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      Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes

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          Abstract

          Geptop has performed effectively in the identification of prokaryotic essential genes since its first release in 2013. It estimates gene essentiality for prokaryotes based on orthology and phylogeny. Genome-scale essentiality data of more prokaryotic species are available, and the information has been collected into public essential gene repositories such as DEG and OGEE. A faster and more accurate toolkit is needed to meet the increasing prokaryotic genome data. We updated Geptop by supplementing more validated essentiality data into reference set (from 19 to 37 species), and introducing multi-process technology to accelerate the computing speed. Compared with Geptop 1.0 and other gene essentiality prediction models, Geptop 2.0 can generate more stable predictions and finish the computation in a shorter time. The software is available both as an online server and a downloadable standalone application. We hope that the improved Geptop 2.0 will facilitate researches in gene essentiality and the development of novel antibacterial drugs. The gene essentiality prediction tool is available at http://cefg.uestc.cn/geptop.

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          Most cited references24

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          DEG 10, an update of the database of essential genes that includes both protein-coding genes and noncoding genomic elements

          The combination of high-density transposon-mediated mutagenesis and high-throughput sequencing has led to significant advancements in research on essential genes, resulting in a dramatic increase in the number of identified prokaryotic essential genes under diverse conditions and a revised essential-gene concept that includes all essential genomic elements, rather than focusing on protein-coding genes only. DEG 10, a new release of the Database of Essential Genes (available at http://www.essentialgene.org), has been developed to accommodate these quantitative and qualitative advancements. In addition to increasing the number of bacterial and archaeal essential genes determined by genome-wide gene essentiality screens, DEG 10 also harbors essential noncoding RNAs, promoters, regulatory sequences and replication origins. These essential genomic elements are determined not only in vitro, but also in vivo, under diverse conditions including those for survival, pathogenesis and antibiotic resistance. We have developed customizable BLAST tools that allow users to perform species- and experiment-specific BLAST searches for a single gene, a list of genes, annotated or unannotated genomes. Therefore, DEG 10 includes essential genomic elements under different conditions in three domains of life, with customizable BLAST tools.
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            Emerging and evolving concepts in gene essentiality

            Gene essentiality is a founding concept of genetics with important implications in both fundamental and applied research. Multiple screens have been performed over the years in bacteria, yeasts, animals and more recently in human cells to identify essential genes. A mounting body of evidence suggests that gene essentiality, rather than being a static and binary property, is both context dependent and evolvable in all kingdoms of life. This concept of a non-absolute nature of gene essentiality changes our fundamental understanding of essential biological processes and could directly affect future treatment strategies for cancer and infectious diseases.
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              A minimal gene set for cellular life derived by comparison of complete bacterial genomes.

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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                04 June 2019
                2019
                : 10
                : 1236
                Affiliations
                School of Life Sciences and Technology, Center for Informational Biology, University of Electronic Science and Technology of China , Chengdu, China
                Author notes

                Edited by: Feng Gao, Tianjin University, China

                Reviewed by: Xiujuan Lei, Shaanxi Normal University, China; Chenggang Yu, Henry M. Jackson Foundation for the Advancement of Military Medicine, United States

                *Correspondence: Feng-Biao Guo, fbguo@ 123456uestc.edu.cn

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2019.01236
                6558110
                31214154
                3d419670-3bfe-4774-8c1e-73a0ae8b84c3
                Copyright © 2019 Wen, Liu, Dong, Guo, Gao and Guo.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 March 2019
                : 17 May 2019
                Page count
                Figures: 3, Tables: 0, Equations: 7, References: 26, Pages: 6, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Funded by: University of Electronic Science and Technology of China 10.13039/501100005408
                Categories
                Microbiology
                Methods

                Microbiology & Virology
                essential genes,prediction,prokaryotes,software,bioinformatics
                Microbiology & Virology
                essential genes, prediction, prokaryotes, software, bioinformatics

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