GENPPI: standalone software for creating protein interaction networks from genomes

Abstract BackGround Bacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships capable of being annotated only from genomes are conserved gene neighbourhoods (CNs), phylogenetic profiles (PPs), and gene fusions. At present, there is no standalone software that enables networks of interactions among proteins to be created using these three evolutionary characteristics with efficient and effective results. Results We developed GENPPI software for the ab initio prediction of interaction networks using predicted proteins from a genome. In our case study, we employed 50 genomes of the genus Corynebacterium. Based on the PP relationship, GENPPI differentiated genomes between the ovis and equi biovars of the species Corynebacterium pseudotuberculosis and created groups among the other species analysed. If we inspected only the CN relationship, we could not entirely separate biovars, only species. Our software GENPPI was determined to be efficient because, for example, it creates interaction networks from the central genomes of 50 species/lineages with an average size of 2200 genes in less than 40 min on a conventional computer. Moreover, the interaction networks that our software creates reflect correct evolutionary relationships between species, which we confirmed with average nucleotide identity analyses. Additionally, this software enables the user to define how he or she intends to explore the PP and CN characteristics through various parameters, enabling the creation of customized interaction networks. For instance, users can set parameters regarding the genus, metagenome, or pangenome. In addition to the parameterization of GENPPI, it is also the user’s choice regarding which set of genomes they are going to study. Conclusions GENPPI can help fill the gap concerning the considerable number of novel genomes assembled monthly and our ability to process interaction networks considering the noncore genes for all completed genome versions. With GENPPI, a user dictates how many and how evolutionarily correlated the genomes answer a scientific query.

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Systematic Detection of Large-Scale Multi-Gene Horizontal Transfer in Prokaryotes

Molecular Biology and Evolution ◽

10.1093/molbev/msab043 ◽

2021 ◽

Author(s):

Lina Kloub ◽

Sean Gosselin ◽

Matthew Fullmer ◽

Joerg Graf ◽

J Peter Gogarten ◽

...

Keyword(s):

Gene Transfer ◽

Large Scale ◽

Single Gene ◽

Gene Families ◽

Microbial Evolution ◽

Phylogenetic Distance ◽

Secretion Systems ◽

Type Iii Secretion Systems ◽

A Genome ◽

Conserved Gene

Abstract Horizontal gene transfer (HGT) is central to prokaryotic evolution. However, little is known about the “scale” of individual HGT events. In this work, we introduce the first computational framework to help answer the following fundamental question: How often does more than one gene get horizontally transferred in a single HGT event? Our method, called HoMer, uses phylogenetic reconciliation to infer single-gene HGT events across a given set of species/strains, employs several techniques to account for inference error and uncertainty, combines that information with gene order information from extant genomes, and uses statistical analysis to identify candidate horizontal multi-gene transfers (HMGTs) in both extant and ancestral species/strains. HoMer is highly scalable and can be easily used to infer HMGTs across hundreds of genomes. We apply HoMer to a genome-scale dataset of over 22000 gene families from 103 Aeromonas genomes and identify a large number of plausible HMGTs of various scales at both small and large phylogenetic distances. Analysis of these HMGTs reveals interesting relationships between gene function, phylogenetic distance, and frequency of multi-gene transfer. Among other insights, we find that (i) the observed relative frequency of HMGT increases as divergence between genomes increases, (ii) HMGTs often have conserved gene functions, and (iii) rare genes are frequently acquired through HMGT. We also analyze in detail HMGTs involving the zonula occludens toxin and type III secretion systems. By enabling the systematic inference of HMGTs on a large scale, HoMer will facilitate a more accurate and more complete understanding of HGT and microbial evolution.

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A Review of Anti-Corruption Wars in Nigeria

Africa’s Public Service Delivery and Performance Review ◽

10.4102/apsdpr.v2i3.63 ◽

2014 ◽

Vol 2 (3) ◽

pp. 153 ◽

Cited By ~ 2

Author(s):

Nnamdi Nwaodu ◽

David Adam ◽

Okechukwu Okereke

Keyword(s):

Qualitative Data ◽

Secondary Data ◽

Economic Life ◽

Recent Attempt ◽

Poverty Level ◽

Secondary Sources ◽

Online Databases ◽

Efficient Performance ◽

Financial Crimes

Corruption still subsists as one of the greatest challenges facing Nigeria. The existence of this phenomenon in virtually all aspects of the nation’s socio-economic life is said to be one reason why poverty level remains high irrespective of her position as the six highest suppliers of oil to the whole wide world, and a possessor of numerous other human and natural resources. A recent attempt by the Federal Government of Nigeria to curb this societal ill led to the establishment of Economic and Financial Crimes Commission (EFCC), the Independent Corrupt Practices & Related Offences Commission (ICPC) among others bodies. This paper historically explores the anti-corruption war in Nigeria and specifically zeros itself to review EFCC’s role in this war. The methodology adopted in this paper is the narrative-textual case study (NTCS), a research method that sources the required quantitative and qualitative secondary data on the phenomenon of study from secondary sources like the internet, World Wide Web, online databases, e-libraries et cetera. On the strength of the qualitative data sourced, it was discovered that the agency has made some successes but is being hindered by political, administrative and judicial bureaucracy from efficient performance. The paper therefore boldly recommends that transparency be enshrined into all aspect Nigerian political and administrative life and extant anti-graft laws be reviewed, harmonized and strengthened to enhance the effectiveness of fight against corruption and breach of corporate governance ethics by those holding political and non-political positions in Nigeria.

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Moving image analysis to the cloud: A case study with a genome-scale tomographic study

10.1063/1.4937539 ◽

2016 ◽

Cited By ~ 2

Author(s):

Kevin Mader ◽

Marco Stampanoni

Keyword(s):

Image Analysis ◽

Moving Image ◽

A Genome ◽

Genome Scale

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The Absence of Universally-Conserved Protein-coding Genes

10.1101/842633 ◽

2019 ◽

Author(s):

Change Laura Tan

Keyword(s):

Public Access ◽

Orphan Genes ◽

Protein Coding ◽

Great Opportunity ◽

Protein Coding Genes ◽

Phylogenetic Profiles ◽

Gene Count ◽

A Genome ◽

Wide Scale ◽

Specific Species

AbstractPublic access to thousands of completely sequenced and annotated genomes provides a great opportunity to address the relationships of different organisms, at the molecular level and on a genome-wide scale. Via comparing the phylogenetic profiles of all protein-coding genes in 317 model species described in the OrthoInspector3.0 database, we found that approximately 29.8% of the total protein-coding genes were orphan genes (genes unique to a specific species) while < 0.01% were universal genes (genes with homologs in each of the 317 species analyzed). When weighted by potential birth event, the orphan genes comprised 82% of the total, while the universal genes accounted for less than 0.00008%. Strikingly, as the analyzed genomes increased, the sum total of universal and nearly-universal genes plateaued while that of orphan and nearly-orphan genes grew continuously. When the compared species increased to the inclusion of 3863 bacteria, 711 eukaryotes, and 179 archaea, not one of the universal genes remained. The results speak to a previously unappreciated degree of genetic biodiversity, which we propose to quantify using the birth-event-weighted gene count method.

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Evolutionary Analyses of Protein Interaction Networks

Biological Data Mining in Protein Interaction Networks ◽

10.4018/978-1-60566-398-2.ch010 ◽

2009 ◽

pp. 169-181 ◽

Cited By ~ 2

Author(s):

Takashi Makino ◽

Aoife McLysaght

Keyword(s):

Molecular Evolution ◽

Comparative Genomics ◽

Protein Interaction ◽

Protein Interaction Networks ◽

Evolutionary Rates ◽

Interaction Networks ◽

Evolutionary Mechanisms ◽

Ancestral Gene ◽

Protein Protein Interaction ◽

A Genome

This chapter introduces evolutionary analyses of protein interaction networks and of proteins as components of the networks. The authors show relationships between proteins in the networks and their evolutionary rates. For understanding protein-protein interaction (PPI) divergence, duplicated genes are often compared because they are derived from a common ancestral gene. In order to reveal evolutionary mechanisms acting on the interactome it is necessary to compare PPIs across species. Investigation of co-localization of interacting genes in a genome shows that PPIs have an important role in the maintenance of a physical link between neighboring genes. The purpose of this chapter is to introduce methodologies for analyzing PPI data and to describe molecular evolution and comparative genomics insights gained from such studies.

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The mosaic of ancestral karyotype blocks in the Sinapis alba L. genome

Genome ◽

10.1139/g10-097 ◽

2011 ◽

Vol 54 (1) ◽

pp. 33-41 ◽

Cited By ~ 11

Author(s):

Matthew N. Nelson ◽

Isobel A.P. Parkin ◽

Derek J. Lydiate

Keyword(s):

Genetic Research ◽

Brassica Species ◽

Sinapis Alba ◽

Ancestral Karyotype ◽

Crop Species ◽

B Genome ◽

A Genome ◽

The Rich ◽

Conserved Gene ◽

First Time

The organisation of the Sinapis alba genome, comprising 12 linkage groups (n = 12), was compared with the Brassicaceae ancestral karyotype (AK) genomic blocks previously described in other crucifer species. Most of the S. alba genome falls into conserved triplicated genomic blocks that closely match the AK-defined genomic blocks found in other crucifer species including the A, B, and C genomes of closely related Brassica species. In one instance, an S. alba linkage group (S05) was completely collinear with one AK chromosome (AK1), the first time this has been observed in a member of the Brassiceae tribe. However, as observed for other members of the Brassiceae tribe, ancestral genomic blocks were fragmented in the S. alba genome, supporting previously reported comparative chromosome painting describing rearrangements of the AK karyotype prior to the divergence of the Brassiceae from other crucifers. The presented data also refute previous phylogenetic reports that suggest S. alba was more closely related to Brassica nigra (B genome) than to B. rapa (A genome) and B. oleracea (C genome). A comparison of the S. alba and Arabidopsis thaliana genomes revealed many regions of conserved gene order, which will facilitate access to the rich genomic resources available in the model species A. thaliana for genetic research in the less well-resourced crop species S. alba.

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The World Bacterial Biogeography and Biodiversity through Databases: A Case Study of NCBI Nucleotide Database and GBIF Database

BioMed Research International ◽

10.1155/2013/240175 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Okba Selama ◽

Phillip James ◽

Farida Nateche ◽

Elizabeth M. H. Wellington ◽

Hocine Hacène

Keyword(s):

Geographical Area ◽

Geographic Area ◽

Global Scale ◽

Service Access ◽

Novel Approach ◽

Online Databases ◽

The Usa ◽

Nucleotide Database ◽

Bacterial Biodiversity

Databases are an essential tool and resource within the field of bioinformatics. The primary aim of this study was to generate an overview of global bacterial biodiversity and biogeography using available data from the two largest public online databases, NCBI Nucleotide and GBIF. The secondary aim was to highlight the contribution each geographic area has to each database. The basis for data analysis of this study was the metadata provided by both databases, mainly, the taxonomy and the geographical area origin of isolation of the microorganism (record). These were directly obtained from GBIF through the online interface, whileE-utilitiesandPythonwere used in combination with a programmatic web service access to obtain data from the NCBI Nucleotide Database. Results indicate that the American continent, and more specifically the USA, is the top contributor, while Africa and Antarctica are less well represented. This highlights the imbalance of exploration within these areas rather than any reduction in biodiversity. This study describes a novel approach to generating global scale patterns of bacterial biodiversity and biogeography and indicates that theProteobacteriaare the most abundant and widely distributed phylum within both databases.

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Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer

Briefings in Bioinformatics ◽

10.1093/bib/bbz118 ◽

2019 ◽

Vol 21 (5) ◽

pp. 1742-1755 ◽

Cited By ~ 26

Author(s):

Siqi Bao ◽

Hengqiang Zhao ◽

Jian Yuan ◽

Dandan Fan ◽

Zicheng Zhang ◽

...

Keyword(s):

Breast Cancer ◽

Genomic Instability ◽

Genome Instability ◽

Risk Group ◽

Expression Profiles ◽

Risk Groups ◽

Low Risk ◽

A Genome ◽

Significant Difference

Abstract Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.

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The Economic and Geographical Aspects of the Status of Small-Scale Photovoltaic Systems in Hungary—A Case Study

Energies ◽

10.3390/en13133489 ◽

2020 ◽

Vol 13 (13) ◽

pp. 3489 ◽

Cited By ~ 3

Author(s):

Gábor Pintér ◽

Henrik Zsiborács ◽

Nóra Hegedűsné Baranyai ◽

András Vincze ◽

Zoltán Birkner

Keyword(s):

Power Plants ◽

Photovoltaic System ◽

Small Scale ◽

Photovoltaic Systems ◽

Comprehensive Investigation ◽

Photovoltaic Power ◽

The Status ◽

Average Size ◽

Geographical Locations

The use of solar energy is an obvious choice; the energy of the sun is not only indispensable for most processes in nature but it is also a clean, abundant, sustainable, and—most importantly—universally available resource. Although the further spread of photovoltaic systems, which make use of this source of energy, is expected in the future all around the world, no comprehensive investigation has been conducted into the current situation of the small-scale photovoltaic power plants in Hungary, where this type of photovoltaic system is the most popular. By means of a case study, whose novelty lies in its focus on small-scale power plants and their complex examination, including economic and geographic indicators, this paper analyzes their status in Hungary. The study endeavors to establish the reasons for the popularity of this type of power plant and to identify some typical geographical locations with well-illustrated photovoltaic density. Residential, as well as business prosumers, were examined with the aim of learning more about the density of the small-scale photovoltaic systems and their geographical locations. Another goal was to calculate the average size of small-scale photovoltaic power plants and to gain more understanding of their economic aspects. The outcomes of this research include maps displaying the density of the small-scale photovoltaic power plants in Hungary and the results of the economic calculations for such investments.

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