scholarly journals An in silico analysis of robust but fragile gene regulation links enhancer length to robustness

2019 ◽  
Author(s):  
Kenneth A Barr ◽  
John Reinitz ◽  
Ovidiu Radulescu
Keyword(s):  
Gene Regulation ◽  
In Silico ◽  
In Silico Analysis ◽  
Mathematical Concept ◽  
Sequence Length ◽  
Local Concentration ◽  
Quantitative Evidence ◽  
Regulatory Systems ◽  
Genetic Sequences ◽  
Gene Regulatory

1AbstractOrganisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is robust to a perturbation in up to r - 1 randomly chosen parameters. In this work we use this idea to investigate the robustness of gene regulation using a sequence level model of the Drosophila melanogaster gene even-skipped. We find that gene regulation can be remarkably sensitive to changes in transcription factor concentrations at the boundaries of expression features, while it is robust to perturbation elsewhere. We also find that the length of sequence used to control an expression feature correlates negatively with the number of nucleotides that are sensitive to mutation in both natural and in silico predicted enhancers. In all cases, the exact degree of robustness obtained is dependent not only on DNA sequence, but also on the local concentration of regulatory factors. By analyzing both natural and synthetic sequences, we provide strong quantitative evidence that increased sequence length makes gene regulatory systems more robust to genetic perturbation.2Author SummaryRobustness assures that organisms can survive when faced with unpredictable environments or genetic mutations. In this work, we characterize the robustness of gene regulation using an experimentally validated model of the regulation of the Drosophila gene even-skipped. We use a mathematically precise definition of robustness that allows us to make quantitative comparisons of robustness between different genetic sequences or between different nuclei. From this analysis, we found that genetic sequences that were not previously known to be important for gene regulation reduce sensitivity to genetic perturbation. In contrast, we found that gene regulation can be very sensitive to the levels of regulators. This extreme sensitivity was only observed at the boundaries of expression features, where switch-like behavior is desirable. This highlights the importance of considering context when assessing robustness.

scholarly journals In Silico Study Suggesting the Bias of Primers Choice in the Molecular Identification of Fungal Aerosols

2021 ◽  
Vol 7 (2) ◽  
pp. 99
Author(s):  
Hamza Mbareche ◽  
Marc Veillette ◽  
Guillaume J. Bilodeau
Keyword(s):  
In Silico ◽  
Fungal Diversity ◽  
High Throughput Sequencing ◽  
In Silico Analysis ◽  
Its Region ◽  
Internal Transcribed Spacers ◽  
Sequence Length ◽  
Universal Method ◽  
Continuous Work ◽  
Its1 And Its2

This paper presents an in silico analysis to assess the current state of the fungal UNITE database in terms of the two eukaryote nuclear ribosomal regions, Internal Transcribed Spacers 1 and 2 (ITS1 and ITS2), used in describing fungal diversity. Microbial diversity is often evaluated with amplicon-based high-throughput sequencing approaches, which is a target enrichment method that relies on the amplification of a specific target using particular primers before sequencing. Thus, the results are highly dependent on the quality of the primers used for amplification. The goal of this study is to validate if the mismatches of the primers on the binding sites of the targeted taxa could explain the differences observed when using either ITS1 or ITS2 in describing airborne fungal diversity. Hence, the choice of the pairs of primers for each barcode concur with a study comparing the performance of ITS1 and ITS2 in three occupational environments. The sequence length varied between the amplicons retrieved from the UNITE database using the pair of primers targeting ITS1 and ITS2. However, the database contains an equal number of unidentified taxa from ITS1 and ITS2 regions in the six taxonomic levels employed (phylum, class, order, family, genus, species). The chosen ITS primers showed differences in their ability to amplify fungal sequences from the UNITE database. Eleven taxa consisting of Trichocomaceae, Dothioraceae, Botryosphaeriaceae, Mucorales, Saccharomycetes, Pucciniomycetes, Ophiocordyceps, Microsporidia, Archaeorhizomycetes, Mycenaceae, and Tulasnellaceae showed large variations between the two regions. Note that members of the latter taxa are not all typical fungi found in the air. As no universal method is currently available to cover all the fungal kingdom, continuous work in designing primers, and particularly combining multiple primers targeting the ITS region is the best way to compensate for the biases of each one to get a larger view of the fungal diversity.

In Silico Analysis of miRNA-Mediated Gene Regulation in OCA and OA Genes

2014 ◽  
Vol 70 (3) ◽  
pp. 1923-1932 ◽  
Author(s):  
Balu Kamaraj ◽  
Chandrasekhar Gopalakrishnan ◽  
Rituraj Purohit
Keyword(s):  
Gene Regulation ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

scholarly journals The role of mobile genetic elements in evolution of cyanobacteria

2011 ◽  
Vol 9 (4) ◽  
pp. 52-62
Author(s):  
Lidia E Mikheeva ◽  
Elena A Karbysheva ◽  
Sergey V Shestakov
Keyword(s):  
Gene Regulation ◽  
Significant Role ◽  
In Silico ◽  
In Silico Analysis ◽  
Whole Genome ◽  
Number Of Genes ◽  
Genes Encoding ◽  
Adaptation Processes ◽  
Silico Analysis

Possible pathways of cyanobacterial evolution are discussed on the basis of in silico analysis of fully sequenced genomes of 45 species/strains of cyanobacteria. The information on quantity and functions of different mobile elements (IS, MITE elements and group II introns) was reviewed. Positive correlation between whole genome sizes and number of genes, encoding transposases has been revealed. It is suggested that transpositions play significant role in genome rearrangements taking part in gene regulation and adaptation processes determining the directions of microevolution processes in cyanobacterial populations.

scholarly journals An in silico analysis of robust but fragile gene regulation links enhancer length to robustness

2019 ◽  
Vol 15 (11) ◽  
pp. e1007497 ◽  
Author(s):  
Kenneth Barr ◽  
John Reinitz ◽  
Ovidiu Radulescu
Keyword(s):  
Gene Regulation ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

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

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

Identification of BAP1-associated MicroRNAs and Implications in Cancer Development

2019 ◽  
pp. 1-4
Author(s):  
Tikam Chand ◽  
Tikam Chand
Keyword(s):  
Gene Regulation ◽  
In Silico ◽  
Mirna Target ◽  
Target Prediction ◽  
Differential Regulation ◽  
Cancer Development ◽  
Mirna Target Prediction ◽  
Cancer Types ◽  
In Silico Tools

Having role in gene regulation and silencing, miRNAs have been implicated in development and progression of a number of diseases, including cancer. Herein, I present potential miRNAs associated with BAP1 gene identified using in-silico tools such as TargetScan and Exiqon miRNA Target Prediction. I identified fifteen highly conserved miRNA (hsa-miR-423-5p, hsa-miR-3184-5p, hsa-miR-4319, hsa-miR125b-5p, hsa-miR-125a-5p, hsa-miR-6893-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-505-3p.1, hsa-miR-429, hsa-miR-370-3p, hsa-miR-125a-5p, hsa-miR-141-3p, hsa-miR-200a-3p, and hsa-miR-429) associated with BAP1 gene. We also predicted the differential regulation of these twelve miRNAs in different cancer types.

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

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
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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