ArticleG3 (Bethesda, Md.)2025
Detection and annotation of unique regions in mammalian genomes.
Article in G3 (Bethesda, Md.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- SURE-Pipe: a pipeline to compare genomes and extract shared and unique regions.NAR genomics and bioinformatics · 2026Article
- Fast detection of unique genomic regions.Computational and structural biotechnology journal · 2025Review
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Authors and funding
2 authors.
Funding
Abstract
Long unique genomic regions have been reported to be highly enriched for developmental genes in mice and humans. In this paper, we identify unique genomic regions using an efficient method based on fast string matching. We quantify the resource consumption and accuracy of this method before applying it to the genomes of 18 mammals. We annotate their unique regions (URs) of at least 10 kb and find that they are strongly enriched for developmental genes across the board. We then investigated the subset of URs that lack annotations, which we call "anonymous." The longest anonymous UR in the Tasmanian devil spanned 83 kb and contained the gene encoding inositol polyphosphate-5-phosphatase A, which is an essential part of intracellular signaling. This discovery of an essential gene in a UR implies that URs might be given priority when annotating mammalian genomes. Our documented pipeline for annotating URs in any mammalian genome is available from the repository github.com/evolbioinf/auger; the additional data for this study are available from the dataverse at doi.org/10.17617/3.4IKQAG.
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Registered trials
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