ArticlePloS one2017
Gene essentiality, conservation index and co-evolution of genes in cyanobacteria.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 17 citations in OpenAlex.
- Predicting FOX gene candidates for oxic nitrogen fixation using multi-omic machine learning and comparative bioinformatics.Scientific reports · 2026Article
- Metabolic engineering of Synechocystis sp. PCC 6803 for the improved production of phenylpropanoids.Microbial cell factories · 2024Article
- Whole genome sequencing and analysis of selenite-reducing bacteria Bacillus paralicheniformis SR14 in response to different sugar supplements.AMB Express · 2023Article
- Expression of phenylalanine ammonia lyases in Synechocystis sp. PCC 6803 and subsequent improvements of sustainable production of phenylpropanoids.Microbial cell factories · 2022Article
- Regulatory Connections Between the Cyanobacterial Factor PipX and the Ribosome Assembly GTPase EngA.Frontiers in microbiology · 2021Article
- cyAbrB Transcriptional Regulators as Safety Devices To Inhibit Heterocyst Differentiation inJournal of bacteriology · 2019Article
- Cyanobacteria: Promising biocatalysts for sustainable chemical production.The Journal of biological chemistry · 2018Review
- Modules of co-occurrence in the cyanobacterial pan-genome reveal functional associations between groups of ortholog genes.PLoS genetics · 2018Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cyanobacteria, a group of photosynthetic prokaryotes, dominate the earth with ~ 1015 g wet biomass. Despite diversity in habitats and an ancient origin, cyanobacterial phylum has retained a significant core genome. Cyanobacteria are being explored for direct conversion of solar energy and carbon dioxide into biofuels. For this, efficient cyanobacterial strains will need to be designed via metabolic engineering. This will require identification of target knockouts to channelize the flow of carbon toward the product of interest while minimizing deletions of essential genes. We propose "Gene Conservation Index" (GCI) as a quick measure to predict gene essentiality in cyanobacteria. GCI is based on phylogenetic profile of a gene constructed with a reduced dataset of cyanobacterial genomes. GCI is the percentage of organism clusters in which the query gene is present in the reduced dataset. Of the 750 genes deemed to be essential in the experimental study on S. elongatus PCC 7942, we found 494 to be conserved across the phylum which largely comprise of the essential metabolic pathways. On the contrary, the conserved but non-essential genes broadly comprise of genes required under stress conditions. Exceptions to this rule include genes such as the glycogen synthesis and degradation enzymes, deoxyribose-phosphate aldolase (DERA), glucose-6-phosphate 1-dehydrogenase (zwf) and fructose-1,6-bisphosphatase class1, which are conserved but non-essential. While the essential genes are to be avoided during gene knockout studies as potentially lethal deletions, the non-essential but conserved set of genes could be interesting targets for metabolic engineering. Further, we identify clusters of co-evolving genes (CCG), which provide insights that may be useful in annotation. Principal component analysis (PCA) plots of the CCGs are demonstrated as data visualization tools that are complementary to the conventional heatmaps. Our dataset consists of phylogenetic profiles for 23,643 non-redundant cyanobacterial genes. We believe that the data and the analysis presented here will be a great resource to the scientific community interested in cyanobacteria.
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