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Feng Gao - One of the best experts on this subject based on the ideXlab platform.
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A Comprehensive Overview of Online Resources to Identify and Predict Bacterial Essential Genes.
Frontiers in Microbiology, 2017Co-Authors: Chong Peng, Yan Lin, Hao Luo, Feng GaoAbstract:Genes critical for the survival or reproduction of an organism in certain circumstances are classified as Essential Genes. Essential Genes play a significant role in deciphering the survival mechanism of life. They may be greatly applied to pharmaceutics and synthetic biology. The continuous progress of experimental method for Essential gene identification has accelerated the accumulation of gene Essentiality data which facilitates the study of Essential Genes in silico. In this article, we present some available online resources related to gene Essentiality, including bioinformatic software tools for transposon sequencing (Tn-seq) analysis, Essential gene databases and online services to predict bacterial Essential Genes. We review several computational approaches that have been used to predict Essential Genes, and summarize the features used for gene Essentiality prediction. In addition, we evaluate the available online bacterial Essential gene prediction servers based on the experimentally validated Essential gene sets of 30 bacteria from DEG. This article is intended to be a quick reference guide for the microbiologists interested in the Essential Genes.
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Comparative analysis of Essential Genes in prokaryotic genomic islands
Scientific Reports, 2015Co-Authors: Xi Zhang, Chong Peng, Ge Zhang, Feng GaoAbstract:Essential Genes are thought to encode proteins that carry out the basic functions to sustain a cellular life, and genomic islands (GIs) usually contain clusters of horizontally transferred Genes. It has been assumed that Essential Genes are not likely to be located in GIs, but systematical analysis of Essential Genes in GIs has not been explored before. Here, we have analyzed the Essential Genes in 28 prokaryotes by statistical method and reached a conclusion that Essential Genes in GIs are significantly fewer than those outside GIs. The function of 362 Essential Genes found in GIs has been explored further by BLAST against the Virulence Factor Database (VFDB) and the phage/prophage sequence database of PHAge Search Tool (PHAST). Consequently, 64 and 60 eligible Essential Genes are found to share the sequence similarity with the virulence factors and phage/prophages-related Genes, respectively. Meanwhile, we find several toxin-related proteins and repressors encoded by these Essential Genes in GIs. The comparative analysis of Essential Genes in genomic islands will not only shed new light on the development of the prediction algorithm of Essential Genes, but also give a clue to detect the functionality of Essential Genes in genomic islands.
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Protein Localization Analysis of Essential Genes in Prokaryotes
Scientific Reports, 2014Co-Authors: Chong Peng, Feng GaoAbstract:Essential Genes, those critical for the survival of an organism under certain conditions, play a significant role in pharmaceutics and synthetic biology. Knowledge of protein localization is invaluable for understanding their function as well as the interaction of different proteins. However, systematical examination of Essential Genes from the aspect of the localizations of proteins they encode has not been explored before. Here, a comprehensive protein localization analysis of Essential Genes in 27 prokaryotes including 24 bacteria, 2 mycoplasmas and 1 archaeon has been performed. Both statistical analysis of localization information in these genomes and GO (Gene Ontology) terms enriched in the Essential Genes show that proteins encoded by Essential Genes are enriched in internal location sites, while exist in cell envelope with a lower proportion compared with non-Essential ones. Meanwhile, there are few Essential proteins in the external subcellular location sites such as flagellum and fimbrium, and proteins encoded by non-Essential Genes tend to have diverse localizations. These results would provide further insights into the understanding of fundamental functions needed to support a cellular life and improve gene Essentiality prediction by taking the protein localization and enriched GO terms into consideration.
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Enzymes Are Enriched in Bacterial Essential Genes
PLoS ONE, 2011Co-Authors: Feng Gao, Randy Ren ZhangAbstract:Essential Genes, those indispensable for the survival of an organism, play a key role in the emerging field, synthetic biology. Characterization of functions encoded by Essential Genes not only has important practical implications, such as in identifying antibiotic drug targets, but can also enhance our understanding of basic biology, such as functions needed to support cellular life. Enzymes are critical for almost all cellular activities. However, Essential Genes have not been systematically examined from the aspect of enzymes and the chemical reactions that they catalyze. Here, by comprehensively analyzing Essential Genes in 14 bacterial genomes in which large-scale gene Essentiality screens have been performed, we found that enzymes are enriched in Essential Genes. Essential enzymes have overrepresented ligases (especially those forming carbon-oxygen bonds and carbon-nitrogen bonds), nucleotidyltransferases and phosphotransferases, while have underrepresented oxidoreductases. Furthermore, Essential enzymes tend to associate with more gene ontology domains. These results, from the aspect of chemical reactions, provide further insights into the understanding of functions needed to support natural cellular life, as well as synthetic cells, and provide additional parameters that can be integrated into gene Essentiality prediction algorithms.
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Functionality of Essential Genes drives gene strand-bias in bacterial genomes.
Biochemical and Biophysical Research Communications, 2010Co-Authors: Yan Lin, Feng Gao, Chun-ting ZhangAbstract:Essential Genes, indispensable Genes for an organism's survival, encode functions that are considered a foundation of life. Based on those experimentally determined for 10 bacteria, we find that Essential Genes are more preferentially situated at the leading strand than at the lagging strand, for all the 10 genomes studied, confirming previous findings based on either smaller datasets or putatively assigned ones by homology search. Furthermore, we find that rather than all Essential Genes, only those with the COG functional category of information storage and process (J, K and L), and subcategories D (cell cycle control), M (cell wall bioGenesis), O (posttranslational modification), C (energy production and conversion), G (carbohydrate transport and metabolism), E (amino acid transport and metabolism) and F (nucleotide transport and metabolism) are preferentially situated at the leading strand. In contrast, the strand-bias for Essential Genes in other COG functional subcategories is not statistically significant. These results suggest that the remarkable strand-bias of the distribution of Essential Genes is mainly relevant to the aforementioned functionalities, which, therefore, likely play a key role in shaping the gene strand-bias in bacterial genomes.
Yan Lin - One of the best experts on this subject based on the ideXlab platform.
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Identifying Bacterial Essential Genes Based on a Feature-Integrated Method
IEEE ACM Transactions on Computational Biology and Bioinformatics, 2019Co-Authors: Yan Lin, Fa-zhan Zhang, Kai Xue, Yi-zhou Gao, Feng-biao GuoAbstract:Essential Genes are those Genes of an organism that are considered to be crucial for its survival. Identification of Essential Genes is therefore of great significance to advance our understanding of the principles of cellular life. We have developed a novel computational method, which can effectively predict bacterial Essential Genes by extracting and integrating homologous features, protein domain feature, gene intrinsic features, and network topological features. By performing the principal component regression (PCR) analysis for Escherichia coli MG1655, we established a classification model with the average area under curve (AUC) value of 0.992 in ten times 5-fold cross-validation tests. Furthermore, when employing this new model to a distantly related organism—Streptococcus pneumoniae TIGR4, we still got a reliable AUC value of 0.788. These results indicate that our feature-integrated approach could have practical applications in accurately investigating Essential Genes from broad bacterial species, and also provide helpful guidelines for the minimal cell.
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A Comprehensive Overview of Online Resources to Identify and Predict Bacterial Essential Genes.
Frontiers in Microbiology, 2017Co-Authors: Chong Peng, Yan Lin, Hao Luo, Feng GaoAbstract:Genes critical for the survival or reproduction of an organism in certain circumstances are classified as Essential Genes. Essential Genes play a significant role in deciphering the survival mechanism of life. They may be greatly applied to pharmaceutics and synthetic biology. The continuous progress of experimental method for Essential gene identification has accelerated the accumulation of gene Essentiality data which facilitates the study of Essential Genes in silico. In this article, we present some available online resources related to gene Essentiality, including bioinformatic software tools for transposon sequencing (Tn-seq) analysis, Essential gene databases and online services to predict bacterial Essential Genes. We review several computational approaches that have been used to predict Essential Genes, and summarize the features used for gene Essentiality prediction. In addition, we evaluate the available online bacterial Essential gene prediction servers based on the experimentally validated Essential gene sets of 30 bacteria from DEG. This article is intended to be a quick reference guide for the microbiologists interested in the Essential Genes.
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Putative Essential and core-Essential Genes in Mycoplasma genomes
Scientific Reports, 2011Co-Authors: Yan Lin, Randy Ren ZhangAbstract:Mycoplasma, which was used to create the first “synthetic life”, has been an important species in the emerging field, synthetic biology. However, Essential Genes, an important concept of synthetic biology, for both M. mycoides and M. capricolum, as well as 14 other Mycoplasma with available genomes, are still unknown. We have developed a gene Essentiality prediction algorithm that incorporates information of biased gene strand distribution, homologous search and codon adaptation index. The algorithm, which achieved an accuracy of 80.8% and 78.9% in self-consistence and cross-validation tests, respectively, predicted 5880 Essential Genes in the 16 Mycoplasma genomes. The intersection set of Essential Genes in available Mycoplasma genomes consists of 153 core Essential Genes. The predicted Essential Genes (available from pDEG, tubic.tju.edu.cn/pdeg) and the proposed algorithm can be helpful for studying minimal Mycoplasma genomes as well as Essential Genes in other genomes.
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Functionality of Essential Genes drives gene strand-bias in bacterial genomes.
Biochemical and Biophysical Research Communications, 2010Co-Authors: Yan Lin, Feng Gao, Chun-ting ZhangAbstract:Essential Genes, indispensable Genes for an organism's survival, encode functions that are considered a foundation of life. Based on those experimentally determined for 10 bacteria, we find that Essential Genes are more preferentially situated at the leading strand than at the lagging strand, for all the 10 genomes studied, confirming previous findings based on either smaller datasets or putatively assigned ones by homology search. Furthermore, we find that rather than all Essential Genes, only those with the COG functional category of information storage and process (J, K and L), and subcategories D (cell cycle control), M (cell wall bioGenesis), O (posttranslational modification), C (energy production and conversion), G (carbohydrate transport and metabolism), E (amino acid transport and metabolism) and F (nucleotide transport and metabolism) are preferentially situated at the leading strand. In contrast, the strand-bias for Essential Genes in other COG functional subcategories is not statistically significant. These results suggest that the remarkable strand-bias of the distribution of Essential Genes is mainly relevant to the aforementioned functionalities, which, therefore, likely play a key role in shaping the gene strand-bias in bacterial genomes.
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DEG 5.0, a database of Essential Genes in both prokaryotes and eukaryotes
Nucleic Acids Research, 2008Co-Authors: Ren Zhang, Yan LinAbstract:Essential Genes are those indispensable for the survival of an organism, and their functions are therefore considered a foundation of life. Determination of a minimal gene set needed to sustain a life form, a fundamental question in biology, plays a key role in the emerging field, synthetic biology. Five years after we constructed DEG, a database of Essential Genes, DEG 5.0 has significant advances over the 2004 version in both the number of Essential Genes and the number of organisms in which these Genes are determined. The number of prokaryotic Essential Genes in DEG has increased about 10-fold, mainly owing to genome-wide gene Essentiality screens performed in a wide range of bacteria. The number of eukaryotic Essential Genes has increased more than 5-fold, because DEG 1.0 only had yeast ones, but DEG 5.0 also has those in humans, mice, worms, fruit flies, zebrafish and the plant Arabidopsis thaliana. These updates not only represent significant advances of DEG, but also represent the rapid progress of the Essential-gene field. DEG is freely available at the website http://tubic.tju.edu.cn/deg or http://www.Essentialgene.org.
Feng-biao Guo - One of the best experts on this subject based on the ideXlab platform.
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CEG 2.0: an updated database of clusters of Essential Genes including eukaryotic organisms.
Database : the journal of biological databases and curation, 2020Co-Authors: Shuo Liu, Shu-xuan Wang, Wei Liu, Chen Wang, Fa-zhan Zhang, Wen-xin Zheng, Nini Rao, Feng-biao GuoAbstract:Essential Genes are key elements for organisms to maintain their living. Building databases that store Essential Genes in the form of homologous clusters, rather than storing them as a singleton, can provide more enlightening information such as the general Essentiality of homologous Genes in multiple organisms. In 2013, the first database to store prokaryotic Essential Genes in clusters, CEG (Clusters of Essential Genes), was constructed. Afterward, the amount of available data for Essential Genes increased by a factor >3 since the last revision. Herein, we updated CEG to version 2, including more prokaryotic Essential Genes (from 16 gene datasets to 29 gene datasets) and newly added eukaryotic Essential Genes (nine species), specifically the human Essential Genes of 12 cancer cell lines. For prokaryotes, information associated with drug targets, such as protein structure, ligand-protein interaction, virulence factor and matched drugs, is also provided. Finally, we provided the service of Essential gene prediction for both prokaryotes and eukaryotes. We hope our updated database will benefit more researchers in drug targets and evolutionary genomics. Database URL: http://cefg.uestc.cn/ceg.
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Identifying Bacterial Essential Genes Based on a Feature-Integrated Method
IEEE ACM Transactions on Computational Biology and Bioinformatics, 2019Co-Authors: Yan Lin, Fa-zhan Zhang, Kai Xue, Yi-zhou Gao, Feng-biao GuoAbstract:Essential Genes are those Genes of an organism that are considered to be crucial for its survival. Identification of Essential Genes is therefore of great significance to advance our understanding of the principles of cellular life. We have developed a novel computational method, which can effectively predict bacterial Essential Genes by extracting and integrating homologous features, protein domain feature, gene intrinsic features, and network topological features. By performing the principal component regression (PCR) analysis for Escherichia coli MG1655, we established a classification model with the average area under curve (AUC) value of 0.992 in ten times 5-fold cross-validation tests. Furthermore, when employing this new model to a distantly related organism—Streptococcus pneumoniae TIGR4, we still got a reliable AUC value of 0.788. These results indicate that our feature-integrated approach could have practical applications in accurately investigating Essential Genes from broad bacterial species, and also provide helpful guidelines for the minimal cell.
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Three computational tools for predicting bacterial Essential Genes.
Gene Essentiality, 2015Co-Authors: Feng-biao Guo, Lu-wen Ning, Wen WeiAbstract:Essential Genes are those Genes indispensable for the survival of any living cell. Bacterial Essential Genes constitute the cornerstones of synthetic biology and are often attractive targets in the development of antibiotics and vaccines. Because identification of Essential Genes with wet-lab ways often means expensive economic costs and tremendous labor, scientists changed to seek for alternative way of computational prediction. Aiming to help to solve this issue, our research group (CEFG: group of Computational, Comparative, Evolutionary and Functional Genomics, http://cefg.uestc.edu.cn) has constructed three online services to predict Essential Genes in bacterial genomes. These freely available tools are applicable for single gene sequences without annotated functions, single Genes with definite names, and complete genomes of bacterial strains. To ensure reliable predictions, the investigated species should belong to the same family (for EGP) or phylum (for CEG_Match and Geptop) with one of the reference species, respectively. As the pilot software for the issue, predicting accuracies of them have been assessed and compared with existing algorithms, and note that all of other published algorithms have not any formed online services. We hope these services at CEFG will help scientists and researchers in the field of Essential Genes.
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Predicting bacterial Essential Genes using only sequence composition information.
Genetics and Molecular Research, 2014Co-Authors: Lu-wen Ning, Nini Rao, Hao Lin, Hui Ding, Jian Huang, Feng-biao GuoAbstract:Essential Genes are those Genes that are needed by organisms at any time and under any conditions. It is very important for us to identify Essential Genes from bacterial genomes because of their vital role in synthetic biology and biomedical practices. In this paper, we developed a support vector machine (SVM)-based method to predict Essential Genes of bacterial genomes using only compositional features. These features are all derived from the primary sequences, i.e., nucleotide sequences and protein sequences. After training on the multiple samplings of the labeled (Essential or not Essential) features using a library for SVM, we obtained an average area under the ROC curve (AUC) of about 0.82 in a 5-fold cross-validation for Escherichia coli and about 0.74 for Mycoplasma pulmonis. We further evaluated the performance of the method proposed using the dataset consisting of 16 bacterial genomes, and an average AUC of 0.76 was achieved. Based on this training dataset, a model for Essential gene prediction was established. Another two independent genomes, Shewanella oneidensis RW1 and Salmonella enterica serovar Typhimurium SL1344 were used to evalutate the model. Results showed that the AUC sores were 0.77 and 0.81, respectively. For the convenience of the vast majority
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Current status of theoretical studies on Essential Genes in microbes
Hereditas (Beijing), 2012Co-Authors: Feng-biao GuoAbstract:Essential Genes are indispensable for the survival of an organism in optimal conditions. Recently, study on Essential gene is becoming a hot topic of microbiology, genomics, and bioinformatics. This paper described the experiments that determined Essential Genes in some microbes and the theoretical researches on Essential Genes were reviewed. The major content contained comparison of Essential Genes and non-Essential Genes based on information on evolutionary conservation and sequence composition, and in silico prediction of Essential Genes, and analysis of the chromosomal distributions of Essential Genes. Finally, related progresses were concluded and the open problems were pointed out.
Kathryn E. Hentges - One of the best experts on this subject based on the ideXlab platform.
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Identifying mouse developmental Essential Genes using machine learning
Disease Models & Mechanisms, 2018Co-Authors: David Tian, Stephanie Wenlock, Mitra Kabir, George Tzotzos, Andrew J. Doig, Kathryn E. HentgesAbstract:ABSTRACT The Genes that are required for organismal survival are annotated as ‘Essential Genes’. Identifying all the Essential Genes of an animal species can reveal critical functions that are needed during the development of the organism. To inform studies on mouse development, we developed a supervised machine learning classifier based on phenotype data from mouse knockout experiments. We used this classifier to predict the Essentiality of mouse Genes lacking experimental data. Validation of our predictions against a blind test set of recent mouse knockout experimental data indicated a high level of accuracy (>80%). We also validated our predictions for other mouse mutaGenesis methodologies, demonstrating that the predictions are accurate for lethal phenotypes isolated in random chemical mutaGenesis screens and embryonic stem cell screens. The biological functions that are enriched in Essential and non-Essential Genes have been identified, showing that Essential Genes tend to encode intracellular proteins that interact with nucleic acids. The genome distribution of predicted Essential and non-Essential Genes was analysed, demonstrating that the density of Essential Genes varies throughout the genome. A comparison with human Essential and non-Essential Genes was performed, revealing conservation between human and mouse gene Essentiality status. Our genome-wide predictions of mouse Essential Genes will be of value for the planning of mouse knockout experiments and phenotyping assays, for understanding the functional processes required during mouse development, and for the prioritisation of disease candidate Genes identified in human genome and exome sequence datasets.
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The functional diversity of Essential Genes required for mammalian cardiac development.
genesis, 2014Co-Authors: Christopher Clowes, Michael G.s. Boylan, Liam A. Ridge, Emma Barnes, Jayne Wright, Kathryn E. HentgesAbstract:Genes required for an organism to develop to maturity (for which no other gene can compensate) are considered Essential. The continuing functional annotation of the mouse genome has enabled the identification of many Essential Genes required for specific developmental processes including cardiac development. Patterns are now emerging regarding the functional nature of Genes required at specific points throughout gestation. Essential Genes required for development beyond cardiac progenitor cell migration and induction include a small and functionally homogenous group encoding transcription factors, ligands and receptors. Actions of core cardiogenic transcription factors from the Gata, Nkx, Mef, Hand, and Tbx families trigger a marked expansion in the functional diversity of Essential Genes from midgestation onwards. As the embryo grows in size and complexity, Genes required to maintain a functional heartbeat and to provide muscular strength and regulate blood flow are well represented. These Essential Genes regulate further specialization and polarization of cell types along with proliferative, migratory, adhesive, contractile, and structural processes. The identification of patterns regarding the functional nature of Essential Genes across numerous developmental systems may aid prediction of further Essential Genes and those important to development and/or progression of disease. Genesis 52:713–737, 2014.
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eLS - Essential Genes and Human Genetic Disease
eLS, 2013Co-Authors: Kathryn E. HentgesAbstract:Essential Genes are those Genes required for an organism to complete development and survive to birth. There is debate as to whether Essential Genes play a role in human disease, because if they are critical for survival then mutations in these Genes will cause lethality during development, removing individuals carrying these mutations from the population. Yet, Essential Genes can have diverse mutations that either limit or alter their function in a manner that allows individuals with these mutations to survive. These nonlethal, yet pathological, mutations in Essential Genes do contribute to human disease. Studies have demonstrated that Essential disease Genes are highly conserved, participate in many protein–protein interactions and may cause both Mendelian and complex disorders. These results confirm that Essential Genes are valid candidates as disease loci. Key Concepts: Genetic mutations create different alleles of Genes. Hypomorphic alleles retain some gene function. Essential Genes are those that are absolutely required for the survival of the organism, and have null alleles with lethal phenotypes. Human disease can be caused by hypomorphic mutations in Essential Genes. Essential Genes do contribute to human nondevelopmental diseases. Essential Genes can contribute to Mendelian disease and complex disorders. Keywords: Essential Genes; disease; genetics; lethality; mutation; development
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Defining the role of Essential Genes in human disease.
PLoS ONE, 2011Co-Authors: Jonathan E. Dickerson, Ana Zhu, David Robertson, Kathryn E. HentgesAbstract:A greater understanding of the causes of human disease can come from identifying characteristics that are specific to disease Genes. However, a full understanding of the contribution of Essential Genes to human disease is lacking, due to the premise that these Genes tend to cause developmental abnormalities rather than adult disease. We tested the hypothesis that human orthologs of mouse Essential Genes are associated with a variety of human diseases, rather than only those related to miscarriage and birth defects. We segregated human disease Genes according to whether the knockout phenotype of their mouse ortholog was lethal or viable, defining those with orthologs producing lethal knockouts as Essential disease Genes. We show that the human orthologs of mouse Essential Genes are associated with a wide spectrum of diseases affecting diverse physiological systems. Notably, human disease Genes with Essential mouse orthologs are over-represented among disease Genes associated with cancer, suggesting links between adult cellular abnormalities and developmental functions. The proteins encoded by Essential Genes are highly connected in protein-protein interaction networks, which we find correlates with an over-representation of nuclear proteins amongst Essential disease Genes. Disease Genes associated with Essential orthologs also are more likely than those with non-Essential orthologs to contribute to disease through an autosomal dominant inheritance pattern, suggesting that these diseases may actually result from semi-dominant mutant alleles. Overall, we have described attributes found in disease Genes according to the Essentiality status of their mouse orthologs. These findings demonstrate that disease Genes do occupy highly connected positions in protein-protein interaction networks, and that due to the complexity of disease-associated alleles, Essential Genes cannot be ignored as candidates for causing diverse human diseases.
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Regional variation in the density of Essential Genes in mice.
PLoS Genetics, 2007Co-Authors: Kathryn E. Hentges, David D. Pollock, Bin Liu, Monica J. JusticeAbstract:In most species, and particularly in vertebrates, the percentage of Genes absolutely required for survival, the Essential Genes, has not been estimated. To obtain this estimation, we used the mouse as an experimental model to carry out high-efficiency N-ethyl-N-nitrosourea (ENU) mutaGenesis screens in two balancer chromosome regions, and compared our results to a third previously published screen. The number of Essential Genes in each region was predicted based on allele frequencies. We determined that the density of Essential Genes differs by up to an order of magnitude among genomic regions. This indicates that extrapolating from regional estimates to genome-wide estimates of Essential Genes has a huge variance. A particularly high density of Essential Genes on mouse Chromosome 11 coincides with a high degree of regional linkage conservation, providing a possible causal explanation for the density variation. This is the first demonstration of regional variation in Essential gene density in the mouse genome.
Chong Peng - One of the best experts on this subject based on the ideXlab platform.
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A Comprehensive Overview of Online Resources to Identify and Predict Bacterial Essential Genes.
Frontiers in Microbiology, 2017Co-Authors: Chong Peng, Yan Lin, Hao Luo, Feng GaoAbstract:Genes critical for the survival or reproduction of an organism in certain circumstances are classified as Essential Genes. Essential Genes play a significant role in deciphering the survival mechanism of life. They may be greatly applied to pharmaceutics and synthetic biology. The continuous progress of experimental method for Essential gene identification has accelerated the accumulation of gene Essentiality data which facilitates the study of Essential Genes in silico. In this article, we present some available online resources related to gene Essentiality, including bioinformatic software tools for transposon sequencing (Tn-seq) analysis, Essential gene databases and online services to predict bacterial Essential Genes. We review several computational approaches that have been used to predict Essential Genes, and summarize the features used for gene Essentiality prediction. In addition, we evaluate the available online bacterial Essential gene prediction servers based on the experimentally validated Essential gene sets of 30 bacteria from DEG. This article is intended to be a quick reference guide for the microbiologists interested in the Essential Genes.
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Comparative analysis of Essential Genes in prokaryotic genomic islands
Scientific Reports, 2015Co-Authors: Xi Zhang, Chong Peng, Ge Zhang, Feng GaoAbstract:Essential Genes are thought to encode proteins that carry out the basic functions to sustain a cellular life, and genomic islands (GIs) usually contain clusters of horizontally transferred Genes. It has been assumed that Essential Genes are not likely to be located in GIs, but systematical analysis of Essential Genes in GIs has not been explored before. Here, we have analyzed the Essential Genes in 28 prokaryotes by statistical method and reached a conclusion that Essential Genes in GIs are significantly fewer than those outside GIs. The function of 362 Essential Genes found in GIs has been explored further by BLAST against the Virulence Factor Database (VFDB) and the phage/prophage sequence database of PHAge Search Tool (PHAST). Consequently, 64 and 60 eligible Essential Genes are found to share the sequence similarity with the virulence factors and phage/prophages-related Genes, respectively. Meanwhile, we find several toxin-related proteins and repressors encoded by these Essential Genes in GIs. The comparative analysis of Essential Genes in genomic islands will not only shed new light on the development of the prediction algorithm of Essential Genes, but also give a clue to detect the functionality of Essential Genes in genomic islands.
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Protein Localization Analysis of Essential Genes in Prokaryotes
Scientific Reports, 2014Co-Authors: Chong Peng, Feng GaoAbstract:Essential Genes, those critical for the survival of an organism under certain conditions, play a significant role in pharmaceutics and synthetic biology. Knowledge of protein localization is invaluable for understanding their function as well as the interaction of different proteins. However, systematical examination of Essential Genes from the aspect of the localizations of proteins they encode has not been explored before. Here, a comprehensive protein localization analysis of Essential Genes in 27 prokaryotes including 24 bacteria, 2 mycoplasmas and 1 archaeon has been performed. Both statistical analysis of localization information in these genomes and GO (Gene Ontology) terms enriched in the Essential Genes show that proteins encoded by Essential Genes are enriched in internal location sites, while exist in cell envelope with a lower proportion compared with non-Essential ones. Meanwhile, there are few Essential proteins in the external subcellular location sites such as flagellum and fimbrium, and proteins encoded by non-Essential Genes tend to have diverse localizations. These results would provide further insights into the understanding of fundamental functions needed to support a cellular life and improve gene Essentiality prediction by taking the protein localization and enriched GO terms into consideration.