جستجوی مقالات مرتبط با کلیدواژه « پارامترهای ژنتیکی » در نشریات گروه « علوم دام »

Horses were breed for war, hunting, Transporting, recreational, and sports purposes (Khalili 2008). The criterion of selection is mainly based on the horse's own and their parents' performances rather than breeding value. Despite of relatively developed organization of horse husbandry in the country and availability of individual racing results for almost all the progeny and pedigree information of horses, the scientific methods are not applied in selection of the animals for improving the racing performance(Bakhtiari & Kashan 2009). Normally the criteria to estimate the racing performance are time traits (Langlois 1980, Tolley et al. 1985, Ekiz et al. 2005), handicap weights (Langlois 1980, Tolley et al. 1985), rank at finish (Chico 1994, Sobczynska and Lukaszewicz, 2003, Ekiz and Kocak 2005) and earning (Langlois 1980, Ekiz and Kocak 2005). Breeders have traditionally combined information from time trials and races with pedigree evaluations to select potential racing stock, but this evaluation has primarily been based on a subjective synthesis of available information. Although the Standardbred horse is extensively performance tested before selection of breeding stock, studies of the genetic and environmental factors that influence racing performance must be completed before specific selection criteria can be recommended to the industry (Tolley et al. 1983). Racing ability is the main selection criterion in race horses. Breeding value estimation for aspects of racing ability has been carried out following performance tests in many European countries(Àrnason et al. 1994). Traits such as rank, time, prize, etc. are used to estimate the genetic and phenotypic parameters of race horses(Sobczynska & Lukaszewicz 2004). Genetic parameters estimation of racing performance traits is important in breeding programs, therefore, appropriate methods should be used. This study aimed to estimate the genetic parameters of racing performance using a linear model in different breeds of Iranian race horses and estimation of their genetic and phenotypic trends. The result of this study would be used for designing a breeding program for Iranian race horses.

In this study, the performance records of Iranian horse breeds, including Thoroughbred, Crossbreed, Turkmen, and Arabian horse breeds from the horse racing club of the Iranian Equestrian Federation between 2006 to 2014 were used. Performance traits in this study include 1.Racing Time, 2.rank at the Finish, 3.Cumulative Earning, 4.Number of Places, and 5.Number of races. Data were collected and adjusted using Excel software and R scripts. The quality controls included outliers deletion and preparing records for statistical analysis. CFC software (Sargolzaei et al. 2006) was used to survey the structure of the pedigree. For fitting the appropriate model the significant effects were investigated and was applied by SAS software. Variance components and genetic parameters were estimated by the restricted maximum likelihood method for a single trait animal model using ASReml software. A genetic trend is a compilation of average EBV per generation and indicates the direction of change across generations. It is often visualized in a graph and is useful to check whether there are unexpected deviations from linearity, e.g. due to a selection limit. The genetic trend in the racing performance was estimated by calculating the linear regression of average breeding values within birth years on the birth year.

The heritability of finish time at races for Crossbreed and Thoroughbred horses in 1000, +1500, and +1600 distances were estimated in the range of (0.19-0.29) and (0.36-0.45), respectively, and it was 0.25 and 0.13 respectively for the Arabian horse breed in 1000 and +1500 distance, and it was 0.35, 0.38, and 0.44, respectively for the Turkmen horse breed in 1000, 1550 and 1600 distance. The heritability of the rank was in the range of (0.046-0.17), (0.12-0.16), (0.24-0.28) 0), and (0.13-0.22) based on the linear model (Animal model), respectively for Crossbreed, Thoroughbred, Arabian, and Turkmen horse breed. The heritability of the cumulative earning was 0.20, 0.072, 0.019, and 0.033 respectively for the Crossbreed, Thoroughbred, Arabian, and Turkmen horse breeds. The repeatability of finish time for Crossbreed and Thoroughbred in 1000, +1500, and +1600 distance were estimated in the range of (0.38-0.59) and (0.40-0.52), respectively. Also, it was 0.64 and 0.54 respectively for the Arabian horse breed in 1000 and +1500 distance and were 0.60, 0.67, and 0.59, respectively for Turkmen horse breed in 1000, 1550 and 1600 distance meters. The repeatability of the rank was in the range of, (0.14-0.19), (0.13-0.17), (0.2-0.40), and (0.13-0.30), respectively for Crossbreed, Thoroughbred, Arabian, and Turkmen horse breed. The genetic trend of this trait for Crossbreed and Thoroughbred in 1000, +1500, and +1600 distances were estimated in the range of (-0.0629 to -0.0173) and (-0.0384 to -0.0236), respectively. Also, the genetic trend were 0.0372 and -0.0335 respectively for Arabian horse breed in 1000 and +1500 distance and were 0.0104, 0.587, and -0.0462, respectively for Turkmen horse breed in 1000, 1550, and 1600 distance. These results showed an inconsistency between this study and other research (references) due to the number of data, environmental and managerial factors such as the experience of horses in the race, and the type of equipment and tools involved in the competition. Regarding the low estimated heritability of some performance traits in this study, genetic progress through indirect selection will be more usefulness than direct selection on these traits. As the application of modern genetic selection methodologies continues to gain popularity in the racing industry, contemporary heritability estimates from the current population of Thoroughbred, Crossbreed, Turkmen, and Arabian horse breeds will play a vital role in identifying which traits are better suited to selection and in the development of more accurate genomic evaluations for racing performance.

Quality of wool has a major impact on its consumption and ultimate use and therefore, evaluation and genetic analysis of wool characteristics is one of the most important research fields for native sheep. Considering that Iran-black sheep is a result of Baluchi and Chios crossbreeding, the present study was conducted to compare and genetic analysis of fleece characteristics of Baluchi and Iran-black sheep.

In this study, wool samples were collected from 176 Baluchi and 105 Iran-black sheep in Abbas-Abad sheep breeding center located near to Mashhad, Khorasan-Razavi province, in October 2017. Fleece characteristics, including greasy fleece weight, average fiber diameter, average staple length, hetero-type fibers (%), modulated fibers (%), and true wool fibers (%) were measured. To determine the fixed effects (breed, year of birth, type of birth and sex) affecting wool characteristics of the breeds, the GLM procedure of SAS software was used. Least square means comparisons of different fixed effects subclasses was carried out by Tukey-Kramer test at 5 percent probability levels. The components of (co) variances and genetic parameters of the studied traits were estimated using the multi-trait animal model and restricted maximum likelihood using WOMBAT software.

Results showed that the differences between the breeds were significant for average fiber diameter, hetero-type fiber percentage and true wool percentage. None of the studied traits were affected by sex of lamb except for hetero-type and true fiber percentages (P<0.05). Year and type of birth could only affect the greasy fleece weigh (P<0.05). Coefficient of variation for greasy fleece weigh (26.28 percent), hetero-type fiber (76.77 percent) and modulated fiber (99.59 percent) showed that considerable variations are there for these traits in the two studied breeds. Average fiber diameter in Baluchi (26.28 micron) was significantly lower than Iran-black breed (29.26 micron) (P<0.05). True wool percent in Baluchi (94.81 percent) was significantly higher than Iran-black breed (92.65 percent) (P<0.05). Heritability of wool traits in Baluchi breed ranged from 0.26 (modulated fiber percent) to 0.45 (hetero-type percent) and in Iran-black breed ranged from 0.28 (modulated fiber percent) to 0.34 (true fiber percent).

In general, Baluchi breed had finer wool than Iran-black and Iran-black fleece characteristics were worse than the native Baluchi parent. Moreover, moderate heritability for the studied traits in both of the breeds indicated that selection programs for improving these traits in these populations would be effective.Keywords: Baluchi Sheep, Crossbreeding, Wool, Genetic parameters

In this study, body weight records of 19171 American Simmental beef cattle including 8758 bull and 10413 cows from 2000 to 2016 were used to estimate genetic parameters and trend. We conducted genetic evaluation of data from 5199, 10926, 7362 and 5636 genotyped beef cattle of gene-based single nucleotide polymorphisms (SNPs) for birth weight (BW), weaning weight direct (WWD), yearling weight (YW) and post-weaning weight gain (PWG), respectively. Genetic parameters estimated using univariate and bivariate animal models and BLUPf90 software. Heritabilities were estimated for BW, WW, YW and PWG 0.38 ± 0.02, 0.24 ± 0.01, 0.35 ± 0.01 and 0.22 ± 0.02 using univariate analysis, respectively. Genetic correlation between BW and PWG was 0.31. The highest and the lowest genomic accuracy were estimated for WWD (0.68) and PWG (0.27), respectively. Genetic trends were estimated for BW, WW, YW and PWG 0.13, 0.28, 3.43 and 0.05, respectively. In addition, slight changes were observed in the genetic trend of all traits, especially weaning weight direct and yearling weight across years of study which indicates the existence of specific selection goals and criteria in each of these traits. In general, three large-effect closely linked QTLs identified on BTA6 at 37 Mb, on BTA7 at 90 Mb and on BTA14 at 22 Mb. Because correlations were favorable between body weight traits, breeding program should be based on the simultaneous selection of these traits through the selection index.

In this study, genetic parameters and (co) variance components were estimated for weights at birth, 3, 6, 9 month, daily weight gain and Keliber ratio from birth to 3 month and also form 3 month to 9 month. Records of 2544 kids, the progeny of 149 sires and 851 dams were used to analysis data by MTGSAM program. Six different animal models were fitted for all traits. The most appropriate model for weight at 6, 9 and daily weight gain and Keliber ratio form 3 to 9 month was model 2. Estimated direct heritability varied from 0.01 to 0.36, which was minimum (0.01) for daily weight gain and Keliber ratio from birth to 3 month and maximum (0.36) for birth weight. The genetic and phenotypic trends for all traits were estimated near to zero and non-significant. Generally, differences between estimated genetic trends for these traits and estimated values of other studies, is due to difference in animal breeding standard followed by different program selection, difference between models and calculation method, effects of environment, interaction between genetic and environmental, nutrition and climate conditions.

The aim of this research was estimation of genetic parameters for the fat: protein trait (FPR) in daily milk test records of Iranian dairy cow. From a total of 295,820 monthly daily milk test records, 29,582 first-parity cows in 622 herds were used which were calved from 1997 to 2012. The trait was analyzed using a covariance function. Orthogonal Legendre polynomials with a 3th order were implemented to take account of genetic and environmental aspects of milk production over the course of lactation. The data were analyzed with the help of DXMRR software. Maximum phenotypic and genetic correlations (0.209 and 0.988) was obtained between the ninth and tenth month Maximum permanent environment correlation (0.938) was observed between the seventh and eighth months. The lowest (0.029) and highest (0.064) heritability’s were obtained for the third and first months of the lactation, respectively. Low heritability magnitudes showed that there is a low genetic variation for FPR trait which is suggesting much more effects of environmental factors.

In order to estimate the genetic parameters and heritabilities of growth traits and Kleiber ratios in Moghani sheep, data collected in Jafarabad-e-Moghan station from 1994 to 2016 were used. Investigated traits including birth weight, average daily gains and Kleiber ratios during four time periods that is birth to 3 months, 3 t 6 months, 6 to 9 months and 9 to 12 months first analyzed by SAS 9.2 software to indicate the significant fixed effects, finally, 6 animal models running by Wombat software was used to estimate the genetic parameters and heritabilities. The heritability of birth weight (0.31), Average daily gain and Kleiber ratio from birth to 3 months and from 3 to 6 months (0.34, 0.36, 0.40 and 0.38 respectively) were medium to high. The maternal heritabilities and the ratios of maternal permanent environmental variance to the total variance were in the range of 0 to 4 percent and 0 to 2 percent respectively. The genetic trend for birth weight, Average daily gains and Kleiber ratios during four time periods were 0.13, 0.21, 0.27, -0.0000014, 0.01, 0.01, -0.0002 and 0.00004 respectively. These results indicated the relative efficiency of breeding programs for the average daily gains and Kleiber ratios during birth to 3 months and 3 to 6 months in Moghani sheep.

Genetic parameters for birth weight and survival traits were estimated using data collected from 1995 to 2009 in Jafarabad Moghani Sheep Breeding Station. Number of observation for survival and birth weight were 7202 and 6585, respectively. Genetic parameters were estimated using restricted maximum likelihood (REML) procedure under 16 different models, including animal, threshold and sire models using ASReml software. The most appropriate model for each trait was determined based on Akaike’s Information Criterion (AIC) method. The appropriate model for birth weight was included direct additive genetic, maternal additive genetic and common litter effects. Also, the animal model for lamb survival were included direct additive genetic, maternal additive genetic, maternal permanent environmental, common litter effects and covariance between direct and maternal additive genetic effects. The appropriate sire model for lamb survival was included sire direct additive genetic and common litter effects. Estimated direct heritability for birth weight was 0.09±0.02. The direct heritabilities for survival with animal model and sire model was 0.070±0.002 and 0.05±0.02, which after correction was changed to 0.22 and 0.15, respectively. Also, the estimation of heritability for lamb survival from threshold model was 0.30±0.10. Genetic, environmental and phenotypic correlation between birth weight and lamb survival were 0.61±0.24, 0.08±0.02 and 0.07±0.01, respectively. Consideration of environmental factors, including common litter effects, is essential for unbiased estimation of genetic parameters.

For the design of any successful breeding program, knowledge about semen quality traits is greatly important and per-required. Due to the critical role of bulls through artificial insemination in the genetic improvement of the dairy cattle herds, knowledge about semen characteristics and genetic factors which affect semen parameters is essential. In addition, semen with poor fertility requires more units of semen to establish a successful pregnancy and produce a live offspring. Nonetheless, both impacts are economically important factors, which are considered by the producers leading to rejection of bulls with poor semen quality, and investing mainly on highly fertile sires. Summary of previous literatures is highlighted semen traits and their key roles in upcoming fertility and pregnancy of cows within herds (Gacitua et al. 2005). Furthermore, some reports pointed DNA markers can identify the genetic background mechanism of resistance and susceptibility of sperm after freezing and thawing (Purdy et al., 2005). Additionally, previous reports supported  low hereditability scenario of semen characteristics in livestock species (England et al., 2010). Leptin is a globular protein with a tertiary structure similar to a haemopoietic cytokine synthesized by adipose tissue. It is involved in the regulation of feed intake, fetal growth, energy balance, fertility, and immune functions. The leptin molecule (16 kDa) is made up of 167 amino acids with an N-terminal secrotary signal sequence of 21 amino acids. In cattle, the leptin gene is located on the fourth chromosome. It consists of three exons and two introns. Only two exons are translated into the protein. The coding region of the leptin gene (501 nucleotides in length) is in exons 2 and 3, which are separated by an intron of approximately 2 kb. The leptin gene promoter region spans approximately 3 kb. Leptin is necessary for normal reproductive function, but when present in excess, it have detrimental effects on the male reproductive system. Human and animal studies pointed to leptin as a link between infertility and obesity, a suggestion that was corroborated by findings of low sperm count, increased sperm abnormalities, oxidative stress, and increased leptin levels in obese men. In addition, daily leptin administration to normal-weight rats has been shown to result in similar abnormalities in sperm parameters. The bovine growth hormone (bGH) is a 22 KDa single-chain polypeptide hormone, which is produced in the anterior pituitary gland. The encoding gene is approximately 1800 base pair (bp) and consists of five exons separated by four intervening sequences (Harvey et al. 2000). Recently, several studies have investigated the association between bGH locus and reproduction traits. A substitution of cytosine (C) for guanine (G) at the  position of 2141 causes an amino acid change from leucine (leu) to valine (val) at residue 127. This transversion enables the genotyping of this particular locus using the endonuclease AluI, since in the mutant bull, this enzyme does not recognize its target sequence. Several point mutations in the bovine growth hormone (GH) gene have been described, and as such, the Leu127Val polymorphism described by Lucy et al. (1993) has been extensively investigated based on  production and reproduction traits. In addition, Lechniak et al. (1999) have reported the relationship between individual semen quality traits and fertility. The purpose of the present study was to estimate the genetic parameters of some semen quality traits using animal models containing genotype of candidate gene data on Holstein bulls.

For this reason, 67 bulls were selected from two breeding stations in the Northwest of Iran (41 bulls) and the National Livestock Improvement Center (26 bulls), which were in the sperm production stage between 2003- 2013. In this regard, four related traits of semen quality were considered, including: volume of ejaculation, sperm concentration, live sperm percentage before freezing, and live sperm percentage after thawing. The DNA extraction was done from semen according to commercial DNA kit and quality and quantity tests were done using spectrophotometry and gel monitoring. The nucleotide polymorphisms were evaluated in two loci of the leptin gene (Exon 2 and intron 2) by the PCR-RFLP method and in the growth promoter receptor gene (promoter region) using PCR-SSR technique. Finally, using combined phenotypic and molecular information, genetic parameters were estimated through Bayesian statistics and Gibbs sampling. POPGENE software was used for molecular data and descriptive statistics (genotype frequencies, allele frequencies, and hetrozygosity index calculation). Univariate and multi variate analysis for semen characteristics was done using gibbs3f90 and renumf90 softwares.

According to the molecular outputs, in all investigate genes nucleotide variation and polymorphism was observed. The results of univariate analysis of animal model for estimating heritability for traits of semen volume, sperm count, live sperm percentage before freezing, and thawing point were 0.22, 0.14, 0.20, and 0.10, respectively. Reproductive performance is controlled by the genetic make-up of dam, sire, and offspring, but it is largely affectedby environment. Thus, the reproductive efficiency of the breeding herd depends on the fertility of the bulls(Gredler et al., 2005). Bull’s fertility is also essential, since bull's DNA is the primary mechanism through which genetic improvements can efficiently be accomplished. Implementation of artificial insemination (AI) in dairy cattle production allowed improving selection of bulls for production traits. Also, frequent freezing and thawing process of bull semens significantly affected quality index and consequent evaluation of fertilization potential of a semen sample for AI in Holstein breeding stations (Mathevon  et al., 1998).However, the preselection of the samples, the high number of sperm per doses, and the high quality of the semen used in the AI programs  can reduce the variability, thereby giving a low probability of detecting fertility differences associated with seminal parameters. Spermatogenesis is a complex process that involves stem-cell renewal, genome reorganization, and genome repackaging;  so, it culminates in the production of motile gametes (Kealey et al., 2006). The process of spermatogenesis is regulated by reproductive hormones in gonadotropin axis and is controlled by a large number of genes(Sun et al., 2012). Therefore, hormone and their receptors are presumed to be good candidate genes for reproductive traits.

The results of this study indicated that the range of heritability values for the different semen quality characteristics are low to moderate, which may indicate that improvement of environmental factors is more effective than genetics basis.

The present study was conducted to estimate the genetic and phenotypic parameters of productive and reproductive traits of Holstein cows in Mazandaran Holstein dairy cattle. To this purpose, data 39792 records of Holstein cows collected at Mahdasht Milk and Meat Company in sari during 1986 to 2015 were used. Productive traits included corrected 305 days milk records, fat and protein production, and reproductive traits were age at first calving, calving interval, dry period and days open. Genetic parameters were estimated by THRGIBBS1F90 software under single trait animal model using Bayesian statistical method based on Gibbs sampling approach. A total of 200000 cycles were implemented among which the first, 20000 cycles were considered as burn-in period. Heritabilities obtained as 0.34, 0.68, 0.65, 0.17, 0.007, 0.07 and 0.07 for milk production, fat production, protein production, age at first calving, calving interval, dry period and days open, respectively. The genetic correlation between milk production and fat production was 0.48. Genetic correlation between milk production, fat production and protein production with age at first calving was -0.003, 0.14 and 0.39, respectively, Genetic correlation between milk and protein production with calving interval was estimated to be 0.23 and 0.55, respectively. According to the results, correlations between production and reproduction traits could be considered in breeding programs.

 According to the FAO in 2017, Iran, with 40 milion head of sheep and 291200 ton sheep meat, is the eighth country in the world of sheep production(http://www.fao.org/faostat/en/#data). One of the most important factors influencing accuracy of the estimated breeding value is complete sire pedigree information. Registration of father's number in sheep flocks of Iran is a big problem, through not having  any program for the control of matting program and artificial insemination. Therefore, the information of sire pedigree is not complete in sheep flocks. Incomplete pedigree causes incorrect relationship matrix and reduces accuracy of the selection and estimation of the genetic parameters of the traits and increases errors in the estimates(Clement et al., 2001). So, the existence of false and missing father’s information reduces genetic gain that this decrease in traits with low heritability have steeper slope. Imperfect sires pedigree data increase standard deviation between different repetitions of estimating variance components and cause bias estimation of genetic and phenotypic parameters(Sanders et al., 2006). Therefore, increase of unknown father's will be decreased direct and maternal heritability and breeding value, but the phenotypic variance will not be affected(Senneke et al., 2004).The estimation of heritability in complete and unbiased pedigree is similar to its actual value. But, random excluding of  50% of father’s ID led to bias estimation of heritability. If 50% of parent’s ID removed  from pedigree, the estiomation of heritability will be incorrect(Cantet et al.,2000). Generally, incomplete pedigree increases the standard error of estimations(Dong et al., 1988). Comparing random and consecutive exclusion pedigree methods (consecutive From zero to the last generation) for a trait with heritability of 0.15 showed random exclusion method leaded to a slight reduction in genetic variation, which consequently declined estimation of heritability. But for other trait with heritability of 0.30 different estimation of variance components leaded to significant decrease in estimation of heritability. In the consecutive exclusion method, the reduction of heritability was not significant with an increase  missing in pedigree of sires(Abbasi et al., 2011). Our objective in this study was investigation of influence of incomplete sire's pedigree on estimation of (co) variance components, genetic parameters and accuracy.

In this study we simulated a population with weaning weight (WW) and average daily gain(ADG) records. Heritability for weaning weight (WW) and average daily gain(ADG) were 0.15 and 0.30 respectively and genetic, environmental and phenotypic correlation for two traits were 0.5. Average of weaning weight was 22.29 kg, genetic variance was 1.7525, environmental variance was 9.759, phenotypic variance was 11.5, and heritability was 0.15. The average amount of  genetic variance,  environmental variance, and  phenotypic variance for daily weight gain were 190 g, 1078.2 , 2515.8, 3594, respectively and heritability was 0.3. The pedigree file and performance data were included of animal ID, father and mother ID, phenotypic variance, breeding value, and environmental effects for two traits. Visual Basic 6 program was used for simulation. Mating was random in both populations and the maximum maintenance age of sire and dam was 3 and 6 years, respectively. The ratio of female to male was15:1. In the generated data file, the sire numbers were eliminated asrandom and sequential with proportions 0 to 100 perecnt.The resulted data file were analyzed based on  two traits animal model. The accuracy of selection calculated from correlation between actual and predicted breeding values.

The simulation of data file consist of 20625 head of sheep and base population was 2075 head in this study. Data file included animal ID, sire ID, dam ID, phenotypic value for weaning weight and daily weight gain. Random 10% deletion  of father’s ID increaed unknown fathers from 2750 to 4490 ,while unknown fathers for random 80% deletion  was  equal to 16973. In random and consecutive deletion method, phenotypic variances for two traits were slightly constant. The variance of daily weight gain for random deletion in diferent levels was stable. But the genetic variances were decreased and the environmental variances were slightly increased. The heritabilities of two traits were significantly (P<0.05) reduced in random deletion method.  These results were almost contrary to the results of the randomization method in analysis of a trait with heritability of 0.15, in which the reduction of heritability was not significant(Abbasi et al., 2011). Standard error of heritability in final removal percentage with increase in defect of father's ID slightly increased. In randomization method, variation of variance components led to decrease estimated heritability in 0-80% exclusion of father's ID. In exclusion of father's ID estimated heritability slightly increased by 90 and 100 percent,  which were significant compared with base population (P<0.05). The reduction of genetic variances and heritabilities with increasing in deletion proportion of sire pedigree were only significant(P<0.05) for 50 to 90 percent of sire pedigree sequential deletion. The accuracy of selection were reduced from 0.767 to 0.493 and 0.933 to 0.614 for WW and ADG, respectively. Genetic correlations were reduced with increasing in missing proportion of sire number in random deletion method. But in sequential deletion method, the reductions of genetic correlations were only significant for the proportions of 60 and 80 percent in deletion of sire ID.

 Incomplete pedigree generates incorrect relationship matrix and bias in the estimation of variance components, genetic parameters of traits and the accuracy of selection. so that , the percentage of  father's ID deletion had a slight influence on phenotypic variance, phenotypic, and environmental correlation. The effect of random deletion of father’s ID on pedigree information had more influence than consecutive deletion method; then, this effect depends on the actual heritability, kind of traits, and the structure of simulated data. Generally, genetic variances, heritabilities, the accuracy of selection and genetic correlation between two traits were reduced with inceasing the proportional deletion  of sire number. The reduction of accuracy associated with genetic progress of traits; then, it is necessary to develop artificial insemination and others control mating method in order to record father's ID.

Bivariate random regression models were used to estimate variance components of test-day milk yields (TDMY) in the first and second lactations of Iranian buffaloes. Data included 10,133 TDMY records from 862 Iranian buffaloes for first lactation and 786 for second lactation which were collected from 1993 to 2011 by the animal breeding centre of Iran. The models of analysis included the fixed effects of herd-test-date (HTD), year-season (YS) and age at calving as covariate were fitted in the model of analysis. The random variables of model were the additive genetic and animal permanent environmental effects and residual effects. The (co)variance components and the genetic parameters were estimated using the REML method with the Wombat program. In bi-variate model, each parity was treated as a separate trait. In the first lactation, Heritability estimates were low to moderate and ranged from 0.05 to 0.26 and had an erratic pattern. In the second lactation, the heritability estimates increased from the first (0.29) to the second test day (0.31), and then with a slight decrease during lactation, again increased on the last two test days (0.14 and 0.29). The range of genetic correlation between the first day of the first lactation period and the whole day of the test days in the second lactation period were reported between -0.07 and .73. Heritability estimates test-day milk yield are higher at the beginning of the lactation period for first and second lactation which indicates that milk yield in the early months of lactation can be used as a selection criterion in Iranian native buffalo.

The objective of this study was to investigate genetic and phenotypic parameters of body weight of shall lambs in different ages. Records of growth traits obtained from 6,692 lambs (progeny of 195 rams and 1,288 ewes) were used. The records of birth weight, BW (6,690 records), 3-month weight, W3 (6,654 records), 6- month weight, W6 (6,662 records), 9-month weight, W9 (6,599 records) and 12-month weight, W12 (6,528 records) collected between 1997 and 2013 in Shal Breeding Station in Ghazvin province were used. Genetic parameters were estimated applying restricted maximum likelihood method fitting an animal model using WOMBAT program. Test of significance for the fixed effects was carried out using SAS 9.2 software. The mean ± standard deviation of BW, W3, W6, W9 and W12 were 4.31±0.92, 20.90±3.46, 34.13±3.92, 47.42±4.21, and 60.46±4.28 kg, respectively. Direct heritability estimates were 0.13±0.02, 0.57±0.05, 0.52±0.05, 0.79±0.04 and 0.73±0.05 for BW, W3, W6, W9 and W12 respectively. The highest maternal heritability was estimated for W9 (0.32±0.02).

The present research was performed to study the genetic analysis of length of productive life and production traits (milk yield, fat yield and protein yield) Iranian Holstein cows. Thus, the records of 90112 first lactation dairy cows were used. Data were collected from 759 herds during 1996 to 2013 by the Animal Breeding Center of Iran. Estimation of variance components was performed by restricted maximum likelihood method using DMU package. Genetic and phonotypic trends were computed as a linear regression of yearly means on calving year. The estimated heritabilities of length of productive life, functional productive life, milk yield, fat yield and protein yield were 0.04, 0.03, 0.23, 0.17 and 0.20, respectively. Genetic correlation of length of productive life, functional productive life with production traits ranged from 0.02-0.11. Estimated genetic correlation of milk yield with fat yield and protein yield was 0.88 and 0.94, respectively. Genetic trends for lifetime traits (productive and functional) were -0.02 and 0.002 d, respectively (P>0.05) and for milk yield, fat yield and protein yield were 5.46, 0.08 and 0.09 kg, respectively (P

The aim of this study was to estimate genetic parameters associated with longevity and body weights and analysis of longevity in the Guilan province native sheep. The data set included full information of pedigree, sex, year, month and day of culling, dam age, year, month and day of birth, type of birth, and birth weight, 3 and 6-month weight. In order to study genetic relationship between longevity and body weights at different ages, bivariate linear-linear models and AIREML algorithm of WOMBAT software were used. The models included the fixed effects of year and month of birth, sex, type of birth, dam age and linear effect of birth weight as covariate. Direct heritability of longevity was low and equal to 0.03. Althogh direct heritability of birth weight 3 and 6-month weight were equal to 0.13, 0.022 and 0.097 respectively. Also, direct genetic correlation between longevity-birth weight, longevity-three month weight and longevity-six month weight were estimated to be -0.081, 0.91 and -0.90, respectively. Negative correlations indicated that lambs with high birth weight and lambs with high weight in 6 month due to culling from flock don’t have high longevity. Because of the low heritability of longevity, for improving the longevity of lambs from birth to yearling age, environmental and management conditions should be improved and indirect selection should be conducted using the correlated traits to increase the survival rate of Guilan province native lambs.

Iranian native fowl, which are kept in different parts of Iran, are characterized by a long history and vast diversity. Iranian indigenous chickens are meat-cum-egg type. There is evidence of variation in Iranian native fowl for different traits. In many developing countries, the local gene pool still provides the basis for the poultry sector. The genetic resource base of indigenous chickens can form a basis for genetic improvement and diversification to produce a breed adapted to local conditions. However there is little information about existing or potential productivity and production characteristics of indigenous chickens. Breeding of native fowl is important for small farmers to produce more income and also to conserve genetic variation of native breeds. Extensive investigations on the genetic characteristics of economic traits should be conducted before designing a breeding program. The correct method of evaluation of genetic parameters to select the best animals is very critical. Gibbs sampling Bayesian method was used to estimate genetic parameters. This method includes the definition of prior and posterior distribution and then combines to form full conditional posterior distributions for the analysis of complex models with a large number of records. This method is expected to better results achieved. The objective of the present study was to study the genetic characteristics of growth and egg production traits consisting heritability and genetic and phenotypic correlations in native fowl of Khorasan Razavi province.
The collected information of about 21000 native fowl of Khorasan Razavi Province during 2009 to 2012 were used. Genetic parameters of studied traits were estimated via Bayesian implementation of Gibbs sampling using GIBBS3F90 software. Heritability and genetic and phenotypic correlations between traits were estimated using univariate and bivariate animal models. First, to increase the accuracy of calculations, according to the characteristics of the normal distribution, records with more or less than three standard deviations from the mean of each character were considered as outliers and were omitted from the data. Analysis of variance was performed for each studied trait to find out the significant fixed effects. To obtain the marginal posterior distributions for each parameter, Gibbs sampling technique in a special case of MCMC algorithm was used.
Average values of body weight at 8 (BW8) and 12 weeks (BW12) of age, weight and age at sexual maturity (WSM, ASM), egg number (EN) and egg weight (EW) were684.16 g, 1243.75 g, 1811.41 g, 164.21 days, 50.36 g, 38.86 number, respectively. Heritability of BW8, BW12, WSM, ASM, EN and EW were 0.37, 0.40, 0.30, 0.31, 0.46 and 0.11, respectively. The highest heritability among performance traits belonged to egg weight between 28 to 32 weeks of production period (0.46) and the lowest heritability was observed for egg number during first 12 weeks of production (0.11). Moderate to high heritability values show the importance of genes effect on the phenotypic variance and the effectiveness of selection for genetic improvement in the studied traits. Genetic correlation between BW8 and BW12 was high (0.86) and they showed high genetic correlations with ASM (0.84 and 0.69, respectively). These results demonstrated the similarity of genetic structure of these traits. Genetic correlations of BW8, BW12 and WSM with ASM were positive. Therefore, selection for increased growth rate at different ages will unfavorably increase ASM. Growth and egg production traits are both important in native fowl because they are dual-purpose breeds.
The average body weight at different ages in native fowl of Khorasan Razavi Breeding Center were higher than other native fowl breeding centers which shows their proper capacity for meat production. Native fowl of Khorasan Razavi showed relatively suitable performance in egg weight and the age of sexual maturity but the produced egg number needs more attention and must be improved in this breeding center. Because of unfavorable genetic correlations between growth traits and ASM, selection for increased growth and decreased ASM using a selection index would be necessary to improve the economic performance of native fowlin Khorasan Razavi province.

The purpose of dairy cattle breeding is improvement of productive and fertility performance. The breeding of dairy cows was done to increase milk production, longevity, disease resistance and fertility efficiency. In most countries, importation of bulls’ semen with highly breeding values was increased. Global sales of semen expose progeny of sires to climates and production systems vastly different from their original selection environment. This may cause sire re-ranking because the progeny of some sires are not expected to perform to their optimum in every different environment. The objective of this study was to investigate 305 d milk yield and 305 d fat percentage performance of Holstein dairy cows under different climates of Iran.
In this study, the records of 191910 first lactation Iranian Holstein (305 d milk yield and 305 d fat percentage) were used. These records were collected from 1368 herds during 2000 to 2011 by the Animal Breeding Center of Iran. Records from cows without pedigree information were excluded. Age at first calving was required to be between 20 and 40 month and calving interval between 300 and 600 d. According to weather conditions, geographical location of herds was classified to 5 climate groups (arid, semiarid, Mediterranean, semi humid and humid) via De Martonne method.
In this study, the models were developed based on data availability, literature evidence, genetic evaluation models that are used in other countries, and available computing facilities. Single-trait model for these traits was as follows: where yijk denoted 305 d milk yield and 305 d fat percentage, µ was overall mean, HYSi was a combination of fixed effect of herd by year of calving by season of calving, b1 and b2 were linear regression coefficients of Holstein percentage and age at first calving, respectively, HF was the effect of Holstein percentage, Age was effect of age at first calving, aj was a random animal genetic effect and eijk was a random error term. Variance and covariance components were estimated by restricted maximum likelihood method using DMU program. Genetic and phonotypic trends were computed as a linear regression of yearly means on year of birth using the REG procedure of SAS 9.1.
The average of 305 d milk yield was the highest in arid climate (7350.34±1558.29 kg) and was the lowest in humid climate (5578.66 ± 1024.2 kg). The higher 305 d milk yield in the arid climate can be due to better management conditions in these regions compared to other climates. It seems that high humidity in Mediterranean, semi humid and humid climates can intensify higher environmental temperature and thus management and control of diseases can be difficult that result in milk production depression in these climates. The estimated heritability ranged from 0.11 (Mediterranean climate) to 0.29 (arid climate) for 305 d milk yield. Logar et. al., (17) reported that additive genetic variance in environments with high milk production was higher than environments with low milk production. Thus, observed differences in additive genetic variance in the climates can be due to several factors including difference in level of herd yield, environmental variation, data size and management strategies in herds. In arid, semiarid, Mediterranean, semi humid and humid climates, genetic trends of 305 d milk yield was 22.20, 17.37, -0.074, 0.92 and -0.71, respectively. According to the results, it seems that genetic gain in herds of Mediterranean, semi humid and humid climates was very low.
Results showed that average 305 d fat percentage in Mediterranean climate was the highest and in semi humid was the lowest (3.44 ± 0.34% vs. 2.98 ± 0.56%). The estimated heritability for 305 d fat percentage was 0.11 (Mediterranean climate) to 0.29 (arid climate). It is concluded that small size of data in Mediterranean, semi humid and humid climates can lead to lower heritability. Also, differences in the estimated heritabilities in different climates can be due to difference in mean and coefficient of variations of 305 d fat percentage. Genetic trends of 305 d fat percentage was -0.0012, 1.23×10-5, 5×10-5, 0.0002 and -0.0004 for arid, semiarid, Mediterranean, semi humid and humid climates, respectively.
According to differences in genetic parameters of traits in different climates, it seems that performance of cows was different, that can be due to genotype by environment interaction.

The objectives of present study were to estimate the genetic and permanent environmental covariance components and genetic and phenotypic trends of test-day records of somatic cell score (SCS) of the first lactation Iranian Holstein cows. Dataset included the 108995 test day records were collected by the Animal Breeding Center of Iran from 2001 to 2010. The GLM procedure of SAS software was used for fitting the fixed effects in the statistical models of analysis. All analyses were performed using the AIREML algorithm of WOMBAT software. 16 different random regression models were studied and compared based on Akaike’s information criterion. Random regression model with Legendre polynomial functions of orders of 4, 4, 5 were chosen to fit fixed regression, additive genetic and permanent environmental effects, respectively, and residual variance was assumed in 4 heterogeneous levels during the lactation. Estimation of heritability was low (0.022 to 0.032) that indicated this trait mostly affected by environmental factors. Genetic and environmental correlations between daily SCS were high for adjacent tests and low between the beginning and the end of lactation. The estimated environmental correlations were lower than the genetic correlations in all stages of lactation. Annual genetic and phenotypic trends were -0.59±0.103 and -0.08±0.002, respectively, for SCS trait. Both genetic and phenotypic trends for SCS were significant (P

The present investigation was undertaken to study reason of culling, non genetic effects and genetic parameters of longevity with two method linear model and Weibull. A data set of information from Holstein dairy cows of Isfahan province (Iran) was used for this study. The culling date of 36340 animals from 65 herds recorded in 1993-2014 was used. From 33219 culled cows in these years were 27.9 and 72.1 percent for voluntary and involuntary culling respectively. Lifespan and Length of productive life (LPL) were analyzed for longevity. Functional productive life (FPL) was estimated by adjusting LPL for first lactation milk yield relative to herd average. The mean of lifespan and length of productive life were estimated to be 954 and 1710 (days) respectively. The results with GLM procedure showed that HYS and age at the first calving had significant on length of productive life. The results with Lifereg procedure with Weibull function showed that effects of herd, year of first calving (p

This research was conducted to study genetic and phenotypic relationships between growth curve parameters in Mehraban sheep. The data set used in this study were obtained from the Agricultural Organization of Hamedan province and comprised 35414 body weight records from birth to 365 days of age during 2001to 2011. Parameters of Brody growth model were studied which included A (asymptotic mature weight or average mature weight of animal), B (proportion of asymptotic mature weight to weight gain as a percent of mature weight) and K (growth rate until reaching to mature weight). Fixed factors affecting on growth curve parameters were identified using the GLM procedure of SAS software. The model of genetic analysis included direct genetic effect, maternal genetic effect, maternal permanent environmental effect and covariance between direct genetic and maternal genetic effects. To estimate genetic relationship between growth curve parameters, Bayesian method based on Gibbs sampling was used. Direct heritabilities for growth curve parameters of A, B and K were 0.29, 0.63 and 0.27, respectively. Direct genetic correlation between A and B was positive and high (0.58), which indicates that these traits are aligned with each other while the correlations between B and K (-0.69) and between A and K (-0.54) were negative. The results indicated that improvement of growth curve parameters of Mehraban sheep is possible in selection programs. Therefore, it is worthwhile to propose an optimum selection strategy for obtaining appropriate growth curve in Mehraban sheep through changing genetically the model parameters.