ArticlePLoS genetics2006
Inference of splicing regulatory activities by sequence neighborhood analysis.
Article in PLoS genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed, 79 citations in OpenAlex.
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- eSkip-Finder: a machine learning-based web application and database to identify the optimal sequences of antisense oligonucleotides for exon skipping.Nucleic acids research · 2021Article
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- Massive computational identification of somatic variants in exonic splicing enhancers using The Cancer Genome Atlas.Cancer medicine · 2019Article
- Predicting gene structure changes resulting from genetic variants via exon definition features.Bioinformatics (Oxford, England) · 2018Article
- Population-dependent Intron Retention and DNA Methylation in Breast Cancer.Molecular cancer research : MCR · 2018Article
- Genetic variation affecting exon skipping contributes to brain structural atrophy in Alzheimer's disease.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Mutations of Pre-mRNA Splicing Regulatory Elements: Are Predictions Moving Forward to Clinical Diagnostics?International journal of molecular sciences · 2017Review
- Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping.Scientific reports · 2017Article
- Regulation of a strong F9 cryptic 5'ss by intrinsic elements and by combination of tailored U1snRNAs with antisense oligonucleotides.Human molecular genetics · 2015Article
- The role of short RNA loops in recognition of a single-hairpin exon derived from a mammalian-wide interspersed repeat.RNA biology · 2015Article
- In silico screening based on predictive algorithms as a design tool for exon skipping oligonucleotides in Duchenne muscular dystrophy.PloS one · 2015Article
- Redirecting splicing with bifunctional oligonucleotides.Nucleic acids research · 2014Article
- MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing.Genome biology · 2014Article
- Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sequence-specific recognition of nucleic-acid motifs is critical to many cellular processes. We have developed a new and general method called Neighborhood Inference (NI) that predicts sequences with activity in regulating a biochemical process based on the local density of known sites in sequence space. Applied to the problem of RNA splicing regulation, NI was used to predict hundreds of new exonic splicing enhancer (ESE) and silencer (ESS) hexanucleotides from known human ESEs and ESSs. These predictions were supported by cross-validation analysis, by analysis of published splicing regulatory activity data, by sequence-conservation analysis, and by measurement of the splicing regulatory activity of 24 novel predicted ESEs, ESSs, and neutral sequences using an in vivo splicing reporter assay. These results demonstrate the ability of NI to accurately predict splicing regulatory activity and show that the scope of exonic splicing regulatory elements is substantially larger than previously anticipated. Analysis of orthologous exons in four mammals showed that the NI score of ESEs, a measure of function, is much more highly conserved above background than ESE primary sequence. This observation indicates a high degree of selection for ESE activity in mammalian exons, with surprisingly frequent interchangeability between ESE sequences.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.