• Sorted by Date • Classified by Publication Type • Default Ordering •
Pavel P. Kuksa, Yuk Yee Leung, Lee E. Vandivier, Zachary Anderson, Brian D. Gregory, and Li-San Wang. In Silico Identification of RNA Modifications from High-Throughput Sequencing Data Using HAMR, pp. 211–229, Springer New York, New York, NY, 2017.
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.
@inbook{hamr2017bookchapter,
Abstract = {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.},
Address = {New York, NY},
Author = {Kuksa, Pavel P. and Leung, Yuk Yee and Vandivier, Lee E. and Anderson, Zachary and Gregory, Brian D. and Wang, Li-San},
Bib2Html_Pubtype = {Book chapter},
Booktitle = {RNA Methylation: Methods and Protocols},
Date-Added = {2020-03-04 12:28:41 -0500},
Date-Modified = {2020-03-06 13:16:53 -0500},
Doi = {10.1007/978-1-4939-6807-7_14},
Editor = {Lusser, Alexandra},
Isbn = {978-1-4939-6807-7},
Pages = {211--229},
Publisher = {Springer New York},
Title = {In Silico Identification of {RNA} Modifications from High-Throughput Sequencing Data Using {HAMR}},
Url = {https://doi.org/10.1007/978-1-4939-6807-7_14},
Year = {2017},
Bdsk-Url-1 = {https://doi.org/10.1007/978-1-4939-6807-7_14}}
Generated by bib2html.pl (written by Patrick Riley ) on Tue Mar 17, 2020 17:09:56