Modify or die? - RNA modification defects in metazoans

Sarin, L. Peter; Leidel, Sebastian A.

doi:10.4161/15476286.2014.992279

Cited by 68 publications

(62 citation statements)

References 162 publications

(210 reference statements)

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“…Consequently, previous studies characterizing the associations between RNA modifications and human diseases have been mainly focused on modifications occurring in tRNA molecules (Sarin and Leidel 2014;Torres et al 2014;Schaffrath and Leidel 2017). However, pseudouridine, originally thought to be exclusive to these infrastructural RNAs, has been detected in several mRNAs (Carlile et al 2014;Schwartz et al 2014a), suggesting that additional modifications typically thought to be restricted to "classical" RNA molecules may actually occur more widely.…”

Section: Human Rna Modifications and Their Implications In Diseasementioning

confidence: 99%

The RNA modification landscape in human disease

Jonkhout

Tran

Smith

et al. 2017

RNA

470

420

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RNA modifications have been historically considered as fine-tuning chemo-structural features of infrastructural RNAs, such as rRNAs, tRNAs, and snoRNAs. This view has changed dramatically in recent years, to a large extent as a result of systematic efforts to map and quantify various RNA modifications in a transcriptome-wide manner, revealing that RNA modifications are reversible, dynamically regulated, far more widespread than originally thought, and involved in major biological processes, including cell differentiation, sex determination, and stress responses. Here we summarize the state of knowledge and provide a catalog of RNA modifications and their links to neurological disorders, cancers, and other diseases. With the advent of direct RNA-sequencing technologies, we expect that this catalog will help prioritize those RNA modifications for transcriptome-wide maps.

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Section: Human Rna Modifications and Their Implications In Diseasementioning

confidence: 99%

The RNA modification landscape in human disease

Jonkhout

Tran

Smith

et al. 2017

RNA

470

420

View full text Add to dashboard Cite

show abstract

“…Among these various chemical reactions, the most frequent is the transfer of a methyl (CH 3 ) group from a methylation donor (generally S -adenosyl- l -methionine, abbreviated as SAM or AdoMet) to different positions on nucleobases or to the 2′-OH of the ribose [1,2,3,4,5]. Methylated nucleotides are found in every studied RNA species, and their presence allows fine modulation (tuning) of RNA properties in different cellular processes [6,7,8,9]. One of the best-known RNA species is the transfer RNAs (tRNAs), whose properties and functions have now been studied for over 50 years.…”

Section: Introductionmentioning

confidence: 99%

Next‐Generation Sequencing‐Based RiboMethSeq Protocol for Analysis of tRNA 2′‐O‐Methylation

et al. 2017

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Analysis of RNA modifications by traditional physico-chemical approaches is labor intensive, requires substantial amounts of input material and only allows site-by-site measurements. The recent development of qualitative and quantitative approaches based on next-generation sequencing (NGS) opens new perspectives for the analysis of various cellular RNA species. The Illumina sequencing-based RiboMethSeq protocol was initially developed and successfully applied for mapping of ribosomal RNA (rRNA) 2′-O-methylations. This method also gives excellent results in the quantitative analysis of rRNA modifications in different species and under varying growth conditions. However, until now, RiboMethSeq was only employed for rRNA, and the whole sequencing and analysis pipeline was only adapted to this long and rather conserved RNA species. A deep understanding of RNA modification functions requires large and global analysis datasets for other important RNA species, namely for transfer RNAs (tRNAs), which are well known to contain a great variety of functionally-important modified residues. Here, we evaluated the application of the RiboMethSeq protocol for the analysis of tRNA 2′-O-methylation in Escherichia coli and in Saccharomyces cerevisiae. After a careful optimization of the bioinformatic pipeline, RiboMethSeq proved to be suitable for relative quantification of methylation rates for known modified positions in different tRNA species.

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“…In addition to the 5¢ end modifications, host RNAs are highly modified on internal nucleotides (Sarin and Leidel 2014;Rosenthal 2015). However, the function of only a few modifications has been elucidated to date.…”

Section: Generation and Properties Of Cellular Rnamentioning

confidence: 99%

Discrimination of Self and Non-Self Ribonucleic Acids

Gebhardt

Laudenbach

Pichlmair

2017

Journal of Interferon & Cytokine Research

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Most virus infections are controlled through the innate and adaptive immune system. A surprisingly limited number of so-called pattern recognition receptors (PRRs) have the ability to sense a large variety of virus infections. The reason for the broad activity of PRRs lies in the ability to recognize viral nucleic acids. These nucleic acids lack signatures that are present in cytoplasmic cellular nucleic acids and thereby marking them as pathogen-derived. Accumulating evidence suggests that these signatures, which are predominantly sensed by a class of PRRs called retinoic acid-inducible gene I (RIG-I)-like receptors and other proteins, are not unique to viruses but rather resemble immature forms of cellular ribonucleic acids generated by cellular polymerases. RIG-I-like receptors, and other cellular antiviral proteins, may therefore have mainly evolved to sense nonprocessed nucleic acids typically generated by primitive organisms and pathogens. This capability has not only implications on induction of antiviral immunity but also on the function of cellular proteins to handle selfderived RNA with stimulatory potential.

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Modify or die? - RNA modification defects in metazoans

Cited by 68 publications

References 162 publications

The RNA modification landscape in human disease

The RNA modification landscape in human disease

Next‐Generation Sequencing‐Based RiboMethSeq Protocol for Analysis of tRNA 2′‐O‐Methylation

Discrimination of Self and Non-Self Ribonucleic Acids

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