Traces of post-transcriptional RNA modifications in deep sequencing data

tRNA expression and modification landscapes, and their dynamics during zebrafish embryo development

tRNA genes exist in multiple copies in the genome of all organisms across the three domains of life. Besides the sequence differences across tRNA copies, extensive post-transcriptional modification adds a further layer to tRNA diversification. Whilst the crucial role of tRNAs as adapter molecules in protein translation is well established, whether all tRNAs are actually expressed, and whether the differences across isodecoders play any regulatory role is only recently being uncovered. Here we built upon recent developments in the use of NGS-based methods for RNA modification detection and developed tRAM-seq, an experimental protocol and in silico analysis pipeline to investigate tRNA expression and modification. Using tRAM-seq, we analysed the full ensemble of nucleo-cytoplasmic and mitochondrial tRNAs during embryonic development of the model vertebrate zebrafish. We show that the repertoire of tRNAs changes during development, with an apparent major switch in tRNA isodecoder expression and modification profile taking place around the start of gastrulation. Taken together, our findings suggest the existence of a general reprogramming of the expressed tRNA pool, possibly gearing the translational machinery for distinct stages of the delicate and crucial process of embryo development.

Comparative analyses suggest a link between mRNA splicing, stability, and RNA covalent modifications in flowering plants

BACKGROUND

In recent years, covalent modifications on RNA nucleotides have emerged as pivotal moieties influencing the structure, function, and regulatory processes of RNA Polymerase II transcripts such as mRNAs and lncRNAs. However, our understanding of their biological roles and whether these roles are conserved across eukaryotes remains limited.

RESULTS

In this study, we leveraged standard polyadenylation-enriched RNA-sequencing data to identify and characterize RNA modifications that introduce base-pairing errors into cDNA reads. Our investigation incorporated data from three Poaceae (Zea mays, Sorghum bicolor, and Setaria italica), as well as publicly available data from a range of stress and genetic contexts in Sorghum and Arabidopsis thaliana. We uncovered a strong enrichment of RNA covalent modifications (RCMs) deposited on a conserved core set of nuclear mRNAs involved in photosynthesis and translation across these species. However, the cohort of modified transcripts changed based on environmental context and developmental program, a pattern that was also conserved across flowering plants. We determined that RCMs can partly explain accession-level differences in drought tolerance in Sorghum, with stress-associated genes receiving a higher level of RCMs in a drought tolerant accession. To address function, we determined that RCMs are significantly enriched near exon junctions within coding regions, suggesting an association with splicing. Intriguingly, we found that these base-pair disrupting RCMs are associated with stable mRNAs, are highly correlated with protein abundance, and thus likely associated with facilitating translation.

CONCLUSIONS

Our data point to a conserved role for RCMs in mRNA stability and translation across the flowering plant lineage.

General Principles and Limitations for Detection of RNA Modifications by Sequencing

Among the many analytical methods applied to RNA modifications, a particularly pronounced surge has occurred in the past decade in the field of modification mapping. The occurrence of modifications such as m6A in mRNA, albeit known since the 1980s, became amenable to transcriptome-wide analyses through the advent of next-generation sequencing techniques in a rather sudden manner. The term "mapping" here refers to detection of RNA modifications in a sequence context, which has a dramatic impact on the interpretation of biological functions. As a consequence, an impressive number of mapping techniques were published, most in the perspective of what now has become known as "epitranscriptomics". While more and more different modifications were reported to occur in mRNA, conflicting reports and controversial results pointed to a number of technical and theoretical problems rooted in analytics, statistics, and reagents. Rather than finding the proverbial needle in a haystack, the tasks were to determine how many needles of what color in what size of a haystack one was looking at.As the authors of this Account, we think it important to outline the limitations of different mapping methods since many life scientists freshly entering the field confuse the accuracy and precision of modification mapping with that of normal sequencing, which already features numerous caveats by itself. Indeed, we propose here to qualify a specific mapping method by the size of the transcriptome that can be meaningfully analyzed with it.We here focus on high throughput sequencing by Illumina technology, referred to as RNA-Seq. We noted with interest the development of methods for modification detection by other high throughput sequencing platforms that act directly on RNA, e.g., PacBio SMRT and nanopore sequencing, but those are not considered here.In contrast to approaches relying on direct RNA sequencing, current Illumina RNA-Seq protocols require prior conversion of RNA into DNA. This conversion relies on reverse transcription (RT) to create cDNA; thereafter, the cDNA undergoes a sequencing-by-synthesis type of analysis. Thus, a particular behavior of RNA modified nucleotides during the RT-step is a prerequisite for their detection (and quantification) by deep sequencing, and RT properties have great influence on the detection efficiency and reliability. Moreover, the RT-step requires annealing of a synthetic primer, a prerequisite with a crucial impact on library preparation. Thus, all RNA-Seq protocols must feature steps for the introduction of primers, primer landing sites, or adapters on both the RNA 3'- and 5'-ends.

Magnipore: Prediction of differential single nucleotide changes in the Oxford Nanopore Technologies sequencing signal of SARS-CoV-2 samples

Oxford Nanopore Technologies (ONT) allows direct sequencing of ribonucleic acids (RNA) and, in addition, detection of possible RNA modifications due to deviations from the expected ONT signal. The software available so far for this purpose can only detect a small number of modifications. Alternatively, two samples can be compared for different RNA modifications. We present Magnipore, a novel tool to search for significant signal shifts between samples of Oxford Nanopore data from similar or related species. Magnipore classifies them into mutations and potential modifications. We use Magnipore to compare SARS-CoV-2 samples. Included were representatives of the early 2020s Pango lineages (n=6), samples from Pango lineages B.1.1.7 (n=2, Alpha), B.1.617.2 (n=1, Delta), and B.1.529 (n=7, Omicron). Magnipore utilizes position-wise Gaussian distribution models and a comprehensible significance threshold to find differential signals. In the case of Alpha and Delta, Magnipore identifies 55 detected mutations and 15 sites that hint at differential modifications. We predicted potential virus-variant and variant-group-specific differential modifications. Magnipore contributes to advancing RNA modification analysis in the context of viruses and virus variants.

Changes of the tRNA Modification Pattern during the Development of Dictyostelium discoideum

Dictyostelium discoideum is a social amoeba, which on starvation develops from a single-cell state to a multicellular fruiting body. This developmental process is accompanied by massive changes in gene expression, which also affect non-coding RNAs. Here, we investigate how tRNAs as key regulators of the translation process are affected by this transition. To this end, we used LOTTE-seq to sequence the tRNA pool of D. discoideum at different developmental time points and analyzed both tRNA composition and tRNA modification patterns. We developed a workflow for the specific detection of modifications from reverse transcriptase signatures in chemically untreated RNA-seq data at single-nucleotide resolution. It avoids the comparison of treated and untreated RNA-seq data using reverse transcription arrest patterns at nucleotides in the neighborhood of a putative modification site as internal control. We find that nucleotide modification sites in D. discoideum tRNAs largely conform to the modification patterns observed throughout the eukaroytes. However, there are also previously undescribed modification sites. We observe substantial dynamic changes of both expression levels and modification patterns of certain tRNA types during fruiting body development. Beyond the specific application to D. discoideum our results demonstrate that the developmental variability of tRNA expression and modification can be traced efficiently with LOTTE-seq.

Subcellular relocalization and nuclear redistribution of the RNA methyltransferases TRMT1 and TRMT1L upon neuronal activation

RNA modifications are dynamic chemical entities that expand the RNA lexicon and regulate RNA fate. The most abundant modification present in mRNAs, N6-methyladenosine (m⁶A), has been implicated in neurogenesis and memory formation. However, whether additional RNA modifications may be playing a role in neuronal functions and in response to environmental queues is largely unknown. Here we characterize the biochemical function and cellular dynamics of two human RNA methyltransferases previously associated with neurological dysfunction, TRMT1 and its homolog, TRMT1-like (TRMT1L). Using a combination of next-generation sequencing, LC-MS/MS, patient-derived cell lines and knockout mouse models, we confirm the previously reported dimethylguanosine (m^2,2G) activity of TRMT1 in tRNAs, as well as reveal that TRMT1L, whose activity was unknown, is responsible for methylating a subset of cytosolic tRNA^Ala(AGC) isodecoders at position 26. Using a cellular in vitro model that mimics neuronal activation and long term potentiation, we find that both TRMT1 and TRMT1L change their subcellular localization upon neuronal activation. Specifically, we observe a major subcellular relocalization from mitochondria and other cytoplasmic domains (TRMT1) and nucleoli (TRMT1L) to different small punctate compartments in the nucleus, which are as yet uncharacterized. This phenomenon does not occur upon heat shock, suggesting that the relocalization of TRMT1 and TRMT1L is not a general reaction to stress, but rather a specific response to neuronal activation. Our results suggest that subcellular relocalization of RNA modification enzymes may play a role in neuronal plasticity and transmission of information, presumably by addressing new targets.

A tRNA-Derived Small RNA Regulates Ribosomal Protein S28 Protein Levels after Translation Initiation in Humans and Mice

tRNA-derived small RNAs (tsRNAs) have been implicated in many cellular processes, yet the detailed mechanisms are not well defined. We previously found that the 3' end of Leu-CAG tRNA-derived small RNA (LeuCAG3'tsRNA) regulates ribosome biogenesis in humans by maintaining ribosomal protein S28 (RPS28) levels. The tsRNA binds to coding (CDS) and non-coding 3' UTR sequence in the RPS28 mRNA, altering its secondary structure and enhancing its translation. Here we report that the functional 3' UTR target site is present in primates while the CDS target site is present in many vertebrates. We establish that this tsRNA also regulates mouse Rps28 translation by interacting with the CDS target site. We further establish that the change in mRNA translation occurred at a post-initiation step in both species. Overall, our results suggest that LeuCAG3'tsRNA might maintain ribosome biogenesis through a conserved gene regulatory mechanism in vertebrates.

LOTTE-seq (Long hairpin oligonucleotide based tRNA high-throughput sequencing): specific selection of tRNAs with 3'-CCA end for high-throughput sequencing

Transfer RNAs belong to the most abundant type of ribonucleic acid in the cell, and detailed investigations revealed correlations between alterations in the tRNA pool composition and certain diseases like breast cancer. However, currently available methods do not sample the entire tRNA pool or lack specificity for tRNAs. A specific disadvantage of such methods is that only full-length tRNAs are analysed, while tRNA fragments or incomplete cDNAs due to RT stops at modified nucleosides are lost. Another drawback in certain approaches is that the tRNA fraction has to be isolated and separated from high molecular weight RNA, resulting in considerable labour costs and loss of material. Based on a hairpin-shaped adapter oligonucleotide selective for tRNA transcripts, we developed a highly specific protocol for efficient and comprehensive high-throughput analysis of tRNAs that combines the benefits of existing methods and eliminates their disadvantages. Due to a 3'-TGG overhang, the adapter is specifically ligated to the tRNA 3'-CCA end. Reverse transcription prior to the ligation of a second adapter allows to include prematurely terminated cDNA products, increasing the number of tRNA reads. This strategy renders this approach a powerful and universal tool to analyse the tRNA pool of cells and organisms under different conditions in health and disease.

Graphical Workflow System for Modification Calling by Machine Learning of Reverse Transcription Signatures

Modification mapping from cDNA data has become a tremendously important approach in epitranscriptomics. So-called reverse transcription signatures in cDNA contain information on the position and nature of their causative RNA modifications. Data mining of, e.g. Illumina-based high-throughput sequencing data, is therefore fast growing in importance, and the field is still lacking effective tools. Here we present a versatile user-friendly graphical workflow system for modification calling based on machine learning. The workflow commences with a principal module for trimming, mapping, and postprocessing. The latter includes a quantification of mismatch and arrest rates with single-nucleotide resolution across the mapped transcriptome. Further downstream modules include tools for visualization, machine learning, and modification calling. From the machine-learning module, quality assessment parameters are provided to gauge the suitability of the initial dataset for effective machine learning and modification calling. This output is useful to improve the experimental parameters for library preparation and sequencing. In summary, the automation of the bioinformatics workflow allows a faster turnaround of the optimization cycles in modification calling.

Cicada Endosymbionts Have tRNAs That Are Correctly Processed Despite Having Genomes That Do Not Encode All of the tRNA Processing Machinery

The smallest bacterial genomes, in the range of about 0.1 to 0.5 million base pairs, are commonly found in the nutritional endosymbionts of insects. These tiny genomes are missing genes that encode proteins and RNAs required for the translation of mRNAs, one of the most highly conserved and important cellular processes. In this study, we found that the bacterial endosymbionts of cicadas have genomes which encode incomplete tRNA sets and lack genes required for tRNA processing. Nevertheless, we found that endosymbiont tRNAs are correctly processed at their 5′ and 3′ ends and, surprisingly, that mostly exist as tRNA halves. We hypothesize that the cicada host must supply its symbionts with these missing tRNA processing activities.

Gene loss and genome reduction are defining characteristics of endosymbiotic bacteria. The most highly reduced endosymbiont genomes have lost numerous essential genes related to core cellular processes such as replication, transcription, and translation. Computational gene predictions performed for the genomes of the two bacterial symbionts of the cicada Diceroprocta semicincta, “Candidatus Hodgkinia cicadicola” (Alphaproteobacteria) and “Ca. Sulcia muelleri” (Bacteroidetes), have found only 26 and 16 tRNA genes and 15 and 10 aminoacyl tRNA synthetase genes, respectively. Furthermore, the original “Ca. Hodgkinia cicadicola” genome annotation was missing several essential genes involved in tRNA processing, such as those encoding RNase P and CCA tRNA nucleotidyltransferase as well as several RNA editing enzymes required for tRNA maturation. How these cicada endosymbionts perform basic translation-related processes remains unknown. Here, by sequencing eukaryotic mRNAs and total small RNAs, we show that the limited tRNA set predicted by computational annotation of “Ca. Sulcia muelleri” and “Ca. Hodgkinia cicadicola” is likely correct. Furthermore, we show that despite the absence of genes encoding tRNA processing activities in the symbiont genomes, symbiont tRNAs have correctly processed 5′ and 3′ ends and seem to undergo nucleotide modification. Surprisingly, we found that most “Ca. Hodgkinia cicadicola” and “Ca. Sulcia muelleri” tRNAs exist as tRNA halves. We hypothesize that “Ca. Sulcia muelleri” and “Ca. Hodgkinia cicadicola” tRNAs function in bacterial translation but require host-encoded enzymes to do so.

Accurate mapping of tRNA reads

Motivation

Many repetitive DNA elements are transcribed at appreciable expression levels. Mapping the corresponding RNA sequencing reads back to a reference genome is notoriously difficult and error-prone task, however. This is in particular true if chemical modifications introduce systematic mismatches, while at the same time the genomic loci are only approximately identical, as in the case of tRNAs.

Results

We therefore developed a dedicated mapping strategy to handle RNA-seq reads that map to tRNAs relying on a modified target genome in which known tRNA loci are masked and instead intronless tRNA precursor sequences are appended as artificial 'chromosomes'. In a first pass, reads that overlap the boundaries of mature tRNAs are extracted. In the second pass, the remaining reads are mapped to a tRNA-masked target that is augmented by representative mature tRNA sequences. Using both simulated and real life data we show that our best-practice workflow removes most of the mapping artefacts introduced by simpler mapping schemes and makes it possible to reliably identify many of chemical tRNA modifications in generic small RNA-seq data. Using simulated data the FDR is only 2%. We find compelling evidence for tissue specific differences of tRNA modification patterns.

Availability and implementation

The workflow is available both as a bash script and as a Galaxy workflow from https://github.com/AnneHoffmann/tRNA-read-mapping.

Contact

fabian@tbi.univie.ac.at.

Supplementary information

Supplementary data are available at Bioinformatics online.

Engineering of a DNA Polymerase for Direct m6 A Sequencing

Methods for the detection of RNA modifications are of fundamental importance for advancing epitranscriptomics. N6 -methyladenosine (m6 A) is the most abundant RNA modification in mammalian mRNA and is involved in the regulation of gene expression. Current detection techniques are laborious and rely on antibody-based enrichment of m6 A-containing RNA prior to sequencing, since m6 A modifications are generally "erased" during reverse transcription (RT). To overcome the drawbacks associated with indirect detection, we aimed to generate novel DNA polymerase variants for direct m6 A sequencing. Therefore, we developed a screen to evolve an RT-active KlenTaq DNA polymerase variant that sets a mark for N6 -methylation. We identified a mutant that exhibits increased misincorporation opposite m6 A compared to unmodified A. Application of the generated DNA polymerase in next-generation sequencing allowed the identification of m6 A sites directly from the sequencing data of untreated RNA samples.

Protein folding and tRNA biology

Polypeptides can fold into tertiary structures while they are synthesized by the ribosome. In addition to the amino acid sequence, protein folding is determined by several factors within the cell. Among others, the folding pathway of a nascent polypeptide can be affected by transient interactions with other proteins, ligands, or the ribosome, as well as by the translocation through membrane pores. Particularly, the translation machinery and the population of tRNA under different physiological or adaptive responses can dramatically affect protein folding. This review summarizes the scientific evidence describing the role of translation kinetics and tRNA populations on protein folding and addresses current efforts to better understand tRNA biology. It is organized into three main parts, which are focused on: (i) protein folding in the cellular context; (ii) tRNA biology and the complexity of the tRNA population; and (iii) available methods and technical challenges in the characterization of tRNA pools. In this manner, this work illustrates the ways by which functional properties of proteins may be modulated by cellular tRNA populations.

Detection of a Subset of Posttranscriptional Transfer RNA Modifications in Vivo with a Restriction Fragment Length Polymorphism-Based Method

Transfer RNAs (tRNAs) are among the most heavily modified RNA species. Posttranscriptional tRNA modifications (ptRMs) play fundamental roles in modulating tRNA structure and function and are being increasingly linked to human physiology and disease. Detection of ptRMs is often challenging, expensive, and laborious. Restriction fragment length polymorphism (RFLP) analyses study the patterns of DNA cleavage after restriction enzyme treatment and have been used for the qualitative detection of modified bases on mRNAs. It is known that some ptRMs induce specific and reproducible base "mutations" when tRNAs are reverse transcribed. For example, inosine, which derives from the deamination of adenosine, is detected as a guanosine when an inosine-containing tRNA is reverse transcribed, amplified via polymerase chain reaction (PCR), and sequenced. ptRM-dependent base changes on reverse transcription PCR amplicons generated as a consequence of the reverse transcription reaction might create or abolish endonuclease restriction sites. The suitability of RFLP for the detection and/or quantification of ptRMs has not been studied thus far. Here we show that different ptRMs can be detected at specific sites of different tRNA types by RFLP. For the examples studied, we show that this approach can reliably estimate the modification status of the sample, a feature that can be useful in the study of the regulatory role of tRNA modifications in gene expression.

Going global: the new era of mapping modifications in RNA

The post-transcriptional modification of RNA by the addition of one or more chemical groups has been known for over 50 years. These chemical modifications, once thought to be static, are now being discovered to play key regulatory roles in gene expression. The advent of massive parallel sequencing of RNA (RNA-seq) now allows us to probe the complexity of cellular RNA and how chemically altering RNA structure expands the RNA vocabulary. Here we present an overview of the various strategies and technologies that are available to profile RNA chemical modifications at the cellular level. These strategies can be characterized as targeted and untargeted approaches: targeted strategies are developed for one single chemical modification while untargeted strategies are more broadly applicable to a range of such chemical changes. Key for all of these approaches is the ability to locate modifications within the RNA sequence. While most of these methods are built upon an RNA-Seq pipeline, alternative approaches based on mass spectrometry or conventional DNA sequencing retain value in the overall analysis process. We also look forward toward future opportunities and technologies that may expand the types of modifications that can be globally profiled. Given the ever increasing recognition that these RNA chemical modifications play important biological roles, a variety of methods, preferably orthogonal approaches, will be required to globally identify, validate and quantify RNA chemical modifications found in the transcriptome. WIREs RNA 2017, 8:e1367. doi: 10.1002/wrna.1367 For further resources related to this article, please visit the WIREs website.

CoverageAnalyzer (CAn): A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

Combination of reverse transcription (RT) and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modification candidates. CoverageAnalyzer (CAn) was developed in response to the demand for a powerful inspection tool. It is freely available for all three main operating systems. With SAM file format as standard input, CAn is an intuitive and user-friendly tool that is generally applicable to the large community of biomedical users, starting from simple visualization of RNA sequencing (RNA-Seq) data, up to sophisticated modification analysis with significance-based modification candidate calling.

Mitochondrial 16S rRNA Is Methylated by tRNA Methyltransferase TRMT61B in All Vertebrates

The mitochondrial ribosome, which translates all mitochondrial DNA (mtDNA)-encoded proteins, should be tightly regulated pre- and post-transcriptionally. Recently, we found RNA-DNA differences (RDDs) at human mitochondrial 16S (large) rRNA position 947 that were indicative of post-transcriptional modification. Here, we show that these 16S rRNA RDDs result from a 1-methyladenosine (m¹A) modification introduced by TRMT61B, thus being the first vertebrate methyltransferase that modifies both tRNA and rRNAs. m¹A947 is conserved in humans and all vertebrates having adenine at the corresponding mtDNA position (90% of vertebrates). However, this mtDNA base is a thymine in 10% of the vertebrates and a guanine in the 23S rRNA of 95% of bacteria, suggesting alternative evolutionary solutions. m¹A, uridine, or guanine may stabilize the local structure of mitochondrial and bacterial ribosomes. Experimental assessment of genome-edited Escherichia coli showed that unmodified adenine caused impaired protein synthesis and growth. Our findings revealed a conserved mechanism of rRNA modification that has been selected instead of DNA mutations to enable proper mitochondrial ribosome function.

Two solutions were selected during evolution to allow proper function of the vertebrate mitochondrial 16S ribosomal RNAeither RNA methylation by a tRNA methyltransferase or ancient evolutionary mutation.

RNA modifications constitute an important layer of information, with functional implications that are not written in the underlying DNA sequence. Recently, we observed an apparent RNA-DNA difference (RDD) at position 947 of the human mitochondrial 16S ribosomal RNA (rRNA), but its nature and mechanism were unclear. Here we show that this disparity reflects an m¹A modification (methylation at position 1 of the adenine moiety), and demonstrated by a combination of knock-down experiments in cells and in vitro methylation assays that the tRNA methyltransferase TRMT61B is the best candidate enzyme to introduce this modification. We also show that this modification is present in most of the 16S rRNA molecules in isolated mitochondrial ribosomes, and that it occurs in all vertebrates with an adenine (90% of the vertebrates), but not in those with a thymidine at this 16S rRNA position. Finally, as the first step towards understanding the functional importance of this rRNA modification, we used a genome-edited bacterial system to demonstrate that an unmodified adenine reduced the growth and translation rates of the bacteria as compared to both wild-type bacteria and mutant bacteria with a thymidine in the relevant position. Hence, three solutions were selected during evolution to allow proper function of the mitochondrial 16S rRNA—either RNA modification or two alternative ancient evolutionary DNA mutations.

tDRmapper: challenges and solutions to mapping, naming, and quantifying tRNA-derived RNAs from human small RNA-sequencing data

Background

Small RNA-sequencing has revealed the diversity and high abundance of small RNAs derived from tRNAs, referred to as tRNA-derived RNAs. However, at present, there is no standardized nomenclature and there are no methods for accurate annotation and quantification of these small RNAs. tRNA-derived RNAs have unique features that limit the utility of conventional alignment tools and quantification methods.

Results

We describe here the challenges of mapping, naming, and quantifying tRNA-derived RNAs and present a novel method that addresses them, called tDRmapper. We then use tDRmapper to perform a comparative analysis of tRNA-derived RNA profiles across different human cell types and diseases. We found that (1) tRNA-derived RNA profiles can differ dramatically across different cell types and disease states, (2) that positions and types of chemical modifications of tRNA-derived RNAs vary by cell type and disease, and (3) that entirely different tRNA-derived RNA species can be produced from the same parental tRNA depending on the cell type.

Conclusion

tDRmappernot only provides a standardized nomenclature and quantification scheme, but also includes graphical visualization that facilitates the discovery of novel tRNA and tRNA-derived RNA biology.

The reverse transcription signature of N-1-methyladenosine in RNA-Seq is sequence dependent

The combination of Reverse Transcription (RT) and high-throughput sequencing has emerged as a powerful combination to detect modified nucleotides in RNA via analysis of either abortive RT-products or of the incorporation of mismatched dNTPs into cDNA. Here we simultaneously analyze both parameters in detail with respect to the occurrence of N-1-methyladenosine (m¹A) in the template RNA. This naturally occurring modification is associated with structural effects, but it is also known as a mediator of antibiotic resistance in ribosomal RNA. In structural probing experiments with dimethylsulfate, m¹A is routinely detected by RT-arrest. A specifically developed RNA-Seq protocol was tailored to the simultaneous analysis of RT-arrest and misincorporation patterns. By application to a variety of native and synthetic RNA preparations, we found a characteristic signature of m¹A, which, in addition to an arrest rate, features misincorporation as a significant component. Detailed analysis suggests that the signature depends on RNA structure and on the nature of the nucleotide 3′ of m¹A in the template RNA, meaning it is sequence dependent. The RT-signature of m¹A was used for inspection and confirmation of suspected modification sites and resulted in the identification of hitherto unknown m¹A residues in trypanosomal tRNA.

ARM-seq: AlkB-facilitated RNA methylation sequencing reveals a complex landscape of modified tRNA fragments

High throughput RNA sequencing has accelerated discovery of the complex regulatory roles of small RNAs, but RNAs containing modified nucleosides may escape detection when those modifications interfere with reverse transcription during RNA-seq library preparation. Here we describe AlkB-facilitated RNA Methylation sequencing (ARM-Seq) which uses pre-treatment with Escherichia coli AlkB to demethylate 1-methyladenosine, 3-methylcytidine, and 1-methylguanosine, all commonly found in transfer RNAs. Comparative methylation analysis using ARM-Seq provides the first detailed, transcriptome-scale map of these modifications, and reveals an abundance of previously undetected, methylated small RNAs derived from tRNAs. ARM-Seq demonstrates that tRNA-derived small RNAs accurately recapitulate the m¹A modification state for well-characterized yeast tRNAs, and generates new predictions for a large number of human tRNAs, including tRNA precursors and mitochondrial tRNAs. Thus, ARM-Seq provides broad utility for identifying previously overlooked methyl-modified RNAs, can efficiently monitor methylation state, and may reveal new roles for tRNA-derived RNAs as biomarkers or signaling molecules.

Differential and coherent processing patterns from small RNAs

Post-transcriptional processing events related to short RNAs are often reflected in their read profile patterns emerging from high-throughput sequencing data. MicroRNA arm switching across different tissues is a well-known example of what we define as differential processing. Here, short RNAs from the nine cell lines of the ENCODE project, irrespective of their annotation status, were analyzed for genomic loci representing differential or coherent processing. We observed differential processing predominantly in RNAs annotated as miRNA, snoRNA or tRNA. Four out of five known cases of differentially processed miRNAs that were in the input dataset were recovered and several novel cases were discovered. In contrast to differential processing, coherent processing is observed widespread in both annotated and unannotated regions. While the annotated loci predominantly consist of ~24 nt short RNAs, the unannotated loci comparatively consist of ~17 nt short RNAs. Furthermore, these ~17 nt short RNAs are significantly enriched for overlap to transcription start sites and DNase I hypersensitive sites (p-value < 0.01) that are characteristic features of transcription initiation RNAs. We discuss how the computational pipeline developed in this study has the potential to be applied to other forms of RNA-seq data for further transcriptome-wide studies of differential and coherent processing.

The identity of the discriminator base has an impact on CCA addition

CCA-adding enzymes synthesize and maintain the C-C-A sequence at the tRNA 3'-end, generating the attachment site for amino acids. While tRNAs are the most prominent substrates for this polymerase, CCA additions on non-tRNA transcripts are described as well. To identify general features for substrate requirement, a pool of randomized transcripts was incubated with the human CCA-adding enzyme. Most of the RNAs accepted for CCA addition carry an acceptor stem-like terminal structure, consistent with tRNA as the main substrate group for this enzyme. While these RNAs show no sequence conservation, the position upstream of the CCA end was in most cases represented by an adenosine residue. In tRNA, this position is described as discriminator base, an important identity element for correct aminoacylation. Mutational analysis of the impact of the discriminator identity on CCA addition revealed that purine bases (with a preference for adenosine) are strongly favoured over pyrimidines. Furthermore, depending on the tRNA context, a cytosine discriminator can cause a dramatic number of misincorporations during CCA addition. The data correlate with a high frequency of adenosine residues at the discriminator position observed in vivo. Originally identified as a prominent identity element for aminoacylation, this position represents a likewise important element for efficient and accurate CCA addition.

Inosine modifications in human tRNAs are incorporated at the precursor tRNA level

Transfer RNAs (tRNAs) are key adaptor molecules of the genetic code that are heavily modified post-transcriptionally. Inosine at the first residue of the anticodon (position 34; I34) is an essential widespread tRNA modification that has been poorly studied thus far. The modification in eukaryotes results from a deamination reaction of adenine that is catalyzed by the heterodimeric enzyme adenosine deaminase acting on tRNA (hetADAT), composed of two subunits: ADAT2 and ADAT3. Using high-throughput small RNA sequencing (RNAseq), we show that this modification is incorporated to human tRNAs at the precursor tRNA level and during maturation. We also functionally validated the human genes encoding for hetADAT and show that the subunits of this enzyme co-localize in nucleus in an ADAT2-dependent manner. Finally, by knocking down HsADAT2, we demonstrate that variations in the cellular levels of hetADAT will result in changes in the levels of I34 modification in all its potential substrates. Altogether, we present RNAseq as a powerful tool to study post-transcriptional tRNA modifications at the precursor tRNA level and give the first insights on the biology of I34 tRNA modification in metazoans.

Bacterial transfer RNAs

Transfer RNA is an essential adapter molecule that is found across all three domains of life. The primary role of transfer RNA resides in its critical involvement in the accurate translation of messenger RNA codons during protein synthesis and, therefore, ultimately in the determination of cellular gene expression. This review aims to bring together the results of intensive investigations into the synthesis, maturation, modification, aminoacylation, editing and recycling of bacterial transfer RNAs. Codon recognition at the ribosome as well as the ever-increasing number of alternative roles for transfer RNA outside of translation will be discussed in the specific context of bacterial cells.

Analysis of the human mitochondrial transcriptome using directional deep sequencing and parallel analysis of RNA ends

RNA sequencing using next-generation technologies provides comprehensive coverage of transcriptomes at a much greater depth than conventional transcriptomic methods. The human mitochondrial genome is relatively small, and sequencing its transcriptome provides a valuable method to investigate changes in RNA metabolism in great detail. Here we describe two methods that use next-generation technologies to investigate mitochondrial RNAs. Directional RNA sequencing enables the analyses of RNA abundance from each strand of the mitochondrial DNA. Parallel analysis of RNA ends enables the analyses of processing of mitochondrial transcripts, their termini, and annotation of any new transcripts.

BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles

Summary: Non-coding RNAs (ncRNAs) play a vital role in many cellular processes such as RNA splicing, translation, gene regulation. However the vast majority of ncRNAs still have no functional annotation. One prominent approach for putative function assignment is clustering of transcripts according to sequence and secondary structure. However sequence information is changed by post-transcriptional modifications, and secondary structure is only a proxy for the true 3D conformation of the RNA polymer. A different type of information that does not suffer from these issues and that can be used for the detection of RNA classes, is the pattern of processing and its traces in small RNA-seq reads data. Here we introduce BlockClust, an efficient approach to detect transcripts with similar processing patterns. We propose a novel way to encode expression profiles in compact discrete structures, which can then be processed using fast graph-kernel techniques. We perform both unsupervised clustering and develop family specific discriminative models; finally we show how the proposed approach is scalable, accurate and robust across different organisms, tissues and cell lines.

Availability: The whole BlockClust galaxy workflow including all tool dependencies is available at http://toolshed.g2.bx.psu.edu/view/rnateam/blockclust_workflow.

Contact:backofen@informatik.uni-freiburg.de; costa@informatik.uni-freiburg.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Aberrant methylation of tRNAs links cellular stress to neuro-developmental disorders

Mutations in the cytosine-5 RNA methyltransferase NSun2 cause microcephaly and other neurological abnormalities in mice and human. How post-transcriptional methylation contributes to the human disease is currently unknown. By comparing gene expression data with global cytosine-5 RNA methylomes in patient fibroblasts and NSun2-deficient mice, we find that loss of cytosine-5 RNA methylation increases the angiogenin-mediated endonucleolytic cleavage of transfer RNAs (tRNA) leading to an accumulation of 5' tRNA-derived small RNA fragments. Accumulation of 5' tRNA fragments in the absence of NSun2 reduces protein translation rates and activates stress pathways leading to reduced cell size and increased apoptosis of cortical, hippocampal and striatal neurons. Mechanistically, we demonstrate that angiogenin binds with higher affinity to tRNAs lacking site-specific NSun2-mediated methylation and that the presence of 5' tRNA fragments is sufficient and required to trigger cellular stress responses. Furthermore, the enhanced sensitivity of NSun2-deficient brains to oxidative stress can be rescued through inhibition of angiogenin during embryogenesis. In conclusion, failure in NSun2-mediated tRNA methylation contributes to human diseases via stress-induced RNA cleavage.

Biological and bioinformatical approaches to study crosstalk of long-non-coding RNAs and chromatin-modifying proteins

Long-non-coding RNA (lncRNA) regulates gene expression through transcriptional and epigenetic regulation as well as alternative splicing in the nucleus. In addition, regulation is achieved at the levels of mRNA translation, storage and degradation in the cytoplasm. During recent years, several studies have described the interaction of lncRNAs with enzymes that confer so-called epigenetic modifications, such as DNA methylation, histone modifications and chromatin structure or remodelling. LncRNA interaction with chromatin-modifying enzymes (CME) is an emerging field that confers another layer of complexity in transcriptional regulation. Given that CME-lncRNA interactions have been identified in many biological processes, ranging from development to disease, comprehensive understanding of underlying mechanisms is important to inspire basic and translational research in the future. In this review, we highlight recent findings to extend our understanding about the functional interdependencies between lncRNAs and CMEs that activate or repress gene expression. We focus on recent highlights of molecular and functional roles for CME-lncRNAs and provide an interdisciplinary overview of recent technical and methodological developments that have improved biological and bioinformatical approaches for detection and functional studies of CME-lncRNA interaction.

Bioinformatics of prokaryotic RNAs

The genome of most prokaryotes gives rise to surprisingly complex transcriptomes, comprising not only protein-coding mRNAs, often organized as operons, but also harbors dozens or even hundreds of highly structured small regulatory RNAs and unexpectedly large levels of anti-sense transcripts. Comprehensive surveys of prokaryotic transcriptomes and the need to characterize also their non-coding components is heavily dependent on computational methods and workflows, many of which have been developed or at least adapted specifically for the use with bacterial and archaeal data. This review provides an overview on the state-of-the-art of RNA bioinformatics focusing on applications to prokaryotes.

TSSAR: TSS annotation regime for dRNA-seq data

BACKGROUND

Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular. Hitherto, dRNA-seq data were analyzed by visualizing the sequencing reads mapped to the reference genome and manually annotating reliable positions. This is very labor intensive and, due to the subjectivity, biased.

RESULTS

Here, we present TSSAR, a tool for automated de novo TSS annotation from dRNA-seq data that respects the statistics of dRNA-seq libraries. TSSAR uses the premise that the number of sequencing reads starting at a certain genomic position within a transcriptional active region follows a Poisson distribution with a parameter that depends on the local strength of expression. The differences of two dRNA-seq library counts thus follow a Skellam distribution. This provides a statistical basis to identify significantly enriched primary transcripts.We assessed the performance by analyzing a publicly available dRNA-seq data set using TSSAR and two simple approaches that utilize user-defined score cutoffs. We evaluated the power of reproducing the manual TSS annotation. Furthermore, the same data set was used to reproduce 74 experimentally validated TSS in H. pylori from reliable techniques such as RACE or primer extension. Both analyses showed that TSSAR outperforms the static cutoff-dependent approaches.

CONCLUSIONS

Having an automated and efficient tool for analyzing dRNA-seq data facilitates the use of the dRNA-seq technique and promotes its application to more sophisticated analysis. For instance, monitoring the plasticity and dynamics of the transcriptomal architecture triggered by different stimuli and growth conditions becomes possible.The main asset of a novel tool for dRNA-seq analysis that reaches out to a broad user community is usability. As such, we provide TSSAR both as intuitive RESTful Web service ( http://rna.tbi.univie.ac.at/TSSAR) together with a set of post-processing and analysis tools, as well as a stand-alone version for use in high-throughput dRNA-seq data analysis pipelines.

Computational prediction of microRNA genes

The computational identification of novel microRNA (miRNA) genes is a challenging task in bioinformatics. Massive amounts of data describing unknown functional RNA transcripts have to be analyzed for putative miRNA candidates with automated computational pipelines. Beyond those miRNAs that meet the classical definition, high-throughput sequencing techniques have revealed additional miRNA-like molecules that are derived by alternative biogenesis pathways. Exhaustive bioinformatics analyses on such data involve statistical issues as well as precise sequence and structure inspection not only of the functional mature part but also of the whole precursor sequence of the putative miRNA. Apart from a considerable amount of species-specific miRNAs, the majority of all those genes are conserved at least among closely related organisms. Some miRNAs, however, can be traced back to very early points in the evolution of eukaryotic species. Thus, the investigation of the conservation of newly found miRNA candidates comprises an important step in the computational annotation of miRNAs.Topics covered in this chapter include a review on the obvious problem of miRNA annotation and family definition, recommended pipelines of computational miRNA annotation or detection, and an overview of current computer tools for the prediction of miRNAs and their limitations. The chapter closes discussing how those bioinformatic approaches address the problem of faithful miRNA prediction and correct annotation.

MicroRNA discovery by similarity search to a database of RNA-seq profiles

In silico generated search for microRNAs (miRNAs) has been driven by methods compiling structural features of the miRNA precursor hairpin, as well as to some degree combining this with the analysis of RNA-seq profiles for which the miRNA typically leave the drosha/dicer fingerprint of 1-2 ~22 nt blocks of reads corresponding to the mature and star miRNA. In complement to the previous methods, we present a study where we systematically exploit these patterns of read profiles. We created two datasets comprised of 2540 and 4795 read profiles obtained after preprocessing short RNA-seq data from miRBase and ENCODE, respectively. Out of 4795 ENCODE read profiles, 1361 are annotated as non-coding RNAs (ncRNAs) and of which 285 are further annotated as miRNAs. Using deepBlockAlign (dba), we align ncRNA read profiles from ENCODE against the miRBase read profiles (cleaned for "self-matches") and are able to separate ENCODE miRNAs from the other ncRNAs by a Matthews Correlation Coefficient (MCC) of 0.8 and obtain an area under the curve of 0.93. Based on the dba score cut-off of 0.7 at which we observed the maximum MCC of 0.8, we predict 523 novel miRNA candidates. An additional RNA secondary structure analysis reveal that 42 of the candidates overlap with predicted conserved secondary structure. Further analysis reveal that the 523 miRNA candidates are located in genomic regions with MAF block (UCSC) fragmentation and poor sequence conservation, which in part might explain why they have been overlooked in previous efforts. We further analyzed known human and mouse miRNA read profiles and found two distinct classes; the first containing two blocks and the second containing >2 blocks of reads. Also the latter class holds read profiles that have less well defined arrangement of reads in comparison to the former class. On comparison of miRNA read profiles from plants and animals, we observed kingdom specific read profiles that are distinct in terms of both length and distribution of reads within the read profiles to each other. All the data, as well as a server to search miRBase read profiles by uploading a BED file, is available at http://rth.dk/resources/mirdba.

RNA-Seq analyses reveal the order of tRNA processing events and the maturation of C/D box and CRISPR RNAs in the hyperthermophile Methanopyrus kandleri

The methanogenic archaeon Methanopyrus kandleri grows near the upper temperature limit for life. Genome analyses revealed strategies to adapt to these harsh conditions and elucidated a unique transfer RNA (tRNA) C-to-U editing mechanism at base 8 for 30 different tRNA species. Here, RNA-Seq deep sequencing methodology was combined with computational analyses to characterize the small RNome of this hyperthermophilic organism and to obtain insights into the RNA metabolism at extreme temperatures. A large number of 132 small RNAs were identified that guide RNA modifications, which are expected to stabilize structured RNA molecules. The C/D box guide RNAs were shown to exist as circular RNA molecules. In addition, clustered regularly interspaced short palindromic repeats RNA processing and potential regulatory RNAs were identified. Finally, the identification of tRNA precursors before and after the unique C8-to-U8 editing activity enabled the determination of the order of tRNA processing events with termini truncation preceding intron removal. This order of tRNA maturation follows the compartmentalized tRNA processing order found in Eukaryotes and suggests its conservation during evolution.

Alternative processing of the U2 small nuclear RNA produces a 19-22nt fragment with relevance for the detection of non-small cell lung cancer in human serum

RNU2 exists in two functional forms (RNU2-1 and RNU2-2) distinguishable by the presence of a unique 4-bases motif. Detailed investigation of datasets obtained from deep sequencing of five human lung primary tumors revealed that both forms express at a high rate a 19-22nt fragment (miR-U2-1 and -2) from its 3' region and contains the 4-bases motif. Deep sequencing of independent pools of serum samples from healthy donors and lung cancer patients revealed that miR-U2-1 and -2 are pervasively processed in lung tissue by means of endonucleolytic cleavages and stably exported to the blood. Then, microarrays hybridization experiments of matched normal/tumor samples revealed a significant over-expression of miR-U2-1 in 14 of 18 lung primary tumors. Subsequently, qRT-PCR of miR-U2-1 using serum from 62 lung cancer patients and 96 various controls demonstrated that its expression levels identify lung cancer patients with 79% sensitivity and 80% specificity. miR-U2-1 expression correlated with the presence or absence of lung cancer in patients with chronic obstructive pulmonary disease (COPD), other diseases of the lung - not cancer, and in healthy controls. These data suggest that RNU2-1 is a new bi-functional ncRNA that produces a 19-22nt fragment which may be useful in detecting lung cancer non-invasively in high risk patients.

Dicer-processed small RNAs: rules and exceptions

Canonical microRNAs are excised from their hairpin-shaped precursors by Dicer. In order to find possible exceptions to this rule and to identify additional substrates for Dicer processing we re-evaluate the small RNA sequencing data of the Dicer knockdown experiment in MCF-7 cells orignally published by Friedländer et al. [Friedländer et al., 2012, Nucleic Acids Res 40:37-52]. While the well-known non-Dicer mir-451 is not sufficiently expressed in these experiments, there are several additional Dicer-independent microRNAs, among them the important tumor supressor mir-663a. We recover previously described examples of non-miRNA Dicer substrates such as tRNA-Gln and several snoRNAs. Interestingly, sdRNAs derived from box C/D snoRNAs are Dicer-independent, while those derived from box H/ACA snoRNAs are often Dicer dependent. Several pol-III transcripts, in particular the vault RNAs and the great ape specific snaRs are processed by Dicer, while the small RNAs originating from Y RNAs seem to be Dicer independent.

The expanding scope of DNA sequencing

In just seven years, next-generation technologies have reduced the cost and increased the speed of DNA sequencing by four orders of magnitude, and experiments requiring many millions of sequencing reads are now routine. In research, sequencing is being applied not only to assemble genomes and to investigate the genetic basis of human disease, but also to explore myriad phenomena in organismic and cellular biology. In the clinic, the utility of sequence data is being intensively evaluated in diverse contexts, including reproductive medicine, oncology and infectious disease. A recurrent theme in the development of new sequencing applications is the creative 'recombination' of existing experimental building blocks. However, there remain many potentially high-impact applications of next-generation DNA sequencing that are not yet fully realized.

The rectal cancer microRNAome--microRNA expression in rectal cancer and matched normal mucosa

PURPOSE

miRNAs play a prominent role in a variety of physiologic and pathologic biologic processes, including cancer. For rectal cancers, only limited data are available on miRNA expression profiles, whereas the underlying genomic and transcriptomic aberrations have been firmly established. We therefore, aimed to comprehensively map the miRNA expression patterns of this disease.

EXPERIMENTAL DESIGN

Tumor biopsies and corresponding matched mucosa samples were prospectively collected from 57 patients with locally advanced rectal cancers. Total RNA was extracted, and tumor and mucosa miRNA expression profiles were subsequently established for all patients. The expression of selected miRNAs was validated using semi-quantitative real-time PCR.

RESULTS

Forty-nine miRNAs were significantly differentially expressed (log(2)-fold difference >0.5 and P < 0.001) between rectal cancer and normal rectal mucosa. The predicted targets for these miRNAs were enriched for the following pathways: Wnt, TGF-beta, mTOR, insulin, mitogen-activated protein kinase, and ErbB signaling. Thirteen of these 49 miRNAs seem to be rectal cancer-specific, and have not been previously reported for colon cancers: miR-492, miR-542-5p, miR-584, miR-483-5p, miR-144, miR-2110, miR-652, miR-375, miR-147b, miR-148a, miR-190, miR-26a/b, and miR-338-3p. Of clinical impact, miR-135b expression correlated significantly with disease-free and cancer-specific survival in an independent multicenter cohort of 116 patients.

CONCLUSION

This comprehensive analysis of the rectal cancer miRNAome uncovered novel miRNAs and pathways associated with rectal cancer. This information contributes to a detailed view of this disease. Moreover, the identification and validation of miR-135b may help to identify novel molecular targets and pathways for therapeutic exploitation.

Altered tRNA characteristics and 3' maturation in bacterial symbionts with reduced genomes

Translational efficiency is controlled by tRNAs and other genome-encoded mechanisms. In organelles, translational processes are dramatically altered because of genome shrinkage and horizontal acquisition of gene products. The influence of genome reduction on translation in endosymbionts is largely unknown. Here, we investigate whether divergent lineages of Buchnera aphidicola, the reduced-genome bacterial endosymbiont of aphids, possess altered translational features compared with their free-living relative, Escherichia coli. Our RNAseq data support the hypothesis that translation is less optimal in Buchnera than in E. coli. We observed a specific, convergent, pattern of tRNA loss in Buchnera and other endosymbionts that have undergone genome shrinkage. Furthermore, many modified nucleoside pathways that are important for E. coli translation are lost in Buchnera. Additionally, Buchnera’s A + T compositional bias has resulted in reduced tRNA thermostability, and may have altered aminoacyl-tRNA synthetase recognition sites. Buchnera tRNA genes are shorter than those of E. coli, as the majority no longer has a genome-encoded 3' CCA; however, all the expressed, shortened tRNAs undergo 3′ CCA maturation. Moreover, expression of tRNA isoacceptors was not correlated with the usage of corresponding codons. Overall, our data suggest that endosymbiont genome evolution alters tRNA characteristics that are known to influence translational efficiency in their free-living relative.

deepBlockAlign: a tool for aligning RNA-seq profiles of read block patterns

MOTIVATION

High-throughput sequencing methods allow whole transcriptomes to be sequenced fast and cost-effectively. Short RNA sequencing provides not only quantitative expression data but also an opportunity to identify novel coding and non-coding RNAs. Many long transcripts undergo post-transcriptional processing that generates short RNA sequence fragments. Mapped back to a reference genome, they form distinctive patterns that convey information on both the structure of the parent transcript and the modalities of its processing. The miR-miR* pattern from microRNA precursors is the best-known, but by no means singular, example.

RESULTS

deepBlockAlign introduces a two-step approach to align RNA-seq read patterns with the aim of quickly identifying RNAs that share similar processing footprints. Overlapping mapped reads are first merged to blocks and then closely spaced blocks are combined to block groups, each representing a locus of expression. In order to compare block groups, the constituent blocks are first compared using a modified sequence alignment algorithm to determine similarity scores for pairs of blocks. In the second stage, block patterns are compared by means of a modified Sankoff algorithm that takes both block similarities and similarities of pattern of distances within the block groups into account. Hierarchical clustering of block groups clearly separates most miRNA and tRNA, and also identifies about a dozen tRNAs clustering together with miRNA. Most of these putative Dicer-processed tRNAs, including eight cases reported to generate products with miRNA-like features in literature, exhibit read blocks distinguished by precise start position of reads.

AVAILABILITY

The program deepBlockAlign is available as source code from http://rth.dk/resources/dba/.

CONTACT

gorodkin@rth.dk; studla@bioinf.uni-leipzig.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The role of mammalian PPR domain proteins in the regulation of mitochondrial gene expression

Pentatricopeptide repeat (PPR) domain proteins are a large family of RNA-binding proteins that are involved in the maturation and translation of organelle transcripts in eukaryotes. They were first identified in plant organelles and their important role in mammalian mitochondrial gene regulation is now emerging. Mammalian PPR proteins, like their plant counterparts, have diverse roles in mitochondrial transcription, RNA metabolism and translation and consequently are important for mitochondrial function and cell health. Here we discuss the current knowledge about the seven mammalian PPR proteins identified to date and their roles in the regulation of mitochondrial gene expression. Furthermore we discuss the mitochondrial RNA targets of the mammalian PPR proteins and methods to investigate the RNA targets of these mitochondrial RNA-binding proteins. This article is part of a Special Issue entitled: Mitochondrial Gene Expression.