N1-methylation of adenosine (mA) in ND5 mRNA leads to complex I dysfunction in Alzheimer's disease.

One mechanism of particular interest to regulate mRNA fate post-transcriptionally is mRNA modification. Especially the extent of mA mRNA methylation is highly discussed due to methodological differences. However, one single mA site in mitochondrial ND5 mRNA was unanimously reported by different groups.

Data Analysis Pipeline for Detection and Quantification of Pseudouridine (ψ) in RNA by HydraPsiSeq.

Pseudouridine, a modified RNA residue formed by the isomerization of its parental U nucleotide, is prevalent in a majority of cellular RNAs; its presence was reported in tRNA, rRNA, and sn/snoRNA as well as in mRNA/lncRNA. Multiple analytical deep sequencing-based approaches have been proposed for pseudouridine detection and quantification, among which the most popular relies on the use of soluble carbodiimide (termed CMCT). Recently, we developed an alternative protocol for pseudouridine mapping and quantification.

Quantification of substoichiometric modification reveals global tsRNA hypomodification, preferences for angiogenin-mediated tRNA cleavage, and idiosyncratic epitranscriptomes of human neuronal cell-lines.

Modification of tRNA is an integral part of the epitranscriptome with a particularly pronounced potential to generate diversity in RNA expression. Eukaryotic tRNA contains modifications in up to 20% of their nucleotides, but not all sites are always fully modified. Combinations and permutations of partially modified sites in tRNAs can generate a plethora of tRNA isoforms, termed modivariants.

Machine learning algorithm for precise prediction of 2'-O-methylation (Nm) sites from experimental RiboMethSeq datasets.

Analysis of epitranscriptomic RNA modifications by deep sequencing-based approaches brings an essential contribution to the general knowledge on their precise locations and relative stoichiometry in cellular RNAs. To reveal RNA modifications, several analytical approaches have been proposed, including antibody-driven enrichment, analysis of RT-signatures and specific chemical treatments. However, analysis and interpretation of these massive datasets, especially for low abundant cellular RNAs (e.

Non-Redundant tRNA Reference Sequences for Deep Sequencing Analysis of tRNA Abundance and Epitranscriptomic RNA Modifications.

Analysis of RNA by deep-sequencing approaches has found widespread application in modern biology. In addition to measurements of RNA abundance under various physiological conditions, such techniques are now widely used for mapping and quantification of RNA modifications. Transfer RNA (tRNA) molecules are among the frequent targets of such investigation, since they contain multiple modified residues.

NOseq: amplicon sequencing evaluation method for RNA m6A sites after chemical deamination.

Methods for the detection of m6A by RNA-Seq technologies are increasingly sought after. We here present NOseq, a method to detect m6A residues in defined amplicons by virtue of their resistance to chemical deamination, effected by nitrous acid. Partial deamination in NOseq affects all exocyclic amino groups present in nucleobases and thus also changes sequence information.

HydraPsiSeq: a method for systematic and quantitative mapping of pseudouridines in RNA.

Developing methods for accurate detection of RNA modifications remains a major challenge in epitranscriptomics. Next-generation sequencing-based mapping approaches have recently emerged but, often, they are not quantitative and lack specificity. Pseudouridine (ψ), produced by uridine isomerization, is one of the most abundant RNA modification.

Holistic Optimization of Bioinformatic Analysis Pipeline for Detection and Quantification of 2'-O-Methylations in RNA by RiboMethSeq.

A major trend in the epitranscriptomics field over the last 5 years has been the high-throughput analysis of RNA modifications by a combination of specific chemical treatment(s), followed by library preparation and deep sequencing. Multiple protocols have been described for several important RNA modifications, such as 5-methylcytosine (mC), pseudouridine (ψ), 1-methyladenosine (mA), and 2'-O-methylation (Nm). One commonly used method is the alkaline cleavage-based RiboMethSeq protocol, where positions of reads' 5'-ends are used to distinguish nucleotides protected by ribose methylation.

2'--methylation within prokaryotic and eukaryotic tRNA inhibits innate immune activation by endosomal Toll-like receptors but does not affect recognition of whole organisms.

Bacterial RNA has emerged as an important activator of innate immune responses by stimulating Toll-like receptors TLR7 and TLR8 in humans. Guanosine 2'--methylation at position 18 (Gm18) in bacterial tRNA was shown to antagonize tRNA-induced TLR7/8 activation, suggesting a potential role of Gm18 as an immune escape mechanism. This modification also occurs in eukaryotic tRNA, yet a physiological immune function remained to be tested.

RNA ribose methylation (2'-O-methylation): Occurrence, biosynthesis and biological functions.

Methylation of riboses at 2'-OH group is one of the most common RNA modifications found in number of cellular RNAs from almost any species which belong to all three life domains. This modification was extensively studied for decades in rRNAs and tRNAs, but recent data revealed the presence of 2'-O-methyl groups also in low abundant RNAs, like mRNAs. Ribose methylation is formed in RNA by two alternative enzymatic mechanisms: either by stand-alone protein enzymes or by complex assembly of proteins associated with snoRNA guides (sno(s)RNPs).

Next-Generation Sequencing-Based RiboMethSeq Protocol for Analysis of tRNA 2'-O-Methylation.

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.