Search results for: gene transfer

Authors: Yu-Chen Hu

Abstract:

Gene editing by CRISPR and gene regulation by microRNA or CRISPR activation have dramatically changed the way to manipulate cellular gene expression and cell fate. In recent years, various gene editing and gene manipulation technologies have been applied to control stem cell differentiation to enhance tissue regeneration. This research will focus on how to develop CRISPR, CRISPR activation (CRISPRa), CRISPR inhibition (CRISPRi), as well as bi-directional CRISPR-AI gene regulation technologies to control cell differentiation and bone regeneration. Moreover, in this study, CRISPR/Cas13d-mediated RNA editng for miRNA editing and bone regeneration will be discussed.

Keywords: gene therapy, bone regeneration, stem cell, CRISPR, gene regulation

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Authors: Fadhl Alakwaa

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One of the sustainable goals of the system biology is understanding gene-gene interactions. Hence, gene regulatory networks (GRN) need to be constructed for understanding the disease ontology and to reduce the cost of drug development. To construct gene regulatory from gene expression we need to overcome many challenges such as data denoising and dimensionality. In this paper, we develop an integrated system to reduce data dimension and remove the noise. The generated network from our system was validated via available interaction databases and was compared to previous methods. The result revealed the performance of our proposed method.

Keywords: gene regulatory network, biclustering, denoising, system biology

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Authors: Restu Misrianti

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The amino acid variation of Asn (allele A) at position 631 in Mx gene was specific to positive antiviral to avian viral desease. This research was aimed at identifying polymorphism of Mx gene in duck using molecular technique. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) technique was used to select the genotype of AA, AG and GG. There were thirteen duck from Indragiri Hulu regency (Riau Province) used in this experiment. DNA amplification results showed that the Mx gene in duck is found in a 73 bp fragment. Mx gene in duck did not show any polymorphism. The frequency of the resistant allele (AA) was 0%, while the frequency of the susceptible allele (GG) was 100%.

Keywords: duck, Mx gene, PCR, RFLP

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Authors: Saeid Doaei

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The various studies have examined the relationship between FTO gene expression and macronutrients levels. In order to obtain better viewpoint from this interactions, all of the existing studies were reviewed systematically. All published papers have been obtained and reviewed using standard and sensitive keywords from databases such as CINAHL, Embase, PubMed, PsycInfo, and the Cochrane, from 1990 to 2016. The results indicated that all of 6 studies that met the inclusion criteria (from a total of 428 published article) found FTO gene expression changes at short-term follow-ups. Four of six studies found an increased FTO gene expression after calorie restriction, while two of them indicated decreased FTO gene expression. The effect of protein, carbohydrate and fat were separately assessed and suggested by all of six studies. In conclusion, the level of FTO gene expression in hypothalamus is related to macronutrients levels. Future research should evaluate the long-term impact of dietary interventions.

Keywords: obesity, gene expression, FTO, macronutrients

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Authors: Yuriy A. Knirel

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Enteric bacteria Escherichia coli is the predominant facultative anaerobe of the colonic flora, and some specific serotypes are associated with enteritis, hemorrhagic colitis, and hemolytic uremic syndrome. Shigella spp. are human pathogens that cause diarrhea and bacillary dysentery (shigellosis). They are in effect E. coli with a specific mode of pathogenicity. Strains of Salmonella enterica are responsible for a food-borne infection (salmonellosis), and specific serotypes cause typhoid fever and paratyphoid fever. All these bacteria are closely related in respect to structure and genetics of the lipopolysaccharide, including the O-polysaccharide part (O‑antigen). Being exposed to the bacterial cell surface, the O antigen is subject to intense selection by the host immune system and bacteriophages giving rise to diverse O‑antigen forms and providing the basis for typing of bacteria. The O-antigen forms of many bacteria are unique, but some are structurally and genetically related to others. The sequenced O-antigen gene clusters between conserved galF and gnd genes were analyzed taking into account the O-antigen structures established by us and others for all S. enterica and Shigella and most E. coli O-serogroups. Multiple genetic mechanisms of diversification of the O-antigen forms, such as lateral gene transfer and mutations, were elucidated and are summarized in the present paper. They include acquisition or inactivation of genes for sugar synthesis or transfer or recombination of O-antigen gene clusters or their parts. The data obtained contribute to our understanding of the origins of the O‑antigen diversity, shed light on molecular evolutionary relationships between the O-antigens of enteric bacteria, and open a way for studies of the role of gene polymorphism in pathogenicity.

Keywords: enteric bacteria, O-antigen gene cluster, polysaccharide biosynthesis, polysaccharide structure

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

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Authors: Sarita Agarwal, Deepika Delsa Dean

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Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.

Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation

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Authors: Alhadi Bustaman, Soeganda Formalidin, Titin Siswantining

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DNA microarray technology is used to analyze thousand gene expression data simultaneously and a very important task for drug development and test, function annotation, and cancer diagnosis. Various clustering methods have been used for analyzing gene expression data. However, when analyzing very large and heterogeneous collections of gene expression data, conventional clustering methods often cannot produce a satisfactory solution. Biclustering algorithm has been used as an alternative approach to identifying structures from gene expression data. In this paper, we introduce a transform technique based on singular value decomposition to identify normalized matrix of gene expression data followed by Mixed-Clustering algorithm and the Lift algorithm, inspired in the node-deletion and node-addition phases proposed by Cheng and Church based on Agglomerative Hierarchical Clustering (AHC). Experimental study on standard datasets demonstrated the effectiveness of the algorithm in gene expression data.

Keywords: agglomerative hierarchical clustering (AHC), biclustering, gene expression data, lymphoma, singular value decomposition (SVD)

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Authors: M. Ottenbrite, G. Yilmaz, J. Devenish, M. Kang, H. Dan, M. Lin, C. Lau, C. Carrillo, K. Bessonov, J. Nash, E. Topp, J. Guan

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Consumption of food contaminated by antibiotic-resistant (AR) bacteria may lead to the transmission of AR genes in the gut microbiota and cause AR bacterial infection, a significant public health concern. However, information is limited on if and how background microbes from the food matrix (food microbes) may influence resistance transmission. Thus, we assessed the colonization of a β-lactam resistant Salmonella Heidelberg strain (donor) and a β-lactam susceptible S. Typhimurium strain (recipient) and the transfer of the resistance genes in the mouse gut in the presence or absence of food microbes that were derived from washing freshly-harvested carrots. Mice were pre-treated with streptomycin and then inoculated with both donor and recipient bacteria or recipient only. Fecal shedding of the donor, recipient, and transconjugant bacteria was enumerated using selective culture techniques. Transfer of AR genes was confirmed by whole genome sequencing. Gut microbial composition was determined by 16s rRNA amplicon sequencing. Significantly lower numbers of donors and recipients were shed from mice that were inoculated with food microbes compared to those without food microbe inoculation. S. Typhimurium transconjugants were only recovered from mice without inoculation of food microbes. A significantly higher survival rate was in mice with vs. without inoculation of food microbes. The results suggest that the food microbes may compete with both the donor and recipient Salmonella, limit their growth and reduce transmission of the β-lactam resistance gene in the mouse gut.

Keywords: antibiotic resistance, gene transfer, gut microbiota, Salmonella infection

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Authors: Hazha Hidayat, Shayma Ibrahim

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Folate metabolism plays a crucial role in the normal development of the neonatal central nervous system. It is regulated by MTHFR gene polymorphism. Any factors, which will affect this metabolism either by hereditary or gene mutation will lead to many mental disorders. The purpose of this study was to investigate whether MTHFR gene mutation contributes to the development of mental retardation and CP combined with mental retardation in Erbil city. DNA was isolated from the peripheral blood samples of 40 cases suffering from mental retardation (MR) and CP combined with MR were recruited, sequence the 4, 6, 7, 8 exons of the MTHFR gene were done to identify the variants. Exons were amplified by PCR technique and then sequenced according to Sanger method to show the differences with MTHFR reference sequences. We observed (14) mutations in 4, 6, 7, 8 exons in the MTHFR gene associated with Cerebral Palsy combined with mental retardation included deletion, insertion, Substitution. The current study provides additional evidence that multiple variations in the MTHFR gene are associated with mental retardation and Cerebral Palsy.

Keywords: methylenetetrahydrofolate reductase (MTHFR) gene, SNPs, homocysteine, sequencing

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Authors: Dong Tianxiang

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In the context of the era of rural revitalization, rural land is popular for more and more active, and its process has been widely concerned by all walks of life. By analyzing and summarizing the actual situation of land transfer, the author found that land transfer has such problems as ambiguous land transfer benefit subjects, decentralized and disorderly land transfer forms, lack of guarantee system for land transfer, and land transfer affecting food production. Based on the above problems, the author first analyzes the specific situation of land transfer in the study area with relevant econometric models and ArcGIS spatial analysis methods and analyzes its causes to construct a positive role mechanism of land use transformation on land transfer.

Keywords: land transfer, land use, rural revitalization, population loss

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: Somyung Oh, Jeonghyeon Ha, Kyungwon Lee, Sejong Oh

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Microarray is a general scheme to find differentially expressed genes for target concept. The output is expressed by heat map, and biologists analyze related terms of gene ontology to find some characteristics of differentially expressed genes. In this paper, we propose integrated visualization tool for heat map and gene ontology graph. Previous two methods are used by static manner and separated way. Proposed visualization tool integrates them and users can interactively manage it. Users may easily find and confirm related terms of gene ontology for given differentially expressed genes. Proposed tool also visualize connections between genes on heat map and gene ontology graph. We expect biologists to find new meaningful topics by proposed tool.

Keywords: heat map, gene ontology, microarray, differentially expressed gene

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Rachel Matar, Maxime Merheb

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Chemical drugs have been used for many centuries as the only way to cure diseases until the novel gene therapy has been created in 1960. Gene therapy is based on the insertion, correction, or inactivation of genes to treat people with genetic illness (1). Gene therapy has made wonders in Parkison’s, Alzheimer and multiple sclerosis. In addition to great promises in the healing of deadly diseases like many types of cancer and autoimmune diseases (2). This method implies the use of recombinant DNA technology with the help of different viral and non-viral vectors (3). It is nowadays used in somatic cells as well as embryos and gametes. Beside all the benefits of gene therapy, this technique is deemed by some opponents as an ethically unacceptable treatment as it implies playing with the genes of living organisms.

Keywords: gene therapy, genetic disease, cancer, multiple sclerosis

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Authors: Daina Jonkus, Liga Paura, Tatjana Sjakste, Kristina Dokane

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The aim of this study was to analyse PRKAG3 and RYR1 gene and genotypes frequencies in Latvian White pigs’ breed. Genotypes of RYR1 gene two loci (rs196953058 and rs323041392) in 89 exon and PRKAG3 gene two loci (rs196958025 and rs344045190) in gene promoter were detected in 103 individuals of Latvian white pigs’ breed. Analysis of RYR1 gene loci rs196953058 shows all individuals are homozygous by T allele and all animals are with genotypes TT, its mean - in 2769 position is Phenylalanine. Analysis of RYR1 gene loci rs323041392 shows all individuals are homozygous by G allele and all animals are with genotypes GG, its mean - in 4119 positions is Asparagine. In loci rs196953058 and rs323041392, there were no gene polymorphisms. All analysed individuals by two loci rs196953058-rs323041392 have TT-GG genotypes or Phe-Asp amino acids. In PRKAG3 gene loci rs196958025 and rs344045190 there was gene polymorphisms. In both loci frequencies for A allele was higher: 84.6% for rs196958025 and 73.0% for rs344045190. Analysis of PRKAG3 gene loci rs196958025 shows 74% of individuals are homozygous by An allele and animals are with genotypes AA. Only 4% of individuals are homozygous by G allele and animals are with genotypes GG, which is associated with pale meat colour and higher drip loss. Analysis of PRKAG3 gene loci rs344045190 shows 46% of individuals are homozygous with genotypes AA and 54% of individuals are heterozygous with genotypes AG. There are no individuals with GG genotypes. According to the results, in Latvian white pigs population there are no rs344435545 (RYR1 gene) CT heterozygous or TT recessive homozygous genotypes, which is related to the meat quality and pigs’ stress syndrome; and there are 4% rs196958025 (PRKAG3 gene) GG recessive homozygote genotypes, which is related to the meat quality. Acknowledgment: the investigation is supported by VPP 2014-2017 AgroBioRes Project No. 3 LIVESTOCK.

Keywords: genotype frequencies, pig, PRKAG3, RYR1

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Authors: Sadaf Ilyas, Saba Riaz

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The extensive use of antibiotics has led to increases emergence of antibiotic-resistant organisms. Pseudomonas is a notorious opportunistic pathogen involoved in nosocomial infections and exhibit innate resistance to many antibiotics. The present study was conducted to assess the prevalence, levels of antimicrobial susceptibility and resistance mechanisms of Pseudomonas. A total of thirty clinical strains of Pseudomonas were isolated from different clinical sites of infection. All clinical specimens were collected from Chughtais Lahore Lab. Jail road, during 8-07-2010 to 11-01-2011. Biochemical characterization was done using routine biochemical tests. Antimicrobial susceptibility was determined by Kirby-Baeur method. The plasmids were isolated from all the strains and digested with restriction enzyme PstI and EcoRI. Transfer of Multi-resistance plasmid was checked via transformation and conjugation to confirm the plasmid mediated resistance to antibiotics. The prevalence of Pseudomonas in clinical specimens was found out to be 14% of all bacterial infections. IPM has shown to be the most effective drug against Pseudomonas followed by CES, PTB and meropenem, wheareas most of the Pseudomonas strains have developed significant resistance against Penicillins and some Cephalasporins. Antibiotic resistance determinants were carried by plasmids, as they conferred resistance to transformed K1 strains. The isolates readily undergo conjugation, transferring the resistant genes to other strains, illustrating the high rates of cross infection and nosocomial infection in the immunocompromised patients.

Keywords: pseudomonas, antibiotics, drug resistance, horizontal gene transfer

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Authors: Hamid Mustafa, Adeela Ajmal, Kim EuiSoo, Noor-ul-Ain

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World wild, buffalo production is considered as most important component of food industry. Efficient buffalo production is related with reproductive performance of this species. Lack of knowledge of reproductive efficiency and its related genes in buffalo species is a major constraint for sustainable buffalo production. In this study, we performed some bioinformatics analysis on Follicle Stimulating Hormone Receptor (FSHR) gene and explored the possible relationship of this gene among different buffalo breeds and with other farm animals. We also found the evolution pattern for this gene among these species. We investigate CDS lengths, Stop codon variation, homology search, signal peptide, isoelectic point, tertiary structure, motifs and phylogenetic tree. The results of this study indicate 4 different motif in this gene, which are Activin-recp, GS motif, STYKc Protein kinase and transmembrane. The results also indicate that this gene has very close relationship with cattle, bison, sheep and goat. Multiple alignment (MA) showed high conservation of motif which indicates constancy of this gene during evolution. The results of this study can be used and applied for better understanding of this gene for better characterization of Follicle Stimulating Hormone Receptor (FSHR) gene structure in different farm animals, which would be helpful for efficient breeding plans for animal’s production.

Keywords: buffalo, FSHR gene, bioinformatics, production

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Authors: Jae Woong Sull

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Lipid levels are related to the risk of cardiovascular diseases. Cholesterol ester transfer protein (CETP) gene is one of the candidate genes of cardiovascular diseases. A total of 2,304 persons were chosen from a Hospital (N=4,294) in South Korea. Female subjects with the CG/GG genotype had a 2.03 -fold (p=0.0001) higher risk of having abnormal HDL cholesterol levels (<40 mg/dL) than subjects with the CC genotype. Male subjects with the CG/GG genotype had a 1.34 -fold (p=0.0019) higher risk than subjects with the CC genotype. When analyzed by body mass index, the association with CETP was much stronger in male subjects with BMI>=25.69 (OR=1.55, 95% CI: 1.15-2.07, P=0.0037) than in male lean subjects. When analyzed by family history of diabetes, the association with CETP was much stronger in male subjects with positive family history of low physical activity (OR=4.82, 95% CI: 1.86-12.5, P=0.0012) than in male subjects with negative family history of diabetes. This study clearly demonstrates that genetic variants in CETP influence HDL cholesterol levels in Korean adults.

Keywords: CETP, diabetes, obesity, polymorphisms

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Authors: Shahram Nanekarania, Majid Goodarzia

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Calpastatin and callipyge have been known as one of the candidate genes in meat quality and quantity. Calpastatin gene has been located to chromosome 5 of sheep and callipyge gene has been localized in the telomeric region on ovine chromosome 18. The objective of this study was identification of calpastatin and callipyge genes polymorphism and analysis of genotype structure in population of Lori sheep kept in Iran. Blood samples were taken from 120 Lori sheep breed and genomic DNA was extracted by salting out method. Polymorphism was identified using the PCR-RFLP technique. The PCR products were digested with MspI and FaqI restriction enzymes for calpastatin gene and callipyge gene, respectively. In this population, three patterns were observed and AA, AB, BB genotype have been identified with the 0.32, 0.63, 0.05 frequencies for calpastatin gene. The results obtained for the callipyge gene revealed that only the wild-type allele A was observed, indicating that only genotype AA was present in the population under consideration.

Keywords: polymorphism, calpastatin, callipyge, PCR-RFLP, Lori sheep

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

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Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

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The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

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Authors: Christina Killian, Katie Wall, Séamus Fanning, Guerrino Macori

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Deep-level metagenomics offers a useful technical approach to explore the three dynamic One Health axes: healthcare, domiciliary and veterinary. There is currently limited understanding of the composition of complex biofilms, natural abundance of AMR genes and gene transfer occurrence in these ecological niches. By using a newly established small-scale complex biofilm model, COMBAT has the potential to provide new information on microbial diversity, antimicrobial resistance (AMR)-encoding gene abundance, and their transfer in complex biofilms of importance to these three One Health axes. Shotgun metagenomics has been used to sample the genomes of all microbes comprising the complex communities found in each biofilm source. A comparative analysis between untreated and biocide-treated biofilms is described. The basic steps include the purification of genomic DNA, followed by library preparation, sequencing, and finally, data analysis. The use of long-read sequencing facilitates the completion of metagenome-assembled genomes (MAG). Samples were sequenced using a PromethION platform, and following quality checks, binning methods, and bespoke bioinformatics pipelines, we describe the recovery of individual MAGs to identify mobile gene elements (MGE) and the corresponding AMR genotypes that map to these structures. High-throughput sequencing strategies have been deployed to characterize these communities. Accurately defining the profiles of these niches is an essential step towards elucidating the impact of the microbiota on each niche biofilm environment and their evolution.

Keywords: COMBAT, biofilm, metagenomics, high-throughput sequencing

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Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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Authors: Yudi Zhao, Ziyun Zhou, Yueting Yao, Shuying Dai, Zhiling Yan, Longyu Yang, Chuanyin Li, Li Shi, Yufeng Yao

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HPV16 E4 gene plays an important role in viral genome amplification and release. Therefore, a variation of the E4 gene nucleic acid sequence may affect the carcinogenicity of HPV16. In order to understand the relationship between the variation of HPV16 E4 gene and cervical cancer, this study was to amplify and sequence the DNA sequences of E4 genes in 118 HPV16-positive cervical cancer patients and 151 HPV16-positive asymptomatic individuals. After obtaining E4 gene sequences, the phylogenetic trees were constructed by the Neighbor-joining method for gene variation analysis. The results showed that: 1) The distribution of HPV16 variants between the case group and the control group differed greatly (P = 0.015)，and the Asian-American（AA）variant was likely to relate to the occurrence of cervical cancer. 2) DNA sequence analysis showed that there were significant differences in the distribution of 8 variants between the case group and the control group (P < 0.05). And 3) In European (EUR) variant, two variations, C3384T (L18L) and A3449G (P39P), were associated with the initiation and development of cervical cancer. The results suggested that the variation of HPV16 E4 gene may be a contributor affecting the occurrence as well as the development of cervical cancer, and different HPV16 variants may have different carcinogenic capability.

Keywords: cervical cancer, HPV16, E4 gene, variations

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Authors: Kumaran Narayanan, Pei-Sheng Liew

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This paper adapts the bacteriophage N15 protelomerase enzyme to assemble linear chromosomes as vectors for gene expression in human cells. Phage N15 has the unique ability to replicate as a linear plasmid with telomeres in E. coli during its prophage stage of life-cycle. The virus-encoded protelomerase enzyme cuts its circular genome and caps its ends to form hairpin telomeres, resulting in a linear human-chromosome-like structure in E. coli. In mammalian cells, however, no enzyme with TelN-like activities has been found. In this work, we show for the first-time transfer of the protelomerase from phage into human and mouse cells and demonstrate recapitulation of its activity in these hosts. The function of this enzyme is assayed by demonstrating cleavage of its target DNA, followed by detecting telomere formation based on its resistance to recBCD enzyme digestion. We show protelomerase expression persists for at least 60 days, which indicates limited silencing of its expression. Next, we show that an intact human β-globin gene delivered on this linear chromosome accurately retains its expression in the human cellular environment for at least 60 hours, demonstrating its stability and potential as a vector. These results demonstrate that the N15 protelomerse is able to function in mammalian cells to cut and heal DNA to create telomeres, which provides a new tool for creating novel structures by DNA resolution in these hosts.

Keywords: chromosome, beta-globin, DNA, gene expression, linear vector

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Authors: José Carlos Rodríguez, Mario Gómez

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The aim of this paper is to get insight on the nature of university-industry technology transfer (UITT) and technology transfer offices (TTOs) activity at universities in the case of emerging economies. In relation to the process of transferring knowledge/technology in the case of emerging economies, knowledge/technology transfer in these economies are more reactive than in developed economies due to differences in maturity of technologies. It is assumed in this paper that knowledge/technology transfer is a complex phenomenon, and thus the paper contributes to get insight on the nature of UITT and TTOs creation in the case of emerging economies by using a system dynamics model of knowledge/technology transfer in these countries. The paper recognizes the differences between industrialized countries and emerging economies on these phenomena.

Keywords: university-industry technology transfer, technology transfer offices, technology transfer models, emerging economies

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Authors: I. Boroňová, J. Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, S. Mačeková, J. Poráčová, M. M. Blaščáková

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Osteoporosis is a common multifactorial disease with a strong genetic component characterized by reduced bone mass and increased risk of fractures. Genetic factors play an important role in the pathogenesis of osteoporosis. The aim of our study was to identify the genotype and allele distribution of T245G polymorphism in OPG gene in Slovak postmenopausal women. A total of 200 unrelated Slovak postmenopausal women with diagnosed osteoporosis and 200 normal controls were genotyped for T245G (rs3134069) polymorphism of OPG gene. Genotyping was performed using the Custom Taqman®SNP Genotyping assays. Genotypes and alleles frequencies showed no significant differences (p=0.5551; p=0.6022). The results of the present study confirm the importance of T245G polymorphism in OPG gene in the pathogenesis of osteoporosis.

Keywords: OPG gene, T245G polymorphism, osteoporosis, T245G polymorphism, real-time PCR

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Authors: Tiancheng Lan

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E10A is a kind of replication-defective adenovirus which carries the human endostatin gene to inhibit the growth of tumors. Kringle 5(K5) has almost the same function as angiostatin to also inhibit the growth of tumors since they are all the byproduct of the proteolytic cleavage of plasminogen. Tumor size increasing can be suppressed because both of the endostatin and K5 can restrain the angiogenesis process. Therefore, in order to improve the treatment effect on tumor, 2A peptide is used to construct a fusion gene carrying both E10A and K5. Using 2A peptide is an ideal strategy when a fusion gene is expressed because it can avoid many problems during the expression of more than one kind of protein. The overlap extension PCR is also used to connect 2A peptide with E10A and K5. The final construction of fusion gene E10A-2A-K5 can provide a possible new method of the anti-angiogenesis treatment with a better expression performance.

Keywords: E10A, Kringle 5, 2A peptide, overlap extension PCR

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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