PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
November 25, 2013Nucleic Acids Research5,241 citationsOpen Access

miRBase: annotating high confidence microRNAs using deep sequencing data

View Full Paper
AKAna KozomaraSGSam Griffiths‐Jones

Key Points

  • The aim is to update the miRBase database to enhance microRNA annotation quality using deep sequencing data.
  • Processed microRNA data from 24,521 loci across 206 species.
  • Implemented deep sequencing data for assigning confidence levels to microRNA entries.
  • Created a high confidence subset of microRNA entries based on mapped read patterns.
  • Released v20 of miRBase with 30,424 mature microRNA products.
  • Established a high confidence subset for reliable microRNA data.
  • Facilitated researcher contributions via microRNA-specific Wikipedia pages.

Abstract

We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Kozomara et al. (2013) studied this question.

synapsesocial.com/papers/69a018ec93fbce3651069212https://doi.org/10.1093/nar/gkt1181
Ask AI
Helpful
Bookmark
Share
View Full Paper