ArticleBMC genomics2016
Systematic identification and analysis of frequent gene fusion events in metabolic pathways.
Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Limitations of current machine learning models in predicting enzymatic functions for uncharacterized proteins.G3 (Bethesda, Md.) · 2025Article
- C11orf54 catalyzes L-xylulose formation in human metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Predicting Protein Function in the AI and Big Data Era.Biochemistry · 2025Review
- Fusion/fission protein family identification in Archaea.mSystems · 2024Article
- Deciphering the Diversity in Bacterial Transporters That Salvage Queuosine Precursors.Epigenomes · 2024Article
- Alternate routes to mnmJournal of bacteriology · 2024Article
- The exceptional form and function of the giant bacteriumProceedings of the National Academy of Sciences of the United States of America · 2023Article
- Identification of gene fusion events inNAR genomics and bioinformatics · 2020Article
- The evolution of metabolism: How to test evolutionary hypotheses at the genomic level.Computational and structural biotechnology journal · 2020Review
- Multilayered horizontal operon transfers from bacteria reconstruct a thiamine salvage pathway in yeasts.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Modeling genome-wide enzyme evolution predicts strong epistasis underlying catalytic turnover rates.Nature communications · 2018Article
- The last universal common ancestor between ancient Earth chemistry and the onset of genetics.PLoS genetics · 2018Review
- Review
- Confronting the catalytic dark matter encoded by sequenced genomes.Nucleic acids research · 2017Article
- Functional Annotations of Paralogs: A Blessing and a Curse.Life (Basel, Switzerland) · 2016Article
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14 authors.
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Abstract
backgroundGene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur.
resultsHere we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These sets were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database at http://modelseed.org/projects/fusions/ . A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent.
conclusionsCustomary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.
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