Nuclease-mediated depletion biases in ribosome footprint profiling libraries

Detecting ribosome collisions with differential rRNA fragment analysis in ribosome profiling data

It has become clear in recent years that ribosomes regularly stall during translation. Such translation impairment has many causes, including exposure to ribotoxic stress agents, the presence of specific RNA structures or sequences, or a shortage of amino acids or translation factors. If they are not resolved, stalled ribosomes can lead to ribosome collisions that are continuously surveilled by various sensor proteins. This in turn initiates a cascade of signalling events that can change the physiology and behaviour of cells. However, measuring changes in collision abundance has proved challenging, and as a result, the importance of collision-mediated biological responses is still unclear. Here, we show that computational analyses of standard ribosome profiling (Ribo-seq) data enable the prediction of changes in ribosome collisions between conditions. This is achieved by using the known 3D structure of collided ribosomes to define the ribosomal RNA (rRNA) positions that are differentially digested by RNases during the Ribo-seq protocol. Comparison of the relative rRNA reads at these positions allows the relative quantification of collisions between samples, an approach we call differential ribosome collisions by Analysis of rRNA Fragments (dricARF). When applied to public datasets across multiple organisms, our approach detects changes in collision events with unprecedented accuracy and sensitivity. In addition to providing supplementary evidence for ribosome collisions, our tool has the potential to uncover novel biological processes that are mediated by them. dricARF is available as part of the ARF R package and can be accessed through https://github.com/fallerlab/ARF.

Advances in ribosome profiling technologies

Ribosome profiling (or Ribo-seq) has emerged as a powerful approach for revealing the regulatory mechanisms of protein synthesis, on the basis of deep sequencing of ribosome footprints. Recent innovations in Ribo-seq technologies have significantly enhanced their sensitivity, specificity, and resolution. In this review, we outline emerging Ribo-seq derivatives that overcome barriers in low inputs, rRNA contamination, data calibration, and single-cell applications. These advances enable detailed insights into translational control across diverse biological contexts.

Regulation of translation elongation and integrated stress response in heat-shocked neurons

Neurons deviate from a canonical heat shock response (HSR). Here, we revealed that neuronal adaptation to heat shock accompanies a brake on mRNA translation, slowed elongating ribosomes, phosphorylation of eukaryotic elongation factor-2 (p-eEF2), and suppressed the integrated stress response (ISR). Returning neurons to control temperature within 1 h of starting heat shock was necessary for survival and allowed for restored translation following dephosphorylation of eEF2. Subsequent to recovery, neurons briefly activated the ISR and were sensitive to the ISR inhibitor ISRIB, which enhanced protein synthesis and survival. Ribosome profiling and RNA sequencing (RNA-seq) identified newly synthesized and existing transcripts associated with ribosomes during heat shock. Preservation of these transcripts for translation during recovery was in part mediated by p-eEF2 and slowed ribosomes. Our work supports a neuronal heat shock model of a partially suspended state of translation poised for rapid reversal if recovery becomes an option and provides insight into regulation between the HSR and the ISR.

RNA-seq reproducibility of Pseudomonas aeruginosa in laboratory models of cystic fibrosis

Reproducibility is a fundamental expectation in science and enables investigators to have confidence in their research findings and the ability to compare data from disparate sources, but evaluating reproducibility can be elusive. For example, generating RNA sequencing (RNA-seq) data includes multiple steps where variance can be introduced. Thus, it is unclear if RNA-seq data from different sources can be validly compared. While most studies on RNA-seq reproducibility focus on eukaryotes, we evaluate bias in bacteria using Pseudomonas aeruginosa gene expression data from five laboratory models of cystic fibrosis. We leverage a large data set that includes samples prepared in three different laboratories and paired data sets where the same sample was sequenced using at least two different sequencing pipelines. We report here that expression data are highly reproducible across laboratories. In addition, while samples sequenced with different sequencing pipelines showed significantly more variance in expression profiles than between labs, gene expression was still highly reproducible between sequencing pipelines. Further investigation of expression differences between two sequencing pipelines revealed that library preparation methods were the largest source of error, though analyses to identify the source of this variance were inconclusive. Consistent with the reproducibility of expression between sequencing pipelines, we found that different pipelines detected over 80% of the same differentially expressed genes with large expression differences between conditions. Thus, bacterial RNA-seq data from different sources can be validly compared, facilitating the ability to advance understanding of bacterial behavior and physiology using the wide array of publicly available RNA-seq data sets.IMPORTANCERNA sequencing (RNA-seq) has revolutionized biology, but many steps in RNA-seq workflows can introduce variance, potentially compromising reproducibility. While reproducibility in RNA-seq has been thoroughly investigated in eukaryotes, less is known about pipelines and workflows that introduce variance and biases in bacterial RNA-seq data. By leveraging Pseudomonas aeruginosa transcriptomes in cystic fibrosis models from different laboratories and sequenced with different sequencing pipelines, we directly assess sources of bacterial RNA-seq variance. RNA-seq data were highly reproducible, with the largest variance due to sequencing pipelines, specifically library preparation. Different sequencing pipelines detected overlapping differentially expressed genes, especially those with large expression differences between conditions. This study confirms that different approaches to preparing and sequencing bacterial RNA libraries capture comparable transcriptional profiles, supporting investigators' ability to leverage diverse RNA-seq data sets to advance their science.

Optimization of ribosome profiling in plants including structural analysis of rRNA fragments

BACKGROUND

Ribosome profiling (or Ribo-seq) is a technique that provides genome-wide information on the translational landscape (translatome). Across different plant studies, variable methodological setups have been described which raises questions about the general comparability of data that were generated from diverging methodologies. Furthermore, a common problem when performing Ribo-seq are abundant rRNA fragments that are wastefully incorporated into the libraries and dramatically reduce sequencing depth. To remove these rRNA contaminants, it is common to perform preliminary trials to identify these fragments because they are thought to vary depending on nuclease treatment, tissue source, and plant species.

RESULTS

Here, we compile valuable insights gathered over years of generating Ribo-seq datasets from different species and experimental setups. We highlight which technical steps are important for maintaining cross experiment comparability and describe a highly efficient approach for rRNA removal. Furthermore, we provide evidence that many rRNA fragments are structurally preserved over diverse nuclease regimes, as well as across plant species. Using a recently published cryo-electron microscopy (cryo-EM) structure of the tobacco 80S ribosome, we show that the most abundant rRNA fragments are spatially derived from the solvent-exposed surface of the ribosome.

CONCLUSION

The guidelines presented here shall aid newcomers in establishing ribosome profiling in new plant species and provide insights that will help in customizing the methodology for individual research goals.

Calibrated ribosome profiling assesses the dynamics of ribosomal flux on transcripts

Ribosome profiling, which is based on deep sequencing of ribosome footprints, has served as a powerful tool for elucidating the regulatory mechanism of protein synthesis. However, the current method has substantial issues: contamination by rRNAs and the lack of appropriate methods to measure ribosome numbers in transcripts. Here, we overcome these hurdles through the development of "Ribo-FilterOut", which is based on the separation of footprints from ribosome subunits by ultrafiltration, and "Ribo-Calibration", which relies on external spike-ins of stoichiometrically defined mRNA-ribosome complexes. A combination of these approaches estimates the number of ribosomes on a transcript, the translation initiation rate, and the overall number of translation events before its decay, all in a genome-wide manner. Moreover, our method reveals the allocation of ribosomes under heat shock stress, during aging, and across cell types. Our strategy of modified ribosome profiling measures kinetic and stoichiometric parameters of cellular translation across the transcriptome.

Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

RIP-PEN-seq identifies a class of kink-turn RNAs as splicing regulators

A kink-turn (K-turn) is a three-dimensional RNA structure that exists in all three primary phylogenetic domains. In this study, we developed the RIP-PEN-seq method to identify the full-length sequences of RNAs bound by the K-turn binding protein 15.5K and discovered a previously uncharacterized class of RNAs with backward K-turn motifs (bktRNAs) in humans and mice. All bktRNAs share two consensus sequence motifs at their fixed terminal position and have complex folding properties, expression and evolution patterns. We found that a highly conserved bktRNA1 guides the methyltransferase fibrillarin to install RNA methylation of U12 small nuclear RNA in humans. Depletion of bktRNA1 causes global splicing dysregulation of U12-type introns by impairing the recruitment of ZCRB1 to the minor spliceosome. Most bktRNAs regulate the splicing of local introns by interacting with the 15.5K protein. Taken together, our findings characterize a class of small RNAs and uncover another layer of gene expression regulation that involves crosstalk among bktRNAs, RNA splicing and RNA methylation.

Principles, challenges, and advances in ribosome profiling: from bulk to low-input and single-cell analysis

Ribosome profiling has revolutionized our understanding of gene expression regulation by providing a snapshot of global translation in vivo. This powerful technique enables the investigation of the dynamics of translation initiation, elongation, and termination, and has provided insights into the regulation of protein synthesis under various conditions. Despite its widespread adoption, challenges persist in obtaining high-quality ribosome profiling data. In this review, we discuss the fundamental principles of ribosome profiling and related methodologies, including selective ribosome profiling and translation complex profiling. We also delve into quality control to assess the reliability of ribosome profiling datasets, and the efforts to improve data quality by modifying the standard procedures. Additionally, we highlight recent advancements in ribosome profiling that enable the transition from bulk to low-input and single-cell applications. Single-cell ribosome profiling has emerged as a crucial tool for exploring translation heterogeneity within specific cell populations. However, the challenges of capturing mRNAs efficiently and the sparse nature of footprint reads in single-cell ribosome profiling present ongoing obstacles. The need to refine ribosome profiling techniques remains, especially when used at the single-cell level.

A rapid protocol for ribosome profiling of low input samples

Ribosome profiling provides quantitative, comprehensive, and high-resolution snapshots of cellular translation by the high-throughput sequencing of short mRNA fragments that are protected by ribosomes from nucleolytic digestion. While the overall principle is simple, the workflow of ribosome profiling experiments is complex and challenging, and typically requires large amounts of sample, limiting its broad applicability. Here, we present a new protocol for ultra-rapid ribosome profiling from low-input samples. It features a robust strategy for sequencing library preparation within one day that employs solid phase purification of reaction intermediates, allowing to reduce the input to as little as 0.1 pmol of ∼30 nt RNA fragments. Hence, it is particularly suited for the analyses of small samples or targeted ribosome profiling. Its high sensitivity and its ease of implementation will foster the generation of higher quality data from small samples, which opens new opportunities in applying ribosome profiling.

Led-Seq: ligation-enhanced double-end sequence-based structure analysis of RNA

Structural analysis of RNA is an important and versatile tool to investigate the function of this type of molecules in the cell as well as in vitro. Several robust and reliable procedures are available, relying on chemical modification inducing RT stops or nucleotide misincorporations during reverse transcription. Others are based on cleavage reactions and RT stop signals. However, these methods address only one side of the RT stop or misincorporation position. Here, we describe Led-Seq, a new approach based on lead-induced cleavage of unpaired RNA positions, where both resulting cleavage products are investigated. The RNA fragments carrying 2', 3'-cyclic phosphate or 5'-OH ends are selectively ligated to oligonucleotide adapters by specific RNA ligases. In a deep sequencing analysis, the cleavage sites are identified as ligation positions, avoiding possible false positive signals based on premature RT stops. With a benchmark set of transcripts in Escherichia coli, we show that Led-Seq is an improved and reliable approach based on metal ion-induced phosphodiester hydrolysis to investigate RNA structures in vivo.

Translation Rescue by Targeting Ppp1r15a through Its Upstream Open Reading Frame in Sepsis-Induced Acute Kidney Injury in a Murine Model

BACKGROUND

Translation shutdown is a hallmark of late-phase, sepsis-induced kidney injury. Methods for controlling protein synthesis in the kidney are limited. Reversing translation shutdown requires dephosphorylation of the eukaryotic initiation factor 2 (eIF2) subunit eIF2 α ; this is mediated by a key regulatory molecule, protein phosphatase 1 regulatory subunit 15A (Ppp1r15a), also known as GADD34.

METHODS

To study protein synthesis in the kidney in a murine endotoxemia model and investigate the feasibility of translation control in vivo by boosting the protein expression of Ppp1r15a, we combined multiple tools, including ribosome profiling (Ribo-seq), proteomics, polyribosome profiling, and antisense oligonucleotides, and a newly generated Ppp1r15a knock-in mouse model and multiple mutant cell lines.

RESULTS

We report that translation shutdown in established sepsis-induced kidney injury is brought about by excessive eIF2 α phosphorylation and sustained by blunted expression of the counter-regulatory phosphatase Ppp1r15a. We determined the blunted Ppp1r15a expression persists because of the presence of an upstream open reading frame (uORF). Overcoming this barrier with genetic and antisense oligonucleotide approaches enabled the overexpression of Ppp1r15a, which salvaged translation and improved kidney function in an endotoxemia model. Loss of this uORF also had broad effects on the composition and phosphorylation status of the immunopeptidome-peptides associated with the MHC-that extended beyond the eIF2 α axis.

CONCLUSIONS

We found Ppp1r15a is translationally repressed during late-phase sepsis because of the existence of an uORF, which is a prime therapeutic candidate for this strategic rescue of translation in late-phase sepsis. The ability to accurately control translation dynamics during sepsis may offer new paths for the development of therapies at codon-level precision.

PODCAST

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A custom library construction method for super-resolution ribosome profiling in Arabidopsis

BACKGROUND

Ribosome profiling, also known as Ribo-seq, is a powerful technique to study genome-wide mRNA translation. It reveals the precise positions and quantification of ribosomes on mRNAs through deep sequencing of ribosome footprints. We previously optimized the resolution of this technique in plants. However, several key reagents in our original method have been discontinued, and thus, there is an urgent need to establish an alternative protocol.

RESULTS

Here we describe a step-by-step protocol that combines our optimized ribosome footprinting in plants with available custom library construction methods established in yeast and bacteria. We tested this protocol in 7-day-old Arabidopsis seedlings and evaluated the quality of the sequencing data regarding ribosome footprint length, mapped genomic features, and the periodic properties corresponding to actively translating ribosomes through open resource bioinformatic tools. We successfully generated high-quality Ribo-seq data comparable with our original method.

CONCLUSIONS

We established a custom library construction method for super-resolution Ribo-seq in Arabidopsis. The experimental protocol and bioinformatic pipeline should be readily applicable to other plant tissues and species.

Short open reading frame genes in innate immunity: from discovery to characterization

Next-generation sequencing (NGS) technologies have greatly expanded the size of the known transcriptome. Many newly discovered transcripts are classified as long noncoding RNAs (lncRNAs) which are assumed to affect phenotype through sequence and structure and not via translated protein products despite the vast majority of them harboring short open reading frames (sORFs). Recent advances have demonstrated that the noncoding designation is incorrect in many cases and that sORF-encoded peptides (SEPs) translated from these transcripts are important contributors to diverse biological processes. Interest in SEPs is at an early stage and there is evidence for the existence of thousands of SEPs that are yet unstudied. We hope to pique interest in investigating this unexplored proteome by providing a discussion of SEP characterization generally and describing specific discoveries in innate immunity.

Identifying ribosome heterogeneity using ribosome profiling

Recent studies have revealed multiple mechanisms that can lead to heterogeneity in ribosomal composition. This heterogeneity can lead to preferential translation of specific panels of mRNAs, and is defined in large part by the ribosomal protein (RP) content, amongst other things. However, it is currently unknown to what extent ribosomal composition is heterogeneous across tissues, which is compounded by a lack of tools available to study it. Here we present dripARF, a method for detecting differential RP incorporation into the ribosome using Ribosome Profiling (Ribo-seq) data. We combine the 'waste' rRNA fragment data generated in Ribo-seq with the known 3D structure of the human ribosome to predict differences in the composition of ribosomes in the material being studied. We have validated this approach using publicly available data, and have revealed a potential role for eS25/RPS25 in development. Our results indicate that ribosome heterogeneity can be detected in Ribo-seq data, providing a new method to study this phenomenon. Furthermore, with dripARF, previously published Ribo-seq data provides a wealth of new information, allowing the identification of RPs of interest in many disease and normal contexts. dripARF is available as part of the ARF R package and can be accessed through https://github.com/fallerlab/ARF.

Comparison of rRNA depletion methods for efficient bacterial mRNA sequencing

Current methods of high-throughput RNA sequencing of prokaryotes, including transcriptome analysis or ribosomal profiling, need deep sequencing to achieve sufficient numbers of effective reads (e.g., mapping to mRNA) in order to also find weakly expressed genetic elements. The fraction of high-quality reads mapping to coding RNAs (i.e., mRNA) is mainly influenced by the large content of rRNA and, to a lesser extent, tRNA in total RNA. Thus, depletion of rRNA increases coverage and thus sequencing costs. RiboZero, a depletion kit based on probe hybridisation and rRNA-removal was found to be most efficient in the past, but it was discontinued in 2018. To facilitate comparability with previous experiments and to help choose adequate replacements, we compare three commercially available rRNA depletion kits also based on hybridization and magnetic beads, i.e., riboPOOLs, RiboMinus and MICROBExpress, with the former RiboZero. Additionally, we constructed biotinylated probes for magnetic bead capture and rRNA depletion in this study. Based on E. coli, we found similar efficiencies in rRNA depletion for riboPOOLs and the self-made depletion method; both comparable to the former RiboZero, followed by RiboMinus, succeeded by MICROBExpress. Further, our in-house protocol allows customized species-specific rRNA or even tRNA depletion or depletion of other RNA targets. Both, the self-made biotinylated probes and riboPOOLs, were most successful in reducing the rRNA content and thereby increasing sequencing depth concerning mRNA reads. Additionally, the number of reads matching to weakly expressed genes are increased. In conclusion, the self-made specific biotinylated probes and riboPOOLs are an adequate replacement for the former RiboZero. Both are very efficient in depleting rRNAs, increasing mRNA reads and thus sequencing efficiency.

Identifying Small Open Reading Frames in Prokaryotes with Ribosome Profiling

Small proteins encoded by open reading frames (ORFs) shorter than 50 codons (small ORFs [sORFs]) are often overlooked by annotation engines and are difficult to characterize using traditional biochemical techniques. Ribosome profiling has tremendous potential to empirically improve the annotations of prokaryotic genomes. Recent improvements in ribosome profiling methods for bacterial model organisms have revealed many new sORFs in well-characterized genomes. Antibiotics that trap ribosomes just after initiation have played a key role in these developments by allowing the unambiguous identification of the start codons (and, hence, the reading frame) for novel ORFs. Here, we describe these new methods and highlight critical controls and considerations for adapting ribosome profiling to different prokaryotic species.

Exploring Ribosome-Positioning on Translating Transcripts with Ribosome Profiling

The emergence of ribosome profiling as a tool for measuring the translatome has provided researchers with valuable insights into the post-transcriptional regulation of gene expression. Despite the biological insights and technical improvements made since the technique was initially described by Ingolia et al. (Science 324(5924):218-223, 2009), ribosome profiling measurements and subsequent data analysis remain challenging. Here, we describe our lab's protocol for performing ribosome profiling in bacteria, yeast, and mammalian cells. This protocol has integrated elements from three published ribosome profiling methods. In addition, we describe a tool called RiboViz (Carja et al., BMC Bioinformatics 18:461, 2017) ( https://github.com/riboviz/riboviz ) for the analysis and visualization of ribosome profiling data. Given raw sequencing reads and transcriptome information (e.g., FASTA, GFF) for a species, RiboViz performs the necessary pre-processing and mapping of the raw sequencing reads. RiboViz also provides the user with various quality control visualizations.

Conversion of Ribosome-Protected mRNA to DNA and Deep Sequencing for Ribosome Profiling in Haloferax volcanii

The translation of messenger RNA (mRNA) into protein is an essential process for all forms of life. The ability to monitor this process in a quantitative way by ribosome profiling-based approaches has revolutionized our ability to monitor protein synthesis in vivo and to explore and model complex cellular processes. Ribosome profiling is a high-throughput technique that globally analyzes the full set of ribosomes engaged in translation, providing insights into important aspects of the mechanism of protein synthesis and its regulation. This protocol covers the construction of a ribosome profiling library from culture harvesting, footprint isolation via ultracentrifugation, gel-based size fractionation, and footprint sequencing for a model halophilic archaeon, Haloferax volcanii. This approach has revealed the first global view of translation in the archaea.

High-Resolution Ribosome Profiling for Determining Ribosome Functional States During Translation Elongation

Translation elongation is a highly choreographed process that involves substantial conformational changes of the ribosome to accommodate aminoacyl-tRNAs and traverse along the mRNA template. To capture distinct functional states of the ribosome, a high-resolution ribosome profiling-based approach has been developed. By deep-sequencing differently sized ribosome-protected mRNA fragments, this approach captures not only ribosome positions but also their functional states in vivo across the Saccharomyces cerevisiae transcriptome with codon resolution. This chapter presents a condensed and step-by-step protocol for preserving ribosomes in their functional states using a cocktail of antibiotics that traps distinct steps of elongating ribosomes and for constructing a cDNA library derived from the ribosome-protected mRNA fragments for deep sequencing.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

Simultaneous ribosome profiling of hundreds of microbes from the human microbiome

Ribosome profiling enables sequencing of ribosome-bound fragments of RNA, revealing which transcripts are being translated as well as the position of ribosomes along mRNAs. Although ribosome profiling has been applied to cultured bacterial isolates, its application to uncultured, mixed communities has been challenging. We present MetaRibo-Seq, a protocol that enables the application of ribosome profiling directly to the human fecal microbiome. MetaRibo-Seq is a benchmarked method that includes several modifications to existing ribosome profiling protocols, specifically addressing challenges involving fecal sample storage, purity and input requirements. We also provide a computational workflow to quality control and trim reads, de novo assemble a reference metagenome with metagenomic reads, align MetaRibo-Seq reads to the reference, and assess MetaRibo-Seq library quality ( https://github.com/bhattlab/bhattlab_workflows/tree/master/metariboseq ). This MetaRibo-Seq protocol enables researchers in standard molecular biology laboratories to study translation in the fecal microbiome in ~5 d.

RiboRid: A low cost, advanced, and ultra-efficient method to remove ribosomal RNA for bacterial transcriptomics

RNA sequencing techniques have enabled the systematic elucidation of gene expression (RNA-Seq), transcription start sites (differential RNA-Seq), transcript 3′ ends (Term-Seq), and post-transcriptional processes (ribosome profiling). The main challenge of transcriptomic studies is to remove ribosomal RNAs (rRNAs), which comprise more than 90% of the total RNA in a cell. Here, we report a low-cost and robust bacterial rRNA depletion method, RiboRid, based on the enzymatic degradation of rRNA by thermostable RNase H. This method implemented experimental considerations to minimize nonspecific degradation of mRNA and is capable of depleting pre-rRNAs that often comprise a large portion of RNA, even after rRNA depletion. We demonstrated the highly efficient removal of rRNA up to a removal efficiency of 99.99% for various transcriptome studies, including RNA-Seq, Term-Seq, and ribosome profiling, with a cost of approximately $10 per sample. This method is expected to be a robust method for large-scale high-throughput bacterial transcriptomic studies.

Removal of ribosomal RNAs, a major constituent (over 90%) of cellular RNA is a critical experimental step for transcriptomic studies that deal with messenger RNAs. In this manuscript, we describe a robust method to subtract ribosomal RNA from various RNA samples. The method is based on the enzymatic degradation of target RNA by short complementary DNA and RNA:DNA duplex specific nuclease. The method comprises carefully designed experimental procedures to minimize experimental bias and unwanted removal of messenger RNAs. We validate the method on various types of transcriptomic studies for seven diverse bacterial species. This method successfully removed ribosomal RNA with over 99% of efficiency and it was comparable to commercial systems even for degraded RNA samples at a fraction of a cost.

TERA-Seq: true end-to-end sequencing of native RNA molecules for transcriptome characterization

Direct sequencing of single, native RNA molecules through nanopores has a strong potential to transform research in all aspects of RNA biology and clinical diagnostics. The existing platform from Oxford Nanopore Technologies is unable to sequence the very 5′ ends of RNAs and is limited to polyadenylated molecules. Here, we develop True End-to-end RNA Sequencing (TERA-Seq), a platform that addresses these limitations, permitting more thorough transcriptome characterization. TERA-Seq describes both poly- and non-polyadenylated RNA molecules and accurately identifies their native 5′ and 3′ ends by ligating uniquely designed adapters that are sequenced along with the transcript. We find that capped, full-length mRNAs in human cells show marked variation of poly(A) tail lengths at the single molecule level. We report prevalent capping downstream of canonical transcriptional start sites in otherwise fully spliced and polyadenylated molecules. We reveal RNA processing and decay at single molecule level and find that mRNAs decay cotranslationally, often from their 5′ ends, while frequently retaining poly(A) tails. TERA-Seq will prove useful in many applications where true end-to-end direct sequencing of single, native RNA molecules and their isoforms is desirable.

Ribo-ODDR: Oligo design pipeline for experiment-specific rRNA depletion in ribo-seq

Motivation

Ribosome Profiling (Ribo-seq) has revolutionized the study of RNA translation by providing information on ribosome positions across all translated RNAs with nucleotide-resolution. Yet several technical limitations restrict the sequencing depth of such experiments, the most common of which is the overabundance of rRNA fragments. Various strategies can be employed to tackle this issue, including the use of commercial rRNA depletion kits. However, as they are designed for more standardized RNAseq experiments, they may perform suboptimally in Ribo-seq. In order to overcome this, it is possible to use custom biotinylated oligos complementary to the most abundant rRNA fragments, however currently no computational framework exists to aid the design of optimal oligos.

Results

Here, we first show that a major confounding issue is that the rRNA fragments generated via Ribo-seq vary significantly with differing experimental conditions, suggesting that a ‘one-size-fits-all’ approach may be inefficient. Therefore we developed Ribo-ODDR, an oligo design pipeline integrated with a user-friendly interface that assists in oligo selection for efficient experiment-specific rRNA depletion. Ribo-ODDR uses preliminary data to identify the most abundant rRNA fragments, and calculates the rRNA depletion efficiency of potential oligos. We experimentally show that Ribo-ODDR designed oligos outperform commercially available kits and lead to a significant increase in rRNA depletion in Ribo-seq.

Availability and implementation

Ribo-ODDR is freely accessible at https://github.com/fallerlab/Ribo-ODDR.

Supplementary information

Supplementary data are available at Bioinformatics online.

Best practices to ensure robust investigation of circular RNAs: pitfalls and tips

Pre-mRNAs from thousands of eukaryotic genes can be non-canonically spliced to generate circular RNAs (circRNAs) that have covalently linked ends. Most mature circular RNAs are expressed at low levels, but some have known physiological functions and/or accumulate to higher levels than their associated linear mRNAs. These observations have sparked great interest into this class of previously underappreciated RNAs and prompted the development of new experimental approaches to study them, especially methods to measure or modulate circular RNA expression levels. Nonetheless, each of these approaches has caveats and potential pitfalls that must be controlled for when designing experiments and interpreting results. Here, we provide practical advice, tips, and suggested guidelines for performing robust identification, validation, and functional characterization of circular RNAs. Beyond promoting rigor and reproducibility, these suggestions should help bring clarity to the field, especially how circular RNAs function and whether these transcripts may sponge microRNAs/proteins or serve as templates for translation.

Optimized design of antisense oligomers for targeted rRNA depletion

RNA sequencing (RNA-seq) is extensively used to quantify gene expression transcriptome-wide. Although often paired with polyadenylate (poly(A)) selection to enrich for messenger RNA (mRNA), many applications require alternate approaches to counteract the high proportion of ribosomal RNA (rRNA) in total RNA. Recently, digestion using RNaseH and antisense DNA oligomers tiling target rRNAs has emerged as an alternative to commercial rRNA depletion kits. Here, we present a streamlined, more economical RNaseH-mediated rRNA depletion with substantially lower up-front costs, using shorter antisense oligos only sparsely tiled along the target RNA in a 5-min digestion reaction. We introduce a novel Web tool, Oligo-ASST, that simplifies oligo design to target regions with optimal thermodynamic properties, and additionally can generate compact, common oligo pools that simultaneously target divergent RNAs, e.g. across different species. We demonstrate the efficacy of these strategies by generating rRNA-depletion oligos for Xenopus laevis and for zebrafish, which expresses two distinct versions of rRNAs during embryogenesis. The resulting RNA-seq libraries reduce rRNA to <5% of aligned reads, on par with poly(A) selection, and also reveal expression of many non-adenylated RNA species. Oligo-ASST is freely available at https://mtleelab.pitt.edu/oligo to design antisense oligos for any taxon or to target any abundant RNA for depletion.