Comprehensive identification of diverse ribosomal RNA modifications by targeted nanopore direct RNA sequencing and JACUSA2

Charting the epitranscriptomic landscape across RNA biotypes using native RNA nanopore sequencing

RNA modifications are conserved chemical features found in all domains of life and across diverse RNA biotypes, shaping gene expression profiles and enabling rapid responses to environmental changes. Their broad chemical diversity and dynamic nature pose significant challenges for studying them comprehensively. These limitations can now be addressed through direct RNA nanopore sequencing (DRS), which allows simultaneous identification of diverse RNA modification types at single-molecule and single-nucleotide resolution. Here, we review recent efforts pioneering the use of DRS to better understand the epitranscriptomic landscape. We highlight how DRS can be applied to investigate different RNA biotypes, emphasizing the use of specialized library preparation protocols and downstream bioinformatic workflows to detect both natural and synthetic RNA modifications. Finally, we provide a perspective on the future role of DRS in epitranscriptomic research, highlighting remaining challenges and emerging opportunities from improved sequencing yields and accuracy enabled by the latest DRS chemistry.

Detecting a wide range of epitranscriptomic modifications using a nanopore-sequencing-based computational approach with 1D score-clustering

To date, over 40 epigenetic and 300 epitranscriptomic modifications have been identified. However, current short-read sequencing-based experimental methods can detect <10% of these modifications. Integrating long-read sequencing technologies with advanced computational approaches, including statistical analysis and machine learning, offers a promising new frontier to address this challenge. While supervised machine learning methods have achieved some success, their usefulness is restricted to a limited number of well-characterized modifications. Here, we introduce Modena, an innovative unsupervised learning approach utilizing long-read nanopore sequencing capable of detecting a broad range of modifications. Modena outperformed other methods in five out of six benchmark datasets, in some cases by a wide margin, while being equally competitive with the second best method on one dataset. Uniquely, Modena also demonstrates consistent accuracy on a DNA dataset, distinguishing it from other approaches. A key feature of Modena is its use of 'dynamic thresholding', an approach based on 1D score-clustering. This methodology differs substantially from the traditional statistics-based 'hard-thresholds.' We show that this approach is not limited to Modena but has broader applicability. Specifically, when combined with two existing algorithms, 'dynamic thresholding' significantly enhances their performance, resulting in up to a threefold improvement in F1-scores.

Visualizing the modification landscape of the human 60S ribosomal subunit at close to atomic resolution

Chemical modifications of ribosomal RNAs (rRNAs) and proteins expand their topological repertoire, and together with the plethora of bound ligands, fine-tune ribosomal function. Detailed knowledge of this natural composition provides important insights into ribosome genesis and function and clarifies some aspects of ribosomopathies. The discovery of new structural properties and functional aspects of ribosomes has gone hand in hand with cryo-electron microscopy (cryo-EM) and its technological development. In line with the ability to visualize atomic details - a prerequisite for identifying chemical modifications and ligands in cryo-EM maps - in this work we present the structure of the 60S ribosomal subunit from HeLa cells at the very high global resolution of 1.78 Å. We identified 113 rRNA modifications and four protein modifications including uL2-Hisβ-ox216, which stabilizes the local structure near the peptidyl transferase centre via an extended hydrogen-bonding network. We can differentiate metal ions Mg2+ and K+, polyamines spermine, spermidine and putrescine and identify thousands of water molecules binding to the 60S subunit. Approaching atomic resolution cryo-EM has become a powerful tool to examine fine details of macromolecular structures that will expand our knowledge about translation and other biological processes in the future and assess the variability of the chemical space due to differences between species/tissues or varying physicochemical environment.

Epitranscriptomic rRNA fingerprinting reveals tissue-of-origin and tumor-specific signatures

Mammalian ribosomal RNA (rRNA) molecules are highly abundant RNAs, decorated with over 220 rRNA modifications. Previous works have shown that some rRNA modification types can be dynamically regulated; however, how and when the mammalian rRNA modification landscape is remodeled remains largely unexplored. Here, we employ direct RNA sequencing to chart the human and mouse rRNA epitranscriptome across tissues, developmental stages, cell types, and disease. Our analyses reveal multiple rRNA sites that are differentially modified in a tissue- and/or developmental stage-specific manner, including previously unannotated modified sites. We demonstrate that rRNA modification patterns can be used for tissue and cell-type identification, which we hereby term "epitranscriptomic fingerprinting." We then explore rRNA modification patterns in normal-tumor matched samples from lung cancer patients, finding that epitranscriptomic fingerprinting accurately classifies clinical samples into normal and tumor groups from only 250 reads per sample, demonstrating the potential of rRNA modifications as diagnostic biomarkers.

NERD-seq: a novel approach of Nanopore direct RNA sequencing that expands representation of non-coding RNAs

Non-coding RNAs (ncRNAs) are frequently documented RNA modification substrates. Nanopore Technologies enables the direct sequencing of RNAs and the detection of modified nucleobases. Ordinarily, direct RNA sequencing uses polyadenylation selection, studying primarily mRNA gene expression. Here, we present NERD-seq, which enables detection of multiple non-coding RNAs, excluded by the standard approach, alongside natively polyadenylated transcripts. Using neural tissues as a proof of principle, we show that NERD-seq expands representation of frequently modified non-coding RNAs, such as snoRNAs, snRNAs, scRNAs, srpRNAs, tRNAs, and rRFs. NERD-seq represents an RNA-seq approach to simultaneously study mRNA and ncRNA epitranscriptomes in brain tissues and beyond.

Detecting m6A at single-molecular resolution via direct RNA sequencing and realistic training data

Direct RNA sequencing offers the possibility to simultaneously identify canonical bases and epi-transcriptomic modifications in each single RNA molecule. Thus far, the development of computational methods has been hampered by the lack of biologically realistic training data that carries modification labels at molecular resolution. Here, we report on the synthesis of such samples and the development of a bespoke algorithm, mAFiA (m6A Finding Algorithm), that accurately detects single m6A nucleotides in both synthetic RNAs and natural mRNA on single read level. Our approach uncovers distinct modification patterns in single molecules that would appear identical at the ensemble level. Compared to existing methods, mAFiA also demonstrates improved accuracy in measuring site-level m6A stoichiometry in biological samples.

Detection of queuosine and queuosine precursors in tRNAs by direct RNA sequencing

Queuosine (Q) is a complex tRNA modification found in bacteria and eukaryotes at position 34 of four tRNAs with a GUN anticodon, and it regulates the translational efficiency and fidelity of the respective codons that differ at the Wobble position. In bacteria, the biosynthesis of Q involves two precursors, preQ0 and preQ1, whereas eukaryotes directly obtain Q from bacterial sources. The study of queuosine has been challenging due to the limited availability of high-throughput methods for its detection and analysis. Here, we have employed direct RNA sequencing using nanopore technology to detect the modification of tRNAs with Q and Q precursors. These modifications were detected with high accuracy on synthetic tRNAs as well as on tRNAs extracted from Schizosaccharomyces pombe and Escherichia coli by comparing unmodified to modified tRNAs using the tool JACUSA2. Furthermore, we present an improved protocol for the alignment of raw sequence reads that gives high specificity and recall for tRNAs ex cellulo that, by nature, carry multiple modifications. Altogether, our results show that 7-deazaguanine-derivatives such as queuosine are readily detectable using direct RNA sequencing. This advancement opens up new possibilities for investigating these modifications in native tRNAs, furthering our understanding of their biological function.