ArticleBioinformatics (Oxford, England)2010
Selenoprofiles: profile-based scanning of eukaryotic genome sequences for selenoprotein genes.
Article in Bioinformatics (Oxford, England), 2010. 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.
- Selenoproteins: Minute yet vital players governing cellular fate.Genes & diseases · 2026Review
- Tracing the vertebrate selenoproteome evolution reveals expansions in ray-finned fishes and convergent depletions in tetrapods.BMC genomics · 2026Article
- Large-scale mining of plant genomes unlocks the diversity of oxidosqualene cyclases.Nature chemical biology · 2026Article
- Overcoming the widespread flaws in the annotation of vertebrate selenoprotein genes in public databases.PLoS computational biology · 2026Article
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- Naked mole rat TRF1 safeguards glycolytic capacity and telomere replication under low oxygen.Science advances · 2021Article
- The algal selenoproteomes.BMC genomics · 2020Article
- Bioinformatics of Selenoproteins.Antioxidants & redox signaling · 2020Review
- Bioinformatics of Metalloproteins and Metalloproteomes.Molecules (Basel, Switzerland) · 2020Review
- The genome sequence of the grape phylloxera provides insights into the evolution, adaptation, and invasion routes of an iconic pest.BMC biology · 2020Article
- Processive Recoding and Metazoan Evolution of Selenoprotein P: Up to 132 UGAs in Molluscs.Journal of molecular biology · 2019Article
- Phylogenomics Provides New Insights into Gains and Losses of Selenoproteins among Archaeplastida.International journal of molecular sciences · 2019Article
- Role of Key Micronutrients from Nutrigenetic and Nutrigenomic Perspectives in Cancer Prevention.Medicina (Kaunas, Lithuania) · 2019Review
- RefSeq curation and annotation of stop codon recoding in vertebrates.Nucleic acids research · 2019Article
- Selenium-Dependent Antioxidant Enzymes: Actions and Properties of Selenoproteins.Antioxidants (Basel, Switzerland) · 2018Review
- Computational identification of the selenocysteine tRNA (tRNASec) in genomes.PLoS computational biology · 2017Article
- Human selenoprotein P and S variant mRNAs with different numbers of SECIS elements and inferences from mutant mice of the roles of multiple SECIS elements.Open biology · 2016Article
- Novel Ciliate Genetic Code Variants Including the Reassignment of All Three Stop Codons to Sense Codons in Condylostoma magnum.Molecular biology and evolution · 2016Article
- Lokiarchaeota Marks the Transition between the Archaeal and Eukaryotic Selenocysteine Encoding Systems.Molecular biology and evolution · 2016Article
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2 authors.
Funding
Abstract
motivationSelenoproteins are a group of proteins that contain selenocysteine (Sec), a rare amino acid inserted co-translationally into the protein chain. The Sec codon is UGA, which is normally a stop codon. In selenoproteins, UGA is recoded to Sec in presence of specific features on selenoprotein gene transcripts. Due to the dual role of the UGA codon, selenoprotein prediction and annotation are difficult tasks, and even known selenoproteins are often misannotated in genome databases.
resultsWe present an homology-based in silico method to scan genomes for members of the known eukaryotic selenoprotein families: selenoprofiles. The core of the method is a set of manually curated highly reliable multiple sequence alignments of selenoprotein families, which are used as queries to scan genomic sequences. Results of the scan are processed through a number of steps, to produce highly accurate predictions of selenoprotein genes with little or no human intervention. Selenoprofiles is a valuable tool for bioinformatic characterization of eukaryotic selenoproteomes, and can complement genome annotation pipelines. AVAILABILITY AND IMPLEMENTATION: Selenoprofiles is a python-built pipeline that internally runs psitblastn, exonerate, genewise, SECISearch and a number of custom-made scripts and programs. The program is available at http://big.crg.cat/services/selenoprofiles. The predictions presented in this article are available through DAS at http://genome.crg.cat:9000/das/Selenoprofiles_ensembl.
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