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Adenosine deaminases that act on RNA bind double-stranded and structured RNAs and convert adenosines to inosines by hydrolytic deamination. Inosines are recognized as guanosines, and, hence, RNA editing alters the sequence information but also structure of RNAs. Editing by ADARs is widespread and essential for normal life and development. Precursors of miRNAs are abundantly edited by ADARs, but neither the abundance nor the consequences of miRNA editing has been firmly established. Using transgenic mouse embryos that are deficient in the two enzymatically active editing enzymes ADAR and ADARB1, we compare relative frequencies but also sequence composition of miRNAs in these genetically modified backgrounds to wild-type mice by "next-generation sequencing." Deficiency of ADARB1 leads to a reproducible change in abundance of specific miRNAs and their predicted targets. Changes in miRNA abundance seem unrelated to editing events. Additional deletion of ADAR has surprisingly little impact on the mature miRNA repertoire, indicating that miRNA expression is primarily dependent on ADARB1. A-to-G transitions reflecting A-to-I editing events can be detected at few sites and at low frequency during the early embryonic stage investigated. Again, most editing events are ADARB1-dependent with only few editing sites being specifically edited by ADAR. Besides known editing events in miRNAs, a few novel, previously unknown editing events were identified. Some editing events are located to the seed region of miRNAs, opening the possibility that editing leads to their retargeting.
Pubmed ID: 22310477
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A mapping program for Next Generation Sequencing reads that is more than twice as fast as BWA, while achieving a mapping sensitivity similar to Stampy or Bowtie2. NextGenMap uses a memory efficient index structure (hash table) to store the positions of all 13-mers present in the reference genome. This index enables a quick identification of potential mapping regions for every read. Unlike other methods, NextGenMap dynamically determines for each read individually how many of the potential mapping regions have to be evaluated by a pairwise sequence alignment. Moreover, NextGenMap uses fast SIMD instructions (SSE) to accelerate the alignment calculations on the CPU. If available NextGenMap calculates the alignments on the GPU (using OpenCL/CUDA) resulting in a runtime reduction of another 20 - 50 %, depending on the underlying data set.
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