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.
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Abbreviations
- 3′:
-
3-prime (3′)
- 5′:
-
5-prime (5′)
- bp:
-
Base pair
- cDNA:
-
Complementary DNA
- HAMR:
-
High-throughput annotation of modified ribonucleotides
- mRNA:
-
Messenger RNA
- mRNA-seq:
-
messenger RNA sequencing
- nt:
-
Nucleotide
- RNA-seq:
-
RNA sequencing
- RT:
-
Reverse transcriptase
- smRNA:
-
Small RNA
- smRNA-seq:
-
Small RNA sequencing
- SNP:
-
single nucleotide polymorphism
- tRNA:
-
Transfer RNA
References
Dominissini D, Nachtergaele S, Moshitch-Moshkovitz S et al (2016) The dynamic N(1)-methyladenosine methylome in eukaryotic messenger RNA. Nature 530:441–446
Eigenbrod T, Keller P, Kaiser S et al (2015) Recognition of specified RNA modifications by the Innate immune system. Methods Enzymol 560:73–89
Li S, Mason CE (2014) The pivotal regulatory landscape of RNA modifications. Annu Rev Genomics Hum Genet 15:127–150
Lee M, Kim B, Kim VN (2014) Emerging roles of RNA modification: m(6)A and U-tail. Cell 158:980–987
Satterlee JS, Basanta-Sanchez M, Blanco S et al (2014) Novel RNA modifications in the nervous system: form and function. J Neurosci 34:15170–15177
Delatte B, Wang F, Ngoc LV et al (2016) Transcriptome-wide distribution and function of RNA hydroxymethylcytosine. Science 351:282–285
Sundaram M, Durant PC, Davis DR (2000) Hypermodified nucleosides in the anticodon of tRNALys stabilize a canonical Uturn structure. Biochemistry 39:12575–12584
Kierzek E, Malgowska M, Lisowiec J, Turner DH, Gdaniec Z, Kierzek R (2014) The contribution of pseudouridine to stabilities and structure of RNAs. Nucleic Acids Res 42:3492–3501
Schwartz S, Mumbach MR, Jovanovic M et al (2014) Perturbation of m6A writers reveals two distinct classes of mRNA methylation at internal and 5′ sites. Cell Rep 8:284–296
Meyer KD, Jaffrey SR (2014) The dynamic epitranscriptome:N6-methyladenosine and gene expression control. Nat Rev Mol Cell Biol 15:313–326
Karijolich J, Yu YT (2015) The new era of RNA modification. RNA 21:659–660
Sun WJ, Li JH, Liu S et al (2016) RMBase: a resource for decoding the landscape of RNA modifications from high-throughput sequencing data. Nucleic Acids Res 44:D259–D265
Schwartz S, Bernstein DA, Mumbach MR, Jovanovic M, Herbst RH, León-Ricardo BX, Engreitz JM, Guttman M, Satija R, Lander ES, Fink G, Regev A (2014b) Transcriptome-wide mapping reveals widespread dynamic-regulated pseudouridylation of ncRNA and mRNA. Cell 159:148–162
Vandivier LE, Campos R, Kuksa PP et al (2015) Chemical modifications mark alternatively spliced and uncapped messenger RNAs in arabidopsis. Plant Cell 27:3024–3037
Meyer KD, Saletore Y, Zumbo P (2012) Comprehensive analysis of mRNA methylation reveals enrichment in 3′ UTRs and near stop codons. Cell 149:1635–1646
Gupta RC, Randerath K (1977) Use of specific endonuclease cleavage in RNA sequencing. Nucleic Acids Res 4:1957–1978
Woodson SA, Muller JG, Burrows CJ et al (1993) A primer extension assay for modification of guanine by Ni(II) complexes. Nucleic Acids Res 21:5524–5525
Motorin Y, Muller S, Behm-Ansmant I, Branlant C (2007) Identification of modified residues in RNAs by reverse transcription-based methods. Methods Enzymol 425:21–53
Behm-Ansmant I, Helm M, Motorin Y (2011) Use of specific chemical reagents for detection of modified nucleotides in RNA. JNucleic Acids 2011:408053
Ryvkin P, Leung YY, Silverman IM et al (2013) HAMR: high-throughput annotation of modified ribonucleotides. RNA 19: 1684–1692
Dominissini D, Moshitch-Moshkovitz S, Schwartz S et al (2012) Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 485:201–206
Squires JE, Patel HR, Nousch M et al (2012) Widespread occurrence of 5-methylcytosine in human coding and non-coding RNA. Nucleic Acids Res 40:5023–5033
Horowitz S, Horowitz A, Nilsen TW et al (1984) Mapping of N6-methyladenosine residues in bovine prolactin mRNA. Proc Natl Acad Sci U S A 81:5667–5671
Li H, Handsaker B, Wysoker A et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetJ 17(1):10–12
Dobin A, Davis CA, Schlesinger F et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21
Machnicka MA, Milanowska K, Osman OO et al (2013) MODOMICS: a database of RNA modification pathways: 2012 update. Nucleic Acids Res 41:D262–D267
Leung YY, Ryvkin P, Ungar LH et al (2013) CoRAL: predicting non-coding RNAs from small RNA-sequencing data. Nucleic Acids Res 41:e137
Acknowledgments
This work is supported by the National Institute of General Medical Sciences [R01-GM099962 to P.P.K, Y.Y.L, B.D.G., and L.S.W], National Institute on Aging [U24-AG041689 to L.S.W.], National Science Foundation [CAREER Award MCB-1053846, MCB-1243947, and IOS-1444490 to B.D.G.]. We thank Alexandre Amlie-Wolf and other members of the Wang and Gregory labs for their comments and help with this work.
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Kuksa, P.P., Leung, Y.Y., Vandivier, L.E., Anderson, Z., Gregory, B.D., Wang, LS. (2017). In Silico Identification of RNA Modifications from High-Throughput Sequencing Data Using HAMR. In: Lusser, A. (eds) RNA Methylation. Methods in Molecular Biology, vol 1562. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6807-7_14
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DOI: https://doi.org/10.1007/978-1-4939-6807-7_14
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