Genetic diversity and signatures of selection in four indigenous horse breeds of Iran.

Indigenous Iranian horse breeds were evolutionarily affected by natural and artificial selection in distinct phylogeographic clades, which shaped their genomes in several unique ways. The aims of this study were to evaluate the genetic diversity and genomewide selection signatures in four indigenous Iranian horse breeds. We evaluated 169 horses from Caspian (n = 21), Turkmen (n = 29), Kurdish (n = 67), and Persian Arabian (n = 52) populations, using genomewide genotyping data. The contemporary effective population sizes were 59, 98, 102, and 113 for Turkmen, Caspian, Persian Arabian, and Kurdish breeds, respectively. By analysis of the population genetic structure, we classified the north breeds (Caspian and Turkmen) and west/southwest breeds (Persian Arabian and Kurdish) into two phylogeographic clades reflecting their geographic origin. Using the de-correlated composite of multiple selection signal statistics based on pairwise comparisons, we detected a different number of significant SNPs under putative selection from 13 to 28 for the six pairwise comparisons (FDR < 0.05). The identified SNPs under putative selection coincided with genes previously associated with known QTLs for morphological, adaptation, and fitness traits. Our results showed HMGA2 and LLPH as strong candidate genes for height variation between Caspian horses with a small size and the other studied breeds with a medium size. Using the results of studies on human height retrieved from the GWAS catalog, we suggested 38 new putative candidate genes under selection. These results provide a genomewide map of selection signatures in the studied breeds, which represent valuable information for formulating genetic conservation and improved breeding strategies for the breeds.

Genome-wide association study reveals novel candidate genes for litter size in Markhoz goats.

Introduction: The Markhoz goat is the only breed that can produce high-quality fiber called mohair in Iran; however, the size of its population has faced a dramatic decline during the last decades, mainly due to the reluctance of farmers to rear Markhoz goats caused by a reduction in goat production income. Litter size at birth (LSB) and weaning (LSW) are two economically important reproductive traits for local goat breeders and have the potential of increasing the population growth rate. The present study was aimed to identify possible genomic regions that are associated with LSB and LSW in Markhoz goats using a genome-wide association study (GWAS). Methods: To this end, 136 Markhoz goats with record(s) of kidding were selected for GWAS using the Illumina Caprine 50K bead chip. The individual breeding values (BV) of available LSB and LSW records estimated under an animal mixed model were used as the dependent variable in the GWAS, thereby incorporating repeated categorical variables of litter size. Results: Four SNPs on chromosomes 2, 20 and 21 were identified to be significantly associated (FDR p < 0.05) with LSB after multiple testing correction under a Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model. Least-square analysis was performed to investigate the effects of detected genotypes on LSB. Ultimately, the GWAS results introduced six candidate genes, including GABRA5, AKAP13, SV2B, PPP1R1C, SSFA2 and TRNAS-GCU in a 100 kb adjacent region of the identified SNPs. Previous studies proposed functional roles of GABRA5 and AKAP13 genes in reproductive processes; however, the role of other candidate genes in reproduction is not clear. Conclusion: These findings warrant further investigation for use in marker-assisted selection programs in Markhoz goats.

Effects of Imported Semen Based on Different Selection Indices on Some Production and Reproduction Traits in Iranian Holstein Cattle.

The aim of the present study was to evaluate the effects of imported semen of Holstein bulls from different countries on the economic traits of their daughters using the Lifetime Net Income (LNI) index in various climates of Iran. The data included the first lactation records of 274,057 Holstein cows collected during 1993 to 2017 by the Animal Breeding Center of Iran from 10 large dairy farms located in various provinces of Iran. The investigated traits included milk, fat and protein yields, calving age and calving interval. Breeding values of progenies were predicted by the Best Linear Unbiased Prediction (BLUP) method under the multi-trait animal model using DMU software. The genetic-economic merit of the progenies was estimated by the LNI index. There were significant differences between the estimated breeding values (EBVs) of sire groups (based on bull semen origin) for milk, fat and protein yields, calving age and calving interval in each climate (p < 0.01). The obtained results showed that the highest least-square means of LNI index in semi-cold, moderate and warm climates belonged to the daughters of French sires; however, daughters of German sires were estimated to have the highest least-square means in the cold climate.

Genetic evaluation of age at first calving and days open under different censoring scenarios in Iranian Holstein cows.

The present study aimed to investigate the effect of censoring, the situations in which incomplete at the time, out of range, and/or delayed records were considered, in the estimation of genetic parameters for age at first calving (AFC) and days open (DO) in Iranian Holstein cows. The dataset included 281,772 records collected from 1991 to 2019 by the Vahdat Cooperative Company, a pioneer dairy farm in Isfahan Province, the central part of Iran. Five animal models including linear model (LM), penalty model (PM), modified penalty model (MPM), linear-threshold model (LTM), and modified linear-threshold model (MLTM) were used for genetic evaluation of the trait studied. The predictive ability of the models was assessed using cross-validation. The lowest mean square of error and highest r(y,y) were obtained under MLTM for AFC and under LTM for DO, indicating that MLTM and LTM are recommended for genetic evaluation of AFC and DO with censored records in Iranian Holstein cows, respectively. The prediction accuracy of the models for AFC was relatively similar, ranging from 0.46 (under LM) to 0.48 (under PM, LTM, and MLTM). For DO, prediction accuracy values ranged from 0.36 (under LM) to 0.47 (under PM and LTM). The posterior mean for heritability of AFC under MLTM was 0.11. There was no significant difference among posterior means for the heritability of AFC under different models. Therefore, LM is preferred for genetic evaluation of AFC in Iranian Holsteins, and taking censored records into account is unnecessary. The posterior mean for heritability of DO under LTM was 0.09. There were no statistically significant differences among the heritability estimates of DO under LTM, PM, and MLTM. But considering censored records for genetic evaluation of DO affects the estimation of heritability and improved model accuracy for this trait. Therefore, LTM is preferred and recommended for genetic evaluation of DO in Iranian Holsteins.

Constraint-Based, Score-Based and Hybrid Algorithms to Construct Bayesian Gene Networks in the Bovine Transcriptome.

Bayesian gene networks are powerful for modelling causal relationships and incorporating prior knowledge for making inferences about relationships. We used three algorithms to construct Bayesian gene networks around genes expressed in the bovine uterus and compared the efficacies of the algorithms. Dataset GSE33030 from the Gene Expression Omnibus (GEO) repository was analyzed using different algorithms for hub gene expression due to the effect of progesterone on bovine endometrial tissue following conception. Six different algorithms (grow-shrink, max-min parent children, tabu search, hill-climbing, max-min hill-climbing and restricted maximum) were compared in three higher categories, including constraint-based, score-based and hybrid algorithms. Gene network parameters were estimated using the bnlearn bundle, which is a Bayesian network structure learning toolbox implemented in R. The results obtained indicated the tabu search algorithm identified the highest degree between genes (390), Markov blankets (25.64), neighborhood sizes (8.76) and branching factors (4.38). The results showed that the highest number of shared hub genes (e.g., proline dehydrogenase 1 (PRODH), Sam-pointed domain containing Ets transcription factor (SPDEF), monocyte-to-macrophage differentiation associated 2 (MMD2), semaphorin 3E (SEMA3E), solute carrier family 27 member 6 (SLC27A6) and actin gamma 2 (ACTG2)) was seen between the hybrid and the constraint-based algorithms, and these genes could be recommended as central to the GSE33030 data series. Functional annotation of the hub genes in uterine tissue during progesterone treatment in the pregnancy period showed that the predicted hub genes were involved in extracellular pathways, lipid and protein metabolism, protein structure and post-translational processes. The identified hub genes obtained by the score-based algorithms had a role in 2-arachidonoylglycerol and enzyme modulation. In conclusion, different algorithms and subsequent topological parameters were used to identify hub genes to better illuminate pathways acting in response to progesterone treatment in the bovine uterus, which should help with our understanding of gene regulatory networks in complex trait expression.

In silico investigation of uncoupling protein function in avian genomes.

Introduction: The uncoupling proteins (UCPs) are involved in lipid metabolism and belong to a family of mitochondrial anionic transporters. In poultry, only one UCP homologue has been identified and experimentally shown to be associated with growth, feed conversion ratio, and abdominal fat according to its predominant expression in bird muscles. In endotherm birds, cell metabolic efficiency can be tuned by the rate of mitochondrial coupling. Thus, avUCP may be a key contributor to controlling metabolic rate during particular environmental changes. Methods: This study aimed to perform a set of in-silico investigations primarily focused on the structural, biological, and biomimetic functions of avUCP. Thereby, using in silico genome analyses among 8 avian species (chicken, turkey, swallow, manakin, sparrow, wagtail, pigeon, and mallard) and a series of bioinformatic approaches, we provide phylogenetic inference and comparative genomics of avUCPs and investigate whether sequence variation can alter coding sequence characteristics, the protein structure, and its biological features. Complementarily, a combination of literature mining and prediction approaches was also applied to predict the gene networks of avUCP to identify genes, pathways, and biological crosstalk associated with avUCP function. Results: The results showed the evolutionary alteration of UCP proteins in different avian species. Uncoupling proteins in avian species are highly conserved trans membrane proteins as seen by sequence alignment, physio-chemical parameters, and predicted protein structures. Taken together, avUCP has the potential to be considered a functional marker for the identification of cell metabolic state, thermogenesis, and oxidative stress caused by cold, heat, fasting, transfer, and other chemical stimuli stresses in birds. It can also be deduced that avUCP, in migrant or domestic birds, may increase heat stress resistance by reducing fatty acid transport/b-oxidation and thermoregulation alongside antioxidant defense mechanisms. The predicted gene network for avUCP highlighted a cluster of 21 genes involved in response to stress and 28 genes related to lipid metabolism and the proton buffering system. Finally, among 11 enriched pathways, crosstalk of 5 signaling pathways including MAPK, adipocytokine, mTOR, insulin, ErbB, and GnRH was predicted, indicating a possible combination of positive or negative feedback among pathways to regulate avUCP functions. Discussion: Genetic selection for fast-growing commercial poultry has unintentionally increased susceptibility to many kinds of oxidative stress, and so avUCP could be considered as a potential candidate gene for balancing energy expenditure and reactive oxygen species production, especially in breeding programs. In conclusion, avUCP can be introduced as a pleiotropic gene that requires the contribution of regulatory genes, hormones, pathways, and genetic crosstalk to allow its finely-tuned function.

Meta-analysis of association between c.963A>G single-nucleotide polymorphism on BMP15 gene and litter size in goats.

Litter size is an important economic trait in the goat industry. Previous studies on the bone morphogenetic protein 15 (BMP15) gene detected some single-nucleotide polymorphisms (SNPs) such as c.963A > G that were associated with an increase in ovulation rate and litter size. The aim of this study was to conduct a meta-analysis on the effect of this polymorphism on litter size. We gathered and pooled data from five eligible published studies. To investigate the effect of c.963A > G on litter size, we utilized four different genetic models assuming dominant (GG  +  GA vs. AA), recessive (GG vs. GA  +  AA), additive (GG vs. AA) and co-dominant (GG  +  AA vs. GA) model of inheritance. Data were analyzed under random-effects models based on the I 2 value. Furthermore, sensitivity analysis was carried out to validate the stability of results. The results showed that the c.963A > G polymorphism is associated with litter size when applying a dominant model (standardized mean difference (SMD) is 0.815, 95 % CI [0.170, 1.461], P  value  =  0.013) and also with an additive model (SMD  =  0.755, 95 % CI [0.111, 1.400], P  value  =  0.022). However, the effect of c.963A > G polymorphism was not significant under recessive (SMD  =  0.186, 95 % CI [ - 0.195, 4.259], P  value  =  0.339) and co-dominant (SMD  =   - 0.119, 95 % CI [ - 0.525, 0.288], P  value  =  0.568) models. Sensitivity analysis demonstrated that dropping studies with wide confidence intervals affects overall results under the assumption of an additive model. The meta-analysis results revealed that the AA genotype could be positively connected with litter size in goats.

A novel variant in the promoter region of miR-9 gene strongly affects litter size in Markhoz goats.

This study aimed to identify and evaluate the effects of single nucleotide polymorphisms (SNPs) within miR-9 and miR-27a genes and their promoters, as well as 3'UTR regions of KITLG and IGF1 genes on litter size in Markhoz goats. PCR-SSCP analysis revealed different band patterns and sequencing results confirmed four SNPs including a C/A, a A/G, a C/T and a A/G substitution located in the promoter region of miR-9 gene, 48 bp upstream of miR-9 seed region within the 3'UTR of KITLG gene, 37 bp downstream of miR-27a gene and 39 bp upstream of miR-9 seed region within the 3'UTR of IGF1 gene, respectively. The results of the least-square analyses indicated that AA genotype of miR-9 gene strongly and positively affects litter size in Markhoz goats (P < 0.01). Furthermore, the results of the logistic regression analyses confirmed that the A allele of miR-9 gene has a tremendous impact on litter size in Markhoz goats (P < 0.01). Scanning the promoter region of miR-9 gene showed that changing C allele to A may prevent HES1, HES2, NRF1 and TCFL5 transcription factors (TFs) from binding to the promoter, which can reduce the expression of miR-9 gene. Principle component analysis (PCA) showed that approximately 60% of the variation of the data set was explained by two of four SNPs. Also, the biplot from the PCA showed a strong association between litter size and C/A polymorphism of miR-9 promoter. Linkage disequilibrium analysis revealed a very slight linkage among investigated loci.

Effect of abortion on milk production, health, and reproductive performance of Holstein dairy cattle.

The objective of this study was to identify the effect of abortion on performance of Iranian Holstein cows that calved between 2005-2014. Abortion records were categorized in two groups: 1) new abortion (NLA), and 2) rebreeding abortion (RA). Production data (305-d milk, fat, and protein yields) were analyzed using PROC MIXED, number of inseminations per lactation period (INS), postpartum health disorders (PPHD), and culling records using PROC GLIMMIX, and calving to conception records using PROC PHREG of SAS software (SAS Institute, 2013). For each separate model, main herd-cow factors and all two-way significant interactions were considered in the analyses with results being reported for each calving status by lactation period. In total, 12.5 % of lactation periods were associated with at least one case of abortion, while 1.9 % of the lactation periods commenced with an abortion. Based on results from the present study, milk production decreased for cows having abortion classified as NLA or RA. Overall, when there was a RA, there was an increase in median days non-pregnant (DNP) by 132 d and INS by 1.6, whereas cows with NLA had median DNP of 15 d less and an INS of 0.17 less than cows with normal parturitions. Compared with cows with normal parturitions, cows with a NLA were 1.24, 1.88, and 2.41 times more likely to have PPHD, and be culled from the herd for involuntary reasons and reasons related to reproduction, respectively. The results of this study indicate abortions were associated with cow health and milk production and reproductive performance, indicating losses due to abortion are not only a direct result of the loss of a pregnancy.

Association between c.1189G>A single nucleotide polymorphism of GDF9 gene and litter size in goats: A meta-analysis.

Litter size is one of the most important traits in goat production and breeding. The most common and presumed single nucleotide polymorphism (SNP) detected in the Growth Differentiation Factor 9 gene is c.1189G>A (rs637044681, Ensembl) which results in an altered sequence of the encoded protein. In some studies, there was no effect of this SNP on litter size, while in other studies there was an effect. In the present study there was a meta-analysis conducted by pooling results from 11 eligible published studies to investigate effects of c.1189G>A polymorphism on litter size using four different genetic models including dominant (AA + AG compared with GG), recessive (AA compared with AG + GG), additive (AA compared with GG) and co-dominant (AA + GG compared with AG). Data were analyzed using fixed and random-effect models based on the I-squared value. Results indicate the c.1189G>A polymorphism is positively associated with litter size with use of the dominant model (SMD = 0.093, 95% CI = 0.028 to 0.158, P-Value = 0.005). There, however, was no effect of the c.1189G>A polymorphism using the recessive (SMD = 0.065, 95% CI = -0.164 to 0.295, P-Value = 0.577), additive (SMD = 0.172, 95% CI = -0.169 to 0.513, P-Value = 0.324) and co-dominant (SMD = -0.083, 95% CI = -0.200 to 0.034, P-Value = 0.164) genetic models. Results from use of the sensitivity analysis indicate the GG genotype affect litter size with use of the additive model (P < 0.01). The results from this meta-analysis indicate the GG genotype is associated with litter size in goats.

WITHDRAWN:Identification of bovine uterine transcriptomic hub genes using Bayesian network algorithms.

Ahead of Print article withdrawn by publisher.

Genetic parameters for daily milk somatic cell score and relationships with yield traits of primiparous Holstein cattle in Iran.

BACKGROUND: Despite the importance of relationships between somatic cell score (SCS) and currently selected traits (milk, fat and protein yield) of Holstein cows, there was a lack of comprehensive literature for it in Iran. Therefore we tried to examine heritabilities and relationships between these traits using a fixed-regression animal model and Bayesian inference. The data set consisted of 1,078,966 test-day observations from 146,765 primiparous daughters of 1930 sires, with calvings from 2002 to 2013. RESULTS: Marginal posterior means of heritability estimates for SCS (0.03 ± 0.002) were distinctly lower than those for milk (0.204 ± 0.006), fat (0.096 ± 0.004) and protein (0.147 ± 0.005) yields. In the case of phenotypic correlations, the relationships between production and SCS were near zero at the beginning of lactation but become increasingly negative as days in milk increased. Although all environmental correlations between production and SCS were negative (-0.177 ± 0.007, -0.165 ± 0.008 and -0.152 ± 0.007 between SCS and milk, fat, and protein yield, respectively), slightly antagonistic genetic correlations were found; with posterior mean of relationships ranging from 0.01 ± 0.039 to 0.11 ± 0.036. This genetic opposition was distinctly higher for protein than for fat. CONCLUSION: Although small, the positive genetic correlations suggest some genetic antagonism between desired increased milk production and reduced SCS (i.e., single-trait selection for increased milk production will also increase SCS).