In silico Analysis and Expression Patterns of TmLysozyme-like Gene in Tenebrio molitor

Plant dicarboxylate carriers (DICs) transport a wide range of dicarboxylates across the mitochondrial inner membrane. The Arabidopsis thalianaDIC family is composed of three genes (AtDIC1, 2 and 3), whereas two genes (EgDIC1 and EgDIC2) have been retrieved in Eucalyptus grandis. Here, by combining in silico and in planta analyses, we provide evidence that DICs are partially redundant, important in plant adaptation to environmental stresses and part of a low-oxygen response in both species. AtDIC1 and AtDIC2 are present in most plant species and have very similar gene structure, developmental expression patterns and absolute expression across natural Arabidopsis accessions. In contrast, AtDIC3 seems to be an early genome acquisition found in Brassicaceae and shows relatively low (or no) expression across these accessions. In silico analysis revealed that both AtDICs and EgDICs are highly responsive to stresses, especially to cold and submergence, while their promoters are enriched for stress-responsive transcription factors binding sites. The expression of AtDIC1 and AtDIC2 is highly correlated across natural accessions and in response to stresses, while no correlation was found for AtDIC3. Gene ontology enrichment analysis suggests a role for AtDIC1 and AtDIC2 in response to hypoxia, and for AtDIC3 in phosphate starvation. Accordingly, the investigated genes are induced by submergence stress in A. thaliana and E. grandis while AtDIC2 overexpression improved seedling survival to submergence. Interestingly, the induction of AtDIC1 and AtDIC2 is abrogated in the erfVII mutant that is devoid of plant oxygen sensing, suggesting that these genes are part of a conserved hypoxia response in Arabidopsis.

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The Expression Patterns of BECN1, LAMP2, and PINK1 Genes in Colorectal Cancer Are Potentially Regulated by Micrornas and CpG Islands: An In Silico Study

Journal of Clinical Medicine ◽

10.3390/jcm9124020 ◽

2020 ◽

Vol 9 (12) ◽

pp. 4020

Author(s):

Martyna Bednarczyk ◽

Edyta Fatyga ◽

Sylwia Dzięgielewska-Gęsiak ◽

Dariusz Waniczek ◽

Beniamin Grabarek ◽

...

Keyword(s):

Colorectal Cancer ◽

In Silico ◽

Expression Patterns ◽

Cpg Islands ◽

In Silico Analysis ◽

Epigenetic Changes ◽

Grid Infrastructure ◽

In Silico Study ◽

Silico Analysis

Background: Autophagy plays a dual role of tumor suppression and tumor promotion in colorectal cancer. The study aimed to find those microRNAs (miRNAs) important in BECN1, LAMP2, and PINK1 regulation and to determine the possible role of the epigenetic changes in examined colorectal cancer using an in silico approach. Methods: A total of 44 pairs of surgically removed tumors at clinical stages I‒IV and healthy samples (marginal tissues) from patients’ guts were analyzed. Analysis of the obtained results was conducted using the PL-Grid Infrastructure and Statistica 12.0 program. The miRNAs and CpG islands were estimated using the microrna.org database and MethPrimer program. Results: The autophagy-related genes were shown to be able to be regulated by miRNAs (BECN1—49 mRNA, LAMP2—62 mRNA, PINK1—6 mRNA). It was observed that promotion regions containing at least one CpG region were present in the sequence of each gene. Conclusions: The in silico analysis performed allowed us to determine the possible role of epigenetic mechanisms of regulation gene expression, which may be an interesting therapeutic target in the treatment of colorectal cancer.

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Comparative in Silico Analysis of Ferric Reduction Oxidase (FRO) Genes Expression Patterns in Response to Abiotic Stresses, Metal and Hormone Applications

Molecules ◽

10.3390/molecules23051163 ◽

2018 ◽

Vol 23 (5) ◽

pp. 1163 ◽

Cited By ~ 6

Author(s):

Izhar Muhammad ◽

Xiu-Qing Jing ◽

Abdullah Shalmani ◽

Muhammad Ali ◽

Shi Yi ◽

...

Keyword(s):

In Silico ◽

Abiotic Stresses ◽

Expression Patterns ◽

In Silico Analysis ◽

Genes Expression ◽

Silico Analysis

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Comparative gene-based in silico analysis of transcriptomes in different bovine tissues and (or) organs

Genome ◽

10.1139/g04-084 ◽

2004 ◽

Vol 47 (6) ◽

pp. 1164-1172 ◽

Cited By ~ 2

Author(s):

Zhihua Jiang ◽

Xiao-Lin Wu ◽

Matthew D Garcia ◽

Kirsten B Griffin ◽

Jennifer J Michal ◽

...

Keyword(s):

Expressed Sequence Tags ◽

In Silico ◽

Expression Patterns ◽

In Silico Analysis ◽

Orthologous Genes ◽

Functional Relations ◽

Human Genes ◽

Expressed Sequence ◽

Silico Analysis ◽

Tissue Library

A gene-based approach was used to annotate 322 168 cattle expressed sequence tags (ESTs) based on human genes in order to census the transcriptomes, analyze their expression similarities, and identify genes preferentially expressed in different bovine tissues and (or) organs. Of the 34 157 human coding genes used in a standalone BLAST search, 14 928 could be matched with provisional orthologous sequences in a total of 230 135 bovine ESTs. The remaining 92 033 bovine ESTs were estimated to represent an additional 5970 genes in cattle. On average, ~8600 genes were estimated to be expressed in a single tissue and (or) organ and 13 000 in a pooled tissue library. On the basis of the estimated numbers of genes, no more than 3% of genes would be missed when ~34 000 ESTs were sequenced from a single tissue and (or) organ library and ~40 000 ESTs from a pooled source, respectively. Cluster analyses of the gene expression patterns among 12 single tissues and (or) organs in cattle revealed that their expression similarities would depend on physiological functions. In addition, a total of 1502 genes were identified as preferentially expressed genes in these 12 single tissues and (or) organs with LOD (logarithm of the odds, base 10) ≥ 3.0. Therefore, our study provides some insights for further investigating the developmental and functional relations of various tissues and organs in mammals.Key words: cattle, expressed sequence tags (ESTs), orthologous genes, comparative gene-based approach, in silico census, tissue/organs, transcriptomes.

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A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

Seminars in Oncology ◽

10.1053/j.seminoncol.2020.02.012 ◽

2020 ◽

Vol 47 (6) ◽

pp. 398-408

Author(s):

Sonam Tulsyan ◽

Showket Hussain ◽

Balraj Mittal ◽

Sundeep Singh Saluja ◽

Pranay Tanwar ◽

...

Keyword(s):

Systematic Review ◽

Gallbladder Carcinoma ◽

In Silico ◽

In Silico Analysis ◽

Transcriptomic Profile ◽

Silico Analysis

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In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

10.1055/s-0039-1680245 ◽

2019 ◽

Author(s):

I. Farah ◽

A. El-Mubark ◽

M. Osman ◽

A. Soliman ◽

F. Ali ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

In Silico ◽

In Silico Analysis ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Prothrombin Gene ◽

Silico Analysis

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Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

Current Medicinal Chemistry ◽

10.2174/0929867327666200727114410 ◽

2020 ◽

Vol 27 (38) ◽

pp. 6523-6535 ◽

Cited By ~ 3

Author(s):

Antreas Afantitis ◽

Andreas Tsoumanis ◽

Georgia Melagraki

Keyword(s):

Data Analysis ◽

Virtual Screening ◽

In Silico ◽

Model Development ◽

In Silico Analysis ◽

Material Design ◽

Efficient Solutions ◽

Biological Data ◽

Cost Efficient ◽

Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

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