ArticleGenome biology and evolution2016
Towards Consensus Gene Ages.
Article in Genome biology and evolution, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
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- Orthologs at the Base of the Olfactores Clade.Genes · 2024Review
- Evolution-strengthened knowledge graph enables predicting the targetability and druggability of genes.PNAS nexus · 2023Article
- Uncovering gene-family founder events during major evolutionary transitions in animals, plants and fungi using GenEra.Genome biology · 2023Article
- Proteotype coevolution and quantitative diversity across 11 mammalian species.Science advances · 2022Article
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- A Thermodynamic Model for Water Activity and Redox Potential in Evolution and Development.Journal of molecular evolution · 2022Article
- Proteome-wide mapping of short-lived proteins in human cells.Molecular cell · 2021Article
- During evolution from the earliest tetrapoda, newly-recruited genes are increasingly paralogues of existing genes and distribute non-randomly among the chromosomes.BMC genomics · 2021Article
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- The Distinct Properties of the Consecutive Disordered Regions Inside or Outside Protein Domains and Their Functional Significance.International journal of molecular sciences · 2021Article
- Cancer progression as a sequence of atavistic reversions.BioEssays : news and reviews in molecular, cellular and developmental biology · 2021Article
- Article
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Authors and funding
3 authors.
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Abstract
Correctly estimating the age of a gene or gene family is important for a variety of fields, including molecular evolution, comparative genomics, and phylogenetics, and increasingly for systems biology and disease genetics. However, most studies use only a point estimate of a gene's age, neglecting the substantial uncertainty involved in this estimation. Here, we characterize this uncertainty by investigating the effect of algorithm choice on gene-age inference and calculate consensus gene ages with attendant error distributions for a variety of model eukaryotes. We use 13 orthology inference algorithms to create gene-age datasets and then characterize the error around each age-call on a per-gene and per-algorithm basis. Systematic error was found to be a large factor in estimating gene age, suggesting that simple consensus algorithms are not enough to give a reliable point estimate. We also found that different sources of error can affect downstream analyses, such as gene ontology enrichment. Our consensus gene-age datasets, with associated error terms, are made fully available at so that researchers can propagate this uncertainty through their analyses (geneages.org).
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