selection

Molecular markers that reveal polymorphisms at the DNA level now play a key role in animal genetics. However, the selection of molecular markers is crucial depending on the purpose, viz. this depends on different molecular biology techniques and their effects. Over the last decade, interest in identifying genes or genomic regions targeted by selection has grown. Identifying selection signatures can provide valuable insights into the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. Type characteristics are important for breed identification and classification and are also positively correlated with body weight. This study aimed to identify effective genes and genomic regions under positive selection signatures in different goat breeds using selection signature methods. For this purpose, FST and hapFLK analyses were performed using the genome-wide single nucleotide polymorphisms (SNPs).
In this research, the information from 728 goats of four different breeds was used to identify genomic regions associated with type traits. To determine the genotype of the samples, Illumina caprine Bead Chip 50K was used. The genomic information of goat breeds was extracted from the Figshare database. Quality control was performed using the Plink software. The markers or individuals were excluded from further study based on the following criteria: unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) <0.05, and a P-value for Hardy-Weinberg equilibrium test less than 10-3. After quality control, 36861 SNPs from goat SNP chip 50K from 691 goats remained for further analysis. To identify the signatures of selection, two statistical methods of FST and hapFLK were used under the software packages FST and hapFLK, respectively. Candidate genes were identified using the Plink v1.9 software and the Illumina gene list in R by SNPs located in the highest  FST and hapFLK values. In addition, the latest published version of the animal genome database was used to define QTLs associated with economically important traits at identified loci. The GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes.
The FST and hapFLK statistics were used to identify genomic regions subjected to positive selection associated with type traits in four goat breeds. Using the FST approach, we identified eight genomic regions on chromosomes 3, 4, 7, 13, 15, 18, 20, and 29. The identified candidate genes associated with type traits in these genomic regions included TGFBR3, CALCR, ACAD8, BCAR1, and ADAMTS6. Some of the genes located in the identified selection regions were directly and indirectly related to cell differentiation and proliferation, skeletal muscle growth and development, body length, calcium channel regulation, muscle fiber homeostasis, protein synthesis, and muscle cell size. Some of these genes in the selected regions were consistent with previous studies. The results of the reported QTLs in the selected regions and the bovine orthologous regions were QTLs located in the identified regions that were related to average daily gain, body weight, trunk width, and metabolic body weight. Furthermore, the results of the hapFLK statistics in this research led to the identification of five genomic regions on chromosomes 1, 5, 6, 13, and 30, and they were in the 99.9th percentile of all hapFLK values. The identified candidate genes associated with the type trait in these genomic regions included FNDC3B, STAB2, and CCNY. They were found to have different functions in fibroblast proliferation and bone cell differentiation.
Various/different genes that emerged in studied regions can be considered candidates for selection based on their function. By the way, various genes found in these regions can be considered candidates for selection based on their function. Most of the selected genes were found to be consistent with some previous studies and to be involved in production traits. A survey of extracted QTLs also found that these QTLs are involved in some economically important traits in goats, such as average daily gain and body weight in yearlings. However, further association and functional studies are required to demonstrate the importance of the genes obtained from association analyses. Leveraging these findings can accelerate genetic progress in breeding programs and help understand the genetic mechanism that controls these traits.
In this research, to identify genomic regions under selection associated with type traits were used the information obtained from 728 goats of different breeds including Beetal, Daira Deen Panah, Barbari, Teddi, In order to determine the genotype of the samples, Illumina caprine Bead Chip 50K were used. The genomic information of goat breeds was extracted from the figshare database. Quality control was conducted using the Plink software. The markers or individuals were excluded from the further study based on the following criteria: unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) < 0.05, and a P-value for Hardy–Weinberg equilibrium test less than 10-3. After quality control, 36,861 SNPs from Goat SNP chip 50K on 691 goats were remained for the future analysis. To identify the signatures of selection, two statistical methods of FST and hapFLK were used under FST and hapFLK software packages, respectively. Candidate genes were identified by SNPs located at 1% upper range of FST and hapFLK using Plink v1.9 software and the gene list of Illumina in R. Additionally, the latest published version of Animal genome database was used for defining QTLs associated with economic important traits in identified locations. GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes. We used the FST and hapFLK statistics to identify genomic regions that have been under positive selection associated with type traits in four goat breeds. Using FST approach, we identified eight genomic regions on chromosomes 3, 4, 7, 13, 15, 18, 20, and 29 chromosome. The identified candidate genes associated with type trait in these genomic regions included TGFBR3, CALCR, ACAD8, BCAR1, ADAMTS6. Some of the genes located in identified regions under selection were associated with the cell differentiation and proliferation, skeletal muscle growth and development, body length, calcium channel regulation, muscle fiber homeostasis, protein synthesis and muscle cell size which can be directly and indirectly related to the trait of the type traits. Some of these genes in the selected regions were consistent with previous studies. Result of the reported QTLs in the selected regions and the orthologous regions of cattle were located in the identified regions, QTLs related to average daily gain, body weight, rump width and body metabolic weight. Also, the results of hapFLK statistics in this research led to the identification of five genomic regions on chromosomes 1, 5, 6, 13, and 30, and they were in the 99.9 percentile of all hapFLK values. The identified candidate genes associated with the type trait in these genomic regions included FNDC3B, STAB2 and CCNY. It was determined that they had different functions in proliferation of fibroblasts and differentiation of bone cells. Result of the reported QTLs in the selected regions and orthologous cattle in the identified regions, QTLs related to metabolic body weight were located. various genes that were founded within these regions can be considered as candidates under selection based on function. Most of the genes under selection were found are consistent with some previous studies and to be involved in production traits. Also, survey on extracted QTLs was shown that these QTLs involved in some economical important traits in goat such as average daily gain and body weight in yearling. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes and survey on QTLs related to selected regions. However, will be necessary to carry out more association and functional studies to demonstrate the implication of genes obtained from association analyses. Using these findings can accelerate the genetic progress in the breeding programs and can be used to understand the genetic mechanism controlling this trait.

Selective honey bee breeding is a phenomenon that fascinates beekeepers around the world. They often regard it as one of the most enigmatic and complex aspects of beekeeping. Indeed, according to our experiences participating in many international projects, both beekeepers and bee experts without a background in plant or animal breeding often have trouble correctly interpreting and conceptually visualizing the breeding process. These difficulties arise partly because of the complex reproductive biology of honey bees, where queens mate with a multitude of drones. Fundamentally the greatest struggle for people to understand is how selection of animals with preferred characteristics in one generation leads to improved progeny in the next. The leading misconception regarding honey bee breeding is confusing breeding with the simple rearing and multiplication of queens, where individual queens are evaluated predominantly by their egg laying ability and body size. Those two markers of queen quality (fecundity and size) are certainly important for the propagation of queens, but selective breeding requires more than propagation. Selectivebreeding implies the intentional selection for genetic improvement of the population as a whole, with every new generation improved compared to the previous one, ideally for all traits of interest.

Artificial and natural selection not only increases the frequency of new-useful mutations but also remains some signals throughout the genome. Since these regions often control economically important traits, identifying and tracking these regions is the most important subject in animal genetics. Also, natural and artificial selection related to adaptation and economic traits, such as litter size, results in changes at the genomic level which leads to the appearance of selection signatures. Several tests including the linkage disequilibrium-based approach, site frequency spectrum, and population differentiation-based approach have been developed to explore the footprints of selection in the genome. Domestication and selection have significantly changed the behavioral and phenotypic traits in modern domestic animals. The selection of animals by humans left detectable signatures on the genome of modern sheep. The identification of these signals can help us to improve the genetic characteristics of economically important traits in sheep. Over the last decade, interest in the detection of genes or genomic regions that are targeted by selection has been growing. Identifying signatures of selection can provide valuable insights about the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. One of the best ways to understand physiological processes is to analyze gene regulation networks. Identification of genes involved in economic traits as molecular markers in breeding is of special importance. Gene regulation networks enable the researcher to study all of the genes together. This study aimed to identify selection signature regions and candidate genes related to adaptation and the number of lambs born.
To identify the signatures of selection in Iranian native sheep and Egyptian breeds, genomic information of 96 native sheep (including 96 Zandi) and 107 Egyptian sheep (including 59 Barki and 48 Rahmani) were used. The genomic information of foreign breeds was extracted from the Dryad database (https://dryad.com/articles/dataset). To determine the genotype of the samples, Illumina Bead Chip 50K was used. Quality control was conducted using the Plink software. The markers or individuals were excluded from the further study based on the following criteria: unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) < 0.05, and a P-value for Hardy–Weinberg equilibrium test less than 10-6. After the quality control of the data, the hapFLK statistical method, with hapFLK v1.4 software, was used to identify selection signatures. The genomic version of the Oar_v4.0 database in NCBI was used for detecting the genomic position of single nucleotide polymorphisms (SNPs) in the sheep genome. Candidate genes were identified by SNPs located at 0.1% upper range of hapFLK using BioMart software in ensemble 109. Then, using the PANTHER database, the general biological function of the genes was checked. At this stage, it is assumed that genes that belong to a functional class can be considered as a group of genes that have some specific and common characteristics, and the QTLs in the selected region were extracted using the Animal Genome database, and the genes were compared with other research. GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes.
Based on the results of hapFLK, by comparing the Zandi population with Egyptian breeds (Barki and Rahmani), seven genomic regions on chromosomes 1, 2 (three regions), 10, 25, and 26 were identified. Candidate genes of DNAJB4, FNDC3B, GULP1, ACVR1, and FGF9 were in these regions. Further investigation using bioinformatics tools showed these genomic regions overlapped with the immune system, adaptation, litter size, and lipid and muscle metabolism.
The results of this study may provide an important source to facilitate the identification of genomic regions and then, the genes affecting economically important traits in the sheep industry. However, it will be necessary to carry out more association and functional studies to demonstrate the implications of these genes. Therefore, in subsequent studies with more samples and more breeds of domestic and wild sheep in Iran, a better understanding of candidate genes for important economic traits in domestic and wild species would be achieved.

The purpose of this study was to investigate the effect of different rates marker genotyping error and the type of mating and selection design (breeding value and phenotypic) on the accuracy of genomic prediction assessment under different levels of heritability (0.05, 0.1 and 0.3) and marker density (500, 1000 and 1500) by simulation in threshold trait. The genome consisted of two chromosomes, each 100 cM, and 125 QTLs were randomly distributed on each chromosome. In order to simulation a threshold trait, 20 percent of the top-level phenotypes were considered to be 2, and the rest were considered as 1. Genomic breeding value was predicted using marker effects estimated by Bayes B statistical method. Comparison of the accuracy of genomic evaluations showed that selection and mating designs of breeding value was more accurate than the selection and mating designs of phenotypic. The accuracy of genomic prediction decreased with increasing marker genotyping error in both selection and mating designs of breeding value and phenotypic. The results showed that with increasing the percentage of marker genotyping error, increasing the number of markers leads to increasing the accuracy of genomic breeding value prediction.

Performance of native fowl can be improved by making changes in feeding, rearing and health issues. On the other hand, genetic improvement of these breeds can be achieved through the breeding programs such as selection, crossbreeding, or both. Selection programs may be time consuming, but implementing them will lead to a continued improvement (Padhi 2016). Considering the genetic diversity among the native fowl breeds of Iran, several breeding stations were established in different provinces of the country for the purpose of reproduction and genetic improvement of these breeds. Mating related animals in closed populations leading to accumulated inbreeding and reduced genetic diversity has destructive effects on additive genetic variance and phenotypic values (Falconer and Mackay 1996). Inbreeding is associated with an increase in homozygosity and usually decrease the fitness of individuals in the population, which is referred to as inbreeding depression (Ayroles et al. 2009). Inbreeding depression in domestic animals can cause reduced selection response and potential genetic gain in economic traits (Selvaggi et al. 2010). Since the improved Fars native fowls have been raised in a closed population and selected for some important economic traits during the successive generations, their inbreeding coefficients may increase and reduce the effectiveness of breeding programs. Therefore, it is of significant importance to monitor the inbreeding rate and its consequences on different traits. The purpose of this study was to monitor the inbreeding rate and evaluate its possible effects on some important economic traits in improved Fars native fowl population using the pedigree information of 25 generations via different models.

Data of 63250 birds during the period 1369-1397 (25 generations) recorded in the breeding station of Fars native fowl were included in the study. Studied traits include body weight at hatch (BW1), body weight at 8 weeks of age (BW8), body weight at 12 weeks of age (BW12), age at sexual maturity (ASM), weight at sexual maturity (WSM), egg weight at 1st day of laying (EW1), egg number (EN) and average egg weight (AEW). Individual and maternal inbreeding coefficients of all birds estimated using the CFC program. Estimated inbreeding coefficients grouped into seven different categories of inbreeding: 0, 0 to 5%, 5 to 10%, 10 to 15%, 15 to 20%, 20 to 25% and 25 to 30%. Regression coefficients of studied traits on individual and maternal inbreeding percentage were estimated by Wombat software (May 2007) and restricted maximum likelihood (REML) method using six different models. Individual and maternal inbreeding coefficients were also included as a covariate in the model. In this study, among the six statistical models considered for each trait, finally, the appropriate model for each of them was selected through three methods of likelihood ratio test (LRT), Akaike’s information criterion (AIC) and Bayesian information criterion (BIC).

Pedigree analysis showed that 40184 birds were inbred and the mean of individual and maternal inbreeding was relatively low over 25 generations. The average individual and maternal inbreeding did not differ much over the generations. According to the results, the mean inbreeding for all birds was approximately equal to 2 % and in inbred birds was 4 %. From the fifth generation onwards, the average inbreeding (individual and maternal) of birds in the whole population was increasing. In the first four generations, inbreeding rate of population was estimated to be zero, which may be due to the unknown pedigree information in the first generations. Various studies have shown that accurate estimation of inbreeding is highly dependent on pedigree information. The results of a previous study on laying hen strains indicated that pedigree information influenced the inbreeding estimation in the first generations (Szwaczkowski et al. 2003). In another study, Cassell et al. (2003) reported that the use of incomplete pedigree in estimating the mean inbreeding reduces the mean inbreeding estimate and the variance of these estimates in cows. From the fifth to eighth generation, the rate of individual and maternal inbreeding was very small. Distribution of birds in different categories of inbreeding showed that 36.57 % (23066 birds) were non-inbred. Classifying birds into different inbreeding groups indicated that the highest number of inbred birds was in the inbreeding group 0 to 5 % (47.72 %) and 5 to 10 % (15.48 %). Although the number of inbred birds is high, but the amount of inbreeding coefficient is significantly low, reflecting careful planning of mating in the station. The study of Kamali et al. (2007) on the pedigree information of Fars native fowl (21245 birds) during eight generations demonstrated that the inbreeding rate is low. In addition, in the previous study on the improved Mazandaran native fowl during 26 generations, it was shown that the rate of inbreeding is relatively low, which is in accordance with the results observed in the present study (Ghorbani and Omrani 1399). According to the fitted models, model 5 for BW1, BW8 and BW12, model 6 for ASM and AEW, model 2 for WSM, model 4 for EN and EW1 considered as the most suitable model. Estimating the inbreeding depression in the studied traits revealed the most effect of inbreeding on the BW12, so that for every 1 % increase in individual inbreeding, BW12 is reduced by 2.14 grams. Also, for every one % increase in individual inbreeding, BW8 decreases by 1.07 grams. The highest effect of inbreeding was observed on BW8 and BW12, so that for every 1 % increase in individual inbreeding, BW12 decreases by 2.14 grams and BW8 decreases by 1.07 grams. ASM was significantly affected by inbreeding depression. ASM increased by 0.38 day per 1 % increase in inbreeding. The finding of earlier studies regarding the inbreeding effect on the ASM have shown that increased inbreeding does not have the same effect on different strains. For example, increase in inbreeding level results in increased ASM in the Leghorn (Sewalem et al. 1999) and decreased ASM in the New Hampshire (Szwaczkowski et al. 2003). Taken together, pedigree analysis showed that the depression effect of inbreeding on egg traits including EN, EW1 and AEW was negligible.

According to the results of pedigree analysis, inbreeding rate of improved Fars native fowl population is increasing at an acceptable level with a relatively gentle slope. In addition, depression caused by inbreeding in the population was fairly low. Since maintaining genetic diversity and keeping down the inbreeding rate in the station are considered as main factors in developing the breeding programs, it can be concluded that the implementation of breeding programs and selection of superior birds during the generations has gone in the right direction.

 Introducing new commercial lines is one of the goals of silkworm breeding centers in the world. Iran has the potential to introduce new lines for hybrid silkworm production due to its silkworm genetic resources and silkworm egg production technology. The performance of productive, reproductive and viability traits in the parental silkworms, including Japanese-shaped and Chinese-shaped lines, changes after several years for various reasons, including inbreeding. Therefore, after a few years, it is necessary to introduce new silkworm strains. Most silkworm breeding schemes in most of the countries are based on the introduction of the Chinese and Japanese-shaped lines to make commercial silkworm hybrid.

 Five Japanese - shape lines of silkworms named 31, 103, 151, 153, and 1524 were selected from silkworm germplasm of Iran Silk Research Center in the spring of 2012. All genetic combinations obtained by using the diallel method of mating system (20 crosses) were reared in autumn 2012 and spring 2013. After two generations of mass rearing in each genetic combination, the reciprocal crosses in the diallel design were mixed to establish the basic generation of this breeding scheme. The selection program was based on independent culling levels (I.C.L.) method applied from 2014 to 2019 in the selected group. At the same time, all parental lines were reared as control by using a random mating system. Of the 10 genetic compounds, six combinations were retained and the rest were rejected. In this breeding program, due to the necessity of eliminating weak families, family selection, and individual selection were both used simultaneously. In the present study, the productive traits of cocoon weight, cocoon shell percentage, good cocoon percentage, number of cocoons per liter, and cocoon weight per liter were compared simultaneously in the genetic combinations and control lines. Two-factor analysis of variance (including 6 genotypes and 5 years) was performed in a completely randomized design with six replications; then the results were analyzed using SAS statistical software.

In general, the effects of genotype, year and interaction effect of genotype and year were significant for all studied traits. Based on the average performance of each trait during selection program from 2016 to 2019 years (average performance of G2, G3, G4 and G5 generations), the cocoon weight in the combinations of IRA1, IRA11 and IRA7 was more than the parental lines. This advantage was also seen in the trait of cocoon weight per liter. For the cocoon shell percentage, none of the genetic combinations in all the studied years were completely superior to parents. The response to selection for cocoon weight based on deviation from the maternal control line in IRA5 and IRA1 was positive and significant. The two genetic compounds, IRA1 and IRA3, whose parent was 103, had the highest genetic progression for cocoon shell percentage. Due to the superiority of the good cocoons percentage in IRA1, this genetic combination performed well in terms of cocoon economic traits. IRA9, whose cocoon weight gain was lower than the others, not only did not show any improvement in cocoon shell weight compared to the parent during these years, but also showed the lowest amount compared to other genetic combinations.

 The six new genetic compounds in this breeding program had the minimum requirements for the economically important traits of the silkworm. In other words, cocoon-related characteristics such as cocoon weight, good cocoon percentage of each family, and cocoon size are superior to all parental lines, then they could introduce to the silkworm gene bank. IRA1 was superior to parents in most of the studied traits. This genetic combination showed the best performance compared to the parent for both cocoon weight and cocoon shell percentage. Therefore it can be considered more in subsequent evaluations. IRA3 also responded relatively well. Other new genetic combinations did not have a significant advantage over their parents in terms of cocoon shell percentage. However, lower performance in some traits is not a reason for the new strain to be undesirable. Because the selection of the best paternal and maternal lines (Chinese-shaped and Japanese-shaped lines) will be determined after that the hybridization program was carried out to produce all hybrids and then the best hybrids were selected based on  estimation of specific combining ability for all important traits.

The optimization of the reference population in genomic evaluation plays an important role in livestock breeding, because of its potential impact on the accuracy of estimating the marker effects and genomic breeding values. In the present study, seven different train set selection methods including selection of all, selection of the highest and lowest performances, random selection, selection of individuals with the most and least marker and QTL similarity were evaluated. In genome wide association study selection of all as train set detected common SNPs which make a high variation on the trait. However selective train set was just reported rare SNPs with a major effect on the trait. In genomic selection simultaneous use of high-density markers and selective train set in comparison with low-density and selection of all as train set reduced accuracy, but did not change the ranking of animals. There was also an interaction between train set selection method and generation (P≤0.0134) as well as the linkage disequilibrium (P≤ 2e-16). In general, selection of all animals as a train set resulted in higher accuracy compared to six selective train set methods. There were no differences between the methods of selecting train set in populations with a low effective size (r2 = 0.255, Ne =100), but in populations with a high effective size (r2 = 0.086, Ne =400) methods, with different accuracy predicted genomic breeding values. The highest and lowest accuracy were respectively belonged to most QTL and marker similarity methods.

The objectives of this research were to simulate and optimize three open nucleus breeding schemes for improvement of growth traits and carcass composition in Lori-Bakhtiari lambs with 500 ewes in nucleus using a deterministic approach. These schemes were: scheme 1 with natural mating and mating ratio (M) of 50 ewes per ram in nucleus and member flocks (base), scheme 2 with artificial insemination in nucleus (M=250) and natural mating in base (M=50) and scheme 3 with artificial insemination in nucleus (M=250) and base (M=500). An economic selection index with accuracy of 0.42 was envisaged for base and one with accuracy of 0.67 for nucleus. Advantage of open nucleus over closed nucleus for schemes 1, 2 and 3 was different but optimal relative sizes and monetary genetic lags were 7.5, 5.7 and 8 percent, respectively. With equalization of the monetary genetic lags )sub-optimal( for schemes 1 and 2 being equal to the lag of optimum scheme 1, their base population sizes were 1.035 and 3.1 times the base size of optimum scheme 1 and their monetary genetic gains were 18.9 and 21.1 percent greater than the gain of the latter scheme, respectively. In the above sub-optimal situation, the base population size of scheme 3 was 3 times that of scheme 2, its monetary genetic gain being 1.91% greater. Shifting from traditional system with selection based on body weight at 6 months of age to schemes 1, 2 and 3 with same monetary genetic lags, the monetary genetic gain increased 84.3, 119.12 and 123.3 percent, respectively. However, due to the similarity of the monetary genetic gains of schemes 2 and 3 at the same monetary genetic lags and the higher practicability of scheme 2, implementation of this scheme for ease of initiation and promotion of the open nucleus breeding system was recommended.

In this study, selection strategies were simulated to find optimal selection strategy in Japanese quails. Breeding goal was consisted of body weight and egg weight traits. Effects of using genetic markers related to carcass weight were investigated by five different selection strategies. In this case, breeding goal included body weight, egg weight and carcass weight. Deterministic simulation, based on single stage selection and discrete generation, was used for predicting genetic gain and rate of inbreeding. In the first (base) program, phenotypic information was available on body and egg weights. In the second program, information on body and egg weights along with carcass weight were included in selection index and in the third program, with taking into account the indirect carcass measurements in selection index, including breast weight and back weight, genetic gain was increased for body weight compared with two previous mentioned programs. Genetic gain for body weight was decreased by including indirect carcass measurements in selection index. In marker assisted selection programs, QTL information that described 5, 10, 20 and 50% of genetic variation in carcass weight was also included in selection index. In the next step, within the first breeding program which assumed QTL described 5% of genetic variance for carcass weight, genetic progress of carcass weight was increased 3.1% in relation to base program. This increasing trend was observed for other cases with different values of genetic variance described by assumed QTL. In the fourth program which assumed QTL described 50% of genetic variance for carcass weight, this increase reached to 42%. Genetic response for carcass weight was increased appropriately with considering different values of genetic variance due to QTL. Therefore, the use of QTL information resulted in increase in the accuracy of breeding values and it could be possible to select genetically superior candidates with greater reliability values.

A study with 56 male lambs of Lori-Bakhtiari sheep breed was carried out to investigate the effect of selection to decrease fat on the fatty acids composition in the subcutaneous fat and fat-tail adipose tissue. Subcutaneous fat and fat-tail fat samples were obtained from the back of left side of carcass and fat-tail, respectively. Total 112 samples of subcutaneous fat and fat-tail adipose tissue were obtained from 56 carcasses at six month of age. The fatty acid composition of subcutaneous fat and fat-tail were analyzed after fat extraction by gas chromatography. Data were analyzed using SAS statistical program. Proportion of palmitic (C16:0) in fat tissue significantly (P<0.05) decreased and linoleic (C18:2) significantly increased at the end of the selection program.While body weight lambs was higher at the end of the selection program, unsaturated fatty acids was higher in carcass fat. Ratios of poly unsaturated fatty acids to saturated fatty acids were significantly higher incarcass fat at the end of the selection. Desirable fatty acids and ratio of (C18:0+C18:1)/C16:0 did not significant increase at constant weight. Proportion of palmitic (C16:0), stearic (C18:0)and total saturated fatty acids were significantly higher in subcutaneous fat but oleic fatty acid (C18:1)was significantly higher in fat-tail. Ratios of unsaturated fatty acids to saturated fatty acids, desirable fatty acids and ratio of (C18:0+C18:1)/C16:0 were significantly (P<0.05) higher in fat-tail than subcutaneous fat at constant weight. Inconcluded, selection for decreased carcass fat cause improve fatty acid composition of fat tissue.

This study was carried out to investigate the effect of selection on the reduction of fat-tail size in Lori-Bakhtiari lambs. The study lasted for five years at the Development and Breeding center of Lori-Bakhtiari Sheep Station. Estimation of fat-tail weight, using external fat-tail dimensions was obtained from regression procedure at 6 month age. Soft tissue depth at the point 12 cm from the midline dorsal body on 12th ribs at the age of six months (using an animal model of Scanner Device 480) was determined. Components of (co) variance and genetic parameters were estimated using multivariate animal model and a restricted maximum likelihood approach. Selection as based on economic selection index of multiplying a vector of breeding value traits by vector of economic values of traits was conducted. Coefficients of 1 and -4 for the economic value of body weight and estimation of fat-tail weight traits were applied. Phenotypic and genetic trends were obtained through regression means of phenotype while breeding values on year of birth for each trait being predicted. The results showed that average of fat-tail weight (estimated at the age of six months) in lambs amounted to 2.37 kg. The estimates of heritability and standard error fat-tail amounted to 0.33 ± 0.05. Genetic trend of body weight at the six months of age was 160 gr. The genetic trend of fat-tail weight was estimated as -40 gr, with a high coefficient of determination of 0.94. Depth of soft tissue from ultrasound and at six months of age was accompanied by a negative genetic trend (-0.024 mm). Change of phenotype of body weight and ultrasound soft tissue depths were estimated as positive and more than genetic variations. However, phenotypic trend reduction of fat-tail weight as compared with the genetic trend stood at a lower level.