A genome-wide map of hyper-edited RNA reveals numerous new sites
Nature Communications, ISSN: 2041-1723, Vol: 5, Issue: 1, Page: 4726
2014
- 175Citations
- 222Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations175
- Citation Indexes175
- 175
- CrossRef151
- Captures222
- Readers222
- 222
Article Description
Adenosine-to-inosine editing is one of the most frequent post-transcriptional modifications, manifested as A-to-G mismatches when comparing RNA sequences with their source DNA. Recently, a number of RNA-seq data sets have been screened for the presence of A-to-G editing, and hundreds of thousands of editing sites identified. Here we show that existing screens missed the majority of sites by ignoring reads with excessive ('hyper') editing that do not easily align to the genome. We show that careful alignment and examination of the unmapped reads in RNA-seq studies reveal numerous new sites, usually many more than originally discovered, and in precisely those regions that are most heavily edited. Specifically, we discover 327,096 new editing sites in the heavily studied Illumina Human BodyMap data and more than double the number of detected sites in several published screens. We also identify thousands of new sites in mouse, rat, opossum and fly. Our results establish that hyper-editing evnts account for the majority of editing sites. © 2014 Macmillan Publishers Limited. All rights reserved.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84907361822&origin=inward; http://dx.doi.org/10.1038/ncomms5726; http://www.ncbi.nlm.nih.gov/pubmed/25158696; https://www.nature.com/articles/ncomms5726; https://dx.doi.org/10.1038/ncomms5726; http://europepmc.org/abstract/med/25158696; http://europepmc.org/articles/PMC4365171; http://www.nature.com/ncomms/2014/140827/ncomms5726/full/ncomms5726.html; http://www.nature.com/doifinder/10.1038/ncomms5726; http://www.nature.com/articles/ncomms5726.pdf; http://www.nature.com/articles/ncomms5726
Springer Science and Business Media LLC
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