In Silico Identification of RNA Modifications from High-Throughput Sequencing Data Using HAMR.
In Silico Identification of RNA Modifications from High-Throughput Sequencing Data Using HAMR.
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DOI：
10.1007/978-1-4939-6807-7_14
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Wang LS
中科院分区：
文献类型：
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作者：
Kuksa PP;Leung YY;Vandivier LE;Anderson Z;Gregory BD;Wang LS
RNA molecules are often altered post-transcriptionally by the covalent modification of their nucleotides. These modifications are known to modulate the structure, function, and activity of RNAs. When reverse transcribed into cDNA during RNA sequencing library preparation, atypical (modified) ribonucleotides that affect Watson-Crick base pairing will interfere with reverse transcriptase (RT), resulting in cDNA products with mis-incorporated bases or prematurely terminated RNA products. These interactions with RT can therefore be inferred from mismatch patterns in the sequencing reads, and are distinguishable from simple base-calling errors, single-nucleotide polymorphisms (SNPs), or RNA editing sites. Here, we describe a computational protocol for the in silico identification of modified ribonucleotides from RT-based RNA-seq read-out using the High-throughput Analysis of Modified Ribonucleotides (HAMR) software. HAMR can identify these modifications transcriptome-wide with single nucleotide resolution, and also differentiate between different types of modifications to predict modification identity. Researchers can use HAMR to identify and characterize RNA modifications using RNA-seq data from a variety of common RT-based sequencing protocols such as Poly(A), total RNA-seq, and small RNA-seq.
