scholarly journals A Computational Framework for Tracing the Origins of Genomic Islands in Prokaryotes

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Peng Wan ◽  
Dongsheng Che
Keyword(s):  
Operating System ◽  
Main Idea ◽  
Computational Approach ◽  
Genomic Islands ◽  
Computational Framework ◽  
Blast Search ◽  
Gene Level ◽  
Genome Search ◽  
Genomic Regions ◽  
Query Genome

Genomic islands (GIs) are chunks of genomic fragments that are acquired from nongenealogical organisms through horizontal gene transfer (HGT). Current researches on studying donor-recipient relationships for HGT are limited at a gene level. As more GIs have been identified and verified, the way of studying donor-recipient relationships can be better modeled by using GIs rather than individual genes. In this paper, we report the development of a computational framework for detecting origins of GIs. The main idea of our computational framework is to identify GIs in a query genome, search candidate genomes that contain genomic regions similar to those GIs in the query genome by BLAST search, and then filter out some candidate genomes if those similar genomic regions are also alien (detected by GI detection tools). We have applied our framework in finding the GI origins for Mycobacterium tuberculosis H37Rv, Herminiimonas arsenicoxydans, and three Thermoanaerobacter species. The predicted results were used to establish the donor-recipient network relationships and visualized by Gephi. Our studies have shown that donor genomes detected by our computational approach were mainly consistent with previous studies. Our framework was implemented with Perl and executed on Windows operating system.

Identification of genomic islands in Synechococcus sp. WH8102 using genomic barcode and whole-genome microarray analyses

2020 ◽  
Vol 15 ◽  
Author(s):  
Jiahui Pan ◽  
Xizi Luo ◽  
Tong Shao ◽  
Chaoying Li ◽  
Tingting Zhao ◽  
...  
Keyword(s):  
Genomic Islands ◽  
Whole Genome ◽  
Photosynthetic Organisms ◽  
Depth Study ◽  
Whole Genome Microarray ◽  
Integrated Methods ◽  
Synechococcus Sp ◽  
Intuitive View ◽  
Genomic Regions ◽  
Different Origins

Background: Synechococcus sp. WH8102 is one of the most abundant photosynthetic organisms in many ocean regions. Objective: The aim of this study is to identify genomic islands (GIs) in Synechococcus sp. WH8102 with integrated methods. Methods: We have applied genomic barcode to identify the GIs in Synechococcus sp. WH8102, which could make genomic regions of different origins visually apparent. The gene expression data of the predicted GIs was analyzed through microarray data which was collected for functional analysis of the relevant genes. Results: Seven GIs were identified in Synechococcus sp. WH8102. Most of them are involved in cell surface modification, photosynthesis and drug resistance. In addition, our analysis also revealed the functions of these GIs, which could be used for in-depth study on the evolution of this strain. Conclusion: Genomic barcodes provide us with a comprehensive and intuitive view of the target genome. We can use it to understand the intrinsic characteristics of the whole genome and identify GIs or other similar elements.

Platform Independent Analysis of Probabilities on Multithreaded Programs

2013 ◽  
Vol 1 (3) ◽  
pp. 48-65
Author(s):  
Yuting Chen
Keyword(s):  
Operating System ◽  
Static Analysis ◽  
Main Idea ◽  
Experimental Results ◽  
Machine To Machine ◽  
Concurrent Program ◽  
Acceptable Accuracy ◽  
Multithreaded Programs ◽  
Independent Analysis ◽  
And Performance

A concurrent program is intuitively associated with probability: the executions of the program can produce nondeterministic execution program paths due to the interleavings of threads, whereas some paths can always be executed more frequently than the others. An exploration of the probabilities on the execution paths is expected to provide engineers or compilers with support in helping, either at coding phase or at compile time, to optimize some hottest paths. However, it is not easy to take a static analysis of the probabilities on a concurrent program in that the scheduling of threads of a concurrent program usually depends on the operating system and hardware (e.g., processor) on which the program is executed, which may be vary from machine to machine. In this paper the authors propose a platform independent approach, called ProbPP, to analyzing probabilities on the execution paths of the multithreaded programs. The main idea of ProbPP is to calculate the probabilities on the basis of two kinds of probabilities: Primitive Dependent Probabilities (PDPs) representing the control dependent probabilities among the program statements and Thread Execution Probabilities (TEPs) representing the probabilities of threads being scheduled to execute. The authors have also conducted two preliminary experiments to evaluate the effectiveness and performance of ProbPP, and the experimental results show that ProbPP can provide engineers with acceptable accuracy.

scholarly journals panRGP: a pangenome-based method to predict genomic islands and explore their diversity

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i651-i658 ◽  
Author(s):  
Adelme Bazin ◽  
Guillaume Gautreau ◽  
Claudine Médigue ◽  
David Vallenet ◽  
Alexandra Calteau
Keyword(s):  
Escherichia Coli ◽  
Gene Transfer ◽  
Horizontal Gene Transfer ◽  
Species Level ◽  
Genomic Islands ◽  
Genome Plasticity ◽  
Reference Dataset ◽  
Prokaryotic Genomes ◽  
Ideal Approach ◽  
Genomic Regions

Abstract Motivation Horizontal gene transfer (HGT) is a major source of variability in prokaryotic genomes. Regions of genome plasticity (RGPs) are clusters of genes located in highly variable genomic regions. Most of them arise from HGT and correspond to genomic islands (GIs). The study of those regions at the species level has become increasingly difficult with the data deluge of genomes. To date, no methods are available to identify GIs using hundreds of genomes to explore their diversity. Results We present here the panRGP method that predicts RGPs using pangenome graphs made of all available genomes for a given species. It allows the study of thousands of genomes in order to access the diversity of RGPs and to predict spots of insertions. It gave the best predictions when benchmarked along other GI detection tools against a reference dataset. In addition, we illustrated its use on metagenome assembled genomes by redefining the borders of the leuX tRNA hotspot, a well-studied spot of insertion in Escherichia coli. panRPG is a scalable and reliable tool to predict GIs and spots making it an ideal approach for large comparative studies. Availability and implementation The methods presented in the current work are available through the following software: https://github.com/labgem/PPanGGOLiN. Detailed results and scripts to compute the benchmark metrics are available at https://github.com/axbazin/panrgp_supdata.

scholarly journals Genome-wide patterns of divergence during speciation: the lake whitefish case study

2012 ◽  
Vol 367 (1587) ◽  
pp. 354-363 ◽  
Author(s):  
S. Renaut ◽  
N. Maillet ◽  
E. Normandeau ◽  
C. Sauvage ◽  
N. Derome ◽  
...  
Keyword(s):  
Reproductive Isolation ◽  
Genomic Islands ◽  
Next Generation Sequencing Data ◽  
Adaptive Divergence ◽  
Phenotypic Traits ◽  
Lake Whitefish ◽  
Sequencing Data ◽  
Species Pairs ◽  
Selective Forces ◽  
Genomic Regions

The nature, size and distribution of the genomic regions underlying divergence and promoting reproductive isolation remain largely unknown. Here, we summarize ongoing efforts using young (12 000 yr BP) species pairs of lake whitefish ( Coregonus clupeaformis ) to expand our understanding of the initial genomic patterns of divergence observed during speciation. Our results confirmed the predictions that: (i) on average, phenotypic quantitative trait loci (pQTL) show higher F ST values and are more likely to be outliers (and therefore candidates for being targets of divergent selection) than non-pQTL markers; (ii) large islands of divergence rather than small independent regions under selection characterize the early stages of adaptive divergence of lake whitefish; and (iii) there is a general trend towards an increase in terms of numbers and size of genomic regions of divergence from the least (East L.) to the most differentiated species pair (Cliff L.). This is consistent with previous estimates of reproductive isolation between these species pairs being driven by the same selective forces responsible for environment specialization. Altogether, dwarf and normal whitefish species pairs represent a continuum of both morphological and genomic differentiation contributing to ecological speciation. Admittedly, much progress is still required to more finely map and circumscribe genomic islands of speciation. This will be achieved through the use of next generation sequencing data but also through a better quantification of phenotypic traits moulded by selection as organisms adapt to new environmental conditions.

scholarly journals The clc Element of Pseudomonas sp. Strain B13, a Genomic Island with Various Catabolic Properties

2006 ◽  
Vol 188 (5) ◽  
pp. 1999-2013 ◽  
Author(s):  
Muriel Gaillard ◽  
Tatiana Vallaeys ◽  
Frank Jörg Vorhölter ◽  
Marco Minoia ◽  
Christoph Werlen ◽  
...  
Keyword(s):  
Nucleotide Sequence ◽  
Open Reading Frames ◽  
Genomic Islands ◽  
Functional Prediction ◽  
Bacterial Genomes ◽  
Burkholderia Xenovorans ◽  
Integrative And Conjugative Elements ◽  
Genomic Regions ◽  
Catabolic Plasmids ◽  
Reading Frames

ABSTRACT Pseudomonas sp. strain B13 is a bacterium known to degrade chloroaromatic compounds. The properties to use 3- and 4-chlorocatechol are determined by a self-transferable DNA element, the clc element, which normally resides at two locations in the cell's chromosome. Here we report the complete nucleotide sequence of the clc element, demonstrating the unique catabolic properties while showing its relatedness to genomic islands and integrative and conjugative elements rather than to other known catabolic plasmids. As far as catabolic functions, the clc element harbored, in addition to the genes for chlorocatechol degradation, a complete functional operon for 2-aminophenol degradation and genes for a putative aromatic compound transport protein and for a multicomponent aromatic ring dioxygenase similar to anthranilate hydroxylase. The genes for catabolic functions were inducible under various conditions, suggesting a network of catabolic pathway induction. For about half of the open reading frames (ORFs) on the clc element, no clear functional prediction could be given, although some indications were found for functions that were similar to plasmid conjugation. The region in which these ORFs were situated displayed a high overall conservation of nucleotide sequence and gene order to genomic regions in other recently completed bacterial genomes or to other genomic islands. Most notably, except for two discrete regions, the clc element was almost 100% identical over the whole length to a chromosomal region in Burkholderia xenovorans LB400. This indicates the dynamic evolution of this type of element and the continued transition between elements with a more pathogenic character and those with catabolic properties.

scholarly journals A Computational Method Involving Surface Area to Volume Ratio to Estimate Inorganic Nanoparticle Efficacy

2021 ◽  
Author(s):  
Wesley A. Williams ◽  
Ashley J. Denslow ◽  
Peter W. Radulovic ◽  
Daniel J. Denmark ◽  
Shyam S. Mohapatra
Keyword(s):  
Operating System ◽  
Drug Delivery ◽  
Surface Area ◽  
Imaging Modality ◽  
Drug Loading ◽  
Volume Ratio ◽  
Computational Approach ◽  
Inorganic Nanoparticles ◽  
Computational Method ◽  
Simultaneous Sensing

Inorganic nanoparticles are utilized for therapeutic, diagnostic, or theranostic purposes and the latter involve simultaneous sensing, imaging, or tracking of drug delivery. Further, these nanoparticles differ in their morphologies, which affect outcomes such as the effectiveness of hyperthermia, induction, drug loading, circulation time by escaping the body's immune system, imaging modality clarity, and biosensing. However, design of these theranostics is limited by the lack of a method to predict their therapeutic efficacy. Herein, we report a computational approach involving the surface area (SA) to volume (V) ratios (SA:V), which can help predict the efficacy of the inorganic nanoparticles. The approach comprises a coding platform for the comparator pro-gram and uses a Python 3 on a Windows 10 operating system. Analyses of 22 polyhedral morphologies that inorganic nanoparticles could assume ex silico showed that only particular concave morphologies in this size regime are more productive over the standard sizes. Our results provide a method that can aid in the predicting efficacy of inorganic nanoparticles with certain morphology.

scholarly journals Comparative analyses of SAR-CoV2 genomes from different geographical locations and other coronavirus family genomes reveals unique features potentially consequential to host-virus interaction and pathogenesis

2020 ◽  
Author(s):  
Rahila Sardar ◽  
Deepshikha Satish ◽  
Shweta Birla ◽  
Dinesh Gupta
Keyword(s):  
Target Gene ◽  
Mutational Analysis ◽  
Viral Pathogenesis ◽  
Computational Approach ◽  
Surface Glycoprotein ◽  
Host Responses ◽  
Gene Level ◽  
Virus Interaction ◽  
The Impact ◽  
Geographical Locations

AbstractThe ongoing pandemic of the coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). We have performed an integrated sequence-based analysis of SARS-CoV2 genomes from different geographical locations in order to identify its unique features absent in SARS-CoV and other related coronavirus family genomes, conferring unique infection, facilitation of transmission, virulence and immunogenic features to the virus. The phylogeny of the genomes yields some interesting results. Systematic gene level mutational analysis of the genomes has enabled us to identify several unique features of the SARS-CoV2 genome, which includes a unique mutation in the spike surface glycoprotein (A930V (24351C>T)) in the Indian SARS-CoV2, absent in other strains studied here. We have also predicted the impact of the mutations in the spike glycoprotein function and stability, using computational approach. To gain further insights into host responses to viral infection, we predict that antiviral host-miRNAs may be controlling the viral pathogenesis. Our analysis reveals nine host miRNAs which can potentially target SARS-CoV2 genes. Interestingly, the nine miRNAs do not have targets in SARS and MERS genomes. Also, hsa-miR-27b is the only unique miRNA which has a target gene in the Indian SARS-CoV2 genome. We also predicted immune epitopes in the genomes

scholarly journals A computational framework for colour metrics and colour space transforms

2016 ◽  
Vol 2 ◽  
pp. e48 ◽  
Author(s):  
Ivar Farup
Keyword(s):  
Main Idea ◽  
Object Oriented ◽  
Colour Difference ◽  
Colour Space ◽  
Computational Framework ◽  
Class Hierarchy ◽  
Computational Overhead ◽  
Python Programming Language ◽  
Python Programming ◽  
Metric Tensors

An object-oriented computational framework for the transformation of colour data and colour metric tensors is presented. The main idea of the design is to represent the transforms between spaces as compositions of objects from a class hierarchy providing the methods for both the transforms themselves and the corresponding Jacobian matrices. In this way, new colour spaces can be implemented on the fly by transforming from any existing colour space, and colour data in various formats as well as colour metric tensors and colour difference data can easily be transformed between the colour spaces. This reduces what normally requires several days of coding to a few lines of code without introducing a significant computational overhead. The framework is implemented in the Python programming language.

scholarly journals RNAModR: Functional analysis of mRNA modifications in R

2016 ◽  
Author(s):  
Maurits Evers ◽  
Andrew Shafik ◽  
Ulrike Schumann ◽  
Thomas Preiss
Keyword(s):  
Statistical Evaluation ◽  
R Package ◽  
Wide Distribution ◽  
Messenger Rnas ◽  
Computational Framework ◽  
Site Distribution ◽  
Mrna Structure ◽  
Gene Level ◽  
Insight Into

AbstractMotivationResearch in the emerging field of epitranscriptomics is increasingly generating comprehensive maps of chemical modifications in messenger RNAs (mRNAs). A computational framework allowing a reproducible and standardised analysis of these mRNA modification data is missing, but will be crucial for reliable functional meta-gene analyses and cross-study comparisons.ResultsWe have developed RNAModR, an open-source and R-based set of methods, to analyse and visualise the transcriptome-wide distribution of mRNA modifications. RNAModR allows the statistical evaluation of the mRNA modification site distribution relative to null sites on a meta-gene level, providing insight into the functional role of these mRNA modifications on e.g. mRNA structure and stability.Availability and implementationRNAModR is available under the GNU General Public License (GPL) as an R-package from https://github.com/mevers/[email protected]

scholarly journals Acquisition and Evolution of the exoU Locus in Pseudomonas aeruginosa

2006 ◽  
Vol 188 (11) ◽  
pp. 4037-4050 ◽  
Author(s):  
Bridget R. Kulasekara ◽  
Hemantha D. Kulasekara ◽  
Matthew C. Wolfgang ◽  
Lisa Stevens ◽  
Dara W. Frank ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Type Iii Secretion ◽  
Genomic Island ◽  
Genomic Islands ◽  
Targeted Mutagenesis ◽  
Host Cells ◽  
System A ◽  
Transmissible Plasmid ◽  
Genomic Regions ◽  
Functional Analyses

ABSTRACT ExoU is a potent Pseudomonas aeruginosa cytotoxin translocated into host cells by the type III secretion system. A comparison of genomes of various P. aeruginosa strains showed that that the ExoU determinant is found in the same polymorphic region of the chromosome near a tRNALys gene, suggesting that exoU is a horizontally acquired virulence determinant. We used yeast recombinational cloning to characterize four distinct ExoU-encoding DNA segments. We then sequenced and annotated three of these four genomic regions. The sequence of the largest DNA segment, named ExoU island A, revealed many plasmid- and genomic island-associated genes, most of which have been conserved across a broad set of β- and γ-Proteobacteria. Comparison of the sequenced ExoU-encoding genomic islands to the corresponding PAO1 tRNALys-linked genomic island, the pathogenicity islands of strain PA14, and pKLC102 of clone C strains allowed us to propose a mechanism for the origin and transmission of the ExoU determinant. The evolutionary history very likely involved transposition of the ExoU determinant onto a transmissible plasmid, followed by transfer of the plasmid into different P. aeruginosa strains. The plasmid subsequently integrated into a tRNALys gene in the chromosome of each recipient, where it acquired insertion sequences and underwent deletions and rearrangements. We have also applied yeast recombinational cloning to facilitate a targeted mutagenesis of ExoU island A, further demonstrating the utility of the specific features of the yeast capture vector for functional analyses of genes on large horizontally acquired genetic elements.

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