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Crossbreeding is a widely adopted practice in the livestock industry, leveraging the advantages of heterosis and breed complementarity. The prediction of Crossbred Performance (CP) often relies on Purebred Performance (PB) due to limited crossbred data availability. However, the effective selection of purebred parents for enhancing CP depends on non-additive genetic effects and environmental factors. These factors are encapsulated in the genetic correlation between crossbred and purebred populations (rpc). In this study, a two-way crossbreeding simulation was employed to investigate various strategies for integrating data from purebred and crossbred populations. The goal was to identify optimal models that maximize CP across different levels of rpc. Different scenarios involving the selection of genotyped individuals from purebred and crossbred populations were explored using ssGBLUP (single-step Genomic Best Linear Unbiased Prediction) and ssGBLUP-MF (ssGBLUP with metafounders) models. The findings revealed an increase in prediction accuracy across all scenarios as rpc values increased. Notably, in the scenario incorporating genotypes from both purebred parent breeds and their crossbreds, both ssGBLUP and ssGBLUP-MF models exhibited nearly identical predictive accuracy. This scenario achieved maximum accuracy when rpc was less than 0.5. However, at rpc = 0.8, ssGBLUP, which exclusively included sire breed genotypes in the training set, achieved the highest overall prediction accuracy at 73.2%. In comparison, the BLUP-UPG (BLUP with unknown parent group) model demonstrated lower accuracy than ssGBLUP and ssGBLUP-MF across all rpc levels. Although ssGBLUP and ssGBLUP-MF did not demonstrate a definitive trend in their respective scenarios, the prediction ability for CP increased when incorporating both crossbred and purebred population genotypes at lower levels of rpc. Furthermore, when rpc was high, utilizing paternal genotype for CP predictions emerged as the most effective strategy. Predicted dispersion remained relatively similar in all scenarios, indicating a slight underestimation of breeding values. Overall, the rpc value emerged as a critical factor in predicting CP based on purebred data. However, the optimal model to maximize CP depends on the factors influencing rpc. Consequently, ongoing research aims to develop models that optimize purebred selection, further enhancing CP.

The aim of this study was to investigate the body shape and morphological comparison between the populations of wild (marine) and farmed common carp using geometric morphology. For this purpose, 65 pieces of fish including 23 wild common carp and 42 farmed common carp were sampled. The samples were then photographed and 16 landmarks were identified on the images. Procrast analysis was used in order to remove the amorphous data from coordinate landmarks. Principal component analysis (PCA) and discriminant function analysis (DFA) tests were used. The results showed that the two populations of wild and farmed common carp are completely separated from each other using PCA and the first three components accounted for about 64.41% of the total changes. Based on DFA for morphometric characteristics, individuals were correctly placed in their original population. The results of this study showed a significant difference in body depth and body width of wild and farmed common carp using geometric morphometric method, so that the farmed common carp had deeper body (related to the displacement of landmarks 5 and 12), a wider body (related to the displacement of landmarks 5,6,10,11 and 12) and also a shorter tail stem (related to the displacement of landmarks 6, 7, 9 and 10) than wild common carp.

When individuals are paralyzed from injury or damage to the brain, upper body movement and function can be compromised. While the use of body motions to interface with machines has shown to be an effective noninvasive strategy to provide movement assistance and to promote physical rehabilitation, learning to use such interfaces to control complex machines is not well understood. In a five session study, we demonstrate that a subset of an uninjured population is able to learn and improve their ability to use a high-dimensional Body-Machine Interface (BoMI), to control a robotic arm. We use a sensor net of four inertial measurement units, placed bilaterally on the upper body, and a BoMI with the capacity to directly control a robot in six dimensions. We consider whether the way in which the robot control space is mapped from human inputs has any impact on learning. Our results suggest that the space of robot control does play a role in the evolution of human learning: specifically, though robot control in joint space appears to be more intuitive initially, control in task space is found to have a greater capacity for longer-term improvement and learning. Our results further suggest that there is an inverse relationship between control dimension couplings and task performance. [ABSTRACT FROM AUTHOR]

Knowledge of linkage disequilibrium (LD), genetic structure and genetic diversity are some key parameters to study the breeding history of indigenous small ruminants. In this study, the OvineSNP50 Bead Chip array was used to estimate and compare LD, genetic diversity, effective population size (Ne) and genomic inbreeding in 186 individuals, from three Iranian indigenous sheep breeds consisting of Baluchi (n = 96), Lori-Bakhtiari (n = 47) and Zel (n = 47). The results of principal component analysis (PCA) revealed that all animals were allocated to the groups that they sampled and the admixture analysis revealed that the structure within the populations is best explained when separated into three groups (K = 3). The average r2 values estimated between adjacent single nucleotide polymorphisms (SNPs) at distances up to 10Kb, were 0.388±0.324, 0.353±0.311, and 0.333±0.309 for Baluchi, Lori-Bakhtiari and Zel, respectively. Estimation of genetic diversity and effective population size (Ne) showed that the Zel breed had the highest heterozygosity and Ne, whereas the lowest value was found in Baluchi breed. Estimation of genomic inbreeding using FROH (based on the long stretches of consecutive homozygous genotypes) showed the highest inbreeding coefficient in Baluchi and the lowest in Zel breed that could be due to higher pressure of artificial selection on Baluchi breed. The results of genomic inbreeding and Ne showed an increase in sharing haplotypes in Baluchi, leading to the enlargement of LD and the consequences of linkage disequilibrium and haplotype blocks confirmed this point. Also, the persistence of the LD phase between Zel and Lori-Bakhtiari was highest indicating that these two breeds would be combined in a multi-breed training population in genomic selection studies.

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.

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 (P

The accuracy of genomic prediction of quantitative traits based on single nucleotide polymorphism (SNP) markers depends among other factors on the allele frequency distribution of quantitative trait loci (QTL). Therefore, the aim of this study was to investigate different QTL allele frequency distributions and their effect on the accuracy of genomic estimated breeding values (GEBVs) using best linear unbiased genomic prediction (GBLUP) in simulated data. A population of 1000 individuals composed of 500 males and 500 females as well as a genome of 1000 cM consisting of 10 chromosomes and with a mutation rate of 2.5 × 10−5 per locus was simulated. QTL frequencies were derived from five distributions of allele frequency including constant, uniform, U-shaped, L-shaped and minor allele frequency (MAF) less than 0.01 (lowMAF). QTL effects were generated from a standard normal distribution. The number of QTL was assumed to be 500, and the simulation was done in 10 replications. The genomic prediction accuracy in the first-validation generation in constant, and the uniform allele frequency distribution was 0.59 and 0.57, respectively. Results showed that the highest accuracy of GEBVs was obtained with constant and uniform distributions followed by L-shaped, U-shaped and lowMAF QTL allele frequency distribution. The regression of true breeding values on predicted breeding values in the first-validation generation was 0.94, 0.92, 0.88, 0.85 and 0.75 for constant, uniform, L-shaped, U-shaped and lowMAF distributions, respectively. Depite different values of regression coefficients, in all scenarios GEBVs are biased downward. Overall, results showed that when QTL had a lower MAF relative to SNP markers, a low linkage disequilibrium (LD) was observed, which had a negative effect on the accuracy of GEBVs. Hence, the effect of the QTL allele frequency distribution on prediction accuracy can be alleviated through using a genomic relationship weighted by MAF or an LD-adjusted relationship matrix.

Abstract 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.

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.

Knowledge of linkage disequilibrium (LD), genetic structure and genetic diversity are some key parameters to study the breeding history of indigenous small ruminants. In this study, the OvineSNP50 Bead Chip array was used to estimate and compare LD, genetic diversity, effective population size (Ne) and genomic inbreeding in 186 individuals, from three Iranian indigenous sheep breeds consisting of Baluchi (n = 96), Lori-Bakhtiari (n = 47) and Zel (n = 47). The results of principal component analysis (PCA) revealed that all animals were allocated to the groups that they sampled and the admixture analysis revealed that the structure within the populations is best explained when separated into three groups (K = 3). The average r2 values estimated between adjacent single nucleotide polymorphisms (SNPs) at distances up to 10Kb, were 0.388±0.324, 0.353±0.311, and 0.333±0.309 for Baluchi, Lori-Bakhtiari and Zel, respectively. Estimation of genetic diversity and effective population size (Ne) showed that the Zel breed had the highest heterozygosity and Ne, whereas the lowest value was found in Baluchi breed. Estimation of genomic inbreeding using FROH (based on the long stretches of consecutive homozygous genotypes) showed the highest inbreeding coefficient in Baluchi and the lowest in Zel breed that could be due to higher pressure of artificial selection on Baluchi breed. The results of genomic inbreeding and Ne showed an increase in sharing haplotypes in Baluchi, leading to the enlargement of LD and the consequences of linkage disequilibrium and haplotype blocks confirmed this point. Also, the persistence of the LD phase between Zel and Lori-Bakhtiari was highest indicating that these two breeds would be combined in a multi-breed training population in genomic selection studies. [ABSTRACT FROM AUTHOR]

The aim of the current study was to investigate the association of G4533815A SNP in STAT5B and A287G SNP in BMPR-IB genes with growth and reproduction related traits in chicken. A sample of 205 individuals from breeding station of Mazandaran native chicken population was selected randomly. All of the individuals were genotyped for both SNPs using PCR-RFLP technique. Marker-trait association analyses were performed using estimated breeding value of the traits as dependent variable in GLM procedure of SAS 9.1. Results suggested that breeding value least square means for genotypes of G4533815A SNP is significantly differed from each other for traits of body weight at 8 and 12 weeks (P

The objective of the present study was to determine single nucleotide polymorphisms (SNP) located in the promoter region of the bovine heat shock protein 70 (Hsp70) gene. And evaluate associations between Hsp70 SNP with conception rates in Holstein and Sarabi cows. Blood samples were collected from 124 cows. The Cows were Holstein (n=72) and Sarabi (n=52). Genomic DNA was extracted using modified salting-out method. The quantity and quality of extracted DNA were examined with spectrophotometery and gel electrophoresis. Specific primers were designed for PCR amplification of a 539 base segment of the bovine Hsp70 promoter. The polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) method was used to scan for mutations within the amplified regions. The polymorphisms were confirmed by direct sequencing. Seven single nucleotide polymorphisms were detected; one deletion at base position 895 four transitions (G1045A, G1117A, T1134C and T1204C), and two transversions (A1125C, G1128T). And also four haplotypes were detected (CAAAGCC, DGGCTTC, CDGGCTTT, CGGAGTT). Statistical analysis showed polymorphism in the promoter region of the bovine heat shock protein 70 region significantly correlated with conception rate (P

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 (Δ4 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.

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. [ABSTRACT FROM AUTHOR]

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.

Stochastic simulation was used for studying the impacts of sexed semen on genetic progress and reproductive performance of dairy cows. Three strategies were compared: WSS (use unsexed semen in cows and heifers), SSH (use sexed semen in heifers and unsexed semen in cows) and SSCH (use sexed semen in both cows and heifers). Conception rate (CR) of unsexed semen was considered to be 35% and 65% in cows and heifers, respectively. CR of sexed semen was considered to be 15 (20% in cows and 50% in heifers), 10, 5 and 0 percentage points lower than unsexed semen. Thus, four subschemes were compared under SSCH (SSCH15, SSCH10, SSCH5, SSCH0) and SSH (SSH15, SSH10, SSH5, SSH0). Moreover, the effect was studied in four distinct paths of selection: active sires (AS), young bulls (YB), bull dams (BD) and milking cows (CW). The average genetic superiority of CW was 12% and 9.5% in SSCH15 and SSH15 strategies relative to a base scheme, respectively. The average genetic superiority of CW was 19% and 10.5% in SSCH0 and SSH0, respectively. Regression analysis showed that genetic superiority of CW increased significantly, that is, 0.5% and 0.1% per every 1% increase in CR in SSCH and SSH, respectively. The result showed that there is a significant difference between genetic superiority of cows in SSCH and SSH schemes. Widespread and limited use of sexed semen in commercial dairy herds resulted in a large genetic advantage in CW. The genetic advantage of gender control was minimal in the selection paths of AS, YB and BD. Open days and services per conception reached to 153 v. 125 days and 5 v. 2.86 under SSCH15 compared with WSS. The age at first calving increased from 774 to 790 days in SSH15 and SSCH15 strategies. Mean of parities decreased to 2.26 v. 2.42 by using sexed semen. The widespread use of sexed semen increased the age average of cows in all parities. Sexed semen increased selection intensity in the CW path, and this contributed to the genetic merit of future cows. On the other hand, sexed semen had a negative effect on the reproductive performance of dairy cows. Generally, although the effect of widespread use of sexed semen (SSCH) on genetic progress is significantly more than limited use of sexed semen (SSH), SSCH decreased reproductive performance of dairy herds dramatically, and this suggests that SSH scenarios might be more appropriate in animal breeding programs. Finally, to make a decision of which schemes are more convenient, it is necessary to compare the economic aspects of schemes.

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 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 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.

New molecular techniques focused on genome analysis, open new possibilities for more accurate evaluation of economiclly important traits in farm animals. Milk production traits are typical quantitative characteristics controlled by a number of genes. Mutations in their sequences may alter animal performance as well as their breeding values. In this study, we investigated the effect of Kpn2I restriction fragment length polymorphisms in the leptin gene, on bull breeding values for milk yield, fat, and protein yield, and their percentage. In order to test for an association between the leptin single-nucleotide polymorphism in exon 2 and milk productivity, we genotyped 134 Iranian Holstein bulls. Breeding values for milk-related traits (milk yield, fat, and protein yield and percentage) were estimated using the BLUP based on an animal model. The effect of the genotypes of Kpn2I polymorphism on the breeding values for milk-related traits was examined using least square methods. The T allele frequency was 0.425. Genotypes were distributed according to the Hardy-Weinberg equilibrium. Bulls with TT genotype had higher milk, fat and protein yield compared with TC and CC bulls (P < 0.05). Bulls with CC genotype had higher protein percentage compared with TT and TC bulls (P < 0.05). The association between leptin polymorphism with milk production traits suggests that this marker may be useful for selection based on molecular information.