OGEE v3: Online GEne Essentiality database with increased coverage of organisms and human cell lines

Gurumayum, Sanathoi; Jiang, Puzi; Hao, Xiaowen; Campos, Túlio de Lima; Young, Neil D.; Korhonen, Pasi K.; Gasser, Robin B.; Bork, Peer; Zhao, Xing‐Ming; He, Lijie; Chen, Wei‐Hua

doi:10.1093/nar/gkaa884

Cited by 61 publications

(52 citation statements)

References 47 publications

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“…The lists of non-essential ribosomal genes (Table S4) were collected from the literature and two online databases, Database of Essential Genes [DEG, (13)] and the Online Gene Essentiality database [OGEE, (14)]. Since these databases, and most of the original literature, focused on essential genes, the supplementary material files for each paper were individually checked to select those genes that had been positively identified as non-essential and ignore those genes that were not listed as essential but whose status had not been specified.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, the absence of certain RP genes can be compensated by changes in the intracellular milieu, such as, for example, high level of Mg 2+ ions (11, 12). Gene essentiality data derived from genome-wide mutagenesis studies are well represented in the literature and are also available in such online databases as the Database of Essential Genes [DEG, (13)] and the Online Gene Essentiality database [OGEE, (14)]. In addition to the global mutagenesis studies, data on gene essentiality have been obtained by monitoring the effects of suppressing gene expression, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Non-essential ribosomal proteins in bacteria and archaea identified using COGs

Galperin

Wolf

Garushyants

et al. 2021

Preprint

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Ribosomal proteins (RPs) are highly conserved across the bacterial and archaeal domains. Although many RPs are essential for survival, genome analysis demonstrates the absence of some RP genes in many bacterial and archaeal genomes. Furthermore, global transposon mutagenesis and/or targeted deletion showed that elimination of some RP genes had only a moderate effect on the bacterial growth rate. Here, we systematically analyze the evolutionary conservation of RPs in prokaryotes by compiling the list of the ribosomal genes that are missing from the one or more genomes in the recently updated version of the Clusters of Orthologous Genes (COG) database. Some of these absences occurred because the respective genes carried frameshifts, presumably, resulting from sequencing errors, while others were overlooked and not translated during genome annotation. Apart from these annotation errors, we identified multiple genuine losses of RP genes in a variety of bacteria and archaea. Some of these losses are clade-specific, whereas others occur in symbionts and parasites with dramatically reduced genomes. The lists of computationally and experimentally defined non-essential ribosomal genes show a substantial overlap, revealing a common trend in prokaryote ribosome evolution that could be linked to the architecture and assembly of the ribosomes. Thus, RPs that are located at the surface of the ribosome and/or are incorporated at a late stage of ribosome assembly are more likely to be non-essential and to be lost during microbial evolution, particularly, in the course of genome compaction.IMPORTANCEIn many prokaryote genomes, one or more ribosomal protein (RP) genes are missing. Analysis of 1,309 prokaryote genomes included in the COG database shows that only about half of the RPs are universally conserved in bacteria and archaea. In contrast, up to 21 other RPs are missing in some genomes, primarily, tiny (<1 Mb) genomes of host-associated bacteria and archaea. Ten universal and nine archaea-specific ribosomal proteins show clear patterns of lineage-specific gene loss. Most of the RPs that are frequently lost from bacterial genomes are located on the ribosome periphery and are non-essential in Escherichia coli and Bacillus subtilis. These results reveal general trends and common constraints in the architecture and evolution of ribosomes in prokaryotes.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Non-essential ribosomal proteins in bacteria and archaea identified using COGs

Galperin

Wolf

Garushyants

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The lists of non-essential ribosomal genes (Table S4) were collected from the literature and two online databases, Database of Essential Genes [DEG, (15)] and the Online Gene Essentiality database [OGEE, (16)]. Since these databases, and most of the original literature, focused on essential genes, the supplementary material files for each paper were individually checked to select those genes that had been positively identified as non-essential and ignore those genes that were not listed as essential but whose status had not been specified.…”

Section: Identification Of Non-essential Ribosomal Genesmentioning

confidence: 99%

“…In addition, the absence of certain RP genes can be compensated by changes in the intracellular milieu, such as, for example, high level of Mg 2+ ions (13,14). Gene essentiality data derived from genome-wide mutagenesis studies are well represented in the literature and are also available in such online databases as the Database of Essential Genes [DEG, (15)] and the Online Gene Essentiality database [OGEE, (16)]. In addition to the global mutagenesis studies, data on RP gene essentiality have been obtained by monitoring the effects of suppressing gene expression, e.g.…”

Section: Introductionmentioning

confidence: 99%

Nonessential Ribosomal Proteins in Bacteria and Archaea Identified Using Clusters of Orthologous Genes

et al. 2021

View full text Add to dashboard Cite

Ribosomal proteins (RPs) are highly conserved across the bacterial and archaeal domains. Although many RPs are essential for survival, genome analysis demonstrates the absence of some RP genes in many bacterial and archaeal genomes. Furthermore, global transposon mutagenesis and/or targeted deletion showed that elimination of some RP genes had only a moderate effect on the bacterial growth rate. Here, we systematically analyze the evolutionary conservation of RPs in prokaryotes by compiling the list of the ribosomal genes that are missing from one or more genomes in the recently updated version of the Clusters of Orthologous Genes (COG) database. Some of these absences occurred because the respective genes carried frameshifts, presumably, resulting from sequencing errors, while others were overlooked and not translated during genome annotation. Apart from these annotation errors, we identified multiple genuine losses of RP genes in a variety of bacteria and archaea. Some of these losses are clade-specific, whereas others occur in symbionts and parasites with dramatically reduced genomes. The lists of computationally and experimentally defined non-essential ribosomal genes show a substantial overlap, revealing a common trend in prokaryote ribosome evolution that could be linked to the architecture and assembly of the ribosomes. Thus, RPs that are located at the surface of the ribosome and/or are incorporated at a late stage of ribosome assembly are more likely to be non-essential and to be lost during microbial evolution, particularly, in the course of genome compaction. IMPORTANCE In many prokaryote genomes, one or more ribosomal protein (RP) genes are missing. Analysis of 1,309 prokaryote genomes included in the COG database shows that only about half of the RPs are universally conserved in bacteria and archaea. In contrast, up to 16 other RPs are missing in some genomes, primarily, tiny (<1 Mb) genomes of host-associated bacteria and archaea. Ten universal and nine archaea-specific ribosomal proteins show clear patterns of lineage-specific gene loss. Most of the RPs that are frequently lost from bacterial genomes are located on the ribosome periphery and are non-essential in Escherichia coli and Bacillus subtilis. These results reveal general trends and common constraints in the architecture and evolution of ribosomes in prokaryotes.

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“…For eukaryotes the task is more challenging, considering their complex multi-cellular architecture. Besides this, only few model organisms have been experimentally screened for essential genes to date, even though the number is growing (21,22). To our knowledge only two studies were published predicting essential genes across eukaryotes using machine learning.…”

Section: Introductionmentioning

confidence: 99%

Identifying essential genes across eukaryotes by machine learning

Beder¹,

Aromolaran

Doenitz

et al. 2021

Preprint

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Identifying essential genes on a genome scale is resource intensive and has been performed for only a few eukaryotes. For less studied organisms essentiality might be predicted by gene homology. However, this approach cannot be applied to non-conserved genes. Additionally, divergent essentiality information is obtained from studying single cells or whole, multi-cellular organisms, and particularly when derived from human cell line screens and human population studies. We employed machine learning across six model eukaryotes and 60,381 genes, using 41,635 features derived from sequence, gene functions and network topology. Within a leave-one-organism-out cross-validation, the classifiers showed a high generalizability with an average accuracy close to 80% in the left-out species. As a case study, we applied the method to Tribolium castaneum and validated predictions experimentally yielding similar performance. Finally, using the classifier based on the studied model organisms enabled linking the essentiality information of human cell line screens and population studies.

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OGEE v3: Online GEne Essentiality database with increased coverage of organisms and human cell lines

Cited by 61 publications

References 47 publications

Non-essential ribosomal proteins in bacteria and archaea identified using COGs

Non-essential ribosomal proteins in bacteria and archaea identified using COGs

Nonessential Ribosomal Proteins in Bacteria and Archaea Identified Using Clusters of Orthologous Genes

Identifying essential genes across eukaryotes by machine learning

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