Genetic variance components of the growth curve for Isfahan indigenous chicken.

BACKGROUND: Being able to model a growth curve using three or four non-linear functional parameters could help explain the growth phenomenon in a precise way and would allow the comparison of an animal's development rate, optimize management and feeding strategies and guide animal production strategies. OBJECTIVE: The goal of this study was to estimate the genetic parameters of growth traits of Isfahan indigenous chicken in Iran and to determine the best non-linear model describing the growth curve. METHODS: The prediction of additive genetic parameters was performed using the REML method by WOMBAT. Direct heritability of the studied traits and genetic correlations between them were obtained. The Logistic, Gompertz, von Bertalanffy, Brody, Negative exponential, Weibull, Janoschek and Bridges models were compared based on the coefficient of determination (R2 ), mean square error (MSE) and akaike information criterion. RESULTS: The Gompertz model was identified as the best model for describing the growth curve for Isfahan native chicken. The heritability of maturity weights (A), initial weight (B) and maturity rate (K) parameters were 0.223 ± 0.002, 0.016 ± 0.005 and 0.087 ± 0.001, respectively. CONCLUSION: This study shows that Isfahan indigenous chicken has the genetic potential for improving growth and reproduction based on their desirable heritabilities and correlations using appropriate models.

Genetic analysis of growth curve in Moghani Sheep using Bayesian and restricted maximum likelihood.

This study was conducted to predict the genetic (co)variance components of growth curve parameters of Moghani sheep breed using the following information: birth weight (N = 7278), 3-mo-old weight (N = 5881), 6-mo-old weight (N = 5013), 9-mo-old weigh (N = 2819], and 12-mo-old weight (N = 2883). The growth parameters (A: maturity weight, B: growth rate, and K: maturity rate) were calculated using Gompertz, Logistic, Brody, and Von Bertalanffy nonlinear models via NLIN procedure of SAS software. The aforementioned models were compared using Akaike information criterion, root mean square error, adjusted co-efficient of determination. Also, both Bayesian (using MTGSAM) and RMEL (using WOMBAT) paradigms were adapted to predict the genetic (co)variance components of growth parameters (A, B, K) due to the best fitted growth models. It was turned out that Von Bertalanffy best fitted to the data in this study. The year of birth and lamb gender had a significant effect on maturity rate (P < 0.01). Also it turned out that within the growth parameter, with increasing (co)variance matrix complexity, the Bayesian paradigm fitted well to the data than the restricted maximum likelihood (REML) one. However, for simple animal model and across all growth parameters, REML outperformed Bayesian. In this way, the h2a predicted (0.15 ± 0.05), (0.11±.05), and (0.04 ± 0.03) for A, B, and K parameters, respectively. Practically, in terms of breeding plan, we could see that genetic improvement of growth parameters in this study is not a tractable strategy to follow up and improvement of the management and environment should be thoroughly considered. In terms of paradigm comparison, REML's bias correction bears up an advantageous approach as far as we are concerned with small sample size. To this end, REML predictions are fairly accurate but the mode of posterior distributions could be overestimated. Finally, the differences between REML and Bayesian estimates were found for all parameter data in this study. We conclude that simulation studies are necessary in order to trade off these parading in the complex random effects scenarios of genetic individual model.

The Iran plateau is known to be the origin of many sheep species nowadays. In Iran, different production systems are operated ranging from intensive to lower-input/extensive ones. However, the majority of these sheep breeds are extensively managed, where lambs are born outside and with little intervention and generally they experience frequent drought and shortage of nutritional value of forages. Meanwhile, the weight of lambs as a whole play a major decision role in rearing or culling them. However, investigations involving the possible genetic improvement of lamb weights over different periods of time have found low genetic variations. This study serves to be comprehensive in addressing this issue in Moghani sheep breed. Fitting many different genetics models over both restricted maximum likelihood and Bayesian paradigms indicated that heritability of weight spanned 0.03 to 0.23. The low genetic variation would lead to recommendations that the improvement of Moghani lamb weights should rather be based upon modification of the environment to create conditions suitable for weight of lambs. This reflects that breeders of Moghani sheep breed have less options to tackle Iran harsh conditions using Moghani sheep genetic potentials.

RNA-Seq Profiling between Commercial and Indigenous Iranian Chickens Highlights Differences in Innate Immune Gene Expression.

The purpose of the current study was to examine transcriptomic-based profiling of differentially expressed innate immune genes between indigenous and commercial chickens. In order to compare the transcriptome profiles of the different chicken breeds, we extracted RNA from blood samples of the Isfahan indigenous chicken (as indigenous) and Ross broiler chicken (as commercial) breeds. RNA-Seq yielded totals of 36,763,939 and 31,545,002 reads for the indigenous and commercial breeds, respectively, with clean reads then aligned to the chicken reference genome (Galgal5). Overall, 1327 genes were significantly differentially expressed, of which 1013 genes were upregulated in the commercial versus the indigenous breed, while 314 were more highly expressed in the indigenous birds. Furthermore, our results demonstrated that the SPARC, ATP6V0D2, IL4I1, SMPDL3A, ADAM7, TMCC3, ULK2, MYO6, THG1L and IRG1 genes were the most significantly expressed genes in the commercial birds and the PAPPA, DUSP1, PSMD12, LHX8, IL8, TRPM2, GDAP1L1, FAM161A, ABCC2 and ASAH2 genes were the most significant in the indigenous chickens. Of notable finding in this study was that the high-level gene expressions of heat-shock proteins (HSPs) in the indigenous breeds could serve as a guideline for future genetic improvement. This study identified genes with breed-specific expression, and comparative transcriptome analysis helped understanding of the differences in underlying genetic mechanisms between commercial and local breeds. Therefore, the current results can be used to identify candidate genes for further breed improvement.

Gene network reveals LASP1, TUBA1C, and S100A6 are likely playing regulatory roles in multiple sclerosis.

Introduction: Multiple sclerosis (MS), a non-contagious and chronic disease of the central nervous system, is an unpredictable and indirectly inherited disease affecting different people in different ways. Using Omics platforms genomics, transcriptomics, proteomics, epigenomics, interactomics, and metabolomics database, it is now possible to construct sound systems biology models to extract full knowledge of the MS and recognize the pathway to uncover the personalized therapeutic tools. Methods: In this study, we used several Bayesian Networks in order to find the transcriptional gene regulation networks that drive MS disease. We used a set of BN algorithms using the R add-on package bnlearn. The BN results underwent further downstream analysis and were validated using a wide range of Cytoscape algorithms, web based computational tools and qPCR amplification of blood samples from 56 MS patients and 44 healthy controls. The results were semantically integrated to improve understanding of the complex molecular architecture underlying MS, distinguishing distinct metabolic pathways and providing a valuable foundation for the discovery of involved genes and possibly new treatments. Results: Results show that the LASP1, TUBA1C, and S100A6 genes were most likely playing a biological role in MS development. Results from qPCR showed a significant increase (P < 0.05) in LASP1 and S100A6 gene expression levels in MS patients compared to that in controls. However, a significant down regulation of TUBA1C gene was observed in the same comparison. Conclusion: This study provides potential diagnostic and therapeutic biomarkers for enhanced understanding of gene regulation underlying MS.

A new gene tree algorithm employing DNA sequences of bovine genome using discrete Fourier transformation.

Within the realms of human thoughts on nature, Fourier analysis is considered as one of the greatest ideas currently put forwarded. The Fourier transform shows that any periodic function can be rewritten as the sum of sinusoidal functions. Having a Fourier transform view on real-world problems like the DNA sequence of genes, would make things intuitively simple to understand in comparison with their initial formal domain view. In this study we used discrete Fourier transform (DFT) on DNA sequences of a set of genes in the bovine genome known to govern milk production, in order to develop a new gene clustering algorithm. The implementation of this algorithm is very user-friendly and requires only simple routine mathematical operations. By transforming the configuration of gene sequences into frequency domain, we sought to elucidate important features and reveal hidden gene properties. This is biologically appealing since no information is lost via this transformation and we are therefore not reducing the number of degrees of freedom. The results from different clustering methods were integrated using evidence accumulation algorithms to provide in insilico validation of our results. We propose using candidate gene sequences accompanied by other genes of biologically unknown function. These will then be assigned some degree of relevant annotation by using our proposed algorithm. Current knowledge in biological gene clustering investigation is also lacking, and so DFT-based methods will help shine a light on use of these algorithms for biological insight.

Estimation of genetic parameters for production, reproduction, and growth curve of Fars indigenous chicken.

Iranian native chicken, including Fars indigenous chicken, is an important genetic resource due to its adaptation to stressful environmental conditions, good endurance and resistance to disease. The aim of this research was to determine the genetic infrastructure of Fars indigenous chicken using several nonlinear functions. The dataset included body weight at hatch (BW1), body weight at the 8th week (BW8), body weight at the 12th week (BW12), weight at sexual maturity (WSM), age at sexual maturity (ASM), number of eggs in the first 12 weeks of laying period (EN), egg weight at the first day of laying (EW1), average egg weight at the 28thday of laying (EW28), and average egg weight at weeks 28, 30, and 32 of the laying period (AEW). Growth models were fitted using the NLIN procedure and WOMBAT software was used to predict variance components for the best fit model parameters. Results suggested three-parameter models, for example, Gompertz, fitted better to the data than others. The maturity weight (A), initial weight (B), and maturity rate (K) parameters in the Gompertz model were 1996.8 ± 6.63, 4.11 ± 0.03, and 0.021 ± 0.0001, respectively. The heritability of A, B, and K parameters were 0.03, 0.05, and 0.12, respectively.

An Integrated Bioinformatics Approach to Identify Network-Derived Hub Genes in Starving Zebrafish.

The present study was aimed at identifying causative hub genes within modules formed by co-expression and protein-protein interaction (PPI) networks, followed by Bayesian network (BN) construction in the liver transcriptome of starved zebrafish. To this end, the GSE11107 and GSE112272 datasets from the GEO databases were downloaded and meta-analyzed using the MetaDE package, an add-on R package. Differentially expressed genes (DEGs) were identified based upon expression intensity N(µ = 0.2, σ2 = 0.4). Reconstruction of BNs was performed by the bnlearn R package on genes within modules using STRINGdb and CEMiTool. ndufs5 (shared among PPI, BN and COEX), rps26, rpl10, sdhc (shared between PPI and BN), ndufa6, ndufa10, ndufb8 (shared between PPI and COEX), skp1, atp5h, ndufb10, rpl5b, zgc:193613, zgc:123327, zgc:123178, wu:fc58f10, zgc:111986, wu:fc37b12, taldo1, wu:fb62f08, zgc:64133 and acp5a (shared between COEX and BN) were identified as causative hub genes affecting gene expression in the liver of starving zebrafish. Future work will shed light on using integrative analyses of miRNA and DNA microarrays simultaneously, and performing in silico and experimental validation of these hub-causative (CST) genes affecting starvation in zebrafish.

Genome-Wide Characterization and Expression Analysis of Fatty acid Desaturase Gene Family in Poplar.

Fatty acid desaturases (FADs) modulate carbon-carbon single bonds to form carbon-carbon double bonds in acyl chains, leading to unsaturated fatty acids (UFAs) that have vital roles in plant growth and development and their response to environmental stresses. In this study, a total of 23 Populus trichocarpaFAD (PtFAD) candidates were identified from the poplar genome and clustered into seven clades, including FAB2, FAD2, FAD3/7/8, FAD5, FAD6, DSD, and SLD. The exon-intron compositions and conserved motifs of the PtFADs, clustered into the same clade, were considerably conserved. It was found that segmental duplication events are predominantly attributable to the PtFAD gene family expansion. Several hormone- and stress-responsive elements in the PtFAD promoters implied that the expression of the PtFAD members was complicatedly regulated. A gene expression pattern analysis revealed that some PtFAD mRNA levels were significantly induced by abiotic stress. An interaction proteins and gene ontology (GO) analysis indicated that the PtFADs are closely associated with the UFAs biosynthesis. In addition, the UFA contents in poplars were significantly changed under drought and salt stresses, especially the ratio of linoleic and linolenic acids. The integration of the PtFAD expression patterns and UFA contents showed that the abiotic stress-induced PtFAD3/7/8 members mediating the conversion of linoleic and linolenic acids play vital roles in response to osmotic stress. This study highlights the profiles and functions of the PtFADs and identifies some valuable genes for forest improvements.

Isoprenoid biosynthesis regulation in poplars by methylerythritol phosphate and mevalonic acid pathways.

It is critical to develop plant isoprenoid production when dealing with human-demanded industries such as flavoring, aroma, pigment, pharmaceuticals, and biomass used for biofuels. The methylerythritol phosphate (MEP) and mevalonic acid (MVA) plant pathways contribute to the dynamic production of isoprenoid compounds. Still, the cross-talk between MVA and MEP in isoprenoid biosynthesis is not quite recognized. Regarding the rate-limiting steps in the MEP pathway through catalyzing 1-deoxy-D-xylulose5-phosphate synthase and 1-deoxy-D-xylulose5-phosphate reductoisomerase (DXR) and also the rate-limiting step in the MVA pathway through catalyzing 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR), the characterization and function of HMGR from Populus trichocarpa (PtHMGR) were analyzed. The results indicated that PtHMGR overexpressors (OEs) displayed various MEP and MVA-related gene expressions compared to NT poplars. The overexpression of PtDXR upregulated MEP-related genes and downregulated MVA-related genes. The overexpression of PtDXR and PtHMGR affected the isoprenoid production involved in both MVA and MEP pathways. Here, results illustrated that the PtHMGR and PtDXR play significant roles in regulating MEP and MVA-related genes and derived isoprenoids. This study clarifies cross-talk between MVA and MEP pathways. It demonstrates the key functions of HMGR and DXR in this cross-talk, which significantly contribute to regulate isoprenoid biosynthesis in poplars.

Probabilistic prediction of segmental body composition in Iranian children and adolescents.

BACKGROUND: Adolescents' body composition is considered an important measure to evaluate health status. An examination of any of the segmental compartments by anthropometric indices is a more usable method than direct methods. OBJECTIVES: To propose a method based on the network approach for predicting segmental body composition components in adolescent boys and girls using anthropometric measurements. METHODS: A dual-energy X-ray absorptiometry (DXA) dataset in the south of Iran, including 476 adolescents (235 girls and 241 boys) with a range of 9-18 years, was obtained. Several anthropometric prediction models based on the network approach were fitted to the training dataset (TRD 80%) using bnlearn, an R add-in package. The best fitted models were applied to the validation dataset (VAD 20%) to assess the prediction accuracy. RESULTS: Present equations consisting of age, weight, height, body mass index (BMI), and hip circumference accounted for 0.85 (P < 0.001) of the variability of DXA values in the corresponding age groups of boys. Similarly, reasonable estimates of DXA values could be obtained from age, weight, height, and BMI in girls over 13 years, and from age, weight, height, BMI, and waist circumference in girls under 13 years, respectively, of 0.77 and 0.83 (P < 0.001). Correlations between robust Gaussian Bayesian network (RGBN) predictions and DXA measurements were highly significant, averaging 0.87 for boys and 0.82 for girls (P < 0.001). CONCLUSIONS: The results revealed that, based on the present study's predictive models, adolescents' body composition might be estimated by input anthropometric information. Given the flexibility and modeling of the present method to test different motivated hypotheses, its application to body compositional data is highly appealing.

Bayesian threshold analysis of litter size in sheep

Background: Litter size at birth (LSB) is one of the most important economic traits in sheep and could be used in genetic improvement schemes for meat production. LSB is inherently a categorical trait and should be analysed with threshold models. Objective: Bayesian threshold models were used to analyze sheep LSB to estimate genetic parameters. Methods: Data was based on 7,901 LSB records from 14,968 dams and 682 sires collected from 1986 to 2012 at Makouie Sheep Breeding Station in Iran. Means of posterior distributions (MPDs) of LSB's genetic parameters were estimated, and the best-fitted models were selected using the deviance information criterion. Results: In the repeated measurement analysis, the estimated direct and maternal heritabilities, and permanent environmental effect (±SE), according to the best-fitted model (model 5), were 0.01 (0.010), 0.02 (0.014), and 0.01 (0.011), respectively. In the univariate analysis, the best estimates of direct and maternal heritabilities were 0.12 (0.064) and 0.08 (0.045), respectively. An increasing trend for direct and maternal heritabilities was observed in parity 2 (0.15 (0.082) and 0.25 (0.083), respectively). In the bivariate analysis, the best estimates of direct and maternal heritabilities for LSB were 0.03 (0.027) and 0.22 (0.041), respectively. The direct and maternal genetic correlations among parities were 0.25 (0.054) and 0.12 (0.021), respectively. Conclusions: The results showed a considerable influence of environmental factors on LSB in each parity of sheep; also, statistically different genetic parameters (p<0.05) were obtained from one parity to another, indicating the different and large influences of genetic and environmental factors for each parity.

Antecedentes: El tamaño de la camada al nacer (LSB) es inherentemente un rasgo categórico y debe analizarse con modelos de umbral. El LSB es uno de los rasgos de producción de carne más importantes en las ovejas y podría usarse en esquemas de mejora genética para la producción de carne. Objetivo: Se utilizaron modelos de umbral bayesiano para analizar el tamaño de la camada de ovejas al nacer (LSB) y estimar parámetros genéticos. Métodos: Los datos se basaron en 7.901 registros de LSB de 14.968 ovejas y 682 carneros recolectados de 1986 a 2012 en la estación de cría de ovejas Makouie en Irán. Se estimaron las medias de distribuciones posteriores (MPD) de los parámetros genéticos de LSB y se seleccionaron los modelos mejor ajustados utilizando el criterio de información de desviación. Resultados: En los análisis de medición repetida, la heredabilidad materna y directa estimada y el efecto ambiental permanente (±SE), según el modelo mejor ajustado (modelo 5), fueron 0,01 (0,010), 0,02 (0,014) y 0,01 (0,011), respectivamente. En el análisis univariado, las mejores estimaciones de heredabilidad directa y materna fueron 0,12 (0,064) y 0,08 (0,045), respectivamente. Se observó una tendencia creciente de heredabilidades directas y maternas en la paridad 2 (0,15 (0,082) y 0,25 (0,083), respectivamente). En el análisis bivariado, las mejores estimaciones de heredabilidad directa y materna para LSB fueron 0,03 (0,027) y 0,22 (0,041), respectivamente. Las correlaciones genéticas directas y maternas entre partos fueron 0,25 (0,054) y 0,12 (0,021), respectivamente. Conclusiones: Los resultados mostraron una influencia considerable de los factores ambientales sobre el LSB en cada parto de las ovejas; además, se obtuvieron parámetros genéticos estadísticamente diferentes (p<0.05) de un parto a otro, indicando las diferentes y grandes influencias de factores genéticos y ambientales para cada parto en ovejas. Los resultados de este estudio se pueden precisar aún más utilizando datos de SNP de todo el genoma sobre diferentes partes para manejar una amplia gama de problemas relacionados con la interacción del entorno genético del rasgo LSB.

Antecedentes: O tamanho da ninhada ao nascer (LSB) é inerentemente uma característica categórica e deve ser analisada com modelos de limiar. LSB é uma das características mais importantes de produção de carne em ovinos e pode ser usado em esquemas de melhoramento genético para a produção de carne. Objetivo: Modelos de limiar bayesiano foram usados para analisar o tamanho da ninhada de ovelhas ao nascer (LSB) para estimar parâmetros genéticos. Métodos: Os dados foram baseados em 7.901 registros LSB de 14.968 ovelhas e 682 carneiros coletados de 1986 a 2012 na Estação de Criação de Ovinos Makouie no Irã. Médias de distribuições posteriores (MPDs) dos parâmetros genéticos de LSB foram estimadas e os modelos mais bem ajustados foram selecionados usando o critério de informação de desvio. Resultados: Nas análises de medidas repetidas, as herdabilidades diretas e maternas estimadas e o efeito do ambiente permanente (±SE), de acordo com o modelo mais bem ajustado (modelo 5), foram 0,01 (0,010), 0,02 (0,014) e 0,01 (0,011), respectivamente. Na análise univariada, as melhores estimativas das herdabilidades direta e materna foram 0,12 (0,064) e 0,08 (0,045), respectivamente. Uma tendência crescente para as herdabilidades direta e materna foi observada na paridade 2 (0,15 (0,082) e 0,25 (0,083), respectivamente). Na análise bivariada, as melhores estimativas de herdabilidades direta e materna para LSB foram 0,03 (0,027) e 0,22 (0,041), respectivamente. As correlações genéticas diretas e maternas entre os partos foram 0,25 (0,054) e 0,12 (0,021), respectivamente. Conclusões: Os resultados mostraram uma influência considerável dos fatores ambientais na LSB em cada paridade de ovelhas; também, parâmetros genéticos estatisticamente diferentes (p<0,05) foram obtidos de uma paridade para outra, indicando as diferentes e grandes influências de fatores genéticos e ambientais para cada paridade em ovinos. Os resultados deste estudo podem ser ainda mais definidos usando dados SNPs de todo o genoma em diferentes partes para lidar com uma ampla gama de problemas relacionados à interação do ambiente genético do traço LSB.

Constraint-Based, Score-Based and Hybrid Algorithms to Construct Bayesian Gene Networks in the Bovine Transcriptome.

Bayesian gene networks are powerful for modelling causal relationships and incorporating prior knowledge for making inferences about relationships. We used three algorithms to construct Bayesian gene networks around genes expressed in the bovine uterus and compared the efficacies of the algorithms. Dataset GSE33030 from the Gene Expression Omnibus (GEO) repository was analyzed using different algorithms for hub gene expression due to the effect of progesterone on bovine endometrial tissue following conception. Six different algorithms (grow-shrink, max-min parent children, tabu search, hill-climbing, max-min hill-climbing and restricted maximum) were compared in three higher categories, including constraint-based, score-based and hybrid algorithms. Gene network parameters were estimated using the bnlearn bundle, which is a Bayesian network structure learning toolbox implemented in R. The results obtained indicated the tabu search algorithm identified the highest degree between genes (390), Markov blankets (25.64), neighborhood sizes (8.76) and branching factors (4.38). The results showed that the highest number of shared hub genes (e.g., proline dehydrogenase 1 (PRODH), Sam-pointed domain containing Ets transcription factor (SPDEF), monocyte-to-macrophage differentiation associated 2 (MMD2), semaphorin 3E (SEMA3E), solute carrier family 27 member 6 (SLC27A6) and actin gamma 2 (ACTG2)) was seen between the hybrid and the constraint-based algorithms, and these genes could be recommended as central to the GSE33030 data series. Functional annotation of the hub genes in uterine tissue during progesterone treatment in the pregnancy period showed that the predicted hub genes were involved in extracellular pathways, lipid and protein metabolism, protein structure and post-translational processes. The identified hub genes obtained by the score-based algorithms had a role in 2-arachidonoylglycerol and enzyme modulation. In conclusion, different algorithms and subsequent topological parameters were used to identify hub genes to better illuminate pathways acting in response to progesterone treatment in the bovine uterus, which should help with our understanding of gene regulatory networks in complex trait expression.

Network Meta-Analysis of Chicken Microarray Data following Avian Influenza Challenge-A Comparison of Highly and Lowly Pathogenic Strains.

The current bioinformatics study was undertaken to analyze the transcriptome of chicken (Gallus gallus) after influenza A virus challenge. A meta-analysis was carried out to explore the host expression response after challenge with lowly pathogenic avian influenza (LPAI) (H1N1, H2N3, H5N2, H5N3 and H9N2) and with highly pathogenic avian influenza (HPAI) H5N1 strains. To do so, ten microarray datasets obtained from the Gene Expression Omnibus (GEO) database were normalized and meta-analyzed for the LPAI and HPAI host response individually. Different undirected networks were constructed and their metrics determined e.g., degree centrality, closeness centrality, harmonic centrality, subgraph centrality and eigenvector centrality. The results showed that, based on criteria of centrality, the CMTR1, EPSTI1, RNF213, HERC4L, IFIT5 and LY96 genes were the most significant during HPAI challenge, with PARD6G, HMG20A, PEX14, RNF151 and TLK1L having the lowest values. However, for LPAI challenge, ZDHHC9, IMMP2L, COX7C, RBM18, DCTN3, and NDUFB1 genes had the largest values for aforementioned criteria, with GTF3C5, DROSHA, ATRX, RFWD2, MED23 and SEC23B genes having the lowest values. The results of this study can be used as a basis for future development of treatments/preventions of the effects of avian influenza in chicken.

Following the Trace of HVS II Mitochondrial Region Within the Nine Iranian Ethnic Groups Based on Genetic Population Analysis.

The Iranian gene pool is seen as an important human genetic resource for investigating the region connecting Mesopotamia and the Iranian plateau. The main objective of this study was to explore gene flow in nine Iranian ethnic/subpopulation groups (402 samples) by examining mtDNA HVS2 sequence variations. This then allowed us to detect mtDNA HVS2 sequence mutations in two independent thalassemia and cystic fibrosis patient sample groups. The patient groups did not explicitly belong to any of the aforementioned nine subpopulations. Across all subpopulations, the haplogroups B4a1c3a, H2a2a1, N10b, H2a2a2, and J1 were seen to be predominant. High haplogroup diversities along with admixture of the exotic groups were observed in this study. The Arab subpopulation was shown to be independent from the others. It was revealed that there is a far distant relationship between Arab and Azeri groups. The thalassemia patient group, represented an almost random sample of most Iranian ethnic groups, and revealed few significant differences (P < 0.05) in their HVS2 sequence. It turned out that the IVS II-I (G → A) mutation in the thalassemia ß-globin gene was highly significant. Since the thalassemia patients in the present study represent many unique haplotypes, we can begin to comprehend the importance of mtDNA with this disease and the necessity for more studies in this context.

Non-extensive thermodynamic entropy to predict the dynamics behavior of COVID-19.

The current world observations in COVID-19 are hardly tractable as a whole, making situations of information to be incompleteness. In pandemic era, mathematical modeling helps epidemiological scientists to take informing decisions about pandemic planning and predict the disease behavior in the future. In this work, we proposed a non-extensive entropy-based model on the thermodynamic approach for predicting the dynamics of COVID-19 disease. To do so, the epidemic details were considered into a single and time-dependent coefficients model. Their four constraints, including the existence of a maximum point were determined analytically. The model was worked out to give a log-normal distribution for the spread rate using the Tsallis entropy. The width of the distribution function was characterized by maximizing the rate of entropy production. The model predicted the number of daily cases and daily deaths with a fairly good agreement with the World Health Organization (WHO) reported data for world-wide, Iran and China over 2019-2020-time span. The proposed model in this work can be further calibrated to fit on different complex distribution COVID-19 data over different range of times.

In silico investigation of uncoupling protein function in avian genomes.

Introduction: The uncoupling proteins (UCPs) are involved in lipid metabolism and belong to a family of mitochondrial anionic transporters. In poultry, only one UCP homologue has been identified and experimentally shown to be associated with growth, feed conversion ratio, and abdominal fat according to its predominant expression in bird muscles. In endotherm birds, cell metabolic efficiency can be tuned by the rate of mitochondrial coupling. Thus, avUCP may be a key contributor to controlling metabolic rate during particular environmental changes. Methods: This study aimed to perform a set of in-silico investigations primarily focused on the structural, biological, and biomimetic functions of avUCP. Thereby, using in silico genome analyses among 8 avian species (chicken, turkey, swallow, manakin, sparrow, wagtail, pigeon, and mallard) and a series of bioinformatic approaches, we provide phylogenetic inference and comparative genomics of avUCPs and investigate whether sequence variation can alter coding sequence characteristics, the protein structure, and its biological features. Complementarily, a combination of literature mining and prediction approaches was also applied to predict the gene networks of avUCP to identify genes, pathways, and biological crosstalk associated with avUCP function. Results: The results showed the evolutionary alteration of UCP proteins in different avian species. Uncoupling proteins in avian species are highly conserved trans membrane proteins as seen by sequence alignment, physio-chemical parameters, and predicted protein structures. Taken together, avUCP has the potential to be considered a functional marker for the identification of cell metabolic state, thermogenesis, and oxidative stress caused by cold, heat, fasting, transfer, and other chemical stimuli stresses in birds. It can also be deduced that avUCP, in migrant or domestic birds, may increase heat stress resistance by reducing fatty acid transport/b-oxidation and thermoregulation alongside antioxidant defense mechanisms. The predicted gene network for avUCP highlighted a cluster of 21 genes involved in response to stress and 28 genes related to lipid metabolism and the proton buffering system. Finally, among 11 enriched pathways, crosstalk of 5 signaling pathways including MAPK, adipocytokine, mTOR, insulin, ErbB, and GnRH was predicted, indicating a possible combination of positive or negative feedback among pathways to regulate avUCP functions. Discussion: Genetic selection for fast-growing commercial poultry has unintentionally increased susceptibility to many kinds of oxidative stress, and so avUCP could be considered as a potential candidate gene for balancing energy expenditure and reactive oxygen species production, especially in breeding programs. In conclusion, avUCP can be introduced as a pleiotropic gene that requires the contribution of regulatory genes, hormones, pathways, and genetic crosstalk to allow its finely-tuned function.

Bayesian estimate of genetic parameters for growth traits in Lori Bakhtiari sheep.

The information of birth (10,017 records), weaning (9439 records), 6 months (7669 records), 9 months (4536 records), and yearling weights (417 records) collected from 1989 to 2016 by the Lori Bakhtiari (Sholi) sheep breeding station located in Shahrekord were used to estimate the genotypic and phenotypic parameters of growth traits of Lori Bakhtiari sheep. The components of variance and genetic parameters were estimated by the Bayesian statistical method based on the Gibbs sampling technique due to the high accuracy of this method. Factors including birth year, lamb sex, birth type, and maternal age at lambing have significant effects on all of these traits (P < 0.01) and were considered fixed effects in the statistical model for estimation of genetic parameters. Lamb weight at weaning was used as a covariate in the model. Based on the models with the lowest Akaike information criterion, direct heritability for birth, weaning, 6-month, 9-month, and yearling weights were 0.36, 0.18, 0.21, 0.27, and 0.32, respectively. The moderate heritability obtained for the studied traits pointed up the effectiveness of selection in genetic improvement, but the environmental conditions should be improved for better performance of weight traits.

Mathematical prediction of the spreading rate of COVID-19 using entropy-based thermodynamic model.

In the COVID-19 pandemic era, undoubtedly mathematical modeling helps epidemiological scientists and authorities to take informing decisions about pandemic planning, wise resource allocation, introducing relevant non-pharmaceutical interventions and implementation of social distancing measures. The current coronavirus disease (COVID-19) emerged in the end of 2019, Wuhan, China, spreads quickly in the world. In this study, an entropy-based thermodynamic model has been used for predicting and spreading the rate of COVID-19. In our model, all the epidemic details were considered into a single time-dependent parameter. The parameter was analytically determined using four constraints, including the existence of an inflexion point and a maximum value. Our model has been layout-based the Shannon entropy and the maximum rate of entropy production of postulated complex system. The results show that our proposed model fits well with the number of confirmed COVID-19 cases in daily basis. Also, as a matter of fact that Shannon entropy is an intersection of information, probability theory, (non)linear dynamical systems and statistical physics, the proposed model in this study can be further calibrated to fit much better on COVID-19 observational data, using the above formalisms.

Genetic analysis of sexual size dimorphism in Markhoz goat.

Genetic bases of sexual size dimorphism (SSD) in Markhoz goat (5268 kids descended from 242 sires and 1499 dams) were unraveled as it was thought that sex-specific genetic mechanism is in the place governing SSD of birth weight (BW), weaning weight at 90 days of age (WW_90d), and post-weaning weights at 6 (W6), 9 (W9), and 12 (W12) months of age. Male kids excelled for BW, WW_90d, W6, W9, and W12 than their female counterparts in the tune of 10, 17, 14, 17, and 23%, respectively. Estimates of sexual dimorphism levels (expressed as M/F) were 1.09, 1.17, 1.14, 1.17, and 1.23 for BW, WW_90d, W6, W9, and W12, respectively, which indicated relatively low levels of sexual size dimorphism in the studied traits. Though the additive genetic, residual and phenotypic variances were higher in males than females, for mostly all studied traits, but the heritability estimates for all traits except birth weight were higher in females. Differences in direct and maternal effects between male and female kids indicated that body weights traits could be treated as separate trait for male and female kids. Cross-sex genetic correlations revealed that almost all ages, genetic correlations between the two sexes, were high, and the lowest estimate (0.88) was for W6, which highlighted this trait as the most dimorphic trait in this breed. High and positive genetic correlations between the sexes indicated that selection for body weight in males would result in a correlated response in females and vice versa and, consequently, would prevent phenotypic divergence.

Association analysis and molecular tagging of phytochemicals in the endangered medicinal plant licorice (Glycyrrhiza glabra L.).

Licorice (Glycyrrhiza glabra L.) is a medicinal plant species valued in many countries in Asia and Europe for its phytochemical characteristics. Licorice biodiversity is becoming threatened nowadays in Iran due to increasing demand and a drastic decline of its natural habitats. Therefore, licorice domestication would be necessary in the near future, and molecular breeding would help to introduce genotypes suitable for cultivation. The present study was carried out with 170 individual licorice plants sampled in the wild in 59 localizations in 21 provinces of Iran. The association of 436 polymorphic AFLP markers, produced by 15 primer combinations (EcoRI/MseI), with six phenotypic phytochemical traits was studied. The AMOVA analysis show gene diversity among and within localizations. The population structure analysis identified two main sub-populations with significant genetic variation. Significant associations were identified between three markers (E3/M40-4, E34/M4-12 and E12/M31-15) and glycyrrhizin concentration, and between four markers (E11/M34-12, E11/M34-15, E9/M7-29, and E9/M7-30) and phenolic compounds contents. Markers detected can be useful in the domestication of licorice as well as in breeding programs. Licorice sampled in four localizations (KBA1, KBA2, SKh2 and Fa1) were found to be superior in terms of glycyrrhizin and antioxidants content, and therefore they can be considered as elite genotypes which could be included in the domestication process.