Papers by Mohammad Shariati
This research was carried out to study of productive and reproductive traits (milk (Milk), fat yi... more This research was carried out to study of productive and reproductive traits (milk (Milk), fat yield and percentage (Fat and FatP), protein yield and percentage (Pro and ProP), lactation length (LL), dry period (DP), age at first calving (AFC) and calving interval (CI)) of Holstein dairy cows in arid and semi aridclimate of Iran. Data were collected of 4805 and 58781 first lactation Iranian Holstein dairy cows in arid and semi-arid climate, respectively during 1996 to 2009 by the Animal Breeding Center of Iran. Variance components were estimated by restricted maximum likelihood method using DMU package. The estimated heritabilities in arid and semi-arid climate were 0.23, 0.27, 0.39, 0.28, 0.41, 0.04, 0.006, 0.23 and 0.04 of production and reproductive traits (Milk, Fat and FatP, Pro and ProP, LL, DP, AFC and CI), respectively and 0.21, 0.18, 0.08, 0.11, 0.34, 0.03, 0.02, 0.10 and 0.05, respectively. The current result showed least square mean of traits in semi-arid climate was higher than arid climate for all traits and it can be due to better management practices however for CI trait should be less(P<0.05).
Global Journal of Animal Scientific Research, Feb 5, 2015
پژوهشهای علوم دامی ایران, Nov 12, 2019
The computation time of Bayesian neural networks was increased with an increase in the number of ... more The computation time of Bayesian neural networks was increased with an increase in the number of neurons in the hidden layer. The computation time of the parametric methods was the same with the exception of GBLUP. The GBLUP method took more computation time. The computation time of neural the networks with 1 to 2 neurons in the hidden layer were less than GBLUP. Genomic prediction using Bayesian Neural Networks with a greater number of neurons is really challenging, and improving their performance in terms of computational cost is necessary before applying them in genomic selection. Conclusion Although parametric methods had better predictive accuracy and predictive ability due to the additive genetic architecture of the studied traits, it can be concluded that Bayesian neural networks are powerful tools in genomic enabled prediction that can predict genomic breeding values with acceptable accuracy. The genomic prediction ability of the neural networks depends on target traits, the animal species, and neural network architecture. Before using Bayesian neural networks in genomic prediction, it is better to compare the results with parametric methods. It is also necessary to improve the computation time of the Bayesian neural networks with a greater number of neurons in hidden layer before applying them in real application of genomic selection.
For some diseases or other phenotypes it is not only interesting to identify which genes are invo... more For some diseases or other phenotypes it is not only interesting to identify which genes are involved but also to find the involved processes or pathways. This is often done using sets of genes such as genetic pathways found in KEGG: Kyoto Encyclopedia of Genes and Genomes (Kanehisa, M., and Goto, S. (2000)). Typically a gene set analysis is performed, for example using methods like the gene set enrichment analysis (Mootha, V.K, Lindgren C.M., and Eriksson K.F. et al. (2003) Subramaniana, A., Tamayoa, P., and Moothaa, V.K. et al. (2005)).
Iranian Journal of Applied Animal Science, 2020
In order to have successful application of genomic selection, reference population and marker den... more In order to have successful application of genomic selection, reference population and marker density should be chosen properly. This study purpose was to investigate the accuracy of genomic estimated breeding values in terms of low (5K), intermediate (50K) and high (777K) densities in the simulated populations, when different scenarios were applied about the reference populations selecting. After simulating the historical (undergoing drift and mutation) and recent (undergoing selection) population structures, 800 individuals were remained in reference population. Three scenarios were considered for reducing the reference population number including: 1) 400 individuals which had the highest relationships with the validation set, 2) 400 individuals which had the highest inbreeding, and 3) 400 selected individuals by random. The genomic breeding values were predicted for traits with two heritability levels (0.25 and 0.5) using best linear unbiased prediction (BLUP) with different mark...
To determine the role of DDX3Y gene in spermatogenesis and infertility in bulls, blood samples we... more To determine the role of DDX3Y gene in spermatogenesis and infertility in bulls, blood samples were collected from five infertile bulls (azoospermic; no sperm in the semen) at the Animal Breeding Center in Karaj, Iran. The recommended human primers by EAA/EQMN were investigated using the BLASTn database for STS marker detection. Alignment of STS marker genes with bovine genome was performed. Primer Premier 5 and CLC Main Workbench 5.5 softwares were used in designing common primer for the bovine and human DDX3Y gene. Genomic DNA screening of peripheral blood was conducted for detection of DDX3Y gene deletion in the Y chromosome by the PCR method. The bioinformatics analysis of human binding-primers of STS markers indicated that there was no chance connection and target fragment production for bovine samples. Investigation of DDX3Y gene on fertile bovine samples showed that the designed primer could detect the target gene as well. The results showed that three bulls had partial delet...
PLOS ONE, 2019
Genomic imprinting results in monoallelic expression of genes in mammals and flowering plants. Un... more Genomic imprinting results in monoallelic expression of genes in mammals and flowering plants. Understanding the function of imprinted genes improves our knowledge of the regulatory processes in the genome. In this study, we have employed classification and clustering algorithms with attribute weighting to specify the unique attributes of both imprinted (monoallelic) and biallelic expressed genes. We have obtained characteristics of 22 known monoallelically expressed (imprinted) and 8 biallelic expressed genes that have been experimentally validated alongside 208 randomly selected genes in bovine (Bos taurus). Attribute weighting methods and various supervised and unsupervised algorithms in machine learning were applied. Unique characteristics were discovered and used to distinguish mono and biallelic expressed genes from each other in bovine. To obtain the accuracy of classification, 10-fold cross-validation with concerning each combination of attribute weighting (feature selection) and machine learning algorithms, was used. Our approach was able to accurately predict mono and biallelic genes using the genomics and proteomics attributes.
Livestock Science, 2011
This article appeared in a journal published by Elsevier. The attached copy is furnished to the a... more This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright
The objective of this study was to compare the accuracy of genomic breeding values prediction wit... more The objective of this study was to compare the accuracy of genomic breeding values prediction with different marker densities before and after the imputation in the simulated purebred and crossbred populations based on different scenarios of reference population and methods of marker effects estimation. The simulated populations included two purebred populations (lines A and B) and two crossbred populations (Cross and Backcross). Three different scenarios on selection of animals in the reference set including: (1) A high relationship with validation population, (2) Random, and (3) High inbreeding rate, were evaluated for imputation of validation population with the densities of 5 and 50K to 777K single marker polymorphism. Then, the accuracy of breeding values estimation in the validation population before and after the imputation was calculated by ABLUP, GBLUP, and SSGBLUP methods in two heritability levels of 0.25 and 0.5. The results showed that the highest accuracy of breeding v...
Genotype imputation from low-density to high-density (SNP) chips is an important step before appl... more Genotype imputation from low-density to high-density (SNP) chips is an important step before applying genomic selection, because denser chips can provide more reliable genomic predictions. In the current research, the accuracy of genotype imputation from low and moderate-density panels (5K and 50K) to high-density panels in the purebred and crossbred populations was assessed. The simulated populations included two purebred populations (lines A and B) and two crossbred populations (cross and backcross). Three scenarios were assessed for selecting the subset of the references that used to impute un-genotyped loci of animals in the validation set, where: 1) high relationship with validation set, 2) randomly, and 3) high inbreeding selecting. Imputing the individuals of validation set 5K and 50K to marker density 777K using the various combinations of reference set was performed by FImpute software. The imputation accuracies were calculated using two methods including Pearson correlatio...
Revista Colombiana de Ciencias Pecuarias, 2018
Evaluación genética de las características de supervivencia y productividad en ovinos cruzados Ar... more Evaluación genética de las características de supervivencia y productividad en ovinos cruzados Arman Avaliação genética de características de sobrevivência e produtividade em ovinos mestiços Arman
Research on Animal Production, 2016
The effects of herd size, semen type, generation overlapping and breeding goal on genetic gain in... more The effects of herd size, semen type, generation overlapping and breeding goal on genetic gain in Holstein cows were studied through stochastic simulation. Three levels of herd size (100, 200, and 400), two levels of semen type (unsexed and sexed), three levels of generation overlapping (low, average and high) and two levels of breeding goal (narrow and broad) were combined together to make 36 scenarios. A base population of 5000 cows recorded for 6 traits (milk, fat and protein production, age at first calving, calving interval and somatic cell score) were simulated for 30 years. Each year 50 young bulls, 10 active sires and 200 bull dams were selected from the population based on economical selection index. The genetic gain changes, inbreeding rate and generation interval were examined for all scenarios. The results showed that genetic gain for broad breeding goal, unsexed semen, herd size 400 and low generation overlapping were higher by 0.6, 3.6, 0.4, 0.5 percent compared with narrow breeding goal, sexed semen, herd size 100 and high generation overlapping, respectively. Inbreeding changes for broad breeding goal, unsexed semen, herd size 100 and average generation overlapping were more than the other levels of these factors. Estimated breeding value for cow dams (CD) were 34.3 % higher when sexed semen was used compared with the unsexed semen. These results were suggested that broad breeding goal, large herd size, sexed semen and high generation overlapping should be noticed in Holstein selection programs.
Biosciences, Biotechnology Research Asia, 2016
The objective of present study is analyzing genetic diversity among three Arab, Baloch and Gadic ... more The objective of present study is analyzing genetic diversity among three Arab, Baloch and Gadic breeds using selected markers. Mutual comparisons of each two breeds were conducted to detect and accurately analyze differences between breeds.. 45 blood samples were collected from three districts of Herat province (Shindand, Gulran and Obe) of three Afghan sheep breeds (Arabi, Baloch and Gadic). 10 µL of blood was collected via the jugular vein in Venoject tubes with EDTA (Ethylene Diamine Tetraacetic Acid) for prevention of blood coagulation and immediately stored in a refrigerator at 4 °C. DNA was extracted from blood using the GenElute™ Blood Genomic DNA Kit. DNA concentration was determined using NanoDrop (Spectrophotometer ND-1000). In this research haplotypic blocks analysis in experimental regions, the way of their erosions and LD graphs are drawn using Haploview v4.2 software. Required information as inputs for this software consisted of genotypic information of markers in experimental regions similarly; the statistics that are used for LD calculation are the same correlational coefficients between r2 and surrounding SNPs. A total of 15 Arabi, 15 Baloch and 15 Gadic sheep breed were genotyped at 53862 SNP loci with the Ovine SNP chip50K Bead chip (http://www.illumina.com). usually those SNP that had been assigned to the 26 autosomes and X chromosome was measured) Then for each SNP, minor allele frequency (MAF) (over all animals) less than 2% were removed and percentage of calls rate ? 95% (how many sheep the marker worked for) was removed (Teo YY, Fry AE, Clark TG, Tai ES, Seielstad M: On the usage of HWE for identifying genotyping errors. Annals of Human Genetics 2007, 71:701-703). Biodiversity is usually described in terms of three intimately connected levels, namely Species diversity, Genetic diversity, Ecosystem diversity. Considering excess of heterozygosity within studied breeds, one can conclude that these breeds are not threatening in terms of heterozygosity decline and can be considered as an appropriate genetic reserve for different husbandry and eugenic purposes in Afghanistan. Furthermore high heterozygosity in studied chromosomes in Arab, Baloch and Gadic breeds suggest high diversity within population in spite of carrying out eugenic activities on livestock due to managerial plans which has managed to reduce the consistency level and keep the diversity in acceptable level.
Genetic correlations among body condition score, yield and fertility in first-parity cows estimat... more Genetic correlations among body condition score, yield and fertility in first-parity cows estimated by random regression models. J.
BMC Bioinformatics, 2012
Background Genome-wide expression profiling using microarrays or sequence-based technologies allo... more Background Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been described. In many cases, these methods test one gene set at a time, and therefore do not consider overlaps among the pathways. Here, we present a Bayesian variable selection method to prioritize gene sets that overcomes this limitation by considering all gene sets simultaneously. We applied Bayesian variable selection to differential expression to prioritize the molecular and genetic pathways involved in the responses to Escherichia coli infection in Danish Holstein cows. Results We used a Bayesian variable selection method to prioritize Kyoto Encyclopedia of Genes and Genomes pathways. We used our data to study how the variable selection method was affected by overlaps among the pathways. In...
animal, 2012
Heritability is a central element in quantitative genetics. New molecular markers to assess genet... more Heritability is a central element in quantitative genetics. New molecular markers to assess genetic variance and heritability are continually under development. The availability of molecular single nucleotide polymorphism (SNP) markers can be applied for estimation of variance components and heritability on population, where relationship information is unknown. In this study, we evaluated the capabilities of two Bayesian genomic models to estimate heritability in simulated populations. The populations comprised different family structures of either no or a limited number of relatives, a single quantitative trait, and with one of two densities of SNP markers. All individuals were both genotyped and phenotyped. Results illustrated that the two models were capable of estimating heritability, when true heritability was 0.15 or higher and populations had a sample size of 400 or higher. For heritabilities of 0.05, all models had difficulties in estimating the true heritability. The two Ba...
From 15th European workshop on QTL mapping and marker assisted selection (QTLMAS) Rennes, Frances... more From 15th European workshop on QTL mapping and marker assisted selection (QTLMAS) Rennes, Frances. 19
Indian Journal of Animal Sciences, 2017
The aim was to compare predictive performance of SVM-based predictors constructed using different... more The aim was to compare predictive performance of SVM-based predictors constructed using different kernel functions (radial, sigmoid, linear and polynomial) in different genetic architectures of a trait (number of QTL, distribution of QTL effects) and heritability levels. To this end, a genome comprised of five chromosomes, one Morgan each, was simulated on which 10,000 bi-allelic single nucleotide polymorphisms (SNP) were distributed. Cross validation employing a grid search was used to tune the meta-parameters of each kernel function. Pearson’s correlation between the true and predicted genomic breeding values (rp,t) and mean squared error of predicted genomic breeding values (MSEp) were used, respectively, as measures of the predictive accuracy and the overall fit. Meta-parameter optimization had a significant effect on predictive performance of SVM-based predictors in such a way that by using improper meta-parameters, the predictive power of models decreased significantly. In all...
Frontiers in Genetics, 2018
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Papers by Mohammad Shariati