Intramolecular circularization increases efficiency of RNA sequencing and enables CLIP-Seq of nuclear RNA from human cells

Advances in methods for tRNA sequencing and quantification

In the past decade tRNA sequencing (tRNA-seq) has attracted considerable attention as an important tool for the development of novel approaches to quantify highly modified tRNA species and to propel tRNA research aimed at understanding the cellular physiology and disease and development of tRNA-based therapeutics. Many methods are available to quantify tRNA abundance while accounting for modifications and tRNA charging/acylation. Advances in both library preparation methods and bioinformatic workflows have enabled developments in next-generation sequencing (NGS) workflows. Other approaches forgo NGS applications in favor of hybridization-based approaches. In this review we provide a brief comparative overview of various tRNA quantification approaches, focusing on the advantages and disadvantages of these methods, which together facilitate reliable tRNA quantification.

Text summarization based on multi-head self-attention mechanism and pointer network

Existing text summarization methods mainly rely on the mapping between manually labeled standard summaries and the original text for feature extraction, often ignoring the internal structure and semantic feature information of the original document. Therefore, the text summary extracted by the existing model has the problems of grammatical structure errors and semantic deviation from the original text. This paper attempts to enhance the model’s attention to the inherent feature information of the source text so that the model can more accurately identify the grammatical structure and semantic information of the document. Therefore, this paper proposes a model based on the multi-head self-attention mechanism and the soft attention mechanism. By introducing an improved multi-head self-attention mechanism in the model coding stage, the training model enables the correct summary syntax and semantic information to obtain higher weight, thereby making the generated summary more coherent and accurate. At the same time, the pointer network model is adopted, and the coverage mechanism is improved to solve out-of-vocabulary and repetitive problems when generating abstracts. This article uses CNN/DailyMail dataset to verify the model proposed in this article and uses the ROUGE indicator to evaluate the model. The experimental results show that the model in this article improves the quality of the generated summary compared with other models.

Quantitative mapping of the cellular small RNA landscape with AQRNA-seq

Current next-generation RNA sequencing methods do not provide accurate quantification of small RNAs within a sample due to sequence-dependent biases in capture, ligation, and amplification during library preparation. We present a method, Absolute Quantification (AQ) RNA-seq, that minimizes biases and provides a direct, linear correlation between sequencing read count and copy number for all small RNAs in a sample. Library preparation and data processing were optimized and validated using a 963-member miRNA reference library, oligonucleotide standards of varying lengths, and northern blots. Application of AQRNA-seq to a panel of human cancer cells revealed >800 detectable miRNAs that varied during cancer progression, while application to bacterial tRNA pools, with the challenges of secondary structure and abundant modifications, revealed 80-fold variation in tRNA isoacceptor levels, stress-induced site-specific tRNA fragmentation, quantitative modification maps, and evidence for stress-induced tRNA-driven codon-biased translation. AQRNA-seq thus provides a versatile means to quantitatively map the small RNA landscape in cells.

Investigating Mitochondrial Transcriptomes and RNA Processing Using Circular RNA Sequencing

Transcriptomic technologies have revolutionized the study of gene expression and RNA biology. Different RNA sequencing methods enable the analyses of diverse species of transcripts, including their abundance, processing, stability, and other specific features. Mitochondrial transcriptomics has benefited from these technologies that have revealed the surprising complexity of its RNAs. Here we describe a method based upon cyclization of mitochondrial RNAs and next generation sequencing to analyze the steady-state levels and sizes of mitochondrial RNAs, their degradation products, as well as their processing intermediates by capturing both 5' and 3' ends of transcripts.

Simultaneous processing and degradation of mitochondrial RNAs revealed by circularized RNA sequencing

Mammalian mitochondrial RNAs are unique as they are derived from primary transcripts that encompass almost the entire mitochondrial genome. This necessitates extensive processing to release the individual mRNAs, rRNAs and tRNAs required for gene expression. Recent studies have revealed many of the proteins required for mitochondrial RNA processing, however the rapid turnover of precursor RNAs has made it impossible to analyze their composition and the hierarchy of processing. Here, we find that circularization of RNA prior to deep sequencing enables the discovery and characterization of unprocessed RNAs. Using this approach, we identify the most stable processing intermediates and the presence of intermediate processing products that are partially degraded and polyadenylated. Analysis of libraries constructed using RNA from mice lacking the nuclease subunit of the mitochondrial RNase P reveals the identities of stalled processing intermediates, their order of cleavage, and confirms the importance of RNase P in generating mature mitochondrial RNAs. Using RNA circularization prior to library preparation should provide a generally useful approach to studying RNA processing in many different biological systems.

Argonaute proteins regulate HIV-1 multiply spliced RNA and viral production in a Dicer independent manner

Argonaute (Ago) proteins associate with microRNAs (miRNAs) to form the core of the RNA-induced silencing complex (RISC) that mediates post-transcriptional gene silencing of target mRNAs. As key players in anti-viral defense, Ago proteins are thought to have the ability to interact with human immunodeficiency virus type 1 (HIV-1) RNA. However, the role of this interaction in regulating HIV-1 replication has been debated. Here, we used high throughput sequencing of RNA isolated by cross-linking immunoprecipitation (HITS-CLIP) to explore the interaction between Ago2 and HIV-1 RNA in infected cells. By only considering reads of 50 nucleotides length in our analysis, we identified more than 30 distinct binding sites for Ago2 along the viral RNA genome. Using reporter assays, we found four binding sites, located near splice donor sites, capable of repressing Luciferase gene expression in an Ago-dependent manner. Furthermore, inhibition of Ago1 and Ago2 levels in cells expressing HIV-1 led to an increase of viral multiply spliced transcripts and to a strong reduction in the extracellular CAp24 level. Depletion of Dicer did not affect these activities. Our results highlight a new role of Ago proteins in the control of multiply spliced HIV-1 transcript levels and viral production, independently of the miRNA pathway.

Stable association of RNAi machinery is conserved between the cytoplasm and nucleus of human cells

Argonaute 2 (AGO2), the catalytic engine of RNAi, is typically associated with inhibition of translation in the cytoplasm. AGO2 has also been implicated in nuclear processes including transcription and splicing. There has been little insight into AGO2's nuclear interactions or how they might differ relative to cytoplasm. Here we investigate the interactions of cytoplasmic and nuclear AGO2 using semi-quantitative mass spectrometry. Mass spectrometry often reveals long lists of candidate proteins, complicating efforts to rigorously discriminate true interacting partners from artifacts. We prioritized candidates using orthogonal analytical strategies that compare replicate mass spectra of proteins associated with Flag-tagged and endogenous AGO2. Interactions with TRNC6A, TRNC6B, TNRC6C, and AGO3 are conserved between nuclei and cytoplasm. TAR binding protein interacted stably with cytoplasmic AGO2 but not nuclear AGO2, consistent with strand loading in the cytoplasm. Our data suggest that interactions between functionally important components of RNAi machinery are conserved between the nucleus and cytoplasm but that accessory proteins differ. Orthogonal analysis of mass spectra is a powerful approach to streamlining identification of protein partners.

Regulation of mammalian transcription and splicing by Nuclear RNAi

RNA interference (RNAi) is well known as a mechanism for controlling mammalian mRNA translation in the cytoplasm, but what would be the consequences if it also functions in cell nuclei? Although RNAi has also been found in nuclei of plants, yeast, and other organisms, there has been relatively little progress towards understanding the potential involvement of mammalian RNAi factors in nuclear processes including transcription and splicing. This review summarizes evidence for mammalian RNAi factors in cell nuclei and mechanisms that might contribute to the control of gene expression. When RNAi factors bind small RNAs, they form ribonucleoprotein complexes that can be selective for target sequences within different classes of nuclear RNA substrates. The versatility of nuclear RNAi may supply a previously underappreciated layer of regulation to transcription, splicing, and other nuclear processes.

CLIPSeqTools--a novel bioinformatics CLIP-seq analysis suite

Immunoprecipitation of RNA binding proteins (RBPs) after in vivo crosslinking, coupled with sequencing of associated RNA footprints (HITS-CLIP, CLIP-seq), is a method of choice for the identification of RNA targets and binding sites for RBPs. Compared with RNA-seq, CLIP-seq analysis is widely diverse and depending on the RBPs that are analyzed, the approaches vary significantly, necessitating the development of flexible and efficient informatics tools. In this study, we present CLIPSeqTools, a novel, highly flexible computational suite that can perform analysis from raw sequencing data with minimal user input. It contains a wide array of tools to provide an in-depth view of CLIP-seq data sets. It supports extensive customization and promotes improvization, a critical virtue, since CLIP-seq analysis is rarely well defined a priori. To highlight CLIPSeqTools capabilities, we used the suite to analyze Ago-miRNA HITS-CLIP data sets that we prepared from human brains.

RNA polymerase II pausing as a context-dependent reader of the genome

The RNA polymerase II (Pol II) transcribes all mRNA genes in eukaryotes and is among the most highly regulated enzymes in the cell. The classic model of mRNA gene regulation involves recruitment of the RNA polymerase to gene promoters in response to environmental signals. Higher eukaryotes have an additional ability to generate multiple cell types. This extra level of regulation enables each cell to interpret the same genome by committing to one of the many possible transcription programs and executing it in a precise and robust manner. Whereas multiple mechanisms are implicated in cell type-specific transcriptional regulation, how one genome can give rise to distinct transcriptional programs and what mechanisms activate and maintain the appropriate program in each cell remains unclear. This review focuses on the process of promoter-proximal Pol II pausing during early transcription elongation as a key step in context-dependent interpretation of the metazoan genome. We highlight aspects of promoter-proximal Pol II pausing, including its interplay with epigenetic mechanisms, that may enable cell type-specific regulation, and emphasize some of the pertinent questions that remain unanswered and open for investigation.

Design and bioinformatics analysis of genome-wide CLIP experiments

The past decades have witnessed a surge of discoveries revealing RNA regulation as a central player in cellular processes. RNAs are regulated by RNA-binding proteins (RBPs) at all post-transcriptional stages, including splicing, transportation, stabilization and translation. Defects in the functions of these RBPs underlie a broad spectrum of human pathologies. Systematic identification of RBP functional targets is among the key biomedical research questions and provides a new direction for drug discovery. The advent of cross-linking immunoprecipitation coupled with high-throughput sequencing (genome-wide CLIP) technology has recently enabled the investigation of genome-wide RBP–RNA binding at single base-pair resolution. This technology has evolved through the development of three distinct versions: HITS-CLIP, PAR-CLIP and iCLIP. Meanwhile, numerous bioinformatics pipelines for handling the genome-wide CLIP data have also been developed. In this review, we discuss the genome-wide CLIP technology and focus on bioinformatics analysis. Specifically, we compare the strengths and weaknesses, as well as the scopes, of various bioinformatics tools. To assist readers in choosing optimal procedures for their analysis, we also review experimental design and procedures that affect bioinformatics analyses.