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The fat tail is a phenotype that divides indigenous Iranian sheep genetic resources into two major groups. The objective of the present study is to refine the map location of candidate regions associated with fat deposition, obtained via two separate whole genome scans contrasting thin and fat tail breeds, and to determine the nature of the selection occurring in these regions using a hitchhiking approach. Zel (thin tail) and Lori-Bakhtiari (fat tail) breed samples that had previously been run on the Illumina Ovine 50 k BeadChip, were genotyped with a denser set of SNPs in the three candidate regions using a Sequenom Mass ARRAY platform. Statistical tests were then performed using different and complementary methods based on either site frequency (FST and Median homozygosity) or haplotype (iHS and XP-EHH). The results from candidate regions on chromosome 5 and X revealed clear evidence of selection with the derived haplotypes that was consistent with selection to near fixation for the haplotypes affecting fat tail size in the fat tail breed. An analysis of the candidate region on chromosome 7 indicated that selection differentiated the beneficial alleles between breeds and homozygosity has increased in the thin tail breed which also had the ancestral haplotype. These results enabled us to confirm the signature of selection in these regions and refine the critical intervals from 113 kb, 201 kb, and 2831 kb to 28 kb, 142 kb, and 1006 kb on chromosome 5, 7, and X respectively. These regions contain several genes associated with fat metabolism or developmental processes consisting of TCF7 and PPP2CA (OAR5), PTGDR and NID2 (OAR7), AR, EBP, CACNA1F, HSD17B10,SLC35A2, BMP15, WDR13, and RBM3 (OAR X), and each of which could potentially be the actual target of selection. The study of core haplotypes alleles in our regions of interest also supported the hypothesis that the first domesticated sheep were thin tailed, and that fat tail animals were developed later. Overall, our results provide a comprehensive assessment of how and where selection has affected the patterns of variation in candidate regions associated with fat deposition in thin and fat tail sheep breeds.

Domestication and selection significantly changed phenotypic and behavioural traits in modern domestic animals. In this study, to identify the genomic regions associated with mastitis, genomic data of German Holstein dairy cattle were analysed. The samples were genotyped using the Bovine 50 K SNP chip. For each defined healthy and sick group, 133 samples from 13,276 genotyped dairy cows were selected based on mastitis random residual effects. Grouping was done to infer selection signatures based on XP-EHH statistic. The results revealed that for the top 0.01 percentile of the obtained XP-EHH values, five genomic regions on chromosomes 8, 11, 12, 14 and 26 of the control group, and four regions on chromosomes 3, 4 (two regions) and 22 of the case group, have been under selection. Also, consideration of the top 0.1 percentile of the XP-EHH values, clarified 21 and 15 selective sweeps in the control and case group, respectively. This study identified some genomic regions containing potential candidate genes associated with resistance and susceptibility to mastitis, immune system and inflammation, milk traits, udder morphology and different types of cancers. In addition, these regions overlap with some quantitative trait loci linked to clinical mastitis, immunoglobulin levels, somatic cell score, udder traits, milk fat and protein, milk yield, milking speed and veterinary treatments. It is noteworthy that we found two regions in the healthy group (on chromosomes 12 and 14) with strong signals, which were not described previously. It is likely that future research could link these identified genomic regions to mastitis. The results of the current study contribute to the identification of causal mutations, genomic regions and genes affecting mastitis incidence in dairy cows.

Parameters such as effective population size (Ne), runs of homozygosity (ROH), and inbreeding based on ROH (FROH) can give new insight into the level of genetic diversity for the population under selection. This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (Ne), Haplotype Block Structure, and runs of homozygosity (ROHs) in several populations of cattle using SNP genotypes. In this study, that the average r2 decreased with the increasing distance of SNP pairs. A general decrease in Ne can be seen for all four populations, indicating a loss of genetic diversity. The Iranian Holstein had the lowest level of genomic inbreeding at an ROH of 1, 5, 10 Mb, while the French Holstein had the highest. The maximum number of ROH is seen at a distance of less than 1 Mb, and the lowest number of ROH is seen at a distance of 10 Mb. The number of ROH decreases with increasing distance due to the increased recombination rate. This is a concern as an increase in inbreeding leads to a reduction in the effective population size, which was also evident in the study populations.

Background Fatness related traits are economically very important in sheep production and are associated with serious diseases in humans. The fat tail is a phenotype that divides domesticated sheep into two major groups. The objective of the present study is to refine the map location of candidate regions associated with fat deposition, obtained via two separate whole genome scans contrasting thin and fat tail breeds, and to determine the nature of the selection occurring in these regions using hitchhiking approach. Results Zel (thin tail) and Lori-Bakhtiari (fat tail) breed samples that had previously been run on the Illumina Ovine 50k BeadChip, were genotyped with a denser set of SNPs in the three candidate regions using a Sequenom Mass ARRAY platform. Statistical tests were then performed using different and complementary methods based on either site frequency (FST and Median homozygosity) or haplotype (iHS and XP-EHH). Results from candidate regions on chromosome 5 and X revealed clear evidence of selection with the derived haplotypes that were consistent with selection to near fixation for the haplotypes affecting fat tail size in the fat tail breed. Analysis of the candidate region on chromosome 7 indicated that selection differentiated the beneficial alleles between breeds and homozygosity has increased in the thin tail breed which also had the ancestral haplotype. These results enabled us to confirm the signature of selection in these regions and refine the critical intervals from 113kb, 201kb and 2,831kb to 28kb, 142kb and 1,006kb on chromosome 5, 7 and X respectively. These regions contain several genes associated with fat metabolism or developmental processes consisting TCF7 and PPP2CA (OAR5), PTGDR and NID2 (OAR7), AR, EBP, CACNA1F, HSD15B, SLC35A2, BMP15, WDR13 and RBM3 (OAR X), each of which could potentially be the actual target of selection. Study of core haplotypes alleles in our regions of interest also supported the hypothesis that the first domesticated sheep were thin tailed and fat tail animals were developed later. Conclusions Our results provide a comprehensive assessment of how and where selection has affected the patterns of variation in candidate regions associated with fat deposition in thin and fat tail sheep breeds. The hitchhiking mapping approach in this study was novel in the sense that most of the exploratory genome scan studies in domestic animals have not clarified the signal from the candidate regions, probably due to the lack of suitable genomic resources.

Heat stress, especially in countries with hot climates, is a major cause of low fertility in high-producing dairy herds. Management strategies are needed to help producers improve the reproductive performance of their dairy animals under such conditions. The current study aims to evaluate the effects of pre- and post-milking insemination on the conception rate (CR) in dairy cows. The dataset included 1294 insemination records leading to pregnancy in 708 lactating Holstein dairy cows. The GLIMMIX model procedure of SAS based on the generalized linear mixed model methodology was used to analyse the results of insemination (success or failure) as a binomial distribution with the logit link function. Differences were observed in CRs between pre- and post-milking insemination. The pregnancy odds ratio (OR) for post-milking insemination relative to that for pre-milking one was estimated at 1.90 [1.23‒2.91; 95% confidence interval (CI)]. Different levels of interaction were obtained between average daily milk production and time of insemination. In the high-producing group, the pregnancy OR for the post-milking relative to that for the pre-milking insemination was estimated at 3.53 (2.00‒6.24; 95% CI). A significant interaction effect was obtained between insemination time and the temperature-humidity index. A pregnancy OR of 2.52 (1.22‒4.14; 95% CI) was recorded for the cows inseminated after milking on days with higher levels of heat and humidity stress v. the pre-milking inseminated ones. Based on the results, post-milking insemination of high-producing cows increased CRs, especially on days with high heat and humidity stress.

The objective of genome mapping is to achieve valuable insight into the connection between gene variants (genotype) and observed traits (phenotype). Part of that objective is to understand the selective forces that have operated on a population. Finding links between genotype-phenotype changes makes it possible to identify selective sweeps by patterns of genetic variation and linkage disequilibrium. Based on Illumina 50KSNP chip data, two approaches, XP-EHH (cross-population extend haplotype homozygosity) and FST (fixation index), were carried out in this research to identify selective sweeps in the genome of three Iranian local sheep breeds: Baluchi (n = 86), Lori-Bakhtiari (n = 45) and Zel (n = 45). Using both methods, 93 candidate genomic regions were identified as harboring putative selective sweeps. Bioinformatics analysis of the genomic regions showed that signatures of selection related to multiple candidate genes, such as HOXB9, HOXB13, ACAN, NPR2, TRIL, AOX1, CSF2, GHR, TNS2, SPAG8, HINT2, ALS2, AAAS, RARG, SYCP2, CAV1, PPP1R3D, PLA2G7, TTLL7 and C20orf10, that play a role in skeletal system and tail, sugar and energy metabolisms, growth, reproduction, immune and nervous system traits. Our findings indicated diverse genomic selection during the domestication of Iranian sheep breeds.

The present research aimed to characterize the Persian Kurdish horse population relative to the Persian Arabian and American Thoroughbred populations using genome-wide SNP data. Fifty-eight Kurdish, 38 Persian Arabian and 83 Thoroughbred horses were genotyped across 670,796 markers. After quality control and pruning to eliminate linkage disequilibrium between loci which resulted in 13,554 SNPs in 52 Kurdish, 24 Persian Arabian and 58 Thoroughbred horses, the Kurdish horses were generally distinguished from the Persian Arabian samples by Principal Component Analyses, cluster analyses and calculation of pairwise FST. Both Persian breeds were discriminated from the Thoroughbred. Pairwise FST between the two Persian samples (0.013) was significantly greater than zero and several fold less than those found between the Thoroughbred and Kurdish (0.052) or Thoroughbred and Persian Arabian (0.057). Cluster analysis assuming three genetic clusters assigned the Kurdish horse and Thoroughbred to distinct clusters (0.942 in cluster 2 and 0.953 in cluster 3 respectively); the Persian Arabian was not in a distinct cluster (0.519 in cluster 1), demonstrating shared ancestry or recent admixture with the Kurdish breed. Diversity as quantified by expected heterozygosity was the highest in the Kurdish horse (0.342), followed by the Persian Arabian (0.328) and the Thoroughbred (0.326). Analysis of Molecular Variance showed that 4.47% of the genetic variation was present among populations (PFIS) were not significantly different from zero in any of the populations. Analysis of individual inbreeding based on runs of homozygosity using a larger SNP set suggested greater diversity in both the Kurdish and Persian Arabian than in the Thoroughbred. These results have implications for developing conservation strategies to achieve sound breeding goals while maintaining genetic diversity.

Background Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle. Results Based on the significant-association threshold (p − 8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10− 2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10− 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs. Conclusions Our results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.

The accuracy of genotype imputation from a customized low-density to a moderate-density single-nucleotide polymorphism marker panel was tested in Italian Mediterranean buffalo using different sizes of reference populations (RP) and imputation programs. Masked genotypes were imputed using Beagle, minimac and FImpute. The accuracy of predicted genotypes was assessed by the percentage of correctly imputed genotypes. As expected, overall imputation accuracy was better for larger RP sizes. However, increasing the RP size from small to intermediate (i.e., from 42 to 202) resulted in a greater improvement in imputation accuracy compared to increasing the RP size from intermediate to large (i.e., from 202 to 736). The percentage of correctly imputed genotypes was 97.3%, 97.9% and 98.0% for minimac, Beagle and FImpute, respectively, using 736 reference individuals. The accuracy of imputation tended to decrease for high minor-allele frequency of imputed genotypes especially when the RP size was small. The variation in accuracy with increasing RP size was highest for Beagle and lowest for minimac. The accuracy of imputation was larger when the genomic relationship between the reference and the target populations was higher for all three imputation software tools used in this study. The trend of increasing imputation accuracy with genomic relationship was strongest when the RP size was small. Our results indicate that imputation of genotypes from a low to a moderate density panel (i.e., 10K to 90K) is a valid option to reduce the cost of genotyping for genomic evaluation in Italian Mediterranean buffalo.

Diacylglycerol O-acyltransferase 1 (DGAT1) plays a key role in the synthesis of triglycerides. Recent studies have shown that a transition mutation resulting in substitutions of guanine by adenine in the DGAT1 gene in cattle has considerable effects on milk yield and composition. Currently, there is no systematic research reporting on the utilization of this gene segment in Iranian buffalo (Bubalus bubalis). In this study, the genetic differentiation of three indigenous Iranian buffalo populations was investigated in the region spanning exon 3 to exon 17 of the DGAT1 gene. A total of 200 buffaloes were genotyped, all the samples were sequenced directly in both directions with forward and reverse sequencing primers. Sequence analysis showed novel SNPs compared to the reference GenBank sequence (DQ886485) at nucleotide positions g.6097A>G, g.7036C>T, g.7338G>A, g.7710C>T, g.8087C>T, g.8259G>A, g.8275G>A, g.8367C>T, and g.8426C>T. No polymorphisms were found within exon 8. Therefore, the K232A position was thought to be a conserved and fixed region for high milk fat content (K allele) in Bos indicus and all buffalo breeds. Comparison with Indian buffalo revealed three exonic SNPs, one of which was nonsynonymous. A unique 22 bp insertion was observed in intron 10 of DGAT1. Linkage disequilibrium analysis allowed the identification of nine haplotypes among the sampled animals. To our knowledge, this is the first report of sequencing analysis of the DGAT1 gene in Iranian buffalo. Our results suggest that genetic diversity exists and could be useful in examining the association between the DGAT1 gene and milk production traits in buffalo.

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

This study was performed to investigate the effect of sub-lethal exposure of bull semen to ethanol on the post-thaw spermatozoa quality. Semen samples (n=24, 6 ejaculates/bull) from 4 Holstein bulls were collected and pooled. Pooled samples were divided into 4 equal parts and each part was frozen after being diluted with Optidyl® extender containing 0 (O-E0), 0.03 (O-E3), 0.09 (O-E9) and 0.15 (O-E15) % (v/v) absolute ethanol. Sperm motility and velocity, plasma membrane integrity and functionality, mitochondrial activity, malondialdehyde concentration, and apoptosis status were evaluated after thawing. A higher percentage of total motility was observed in the O-E9 group as compared to the O-E0, O-E3 and O-E15 groups (p0.05). Also, plasma membrane integrity was higher (p0.05) in the O-E9 group compared to the O-E3, and O-E15 groups. However, the difference between the O-E9 and O-E0 groups was not significant (p0.05). In terms of the proportion of sperm abnormality and plasma membrane functionality no differences (p0.05) were observed between the groups. Our results revealed that malondialdehyde level was lower in ethanol treated (O-E3, O-E9 and O-E15) groups compared to the O-E0 group (p0.05). Furthermore, the percentage of live spermatozoa with active mitochondria was higher in the O-E9 and O-E15 groups compared to the O-E0 and O-E3 groups (p0.05). The O-E3 and O-E9 groups resulted in the highest and lowest percentage of apoptotic spermatozoa, respectively (p0.05). The results of this study demonstrate that supplementation of semen extender with sub-lethal concentration of ethanol influences post-thawed bull sperm quality in a dose dependent manner.

The body weight is an economically important trait in sheep. We performed a genomewide association study using Ovine 50 K SNP chip to identify the genes and chromosome regions associated with body weight in Baluchi sheep. A total of 96 blood samples from two herds along with data on weight at birth (BW), weaning (WW), six month (SMW) and yearling (YW) were collected. Markers were tested for association based on linear regression using the PLINK software. Thirteen different SNP markers reached 5% Bonferroni chromosome-wide significance levels. In this study we detected one SNP with genomewide significance effect on yearling weight on chromosome 8. All significant SNPs at chromosome-wide significance level were within or close to known ovine genes. The SNP at genomewide significance level was within gene SYNE1. Thus, we suggest more investigation to prove these genes as candidate genes for body weight traits in sheep. Growth traits are economically important traits for sheep. Mapping of quantitative trait loci (QTL) is an appropriate approach and provides useful information for marker assisted selection (MAS) and gene-based selection in sheep breeding strategies. Relatively few number of QTLs have been reported in sheep. The current release (February 2014) of the Sheep QTLdb (http://www.animalgenome.org/cgi-bin/ QTLdb) contains 129 QTLs for growth traits reported from a genomic study based on marker-QTL linkage analysis. QTL mapping using linkage map QTLs to large confidence intervals on the genome. As a result, use of QTL in MAS is complicated. It would be possible to exploit linkage disequilibrium (LD) to map QTL if dense markers were available. With the advent of next-generation sequencing

There is a growing interest in odd- and branched-chain fatty acids (OBCFA) in milk following reports that several branched-chain fatty acids (FA) have health promoting effects, and certain milk OBCFA could serve as a biomarker to assess ruminal function. Twenty-four Holstein cows were fed 3 low-forage diets containing 30 g/kg of dry matter of prilled palm fat (PPF), sunflower oil (SO), or an equal mixture of both fats (experiment 1) or 3 diets containing 30 g/kg of dry matter of SO with a forage-to-concentrate ratio of 39:61, 44:56, or 48:52 (Experiment 2); diets were fed to investigate milk OBCFA composition and to explore the relationships between ruminal VFA and milk OBCFA using principal component analysis. Including SO in diets decreased yields of milk 13:0 anteiso, 15:0 anteiso, 15:0, 17:0, cis-9 15:1, and cis-9 17:1 compared with PPF. The molar proportion of ruminal propionate was the lowest and the yields of milk 14:0 iso and 16:0 iso were the greatest with the diet containing both fat supplements. Replacing concentrate with forages linearly increased ruminal acetate and yields of milk 13:0 iso, 14:0 iso, 15:0 iso, 16:0 iso, 17:0 iso, 13:0 anteiso, 15:0 anteiso, 15:0, 17:0, cis-9 15:1, and cis-9 17:1. The principal component analysis revealed that ruminal molar proportion of acetate related to concentrations of milk iso FA containing

1Department of Animal Science, Laboratory for Molecular Genetics Animal Biotechnology, Faculty of Animal and Aquatic Science, Sari Agricultural Sciences and Natural Resources University, Sari, Iran 2Department of Animal Sciences, Faculty of Agronomy Sciences, College of Agriculture Natural Resources, University of Tehran, Karaj, Iran 3Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07 Uppsala, Sweden

Summary The aim of this study was to separate marked additive genetic variability for three quantitative traits in chickens into components associated with classes of minor allele frequency (MAF), individual chromosomes and marker density using the genomewide complex trait analysis (GCTA) approach. Data were from 1351 chickens measured for body weight (BW), ultrasound of breast muscle (BM) and hen house egg production (HHP), each bird with 354 364 SNP genotypes. Estimates of variance components show that SNPs on commercially available genotyping chips marked a large amount of genetic variability for all three traits. The estimated proportion of total variation tagged by all autosomal SNPs was 0.30 (SE 0.04) for BW, 0.33 (SE 0.04) for BM, and 0.19 (SE 0.05) for HHP. We found that a substantial proportion of this variation was explained by low frequency variants (MAF

The objective of this study was to estimate effects of SNP-genotypes on clinical mastitis, somatic cell score (SCS) and on estimated breeding values (EBV) for production traits in Holstein dairy cattle based on selective genotyping methodology. For identification of SNPs, we focused on candidate genes for clinical mastitis. The data set was comprised of a total of 3823 Holstein cows from two Holstein contract herds located in two regions in Iran. Data included 305-d lactation records for the production traits milk yield, fat yield, protein yield, fat percentage, protein percentage, SCC, and the no. of cases of clinical mastitis per lactation. Selection of cows for selective genotyping was based on extreme values for clinical mastitis residuals (CMR) from mixed model analyses. Two extreme groups of 135 cows each were genotyped for two loci of both candidate genes for mastitis TLR4 [=TLR4(1) and TLR4(2)] and CACNA2D1 [=CACNA2D1(1) and CACNA2D1(2)] using PCR-SSCP or PCR-RFLP . Associations between SNP-genotypes and traits of interest were estimated by applying logistic regression analyses, i.e. estimating the probability of the heterogeneous genotype in dependency of the EBVs and of values for CMR. The heterozygous genotype was contrasted to both homozygous genotypes allowing the estimation of effects for dominance. Allele G of TLR4(1) was associated with fewer cases for CM, and showed desired effects in production traits, e.g. higher milk yield and protein yield, and lower values for CMR. Also allele G of CACNA2D1(2) was predominant in the resistant group, and favorably associated with milk yield. Those SNPs are interesting for breeding, because they simultaneously improve both antagonistic traits. Effects of dominance ranged from 0.05 SD to 0.13 SD for the production trait (milk yield), and from 0.04 to 0.19 SD the functional trait (CMR).

Background Genome sequencing and subsequent gene annotation of genomes has led to the elucidation of many genes, but in vertebrates the actual number of protein coding genes are very consistent across species (~20,000). Seven years after sequencing the cattle genome, there are still genes that have limited annotation and the function of many genes are still not understood, or partly understood at best. Based on the assumption that genes with similar patterns of expression across a vast array of tissues and experimental conditions are likely to encode proteins with related functions or participate within a given pathway, we constructed a genome-wide Cattle Gene Co-expression Network (CGCN) using 72 microarray datasets that contained a total of 1470 Affymetrix Genechip Bovine Genome Arrays that were retrieved from either NCBI GEO or EBI ArrayExpress. Results The total of 16,607 probe sets, which represented 11,397 genes, with unique Entrez ID were consolidated into 32 co-expression modules that contained between 29 and 2569 probe sets. All of the identified modules showed strong functional enrichment for gene ontology (GO) terms and Reactome pathways. For example, modules with important biological functions such as response to virus, response to bacteria, energy metabolism, cell signaling and cell cycle have been identified. Moreover, gene co-expression networks using “guilt-by-association” principle have been used to predict the potential function of 132 genes with no functional annotation. Four unknown Hub genes were identified in modules highly enriched for GO terms related to leukocyte activation (LOC509513), RNA processing (LOC100848208), nucleic acid metabolic process (LOC100850151) and organic-acid metabolic process (MGC137211). Such highly connected genes should be investigated more closely as they likely to have key regulatory roles. Conclusions We have demonstrated that the CGCN and its corresponding regulons provides rich information for experimental biologists to design experiments, interpret experimental results, and develop novel hypothesis on gene function in this poorly annotated genome. The network is publicly accessible at http://www.animalgenome.org/cgi-bin/host/reecylab/d. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3176-2) contains supplementary material, which is available to authorized users.

Background Weighted Gene Co-expression Network analysis, a powerful technique used to extract co-expressed gene pattern from mRNA expression data, was constructed to infer common immune strategies used by cattle in response to five different bacterial species (Escherichia coli, Mycobacterium avium, Mycobacterium bovis, Salmonella and Staphylococcus aureus) and a protozoa (Trypanosoma Congolense) using 604 publicly available gene expression microarrays from 12 cattle infection experiments. Results A total of 14,999 transcripts that were differentially expressed (DE) in at least three different infection experiments were consolidated into 15 modules that contained between 43 and 4441 transcripts. The high number of shared DE transcripts between the different types of infections indicated that there were potentially common immune strategies used in response to these infections. The number of transcripts in the identified modules varied in response to different infections. Fourteen modules showed a strong functional enrichment for specific GO/pathway terms related to “immune system process” (71%), “metabolic process” (71%), “growth and developmental process” (64%) and “signaling pathways” (50%), which demonstrated the close interconnection between these biological pathways in response to different infections. The largest module in the network had several over-represented GO/pathway terms related to different aspects of lipid metabolism and genes in this module were down-regulated for the most part during various infections. Significant negative correlations between this module’s eigengene values, three immune related modules in the network, and close interconnection between their hub genes, might indicate the potential co-regulation of these modules during different infections in bovine. In addition, the potential function of 93 genes with no functional annotation was inferred based on neighbor analysis and functional uniformity among associated genes. Several hypothetical genes were differentially expressed during experimental infections, which might indicate their important role in cattle response to different infections. Conclusions We identified several biological pathways involved in immune response to different infections in cattle. These findings provide rich information for experimental biologists to design experiments, interpret experimental results, and develop novel hypothesis on immune response to different infections in cattle. Electronic supplementary material The online version of this article (10.1186/s12865-017-0238-4) contains supplementary material, which is available to authorized users.

Genetic and non-genetic parameters were estimated for early growth traits of Iranian Baluchi lambs using univariate and multivariate models. The investigated traits were: birth weight (BWT), weaning weight (WWT), 6-month weight (6MW) and pre-weaning average daily gain (ADG). Data and pedigree information used in this research were collected at the Abbasabad Sheep Breeding Station during a period between 1973 and 2003 on 15,568 lambs descended from 326 sires and 4737 dams. Twelve models including different combination of direct and maternal effects (additive genetic, permanent environmental and common environmental) as well as additive genetic relationship between direct and maternal effects were used to analyze data. For each trait, the most appropriate model was chosen based on likelihood ratio tests. In addition, multivariate analysis was performed using the most appropriate models obtained in univariate analysis. Based on the most appropriate fitted models, estimates of direct heritabilities were 0.12 ± 0.02, 0.10 ± 0.02, 0.06 ± 0.01 and 0.09 ± 0.02 for BWT, WWT, 6MW and ADG, respectively. Estimates of maternal additive genetic and maternal permanent environmental variances, as a proportion of phenotypic variance (m 2 and pe 2 , respectively) were 0.08 ± 0.02 and 0.08 ± 0.01 for BWT, 0.04 ± 0.01 and 0.09 ± 0.01 for WWT, 0.03 ± 0.01 and 0.03 ± 0.01 for 6MW, and, 0.01 ± 0.01 and 0.08 ± 0.01 for ADG, respectively. Maternal common environmental component was significant only on BWT and was estimated to be 0.19 ± 0.02. The estimate of maternal common environmental variances as a proportion of phenotypic variance (c 2 ) was significant only for BWT (0.19 ± 0.02). Direct genetic correlations among studied traits were positive and ranged from 0.37 (BWT–6MW) to 0.98 (WWT–ADG). Maternal genetic correlation estimates between studied traits were positive varying from 0.11 (BWT–ADG) to 0.64 (ADG–6MW). The estimates of phenotypic and environmental correlations were positive and generally lower than those of genetic correlations. Results indicated that besides direct genetic effects, maternal effects should be included in the statistical model to obtain accurate estimates of genetic parameters for early growth traits.

Native chicken breeding station of Mazandaran was established in 1988 with two main objectives: genetic improvement through selection programs and dissemination of indigenous Mazandarani birds. (Co)variance components and genetic parameters for economically important traits were estimated using (bi) univariate animal models with ASREML procedure in Mazandarani native chicken. The data were from 18 generations of selection (1988-2009). Heritability estimates for body weight at different ages [at hatch (bw1), 8 (bw8), 12 (bw12) weeks of ages and sex maturation (wsm)] ranged from 0.24 ± 0.00 to 0.47 ± 0.01. Heritability for reproductive traits including age at sex maturation (asm); egg number (en); weight of first egg (ew1); average egg weight at 28 (ew28), 30 (ew30), and 32 (ew32) weeks of age; their averages (av); average egg weight for the first 12 weeks of production (ew12); egg mass (em); and egg intensity (eint) varied from 0.16 ± 0.01 to 0.43 ± 0.01. Generally, the magnitudes of heritability for the investigated traits were moderate. However, egg production traits showed smaller heritability compared with growth traits. Genetic correlations among egg weight at different ages were mostly higher than 0.8. On the one hand, body weight at different ages showed positive and relatively moderate genetic correlations with egg weight traits (ew1, ew28, ew30, ew32, ew12, and av) and varied from 0.30 ± 0.03 to 0.59 ± 0.02. On the other hand, low negative genetic correlations were obtained between body weight traits (bw1, bw8, bw12, and wsm) and egg number (en). Also, there is low negative genetic correlation (-24 ± 0.04 to -29 ± 0.05) between egg number and egg weight. Therefore, during simultaneous selection process for both growth and egg production traits, probable reduction in egg production due to low reduction in egg number may be compensated by increases in egg weight.

Embryo transfer is a reproductive technique that has a major impact on the dissemination of economically important genes and the rate of genetic gain in breeding schemes. In recent years, there has been increasing interest in the use of sexed and genotyped embryos in commercial embryo transfer programs. Marker/gene assisted selection (MAS/GAS) projects can be performed in the pre-implantation stage through mass production of characterized embryos. Biopsy of a few cells in the morulla stage is essential for pre-implantation genetic diagnosis (PGD), in which sex determination, evaluation of disease genes, and genotyping for candidate genes are performed. Limited quantity of cells and low amount of DNA restrict the use of multiple molecular analyses in PGD programs. Recently, whole genome amplification (WGA) techniques promise to overcome this problem by providing sufficient input DNA for analysis. Among several techniques proposed for WGA, the primer extension pre-amplification (PEP) and the improved-primer extension pre-amplification (I-PEP) methods are the most commonly used. However, these methods are time-consuming and need more than 12 h amplification cycles. Since the time is a critical parameter in the successful characterized embryo transfer, the shortening of diagnosis time is highly desirable. In this study, we developed a short and simple I-PEP procedure (~3 h) and evaluated its performance for the amplification of bovine genomic DNA. We assessed short WGA procedure by polymerase chain reaction (PCR) amplification of 7 specific loci. The results indicated that the short procedure possesses enough sensitivity for the molecular genetic analysis of 1 input cell. Although the efficiency of the method was 100%, there was an inconsistency between genomic DNA (gDNA) and whole genome amplification product (wgaDNA) genotypes for kappa-casein locus; that is, however, most likely due to allele drop-out (ADO) or false homozigocity. The results of this study indicate that with the application of reliable methods, WGA-amplified bovine DNA will be a useful source for sexing and genotyping bovine embryos in several quantitative trait locus (QTL) markers.

The objectives of this study were to quantify the errors in economic values (EVs) for traits affected by cost or price thresholds when skewed or kurtotic distributions of varying degree are assumed to be normal and when data with a normal distribution is subject to censoring. EVs were estimated for a continuous trait with dichotomous economic implications because of a price premium or penalty arising from a threshold ranging between -4 and 4 standard deviations from the mean. In order to evaluate the impacts of skewness, positive and negative excess kurtosis, standard skew normal, Pearson and the raised cosine distributions were used, respectively. For the various evaluable levels of skewness and kurtosis, the results showed that EVs can be underestimated or overestimated by more than 100% when price determining thresholds fall within a range from the mean that might be expected in practice. Estimates of EVs were very sensitive to censoring or missing data. In contrast to practical genetic evaluation, economic evaluation is very sensitive to lack of normality and missing data. Although in some special situations, the presence of multiple thresholds may attenuate the combined effect of errors at each threshold point, in practical situations there is a tendency for a few key thresholds to dominate the EV, and there are many situations where errors could be compounded across multiple thresholds. In the development of breeding objectives for non-normal continuous traits influenced by value thresholds, it is necessary to select a transformation that will resolve problems of non-normality or consider alternative methods that are less sensitive to non-normality.

An experiment was conducted to investigate the effect of short-term selection for 4 week breast weight (4wk BRW), and to estimate genetic parameters of body weight, and carcass traits. A selection (S) line and control (C) line was randomly selected from a base population. Data were collected over two consecutive hatches for four generations. A total of 1 135 records from 156 sires and 218 dams were used to estimate the genetic parameters. The genetic improvement of 4wk BRW was 3.5, 2.7 and 0.6 g in generation 2, 3 and 4, respectively. The estimated heritability by using pedigree information was 0.35±0.06. There were a significant difference for BW, and carcass weights but not for carcass percent components between lines (P

A stochastic bio-economic model has been used to determine the effects of new reproductive technologies over a 15-year period. A strategy of using conventional artificial insemination (AI) or embryo transfer (ET) using two sex-controlled embryos at different conception rates (CRs) and herd sizes resulted in a 24 state model. The genetic means of AI population increased over the years, and the genetic means of milk production for all of the embryo strategies were greater than those of AI. In addition, the genetic means of milk yield using different embryo-based scenarios in the expanding herds were greater than those for the fixed herds. The net profit of using sexed ET in the expanding herds was greater (P < 0.05) than that of fixed size herds. In general, there was a roughly consistent trend in net profit per cow for sexed ET strategies in the expanding herds over the years, but there was an increasing trend in net profit per cow for sexed ET strategies in the fixed herds over the years. Medium to high CRs for ET and the use of sex-controlled embryo systems, especially for induction of twin births to produce dairy replacements, will be critical elements of a system that produces significant numbers of female calves. The greater number of female calves produced in the sex-controlled scenarios allows the farmer to select animals with the best genetic potential as dairy replacement heifers; therefore, the rate of genetic gain increased in the dairy herd. Results of sensitivity analyses showed that a significant decrease in the production costs and increase in the ET performance are essential for embryo-based technologies to be profitable.

The objective of this study was to develop a method for calculating economic values of clinical mastitis (CM) and somatic cell score (SCS) for inclusion in a dairy cattle breeding goal in the context of a country where farm production and economic data are scarce. In order to calculate the costs and derive economic values for SCS, a new model, 'milk collection method', has been developed and was compared with the Meijering model with individual and average SCS distributions. For the population, estimated economic values using the milk collection method were 1.3 and 2.4 times higher than those of Meijering method with average and individual SCS, respectively. The milk collection method needs no assumptions about normality of the distribution of SCS and because of a lack of normality in Iranian data for SCS, the Meijering method resulted in economic values that were biased downwards. Failing to account for the fact that milk price penalties for SCS are applied at milk collection rather than individual cow level resulted in a further large downward bias in the economic value of SCS. When the distribution of data is unknown or difficult to approximate or when a transformation to normality is not straightforward, the milk collection method would be preferable. Inclusion of SCS and CM in the breeding goal for Iranian dairy cattle is justified based on these results. The model to calculate mastitis costs proposed here could be used to estimate economic values for CM in other developing countries where farm production and economic data are generally poor.

A stochastic bio-economic model was used to determine the effects of applying artificial insemination (AI) with conventional or sexed semen at different conception rates and herd sizes on the genetic progress of productive trait and net profit over a 15-year period. The genetic means of the cattle population was predicted to increase over the years and the rate of genetic progress in the population program using sexed semen was significantly greater than the rate of progress in the population using conventional semen. The theoretical genetic gain was greater than the realized genetic gain for milk yield for all the AI scenarios. In addition, the genetic means for milk yield in the expanding herds were greater than in the fixed sized herds. The trend in net profit generated by using AI strategies with conventional semen over the time horizon was greater when herds were expanding (P < 0.01). The trend in net profit for fixed sized herds was generally negative, however, expanding herds experienced positive net profits over the years. Also, the net profit of using AI strategies with sexed semen was greater when dairy herds were expanding. On the other hand, the net profit of using AI with sexed semen was greater than that of AI with conventional semen at the end of the time horizon. The results of sensitivity analyses indicated that a 20% increase or decrease in milk sales income and feed costs have significantly modified the net profit of AI strategies using either sexed or conventional semen.

The objectives of this study were to estimate economic values (EVs) for three production traits (milk, fat and protein yields) and longevity and to develop a national selection index. The proposed Iranian selection index was compared with selection indices of three other countries in the world. A simple and appropriate model was used to describe the Holstein dairy cattle industry under an Iranian production system. Production parameters and economic data were collected from two Holstein dairy farms in Tehran province. The EVs were estimated at farm level for three breeding perspectives (maximized profit, minimized costs, and economic efficiency) and two restrictions in production system (fixed herd size and fixed total input). The average absolute EVs on profit perspective and herd size restriction for milk, fat, and protein yields (based on $/kg) and longevity ($/month) were 0.11, 0.89, -0.20, and 6.20, respectively. The average absolute EVs under minimized costs per unit of product interest for milk, fat, protein yields and longevity were -0.30, -3.43, 0.88 and -20.40, respectively. The average absolute EVs under maximized economic efficiency for milk, fat and protein yields and longevity were 0.34, 2.73, -0.99 and 36.33, respectively. Relative emphasis for three production traits and longevity were 59.7, 14.3, -3.0 and 23.1, respectively. The comparison of the proposed Iranian index with those countries where most of the semen and embryos are imported points out that developing a national selection index to improve cow profitability and optimum generic trends is necessary. Sensitivity analysis indicated that the influence of milk payment changes on EVs was the greatest as its influence on fat and protein EVs is substantial. EVs for milk and fat yields, with respect to price changes (milk, feed and non-feed), were the least sensitive and most sensitive, respectively.

Functional analysis of the red module. Over-represented GO/pathway terms were grouped based on kappa statistics. The size of each category within a pie chart represents the number of included terms. Only the most significant GO/terms within groups were labeled. GO/pathway terms are represented as nodes, and the node size represents the term enrichment significance, while the edges represent significant similarity between categories. (A) Representative biological processes interactions among module genes. (B) Representative molecular function interactions among module genes. (C) Representative Ractome analysis interactions among module genes. (PDF 2606Â kb)

(A) Frequency of combined interaction scores from the String database [21] and (B) Frequency of TOM connectivity in BGCN. (PDF 648Â kb)

Functional analysis of the light green module genes. Over-represented GO/pathway terms were grouped based on kappa statistics. The size of each category within a pie chart represents the number of included terms. Only the most significant GO/terms within groups were labeled. GO/pathway terms are represented as nodes, and the node size represents the term enrichment significance, while the edges represent significant similarity between categories. (A) Representative biological processes interactions among module genes. (B) Representative molecular function interactions among module genes. (C) Representative Ractome analysis interactions among module genes. (PDF 2605Â kb)

Functional analysis of the red module genes. Over-represented GO/pathway terms were grouped based on kappa statistics. The size of each category within a pie chart represents the number of included terms. Only the most significant GO/terms within groups were labeled. GO/pathway terms are represented as nodes, and the node size represents the term enrichment significance, while the edges represent significant similarity between categories. (A) Representative biological processes interactions among module genes. (B) Representative molecular function interactions among module genes. (C) Representative Ractome analysis interactions among module genes. (PDF 3753Â kb)

In this study, direct and maternal heritabilities were estimated for growth traits and carcass characteristics in Lori-Bakhtiari sheep. Data for birth weight (BW; n=5826), weaning weight (WW; n=5408), body weight at six months of age (6MW; n=4237), body weight at slaughter (SW; n=396), cold carcass weight (CCW; n=291), lean weight (LW; n=204), bone weight (WB; n=291), fat weight (WF; n=204) and fat-tail weight (FTW; n=396) were used to estimate the heritabilities. The data for first three traits had been collected during seventeen years, 1990 to 2006, while for other traits had been collected during six years, 2000 to 2006. Genetic parameters including both direct and maternal genetic effects were estimated using multivariate animal models, and a Derivative Free Restricted Maximum Likelihood (DFREML) approach. The direct heritability for BW, WW, 6MW, SW, CCW, LW, WB, WF and FTW were 0.30 ? 0.03, 0.13 ? 0.03, 0.20 ? 0.03, 0.24 ? 0.06, 0.16 ? 0.06, 0.16 ? 0.06, 0.20 ? 0.11, 0.23 ? 0.11, and 0.27 ? 0.11, respectively. Maternal heritability estimates were 0.22, 0.17, 0.06, 0.10, 0.09, 0.15, 0.26, 0.06 and 0.07 for BW, WW, 6MW, SW, CCW, LW, WB, WF and FTW, respectively. Consequently, genetic progress is possible for growth traits and carcass composition by selection.

Genetic profiles of Iranian Holstein young bulls at the national artificial insemination station were determined on the basis of individual genotypes at 13 ISAG's recommended microsatellites, the most useful markers of choice for parentage identification. In the present study a total of 119 individuals were genotyped at 13 microsatellite loci and for possible parent-offspring combinations. A high level of genetic variation was evident within the investigated individuals as assessed from various genetic diversity measures. The mean number of observed alleles per microsatellite marker was 9.15 and the number of effective alleles as usual was less than the observed values (4.03). The average observed and expected heterozygosity values were 0.612 and 0.898, respectively. The mean polymorphic information content (PIC) value (0.694) further reflected a high level of genetic variability. The average exclusion of probability (PE) of the 13 markers was 0.520, ranging from 0.389 to 0.788. The combined exclusion of probability was 0.999, when 13 microsatellite loci were used for analysis in the individual identification system. Inbreeding was calculated as the difference between observed and expected heterozygosity. Observed homozygosity was less than expected which reflects inbreeding of -3.7% indicating that there are genetic differences between bull-sires and bull-dams used to produce young bulls. The results obtained from this study demonstrate that the microsatellite DNA markers used in the present DNA typing are useful and sufficient for individual identification and parentage verification without accurate pedigree information. (Asian-Aust. J. Anim. Sci. 2006. Vol 19, No. 4 : 463-467)

Different fertility indices were constructed for improving fertility performance in Iranian Holstein dairy cows. Number of inseminations per conception and days from calving to first insemination, each weighted by its economic value, were included as breeding goals in the aggregate genotype definition. Different fertility indices (FI) were constructed with different combinations of available fertility traits number of inseminations to conception (INS), days from calving to first service (DFS), interval between first and last insemination (IFL), and days open (DO). The fertility index (FI1) that included INS and DFS had the greatest genetic gain for INS (−0.39 insemination), DFS (−7.47 days), and profit ($4.3) per generation. Genetic gain for profit, DFS, and INS including only DO showed slight differences regarding FI1. A selection index that included only INS (DFS) presented the larger (smaller) genetic gains for INS and smaller (larger) for DFS, which were −0.40 (−0.034) and −0.975 (−11.18) inseminations and days, respectively. The result of this study showed that recording INS and DFS are preferable traits for including in a fertility subindex. DO can be used in the absence of other fertility traits. © 2014, Springer Science+Business Media Dordrecht.

The genetic architecture of a quantitative trait refers to the number of genetic variants, allele frequencies, and effect sizes of variants that affect a trait and their mode of gene action. This study was conducted to investigate the effect of four shapes of allelic frequency distributions (constant, uniform, L-shaped and U-shaped) and different number of trait-affecting loci (50, 100, 200, 500) on allelic frequency changes, long term genetic response, and maintaining genetic variance. To this end, a population of 440 individuals composed of 40 males and 400 females as well as a genome of 200 cM consisting of two chromosomes and with a mutation rate of 2.5 × 10(-5) per locus was simulated. Selection of superior animals was done using best linear unbiased prediction (BLUP) with assumption of infinitesimal model. Selection intensity was constant over 30 generations of selection. The highest genetic progress obtained when the allelic frequency had L-shaped distribution and number of trait-affecting loci was high (500). Although quantitative genetic theories predict the extinction of genetic variance due to artificial selection in long time, our results showed that under L- and U-shapped allelic frequency distributions, the additive genetic variance is persistent after 30 generations of selection. Further, presence or absence of selection limit can be an indication of low (50) or high (100) number of trait-affecting loci, respectively. It was concluded that the genetic architecture of complex traits is an important subject which should be considered in studies concerning long-term response to selection.

On the basis of the potential benefits to human health there is an increased interest in producing milk containing lower-saturated fatty acid (SFA) and higher unsaturated fatty acid (FA) concentrations, including cis-9 18:1 and cis-9, trans-11-conjugated linoleic acid (CLA). Twenty-four multiparous Holstein cows were used in two experiments according to a completely randomized block design, with 21-day periods to examine the effects of incremental replacement of prilled palm fat (PALM) with sunflower oil (SFO) in high-concentrate diets containing 30 g/kg dry matter (DM) of supplemental fat (Experiment 1) or increases in the forage-to-concentrate (F : C) ratio from 39 : 61 to 48 : 52 of diets containing 30 g/kg DM of SFO (Experiment 2) on milk production, digestibility and milk FA composition. Replacing PALM with SFO had no effect on DM intake, but tended to increase organic matter digestibility, yields of milk, protein and lactose, and decreased linearly milk fat content. Substituting SFO for PALM decreased linearly milk fat 8:0 to 16:0 and cis-9 16:1, and increased linearly 18:0, cis-9 18:1, trans-18:1 (��4 to 16), 18:2 and CLA concentrations. Increases in the F : C ratio of diets containing SFO had no effect on intake, yields of milk, milk protein or milk lactose, lowered milk protein content in a quadratic manner, and increased linearly NDF digestion and milk fat secretion. Replacing concentrates with forages in diets containing SFO increased milk fat 4:0 to 10:0 concentrations in a linear or quadratic manner, decreased linearly cis-9 16:1, trans-6 to -10 18:1, 18:2n-6, trans-7, cis-9 CLA, trans-9, cis-11 CLA and trans-10, cis-12 CLA, without altering milk fat 14:0 to 16:0, trans-11 18:1, cis-9, trans-11 CLA or 18:3n-3 concentrations. In conclusion, replacing prilled palm fat on with SFO in high-concentrate diets had no adverse effects on intake or milk production, other than decreasing milk fat content, but lowered milk fat medium-chain SFA and increased trans FA and polyunsaturated FA concentrations. Increases in the proportion of forage in diets containing SFO increased milk fat synthesis, elevated short-chain SFA and lowered trans FA concentrations, without altering milk polyunsaturated FA content. Changes in fat yield on high-concentrate diets containing SFO varied between experiments and individual animals, with decreases in milk fat secretion being associated with increases in milk fat trans-10 18:1, trans-10, cis-12 CLA and trans-9, cis-11 CLA concentrations.

Summary The objective was to assess goodness of fit and predictive ability of subsets of single nucleotide polymorphism (SNP) markers constructed based on minor allele frequency (MAF), effect sizes and varying marker density. Target traits were body weight (BW), ultrasound measurement of breast muscle (BM) and hen house egg production (HHP) in broiler chickens. We used a 600 K Affymetrix platform with 1352 birds genotyped. The prediction method was genomic best linear unbiased prediction (GBLUP) with 354 564 single nucleotide polymorphisms (SNPs) used to derive a genomic relationship matrix (G). Predictive ability was assessed as the correlation between predicted genomic values and corrected phenotypes from a threefold cross-validation. Predictive ability was 0.27 � 0.002 for BW, 0.33 � 0.001 for BM and 0.20 � 0.002 for HHP. For the three traits studied, predictive ability decreased when SNPs with a higher MAF were used to construct G. Selection of the 20% SNPs with the largest absolute effect sizes induced a predictive ability equal to that from fitting all markers together. When density of markers increased from 5 K to 20 K, predictive ability enhanced slightly. These results provide evidence that designing a low-density chip using low-frequency markers with large effect sizes may be useful for commercial usage.

Three machine learning algorithms: Random Forests (RF), Boosting and Support Vector Machines (SVM) as well as Genomic Best Linear Unbiased Prediction (GBLUP) were used to predict genomic breeding values (GBV) and their predictive performance was compared in different combinations of heritability (0.1, 0.3, and 0.5), number of quantitative trait loci (QTL) (100, 1000) and distribution of QTL effects (normal, uniform and gamma). To this end, a genome comprised of five chromosomes, one Morgan each, was simulated on which 10000 bi-allelic single nucleotide polymorphisms were distributed. Pearson’s correlation between the true and predicted GBV and Mean Squared Error of GBV prediction were used, respectively, as measures of the predictive accuracy and the overall fit achieved with each method. In all methods, an increase in accuracy of prediction was seen following increase in heritability and decrease in the number of QTL. GBLUP had better predictive accuracy than machine learning methods in particular in the scenarios of higher number of QTL and normal and uniform distributions of QTL effects; though in most cases, the differences were non-significant. In the scenarios of small number of QTL and gamma distribution of QTL effects, Boosting outperformed other methods. Regarding Mean Squared Error of GBV prediction, in most cases Boosting outperformed other methods, although the estimates were close to that of GBLUP. Among methods studied, SVM with 0.6 gigabytes (GIG) was the most efficient user of memory followed by RF, GBLUP and Boosting with 1.2-GIG, 1.3-GIG and 2.3-GIG memory requirements, respectively. Regarding computational time, GBLUP, SVM, RF and Boosting ranked first, second, third and last with 10 min, 15 min, 75 min and 600 min, respectively. It was concluded that although stochastic gradient Boosting can predict GBV with high prediction accuracy, significantly longer computational time and memory requirement can be a serious limitation for this algorithm. Therefore, using of other variants of Boosting such as Random Boosting was recommended for genomic evaluation.

Efficient reproductive performance is an important prerequisite for sustainable dairy production systems. Moreover, reproductive performance has become one of the most important functional traits in the dairy cattle industry, because of its economic importance, as well as its effect on animal welfare. The objective of present study was to evaluate the consequence of alternative selection strategies to improve fertility performance of Holstein cows in Iran. The traits milk production (. M), number of inseminations per conception (INS), days from calving to first insemination (DFS), maternal calving difficulty (MCD) and direct calving difficulty (DCD) were included in an aggregate genotype (. H). The selection indices in each strategy were a different combination of fertility traits and milk production. Although fertility traits were included in the aggregate genotype, in the first selection strategy, in which selection was based on milk production, unfavorable genetic gain for fertility traits occurred. In the second strategy, in which genetic gain for milk production was restricted to zero, in comparison to the other strategies, the genetic gains for profit and fertility traits were lowest and highest, respectively. In the third strategy, in which genetic gain for fertility traits was restricted to zero, the genetic gains for milk production and profit differed little compared to the first strategy. Favorable genetic gains were obtained for both fertility traits and milk production in the fourth strategy, in which proportional restriction was used. Although the genetic gain for milk production in this strategy was lower than in the first strategy, genetic gain for profit showed slightly differed. © 2012 Elsevier B.V.

Neuropeptide Y (NPY) and gonadotrophin-releasing hormone receptor (GnRHR) are two candidate genes with a wide variety of physiological functions in growth and especially in reproduction processes. We examined the association of one SNP from each of these genes with growth- and egg production-related traits in Mazandaran native chickens. Two hundred and six individuals were genotyped by PCR-RFLP. Marker-trait association analyses were performed using both breeding value and phenotypic information. The data came from 18 successive generations of selection at a Mazandaran native chicken breeding station in Iran. Data were analyzed with a univariate animal model in an ASREML procedure to estimate breeding values of the birds for these traits. Two alleles were found for both genes, A and a alleles for GnRHR, with frequencies of 0.614 and 0.386, B and b alleles for NPY, with frequencies of 0.780 and 0.221, respectively. The additive genetic effects of the GnRHR gene on egg number and egg mass were significant. Also, body weight at sexual maturity was significantly influenced by the NPY gene. We conclude that GnRHR and NPY genes are associated with egg production and growth traits, respectively.