filtering of the variant file then took place. This filtering serves to increase the quality of the analysis and to sort out inferior variants.

The alignment percentage for all samples was over 97.44% and also the coverage in the sequenced samples ranged from x 4.3 to x 9.12, indicating reasonable quality of the reads. Also, in this study we identified 76,676,529 million variants fairly evenly distributed on the chromosomes of the Khuzestan buffalo. The highest and the lowest number of variants were observed on chromosome 1 chromosome 28, repectively. In this study, the total number of translocation and inversion mutations in the genome level was 298,193,017 and 135,694,466, respectively. In addition, the ratio of transitions to transversion was estimated at 2.1989 (Ts/Tv).

The presence of genetic diversity in the native population of Iranian buffalos are valuable parameters that can be studied to evaluate the genetic potential of economic traits in these populations in order to design suitable breeding programs.

 Selection in animal populations to increase the frequency of ideal alleles causes of remaining some signs in the animal genome, which are usually associated with important traits. Today, with developments in next-generation sequencing and easier access to animal genomic information, some models have been proposed to identify selective signatures based on allelic frequency and haplotype blocks. This research aimed to identify the selective signatures in two horse breeds of Caspian and Kurdish using a k70 SNP chip.

 In this research blood samples from 35 Caspian and 31 Kurdish horses were collected. After DNA extraction and sequencing (by Illumina company), Quality control of the data was performed for minimum allele frequency (PMAF<0.05), genotyping rate (PGENO < 0.5), and deviation from Hardy-Weinberg equilibrium (PH-W<1 ͯ 10-6). Then the theta (θ) test and ensemble site were used for identifying selective signatures and the positions of snaps respectively, and finally, the genes related to these positions were identified.

 After quality control of data and integration of genomic data of two populations based on R package protocols, 61 horses with 52,650 SNPs remained for the rest analysis. Finally, Fst statistical test based on unbiased estimator theta method 31 differentiating markers of the two studied horse breed were identified

The results showed that Caspian and Kurdish horse breeds belong to two separate groups. The Kurdish horse breed has more diversity and variety than the Caspian. The most important genes associated with significant SNPs were INPP5F, HPSE2, R3HCC1, DOCK3, ITGB6, GM6B, PHEX, WDR13, LRCH2, GRIA3 and THOC2. Most of the identified genes were associated with intercellular exchanges, muscle contractions, immunity, membrane support, DNA stability, and the nervous system.

Conservation of the genetic diversity of indigenous animals is very important. For the sustainable use of genetic resources, it is necessary to first study the genetic structure of populations. The main goals of this research were to identify the population structure of Turkmen and Darehshori horses using dense SNP markers and to compare the effectiveness of PCA, DAPC, and SPC methods in clustering these populations.

For this purpose, 67 Turkmen and 39 Darehshori horses were genotyped using Illumina EquineSNP70 BeadChip. After applying quality control steps, five Turkmen horses and one Darehshori horse were removed. Then, the structure of populations was identified by three methods of principal component analysis (PCA), discriminant analysis of principal components (DAPC), and superparamagnetic clustering (SPC). These methods do not depend on previous assumptions and make it possible to analyze very large genome databases without prior knowledge of individual ancestry. These methods are also very fast and efficient.

This study compared the efficiency of these three clustering methods in identifying population structures. All three methods were successful in separating the two breeds, and Turkmen and Darehshori breeds were grouped into separate genetic groups. The difference is that the DAPC method only separated the two main populations, but the PCA and SPC methods could identify several subpopulations in each breed. The results of this study showed that the SPC method for studying the population structure of indigenous breeds with unknown information can be more useful than other methods. Therefore, using this method, a suitable program can be designed to conserve and use genetic resources.

PCA, DAPC, and SPC methods were able to successfully identify the genetic structure of Turkmen and Darehshori breeds, and in general, it can be said that the information obtained from dense SNP markers can be a powerful tool for identifying the population structure of indigenous breeds.

The growth models own a very great importance in biological systems.  For example, by analyzing the growth curve of ruminant animals and poultries, it is possible to fastener and to manage their rearing, nutritional and behavioral requirements, based on their growth routines and principles. On the other hand the growth pattern of animals might be used in evaluating their genetic potential for breeding purposes. Thus, to evaluate and describe the growth pattern of Japanese quail, this study aimed to evaluate the capabilities and advantages of non-linear and nonlinear mixed models to describe and evaluate the growth pattern of Japanese quail.

In order to assess and designate the growth pattern of Japanese quail, we used the growth data of three groups; high weight (HW), low weight (LW) and the control lines of Japanese quail. Different models, including logistic, Gompertz and Richard's both non-linear and nonlinear mixed models were fitted to the data. For evaluation of models three criteria including coefficient of determination (R2), mean square error (MSE) and Akaike's information criterion (AIC) were employed as criteria to compare the mentioned six different models.

Values of the coefficient of determination (R2), for logistic, Gompertz and Richard's nonlinear models were 0.954, 0.957 and 0.951, mean square error (MSE) for three models were 74.034, 72.560 and 72.730, and Akaike's information criterion (AIC) for the models were 65829, 65307 and 65349, respectively. The results for non-linear mixed models, in the same order mentioned above and for R2, MSE and AIC, were 0.976, 0.978 and 0.978; 33.400, 31.658 and 31.849; 61449, 60641 and 60591 respectively.

The results showed that nonlinear mixed models had higher accuracy and less mean square error, compared to nonlinear models and Richard’s model is more capable (better) to the predict growth pattern of Japanese quail. Also among non-linear models Gompertz model had a better fit to the purpose. In general it can be said that the parameters determined by the functions inspected in this study, are not much different.

Honeybees, as pollinating insects, are an important part of nature. Because behavioral traits are so important in honeybees, comparing brain tissue transcriptomes of the two subspecies with aggressive and calm behavioral characteristics makes it possible to understand this behavioral difference genetically. This study aimed to investigate to gene expression profile and identify the key genes in brain tissue in Italian (Apis Mellifera Ligustica) and African (Apis mellifera Scutellata) honeybees concerning behavioral traits. The Italian honeybee has calm behavioral characteristics, while the African is known as an aggressive honeybee.

RNA-Seq data were obtained from the NCBI  (GEO) database, and after pre-processing of reads, the brain tissue transcriptomes of both subspecies were aligned and mapped on the honey bee reference genome (v A.mel 4.5), and then data qualification, transcriptome assembly, differential expression analysis, and gene ontology were performed.

Differential gene expression analysis identified 16,701 genes on the honeybee reference genome, of which 22 genes in brain tissue between the two subspecies had significant differential expression (adj p-value <0 .05 and Log2FC>2). As well, some of these genes were first identified. Gene ontology analysis showed that among these 22 genes, such as ITPR, MRJP, HSP70Ab, MBS, GB45410, and Def1 are directly or indirectly involved in the occurrence of various traits such as defensive, health behavior, reproductive, heat, light, and smell sensitivity. In addition, the SNPs encoding the honeybee brain tissue genome were identified in both subspecies, and 99636 SNPs were identified in the Italian, and 92514 SNPs were identified in the African subspecies.

RNA-seq data, due to its high throughput, can provide us with accurate information about the expression of genes in different tissues in various subspecies. In this study, genes involved in honeybee behavioral traits and the SNPs in these genes were identified

The agriculture contribute to 50-60 % of global methane emission and ruminants have a key role in this contribution. Methane has an important role in global warming and it's global warming potential is 25 times greater than CO2. Furthermore, methane is the second most abundant global anthropogenic greenhouse gas after carbon dioxide. The present study aimed to perform genome wide association study to identify genome regions affecting the predicated methane production based on the concentrations of volatile fatty acids of rumen in Iranian Holstein cattle. One-hundred and fifty hair and rumen digesta samples were sampled using the two-tailed strategy based on breeding values of milk. After the measurement of the concentration of volatile fatty acids of rumen, methane emission of each animal was predicated according to these acids. DNA of animals was genotyped using GGP-LD v4 SNP panel (contains 30108 SNPs). Fourteen significant SNPs associated with methane emission trait located on 1, 2, 6, 10, 15, 17 and 18 chromosome were identified. Using annotating some quantitative trait locus (QTLs) were discovered around some of these SNPs. The results showed a genetic selection potential to mitigate methane emission per animal. Since genetic improvements are heritable, cumulative, and permanent, this improvement would be permanent and beneficial.

Establishment and maintenance of pregnancy are essential for product persistency in ruminants, and especially in dairy cattle. Embryo implantation into the uterus is an essential process for the maintenance of pregnancy, and involves complex interactions between the embryo and maternal endometrium. Examination of genes and mechanisms regulating the initiation of implantation is necessary to understand implantation process. In this study, in order to better understand the molecular basis of implantation, we undertook the transcriptome profiling of endometrial cells of pregnant with non-pregnant cows, during this period. In total differentially expressed genes were identified with the comparison of the endometrial profiles. Thus, after preprocessing and analysis of data and meta-analysis, gene interactions were investigated using data mining approach. Also with the reconstruction of network and search for important and functional modules, we found 4 main modules. The most important genes contained CLU, ACTA2, MX1, MX2, C1S, COL3A1, S100A11, NID1, SELL, PTN and CDH13. The results of this study suggest that identified modules can be used as markers for uterus receptivity, and embryo implantation.

The main objective of dairy farmers is to maximize their profit. Increased incidence of mastitis in farms is one of the health problems, causing in serious economic losses as a consequence of treatment costs and reduction of production and longevity. The objective of this study was to evaluate the genetic architecture and associated genomic regions with milk production and somatic cell score (SCS) as an indirect measure of mastitis and the quality of raw milk. Thus, an SNP data set from 1938 Holstein bulls were used in a single-step genome-wide association study. The proportion of additive genetic variance (agv) for each of 1.5-Mb genomic window (adjacent SNPs) was used to identify informative genomic regions, accounting for more than 1% of the agv. A total of 11 significant windows over 9 bovine autosomes were found for the SCS. A peak on BTA14 explained the largest proportion of variance (3.85%). These regions together, explained 20% of agv and harbored 94 candidate genes. For milk yield, we identified 6 informative windows across 6 chromosomes, and a peak on BTA10 explained 2.08% of agv. These regions, explained 8.8% of the agv and sheltered 89 candidate genes. For the fat yield, 9 significant windows were identified on 7 chromosomes and explained 15.6% of agv, and 9 windows contained 87 candidate genes on 8 bovine autosomes were associated with milk protein yield (10.6% of agv). Four genomic regions had a pleiotropic effect. These findings can be an important source of information in genomic evaluation of dairy cattle.

In order to evaluate the effect of genotype by environment interaction on production traits of Holstein cattle of Iran, first lactation test day records of 344170, 135000 and 156840 of milk, fat and protein yield on 34417, 13500 and 15684 cows and SNP markers of 1935 genotyped bulls were used. The production data were retrieved from the Animal Breeding Center and Productions Improvement of Iran’s database which were collected from 2013 to 2018. To consider the interaction of genotype and environment, mean of temperature-humidity index (THI) in three days before each test day records as continuous environmental effect were retrieved from the 35 closest meteorological stations in the vicinity of 139 Holstein herds from 13 provinces. Variance and covariance components were estimated through a single-trait random regression model with orthogonal Legendre polynomials of second order for days in milk and THI using AIREMLF90 software. The results showed that changes in THI across lactation led tofluctuations in additive genetic variance over time. The change in heritability of milk production traits over lactation followed the same trend as additive genetic variance. The results from cross-validation analysis showed that including genomic information into the predictive model, increased prediction accuracy and including THI information increased unbiasedness. Due to the changes in milk production of daughters of bulls across days and THI , genotype by environment interaction should be considered when selecting bulls under different conditions.

This study was conducted to evaluate prevalence of BVD and the strategies which were applied for prevention of BVD over the past 50 years in some provinces of Iran. Blood samples of 500 Iranian Holstein race were randomly collected from three dairy farms located in Tehran, Isfahan and Qazvin provinces. BVD control protocols of these farms were recorded. ELISA technique was used to measure the antibody and antigen titers for BVD. RT-PCR technique was performed to investigate the presence and the type of virus in all samples. The prevalence of Ab-/ Ag-, Ab+/ Ag-, Ab-/ Ag+ and Ab-/ Ag+ were 10.2%, 78.8%, 7.2% and 3.8%, respectively. Furthermore, approximately 4.2% of the animals were PI and the prevalence of antibody and antigen titers had not significant difference in three provinces. All positive samples were BVDV type 1. Type 2 was not observed in this study. The results of the study indicated that the efficiency of the used protocols to control BVD diseases is not successful. So, to control the BVD, applying large management policies at the national level is fundamental beside the biosecurity strategies.

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.

The objectives of this study were to estimate heritability and genetic, environmental and phenotypic correlations between retained placenta (RP) and metritis (MET) and also identification of risk factors associated with these traits in the first three parities of Iranian Holsteins. In the present investigation, data on RP and MET in Holstein dairy cows which were collected from 2008 to 2017 in 17 large dairy herds were used. Data across the first, second and third parties included records on 63039, 46265 and 30031 cows, respectively. A multivariate analysis under threshold models was considered for genetics evaluation. Multivariate Logistic regression models were used to identify the risk factors associated with MET and RP. The most important risk factor associated with RP and MET were stillbirth and Retained Placenta, respectively. Posterior means for heritability of RP were 0.06, 0.03, and 0.05 and those of MET were 0.03, 0.2, and 0.03 in the first, second, and third parity, respectively. Posterior means of genetic correlations across parities were moderate to high for RP (0.41-0.73) and MET (0.34-0.9). Genetic and phenotypic correlations between RP and / or between MET across the parities were lower than unity which implying RP and/or MET may be considered as distinct traits in different parities which is required to be considered in genetic evaluation of these traits in the Iranian Holstein cows.

In order to estimate the effective population size (Ne) in Iranian water buffalo blood and hair samples of 407 individual from Azari (N=260), Khuzestani (N=120) and Mazandrani (N=27) buffalo populations were gathered. After DNA extaraction, the samples were genotyped using Axiom® Buffalo Genotyping 90K Array. The Ne was estimated from 700 to 4 generations ago and also for the present generation by linkage disequiblirum data and based on heterozygote-excess method using NeEstimator (V2), respectively. Estimated Ne for Azari, Khuzestani and Mazandarani were calculated 1530, 1375 and 1141, respectively, for 700 generations ago. Ne for the present generation in Azeri, Khuzestani and Mazandarani were estimated 447, 226 and 35, respectively. The Ne for Azeri and Khuzestani were relatively high and these two populations were not endanger to extinction, but their Ne has been declined in the resent generations massively and it is necessary to care about the maintenance of Ne and relatively high diversity for these populations. However, the Mazandarani population is endangered because of low Ne and so it is necessary to carefully monitor their effective population size, improve the profitability of production and planning a suitable mating scheme to control inbreeding and genetically conserve this population.

Increased homozygosity resulted from mating of relatives is considered as one of the challenges faced in dairy farming industry which has attracted the attentions. This research has been conducted to measure homozygosity based on SNP and ROH in high- and low-producing Holstein cows. In current research, both random regression and pedigree index approaches were used to obtain candidate animals for genotyping process. The samples were obtained from 150 Holstein dairy cows (75 by high- and 75 by low-EBV for milk production). We proposed a suitable method, by integrating breeding value estimation calculated by random regression and pedigree index, to select the candidate animals for genotyping. The results showed that putting too much emphasis on production traits in high-producing dairy cows had negative impact on the traits associated with fertility (DPR = -0.55) and productive life (PL = 0.1). The calculated homozygosity based on ROH showed different amount of variation in different chromosomes in the cows with high and low production which may be related to uneven distribution of genes influencing production traits in different chromosomes.

The objective of this study was the detection of polymorphism in ATP1A1 gene and its association with conception rates in Holstein and Sarabi cows by PCR-SSCP method. For this purpose, blood samples were taken from 124 cows. DNA was extracted from whole blood using modified salting-out method and polymerase chain reactions were performed for amplification of 330bp fragment of the bovine ATP1A1gene. The polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) method was used to scan for the mutations within the amplified regions. Subsequently, a numbers of samples per each band pattern were sequenced for identification of Single Nucleotide Polymorphism (SNP). The results of the sequencing and alignment using available sequences in NCBI two SNPs in the ATP1A1 gene that one of those was located in exon14 and another one in intron14 area and the mutation located in exon area was along with no changes in amino acid and obtained protein of this gene. For evaluating of association between this locations and conception rate trait, the band pattern (haplotype) were considered in the model. The results showed that the observed haplotypes in the ATP1A1 gene is not significantly correlated with conception rate.

In order to detect signature of selection on buffalo genome, a set of 287 water buffalo samples from 260 Azari and 27 Mazandarani buffalo breeds were genotyped using the Axiom® Buffalo Genotyping 90K Array. The unbiased fixation index method (FST) was used to detect signatures of selection. In total, 14 regions with outlier FST values (0.1%) were identified. Annotation of these regions using the UMD3.1 Bos taurus Genome Assembly was performed to find putative candidate genes and QTLs within the selected and 105 genes and 28 QTLs with selection signatures were detected. A high proportion of identified genes (N=27) in regions under selection were involved in olfactory receptor, also some of the detected genes were associated with growth and body development, metabolicand apoptosis possesses, immune system development, and mammary gland development. Some of the identified QTLs in regions under selection were associated with growth traits such as body weight at birth, weaning and mature, subcutaneous fat, meat yield and carcass weight. The detected QTL for milk traits were only associated with milk contents and somatic cell count. However, it is recommended to carry out association studies to show the actual function of these genes.

The methane production from ruminant production system was estimated to reach 250-500 L per animal per day which has been reported to contribute up to 8-10 % of global warming during the next 50-100 years. The aim of this study was to investigate the correlation among methane emission (predicted by volatile fatty acids) with milk production traits, its components and breeding values (BV) of these traits in Iranian Holstein cattle. The rumen digesta was obtained from 150 cattle through stomach tubing and this population divided into 2 groups with 75 cattle in each (the groups have different milk production BV). Data were analyzed by R.3.3.0. The results showed that methane emission per unit of milk and fat were different in the two groups (P<0.0001). Also, the BVs of milk production, fat and protein traits and daily production of milk, fat and protein had weak to moderate negative correlation with methane emission per unit(P<0.05). The highest correlation was observed between daily production of fat with methane emission per unit of fat (-0.79) as well as daily milk production with methane emission per unit of milk (-0.62). These results showed that methane emission may be reduced by indirect selection per generation for the traits had a high correlation with the gas (daily production of milk and fat).

The objectives of this study were to identify a suitable mathematical method for describing the growth traits of Mahabadi goat. Thereafter, four non-linear growth function of Brody, Gompertz, Logistic and Von Bertalanffy were applied. Growth curve analyzed based on weekly records of live weight form birth to 105 days of Mahabadi goat breed. Growth models were fitted to a total of 2036 weight-age data belonging to 126 kids. The growth models were compared by using the coefficient of determination (R2), Root mean square error (MSE) and Akaike information criterion (AIC). Among all non-linear models, the Brody function had the smallest AIC and MSE values and the higher R2 value, indicating the best fit for Mahabadi breed growth data. Average of birth weight, weaning weight (105days old) and pre-weaning average daily gain (ADG) for Mahabadi goat were3.25kg, 13.5kg and 0.092kg, respectively. The results of this study can help farmer to management strategies and make decision in selection and culling of kids through the growth curve.