ArticleMolecular biology and evolution2021
dbCNS: A New Database for Conserved Noncoding Sequences.
Article in Molecular biology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- An epigenetic toolbox for conservation biologists.Evolutionary applications · 2024Article
- PlantPAN 4.0: updated database for identifying conserved non-coding sequences and exploring dynamic transcriptional regulation in plant promoters.Nucleic acids research · 2024Article
- CNEReg Interprets Ruminant-specific Conserved Non-coding Elements by Developmental Gene Regulatory Network.Genomics, proteomics & bioinformatics · 2023Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We developed dbCNS (http://yamasati.nig.ac.jp/dbcns), a new database for conserved noncoding sequences (CNSs). CNSs exist in many eukaryotes and are assumed to be involved in protein expression control. Version 1 of dbCNS, introduced here, includes a powerful and precise CNS identification pipeline for multiple vertebrate genomes. Mutations in CNSs may induce morphological changes and cause genetic diseases. For this reason, many vertebrate CNSs have been identified, with special reference to primate genomes. We integrated ∼6.9 million CNSs from many vertebrate genomes into dbCNS, which allows users to extract CNSs near genes of interest using keyword searches. In addition to CNSs, dbCNS contains published genome sequences of 161 species. With purposeful taxonomic sampling of genomes, users can employ CNSs as queries to reconstruct CNS alignments and phylogenetic trees, to evaluate CNS modifications, acquisitions, and losses, and to roughly identify species with CNSs having accelerated substitution rates. dbCNS also produces links to dbSNP for searching pathogenic single-nucleotide polymorphisms in human CNSs. Thus, dbCNS connects morphological changes with genetic diseases. A test analysis using 38 gnathostome genomes was accomplished within 30 s. dbCNS results can evaluate CNSs identified by other stand-alone programs using genome-scale data.
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Registered trials
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