ArticlePLoS computational biology2019
Measuring the impact of gene prediction on gene loss estimates in Eukaryotes by quantifying falsely inferred absences.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
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- Predicting Protein Function in the AI and Big Data Era.Biochemistry · 2025Review
- Rampant Interkingdom Horizontal Gene Transfer in Pezizomycotina? An Updated Inspection of Anomalous Phylogenies.International journal of molecular sciences · 2025Article
- Multiple Displacement Amplification Facilitates SMRT Sequencing of Microscopic Animals and the Genome of the Gastrotrich Lepidodermella squamata (Dujardin 1841).Genome biology and evolution · 2024Article
- Beyond genes-for-behaviour: The potential for genomics to resolve long-standing questions in avian brood parasitism.Ecology and evolution · 2024Review
- Domain collapse and active site ablation generate a widespread animal mitochondrial seryl-tRNA synthetase.Nucleic acids research · 2023Article
- Wide-scale identification of novel/eliminated genes responsible for evolutionary transformations.Biology direct · 2023Article
- Article
- Increased Sampling and Intracomplex Homologies Favor Vertical Over Horizontal Inheritance of the Dam1 Complex.Genome biology and evolution · 2023Article
- Integrating Phylogenetics With Intron Positions Illuminates the Origin of the Complex Spliceosome.Molecular biology and evolution · 2023Article
- Real or fake? Measuring the impact of protein annotation errors on estimates of domain gain and loss events.Frontiers in bioinformatics · 2023Article
- The spread of the first introns in proto-eukaryotic paralogs.Communications biology · 2022Article
- Carotenoid modifying enzymes in metazoans.Methods in enzymology · 2022Article
- GFICLEE: ultrafast tree-based phylogenetic profile method inferring gene function at the genomic-wide level.BMC genomics · 2021Article
- Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes.Briefings in bioinformatics · 2021Article
- Article
- Gene Duplication and Gain in the Trematode Atriophallophorus winterbourni Contributes to Adaptation to Parasitism.Genome biology and evolution · 2021Article
- Timing the origin of eukaryotic cellular complexity with ancient duplications.Nature ecology & evolution · 2021Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In recent years it became clear that in eukaryotic genome evolution gene loss is prevalent over gene gain. However, the absence of genes in an annotated genome is not always equivalent to the loss of genes. Due to sequencing issues, or incorrect gene prediction, genes can be falsely inferred as absent. This implies that loss estimates are overestimated and, more generally, that falsely inferred absences impact genomic comparative studies. However, reliable estimates of how prevalent this issue is are lacking. Here we quantified the impact of gene prediction on gene loss estimates in eukaryotes by analysing 209 phylogenetically diverse eukaryotic organisms and comparing their predicted proteomes to that of their respective six-frame translated genomes. We observe that 4.61% of domains per species were falsely inferred to be absent for Pfam domains predicted to have been present in the last eukaryotic common ancestor. Between phylogenetically different categories this estimate varies substantially: for clade-specific loss (ancestral loss) we found 1.30% and for species-specific loss 16.88% to be falsely inferred as absent. For BUSCO 1-to-1 orthologous families, 18.30% were falsely inferred to be absent. Finally, we showed that falsely inferred absences indeed impact loss estimates, with the number of losses decreasing by 11.78%. Our work strengthens the increasing number of studies showing that gene loss is an important factor in eukaryotic genome evolution. However, while we demonstrate that on average inferring gene absences from predicted proteomes is reliable, caution is warranted when inferring species-specific absences.
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