ArticleBMC bioinformatics2010
Missing genes in the annotation of prokaryotic genomes.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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58 citing papers in PubMed, 118 citations in OpenAlex.
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- Small Protein Enrichment Improves Proteomics Detection of sORF Encoded Polypeptides.Frontiers in genetics · 2021Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProtein-coding gene detection in prokaryotic genomes is considered a much simpler problem than in intron-containing eukaryotic genomes. However there have been reports that prokaryotic gene finder programs have problems with small genes (either over-predicting or under-predicting). Therefore the question arises as to whether current genome annotations have systematically missing, small genes.
resultsWe have developed a high-performance computing methodology to investigate this problem. In this methodology we compare all ORFs larger than or equal to 33 aa from all fully-sequenced prokaryotic replicons. Based on that comparison, and using conservative criteria requiring a minimum taxonomic diversity between conserved ORFs in different genomes, we have discovered 1,153 candidate genes that are missing from current genome annotations. These missing genes are similar only to each other and do not have any strong similarity to gene sequences in public databases, with the implication that these ORFs belong to missing gene families. We also uncovered 38,895 intergenic ORFs, readily identified as putative genes by similarity to currently annotated genes (we call these absent annotations). The vast majority of the missing genes found are small (less than 100 aa). A comparison of select examples with GeneMark, EasyGene and Glimmer predictions yields evidence that some of these genes are escaping detection by these programs.
conclusionsProkaryotic gene finders and prokaryotic genome annotations require improvement for accurate prediction of small genes. The number of missing gene families found is likely a lower bound on the actual number, due to the conservative criteria used to determine whether an ORF corresponds to a real gene.
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