ArticleScientific reports2017
Identification of introns harboring functional sequence elements through positional conservation.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Evidence-Based Guide to Using Artificial Introns for Tissue-Specific Knockout in Mice.International journal of molecular sciences · 2023Review
- The role of neurotrophin genes involved in the vulnerability to gambling disorder.Scientific reports · 2022Article
- The evolution of hemocyanin genes in Tectipleura: a multitude of conserved introns in highly diverse gastropods.BMC ecology and evolution · 2021Article
- Article
- First Come, First Served: Sui Generis Features of the First Intron.Plants (Basel, Switzerland) · 2020Review
- pCADD: SNV prioritisation in Sus scrofa.Genetics, selection, evolution : GSE · 2020Article
- Enrichment of rare alleles within epigenetic chromatin marks in the first intron.Genomics & informatics · 2019Article
- Analysis of the Functional Relevance of Epigenetic Chromatin Marks in the First Intron Associated with Specific Gene Expression Patterns.Genome biology and evolution · 2019Article
- Conservation of Intronic Sequences in Vertebrate Mitochondrial Solute Carrier Genes (Zebrafish, Chicken, Mouse and Human).Non-coding RNA · 2019Article
- A versatile toolbox for knock-in gene targeting based on the Multisite Gateway technology.PloS one · 2019Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many human introns carry out a function, in the sense that they are critical to maintain normal cellular activity. Their identification is fundamental to understanding cellular processes and disease. However, being noncoding elements, such functional introns are poorly predicted based on traditional approaches of sequence and structure conservation. Here, we generated a dataset of human functional introns that carry out different types of functions. We showed that functional introns share common characteristics, such as higher positional conservation along the coding sequence and reduced loss rates, regardless of their specific function. A unique property of the data is that if an intron is unknown to be functional, it still does not mean that it is indeed non-functional. We developed a probabilistic framework that explicitly accounts for this unique property, and predicts which specific human introns are functional. We show that we successfully predict function even when the algorithm is trained on introns with a different type of function. This ability has many implications in studying regulatory networks, gene regulation, the effect of mutations outside exons on human disease, and on our general understanding of intron evolution and their functional exaptation in mammals.
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