Mixing genome annotation methods in a comparative analysis inflates the apparent number of lineage-specific genes Article Swipe
Caroline M. Weisman
,
Andrew W. Murray
,
Sean R. Eddy
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.cub.2022.04.085
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.cub.2022.04.085
Comparisons of genomes of different species are used to identify lineage-specific genes, those genes that appear unique to one species or clade. Lineage-specific genes are often thought to represent genetic novelty that underlies unique adaptations. Identification of these genes depends not only on genome sequences, but also on inferred gene annotations. Comparative analyses typically use available genomes that have been annotated using different methods, increasing the risk that orthologous DNA sequences may be erroneously annotated as a gene in one species but not another, appearing lineage specific as a result. To evaluate the impact of such "annotation heterogeneity," we identified four clades of species with sequenced genomes with more than one publicly available gene annotation, allowing us to compare the number of lineage-specific genes inferred when differing annotation methods are used to those resulting when annotation method is uniform across the clade. In these case studies, annotation heterogeneity increases the apparent number of lineage-specific genes by up to 15-fold, suggesting that annotation heterogeneity is a substantial source of potential artifact.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.cub.2022.04.085
- OA Status
- hybrid
- Cited By
- 92
- References
- 29
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4280506768Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.cub.2022.04.085Digital Object Identifier
- Title
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Mixing genome annotation methods in a comparative analysis inflates the apparent number of lineage-specific genesWork title
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articleOpenAlex work type
- Language
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enPrimary language
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2022Year of publication
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2022-05-18Full publication date if available
- Authors
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Caroline M. Weisman, Andrew W. Murray, Sean R. EddyList of authors in order
- Landing page
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https://doi.org/10.1016/j.cub.2022.04.085Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.cub.2022.04.085Direct OA link when available
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Biology, Genome, Lineage (genetic), Gene, Mixing (physics), Computational biology, Genetics, Evolutionary biology, Annotation, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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92Total citation count in OpenAlex
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2025: 25, 2024: 28, 2023: 28, 2022: 9, 2021: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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