gene ontology

In recent years, highly pathogenicity avian influenza (HPAI), especially H5N1, has emerged as a major global health concern due to its potential as a zoonotic disease and its devastating impact on poultry populations. Identifying the molecular mechanisms of response to HPAI infection is critical to control, treat, and prevent the risk of a potential pandemic. Microarray technology is becoming a standard technology used in research laboratories all across the world and it is considered as one of the centers of research in cellular processes related to the level and manner of gene expression, including gene function and cell differentiation mechanisms. By using microarray technology, it is possible to obtain a detailed view of the interaction function of genes while simultaneously studying how the genome is expressed. Using microarrays provides the analysis of gene expression in response to viral infections such as influenza, etc., the study of host-pathogen interactions, and also the identification of the effectiveness of drugs and vaccines. This study aimed to analyze the microarray data of H5N1 avian influenza to compare the gene network and analyze the functional pathway in chickens and ducks.

Data mining and searching of microarray data related to Highly Pathogenic Avian Influenza infection was done in the GEO gene expression database (https://www.ncbi.nlm.nih.gov/geo). The microarray data set with accession number GSE33389 based on the GPL3213 platform was selected which contained lung tissue samples challenged with H5N1 virus in chickens and ducks. Normalization of selected microarray data was done using R software, and samples were grouped to compare between infected and control samples. Limma, Biobase, and GEOquery software packages in R software were used to determine the expression level of genes and to investigate the differentially expressed genes (DEGs) between healthy and H5N1 influenza virus-infected lung tissue samples in chickens and ducks. The criterion for selecting significant DEGs was considered as |logFC|>2 and P<0.05. DAVID online tool (https://david.ncifcrf.gov) was used to investigate biological pathways, structural and functional characteristics of genes with different expressions, and functional interpretation of upregulated and downregulated DEGs. It was evaluated and visualized separately based on biological processes (BP), molecular functions (MF), and cellular components (CC). KEGG tool (http://www.genome.jp/kegg) was used to evaluate and study metabolic pathway enrichment. To reveal interactions between proteins and analyze them, STRING database and Cytoscape software were used. While using the Cytohubba plugin to identify and display key genes, the main modules affecting the interaction of genes and proteins were also identified by the MCODE plugin.

Gene expression analysis revealed 2062 and 565 differentially expressed genes between normal and infected tissue in chickens and ducks, respectively (P<0.05 and |logFC|>2). The results of bioinformatics analysis and protein-protein interaction network analysis showed BUB1, NDC80, CDC20, PLK1, PRC1, KIF11, and AURKA genes as hub genes in chicken and also COL6A3, COL3A1, COL4A3, COL18A1, PLOD2, PLOD1, and P4HA2 as highly effective genes in duck (P< 0.05). The results of the ontology comparison of DEGs proved that most of these genes in chickens are involved in the innate immune response and inflammatory resistance of the host, and the most effective genes in ducks play a role in lipid metabolism and energy production to meet the host's resistance to disease. The results of comparative gene network analysis between chickens and ducks are promising to increase our understanding of the host response to H5N1 influenza infection and the factors affecting virus pathogenesis in different avian species. Differentially expressed genes in response to H5N1 infection in chickens and ducks play critical roles in various biological processes, including immune response, inflammation, viral replication, and host-pathogen interactions.In general, gene network analysis showed that chickens and ducks use different genetic strategies to respond to avian influenza virus infection.

The present research was conducted to discover the response to H5N1 HPAI infection in chickens and ducks through comparative gene network analysis. It is important to note that the gene network analysis presented in this research is an initial step towards discovering the response mode of HPAI (H5N1) infection in chickens and ducks, and further functional studies, validation experiments, and integration with other omics data are needed to confirm the role of genes, pathways and hub genes in the host response to H5N1 virus. Therefore, the results of comparative gene network analysis in chickens and ducks obtained from this research can provide valuable insight into the underlying molecular mechanisms of host response to H5N1 influenza infection. Thus, by identifying differentially expressed genes, functional modules, and hub genes in this research, it can be stated that potential targets for future research have been highlighted to some extent. Undoubtedly, further studies in this field will improve our knowledge about the pathogenesis of avian influenza and will help to develop strategies for effective control and prevention of H5N1 influenza outbreaks.

Among different sheep breeds in the world, the Texel breed is known as a meaty and muscular breed. Skeletal muscle growth is a step-by-step and exponential process from differentiation, development and maturation, which is regulated by gene networks and cell signaling pathways, and several genes and factors are involved in the process of muscle fiber formation and their growth and hypertrophy (Badday Betti et al. 2022). The study of gene expression is done with several methods, and this gene expression information is used in breeding programs as a tool to improve phenotypic choices. Databases are a large source of expression data that can be used by bioinformatics methods to integrate heterogeneous data from different studies and platforms. In this study, by integrating the microarray and RNA-Seq data available in the database belonging to the muscle tissue of Texel breed sheep, the transcriptomic profile of the muscle was compared at two ages of embryonic and adult. Microarray data related to longissimus dorsi muscle tissue with three replicates d-70 embryos from GEO database with accession number GSE23563 and RNA-Seq data related to muscle tissue from six samples with two replicates from adult individuals from ArrayExpress database were selected. Limma, Biobase and GEOquery software packages were used to calculate the expression values of the microarray data related to the embryonic age  in the R environment, and Tuxedo, HTSeq and DESeq2 packages were used in the Linux and R environment to calculate the expression values of the RNA-Seq data (Kamali et al. 2022; Sahraei et al. 2019). Then two types of expression values were integrated and to eliminate non-biological effects, the batch effects were also removed. Next, differential genes were identified with the limma software package. In order to identify the relationship between the identified differential genes, the gene network was drawn between them by software of Cytoscape version 3.7.1 and String 1.5.1 program. next, due to the vastness of the gene network, each network was clustered with MCODE 1.6.1 and CytoCluster 2.1.0 programs (ClusterOne algorithm) and significant clusters (P-value < 0.05) were identified (Saedi et al. 2022). In order to better understand the ontology and function of the identified differential genes, the Gene Ontology of the genes was investigated using software of Cytoscape version 3.7.1 and ClueGO 2.5.9 and CluePedia 1.5.9 programs. After receiving the Gene Ontology results, significant Gene Ontology terms (P-Value < 0.05) related to functional groups were identified. Finally, the selected genes (Adj P-Value < 0.05) were identified and introduced in these two age groups. After quality control, correcting and normalizing the microarray data, the GPL10778 platform annotation file with 1042520 Probe ID was used to calculate their expression values. After relevant analyzes of 9289 Probe ID identified related to the data of this study, 7918 Gene Symbol was identified finally. After quality control, trimming and normalizing the RNA-Seq data in total, the number of Ensembl_Genes based on which the reading values were calculated by HTSeq was 27056. After removing IDs that had zero readings in all 6 samples, 10855 IDs remained. Then, these 10855 Ensembl ID were merged with the annotation file to obtain Gene Symbol, and finally 9417 common genes were identified between the six samples of adult age. The results of differential expression analysis showed that there were significant differences in the expression of 62 genes (37 increased and 25 decreased) in the muscle tissue between adult and embryonic age. By creating a gene network between differential genes, 15 selected genes were identified, including MYH1, ACTN3, CASQ1, TMOD4, FBP2, SLC2A4, MX1, COX4I1, SOD2, MFN2, UQCRB, UCP3, PRKAB2, PHKG2, PPP1R3C. The function of these genes has been proven in cell proliferation, protein synthesis, myofibril formation, and lipid metabolism. Differential gene enrichment analysis revealed some biological processes such as Vasculogenesis, positive regulation of ossification, positive regulation of muscle tissue development, regulation of muscle contraction, contractile fiber part, calcium signaling, calcineurin-NFAT signaling cascade and regulation of receptor signaling pathway via JAK-STAT, the molecular function of regulating cation channel activity and the cellular components of the contractile fiber. This study in addition to confirming the accuracy of the integration method of two types of heterogeneous data, provided a general view of the transcriptomic differences of Texel sheep muscle tissue at two important age points to be a useful source for biological investigations of genes related to muscle growth and development in sheep.

The number of teat is an important trait in relation to the maternal ability of high litter size sheeps, it is important to know the genetic function and controlling positions of this trait in the genomes of different species. High litter size domestic animals are potentially dependent on colostrum-derived immunoglobulins due to placental structure in the early hours of life. Therefore, the number of teat plays a critical role when there are more offspring born at birth than the number of teats. In some cases, particularly the number of the extra teat and even their position is very important. A method to identify new loci and confirm existing QTL is through genome-wide association studies (GWAS). 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 present study aimed to conduct a genome wide association studies (GWAS) based on Gene-set enrichment analysis for identifying the loci associated with teat number trait using the high-density SNPs.

Hu sheep, a descendant of Mongolian sheep, is a famous lambing breed in China. In ewes of the Hu sheep, TT (individuals with two normal teats) and MT (individuals with two normal teats and one or two supernumerary teats) account for 76–62% and 38–24% respectively. For MT ewes, the supernumerary teats are smaller than the normal teats, but some can produce milk. In the current study, we analyzed the complex genetic mechanism of differences in teat number using single-locus GWAS in a total of 160 Hu sheep. The gene set analysis basically consists of three different steps: the assignment of SNPs to genes, the assignment of genes to functional categories, and finally the association analysis between each functional category and the phenotype of interest. Genome wide association study was performed with birth weight and biometric traits using GEMMA software. Using the biomaRt2 R package, the SNP were assigned to genes if they were within the genomic sequence of the gene or within a flanking region of 25 kb up- and downstream of the gene. 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 (Gambra et al., 2013; 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. A better understanding of the biology underlying meat production specifically, and an advance in the annotation of the ovine genome, can provide new opportunities for predicting production using gene set information.In this research, 7 SNP markers on chromosomes 3, 5, 7, 8, 12, 14 and 17 located in CDH11, NUMB, FGF2, ESR1, LGR5, INSR and PTGS2 genes were identified. Some of the found genes, are consistent with some of the previous studies related to teat number traits. According to pathway analysis, 11 pathways from gene ontology and biological pathways were associated with teat number (P˂0.05). Among these pathways, Blastocyst development, Mesenchymal cell development, Developmental growth involved in morphogenesis, Muscle cell differentiation and AMPK signaling pathway have important functions in development of mammary gland and activation of the AMPK signaling pathway. 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 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.

In total, this study supported previous results from GWAS of teat number, also revealed additional regions in the sheep genome associated with these economically important trait. Using these findings could potentially be useful for genetic selection in the breeding programs.

Due to the high importance of egg shell quality in terms of hardness, extensive transportation with high volume of this product between different countries, the importance of shell quality in terms of protecting the internal content from extra-shell contamination and also one of the ways to improve traits, relying on The genetic structure of a trait is the application of genetic selection. Therefore, the aim this study is to use transcriptome data obtained from uterine tissue of two groups of laying hens with hard and weak eggshell, in each of the three stages of the calcification period (initiation, growth and termination). Gene expression profile was determined and differential expression of genes is analyzed so that different index genes can be expressed and their ontology can be studied to help the results. As a result, the genetic structure of the trait and the list of index genes have been regularly completed, and with the information obtained from the present study, the correct and practical genetic selection can be made in laying hen breeds. The aim of this study was to investigate the gene expression profile between two groups of chickens with hard and weak eggshells in three stages of calcification period (initiation, growth and termination), to identify significant index genes with different expression and analysis. Ontology and the paths involved are related to them. Therefore, in this study, transcripts (total mRNA sequences) of 18 samples of uterine tissue including three replicates in each stage of each group were prepared. The process of converting the initial format of readings was done using SRAtoolkit software, measuring the quality of readings with fastQC software, editing readings with Trimmomatic software and re-measuring the quality of readings after editing with fastQC software; Also, the alignment and mapping of the readings were done using Hisat2 software and format conversion and sorting of results was performed using Samtools software. Finally, the differential expression analysis of genes was performed using Cufflinks software package (Cufflink, Cuffmerge and Cuffdiff software) and Then, considering p-value <0.00025 and the criterion for comparing the value of differential gene expression, log2 (fold_change) less than -4 and greater than +4 were identified as the most significant genes with different and significant expression. Histogram of the results was performed using CummeRbund package in R software environment and ontological analysis was performed using DAVID and Ensembl databases. According to the results of gene expression profile, 28833 genes were identified on the transcript of the samples. Finally, by analyzing the differential expression of genes, 1338 genes at the initiation stage, 81 genes at the growth stage and 190 genes at the termination stage were identified with significantly different expressions, that Considering log2(fold_change) > +4 and log2(fold_change) < -4, 51 genes at the initiation stage, two genes at the growth stage and four genes at the termination stage had different and significant expression. The largest difference in gene expression between the two groups at the initiation stage, ENSGALG0000000044418 gene with log2 (fold_change) equal to 8/63 and at the growth stage, ENSGALG0000000049618 gene with log2 (fold_change) equal to 6/82 and at the termination stage, ENSGALG0000000049618 gene with log2 (fold_change) equal to 5/14 was observed. Ontological analysis of index genes showed that they are mainly involved in protein binding activities (ENSGAL000000444418, NMRAL1, SLITRK4, CHL1, ENSGAL00000009041, PHACTR3 and CORIN genes), DNA transcription regulation (LHX1, TFAP2A, RUNX3, ETV1, NR4A3 and RUNX1 genes), immune response (ENSGAL0000000043996, TMEM117, AvBD9, GCNT3, ENSGAL00000046947 and ENSGAL00000051617 genes), fat metabolism (PNPLA3, NR4A3, CD36, FFAR4 and DGKB genes) and calcium ion binding (ANXA10, CAPN8, CDH18 and DGKB genes), respectively. In the differential expression analysis of genes, considering log2 (fold_change) more than +4 and less than -4, in the initial stage, 51 genes, in the growth stage, two genes and in the termination stage, four genes were identified. The highest differences in gene expression between the two groups were observed in the initial stage, ENSGALG00000044418 and PDZK1IP1 genes, in the growth stage, ENSGALG00000049618, ENSGALG00000048945 and TMEM63C genes and in the termination stage, ENSGALG000000004400 and ENSG26 genes; The results of ontological analysis of index genes showed that they are mainly involved in protein binding, DNA transcription regulation, immune response, lipid metabolism and calcium ion binding, respectively.

Gastrointestinal nematodes (GIN) represent a major health issue for livestock production systems worldwide. Haemonchus contortus is one of the most pathogenic GIN in small ruminants and causes serious losses to farmers, both in impaired production and in control with anthelmintics. It has long been recognized that differences in host resistance and susceptibility to parasitic infection exist in various sheep breeds and that genetics may play an important role in regulating host resistance, which has spurred efforts to control parasitic infection through selective breeding for naturally resistant sheep. A detailed understanding of the genes and mechanisms involved in expressing a resistant phenotype and the factors that regulate this response would facilitate the identification of candidate genes for selection. Recent advances in high-throughput technology, such as microarrays and RNA sequencing, have made a large number of transcriptome data accessible. As a result, researchers are now able to obtain more reliable results by integrating information from multiple sources. Accordingly, meta-analysis can be used as a useful and powerful tool to identify differential gene expression. It can also find out genes that their products are key molecules in response to the infection and use in animal breeding programs. The purpose of this study was to conduct a systematic review and meta-analysis on data collected from infected sheep with H. contortus and general analysis of changes in abomasal gene transcripts in response to infection using RNA-seq technology and bioinformatics tools. In this study, to identify infection-related genes, pathways, and molecular mechanisms underlying host resistance to this parasite, a meta-analysis was performed by combining two different datasets, including 70 samples of sheep H. contortus infection with Rankprod package of R software. After pre-processing, to remove heterogenicity across studies, batch effect correction was performed on gene expression data. The result of the principal component analysis showed that batch correction reduced the batch variation among the datasets. Meta-analysis was carried out and DEGs selected by meta-analysis were further analyzed and characterized. Enrichment analysis, as an efficient method for functional analysis of massive genetic data, was used to determine the biological process, molecular function, and cellular component of DEGs. Moreover, we searched upstream regions of DEGs for over-represented DNA motifs and functional analysis of discovered motifs. To explore the potential interaction network of the DEGs, the protein-protein interaction network among the DEGs was analyzed using the STRING database, which included direct and indirect associations of proteins. After analyzing the result derived from STRING analysis and expression change information for each DEG, the network figure was drawn for the selected DEGs (connected with one or more DEGs) by using the Cytoscape software and hub genes identified with the CytoHubba plugin of Cytoscape. Results derived from the meta-analysis showed a total of 1388 differentially expressed genes between resistant and susceptible sheep. Among them, 1137 were significantly upregulated, whereas 251 were downregulated across the datasets. In the identified DEGs, DEGs corresponding to ribosomal protein S3A, lysozyme C-1-like (LOC443320), and heterogeneous nuclear ribonucleoprotein K were the most strongly upregulated ones, while tenascin C and fibromodulin were the most strongly downregulated. Results from enrichment analysis showed these differentially expressed genes (DEGs) were involved in different biological processes such as one-carbon metabolism, translation, cell surface receptor signaling pathway, immune response, metabolic pathways, PPAR signaling pathway, etc. Moreover, searching in upstream regions of DEGs to find DNA motifs, were able to identify eight conserved sequence motifs. The functional analysis of these motifs revealed that they were involved in the positive regulation of gene expression, defense response, positive regulation of immune response, cellular calcium ion homeostasis, etc. Using the protein-protein interaction analysis also identified multiple hub genes such as albumin and CD4 which may show that improved immune response, induced by up-regulation different genes affects the creation of resistance. The mechanisms of sheep resistance to GIN infections involve complex immune responses. Our results offered overall insight into changes in the transcriptomes of resistant and susceptible sheep and molecular mechanisms of host resistance induced by H. contortus infection. We propose these DEGs as a useful resource of molecular biomarkers and potential candidate genes for breeding programs which can provide a basis for further research on this topic.

Genomic selection has provided the sheep industry with a powerful tool to increase genetic gains on economically important traits such as meat production (Taylor et al. 2016). In addition identifying genes with large effects on economically important traits, has been one of the important goals in sheep breeding. One way to identify new loci and confirm existing QTL is through genome-wide association studies (GWAS). 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 present study aimed to conduct a genome wide association studies (GWAS) based on Gene-set enrichment analysis for identifying the loci associated with birth weight and biometric traits using the high-density SNPs.

Phenotypes records and genotypic data related to birth weight, body length, withers height and chest girth were obtained from 277 Luzhong sheep. The gene set analysis consists basically in three different steps: the assignment of SNPs to genes, the assignment of genes to functional categories, and finally the association analysis between each functional category and the phenotype of interest. Genome wide association study was performed with birth weight and biometric traits using GEMMA software. Using the biomaRt2 R package the SNP were assigned to genes if they were within the genomic sequence of the gene or within a flanking region of 25 kb up- and downstream of the gene. 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 (Gambra et al., 2013; 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 ovine genome, can provide new opportunities for predicting production using gene set information.In this research, 14 SNP markers on chromosomes 2, 3, 5, 7, 11, 13, 17, 19. 20 and 25 located in MYL1, MYL3, ACACA (birth weight), PLCB1, BMPR1A, LRPPRC, PTBP1, TMEM117 (body length), ADIPOR2, SYN3, TRAK1 (withers height) and PPARG, HMGA1 (chest girth) genes were identified. Some of the genes that were found are consistent with some previous studies related to birth weight and biometric traits. According to pathway analysis, 21 pathways from gene ontology and biological pathways were associated with the birth weight and biometric traits (P˂0.05). Among these pathways, muscle structure development, carbohydrate derivative metabolic process, anatomical structure formation involved in morphogenesis, skeletal system development, positive regulation of ossification, muscle cell proliferation and GnRH signaling pathway have important functions in development of skeletal muscle, glucose homeostasis, osteogenesis process, regulation of ion calcium and activation of the MAPK signaling pathway. 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.ConclusionsIn total, this study supported previous results from GWAS of birth weight and biometric traits, also revealed additional regions in the sheep genome associated with these economically important traits, using these findings could potentially be useful for genetic selection in the breeding programs.

total, this study supported previous results from GWAS of birth weight and biometric traits, also revealed additional regions in the sheep genome associated with these economically important traits, using these findings could potentially be useful for genetic selection in the breeding programs.In total, this study supported previous results from GWAS of birth weight and biometric traits, also revealed additional regions in the sheep genome associated with these economically important traits, using these findings could potentially be useful for genetic selection in the breeding programs.

Tail in sheep is a valuable energy source. However, in modern intensive and semi-intensive sheep industry the lean-tailed sheep breeds have more desirable and marketable. Therefore, due to the negative effect of tail size on production efficiency, researchers are looking for methods to eliminate this trait. Identification of genes involved in the process of fat deposition in tail is necessary for reducing tail size in sheep. Several genomic methods such as genome-wide association and selection signature studies or gene expression analysis for describing a possible genetic background for deposition of fat in various fat-tail breeds have been used. The aim of this study was to identify effective genes in fat-tailed sheep breeds (Afshari and Sunite) compared to breeds without tail (Dorper and German Mutton) using selection signature and gene ontology methods.

In this study, genotype information of 366 sheep (37 Afshari, 69 Sunite, 99 Dorper and 161 German Mutton) genotyped with Illumina Ovine SNP50K BeadChip genome arrays, were used. The XP-EHH method using R software package version 1.9 was used to identify selection signature. Genomic version Oar_v4.0 database NCBI was used for detecting the genomic position of SNPs in sheep genome. Candidate genes were identified by SNPs located at 1% upper range of XP-EHH using Plink v1.9 software and gene list of Illumina in R. Additionally, the latest published version of Animal genome database was used for defining QTLs associated with fat deposition traits in identified locations.

Based on the results of XP-EHH, 18 common genes were identified from comparing Afshari population with German Mutton and Dorper breeds, in which five genes (LOC114116389, LOC114118754, KCMF1, TCF7L1 and RASSF2) were associated with QTLs related to fat deposition including carcass fat percentage, internal fat amount and fat tail deposition. 15 common genes were also identified from comparing Sunite population with German Mutton and Dorper populations, in which two genes (SEMA5B and CDH9) were associated with QTLs related to fat deposition. The results of gene ontology showed that some of these genes play effective roles in signaling Wnt, growth, development and morphology of cells.

based on the results of selection signature using XP-EHH method in Afshari and Sunite breeds, RASSF2 gene was identified as a selection signature in Afshari breeds. This gene was also related to tail fat storage QTL, which was identified for the first time in this study. LOC11411689 and LOC114118754 genes related to carcass fat percentage QTL, KCMF1 and TCF7L1 genes related to the QTL of internal fat amount in Afshari breed were also identified. In addition, the SEMA5B gene associated with the QTL of carcass fat percentage and the CDH9 gene associated with of subcutaneous fat weight were identified in the Sunite breed. The results of this study could be used in sheep breeding programs to reduce fat deposition in tail, especially for Afshari breed.

Unlike evaluation of male fertility which is done based on the phenotype records of females e.g., conception rate, semen traits are directly measured in bulls. The objective of this study was to identify genomic regions associated with sperm traits in Holstein bulls using the genome wide association based on gene set enrichment analysis.

For this purpose, phenotype records included 1508 genotyped Holstein bulls were used for ejaculate volume, sperm concentration, number of motile sperm, progressive sperm motility, and number of progressive motile sperm in each ejaculation. The evaluation of genome-wide association was carried out PLINK software (v. 1.90). In the next step, using the biomaRt2 R package R the SNP was 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. For the assignment of the genes to functional categories, the GO, KEGG, DAVID and PANTHER databases were used.

In this research, 11 SNP markers on chromosomes 1, 2, 5, 7, 8, 15, 18, 20, 21, 25, and 27 associated with SPEF2, SEPT12, SLC24A, BSP3, ETNK1, ERBB4 (sperm motility and number of progressive motile sperm), DSCAML, MYH3, RPM1 , RPM2, CAPSL (number of sperm and sperm concentration), DMRT1, and PPARγ genes (ejaculate volume) were identified. Some of these genes in the significant regions were consistent with some previous studies. In pathway analysis, 15 pathways from gene ontology were associated with the sperm traits. Among those pathways, the purine nucleotide metabolic process, cellular calcium ion homeostasis and regulation of fertilization biological pathway had an important role in the progressive sperm motility and number of progressive motile sperm. Also, the calcium channel regulator activity, PPAR signaling pathway, steroid hormone mediated signaling pathway and focal adhesion had significant association with ejaculate volume and sperm concentration.

The Identification of these candidate genes and selection bulls using genomic selection can considerable to improve male fertility and benefits of animal breeding centers and decrease production prices for consumers.

The present study was performed to identify the copy number variations and their impacts on the genes of dromedary camels using whole genome sequencing data of two Iranian dromedary camels (Yazdi camel and Trodi camel). Whole genome sequencing of the Yazdi and Trodi samples produced about 456 and 418.8 paired-end reads with a read length of 100 bp, respectively. After mapping of trimmed reads to reference genome (NCBI accession number: GCA_000767585.1), a read-depth based algorithm was used to identify copy number variations. Identified copy number variations of studied samples, were 831 for Yazdi and 312 for Trodi camels. Nearly 60% (606 genes for Yazdi and 288 for Trodi camel) of the identified variants overlapped with the genes, and the rest were in the none genic regions. The obtained results showed that important genes including genes involved in immune system function and programmed cell death have copy number variation. As well as, two important genes of studied samples, OOEP and WWC3, which are involved in mammalian reproductive function, had copy number variation.

The aim of this study was to investigate the gene expression profile and find the important genes in the differentiation and evolution of the queen, worker and drone honey bee at Stage 5 Larvae. Therefore, transcripts (total mRNA sequence) of 15 samples of Italian honey bee (A. m. ligustica) including 5 drone, 5 worker and 5 queen bees were aligned to the reference genome of the honey bee. In gene expression analysis of RNA-Seq data, 15962 genes and 31297 isoforms were identified. In our differential gene expression analyses, 465 genes between drone and queen bees, 495 genes between worker and queen bees and 764 genes between drone and worker bees, were expressed differently (P <0.000005). The largest difference in expression of genes was observed between drone and workers were for GB45614 and GB42053, with log2 fold change that was -10 and 11.5, respectively. In drone and queen bees comparison, GB45614 and GB48020 genes with log2 fold change 7.11 and 8.11, and in queen and worker bees comparison, GB43508 and GB42053 with log2 fold change 6.6 and -9, had the largest difference in gene expression, respectively. The analysis of the gene ontology (GO) and the pathways involved showed that the function of many of these genes has yet to be found. However, a large number of the genes expressed defiantly in drone and queen bees were related to integral component of membrane, calcium ion binding, carboxypeptidase, cholecystokinin receptor,chitin metabolic process, chymotrypsin inhibitor, haemolymph juvenile hormone binding and pupal cuticle protein, while differentially expressed genes in queen and worker bees comparison were related to metabolic pathways, enzymes metabolism, Pyrimidine metabolism, lipid metabolism, protein kinase, ATP binding and nucleic acid, intracellular cholesterol transport, chitin metabolic process, nitrogen compound metabolic process, hydrolase activity and chitin binding. The genes expressed at different levels in worker bees and drones were related to structural elements, the metabolism membrane and transfer of amino acids, calcium-ion-bound, ion-binder, intracellular cholesterol transport and chitin metabolism.

Processes of muscle development and lipid metabolism that plays important roles during fetal growth and development stages, are different in thin- and fat-tailed sheep breeds. Therefore, in order to have a better perception of differentially expressed genes and their pathways in ovine prenatal muscle tissue , the gene expression data from muscle tissue of two thin- and fat-tailed breeds of sheep derived from the gene expression array experiment (Access number: GSE23563) were analyzed. The LIMMA package in R used to identify 691, 410, 404, 290 and 155 differentially expressed genes at 70, 85, 100, 120, and 135 days from gestation, respectively.Also,identification of significant gene clusters was performed for each fetal stage using Cytoscape. Finally,13 genes were recognized as differentially expressed at all 5 stages of sampling; among them, EEF1A2, ITGAM,NINL and RPL39 were confirmed as genes related to fetal weight, involved in the muscle development and lipid metabolism regulation.Also Gene Ontology and KEGG pathway analysis for differentially expressed genes by DAVID led to identification of significant processes and pathways associated with myogenesis, lipid metabolism and nervous and immune system in the developing muscle tissue transcriptome. The results of this study could provide supplementary information revealing genes with significant impact on the formation of muscle and fat tissues during fetal development and also the pathways involved in these biological processes.These genes might provide some evidence on DNA markers associated with some economic traits including birth weight,carcass and meat quality traits in sheep which can be applied in selection and breeding programs.

The aim of this research was to study gene expression profiling and differential analysis between Bos taurus (Holstein) and Bos indicus (Cholistani) subspecies. The transcriptome was assembled through aligning and mapping the RNA-Seq reads that have already been sequenced by next generation sequencing technology. Among 24616 genes and 26717 transcripts, only 41 genes were differently expressed. The highest digital gene expression was measured for a mitochondrial gene (ENSBTAG00000043545), and was only expressed in the Cholistani population. One gene had two differentially expressed isoforms. Gene pathway analysis indicated that the differential expressed genes included in pathways, are particularly related to immunity, response to stress and angiogenesis. These pathways have probably resulted in adoption to various climatological conditions and perceptible phenotypes in the studied subspecies during their evolution.

Ascites syndrome is a metabolic disorder in late ages of meat-type chickens. The only commercial broiler strain of Iran, Arian, has been incurred by this syndrome during a couple of decades ago. Due to susceptibility to ascites and some poor performance issues this strain are wiping out from indigenous market. Prevalence of ascites syndrome in commercial broiler of Arian is nearly 10% in average and in paternal lines it gets more fatality. Role of genetic factors in arising ascites has been proven by former researchers. Fighting against this syndrome through old methods are expensive and time consuming. Since presence of hypertrophy in a tissue needs to make facilities such as blood vessels to providing oxygen and nutrients so studying on angiogenesis pathway and its key important genes was directed. Whereas numerous organs engage the disease and among them heart has key role for initiating and developing the disease, so genomic study dealing with next generation sequencing (NGS) technology has been conducted to identify genes relating to angiogenesis and hypertrophy in right ventricle of ascites susceptible birds. 464 one-day-old chicks from B-line pedigree of Arian strain have been reared up to 21 days at the same rearing and nutritional conditions. At the age of 21 the rearing house was divided to 3 sections. Normal and cold sections at the ends of the house and buffer section at the middle. 464 chickens were transferred from normal to the cold section and kept the ambient temperature lower than 16 degrees for inducing ascites. 120 birds from cold section were selected randomly and slaughtered at the age of 42. Those of birds having ascites symptoms classified to ascites susceptible (As) and the other assigned to healthy (He). Samples of right ventricle was picked up and stored with RNAase-Later in liquid N tank. Then 12 As samples and 12 He samples were chosen for extracting total RNA by Biozol kit. After that every 6 samples in each groups pooled together and finally 2 As and 2 He samples prepared to make cDNA libraries for high throughput sequencer machine, Ilumina Hiseq 2000. RNA integrity score (RIN) were more than 7 for all samples. All small RNAs such as microRNAs, rRNAs and tRNAs were eliminated by oligo dt beads and finally all mRNAs was used for preparing library. cDNAs as long as 200 bp were selected for library. Sequencing has been done by BGI Company. For mapping, aligning, and DE analyzing several softwares were used such as: Tophat, cufflinks, cuffmerge and cuffdiff. Then significant DEGs imported to String for creating gene expression network and use DAVID 6.8 for investigation gene annotation and pathway analysis and finally Cytoscape v. 3.5.1 was used for network and cluster analysis. Nearly 90% of reads mapped on genome reference. In ascites group among 125 DEGs 79 genes was upregulated and 46 loci was down-regulated. Among 125 significant differentially expressed genes (FDR<20%) between As and He birds 59 genes were identified in a pathway in KEGG database. Gene ontology has been shown that the most significant biological process term containing 9 genes in term of gga04512: ECM-receptors interaction. The gene expression network analysis shows that average node neighboring was 3.763, network heterogeneity was 0.9 and network centralization was 0.236. Cluster analysis depicted 3 significant clusters involving key rule in angiogenesis including Cyclin- ependent Kinase1 (CDK1), ECM-receptors interaction and Interleukin 7 (IL7) (p-value<0.05). Up regulating of CDK1 with CCNB1 and CCNB2 may activated maturation promoting factor (MPF) that eventually induce cell division and proliferation in endothelial cells (ECs). Up regulating COL6A2 shows its roles in remodeling of ECM-receptors that in turn involving in proangiogenesis process in right ventricle hypertrophy in As birds. IL7 up regulated significantly (P-value<0.05) in As birds. This factor can induce IL8 and Ang-1 secretion from ECs. These factors have key important role for vascular remodeling and vascular tone in proangiogenesis and angiogenesis process. Studying on gene networks in susceptible bird’s heart cells has been shown that over expression in angiogenesis related genes was seen significantly in susceptible birds especially in ECM-receptor interaction, Cell division and IL-7 pathways as well. All these recent pathways rule actively in angiogenesis process and vascular network remodeling. So after finding these networks and related clusters it can be possible to find more extended studies on down regulated genes in apart or together for using breeding improvement objectives.

This study was carried out for identification of deletions, insertions (INDELs) and assessment of their related functional groups in two Iranian dromedary camels (Yazdi camel and Trodi camel) using whole genome sequencing data. In this study, two powerful variant callers (GATK and SAMtools) were used to increase precision and accuracy of detected INDELs. Finally, common identified variants between two programs, after quality filtration, were considered as final INDELs. The present study led to identification of 351429 INDELs for Yazdi camel and 341479 INDELs for Trodi camel. Annotated INDELs that classified as high impact INDELs, were used for further analysis. The numbers of high impact INDELs were 3424 and 3506 for Yazdi and Trodi camels, respectively. To compare Iranian camels with non-Iranian camels, we used whole genome sequencing data of one African origin camel. Comparison of high impact INDELs between three samples showed that 1595 INDELs were common between them. Assessment of gene ontology’s results showed that many of significant terms are related to the ability of camels to withstand serve desert conditions.

Economic pressure on the modern poultry industry has directed the selection process towards fast-growing broilers that have a reduced feed conversion ratio. Selection based heavily on growth characteristics could adversely affect immune competence leaving chickens more susceptible to disease. Native breeds of chickens are playing an important role in rural economies in most of the developing and underdeveloped countries. The immune system is an adaptive defensed at evolved in phylogenesis to control an organism’s integrity and apoptosis system is involved in many immune system mechanisms and diseases therefore this study has emphasized on apoptosis system. Recently, next generation sequencing technology (RNA-Seq) has become available as a powerful tool to investigate transcriptional profiles for gene expression analysis of many organisms. So, we performed comparative gene expression analysis of native and commercial chickens by RNAsequencing technology, in order to, detect differentially expressed genes involved in apoptosis in native and commercial breed poultry.
The chicken in this study was female from Esfahani and Ross breeds (47 days of age). The blood samples were collected from Brachial/ulnar wing vein; 5 ml was taken. The total RNA was extracted by using Trizol (Invitrogen, USA) according to the manufacture's protocol. The RNA pool was prepared by mixing together equal quantities of three RNA samples per group/ Total RNA was sent to BGI Company (China) for paired-end sequencing by an Illumina Hiseq 2000 platform and the raw reads were generated. Approximately 18 million fragments were sequenced with length of 150 bp. The quality of the row data was checked with Fast QC vol 0.11.2 and Trimmomatic (v 0.35) were used to remove Illumina adaptors, trimming of reads as well as quality or filtering reads by removing low-quality reads. The reads passed the quality control were mapped to the reference genome using Tophat2 (v2.1.1). For aligning and DE analyzing were used cufflinks, cuffmerge and cuffdiff. Then significant DEGs imported to String for creating gene expression network and use DAVID 6.8 for investigation gene annotation and pathway analysis and finally Cytoscape v. 3.5.1 was used for network and cluster analysis.
Among 1328 significant differentially expressed genes in immune system, 11 genes were identified in a pathway in KEGG database, which named apoptosis genes. Gene ontology has been shown that the most significant biological process term containing 4 genes in term of GO: 1900182 positive regulation of protein localization to nucleus. The apoptosis genes Network analysis showed that number of nods was 11, number of edges was 20, average of degree was 3.64, average local clustering coefficient was0.621. Furthermore, analysis of apoptosis gene networks by Cytoscape showed that PIK3R1 had the highest value by degree. Beside of this result, AKT1 and CSF2RB had the highest value by Beetwinness Centrality. The highest out degree and the lowest in degree were related to AKT1.
Overall, 3 apoptic genes including PIK3R1, AKT1 and CSF2RB were recognized as very important in breeding poultry. According to involving apoptic genes in disease and Innate immune system, we mayuse these genes in breeding plans. We can regulate them with appropriate cell and molecular methods or using epigenetic procedures.

Identification of disease-causing genes that underlie complex traits such as susceptibility to disease not only can improve diagnosis and the prevention of illness, but also help breeder to select resistance animals against diseases. In the current study to aim the higher power of statistical analysis to identification of genes and biological pathways related to mastitis disease, we used Fisher meta-analysis to combine p-values obtained from individual analysis of datasets extracted from 6 microarray-based studies which investigate transcriptomic data of mammary gland tissue infected by Escherichia coli (E. coli) in dairy cows. Identification of genes that did not show a significant p-value in any of the independent studies may confirm the aim and lead to introduce a more complete set of biological pathways involved in this disease such as the pathways related to immune response, inflammation, proteolysis, growth, and death of cell. Positive regulation of transcription from RNA polymerase II promoter, is new pathways related to this disease which despite of the enrichment by maximum number of up-regulated genes in this study, have not been reported in previous mastitis studies.