Objective Over the last decade, interest in detection of genes or genomic regions that are targeted by selection has been growing. Identifying signatures of selection can provide valuable insights about the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. The aim of this study was to identify genomic region with a positive signature of selection related to wool quality in sheep breeds using selection signature FST and hapFLK methods. Materials and methods In this study, data from 146 Zandi and Merino animals genotyped using 50 K BeadChip were used to identify genomic regions under selection associated with wool quality traits. After quality control of the initial data using plink software, 46,793 SNP markers in 144 animals of sheep were finally entered for further analysis. To identify the signatures of selection, two statistical methods of FST and hapFLK were used under FST and hapFLK software packages, respectively. Candidate genes were identified by SNPs located at 0.1% upper range of FST and hapFLK values. GeneCards and UniProtKB databases were also used to interpret the function of the obtained genes. Results Using FST approach, we identified eight genomic regions on chromosomes 1 (two region), 1, 3 (two region), 10, 13, and 19 chromosomes, which were in the 99.9 percentile of all FST values. The identified candidate genes associated with wool trait in these genomic regions included POU1F1, FGF12, GNAS, LHX2, TMTC3, NBEA, MITF. Genes located in identified regions under selection were associated with the crimp of wool, growth and development of skin, fiber diameter, hair follicle development, growth and development of fiber, stimulation of collagen, regulation of epithelial cell and skin pigments, which can be directly and indirectly related to the trait of the wool quality. Also, the results of hapFLK statistics in this research led to the identification of four genomic regions on chromosomes 7, 10, 14, and 19. The identified candidate genes associated with the wool trait in these genomic regions included DUOX1, RHPN2 and LOC106991379. It was determined that they had different functions in collagen differentiation and gene expression of keratinocytes. Conclusions Various genes that were founded within these regions can be considered as candidates for selection based on function. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of genes obtained from association analyses. The results of our research can be used to understand the genetic mechanism controlling wool traits and using these findings could potentially be useful for genetic selection in sheep for better clean fleece yield and mean fiber diameters.

Data of Kermani sheep which collected during 1980-2002 were used in this study to estimate genetic parameters of growth chracteriestics. Traits were birth weight (BW, n=2086), 3 months weight (3MW,n=1922), 6 months weight (6MW, n=1142), 9 months weight (9MW,n=1583) and 12 months weight (12MW,n=774).Data of wool chracteriestics were measured and gathered in this study and were used to estimate genetic parameters of wool chracteriestics.Trait were staple length (SL,n=629), fleece yield (FY,n=629), fibre diameter(FD,n=629) and fleece weight (FW,n=629). Univariete and multivariate animal models with DFREML methods were used to estimate variance component.Estimated heritability in univariete analysis for BW, 3MW, 6MW, 9MW, 12MW, SL, FY, FD and FW were 0/101± 0.069, 0.296± 0.079, 0.308±0.087, 0.062± 0.078, 0.260± 0.071, 0.202± 0.111, 0.201±0.434, 0.205±0.333 and 0.414±0.10 respectively. Estimated heritability in multivariate analysis for BW, 3MW, 6MW, 9MW, 12MW, SL, FY, FD, and FW were 0.233±0/068, 0.576±0.079, 0.498±0.078, 0.299±0.076, 0.367±0.090, 0.639±0.233, 0.867±0.310, 0.930±0.790 and 0.595±0.110 respectively.Estimates of correlation coefficient between growth characteristics were high and positive and ranged from 0.87 to 0.98. Correlation coefficient between wool characteristics were positive but low and ranged from 0.001 to 0.15.

The aim of this study was to compare the characteristics of wool from Arkhamerino, Ghezel and Moghani crosses. In order to evaluate fleece characteristics, wool samples were obtained from 176 Arkhamerino×Ghezel (ARG) and 80 Arkhamerino×Moghani (ARM) F1 crosses (aged 9-15 months). Samples were taken in spring from right mid-side during a period of three years (1999-2001). Fleece characteristics including fiber diameter (FD), fiber diameter variability (CVd), staple length (SL), kemp (KP) and medulation (MP) percentage were analyzed. Average fleece characteristics of FD, CVd, SL, KP and MP for ARG were 27.11±0.25m, 36.6±0.59%, 11.94±0.32 cm, 1.56±0.35% and 7.33±0.72% and for ARM were 26.18±0.46m, 36.16±0.97, 10.95±0.39cm, 2.27±0.29 and 8.82±0.91, respectively. Data were analyzed for genotype, sex, birth year and birth type by general linear model (Glm) and the age of sheep (or lambs) considered as a cofactor in statistical model. The genotype had a significant (P<0.05) effect on FD and ARM crosses had produced finer wool. Sex significantly (P<0.05) affected FD, CVd and SL. Females had finer wool with higher CV and longer staple. Year of birth had significant (P<0.05) effect on SL (P<0.05). F1 crosses which were born in 2000 had shorter staples. The interaction of genotype and the year of birth significantly (P<0.05) affected CVd. Type of birth had no significant effect on fleece characteristics.

Introduction: Identifying of genes with large effects on economically important traits, has been one of the important goal to sheep breeding. Over recent years, advances in DNA-based marker technology have made it possible to identify genomic regions or quantitative trait loci (QTLs) underlying complex traits, such as fleece traits, in sheep. The present study aimed to conduct a genome wide association studies (GWAS) based on gene-set enrichment analysis for identifying the loci associated with wool traits in native Zandi sheep using the 50K arrays. Material and Methods: A total of 300 Iranian Zandi sheep used in this study came from the Zandi sheep breeding station. Wool sampling coincided with the maximum wool growth prior to the shearing of wool. In order to facilitate sampling, sheep were restrained in a lateral position and true wool from the left mid-side site was cut from a 5×5 cm2 close to the skin using regular scissors. Each sample was separately packaged and labeled with ear tag number of the sheep. We measured and recorded four wool production traits: staple length (SL), mean fiber diameter (MFD), fiber diameter coefficient of variation (CVFD), and the proportion of fiber that are equal or more than 30 µm (PR), kemp percentage (KEMP%) and outer coat fiber (OCF) were measured. Genomic DNA extraction from sheep blood was performed by the applying a modified salting out protocol and genotyping of the Sheep SNPChip 50 K SNP Bead from Illumina Inc. 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 wool 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 50 kb up- and downstream of the gene and bioinformatics analysis was implemented to identify the biological pathways performed in GO, KEEG, DAVID and PANTHER databases. 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. In the next step, a bioinformatics analysis was implemented to identify the biological pathways performed in GeneCards databases. Result and Discussion: The result from genomic control showed weak population stratification with for woot traits among Zandi sheep population. We identified different sets of candidate genes related to wool traits including: CEP290, PRKCZ, TMTC3, RHPN2, TNFSF4, NLGN1, SPHKAP, PLCE1, FAT1 and PIK3R4 in Zandi sheep. Some of the found genes, are consistent with some of the previous studies related to reproductive traits. According to pathway analysis, 21 pathways from gene ontology and biological pathways were associated with the wool traits (P˂0.05).  Some of the genes were found are consistent with some prior studies and to be involved biological pathways related to hair follicle development, keratinocytes differentiation, synthesizes an enzyme of threonine kinases, development of epidermal and Wnt signaling pathway. Conclusion: In total, this study supported previous results from GWAS of wool traits, also revealed additional regions in the sheep genome associated with these economically important traits. These findings could potentially be useful for genetic selection in the breeding programs and can be used to understand the genetic mechanism controlling this trait.

Introduction: Identifying of genes with large effects on economically important traits, has been one of the important goals in sheep breeding. Over the last decade, by the advent of genome-wide panels of single nucleotide polymorphisms (SNPs), it has become possible to identify and localize QTLs for complex traits in many livestock species. One important obstacle in association studies is the confounding effect of population structure. Because this effect generally increases in proportion to population size, population structure remains a major concern in association analyses. To date, 98 QTLs for wool traits have been reported via genome scan based on marker-QTL linkage analyses (http: //cn. animalgenome. org/cgi-bin/QTLdb/OA/index, 27 Aug, 2017). Compared with traditional QTL mapping strategies, a GWAS has major advantages both in its power to detect causal variants with modest effects and in defining narrower genomic regions harboring causal variants for economically important traits. In this study, we assessed population stratification and performed a genome-wide association study (GWAS) of wool quality traits in Zandi sheep. Material and methods: A total of 96 Iranian Zandi sheep was used in the study. The following four traits were analyzed: staple length (SL), mean fiber diameter (MFD), fiber diameter coefficient of variation (FDCV), and the proportion of fiber that was equal or more than 30 µ m (F≥ 30). Animals were genotyped using 50 K SNPChip panel. Quality control of the genotype data consisted in removing SNPs with a call rate less than 95 %, SNPs with a minor allele frequency (MAF) less than 5 %, SNPs with more than x % missing genotypes, and SNPs that deviated strongly from Hardy– Weinberg equilibrium (P < 10 − 6 ). The PLINK was used to generate the matrix using the GLM algorithm. In this study, although the resources of this breed were very clear, we still examined the distribution of the test statistics obtained from the numerous association tests. We also assessed their deviation from the expected distribution of no SNPs being associated with the trait of interest using a quantile-quantile (Q-Q) plot, which is commonly used to analyze population stratification in GWAS. We use SNPEVG tool to show the (Q-Q) plot. The Bonferroni method was used to adjust for multiple testing from the number of SNP loci detected. We declared a significant SNP at the genomewide significance level if the raw P-value was0. 05/N, here N is the number of SNP loci tested in the analysis. The exact positions of the annotated genes were extracted from the latest sheep genome Oar_v4. 0 assembly along with the NCBI annotation release 102 of the sheep genome. To investigate if the significant SNPs detected in this study were within the range of previously identified QTL for relevant traits, we searched for meat or production QTL in the Animal QTLdb within a 1-Mb region on both sides of each significant haplotype. Results and discussion: After quality control, 2 individuals were excluded, leaving 94 sheep for the association analysis. Additionally, we removed 1070 SNPs with call rates less than 95% and 7717 SNPs with MAF less than 0. 05. A total of 40, 879 SNPs passed these quality-control filters and were retained in the dataset. These SNPs were distributed across 26 autosomes, with the number of SNPs per chromosome ranging from 747 to 5694, and with a mean distance between adjacent SNPs ranging from 50. 4 to 68. 7 kb. Wool MFD was 29. 85± 0. 03 µ m with an individual sheep range of 22. 4-39. 04 µ m. The overall coefficient of variation of fiber diameter was 43. 12%± 0. 7% with an individual sheep range of 19. 7%– 68. 0%. The average percentages of fiber that had equal or more than 30 µ m were 27. 04± 0. 03% with an individual sheep range of 12. 04-43. 10%. Average wool staple length was 11. 25± 0. 03 cm with an individual sheep range of 6-19 cm. The result from genomic control showed weak population stratification for SL, MDF, FDCV and F≥ 30 between populations of Zandi sheep. The genomic inflation factors (λ gc) for the four traits were equal to 1. 127, 1. 101, 1. 059, and 1. 009 for MDF, FDCV, FD≥ 30 and SL, respectively. However, the Q-Q plots clearly showed there was no evidence of any systematic bias due to population structure or analytical approach in our case. Overally, two significant SNPs at the genome-wise level were identified for FD, and FDCV. No significant SNPs was identified for SLor FD≥ 30. Two Haplotype region within ERBB2 and GNAS genes previously reported in human growth and development hair and skin. Haplotypes were located with previously QTL reported to affect fiber diameter and fiber diameter coefficient of variation in Merino and INRA401 breed sheep. The functions of all of the above genes are directly or indirectly related to skin and hair development. Hair follicles are skin appendages and produce hair; therefore, we hypothesize that these genes control hair follicle development and fiber diameter trait. Conclusion: The results of this study could provide a suite of novel SNP markers and candidate genes associated with wool traits and hence, may play an important role in understanding the biology of wool traits in fat-tailed sheep.

Accurate estimation of variance components using pedigree and genomic data plays a key role in prediction of breeding values. Since SNP markers in genomic selection are distributed across the genome, they may cover all quantitative traits loci and potentially explain all of genetic variation. In this study, genotype data from Merino sheep, genotyped by 50k Illumina SNP chip were used. Staple length and Fibre diameter traits were studied in this research. To study the association between allele frequency spectrum and captured additive genetic variance, all SNPs were partitioned in five MAF bins with the equal numbers of SNPs. Two statistical models including separate analysis for each category of MAF SNPs or joint analysis of all MAF groups were fitted. The analysis were performed using REML (parametric) and a Bayesian method implemented via Gibbs sampling and RKHS (semi-parametric) model. Using all common SNPs in REML approach, estimates of genomic heritability were 0. 72 and 0. 48 for Staple length and Fibre diameter, respectively. In Bayesian approach, genomic heritability for mentioned traits were 0. 74 and 0. 47 respectively. In the separate analysis, estimates of genomic heritability using REML and Bayesian approaches for each MAF class were similar, but in joint analysis estimates of two approaches were different. Overall, when the model is simple both approaches perform similarly while when model is complicated as joint analysis in present study, two approaches work different. Therefore, to determine which approach is more reliable, further research is required