University of GuilanAnimal Production Research2252-087211320221122Genetic similarities and phylogenetic analysis of wild and domesticated species of sheep based on mitochondrial genomeGenetic similarities and phylogenetic analysis of wild and domesticated species of sheep based on mitochondrial genome113593710.22124/ar.2022.22429.1709FAF.RabieiFormer MSc Student, Department of Animal Science, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran0000-0003-0792-1980R.AbdoliAssistant professor, Iran Silk Research Centre, Agricultural Research, Education and Extension Organization (AREEO), Gilan, Iran0000-0003-0792-1980F.RafeieAssistant professor, Department of Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, IranN.Ghavi Hossein-ZadehProfessor, Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran0000-0001-9458-5860Journal Article20220605<strong>Introduction</strong>: Mitochondrial DNA (mitogenome) is a small and extra-chromosomal DNA, located in the cytoplasm and presents an ideal model to study evolution and genetic similarity. Classical phylogenetics is based on the morphological characteristics of the organisms, while in modern approaches, the phylogenetic distance and its related comparative methods are estimated based on observed genetic diversity in the studied genetic sequences. The aim of the present study was to investigate the divergence and percentage of genetic similarity along with the phylogenetic analysis of the seven main known species of wild and domestic sheep based on the complete sequence of the mitochondrial genome and the separate sequences of 13 protein-coding genes for each genome.
<strong>Materials and methods:</strong> In the present study, complete mitochondrial genome sequences along with separate sequences of 13 protein-coding genes (including <em>NADH ubiquinone oxidoreductase </em>(<em>ND1, ND2, ND3, ND4, ND5, </em>and <em>ND6</em>), <em>cytochrome c oxidase </em>(<em>COX1, COX2, </em>and <em>COX3</em>), <em>ATP synthase </em>(<em>ATP6 </em>and <em>ATP8</em>), <em>NADH dehydrogenase 4 L </em>(<em>ND4L</em>), and <em>cytochrome b </em>(<em>CYTB</em>)) per each genome from six wild species of sheep including Asian Mouflon (<em>Ovis orientalis</em>), Bighorn (<em>Ovis canadensis</em>), Argali (<em>Ovis ammon</em>), Urial (<em>Ovis vignei</em>), Snow (<em>Ovis nivicola</em>), Dall (<em>Ovis dalli</em>), and domesticated species of sheep (<em>Ovis aries</em>) were retrieved from NCBI database and compared to each other. Mitochondrial genomes and genes’ alignment were accomplished by the MegAlign module of DNASTAR software and compared by the Clustal W method. The Sequence Distances sub-section of the MegAlign module of DNASTAR also was used for the analysis of complete genome and gene sequences divergence and similarity percentage. For phylogenetic analysis, complete mitochondrial genomes and protein-coding genes’ sequences were aligned using MEGA7 software. Based on the alignment, phylogenetic tree was constructed using the maximum likelihood method. The percentage of replicate trees of 1000 replicates of bootstrap test was used to represent the evolutionary history for the studied sheep species.
<strong>Results and discussion:</strong> The results obtained from sequence distance analysis showed high genetic similarity (99.8 %) between <em>Ovis orientalis</em> and <em>Ovis aries</em>. Also, the lowest similarity (95 %) was observed between <em>Ovis aries</em> and <em>Ovis dalli</em>. In phylogenetic analysis, two main clusters, each with different sub-clusters were identified. Domesticated species of sheep (<em>Ovis aries</em>) along with <em>Ovis orientalis</em>, <em>Ovis vignei</em>, and <em>Ovis ammon</em> wild species of sheep formed distinct cluster, and <em>Ovis nivicola</em>, <em>Ovis dalli</em>, and <em>Ovis Canadensis</em> fell in a same cluster. In terms of all 13 protein-coding genes (including <em>NADH ubiquinone oxidoreductase </em>(<em>ND1, ND2, ND3, ND4, ND5</em>,<em> </em>and <em>ND6</em>), <em>cytochrome c oxidase </em>(<em>COX1, COX2</em>,<em> </em>and <em>COX3</em>), <em>ATP synthase </em>(<em>ATP6 </em>and <em>ATP8</em>), <em>NADH dehydrogenase 4 L </em>(<em>ND4L</em>) and <em>cytochrome b </em>(<em>CYTB</em>)), the results obtained from sequence distance similarity analysis and phylogenetic trees were similar to the sequences of the complete mitochondrial genomes. More than 99% of the genetic similarity for ND1, ND2, ND5, ND6, COX1, COX2, COX3, and ATP6 genes and 100% of the genetic similarity for ND3, ND4, ND4L, ATP8, and CYTB genes between domestic sheep (<em>Ovis aries</em>) and Mouflon (<em>Ovis orientalis</em>) sheep species were found. Also, similar to the results obtained from the comparison of the complete mitochondrial genome, the domestic sheep species (<em>Ovis aries</em>) showed the least genetic similarity with the Dall (<em>Ovis dalli</em>) and Bighorn (<em>Ovis canadensis</em>) wild sheep species in all 13 protein-coding genes. Similar to the results of phylogenetic analysis of complete mitochondrial genomes, domestic sheep species (<em>Ovis aries</em>) together with <em>Ovies orientalis</em> wild sheep were placed in the same sub-cluster and <em>Ovis vignei</em> and <em>Ovis ammon</em> species were placed in other distinct sub-clusters. In addition, the <em>Ovis nivicola</em>, <em>Ovis dalli</em>, and <em>Ovis canadensis</em> wild species fell in another main cluster, and in this cluster, <em>Ovis dalli</em> and <em>Ovis canadensis</em> were placed in a similar sub-cluster and <em>Ovis nivicola</em> in another distinct sub-cluster.
<strong>Conclusions:</strong> In previous studies, small parts of the mitochondrial genome (such as a part of the control region or cytochrome b gene) have been considered to show the genetic differences and phylogenetic relationships between different species and breeds of sheep. In the present study, the complete sequences of the mitochondrial genome along with the complete sequences of 13 protein-encoding genes per each genome in seven main species of wild and domestic sheep have been considered for examining genetic similarity and divergence and phylogenetic analysis for the first time. Based on the results obtained from the present study, mitochondrial genome sequences could be used for accurate phylogenetic analysis and clustering of different species of sheep.<strong>Introduction</strong>: Mitochondrial DNA (mitogenome) is a small and extra-chromosomal DNA, located in the cytoplasm and presents an ideal model to study evolution and genetic similarity. Classical phylogenetics is based on the morphological characteristics of the organisms, while in modern approaches, the phylogenetic distance and its related comparative methods are estimated based on observed genetic diversity in the studied genetic sequences. The aim of the present study was to investigate the divergence and percentage of genetic similarity along with the phylogenetic analysis of the seven main known species of wild and domestic sheep based on the complete sequence of the mitochondrial genome and the separate sequences of 13 protein-coding genes for each genome.
<strong>Materials and methods:</strong> In the present study, complete mitochondrial genome sequences along with separate sequences of 13 protein-coding genes (including <em>NADH ubiquinone oxidoreductase </em>(<em>ND1, ND2, ND3, ND4, ND5, </em>and <em>ND6</em>), <em>cytochrome c oxidase </em>(<em>COX1, COX2, </em>and <em>COX3</em>), <em>ATP synthase </em>(<em>ATP6 </em>and <em>ATP8</em>), <em>NADH dehydrogenase 4 L </em>(<em>ND4L</em>), and <em>cytochrome b </em>(<em>CYTB</em>)) per each genome from six wild species of sheep including Asian Mouflon (<em>Ovis orientalis</em>), Bighorn (<em>Ovis canadensis</em>), Argali (<em>Ovis ammon</em>), Urial (<em>Ovis vignei</em>), Snow (<em>Ovis nivicola</em>), Dall (<em>Ovis dalli</em>), and domesticated species of sheep (<em>Ovis aries</em>) were retrieved from NCBI database and compared to each other. Mitochondrial genomes and genes’ alignment were accomplished by the MegAlign module of DNASTAR software and compared by the Clustal W method. The Sequence Distances sub-section of the MegAlign module of DNASTAR also was used for the analysis of complete genome and gene sequences divergence and similarity percentage. For phylogenetic analysis, complete mitochondrial genomes and protein-coding genes’ sequences were aligned using MEGA7 software. Based on the alignment, phylogenetic tree was constructed using the maximum likelihood method. The percentage of replicate trees of 1000 replicates of bootstrap test was used to represent the evolutionary history for the studied sheep species.
<strong>Results and discussion:</strong> The results obtained from sequence distance analysis showed high genetic similarity (99.8 %) between <em>Ovis orientalis</em> and <em>Ovis aries</em>. Also, the lowest similarity (95 %) was observed between <em>Ovis aries</em> and <em>Ovis dalli</em>. In phylogenetic analysis, two main clusters, each with different sub-clusters were identified. Domesticated species of sheep (<em>Ovis aries</em>) along with <em>Ovis orientalis</em>, <em>Ovis vignei</em>, and <em>Ovis ammon</em> wild species of sheep formed distinct cluster, and <em>Ovis nivicola</em>, <em>Ovis dalli</em>, and <em>Ovis Canadensis</em> fell in a same cluster. In terms of all 13 protein-coding genes (including <em>NADH ubiquinone oxidoreductase </em>(<em>ND1, ND2, ND3, ND4, ND5</em>,<em> </em>and <em>ND6</em>), <em>cytochrome c oxidase </em>(<em>COX1, COX2</em>,<em> </em>and <em>COX3</em>), <em>ATP synthase </em>(<em>ATP6 </em>and <em>ATP8</em>), <em>NADH dehydrogenase 4 L </em>(<em>ND4L</em>) and <em>cytochrome b </em>(<em>CYTB</em>)), the results obtained from sequence distance similarity analysis and phylogenetic trees were similar to the sequences of the complete mitochondrial genomes. More than 99% of the genetic similarity for ND1, ND2, ND5, ND6, COX1, COX2, COX3, and ATP6 genes and 100% of the genetic similarity for ND3, ND4, ND4L, ATP8, and CYTB genes between domestic sheep (<em>Ovis aries</em>) and Mouflon (<em>Ovis orientalis</em>) sheep species were found. Also, similar to the results obtained from the comparison of the complete mitochondrial genome, the domestic sheep species (<em>Ovis aries</em>) showed the least genetic similarity with the Dall (<em>Ovis dalli</em>) and Bighorn (<em>Ovis canadensis</em>) wild sheep species in all 13 protein-coding genes. Similar to the results of phylogenetic analysis of complete mitochondrial genomes, domestic sheep species (<em>Ovis aries</em>) together with <em>Ovies orientalis</em> wild sheep were placed in the same sub-cluster and <em>Ovis vignei</em> and <em>Ovis ammon</em> species were placed in other distinct sub-clusters. In addition, the <em>Ovis nivicola</em>, <em>Ovis dalli</em>, and <em>Ovis canadensis</em> wild species fell in another main cluster, and in this cluster, <em>Ovis dalli</em> and <em>Ovis canadensis</em> were placed in a similar sub-cluster and <em>Ovis nivicola</em> in another distinct sub-cluster.
<strong>Conclusions:</strong> In previous studies, small parts of the mitochondrial genome (such as a part of the control region or cytochrome b gene) have been considered to show the genetic differences and phylogenetic relationships between different species and breeds of sheep. In the present study, the complete sequences of the mitochondrial genome along with the complete sequences of 13 protein-encoding genes per each genome in seven main species of wild and domestic sheep have been considered for examining genetic similarity and divergence and phylogenetic analysis for the first time. Based on the results obtained from the present study, mitochondrial genome sequences could be used for accurate phylogenetic analysis and clustering of different species of sheep.https://ar.guilan.ac.ir/article_5937_e46dad6abf9f272a4e634cdebb49f564.pdfUniversity of GuilanAnimal Production Research2252-087211320221122Multi-population joint genome-wide association study to detect genomic regions associated with litter size in sheepMulti-population joint genome-wide association study to detect genomic regions associated with litter size in sheep1526593510.22124/ar.2022.21763.1688FAM.GholizadehAssociate Professor, Department of Animal Science and Fisheries, Sari Agricultural Sciences and Natural Resources University, Sari, Iran0000-0003-4544-1566S. M.Esmaeili-FardDepartment of Animal Science, Faculty of Animal Science and Fisheries, Agricultural Sciences &amp; Natural Resources University of Sari, Mazandaran, Iran0000-0001-7509-5030Journal Article20220212<strong>Introduction</strong>: Reproduction is one of the most important economic traits in sheep with within and between-breeds variation. Reproductive traits normally show low to medium heritability and therefore response to conventional selection methods is not satisfactory for these traits. Considering the genetic information of the genetic variants underlying reproduction variability could efficiently increase the selection efficacy. Genome-wide association studies (GWAS) have been used to identify associations between genotypes and phenotypes as well as candidate genes for economically important traits. Statistical power in GWAS is mostly affected by sample size. The low sample size is hence a main obstacle in GWAS. Combining multiple data sets of different studies for joint (mega) GWAS provides an opportunity to increase the sample size required for GWAS. This study was performed to identify genomic regions affecting litter size in sheep using the mega-analysis of GWAS.
<strong>Materials and methods</strong><strong>: </strong>Multi-population joint GWAS was performed using genotypic and phenotypic data of six sheep breeds retrieved from the database. Quality control was performed using the Plink software. The markers or individuals were removed from the further study based on the following criteria: (1) unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) < 0.05, and a <em>P</em>-value for Hardy–Weinberg equilibrium test less than 10<sup>-6</sup>. Before analysis, imputation of missing genotypes for combined data set was implemented by LD-kNNi method. Mega-analysis was performed using a mixed linear model in TASSEL software considering kinship and population structure (top five components of principal component analysis (PCA)) as confounding effects. The quantile–quantile (Q–Q) plot was visualized by plotting the distribution of obtained <em>vs.</em> expected log10 (<em>P</em>-value). The association results along the genome and the significant SNPs were visualized in the Manhattan plot. To account for multiple test problem and identify the genome-wide and chromosome-wide significance level, Bonferroni test was used based on the number of independent SNPs obtained from pairwise linkage disequilibrium analysis. After GWAS analysis, the 300 bp sequence upstream and downstream of the significant SNP was explored to identify the adjacent candidate genes using Ovis aries_v4.0 (UCSC).
<strong>Results and discussion: </strong>In the present study, we implemented a mega GWAS using six different sheep breed data to identify the genetic mechanisms responsible for litter size in sheep. After quality control, 305 animals and 351,615 SNP markers with a mean MAF of 0.33 were kept for further analysis. The results of the mega-analysis identified one marker on chromosome 21 at the genome-wide level and 10 markers at the chromosome-wide level on chromosomes 1, 2, 3, 14, 17, and 22. The quantile–quantile plot that features the total distribution of the observed <em>P</em>-values (−log10 <em>P</em>-values) of quality passed SNPs <em>vs.</em> the expected values, showed the effective control for confounding effects. Many of the significant SNPs identified in this study were located in or very adjacent to known genes (<em>OPCML</em>, <em>GULP1</em>, <em>RBP4</em>, <em>MMP2,</em> and <em>LPCAT2</em>) that have been already reported for their contribution to fertility and pregnancy success. It has been reported that <em>OPCML</em> is more consistently expressed in cells lining the uterus, oviduct, and rete ovarii. <em>OPCML</em> has been reported as a tumor suppressor protein that is frequently inactivated in epithelial ovarian cancer. It has been reported that the <em>RBP4</em> gene is expressed during the period of fast elongation of the pig blastocyst which is a crucial period for the survival of the embryos. Also, it has been suggested that <em>RBP4</em> has the main contribution in uterine and conceptus physiology during the establishment of pregnancy and therefore can be considered as a candidate gene for litter size. <em>MMP2</em> has an essential function during ovulation and pregnancy through extracellular matrix (ECM) components degradation and therefore enabling cell migration and angiogenesis.
<strong>Conclusions: </strong>Comparison of the results of this study with previous reports showed that the mega-analysis of GWAS, compared to the meta-analysis already reported for GWAS results, had comparable power in identifying genomic regions influencing litter size in sheep but identified fewer genomic regions than individual GWAS for each breed. No previously reported major genes controlling litter size in sheep were identified using our mega GWAS. The results of our research are suggested for further investigations in identifying causal genetic variants or genomic regions underlying the litter size variation in sheep and can be used to understand the genetic mechanism controlling this trait.<strong>Introduction</strong>: Reproduction is one of the most important economic traits in sheep with within and between-breeds variation. Reproductive traits normally show low to medium heritability and therefore response to conventional selection methods is not satisfactory for these traits. Considering the genetic information of the genetic variants underlying reproduction variability could efficiently increase the selection efficacy. Genome-wide association studies (GWAS) have been used to identify associations between genotypes and phenotypes as well as candidate genes for economically important traits. Statistical power in GWAS is mostly affected by sample size. The low sample size is hence a main obstacle in GWAS. Combining multiple data sets of different studies for joint (mega) GWAS provides an opportunity to increase the sample size required for GWAS. This study was performed to identify genomic regions affecting litter size in sheep using the mega-analysis of GWAS.
<strong>Materials and methods</strong><strong>: </strong>Multi-population joint GWAS was performed using genotypic and phenotypic data of six sheep breeds retrieved from the database. Quality control was performed using the Plink software. The markers or individuals were removed from the further study based on the following criteria: (1) unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) < 0.05, and a <em>P</em>-value for Hardy–Weinberg equilibrium test less than 10<sup>-6</sup>. Before analysis, imputation of missing genotypes for combined data set was implemented by LD-kNNi method. Mega-analysis was performed using a mixed linear model in TASSEL software considering kinship and population structure (top five components of principal component analysis (PCA)) as confounding effects. The quantile–quantile (Q–Q) plot was visualized by plotting the distribution of obtained <em>vs.</em> expected log10 (<em>P</em>-value). The association results along the genome and the significant SNPs were visualized in the Manhattan plot. To account for multiple test problem and identify the genome-wide and chromosome-wide significance level, Bonferroni test was used based on the number of independent SNPs obtained from pairwise linkage disequilibrium analysis. After GWAS analysis, the 300 bp sequence upstream and downstream of the significant SNP was explored to identify the adjacent candidate genes using Ovis aries_v4.0 (UCSC).
<strong>Results and discussion: </strong>In the present study, we implemented a mega GWAS using six different sheep breed data to identify the genetic mechanisms responsible for litter size in sheep. After quality control, 305 animals and 351,615 SNP markers with a mean MAF of 0.33 were kept for further analysis. The results of the mega-analysis identified one marker on chromosome 21 at the genome-wide level and 10 markers at the chromosome-wide level on chromosomes 1, 2, 3, 14, 17, and 22. The quantile–quantile plot that features the total distribution of the observed <em>P</em>-values (−log10 <em>P</em>-values) of quality passed SNPs <em>vs.</em> the expected values, showed the effective control for confounding effects. Many of the significant SNPs identified in this study were located in or very adjacent to known genes (<em>OPCML</em>, <em>GULP1</em>, <em>RBP4</em>, <em>MMP2,</em> and <em>LPCAT2</em>) that have been already reported for their contribution to fertility and pregnancy success. It has been reported that <em>OPCML</em> is more consistently expressed in cells lining the uterus, oviduct, and rete ovarii. <em>OPCML</em> has been reported as a tumor suppressor protein that is frequently inactivated in epithelial ovarian cancer. It has been reported that the <em>RBP4</em> gene is expressed during the period of fast elongation of the pig blastocyst which is a crucial period for the survival of the embryos. Also, it has been suggested that <em>RBP4</em> has the main contribution in uterine and conceptus physiology during the establishment of pregnancy and therefore can be considered as a candidate gene for litter size. <em>MMP2</em> has an essential function during ovulation and pregnancy through extracellular matrix (ECM) components degradation and therefore enabling cell migration and angiogenesis.
<strong>Conclusions: </strong>Comparison of the results of this study with previous reports showed that the mega-analysis of GWAS, compared to the meta-analysis already reported for GWAS results, had comparable power in identifying genomic regions influencing litter size in sheep but identified fewer genomic regions than individual GWAS for each breed. No previously reported major genes controlling litter size in sheep were identified using our mega GWAS. The results of our research are suggested for further investigations in identifying causal genetic variants or genomic regions underlying the litter size variation in sheep and can be used to understand the genetic mechanism controlling this trait.https://ar.guilan.ac.ir/article_5935_f57902a1e8079772d3298f511445d51a.pdfUniversity of GuilanAnimal Production Research2252-087211320221122Study of the genetic structure of the Shin Bash sheep population by molecular markersStudy of the genetic structure of the Shin Bash sheep population by molecular markers2740593310.22124/ar.2022.21249.1671FAA.JavanrouhAssistant Professor, Animal Science Research Institute of Iran, Agriculture Research, Education and Extension Organization (AREEO), Karaj, Iranorcid 0000-0001-9956-8779S.KhodamoradiAssistant professor, Animal Science Department, Mahabad Branch, Islamic Azad University, Mahabad, Iranhttps://orcid.org/00Journal Article20211212<strong>Introduction</strong>: West Azerbaijan province is the second most populous sheep province in Iran. In this province, different breeds of sheep such as Makui, Herki, Ghezel, Afshar, and Shin Bash are bred. Shin Bash sheep are bred in the south of West Azerbaijan province, especially in the cities of Mahabad and Piranshahr, and its population is about 200,000. Nowadays, the management of genetic resources and the study of the risk of genetic diversity of populations has become very important. The need to preserve the genetic resources of native livestock and use these genetic resources in the future determines the genetic structure of populations, and the study of the genetic diversity within each population can help manage genetic resources and provide good information for breeding programs. With the development of molecular techniques and the use of molecular markers as a tool to assess genetic diversity, useful information has been provided at various levels such as population structure, gene flow rate, phylogenetic relationships, and genealogy tests. Identification of livestock using various molecular techniques is highly accurate and the results of studies can be used in breeding and management programs. The purpose of this study was to study the genetic structure of Shin Bash sheep using microsatellite markers on the nuclear genome and SNP markers on mitochondrial DNA (mtDNA) and to introduce a lesser-known population.
<strong>Materials and methods:</strong> To study the genetic structure of the Shin Bash sheep population, 75 blood samples were collected from their geographic regions. Genomic DNA was extracted by using a modified Salting-Out method. Ten microsatellite markers and a control region (CR) of D-Loop belonging to mitochondrial DNA (mtDNA) were studied. Microsatellite loci were amplified in a multiplex PCR. Selected primers were labeled and genotyping was conducted using the Genetic Analyzer system. To analyze the data obtained from microsatellite markers, population parameters include: the Hardy-Weinberg equilibrium test, number of alleles per site, number of effective alleles, observed and expected heterozygosity, Shannon index, and F-statistic were calculated using POPGENE software version 3.1 and GENALEX version 6.5. In this research, Chromas ver. 2.33 (http://www.technelysium.com.au/chromas.html) was used to sort the sequencing data. Thus, the nucleotide sequence of each individual in this software was called and saved after sorting in the FASTA format. Also, to ensure the correct reading of the nucleotides, all sequences were examined using Blast online software at the NCBI site, indicating that this sequence is related to sheep mtDNA. To analyze the data obtained from sequencing in the control region of sheep mtDNA, MEGA version 7.0 and DnaSP version 6.12 were used.
<strong> Results and discussion:</strong> A Total of 84 alleles were identified; thus, the mean number of alleles per locus was 8.4. A total of 10 microsatellite loci were studied, seven were at Hardy-Weinberg equilibrium and three had significant deviations from Hardy-Weinberg equilibrium. Hardy-Weinberg disequilibrium can be caused by an increase in homozygotes <em>vs.</em> heterozygotes or, conversely, a high mutation rate, the formation of new alleles, and the presence of null alleles. The mean expected heterozygosity and observed heterozygosity in this population were 0.724 ± 0.042 and 0.80 ± 0.058, respectively. The F<sub>IS</sub> value for this population was -0.108 which showed low inbreeding and considerable diversity in the studied population. The results of the control region (CR) of mtDNA showed that haplotype diversity and percentage of the polymorphic site were 0.938 ± 0.039 and 4.59, respectively. A total of 24 sequenced individuals of the control region (CR) of mtDNA and 17 haplotypes were identified in the studied population. The amount of nucleotide diversity in the Shin Bash population was 0.0131 ±0.0013 per site. The results of this study showed that 50% of the Shin Bash population has haplogroup A, 29.2% haplogroup B, and 20.8% haplogroup C.
<strong>Conclusions</strong>: The results of this study, using microsatellite markers, showed that the population of Shin Bash sheep has significant genetic diversity. The negative F<sub>IS</sub> index indicates the observed heterozygosity superiority over the expected heterozygosity and thus indicates non-inbreeding and the existence of acceptable diversity within the Shin Bash sheep population. The results of mtDNA control region sequencing also showed the presence of haplotypic diversity and higher nucleotide diversity in the Shin Bash sheep population. On the other hand, the results of determining haplotype groups showed that this population has all three types of haplotype groups A, B, and C.<strong>Introduction</strong>: West Azerbaijan province is the second most populous sheep province in Iran. In this province, different breeds of sheep such as Makui, Herki, Ghezel, Afshar, and Shin Bash are bred. Shin Bash sheep are bred in the south of West Azerbaijan province, especially in the cities of Mahabad and Piranshahr, and its population is about 200,000. Nowadays, the management of genetic resources and the study of the risk of genetic diversity of populations has become very important. The need to preserve the genetic resources of native livestock and use these genetic resources in the future determines the genetic structure of populations, and the study of the genetic diversity within each population can help manage genetic resources and provide good information for breeding programs. With the development of molecular techniques and the use of molecular markers as a tool to assess genetic diversity, useful information has been provided at various levels such as population structure, gene flow rate, phylogenetic relationships, and genealogy tests. Identification of livestock using various molecular techniques is highly accurate and the results of studies can be used in breeding and management programs. The purpose of this study was to study the genetic structure of Shin Bash sheep using microsatellite markers on the nuclear genome and SNP markers on mitochondrial DNA (mtDNA) and to introduce a lesser-known population.
<strong>Materials and methods:</strong> To study the genetic structure of the Shin Bash sheep population, 75 blood samples were collected from their geographic regions. Genomic DNA was extracted by using a modified Salting-Out method. Ten microsatellite markers and a control region (CR) of D-Loop belonging to mitochondrial DNA (mtDNA) were studied. Microsatellite loci were amplified in a multiplex PCR. Selected primers were labeled and genotyping was conducted using the Genetic Analyzer system. To analyze the data obtained from microsatellite markers, population parameters include: the Hardy-Weinberg equilibrium test, number of alleles per site, number of effective alleles, observed and expected heterozygosity, Shannon index, and F-statistic were calculated using POPGENE software version 3.1 and GENALEX version 6.5. In this research, Chromas ver. 2.33 (http://www.technelysium.com.au/chromas.html) was used to sort the sequencing data. Thus, the nucleotide sequence of each individual in this software was called and saved after sorting in the FASTA format. Also, to ensure the correct reading of the nucleotides, all sequences were examined using Blast online software at the NCBI site, indicating that this sequence is related to sheep mtDNA. To analyze the data obtained from sequencing in the control region of sheep mtDNA, MEGA version 7.0 and DnaSP version 6.12 were used.
<strong> Results and discussion:</strong> A Total of 84 alleles were identified; thus, the mean number of alleles per locus was 8.4. A total of 10 microsatellite loci were studied, seven were at Hardy-Weinberg equilibrium and three had significant deviations from Hardy-Weinberg equilibrium. Hardy-Weinberg disequilibrium can be caused by an increase in homozygotes <em>vs.</em> heterozygotes or, conversely, a high mutation rate, the formation of new alleles, and the presence of null alleles. The mean expected heterozygosity and observed heterozygosity in this population were 0.724 ± 0.042 and 0.80 ± 0.058, respectively. The F<sub>IS</sub> value for this population was -0.108 which showed low inbreeding and considerable diversity in the studied population. The results of the control region (CR) of mtDNA showed that haplotype diversity and percentage of the polymorphic site were 0.938 ± 0.039 and 4.59, respectively. A total of 24 sequenced individuals of the control region (CR) of mtDNA and 17 haplotypes were identified in the studied population. The amount of nucleotide diversity in the Shin Bash population was 0.0131 ±0.0013 per site. The results of this study showed that 50% of the Shin Bash population has haplogroup A, 29.2% haplogroup B, and 20.8% haplogroup C.
<strong>Conclusions</strong>: The results of this study, using microsatellite markers, showed that the population of Shin Bash sheep has significant genetic diversity. The negative F<sub>IS</sub> index indicates the observed heterozygosity superiority over the expected heterozygosity and thus indicates non-inbreeding and the existence of acceptable diversity within the Shin Bash sheep population. The results of mtDNA control region sequencing also showed the presence of haplotypic diversity and higher nucleotide diversity in the Shin Bash sheep population. On the other hand, the results of determining haplotype groups showed that this population has all three types of haplotype groups A, B, and C.https://ar.guilan.ac.ir/article_5933_ce725b5a253f3f2fd7df0cd91d42fb7f.pdfUniversity of GuilanAnimal Production Research2252-087211320221122Genomic-wide association study for egg weight-related traits in Rhode Island Red breed using Bayesian methodsGenomic-wide association study for egg weight-related traits in Rhode Island Red breed using Bayesian methods4153593010.22124/ar.2022.18153.1577FAA. H.Khaltabadi FarahaniAssociate Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran0000-0001-5805-590XH.MohammadiAssistant Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, IranM. H.MoradiAssociate Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran1111-1111-1111-1111H. A.GhasemiAssociate Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, IranI.HajkhodadadiAssociate Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, IranJournal Article20201111<strong>Introduction</strong>: The goal of genome-wide association (GWA) studies of quantitative traits is to identify genomic regions that explain a substantial proportion of the genetic variation for the trait, with the ultimate goal to identify causal mutations underlying the genetic basis of the trait. The standard GWA approach is to genotype a population that has been phenotyped for the trait(s) of interest and genotyped for many genetic markers across the genome and to analyze these data by estimating and testing the effects of marker genotypes on phenotypes using a regression-type of analysis for each single nucleotide polymorphism (SNP), one at a time. Bayesian methods such as Bayes A and Bayes B assume a heavy tail prior distribution for SNP effects and use Markov Chain Monte Carlo (MCMC) to sample from the posterior distribution. Although the objective of these methods was to predict the breeding value of selection candidates (genomic breeding values), they do that by estimating the effects of all SNPs. The estimated SNP effect, the proportion of variance explained by a SNP, or the number of times the SNP fits in the model with non–zero effect can be used as criteria to identify locations or genomic regions that affect the trait of interest. Results have shown that these Bayesian methods can effectively detect QTL in simulated and real data. Recently, a new methodology has been developed to address this limitation and allow for a better understanding of the genetic architecture of complex traits through a gene network analysis. For this purpose, to identify genomic regions and candidate genes associated with egg weight (EW), a genome-wide association study (GWAS) was performed in the present study using Affymetrix 600 K high density SNP array in 1,078 hens of 11th generation of Rhode Island Red.<br /><strong>Materials and methods:</strong> Data available for 1,078 pedigree-recorded hens were used to collect phenotypic EW-related data. Seven traits, including egg weight at the first laying of hens, and egg weight at 28, 36, 56, 66, 72, and 80 weeks of age were collected for each bird. The analyses were performed using GenSel v4.73R, by fitting covariates for haplotype alleles in BayesA and BayesB models. A single Markov chain Monte Carlo (MCMC) chain of length 41,000, including burn-in of 1,000 first iterations, was computed for each analysis to obtain posterior estimates of covariate effects. These were used to obtain a direct genetic variance for animals. The primary analysis showed that correlations and regression coefficients had converged at this chain length. Annotation terms and pathway analyses were conducted using protein analysis through evolutionary relationships of PANTHER software version 10.0.<br /><strong>Results and discussion: </strong>The results showed that the BayesA method performed better in explaining additive genetic variance compared to BayesB method. Nine markers obtained from BayesA with the highest additive genetic variance were located on chromosomes 1, 3, 5, and 20. Genes that overlap in regions of interest were identified with the Ensembl BioMart data mining (http://www.ensembl.org/biomart/) based on the Galgal6 assembly and the Ensembl Genes 96 database. The detected SNPs were located close to 35 genes, among which, the candidate genes of <em>BPIFB2, OCX36, CPT1A, TCF15, CECR2, SIAH3, FADS1, FADS2,</em> and <em>SGK1</em> play important functions in the egg production process through the albumen protein formation, fatty acids metabolism, and eggshell formation. It is noteworthy that the present study has detected an association in regions different from that reported by previous studies. This can be because of flock particularities, such as the extent of linkage disequilibrium, allelic frequencies, and statistical approaches.<br /><strong>Conclusions:</strong> The results of the present study showed that when the genetic architecture of studied traits follows infinitesimal model assumptions, the BayesA method usually performs better than BayesB. Moreover, considering the identification of new genome regions and the key role of the mentioned genes on the development of egg weight, the efficiency of the BayesA method can be confirmed for GWAS in egg weight traits.<strong>Introduction</strong>: The goal of genome-wide association (GWA) studies of quantitative traits is to identify genomic regions that explain a substantial proportion of the genetic variation for the trait, with the ultimate goal to identify causal mutations underlying the genetic basis of the trait. The standard GWA approach is to genotype a population that has been phenotyped for the trait(s) of interest and genotyped for many genetic markers across the genome and to analyze these data by estimating and testing the effects of marker genotypes on phenotypes using a regression-type of analysis for each single nucleotide polymorphism (SNP), one at a time. Bayesian methods such as Bayes A and Bayes B assume a heavy tail prior distribution for SNP effects and use Markov Chain Monte Carlo (MCMC) to sample from the posterior distribution. Although the objective of these methods was to predict the breeding value of selection candidates (genomic breeding values), they do that by estimating the effects of all SNPs. The estimated SNP effect, the proportion of variance explained by a SNP, or the number of times the SNP fits in the model with non–zero effect can be used as criteria to identify locations or genomic regions that affect the trait of interest. Results have shown that these Bayesian methods can effectively detect QTL in simulated and real data. Recently, a new methodology has been developed to address this limitation and allow for a better understanding of the genetic architecture of complex traits through a gene network analysis. For this purpose, to identify genomic regions and candidate genes associated with egg weight (EW), a genome-wide association study (GWAS) was performed in the present study using Affymetrix 600 K high density SNP array in 1,078 hens of 11th generation of Rhode Island Red.<br /><strong>Materials and methods:</strong> Data available for 1,078 pedigree-recorded hens were used to collect phenotypic EW-related data. Seven traits, including egg weight at the first laying of hens, and egg weight at 28, 36, 56, 66, 72, and 80 weeks of age were collected for each bird. The analyses were performed using GenSel v4.73R, by fitting covariates for haplotype alleles in BayesA and BayesB models. A single Markov chain Monte Carlo (MCMC) chain of length 41,000, including burn-in of 1,000 first iterations, was computed for each analysis to obtain posterior estimates of covariate effects. These were used to obtain a direct genetic variance for animals. The primary analysis showed that correlations and regression coefficients had converged at this chain length. Annotation terms and pathway analyses were conducted using protein analysis through evolutionary relationships of PANTHER software version 10.0.<br /><strong>Results and discussion: </strong>The results showed that the BayesA method performed better in explaining additive genetic variance compared to BayesB method. Nine markers obtained from BayesA with the highest additive genetic variance were located on chromosomes 1, 3, 5, and 20. Genes that overlap in regions of interest were identified with the Ensembl BioMart data mining (http://www.ensembl.org/biomart/) based on the Galgal6 assembly and the Ensembl Genes 96 database. The detected SNPs were located close to 35 genes, among which, the candidate genes of <em>BPIFB2, OCX36, CPT1A, TCF15, CECR2, SIAH3, FADS1, FADS2,</em> and <em>SGK1</em> play important functions in the egg production process through the albumen protein formation, fatty acids metabolism, and eggshell formation. It is noteworthy that the present study has detected an association in regions different from that reported by previous studies. This can be because of flock particularities, such as the extent of linkage disequilibrium, allelic frequencies, and statistical approaches.<br /><strong>Conclusions:</strong> The results of the present study showed that when the genetic architecture of studied traits follows infinitesimal model assumptions, the BayesA method usually performs better than BayesB. Moreover, considering the identification of new genome regions and the key role of the mentioned genes on the development of egg weight, the efficiency of the BayesA method can be confirmed for GWAS in egg weight traits.https://ar.guilan.ac.ir/article_5930_2764aa96efb5a0de65a350d3e0c1ffa2.pdfUniversity of GuilanAnimal Production Research2252-087211320221122Prediction of body weight of Sistani cows using computer visionPrediction of body weight of Sistani cows using computer vision5566593210.22124/ar.2022.20726.1651FAM.KhojastehkeyAssistant Professor, Animal Science Research Department, Qom Agriculture and Natural Resources Research and Education Center, AREEO, Qom, IranA.SadeghipanahAssistant Professor, Animal Science Research Institute of Iran, Agriculture Research, Education and Extension Organization (AREEO), Karaj, IranN.AsadzadehAssistant Professor, Animal Science Research Institute of Iran, Agriculture Research, Education and Extension Organization (AREEO), Karaj, IranA.AghashahiAssociate Professor, Animal Science Research Institute of Iran, Agriculture Research, Education and Extension Organization (AREEO), Karaj, Iran0000-0000-0000-0000M.Keikhah SaberAssistant Professor, Animal Science Research Department, Sistan and Baluchestan Agriculture and Natural Resources Research and Education Center, AREEO, Zahedan, IranM.Bitaraf SaniAssistant Professor, Animal Science Research Department, Yazd Agriculture and Natural Resources Research and Education Center, AREEO, Yazd, IranS.EsmaeilkhanianAssociate Professor, Animal Science Research Institute of Iran, Agriculture Research, Education and Extension Organization (AREEO), Karaj, IranJournal Article20211012<strong>Introduction</strong>: Sistani cows are generally restless animals; therefore, controlling, treating, and weighing them is difficult. On the other hand, recording the weight of domestic animals, including Sistani cows, is inevitable, because it provides a good scale for management decisions in the herd such as balancing the diet, changing environmental conditions, or determining the time of slaughter of fattening animals. In addition to scales, various methods are commonly used to measure the body weight of large animals. Some of these methods include the use of weight-meters, appraisal assessments, and the use of mathematical models. One of the new methods for predicting livestock weight is artificial intelligence. Because some reports are indicating that artificial intelligence could facilitate the weighing process of animals, this study was performed to predict the body weight of Sistani cows using computer vision technology.<br /><strong>Materials and methods: </strong>The data required for this study were recorded in the Zahak breeding station located in Sistan and Baluchestan province of Iran. The recording operation involved the weighing and biometric measurement of about 190 Sistani cattle, including calves, heifers, and male and female animals, every three months during a year. At the time of weighing, images of the lateral view of each animal were taken and recorded using the CANON SX150IS digital camera. During this period, a total of 358 weight records of Sistani cows at different ages were recorded. The digital images were initially preprocessed using MATLAB software, and then some morphological features were extracted from each image. For predicting the weight of Sistani cows via the Artificial Neural Network (ANN), the extracted features of images were introduced to the ANN model as input and the weight of cows as output. The "feed-forward neural network", which was trained by the "error propagation" algorithm, was used to predict the weight of cows. The function used in the hidden layer of the ANN model was sigmoidal and in the output layer was linear. An ANN model which had the highest precision and lowest error was selected as the final model for predicting the animal weights. The criteria for selecting the best model were the highest determination coefficient (R<sup>2</sup>) and the lowest mean square error (MSE) compared to other available models.<br /><strong>Results and discussion: </strong>Out of 22 features extracted from each image, only 15 of them, which had a higher correlation with the body weight of cows at different ages, were selected as effective features. As result, equivalent diameter, major axis length, minor axis length, bounding box, convex area, filled area, area, perimeter, and the number of non-zero pixels of the image (NNZ) had the highest correlation with the cattle weights (<em>P</em><0.01) and used as effective features to train the ANN model. The final ANN model had 15 neurons in the input layer including selected image features, 11 neurons in the hidden layer, and one neuron in the output layer including the weight of the cows. The precisions of the artificial neural network in the training, validation, and test phase were 0.974, 0.970, and 0.981, respectively. The results showed that the final ANN model had acceptable precision in all light, medium, and heavy-weight cows, and the size and the age of animals did not have a significant effect on the precision of the artificial neural network model. A correlation between the actual weight of Sistani cows and the weights predicted by the ANN model was 98.3%. The average error of the model in predicting the weight of cows was 1.11%. In the practical test, a 2.32 kg deviation was observed between the predictions of the ANN model and actual weights in Sistani cows. The accuracy of the ANN model for predicting the weight of Sistani cows in the present study is acceptable and within the range of the other reports.<br /><strong>Conclusions: </strong>The proposed method based on image processing and ANN, had acceptable results in predicting the weight of Sistani cows. Given the difficulties of weighing Sistani cows as heavy livestock and sometimes the time-consuming process, it seems that the use of new technologies such as computer vision methods can be a good alternative to conventional weighing methods and facilitate and reduce recording costs of Sistani cows.<strong>Introduction</strong>: Sistani cows are generally restless animals; therefore, controlling, treating, and weighing them is difficult. On the other hand, recording the weight of domestic animals, including Sistani cows, is inevitable, because it provides a good scale for management decisions in the herd such as balancing the diet, changing environmental conditions, or determining the time of slaughter of fattening animals. In addition to scales, various methods are commonly used to measure the body weight of large animals. Some of these methods include the use of weight-meters, appraisal assessments, and the use of mathematical models. One of the new methods for predicting livestock weight is artificial intelligence. Because some reports are indicating that artificial intelligence could facilitate the weighing process of animals, this study was performed to predict the body weight of Sistani cows using computer vision technology.<br /><strong>Materials and methods: </strong>The data required for this study were recorded in the Zahak breeding station located in Sistan and Baluchestan province of Iran. The recording operation involved the weighing and biometric measurement of about 190 Sistani cattle, including calves, heifers, and male and female animals, every three months during a year. At the time of weighing, images of the lateral view of each animal were taken and recorded using the CANON SX150IS digital camera. During this period, a total of 358 weight records of Sistani cows at different ages were recorded. The digital images were initially preprocessed using MATLAB software, and then some morphological features were extracted from each image. For predicting the weight of Sistani cows via the Artificial Neural Network (ANN), the extracted features of images were introduced to the ANN model as input and the weight of cows as output. The "feed-forward neural network", which was trained by the "error propagation" algorithm, was used to predict the weight of cows. The function used in the hidden layer of the ANN model was sigmoidal and in the output layer was linear. An ANN model which had the highest precision and lowest error was selected as the final model for predicting the animal weights. The criteria for selecting the best model were the highest determination coefficient (R<sup>2</sup>) and the lowest mean square error (MSE) compared to other available models.<br /><strong>Results and discussion: </strong>Out of 22 features extracted from each image, only 15 of them, which had a higher correlation with the body weight of cows at different ages, were selected as effective features. As result, equivalent diameter, major axis length, minor axis length, bounding box, convex area, filled area, area, perimeter, and the number of non-zero pixels of the image (NNZ) had the highest correlation with the cattle weights (<em>P</em><0.01) and used as effective features to train the ANN model. The final ANN model had 15 neurons in the input layer including selected image features, 11 neurons in the hidden layer, and one neuron in the output layer including the weight of the cows. The precisions of the artificial neural network in the training, validation, and test phase were 0.974, 0.970, and 0.981, respectively. The results showed that the final ANN model had acceptable precision in all light, medium, and heavy-weight cows, and the size and the age of animals did not have a significant effect on the precision of the artificial neural network model. A correlation between the actual weight of Sistani cows and the weights predicted by the ANN model was 98.3%. The average error of the model in predicting the weight of cows was 1.11%. In the practical test, a 2.32 kg deviation was observed between the predictions of the ANN model and actual weights in Sistani cows. The accuracy of the ANN model for predicting the weight of Sistani cows in the present study is acceptable and within the range of the other reports.<br /><strong>Conclusions: </strong>The proposed method based on image processing and ANN, had acceptable results in predicting the weight of Sistani cows. Given the difficulties of weighing Sistani cows as heavy livestock and sometimes the time-consuming process, it seems that the use of new technologies such as computer vision methods can be a good alternative to conventional weighing methods and facilitate and reduce recording costs of Sistani cows.https://ar.guilan.ac.ir/article_5932_5362749aacf0c07423144bb6c73f28ff.pdfUniversity of GuilanAnimal Production Research2252-087211320221122Influence of vitamin D3 and lactic acid on performance, egg quality, and hatchability in broiler breeder hensInfluence of vitamin D3 and lactic acid on performance, egg quality, and hatchability in broiler breeder hens6781593410.22124/ar.2022.21551.1683FAR.KanaaniPh.D. Student, Department of Animal Sciences, Faculty of Agriculture, University of Tabriz, Tabriz, IranR.KianfarAssociate Professor, Department of Animal Sciences, Faculty of Agriculture, University of Tabriz, Tabriz, Iran0000-0003-3950-8963H.JanmohammadiProfessor, Department of Animal Sciences, Faculty of Agriculture, University of Tabriz, Tabriz, IranW.Kyun KimAssociate Professor, Department of Poultry Sciences, College of Agricultural and Environmental Science, University of Georgia, Athens, USAM.OlyaeeAssistant Professor, Department of Animal Sciences, Faculty of Agriculture, University of Tabriz, Tabriz, IranJournal Article20220122<strong>Introduction</strong>: Vitamin D<sub>3</sub> is one of the important vitamins in calcium metabolism, which is significantly involved in the absorption of calcium from the intestine. The main role of 1, 25-hydroxyvitamin D<sub>3</sub> in vertebrates is to regulate calcium homeostasis, as 1, 25-hydroxyvitamin D<sub>3</sub> has a direct effect on the gut, kidney, and bones by inhibiting the production of parathyroid hormone in the parathyroid glands. The synthesis of 1, 25-dihydroxycholecalciferol is tightly controlled, and the main stimulus for its synthesis is the reduction in plasma calcium. This is a feedback stimulus for the release of parathyroid hormone from the parathyroid gland. This hormone in turn stimulates the 1-hydroxylase enzyme complex in the kidney and causes the conversion of 25-hydroxycholecalciferol through the synthesis of calcium-binding protein in the duodenum, thereby increasing dietary calcium absorption and ultimately plasma calcium. Another powerful factor in calcium absorption is organic acids. By lowering the pH of the digestive tract, organic acids (lactic acid) prevent the formation of an insoluble complex of phytic acid with minerals, making phytate more sensitive to the action of endogenous phytase and preventing it from interfering with the absorption of minerals. Therefore, the purpose of this research was to study the effect of vitamin D<sub>3</sub> and lactic acid on performance, egg quality, and hatchability in broiler breeders.<br /><strong>Materials and methods:</strong> A total of 240 broiler breeder hens and 24 roosters of Ross 308 strain were used in a completely randomized design with a 2×2 factorial arrangement including two levels of vitamin D (3500 and 5500 IU) and two levels of organic acid (zero and 500 mg/kg) in four treatments, six replications, and 10 hens and one rooster per replication. During the experiment, the percentage of hatchability, the number, and weight of eggs produced by each pen were recorded and using the common formulas of egg mass (as the percentage of laying multiplied by the average egg weight), the percentage of egg production as chicken-day and the feed conversion factor (as grams of feed consumed per gram of egg), the amount of feed used to produce each number of eggs and each piece of chicken, as well as the number of chickens produced per chicken was also calculated. Egg characteristics (egg weight and shape index) and egg shell quality (egg specific weight, eggshell weight compared to total egg weight and eggshell thickness), albumen and yolk pH, yolk index, Haugh unit, yolk color, percentage albumen and yolk percentage of four eggs from each replicate were measured every 28 days. The specific weight of the eggs was determined using the flotation method. The egg shape index was determined by measuring the width and length of the egg with a caliper to calculate the ratio of width to length. To determine eggshell parameters, eggs were identified and broken individually. Eggshells were washed under running water and dried at 35 °C for 72 hours. Then the eggshells were weighed and their relative weight was calculated. A digital micrometer (Series 500, Mitoyota, Tokyo, Japan) was used to measure the shell thickness.<br /><strong>Results and discussion:</strong> Results showed that the main effect of vitamin D<sub>3</sub> at higher concentrations was affecting egg weight and reducing egg weight (<em>P</em><0.05). The main effect of vitamin D<sub>3</sub> at higher concentrations caused an increase in albumen pH, shell percentage, shell thickness, and specific gravity of the egg, and a decrease in yolk pH (<em>P</em><0.05). Probably, with the increase in vitamin D<sub>3</sub>, the concentration of 1,25-cholecalciferol and the amount of calcium absorption increase, and since most of the shell is related to calcium carbonate, this leads to an increase in the thickness of the eggshell. The main effect of lactic acid showed a significant effect on performance parameters, and the addition of lactic acid improved performance (<em>P</em><0.05). Lactic acid also significantly increased hatchability and shell thickness and reduced the number of broken eggs (<em>P</em><0.05). It appears that organic acids increase the solubility of wheat phytates during germination. Therefore, acidification of the diet provides a better environment for phytase to reduce the amount of phytate present in digestion and flowing into the small intestine, thereby largely preventing the formation of insoluble mineral-phytate complexes and increasing the quality of the eggshell. Also, the main effect of lactic acid showed no significant influence on the internal quality of the eggs. The low levels of vitamin D<sub>3</sub> and the addition of lactic acid improved shell thickness and reduced the percentage of shell breakage (<em>P</em><0.05).<br /><strong>Conclusions:</strong> In general, according to the results of the present experiment, the use of lactic acid at the rate of 500 mg/kg along with 3500 IU of vitamin D<sub>3</sub> can increase the percentage of production, shell thickness, reduce the number of broken eggs, improve the feed conversion ratio, increase chicken production and reduce feed consumption per egg and chicken at the end of the production period of broiler breeder hens.<strong>Introduction</strong>: Vitamin D<sub>3</sub> is one of the important vitamins in calcium metabolism, which is significantly involved in the absorption of calcium from the intestine. The main role of 1, 25-hydroxyvitamin D<sub>3</sub> in vertebrates is to regulate calcium homeostasis, as 1, 25-hydroxyvitamin D<sub>3</sub> has a direct effect on the gut, kidney, and bones by inhibiting the production of parathyroid hormone in the parathyroid glands. The synthesis of 1, 25-dihydroxycholecalciferol is tightly controlled, and the main stimulus for its synthesis is the reduction in plasma calcium. This is a feedback stimulus for the release of parathyroid hormone from the parathyroid gland. This hormone in turn stimulates the 1-hydroxylase enzyme complex in the kidney and causes the conversion of 25-hydroxycholecalciferol through the synthesis of calcium-binding protein in the duodenum, thereby increasing dietary calcium absorption and ultimately plasma calcium. Another powerful factor in calcium absorption is organic acids. By lowering the pH of the digestive tract, organic acids (lactic acid) prevent the formation of an insoluble complex of phytic acid with minerals, making phytate more sensitive to the action of endogenous phytase and preventing it from interfering with the absorption of minerals. Therefore, the purpose of this research was to study the effect of vitamin D<sub>3</sub> and lactic acid on performance, egg quality, and hatchability in broiler breeders.<br /><strong>Materials and methods:</strong> A total of 240 broiler breeder hens and 24 roosters of Ross 308 strain were used in a completely randomized design with a 2×2 factorial arrangement including two levels of vitamin D (3500 and 5500 IU) and two levels of organic acid (zero and 500 mg/kg) in four treatments, six replications, and 10 hens and one rooster per replication. During the experiment, the percentage of hatchability, the number, and weight of eggs produced by each pen were recorded and using the common formulas of egg mass (as the percentage of laying multiplied by the average egg weight), the percentage of egg production as chicken-day and the feed conversion factor (as grams of feed consumed per gram of egg), the amount of feed used to produce each number of eggs and each piece of chicken, as well as the number of chickens produced per chicken was also calculated. Egg characteristics (egg weight and shape index) and egg shell quality (egg specific weight, eggshell weight compared to total egg weight and eggshell thickness), albumen and yolk pH, yolk index, Haugh unit, yolk color, percentage albumen and yolk percentage of four eggs from each replicate were measured every 28 days. The specific weight of the eggs was determined using the flotation method. The egg shape index was determined by measuring the width and length of the egg with a caliper to calculate the ratio of width to length. To determine eggshell parameters, eggs were identified and broken individually. Eggshells were washed under running water and dried at 35 °C for 72 hours. Then the eggshells were weighed and their relative weight was calculated. A digital micrometer (Series 500, Mitoyota, Tokyo, Japan) was used to measure the shell thickness.<br /><strong>Results and discussion:</strong> Results showed that the main effect of vitamin D<sub>3</sub> at higher concentrations was affecting egg weight and reducing egg weight (<em>P</em><0.05). The main effect of vitamin D<sub>3</sub> at higher concentrations caused an increase in albumen pH, shell percentage, shell thickness, and specific gravity of the egg, and a decrease in yolk pH (<em>P</em><0.05). Probably, with the increase in vitamin D<sub>3</sub>, the concentration of 1,25-cholecalciferol and the amount of calcium absorption increase, and since most of the shell is related to calcium carbonate, this leads to an increase in the thickness of the eggshell. The main effect of lactic acid showed a significant effect on performance parameters, and the addition of lactic acid improved performance (<em>P</em><0.05). Lactic acid also significantly increased hatchability and shell thickness and reduced the number of broken eggs (<em>P</em><0.05). It appears that organic acids increase the solubility of wheat phytates during germination. Therefore, acidification of the diet provides a better environment for phytase to reduce the amount of phytate present in digestion and flowing into the small intestine, thereby largely preventing the formation of insoluble mineral-phytate complexes and increasing the quality of the eggshell. Also, the main effect of lactic acid showed no significant influence on the internal quality of the eggs. The low levels of vitamin D<sub>3</sub> and the addition of lactic acid improved shell thickness and reduced the percentage of shell breakage (<em>P</em><0.05).<br /><strong>Conclusions:</strong> In general, according to the results of the present experiment, the use of lactic acid at the rate of 500 mg/kg along with 3500 IU of vitamin D<sub>3</sub> can increase the percentage of production, shell thickness, reduce the number of broken eggs, improve the feed conversion ratio, increase chicken production and reduce feed consumption per egg and chicken at the end of the production period of broiler breeder hens.https://ar.guilan.ac.ir/article_5934_e030772b0ff9b0de3cdaa552ff2910fa.pdfUniversity of GuilanAnimal Production Research2252-087211320221122Effect of replacing dietary alfalfa with barberry leaf on growth performance and blood indices in ostrichEffect of replacing dietary alfalfa with barberry leaf on growth performance and blood indices in ostrich8392593110.22124/ar.2022.20184.1638FAM.AfshinPh.D. Student, Department of Animal and Poultry Science, College of Agriculture, University of Birjand, Birjand, IranN.AfzaliProfessor, Department of Animal and Poultry Science, College of Agriculture, University of Birjand, Birjand, IranS. J.Hosseini-VashanAssociate Professor, Department of Animal and Poultry Science, College of Agriculture, University of Birjand, Birjand, IranA.HajibabaeiAssistant Professor, Department of Animal and Poultry Science, University of Pretoria, Pretoria, South AfricaJournal Article20210729<strong>Introduction</strong>: The term “Livestock Revolution” was coined to describe the projected increase in demand for animal products due to population growth, increased income, and urbanization in developing countries. In this context, a decision to rear well-adapted livestock species, like the ostrich, could be effective in meeting present and future demands for animal products in a sustainable manner. On the other hand, most of the ostrich production costs are associated with the feeding price similar to broiler chickens. Due to the high ability of ostrich regarding fiber consumption, it is expected that ostriches can benefit from cheaper native foods such as barberry leaves. Ostrich digestive system has a great ability to use fiber diets due to having a long rectum (about eight meters). Furthermore, the microbial population of the cecum and colon in ostrich is similar to the rumen. The total area of barberry cultivation in Iran was reported to be 16007 hectares in 2017 and more than 14700 hectares of that were placed in South Khorasan. The amount of foliage of each barberry shrub is between three to five kg dry mater which remains almost unused after fruit harvesting. Hence, large amounts of branches and leaves from barberry harvesting could be considered agricultural residues for usage in animal feeding, annually. This study aimed to study the effect of replacing dietary alfalfa with barberry leaf on growth performance and blood indices in ostrich.<br /><strong>Materials and methods:</strong> The effects of replacing dietary alfalfa with barberry leaf on ostrich growth performance and some blood parameters were investigated using 20 ostriches (two to seven months of age) in a completely randomized design with five treatments (four replicates each). Barberry leaves and alfalfa used in this study were prepared manually from South Khorasan farms. Then samples were separately pooled and grounded in a hammer mill and were transferred to the laboratory to determine the amount of crude energy, dry matter, crude fat, crude protein, ash, neutral detergent fiber, and acid detergent fiber (all in three replications). The experimental diets were prepared by replacing alfalfa at 0, 25, 50, 75, and 100% with barberry leaf. Diets contain the same metabolizable energy and crude protein. Ostriches had free access to feed and water during the trial. Feed intake and body weight gain of each experimental unit were measured at 60, 120, and 210 days of age, and the feed conversation ratio (FCR) was calculated. At 90 and 210 days of age, blood samples were harvested from the wing vein of ostrich using tubes containing Li-heparin as an anticoagulant, then the blood samples were centrifuged at 3000 × g, 15 min at room temperature, and stored at −20 <sup>◦</sup>C temperature for later analysis. The plasma concentrations of glucose, cholesterol, triglycerides, high-density lipoprotein (HDL), protein, and albumin as well as the activity of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were determined by auto-analyzer spectrophotometry according to the procedures of the manufacturers.<br /><strong>Results and discussion:</strong> The results revealed that dry matter intake (DMI) was enhanced with increasing dietary levels of barberry leaf (<em>P</em><0.05). These findings showed the favorable effects of barberry leaves on feed intake. One of the main reasons associated with the reduction of dry matter consumption following the inclusion of agricultural by-products is the high amount of phenolic compounds, especially the tannins of these products. Barberry leaves have a low concentration of phenolic compounds (especially tannins) compared to other by-products such as pistachio peel, pomegranate pulp, <em>Elaeagnus angustifolia</em> leaves, etc. Substitution of alfalfa hay with barberry leaf at 50% of the diet significantly increased daily weight gain compared to the control group (<em>P</em><0.05). In the whole experimental period, FCR was lower in the diet containing 50% of barberry leaf than in the diet with 100% replacement of alfalfa with barberry leaf (<em>P</em><0.05). Increasing the FCR in the diet by replacing more than 50% of barberry leaves can be related to the reduction of the digestibility of the diet due to a decrease in the particle size of barberry leaves as well as its nature after milling compared to alfalfa and the reduction of the supply of amino acid profile due to synergy of two sources of alfalfa and barberry leaves. The highest concentration of plasma glucose at 90 and 210 days of age (191.33 and 193.3, respectively) were observed in the control diet. Numerous studies have reported the hypoglycemic effects of barberry. Replacement of 50, 75, and 100% of alfalfa with barberry leaf decreased significantly the plasma activity of ALT as compared to the control group (<em>P</em><0.05). Although there are no reports of the use of barberry leaves or its active ingredient (berberine) in ostrich, previous reports have shown that the use of barberry fruit extract reduced liver enzyme concentrations.<br /><strong>Conclusions:</strong> Overall, the results of the current study showed that alfalfa hay could be replaced partially or completely with barberry leaves in the diet of ostriches without severe deleterious effects on performance. Replacement of 50% of alfalfa with barberry leaf would recommend for use in ostrich diets.<strong>Introduction</strong>: The term “Livestock Revolution” was coined to describe the projected increase in demand for animal products due to population growth, increased income, and urbanization in developing countries. In this context, a decision to rear well-adapted livestock species, like the ostrich, could be effective in meeting present and future demands for animal products in a sustainable manner. On the other hand, most of the ostrich production costs are associated with the feeding price similar to broiler chickens. Due to the high ability of ostrich regarding fiber consumption, it is expected that ostriches can benefit from cheaper native foods such as barberry leaves. Ostrich digestive system has a great ability to use fiber diets due to having a long rectum (about eight meters). Furthermore, the microbial population of the cecum and colon in ostrich is similar to the rumen. The total area of barberry cultivation in Iran was reported to be 16007 hectares in 2017 and more than 14700 hectares of that were placed in South Khorasan. The amount of foliage of each barberry shrub is between three to five kg dry mater which remains almost unused after fruit harvesting. Hence, large amounts of branches and leaves from barberry harvesting could be considered agricultural residues for usage in animal feeding, annually. This study aimed to study the effect of replacing dietary alfalfa with barberry leaf on growth performance and blood indices in ostrich.<br /><strong>Materials and methods:</strong> The effects of replacing dietary alfalfa with barberry leaf on ostrich growth performance and some blood parameters were investigated using 20 ostriches (two to seven months of age) in a completely randomized design with five treatments (four replicates each). Barberry leaves and alfalfa used in this study were prepared manually from South Khorasan farms. Then samples were separately pooled and grounded in a hammer mill and were transferred to the laboratory to determine the amount of crude energy, dry matter, crude fat, crude protein, ash, neutral detergent fiber, and acid detergent fiber (all in three replications). The experimental diets were prepared by replacing alfalfa at 0, 25, 50, 75, and 100% with barberry leaf. Diets contain the same metabolizable energy and crude protein. Ostriches had free access to feed and water during the trial. Feed intake and body weight gain of each experimental unit were measured at 60, 120, and 210 days of age, and the feed conversation ratio (FCR) was calculated. At 90 and 210 days of age, blood samples were harvested from the wing vein of ostrich using tubes containing Li-heparin as an anticoagulant, then the blood samples were centrifuged at 3000 × g, 15 min at room temperature, and stored at −20 <sup>◦</sup>C temperature for later analysis. The plasma concentrations of glucose, cholesterol, triglycerides, high-density lipoprotein (HDL), protein, and albumin as well as the activity of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were determined by auto-analyzer spectrophotometry according to the procedures of the manufacturers.<br /><strong>Results and discussion:</strong> The results revealed that dry matter intake (DMI) was enhanced with increasing dietary levels of barberry leaf (<em>P</em><0.05). These findings showed the favorable effects of barberry leaves on feed intake. One of the main reasons associated with the reduction of dry matter consumption following the inclusion of agricultural by-products is the high amount of phenolic compounds, especially the tannins of these products. Barberry leaves have a low concentration of phenolic compounds (especially tannins) compared to other by-products such as pistachio peel, pomegranate pulp, <em>Elaeagnus angustifolia</em> leaves, etc. Substitution of alfalfa hay with barberry leaf at 50% of the diet significantly increased daily weight gain compared to the control group (<em>P</em><0.05). In the whole experimental period, FCR was lower in the diet containing 50% of barberry leaf than in the diet with 100% replacement of alfalfa with barberry leaf (<em>P</em><0.05). Increasing the FCR in the diet by replacing more than 50% of barberry leaves can be related to the reduction of the digestibility of the diet due to a decrease in the particle size of barberry leaves as well as its nature after milling compared to alfalfa and the reduction of the supply of amino acid profile due to synergy of two sources of alfalfa and barberry leaves. The highest concentration of plasma glucose at 90 and 210 days of age (191.33 and 193.3, respectively) were observed in the control diet. Numerous studies have reported the hypoglycemic effects of barberry. Replacement of 50, 75, and 100% of alfalfa with barberry leaf decreased significantly the plasma activity of ALT as compared to the control group (<em>P</em><0.05). Although there are no reports of the use of barberry leaves or its active ingredient (berberine) in ostrich, previous reports have shown that the use of barberry fruit extract reduced liver enzyme concentrations.<br /><strong>Conclusions:</strong> Overall, the results of the current study showed that alfalfa hay could be replaced partially or completely with barberry leaves in the diet of ostriches without severe deleterious effects on performance. Replacement of 50% of alfalfa with barberry leaf would recommend for use in ostrich diets.https://ar.guilan.ac.ir/article_5931_b3f13e895ba518f8b0f845e0d4d5411d.pdf