Selective and flexible depletion of problematic sequences from RNA-seq libraries at the cDNA stage

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.

TREX reveals proteins that bind to specific RNA regions in living cells

Different regions of RNA molecules can often engage in specific interactions with distinct RNA-binding proteins (RBPs), giving rise to diverse modalities of RNA regulation and function. However, there are currently no methods for unbiased identification of RBPs that interact with specific RNA regions in living cells and under endogenous settings. Here we introduce TREX (targeted RNase H-mediated extraction of crosslinked RBPs)-a highly sensitive approach for identifying proteins that directly bind to specific RNA regions in living cells. We demonstrate that TREX outperforms existing methods in identifying known interactors of U1 snRNA, and reveals endogenous region-specific interactors of NORAD long noncoding RNA. Using TREX, we generated a comprehensive region-by-region interactome for 45S rRNA, uncovering both established and previously unknown interactions that regulate ribosome biogenesis. With its applicability to different cell types, TREX is an RNA-centric tool for unbiased positional mapping of endogenous RNA-protein interactions in living cells.

Blocking Abundant RNA Transcripts by High-Affinity Oligonucleotides during Transcriptome Library Preparation

BACKGROUND

RNA sequencing has become the gold standard for transcriptome analysis but has an inherent limitation of challenging quantification of low-abundant transcripts. In contrast to microarray technology, RNA sequencing reads are proportionally divided in function of transcript abundance. Therefore, low-abundant RNAs compete against highly abundant - and sometimes non-informative - RNA species.

RESULTS

We developed an easy-to-use strategy based on high-affinity RNA-binding oligonucleotides to block reverse transcription and PCR amplification of specific RNA transcripts, thereby substantially reducing their abundance in the final sequencing library. To demonstrate the broad application potential of our method, we applied it to different transcripts and library preparation strategies, including YRNAs in small RNA sequencing of human blood plasma, mitochondrial rRNAs in both 3' end sequencing and long-read sequencing, and MALAT1 in single-cell 3' end sequencing. We demonstrate that the blocking strategy is highly efficient, reproducible, specific, and generally results in better transcriptome coverage and complexity.

CONCLUSION

Our method does not require modifications of the library preparation procedure apart from simply adding blocking oligonucleotides to the RT reaction and can thus be easily integrated into virtually any RNA sequencing library preparation protocol.

Next-Generation Yeast Two-Hybrid Screening to Discover Protein-Protein Interactions

Yeast two-hybrid is a powerful approach to discover new protein-protein interactions. Traditional methods involve screening a target protein against a cDNA expression library and assaying individual positive colonies to identify interacting partners. Here we describe a simple approach to perform yeast two-hybrid screens of a cDNA expression library in batch liquid culture. Positive yeast cell populations are enriched under selection and then harvested en masse. Prey cDNAs are amplified and used as input for next-generation sequencing libraries for identification, quantification, and ranking.

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.

An Easy, Cost-Effective, and Scalable Method to Deplete Human Ribosomal RNA for RNA-seq

RNA sequencing (RNA-seq) is a powerful and increasingly prevalent method to characterize and quantify the transcriptome. Ribosomes are extremely abundant, however, and approximately 80% of total RNA is ribosomal RNA (rRNA). Therefore, to detect and quantify less abundant yet biologically important transcripts such as messenger RNA (mRNA) and long noncoding RNAs (lncRNA), it is essential to minimize the rRNA being sequenced. Although commercial methods exist to deplete rRNA from total RNA samples before sequencing, they are expensive and require specific amounts of input RNA, and the most commonly used kit is no longer available as a stand-alone product. Here, we present an optimized rRNA depletion protocol using RNase H and DNA oligonucleotides complementary to human rRNA transcripts. This protocol includes guidelines for DNA oligo preparation, RNA:DNA hybridization, RNase H cleavage and RNA cleanup, and benchmarking of rRNA depletion. The method is flexible because the user can include additional complementary DNA oligos directed against any abundant transcript in their particular system. Furthermore, the performance of this rRNA depletion approach is comparable to or better than that of commercial kits, at a fraction of the cost and across a wide range of input RNA amounts. © 2021 Wiley Periodicals LLC. Basic Protocol: Specific depletion of rRNA transcripts from human total RNA Support Protocol: Preparation of the rRNA depletion DNA oligonucleotide pool.

High-throughput 5'P sequencing enables the study of degradation-associated ribosome stalls

RNA degradation is critical for gene expression and mRNA quality control. mRNA degradation is connected to the translation process up to the degree that 5'-3' mRNA degradation follows the last translating ribosome. Here, we present an improved high-throughput 5'P degradome RNA-sequencing method (HT-5Pseq). HT-5Pseq is easy, scalable, and uses affordable duplex-specific nuclease-based rRNA depletion. We investigate in vivo ribosome stalls focusing on translation termination. By comparing ribosome stalls identified by ribosome profiling, disome-seq and HT-5Pseq, we find that degradation-associated ribosome stalls are often enriched in Arg preceding the stop codon. On the contrary, mRNAs depleted for those stalls use more frequently a TAA stop codon preceded by hydrophobic amino acids. Finally, we show that termination stalls found by HT-5Pseq, and not by other approaches, are associated with decreased mRNA stability. Our work suggests that ribosome stalls associated with mRNA decay can be easily captured by investigating the 5'P degradome.

High Throughput Sequencing for the Detection and Characterization of RNA Viruses

This review aims to assess and recommend approaches for targeted and agnostic High Throughput Sequencing of RNA viruses in a variety of sample matrices. HTS also referred to as deep sequencing, next generation sequencing and third generation sequencing; has much to offer to the field of environmental virology as its increased sequencing depth circumvents issues with cloning environmental isolates for Sanger sequencing. That said however, it is important to consider the challenges and biases that method choice can impart to sequencing results. Here, methodology choices from RNA extraction, reverse transcription to library preparation are compared based on their impact on the detection or characterization of RNA viruses.

Organism-specific depletion of highly abundant RNA species from bacterial total RNA

High-throughput sequencing has become a standard tool for transcriptome analysis. The depletion of overrepresented RNA species from sequencing libraries plays a key role in establishing potent and cost-efficient RNA-seq routines. Commercially available kits are known to obtain good results for the reduction of ribosomal RNA (rRNA). However, we found that the transfer-messenger RNA (tmRNA) was frequently highly abundant in rRNA-depleted samples of Pseudomonas aeruginosa, consuming up to 25 % of the obtained reads. The tmRNA fraction was particularly high in samples taken from stationary cultures. This suggests that overrepresentation of this RNA species reduces the mRNA fraction when cells are grown under challenging conditions. Here, we present an RNase-H-based depletion protocol that targets the tmRNA in addition to ribosomal RNAs. We were able to increase the mRNA fraction to 93–99% and therefore outperform not only the commercially Ribo-off kit (Vazyme) operating by the same principle but also the formerly widely used Ribo-Zero kit (Illumina). Maximizing the read share of scientifically interesting RNA species enhances the discriminatory potential of next-generation RNA-seq experiments and, therefore, can contribute to a better understanding of the transcriptomic landscape of bacterial pathogens and their used mechanisms in host infection.

Nuclease-mediated depletion biases in ribosome footprint profiling libraries

Ribosome footprint profiling is a high-throughput sequencing-based technique that provides detailed and global views of translation in living cells. An essential part of this technology is removal of unwanted, normally very abundant, ribosomal RNA sequences that dominate libraries and increase sequencing costs. The most effective commercial solution (Ribo-Zero) has been discontinued as a standalone product and a number of new, experimentally distinct commercial applications have emerged on the market. Here we evaluated several commercially available alternatives designed for RNA-seq of human samples and find them generally unsuitable for ribosome footprint profiling. We instead recommend the use of custom-designed biotinylated oligos, which were widely used in early ribosome profiling studies. Importantly, we warn that depletion solutions based on targeted nuclease cleavage significantly perturb the high-resolution information that can be derived from the data, and thus do not recommend their use for any applications that require precise determination of the ends of RNA fragments.

Genome-wide capture sequencing to detect hepatitis C virus at the end of antiviral therapy

Background

Viral relapse is a major concern in hepatitis C virus (HCV) antiviral therapy. Currently, there are no satisfactory methods to predict viral relapse, especially in the era of direct acting antivirals in which the virus often quickly becomes undetectable using PCR-based approaches that focus on a small viral region. Next-generation sequencing (NGS) provides an alternative option for viral detection in a genome-wide manner. However, owing to the overwhelming dominance of human genetic content in clinical specimens, direct detection of HCV by NGS has a low sensitivity and hence viral enrichment is required.

Methods

Based on template-dependent multiple displacement amplification (tdMDA), an improved method for whole genome amplification (Wang et al., 2017. Biotechniques 63, 21–27), we evaluated two strategies to enhance the sensitivity of NGS-based HCV detection: duplex-specific nuclease (DSN)-mediated depletion of human sequences and HCV probe-based capture sequencing.

Results

In DSN-mediated depletion, human sequences were significantly reduced in the two HCV serum samples tested, 65.3% → 55.6% → 33.7% (#4727) and 68.6% → 56% → 21% (#4970), respectively for no normalization, self- and driver-applied normalization. However, this approach was associated with a loss of HCV sequences perhaps due to its micro-homology with the human genome. In capture sequencing, HCV-mapped sequencing reads occupied 96.8% (#4727) and 22.14% (#4970) in NGS data, equivalent to 1936x and 7380x enrichment, respectively. Capture sequencing was then applied to ten serum samples collected at the end of HCV antiviral therapy. Interestingly, the number of HCV-mapped reads was significantly higher in relapsed patients (n = 5) than those from patients with sustained virological response (SVR) (n = 5), 102.4 ± 72.3 vs. 2.6 ± 0.55, p = 0.014.

Conclusions

Our data provides concept evidence for a highly sensitive HCV detection by capture sequencing. The abundance difference of HCV sequencing reads at the end of HCV antiviral therapy could be applied to predict treatment outcomes.

Improved bacterial RNA-seq by Cas9-based depletion of ribosomal RNA reads

A major challenge for RNA-seq analysis of gene expression is to achieve sufficient coverage of informative nonribosomal transcripts. In eukaryotic samples, this is typically achieved by selective oligo(dT)-priming of messenger RNAs to exclude ribosomal RNA (rRNA) during cDNA synthesis. However, this strategy is not compatible with prokaryotes in which functional transcripts are generally not polyadenylated. To overcome this, we adopted DASH (depletion of abundant sequences by hybridization), initially developed for eukaryotic cells, to improve both the sensitivity and depth of bacterial RNA-seq. DASH uses the Cas9 nuclease to remove unwanted cDNA sequences prior to library amplification. We report the design, evaluation, and optimization of DASH experiments for standard bacterial short-read sequencing approaches, including software for automated guide RNA (gRNA) design for Cas9-mediated cleavage in bacterial rDNA sequences. Using these gRNA pools, we effectively removed rRNA reads (56%-86%) in RNA-seq libraries from two different model bacteria, the Gram-negative pathogen Salmonella enterica and the anaerobic gut commensal Bacteroides thetaiotaomicron DASH works robustly, even with subnanogram amounts of input RNA. Its efficiency, high sensitivity, ease of implementation, and low cost (∼$5 per sample) render DASH an attractive alternative to rRNA removal protocols, in particular for material-constrained studies where conventional ribodepletion techniques fail.

A smart polymer for sequence-selective binding, pulldown, and release of DNA targets

Selective isolation of DNA is crucial for applications in biology, bionanotechnology, clinical diagnostics and forensics. We herein report a smart methanol-responsive polymer (MeRPy) that can be programmed to bind and separate single- as well as double-stranded DNA targets. Captured targets are quickly isolated and released back into solution by denaturation (sequence-agnostic) or toehold-mediated strand displacement (sequence-selective). The latter mode allows 99.8% efficient removal of unwanted sequences and 79% recovery of highly pure target sequences. We applied MeRPy for the depletion of insulin, glucagon, and transthyretin cDNA from clinical next-generation sequencing (NGS) libraries. This step improved the data quality for low-abundance transcripts in expression profiles of pancreatic tissues. Its low cost, scalability, high stability and ease of use make MeRPy suitable for diverse applications in research and clinical laboratories, including enhancement of NGS libraries, extraction of DNA from biological samples, preparative-scale DNA isolations, and sorting of DNA-labeled non-nucleic acid targets.

Evaluation of protocols for rRNA depletion-based RNA sequencing of nanogram inputs of mammalian total RNA

Next generation RNA-sequencing (RNA-seq) is a flexible approach that can be applied to a range of applications including global quantification of transcript expression, the characterization of RNA structure such as splicing patterns and profiling of expressed mutations. Many RNA-seq protocols require up to microgram levels of total RNA input amounts to generate high quality data, and thus remain impractical for the limited starting material amounts typically obtained from rare cell populations, such as those from early developmental stages or from laser micro-dissected clinical samples. Here, we present an assessment of the contemporary ribosomal RNA depletion-based protocols, and identify those that are suitable for inputs as low as 1-10 ng of intact total RNA and 100-500 ng of partially degraded RNA from formalin-fixed paraffin-embedded tissues.

Cancer transcriptome profiling at the juncture of clinical translation

Methodological breakthroughs over the past four decades have repeatedly revolutionized transcriptome profiling. Using RNA sequencing (RNA-seq), it has now become possible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples. These transcriptomes provide a link between cellular phenotypes and their molecular underpinnings, such as mutations. In the context of cancer, this link represents an opportunity to dissect the complexity and heterogeneity of tumours and to discover new biomarkers or therapeutic strategies. Here, we review the rationale, methodology and translational impact of transcriptome profiling in cancer.

Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish

Terminologies of ovary development, by somewhat subjective describing and naming main changes of oocytes, have been criticized for confusing and inconsistency of terms and classifications, and the incurred consequences impede communication among researchers. In the present work, we developed regression between ovary development and three ribosome RNA (rRNA) indexes, namely 5S rRNA percent, 18S rRNA percent, and 5S–18S rRNA ratio, using close relationship between volume percent of primary growth stage oocytes or gonadosomatic index and rRNA content, demonstrating species-specific quantification of ovary development can be established in species with either synchronous and asynchronous oogenesis. This approach may be extended to any species with primary growth oocytes, e.g. anurans and reptiles, to predict maturity stages in females. We further confirmed that 5S rRNA percent and 5S/18S rRNA ratio can serve as markers to distinguish sexes unambiguously. A micro-invasive sampling method may be invented for non-lethal prediction of ovary development and sex because only a small amount of ovary sample (<50 mg) is needed for the approach established in the current work. Researchers who work with ovary RNA-seq in these taxa should realize that insufficient depletion of rRNA will probably lead to incorrect quantification of gene expression and inaccurate conclusions.

Dynamics of ribosome scanning and recycling revealed by translation complex profiling

Regulation of messenger RNA translation is central to eukaryotic gene expression control. Regulatory inputs are specified by them RNA untranslated regions (UTRs) and often target translation initiation. Initiation involves binding of the 40S ribosomal small subunit (SSU) and associated eukaryotic initiation factors (eIFs)near the mRNA 5′ cap; the SSU then scans in the 3′ direction until it detects the start codon and is joined by the 60S ribosomal large subunit (LSU) to form the 80S ribosome. Scanning and other dynamic aspects of the initiation model have remained as conjectures because methods to trap early intermediates were lacking. Here we uncover the dynamics of the complete translation cycle in live yeast cells using translation complex profile sequencing (TCP-seq), a method developed from the ribosome profiling approach. We document scanning by observing SSU footprints along 5′ UTRs. Scanning SSU have 5′-extended footprints (up to~75 nucleotides), indicative of additional interactions with mRNA emerging from the exit channel, promoting forward movement. We visualized changes in initiation complex conformation as SSU footprints coalesced into three major sizes at start codons (19, 29 and 37 nucleotides). These share the same 5′ start site but differ at the 3′ end, reflecting successive changes at the entry channel from an open to a closed state following start codon recognition. We also observe SSU 'lingering' at stop codons after LSU departure. Our results underpin mechanistic models of translation initiation and termination, built on decades of biochemical and structural investigation, with direct genome-wide in vivo evidence. Our approach captures ribosomal complexes at all phases of translation and will aid in studying translation dynamics in diverse cellular contexts. Dysregulation of translation is common in disease and, for example, SSU scanning is a target of anti-cancer drug development. TCP-seq will prove useful in discerning differences in mRNA-specific initiation in pathologies and their response to treatment.

RNA-Seq methods for transcriptome analysis

Deep sequencing has been revolutionizing biology and medicine in recent years, providing single base-level precision for our understanding of nucleic acid sequences in high throughput fashion. Sequencing of RNA, or RNA-Seq, is now a common method to analyze gene expression and to uncover novel RNA species. Aspects of RNA biogenesis and metabolism can be interrogated with specialized methods for cDNA library preparation. In this study, we review current RNA-Seq methods for general analysis of gene expression and several specific applications, including isoform and gene fusion detection, digital gene expression profiling, targeted sequencing and single-cell analysis. In addition, we discuss approaches to examine aspects of RNA in the cell, technical challenges of existing RNA-Seq methods, and future directions. WIREs RNA 2017, 8:e1364. doi: 10.1002/wrna.1364 For further resources related to this article, please visit the WIREs website.

Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud

Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki.

Probe-Directed Degradation (PDD) for Flexible Removal of Unwanted cDNA Sequences from RNA-Seq Libraries

Most applications for RNA-seq require the depletion of abundant transcripts to gain greater coverage of the underlying transcriptome. The sequences to be targeted for depletion depend on application and species and in many cases may not be supported by commercial depletion kits. This unit describes a method for generating RNA-seq libraries that incorporates probe-directed degradation (PDD), which can deplete any unwanted sequence set, with the low-bias split-adapter method of library generation (although many other library generation methods are in principle compatible). The overall strategy is suitable for applications requiring customized sequence depletion or where faithful representation of fragment ends and lack of sequence bias is paramount. We provide guidelines to rapidly design specific probes against the target sequence, and a detailed protocol for library generation using the split-adapter method including several strategies for streamlining the technique and reducing adapter dimer content.