ArticleDatabase : the journal of biological databases and curation2018
Improved ontology for eukaryotic single-exon coding sequences in biological databases.
Article in Database : the journal of biological databases and curation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 14 citations in OpenAlex.
- Computational Methods for Tracing the Evolutionary History of Human Microproteins Encoded by Intronless Genes.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Verification and comparison of pig, mouse, and human genome similarities: use of manual assembly and analyses.BMC genomics · 2025Article
- Molecular, Structural and Functional Characterization of Antheraea mylitta Expressed Cocoonase: An Integrative Approach.The protein journal · 2025Article
- Genome-wide identification of the OVATE gene family of proteins in soybean and expression profiling under salt stress.Frontiers in plant science · 2025Article
- Genomic characterisation of the metal tolerance protein gene family and elucidation of functional role in heavy metal tolerance and accumulation inFrontiers in plant science · 2025Article
- Mutational Bias and Natural Selection Driving the Synonymous Codon Usage of Single-Exon Genes in Rice (Oryza sativa L.).Rice (New York, N.Y.) · 2023Article
- Genome-wide Identification of Metal Tolerance Protein Genes in Peanut: Differential Expression in the Root of Two Contrasting Cultivars Under Metal Stresses.Frontiers in plant science · 2022Article
- SinEx DB 2.0 update 2020: database for eukaryotic single-exon coding sequences.Database : the journal of biological databases and curation · 2021Article
- Evolutionary Perspective and Expression Analysis of Intronless Genes Highlight the Conservation of Their Regulatory Role.Frontiers in genetics · 2021Article
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Efficient extraction of knowledge from biological data requires the development of structured vocabularies to unambiguously define biological terms. This paper proposes descriptions and definitions to disambiguate the term 'single-exon gene'. Eukaryotic Single-Exon Genes (SEGs) have been defined as genes that do not have introns in their protein coding sequences. They have been studied not only to determine their origin and evolution but also because their expression has been linked to several types of human cancer and neurological/developmental disorders and many exhibit tissue-specific transcription. Unfortunately, the term 'SEGs' is rife with ambiguity, leading to biological misinterpretations. In the classic definition, no distinction is made between SEGs that harbor introns in their untranslated regions (UTRs) versus those without. This distinction is important to make because the presence of introns in UTRs affects transcriptional regulation and post-transcriptional processing of the mRNA. In addition, recent whole-transcriptome shotgun sequencing has led to the discovery of many examples of single-exon mRNAs that arise from alternative splicing of multi-exon genes, these single-exon isoforms are being confused with SEGs despite their clearly different origin. The increasing expansion of RNA-seq datasets makes it imperative to distinguish the different SEG types before annotation errors become indelibly propagated in biological databases. This paper develops a structured vocabulary for their disambiguation, allowing a major reassessment of their evolutionary trajectories, regulation, RNA processing and transport, and provides the opportunity to improve the detection of gene associations with disorders including cancers, neurological and developmental diseases.
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