A comparison between ribo-minus RNA-sequencing and polyA-selected RNA-sequencing

RNA-Independent Regulatory Functions of lncRNA in Complex Disease

During the metagenomics era, high-throughput sequencing efforts both in mice and humans indicate that non-coding RNAs (ncRNAs) constitute a significant fraction of the transcribed genome. During the past decades, the regulatory role of these non-coding transcripts along with their interactions with other molecules have been extensively characterized. However, the study of long non-coding RNAs (lncRNAs), an ncRNA regulatory class with transcript lengths that exceed 200 nucleotides, revealed that certain non-coding transcripts are transcriptional "by-products", while their loci exert their downstream regulatory functions through RNA-independent mechanisms. Such mechanisms include, but are not limited to, chromatin interactions and complex promoter-enhancer competition schemes that involve the underlying ncRNA locus with or without its nascent transcription, mediating significant or even exclusive roles in the regulation of downstream target genes in mammals. Interestingly, such RNA-independent mechanisms often drive pathological manifestations, including oncogenesis. In this review, we summarize selective examples of lncRNAs that regulate target genes independently of their produced transcripts.

Role of long noncoding RNAs in diabetes-associated peripheral arterial disease

Diabetes mellitus (DM) is a metabolic disease that heightens the risks of many vascular complications, including peripheral arterial disease (PAD). Various types of cells, including but not limited to endothelial cells (ECs), vascular smooth muscle cells (VSMCs), and macrophages (MΦs), play crucial roles in the pathogenesis of DM-PAD. Long non-coding RNAs (lncRNAs) are epigenetic regulators that play important roles in cellular function, and their dysregulation in DM can contribute to PAD. This review focuses on the developing field of lncRNAs and their emerging roles in linking DM and PAD. We review the studies investigating the role of lncRNAs in crucial cellular processes contributing to DM-PAD, including those in ECs, VSMCs, and MΦ. By examining the intricate molecular landscape governed by lncRNAs in these relevant cell types, we hope to shed light on the roles of lncRNAs in EC dysfunction, inflammatory responses, and vascular remodeling contributing to DM-PAD. Additionally, we provide an overview of the research approach and methodologies, from identifying disease-relevant lncRNAs to characterizing their molecular and cellular functions in the context of DM-PAD. We also discuss the potential of leveraging lncRNAs in the diagnosis and therapeutics for DM-PAD. Collectively, this review provides a summary of lncRNA-regulated cell functions contributing to DM-PAD and highlights the translational potential of leveraging lncRNA biology to tackle this increasingly prevalent and complex disease.

RNaseH-based ribodepletion of total planarian RNA improves detection of longer and non-polyadenylated transcripts

The overwhelming majority of RNA species isolated from cells or tissues using organic extraction are ribosomal RNAs (rRNA), whereas a relatively small percentage are messenger RNAs (mRNA). For studies that seek to detect mRNA transcripts and measure changes in their expression, this lopsided ratio of desired transcripts to undesired transcripts creates a significant challenge to obtaining sensitive and reproducible results. One method for improving mRNA detection is to selectively amplify polyadenylated (polyA) mRNA molecules when generating RNA-seq libraries, a strategy that is generally very successful in many species. However, this strategy is less effective when starting with total RNA from some species e.g., the planarian species Schmidtea mediterranea (S.med), as it generates libraries that still contain significant and variable amounts of rRNA reads. Further, commercially available ribodepletion kits do not efficiently deplete rRNAs from these samples because their sequences are divergent from mammalian rRNAs. Here we report a customized, optimized, and economical ribodepletion strategy than allows the generation of comprehensive RNA-seq libraries with less than one percent rRNA contamination. We show that this method improves transcript detection, particularly for those without polyA tails (e.g., core histones) and those that are relatively long (e.g., microtubule motor proteins). Using this custom ribodepletion approach, we also detected many transcripts that are not represented in the most recent set of S.med gene annotations, including a subset that are likely expressed transposable elements (TEs). To facilitate future differential expression analyses of these newly identified loci, we created both an annotation file of the new loci we identified and a bioinformatic pipeline for generating additional annotations from future libraries. As significant recent research shows that TE activation is regulated and functionally important, the resources provided here will provide a starting point for investigating such mechanisms in planarians and other species with less conserved rRNA sequences.

Cost-Effective Whole Transcriptome Sequencing Landscape and Diagnostic Potential Biomarkers in Active Tuberculosis

Tuberculosis (TB) is a prevalent and severe infectious disease that poses a significant threat to human health. However, it is frequently disregarded as there are not enough quick and accurate ways to diagnose tuberculosis. Here, we develop a strategy for tuberculosis detection to address the challenges, including an experimental strategy, namely, Double Adapter Directional Capture sequencing (DADCSeq), an easily operated and low-cost whole transcriptome sequencing method, and a computational method to identify hub differentially expressed genes as well as the diagnosis of TB based on whole transcriptome data using DADCSeq on peripheral blood mononuclear cells (PBMCs) from active TB and latent TB or healthy control. Applying our approach to create a robust and stable TB multi-mRNA risk probability model (TBMMRP) that can accurately distinguish active and latent TB patients, including active TB and healthy controls in clinical cohorts, this diagnostic biomarker was successfully validated by several independent cross-platform cohorts with favorable performance in differentiating active TB from latent TB or active TB from healthy controls and further demonstrated superior or similar diagnostic accuracy compared to previous diagnostic markers. Overall, we develop a low-cost and effective strategy for tuberculosis diagnosis; as the clinical cohort increases, we can expand to different disease kinds and learn new features through our disease diagnosis strategy.

A single workflow for multi-species blood transcriptomics

BACKGROUND

Blood transcriptomic analysis is widely used to provide a detailed picture of a physiological state with potential outcomes for applications in diagnostics and monitoring of the immune response to vaccines. However, multi-species transcriptomic analysis is still a challenge from a technological point of view and a standardized workflow is urgently needed to allow interspecies comparisons.

RESULTS

Here, we propose a single and complete total RNA-Seq workflow to generate reliable transcriptomic data from blood samples from humans and from animals typically used in preclinical models. Blood samples from a maximum of six individuals and four different species (rabbit, non-human primate, mouse and human) were extracted and sequenced in triplicates. The workflow was evaluated using different wet-lab and dry-lab criteria, including RNA quality and quantity, the library molarity, the number of raw sequencing reads, the Phred-score quality, the GC content, the performance of ribosomal-RNA and globin depletion, the presence of residual DNA, the strandness, the percentage of coding genes, the number of genes expressed, and the presence of saturation plateau in rarefaction curves. We identified key criteria and their associated thresholds to be achieved for validating the transcriptomic workflow. In this study, we also generated an automated analysis of the transcriptomic data that streamlines the validation of the dataset generated.

CONCLUSIONS

Our study has developed an end-to-end workflow that should improve the standardization and the inter-species comparison in blood transcriptomics studies. In the context of vaccines and drug development, RNA sequencing data from preclinical models can be directly compared with clinical data and used to identify potential biomarkers of value to monitor safety and efficacy.

SCARPET: site-specific quantification of methylated and nonmethylated adenosines reveals m6A stoichiometry

m6A has different stoichiometry at different positions in different mRNAs. However, the exact stoichiometry of m6A is difficult to measure. Here, we describe SCARPET (site-specific cleavage and radioactive-labeling followed by purification, exonuclease digestion, and thin-layer chromatography), a simple and streamlined biochemical assay for quantifying m6A at any specific site in any mRNA. SCARPET involves a site-specific cleavage of mRNA immediately 5' of an adenosine site in an mRNA. This site is radiolabeled with 32P, and after a series of steps to purify the RNA and to remove nonspecific signals, the nucleotide is resolved by TLC to visualize A and m6A at this site. Quantification of these spots reveals the m6A stoichiometry at the site of interest. SCARPET can be applied to poly(A)-enriched RNA, or preferably purified mRNA, which produces more accurate m6A stoichiometry measurements. We show that sample processing steps of SCARPET can be performed in a single day, and results in a specific and accurate measurement of m6A stoichiometry at specific sites in mRNA. Using SCARPET, we measure exact m6A stoichiometries in specific mRNAs and show that Zika genomic RNA lacks m6A at previously mapped sites. SCARPET will be useful for testing specific sites for their m6A stoichiometry and to assess how m6A stoichiometry changes in different conditions and cellular contexts.

Cost and time-efficient construction of a 3'-end mRNA library from unpurified bulk RNA in a single tube

The major drawbacks of RNA sequencing (RNA-seq), a remarkably accurate transcriptome profiling method, is its high cost and poor scalability. Here, we report a highly scalable and cost-effective method for transcriptomics profiling called Bulk transcriptOme profiling of cell Lysate in a single poT (BOLT-seq), which is performed using unpurified bulk 3'-end mRNA in crude cell lysates. During BOLT-seq, RNA/DNA hybrids are directly subjected to tagmentation, and second-strand cDNA synthesis and RNA purification are omitted, allowing libraries to be constructed in 2 h of hands-on time. BOLT-seq was successfully used to cluster small molecule drugs based on their mechanisms of action and intended targets. BOLT-seq competes effectively with alternative library construction and transcriptome profiling methods.

Approaches and challenges in genome-wide circular RNA identification and quantification

Numerous circular RNAs (circRNAs) produced from back-splicing of exon(s) have been recently revealed on a genome-wide scale across species. Although generally expressed at a low level, some relatively abundant circRNAs can play regulatory roles in various biological processes, prompting continuous profiling of circRNA in broader conditions. Over the past decade, distinct strategies have been applied in both transcriptome enrichment and bioinformatic tools for detecting and quantifying circRNAs. Understanding the scope and limitations of these strategies is crucial for the subsequent annotation and characterization of circRNAs, especially those with functional potential. Here, we provide an overview of different transcriptome enrichment, deep sequencing and computational approaches for genome-wide circRNA identification, and discuss strategies for accurate quantification and characterization of circRNA.

Influence of social lifestyles on host-microbe symbioses in the bees

Microbiomes are increasingly recognised as critical for the health of an organism. In eusocial insect societies, frequent social interactions allow for high-fidelity transmission of microbes across generations, leading to closer host-microbe coevolution. The microbial communities of bees with other social lifestyles are less studied, and few comparisons have been made between taxa that vary in social structure. To address this gap, we leveraged a cloud-computing resource and publicly available transcriptomic data to conduct a survey of microbial diversity in bee samples from a variety of social lifestyles and taxa. We consistently recover the core microbes of well-studied corbiculate bees, supporting this method's ability to accurately characterise microbial communities. We find that the bacterial communities of bees are influenced by host location, phylogeny and social lifestyle, although no clear effect was found for fungal or viral microbial communities. Bee genera with more complex societies tend to harbour more diverse microbes, with Wolbachia detected more commonly in solitary tribes. We present a description of the microbiota of Euglossine bees and find that they do not share the "corbiculate core" microbiome. Notably, we find that bacteria with known anti-pathogenic properties are present across social bee genera, suggesting that symbioses that enhance host immunity are important with higher sociality. Our approach provides an inexpensive means of exploring microbiomes of a given taxa and identifying avenues for further research. These findings contribute to our understanding of the relationships between bees and their associated microbial communities, highlighting the importance of considering microbiome dynamics in investigations of bee health.

RNA capture pin technology: investigating long-term stability and mRNA purification specificity of oligonucleotide immobilization on gold and streptavidin surfaces

Advancing biomedical studies necessitates the development of cutting-edge technologies for the rapid extraction of nucleic acid. We characterized an RNA capture pin (RCP) tool that is non-destructive to the sample and enables rapid purification and enrichment of mRNA for subsequent genetic analysis. At the core of this technology is a pin (200 µm × 3 cm) functionalized with dT15 capture sequences that hybridize to mRNA within 2 min of insertion in the specimen. Two methods for immobilizing the oligos on the surface of the RCPs were investigated: gold-thiol and biotin-streptavidin. The RNA capture efficiency of the RCPs was assessed using a radish plant. The average reverse transcription-quantitative polymerase chain reaction (RT-qPCR) cycle amplification values were 19.93 and 24.84 for gold- and streptavidin-coated pins, respectively. The amount of RNA present on the surface of the probes was measured using the Agilent 2100 Bioanalyzer. RNA sequencing was performed to determine the mRNA selectivity of the RNA capture pin. Gene read count analysis confirmed that the RNA purified via the gold-plated RCPs contained 70% messenger RNA, 10% ribosomal RNA, and 20% non-coding RNA. The long-term stability of the bond between the dT15 oligos and the surface of the RCPs was assessed over 4 months. A significant decrease in the dT15 surface coverage of the streptavidin-coated RCPs was observed after 2 weeks of storage at 4 °C. The gold-thiol RNA capture pins exhibited a retention rate of 40% of the oligos after 4 months of storage.

Gene expression dynamics of natural assemblages of heterotrophic flagellates during bacterivory

BACKGROUND

Marine heterotrophic flagellates (HF) are dominant bacterivores in the ocean, where they represent the trophic link between bacteria and higher trophic levels and participate in the recycling of inorganic nutrients for regenerated primary production. Studying their activity and function in the ecosystem is challenging since most of the HFs in the ocean are still uncultured. In the present work, we investigated gene expression of natural HF communities during bacterivory in four unamended seawater incubations.

RESULTS

The most abundant species growing in our incubations belonged to the taxonomic groups MAST-4, MAST-7, Chrysophyceae, and Telonemia. Gene expression dynamics were similar between incubations and could be divided into three states based on microbial counts, each state displaying distinct expression patterns. The analysis of samples where HF growth was highest revealed some highly expressed genes that could be related to bacterivory. Using available genomic and transcriptomic references, we identified 25 species growing in our incubations and used those to compare the expression levels of these specific genes. Video Abstract CONCLUSIONS: Our results indicate that several peptidases, together with some glycoside hydrolases and glycosyltransferases, are more expressed in phagotrophic than in phototrophic species, and thus could be used to infer the process of bacterivory in natural assemblages.

Ageing-associated changes in transcriptional elongation influence longevity

Physiological homeostasis becomes compromised during ageing, as a result of impairment of cellular processes, including transcription and RNA splicing1-4. However, the molecular mechanisms leading to the loss of transcriptional fidelity are so far elusive, as are ways of preventing it. Here we profiled and analysed genome-wide, ageing-related changes in transcriptional processes across different organisms: nematodes, fruitflies, mice, rats and humans. The average transcriptional elongation speed (RNA polymerase II speed) increased with age in all five species. Along with these changes in elongation speed, we observed changes in splicing, including a reduction of unspliced transcripts and the formation of more circular RNAs. Two lifespan-extending interventions, dietary restriction and lowered insulin-IGF signalling, both reversed most of these ageing-related changes. Genetic variants in RNA polymerase II that reduced its speed in worms5 and flies6 increased their lifespan. Similarly, reducing the speed of RNA polymerase II by overexpressing histone components, to counter age-associated changes in nucleosome positioning, also extended lifespan in flies and the division potential of human cells. Our findings uncover fundamental molecular mechanisms underlying animal ageing and lifespan-extending interventions, and point to possible preventive measures.

Inhibition of EZH2 Causes Retrotransposon Derepression and Immune Activation in Porcine Lung Alveolar Macrophages

Alveolar macrophages (AMs) form the first defense line against various respiratory pathogens, and their immune response has a profound impact on the outcome of respiratory infection. Enhancer of zeste homolog 2 (EZH2), which catalyzes the trimethylation of H3K27 for epigenetic repression, has gained increasing attention for its immune regulation function, yet its exact function in AMs remains largely obscure. Using porcine 3D4/21 AM cells as a model, we characterized the transcriptomic and epigenomic alterations after the inhibition of EZH2. We found that the inhibition of EZH2 causes transcriptional activation of numerous immune genes and inhibits the subsequent infection by influenza A virus. Interestingly, specific families of transposable elements, particularly endogenous retrovirus elements (ERVs) and LINEs which belong to retrotransposons, also become derepressed. While some of the derepressed ERV families are pig-specific, a few ancestral families are known to be under EZH2-mediated repression in humans. Given that derepression of ERVs can promote innate immune activation through "viral mimicry", we speculate that ERVs may also contribute to the coinciding immune activation in AMs after the inhibition of EZH2. Overall, this study improves the understanding of the EZH2-related immune regulation in AMs and provides novel insights into the epigenetic regulation of retrotransposons in pigs.

The hitchhikers' guide to RNA sequencing and functional analysis

DNA and RNA sequencing technologies have revolutionized biology and biomedical sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably low costs. RNA sequencing (RNA-Seq) enables transcript identification and quantification, but once sequencing has concluded researchers can be easily overwhelmed with questions such as how to go from raw data to differential expression (DE), pathway analysis and interpretation. Several pipelines and procedures have been developed to this effect. Even though there is no unique way to perform RNA-Seq analysis, it usually follows these steps: 1) raw reads quality check, 2) alignment of reads to a reference genome, 3) aligned reads' summarization according to an annotation file, 4) DE analysis and 5) gene set analysis and/or functional enrichment analysis. Each step requires researchers to make decisions, and the wide variety of options and resulting large volumes of data often lead to interpretation challenges. There also seems to be insufficient guidance on how best to obtain relevant information and derive actionable knowledge from transcription experiments. In this paper, we explain RNA-Seq steps in detail and outline differences and similarities of different popular options, as well as advantages and disadvantages. We also discuss non-coding RNA analysis, multi-omics, meta-transcriptomics and the use of artificial intelligence methods complementing the arsenal of tools available to researchers. Lastly, we perform a complete analysis from raw reads to DE and functional enrichment analysis, visually illustrating how results are not absolute truths and how algorithmic decisions can greatly impact results and interpretation.

Sample Preparation and Differential Gene Expression Analysis of Human Cancer Cell Lines by RNA Sequencing

RNA sequencing (RNA-seq) is a method used for the high-throughput quantification of mRNA in a biological sample. It is widely used to investigate differential gene expression between drug-resistant and sensitive cancers to identify genetic mediators of drug resistance. Here, we describe a comprehensive experimental and bioinformatic pipeline to isolate mRNA from human cell lines, prepare mRNA libraries for next-generation sequencing, and perform post-sequencing bioinformatics analyses.

RNA Sequencing Analysis of Saliva exRNA

Next-generation sequencing (NGS) methodologies are rapidly developing. However, RNA Sequencing of saliva is challenging due to low abundance and integrity of extracellular RNA, as well as large amounts of bacterial RNAs that may be encountered in saliva. In addition, the literature about human salivary extracellular RNA is very scarce. Therefore, in our chapter, we present the most appropriate protocols for saliva collection, pre- and post-processing, including bioinformatic analysis of salivary RNA Sequencing data. However, the choice of the proper method for RNA extraction, cDNA library preparation, and computational pipeline can make a significant impact on the final quality of data and their interpretation.

A cap 0-dependent mRNA capture method to analyze the yeast transcriptome

Analysis of the protein coding transcriptome by the RNA sequencing requires either enrichment of the desired fraction of coding transcripts or depletion of the abundant non-coding fraction consisting mainly of rRNA. We propose an alternative mRNA enrichment strategy based on the RNA-binding properties of the human IFIT1, an antiviral protein recognizing cap 0 RNA. Here, we compare for Saccharomyces cerevisiae an IFIT1-based mRNA pull-down with yeast targeted rRNA depletion by the RiboMinus method. IFIT1-based RNA capture depletes rRNA more effectively, producing high quality RNA-seq data with an excellent coverage of the protein coding transcriptome, while depleting cap-less transcripts such as mitochondrial or some non-coding RNAs. We propose IFIT1 as a cost effective and versatile tool to prepare mRNA libraries for a variety of organisms with cap 0 mRNA ends, including diverse plants, fungi and eukaryotic microbes.

Rapid and sensitive single-cell RNA sequencing with SHERRY2

BACKGROUND

Prevalent single-cell transcriptomic profiling (scRNA-seq) methods are mainly based on the synthesis and enrichment of full-length double-stranded complementary DNA. These approaches are challenging to generate accurate quantification of transcripts when their abundance is low or their full-length amplifications are difficult.

RESULTS

Based on our previous finding that Tn5 transposase can directly cut-and-tag DNA/RNA hetero-duplexes, we present SHERRY2, a specifically optimized protocol for scRNA-seq without second-strand cDNA synthesis. SHERRY2 is free of pre-amplification and eliminates the sequence-dependent bias. In comparison with other widely used scRNA-seq methods, SHERRY2 exhibits significantly higher sensitivity and accuracy even for single nuclei. Besides, SHERRY2 is simple and robust and can be easily scaled up to high-throughput experiments. When testing single lymphocytes and neuron nuclei, SHERRY2 not only obtained accurate countings of transcription factors and long non-coding RNAs, but also provided bias-free results that enriched genes in specific cellular components or functions, which outperformed other protocols. With a few thousand cells sequenced by SHERRY2, we confirmed the expression and dynamics of Myc in different cell types of germinal centers, which were previously only revealed by gene-specific amplification methods.

CONCLUSIONS

SHERRY2 is able to provide high sensitivity, high accuracy, and high throughput for those applications that require a high number of genes identified in each cell. It can reveal the subtle transcriptomic difference between cells and facilitate important biological discoveries.

Novel Method of Full-Length RNA-seq That Expands the Identification of Non-Polyadenylated RNAs Using Nanopore Sequencing

The occurrence of diseases displayed transcriptome alteration, including both coding and non-coding transcripts. The third-generation sequencing (TGS) technologies allow for intensive and comprehensive research of the transcriptome. However, the present standard TGS RNA sequencing method is unable to detect many of the non-polyadenylated [non-poly(A)] RNAs. To obtain more complete transcriptome information, we presented a new comprehensive sequencing approach by performing conventional poly(A) RNA-sequencing combined with the sequencing of non-poly(A) RNA fraction which was tailed by poly(U) on HepG2 and HL-7702 cell lines, enabling the detection of multiple categories of non-poly(A) RNAs excluded by the existing standard approach. Moreover, the length distribution of the full-splice match transcripts was longer than that assembled by short-reads, which contributed to characterizing alternative splicing events and provided a comprehensive portrait of transcriptional complexity. Besides the detection of genes with differential expression patterns in the poly(A) library between HepG2 and HL-7702, we also found a cancer-related non-coding gene in the poly(U) data, that is, growth arrest special 5 (GAS5). Collectively, our results suggested that the novel method effectively captured both poly(A) and non-poly(A) transcripts in the tested cell lines and allowed a deeper exploration of the transcriptome.

Post-transcriptional regulation of 2-acetyl-1-pyrroline (2-AP) biosynthesis pathway, silicon, and heavy metal transporters in response to Zn in fragrant rice

Fragrant rice (Oryza sativa L.) has a high economic and nutritional value, and the application of micronutrients regulates 2-acetyl-1-pyrroline (2-AP) production, which is responsible for aroma in fragrant rice. Alternative splicing (AS) is an important post-transcriptional regulatory mechanism to generate transcript variability and proteome diversity in plants. However, no systematic investigation of AS events in response to micronutrients (Zn) has been performed in fragrant rice. Furthermore, the post-transcriptional regulation of genes involved in 2-AP biosynthesis is also not known. In this study, a comprehensive analysis of AS events under two gradients of Zn treatment in two different fragrant rice cultivars (Meixiangzhan-2 and Xiangyaxiangzhan) was performed based on RNA-seq analysis. A total of 386 and 598 significant AS events were found in Meixiangzhan-2 treated with low and high doses of Zn, respectively. In Xiangyaxiangzhan, a total of 449 and 598 significant AS events were found in low and high doses of Zn, respectively. Go analysis indicated that these genes were highly enriched in physiological processes, metabolism, and cellular processes in both cultivars. However, genotype and dose-dependent AS events were also detected in both cultivars. By comparing differential AS (DAS) events with differentially expressed genes (DEGs), we found a weak overlap among DAS and DEGs in both fragrant rice cultivars indicating that only a few genes are post-transcriptionally regulated in response to Zn treatment. We further report that Zn differentially regulates the expression of 2-AP biosynthesis-related genes in both cultivars and Zn treatment altered the editing frequency of single nucleotide polymorphism (SNPs) in the genes involved in 2-AP biosynthesis. Finally, we showed that epigenetic modifications associated with active gene transcription are generally enriched over 2-AP biosynthesis-related genes. Similar to the 2-AP pathway, we found that heavy metal transporters (genes related to silicon, iron, Zn and other metal transport) are also regulated at transcriptional and post-transcriptional levels in response to Zn in fragrant rice. Taken together, our results provide evidence of the post-transcriptional gene regulation in fragrant rice in response to Zn treatment and highlight that the 2-AP biosynthesis pathway and heavy metal transporters may also be regulated through epigenetic modifications. These findings will serve as a cornerstone for further investigation to understand the molecular mechanisms of 2-AP biosynthesis and regulation of heavy metal transporters in fragrant rice.

Revisiting Rustrela Virus: New Cases of Encephalitis and a Solution to the Capsid Enigma

Rustrela virus (RusV; species Rubivirus strelense) is a recently discovered relative of rubella virus (RuV) that has been detected in cases of encephalitis in diverse mammals. Here, we diagnosed two additional cases of fatal RusV-associated meningoencephalitis in a South American coati (Nasua nasua) and a Eurasian or European otter (Lutra lutra) that were detected in a zoological garden with history of prior RusV infections. Both animals showed abnormal movement or unusual behavior and their brains tested positive for RusV using specific reverse transcription quantitative PCR (RT-qPCR) and RNA in situ hybridization. As previous sequencing of the RusV genome proved to be very challenging, we employed a sophisticated target-specific capture enrichment with specifically designed RNA baits to generate complete RusV genome sequences from both detected encephalitic animals and apparently healthy wild yellow-necked field mice (Apodemus flavicollis). Furthermore, the technique was used to revise three previously published RusV genomes from two encephalitic animals and a wild yellow-necked field mouse. When comparing the newly generated RusV sequences to the previously published RusV genomes, we identified a previously undetected stretch of 309 nucleotides predicted to represent the intergenic region and the sequence encoding the N terminus of the capsid protein. This indicated that the original RusV sequence was likely incomplete due to misassembly of the genome at a region with an exceptionally high G+C content of >80 mol%. The new sequence data indicate that RusV has an overall genome length of 9,631 nucleotides with the longest intergenic region (290 nucleotides) and capsid protein-encoding sequence (331 codons) within the genus Rubivirus.

IMPORTANCE The detection of rustrela virus (RusV)-associated encephalitis in two carnivoran mammal species further extends the knowledge on susceptible species. Furthermore, we provide clinical and pathological data for the two new RusV cases, which were until now limited to the initial description of this fatal encephalitis. Using a sophisticated enrichment method prior to sequencing of the viral genome, we markedly improved the virus-to-background sequence ratio compared to that of standard procedures. Consequently, we were able to resolve and update the intergenic region and the coding region for the N terminus of the capsid protein of the initial RusV genome sequence. The updated putative capsid protein now resembles those of rubella and ruhugu virus in size and harbors a predicted RNA-binding domain that had not been identified in the initial RusV genome version. The newly determined complete RusV genomes strongly improve our knowledge of the genome structure of this novel rubivirus.

High transcriptome plasticity drives phosphate starvation responses in tomato

Tomato is an important vegetable crop and fluctuating available soil phosphate (Pi) level elicits several morpho-physiological responses driven by underlying molecular responses. Therefore, understanding these molecular responses at the gene and isoform levels has become critical in the quest for developing crops with improved Pi use efficiency. A quantitative time-series RNA-seq analysis was performed to decipher the global transcriptomic changes that accompany Pi starvation in tomato. Apart from changes in the expression levels of genes, there were also alterations in the expression of alternatively-spliced transcripts. Physiological responses such as anthocyanin accumulation, reactive oxygen species generation and cell death are obvious 7 days after Pi deprivation accompanied with the maximum amount of transcriptional change in the genome making it an important stage for in-depth study while studying Pi stress responses (PSR). Our study demonstrates that transcriptomic changes under Pi deficiency are dynamic and complex in tomato. Overall, our study dwells on the dynamism of the transcriptome in eliciting a response to adapt to low Pi stress and lays it bare. Findings from this study will prove to be an invaluable resource for researchers using tomato as a model for understanding nutrient deficiency.

Integrative analysis reveals a lineage-specific circular RNA landscape for adipo-osteogenesis of human mesenchymal stem cells

Background

The balance between osteogenesis and adipogenesis of mesenchymal stem cells (MSCs) is critical to skeletal development and diseases. As a research hotspot, circular RNAs (circRNAs) have expanded our understanding of a hidden layer of the transcriptome. Yet, their roles during adipo-osteogenesis remain poorly described.

Methods

The identity of human MSCs derived from bone marrow and adipose were first determined by flow cytometry, cellular staining, and quantitative polymerase chain reaction (qPCR). Multi-strategic RNA-sequencing was performed using Poly A, RiboMinus and RiboMinus/RNase R methods. Integrative analysis was performed to identify lineage-specific expressed circRNAs. The structural and expressional characteristics were identified by Sanger sequencing and qPCR, respectively. The regulatory effects of adipogenesis-specific circ-CRLF1 were confirmed using siRNA transcfection and qPCR.

Results

We generated a whole transcriptome map during adipo-osteogenesis based on 10 Poly A, 20 RiboMinus and 20 RiboMinus/ RNase R datasets. A total of 31,326 circRNAs were identified and quantified from ~ 3.4 billion paired-end reads. Furthermore, the integrative analysis revealed that 1166 circRNA genes exhibited strong lineage-specific expression patterns. Their host genes were enriched in distinct biological functions, such as cell adhesion, cytokine signaling, and cell division. We randomly selected and validated the back-spliced junction sites and expression patterns of 12 lineage-specific circRNAs. Functional analysis indicated that circ-CRLF1 negatively regulated adipogenesis.

Conclusions

Our integrative analysis reveals an accurate and generally applicable lineage-specific circRNA landscape for adipo-osteogenesis of MSCs and provides a potential therapeutic target, circ-CRLF1, for the treatment of skeleton-related disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-022-02792-5.

A method for simultaneous detection of small and long RNA biotypes by ribodepleted RNA-Seq

RNA sequencing offers unprecedented access to the transcriptome. Key to this is the identification and quantification of many different species of RNA from the same sample at the same time. In this study we describe a novel protocol for simultaneous detection of coding and non-coding transcripts using modifications to the Ion Total RNA-Seq kit v2 protocol, with integration of QIASeq FastSelect rRNA removal kit. We report highly consistent sequencing libraries can be produced from both frozen high integrity mouse hippocampal tissue and the more challenging post-mortem human tissue. Removal of rRNA using FastSelect was extremely efficient, resulting in less than 1.5% rRNA content in the final library. We identified > 30,000 unique transcripts from all samples, including protein-coding genes and many species of non-coding RNA, in biologically-relevant proportions. Furthermore, the normalized sequencing read count for select genes significantly negatively correlated with Ct values from qRT-PCR analysis from the same samples. These results indicate that this protocol accurately and consistently identifies and quantifies a wide variety of transcripts simultaneously. The highly efficient rRNA depletion, coupled with minimized sample handling and without complicated and high-loss size selection protocols, makes this protocol useful to researchers wishing to investigate whole transcriptomes.

Accurate Prediction of Protein Sequences for Proteogenomics Data Integration

This book chapter discusses proteogenomics data integration and provides an overview into the different omics layer involved in defining the proteome of a living organism. Various aspects of genome variability affecting either the sequence or abundance level of proteins are discussed in this book chapter, such as the effect of single-nucleotide variants or larger genomic structural variants on the proteome. Next, various sequencing technologies are introduced and discussed from a proteogenomics data integration perspective such as those providing short- and long-read sequencing and listing their respective advantages and shortcomings for accurate protein variant prediction using genomic/transcriptomics sequencing data. Finally, the various bioinformatics tools used to process and analyze DNA/RNA sequencing data are discussed with the ultimate goal of obtaining accurately predicted sample-specific protein sequences that can be used as a drop-in replacement in existing approaches for peptide and protein identification using popular database search engines such as MSFragger, SearchGUI/PeptideShaker.

Deregulation of ncRNA in Neurodegenerative Disease: Focus on circRNA, lncRNA and miRNA in Amyotrophic Lateral Sclerosis

Parallel and massive sequencing of total RNA samples derived from different samples are possible thanks to the use of NGS (Next Generation Sequencing) technologies. This allowed characterizing the transcriptomic profile of both cell and tissue populations, increasing the knowledge of the molecular pathological processes of complex diseases, such as neurodegenerative diseases (NDs). Among the NDs, Amyotrophic Lateral Sclerosis (ALS) is caused by the progressive loss of motor neurons (MNs), and, to date, the diagnosis is often made by exclusion because there is no specific symptomatologic picture. For this reason, it is important to search for biomarkers that are clinically useful for carrying out a fast and accurate diagnosis of ALS. Thanks to various studies, it has been possible to propose several molecular mechanisms associated with the disease, some of which include the action of non-coding RNA, including circRNAs, miRNAs, and lncRNAs which will be discussed in the present review. The evidence analyzed in this review highlights the importance of conducting studies to better characterize the different ncRNAs in the disease to use them as possible diagnostic, prognostic, and/or predictive biomarkers of ALS and other NDs.

RNA-seq library preparation for comprehensive transcriptome analysis in cancer cells: The impact of insert size

With long reads and high coverage, RNA-seq enables comprehensive transcriptome analysis of cancer cells, provided that optimal length of libraries (and their inserts) is assured, to avoid overlap of paired reads and consequent loss of sequencing data. We assessed TruSeq Stranded library preparation protocols (poly(A) enrichment-PA and rRNA depletion-RD) for the thoroughness of transcriptome analysis of a heterogeneous cancer, acute lymphoblastic leukemia. We applied 2x150PE sequencing, >150 M reads/sample on Illumina NovaSeq6000. We show that PA outperforms RD for the analysis of gene expression and structural aberrations. RD is more suitable for detection of various classes of RNAs, mutations or polymorphisms. We demonstrate that reduced RNA fragmentation time (generating longer inserts) positively affects detection of structural RNA changes, without introducing bias into gene expression analysis. We recommend this modification for all RNA-seq studies utilizing reads longer than 75 nt, aimed to go beyond gene expression analysis and to detect also structural changes.

Metabolic turnover and dynamics of modified ribonucleosides by 13C labeling

Tandem mass spectrometry (MS/MS) is an accurate tool to assess modified ribonucleosides and their dynamics in mammalian cells. However, MS/MS quantification of lowly abundant modifications in non-ribosomal RNAs is unreliable, and the dynamic features of various modifications are poorly understood. Here, we developed a ¹³C labeling approach, called ¹³C-dynamods, to quantify the turnover of base modifications in newly transcribed RNA. This turnover-based approach helped to resolve mRNA from ncRNA modifications in purified RNA or free ribonucleoside samples and showed the distinct kinetics of the N6-methyladenosine (m⁶A) versus 7-methylguanosine (m⁷G) modification in polyA+-purified RNA. We uncovered that N6,N6-dimethyladenosine (m⁶₂A) exhibits distinct turnover in small RNAs and free ribonucleosides when compared to known m⁶₂A-modified large rRNAs. Finally, combined measurements of turnover and abundance of these modifications informed on the transcriptional versus posttranscriptional sensitivity of modified ncRNAs and mRNAs, respectively, to stress conditions. Thus, ¹³C-dynamods enables studies of the origin of modified RNAs at steady-state and subsequent dynamics under nonstationary conditions. These results open new directions to probe the presence and biological regulation of modifications in particular RNAs.

A simple and robust method for simultaneous dual-omics profiling with limited numbers of cells

Deciphering epigenetic regulation of gene expression requires measuring the epigenome and transcriptome jointly. Single-cell multi-omics technologies have been developed for concurrent profiling of chromatin accessibility and gene expression. However, multi-omics profiling of low-input bulk samples remains challenging. Therefore, we developed low-input ATAC&mRNA-seq, a simple and robust method for studying the role of chromatin structure in gene regulation in a single experiment with thousands of cells, to maximize insights from limited input material by obtaining ATAC-seq and mRNA-seq data simultaneously from the same cells with data quality comparable to that of conventional mono-omics assays. Integrative data analysis revealed similar strong association between promoter accessibility and gene expression when using the data of low-input ATAC&mRNA-seq as when using single-assay data, underscoring the accuracy and reliability of our dual-omics assay to generate both datum types simultaneously with just thousands of cells. We envision our method to be widely applied in many biological disciplines with limited materials.

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.

Kmerator Suite: design of specific k-mer signatures and automatic metadata discovery in large RNA-seq datasets

The huge body of publicly available RNA-sequencing (RNA-seq) libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large dataset characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor gene-specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualized through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non-coding RNAs for human health applications.

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.

INTACT vs. FANS for Cell-Type-Specific Nuclei Sorting: A Comprehensive Qualitative and Quantitative Comparison

Increasing numbers of studies seek to characterize the different cellular sub-populations present in mammalian tissues. The techniques “Isolation of Nuclei Tagged in Specific Cell Types” (INTACT) or “Fluorescence-Activated Nuclei Sorting” (FANS) are frequently used for isolating nuclei of specific cellular subtypes. These nuclei are then used for molecular characterization of the cellular sub-populations. Despite the increasing popularity of both techniques, little is known about their isolation efficiency, advantages, and disadvantages or downstream molecular effects. In our study, we compared the physical and molecular attributes of sfGFP+ nuclei isolated by the two methods—INTACT and FANS—from the neocortices of Arc-CreERT2 × CAG-Sun1/sfGFP animals. We identified differences in efficiency of sfGFP+ nuclei isolation, nuclear size as well as transcriptional (RNA-seq) and chromatin accessibility (ATAC-seq) states. Therefore, our study presents a comprehensive comparison between the two widely used nuclei sorting techniques, identifying the advantages and disadvantages for both INTACT and FANS. Our conclusions are summarized in a table to guide researchers in selecting the most suitable methodology for their individual experimental design.

SLIDR and SLOPPR: flexible identification of spliced leader trans-splicing and prediction of eukaryotic operons from RNA-Seq data

BACKGROUND

Spliced leader (SL) trans-splicing replaces the 5' end of pre-mRNAs with the spliced leader, an exon derived from a specialised non-coding RNA originating from elsewhere in the genome. This process is essential for resolving polycistronic pre-mRNAs produced by eukaryotic operons into monocistronic transcripts. SL trans-splicing and operons may have independently evolved multiple times throughout Eukarya, yet our understanding of these phenomena is limited to only a few well-characterised organisms, most notably C. elegans and trypanosomes. The primary barrier to systematic discovery and characterisation of SL trans-splicing and operons is the lack of computational tools for exploiting the surge of transcriptomic and genomic resources for a wide range of eukaryotes.

RESULTS

Here we present two novel pipelines that automate the discovery of SLs and the prediction of operons in eukaryotic genomes from RNA-Seq data. SLIDR assembles putative SLs from 5' read tails present after read alignment to a reference genome or transcriptome, which are then verified by interrogating corresponding SL RNA genes for sequence motifs expected in bona fide SL RNA molecules. SLOPPR identifies RNA-Seq reads that contain a given 5' SL sequence, quantifies genome-wide SL trans-splicing events and predicts operons via distinct patterns of SL trans-splicing events across adjacent genes. We tested both pipelines with organisms known to carry out SL trans-splicing and organise their genes into operons, and demonstrate that (1) SLIDR correctly detects expected SLs and often discovers novel SL variants; (2) SLOPPR correctly identifies functionally specialised SLs, correctly predicts known operons and detects plausible novel operons.

CONCLUSIONS

SLIDR and SLOPPR are flexible tools that will accelerate research into the evolutionary dynamics of SL trans-splicing and operons throughout Eukarya and improve gene discovery and annotation for a wide range of eukaryotic genomes. Both pipelines are implemented in Bash and R and are built upon readily available software commonly installed on most bioinformatics servers. Biological insight can be gleaned even from sparse, low-coverage datasets, implying that an untapped wealth of information can be retrieved from existing RNA-Seq datasets as well as from novel full-isoform sequencing protocols as they become more widely available.

Non-Coding RNA Signatures of B-Cell Acute Lymphoblastic Leukemia

Non-coding RNAs (ncRNAs) comprise a diverse class of non-protein coding transcripts that regulate critical cellular processes associated with cancer. Advances in RNA-sequencing (RNA-Seq) have led to the characterization of non-coding RNA expression across different types of human cancers. Through comprehensive RNA-Seq profiling, a growing number of studies demonstrate that ncRNAs, including long non-coding RNA (lncRNAs) and microRNAs (miRNA), play central roles in progenitor B-cell acute lymphoblastic leukemia (B-ALL) pathogenesis. Furthermore, due to their central roles in cellular homeostasis and their potential as biomarkers, the study of ncRNAs continues to provide new insight into the molecular mechanisms of B-ALL. This article reviews the ncRNA signatures reported for all B-ALL subtypes, focusing on technological developments in transcriptome profiling and recently discovered examples of ncRNAs with biologic and therapeutic relevance in B-ALL.

Non-coding RNAs in cardiomyocyte proliferation and cardiac regeneration: Dissecting their therapeutic values

Cardiovascular diseases are associated with high incidence and mortality, contribute to disability and place a heavy economic burden on countries worldwide. Stimulating endogenous cardiomyocyte proliferation and regeneration has been considering as a key to repair the injured heart caused by ischaemia. Emerging evidence has proved that non‐coding RNAs participate in cardiac proliferation and regeneration. In this review, we focus on the observation and mechanism that microRNAs (or miRNAs), long non‐coding RNAs (or lncRNAs) and circular RNA (or circRNAs) regulate cardiomyocyte proliferation and regeneration to repair a damaged heart. Furthermore, we highlight the potential therapeutic role of some non‐coding RNAs used in stimulating CMs proliferation. Finally, perspective on the development of non‐coding RNAs therapy in cardiac regeneration is presented.

Library Preparation Based on Transposase Assisted RNA/DNA Hybrid Co-Tagmentation for Next-Generation Sequencing of Human Noroviruses

Human noroviruses (HuNoVs) are one of the leading causes of foodborne illnesses globally. The viral genome is the most essential information for viral source tracing and viral transmission pattern monitoring. However, whole genome sequencing of HuNoVs is still challenging due to the sequence heterogeneity among different genotypes and low titer in samples. To address this need, in this study, the Transposase assisted RNA/DNA hybrid Co-tagmentation (TRACE-seq) method was established for next generation sequencing library preparation of HuNoVs. Our data demonstrated that almost the whole HuNoVs genome (>7 kb) could be obtained from all of the 11 clinical samples tested. Twelve genotypes including GI.3, GI.4, GI.5, GI.8, GII.2, GII.3, GII.4, GII.6, GII.12, GII.13, GII.14, and GII.21 were involved. Compared with the traditional method for viral metagenomics library preparation, optimized TRACE-seq greatly reduced the interference from the host's and bacterial RNAs. In addition, viral genome sequences can be assembled by using less raw data with sufficient depth along the whole genome. Therefore, for the high versatility and reliability, this method is promising for whole viral genome attainment. It is particularly applicable for the viruses with a low titer that are mixed with a complicated host background and are unable to be cultured in vitro, like the HuNoVs utilized in this study.

Paired rRNA-depleted and polyA-selected RNA sequencing data and supporting multi-omics data from human T cells

Both poly(A) enrichment and ribosomal RNA depletion are commonly used for RNA sequencing. Either has its advantages and disadvantages that may lead to biases in the downstream analyses. To better access these effects, we carried out both ribosomal RNA-depleted and poly(A)-selected RNA-seq for CD4+ T naive cells isolated from 40 healthy individuals from the Blueprint Project. For these 40 individuals, the genomic and epigenetic data were also available. This dataset offers a unique opportunity to understand how library construction influences differential gene expression, alternative splicing and molecular QTL (quantitative loci) analyses for human primary cells.

Large scale, robust, and accurate whole transcriptome profiling from clinical formalin-fixed paraffin-embedded samples

Transcriptome profiling can provide information of great value in clinical decision-making, yet RNA from readily available formalin-fixed paraffin-embedded (FFPE) tissue is often too degraded for quality sequencing. To assess the clinical utility of FFPE-derived RNA, we performed ribo-deplete RNA extractions on > 3200 FFPE slide samples; 25 of these had direct FFPE vs. fresh frozen (FF) replicates, 57 were sequenced in 2 different labs, 87 underwent multiple library analyses, and 16 had direct microdissected vs. macrodissected replicates. Poly-A versus ribo-depletion RNA extraction methods were compared using transcriptomes of TCGA cohort and 3116 FFPE samples. Compared to FF, FFPE transcripts coding for nuclear/cytoplasmic proteins involved in DNA packaging, replication, and protein synthesis were detected at lower rates and zinc finger family transcripts were of poorer quality. The greatest difference in extraction methods was in histone transcripts which typically lack poly-A tails. Encouragingly, the overall sequencing success rate was 81%. Exome coverage was highly concordant in direct FFPE and FF replicates, with 98% agreement in coding exon coverage and a median correlation of whole transcriptome profiles of 0.95. We provide strong rationale for clinical use of FFPE-derived RNA based on the robustness, reproducibility, and consistency of whole transcriptome profiling.

Non-coding RNAs: the new central dogma of cancer biology

The central dogma of molecular biology states that the functions of RNA revolve around protein translation. Until the last decade, most researches were geared towards characterization of RNAs as intermediaries in protein translation, namely, messenger RNAs (mRNAs) as temporary copies of genetic information, ribosomal RNAs (rRNAs) as a main component of ribosome, or translators of codon sequence (tRNAs). The statistical reality, however, is that these processes account for less than 2% of the genome, and insufficiently explain the functionality of 98% of transcribed RNAs. Recent discoveries have unveiled thousands of unique non-coding RNAs (ncRNAs) and shifted the perception of them from being "junk" transcriptional products to "yet to be elucidated"-and potentially monumentally important-RNAs. Most ncRNAs are now known as key regulators in various networks in which they could lead to specific cellular responses and fates. In major cancers, ncRNAs have been identified as both oncogenic drivers and tumor suppressors, indicating a complex regulatory network among these ncRNAs. Herein, we provide a comprehensive review of the various ncRNAs and their functional roles in cancer, and the pre-clinical and clinical development of ncRNA-based therapeutics. A deeper understanding of ncRNAs could facilitate better design of personalized therapeutics.

Evaluation of U.S. Food and Drug Administration Enteric Viruses Microarray for Detection of Hepatitis A Virus and Norovirus in Inoculated Tomatoes, Green Onions, and Celery

ABSTRACT

Foodborne viral contamination of fresh produce has been associated with numerous outbreaks. Detection of such contaminated foods is important in protecting public health. Here, we demonstrate for the first time the capability of the U.S. Food and Drug Administration Enteric Viruses tiling microarray (FDA-EVIR) to perform rapid molecular identification of hepatitis A virus (HAV) and human norovirus extracted from artificially inoculated fresh produce. Two published viral extraction strategies, total RNA extraction or virus particle isolation, were used to prepare the viral targets. The total RNA extraction method was used on material eluted from tomatoes, using an alkaline Tris-glycine-beef extract (TGBE) buffer. Optimization procedures including DNase treatment and poly(A)-RNA enrichment were adopted to improve microarray sensitivity. For green onions or celery, material was eluted using either glycine buffer or TGBE buffer supplemented with pectinase, respectively, and then virus particles were concentrated by ultracentrifugation. We also assessed the amount of viral RNA extracted from celery using three commercially available kits and how well that RNA performed on FDA-EVIR. Our results confirm that FDA-EVIR can identify common enteric viruses isolated from fresh produce when present as either a single or mixed species of viruses. Using total RNA extraction from tomatoes yielded a limit of detection of 1.0 × 105 genome equivalents (ge) of HAV per array input. The limit of detection for viral RNA obtained using ultracentrifugation was 1.2 × 105 ge of HAV from green onions and 1.0 × 103 ge of norovirus from celery per array input. Extending microarray methods to other food matrices should provide important support to surveillance and outbreak investigations.

HIGHLIGHTS

Comparison of Poly-A+ Selection and rRNA Depletion in Detection of lncRNA in Two Equine Tissues Using RNA-seq

Long non-coding RNAs (lncRNAs) are untranslated regulatory transcripts longer than 200 nucleotides that can play a role in transcriptional, post-translational, and epigenetic regulation. Traditionally, RNA-sequencing (RNA-seq) libraries have been created by isolating transcriptomic RNA via poly-A+ selection. In the past 10 years, methods to perform ribosomal RNA (rRNA) depletion of total RNA have been developed as an alternative, aiming for better coverage of whole transcriptomic RNA, both polyadenylated and non-polyadenylated transcripts. The purpose of this study was to determine which library preparation method is optimal for lncRNA investigations in the horse. Using liver and cerebral parietal lobe tissues from two healthy Thoroughbred mares, RNA-seq libraries were prepared using standard poly-A+ selection and rRNA-depletion methods. Averaging the two biologic replicates, poly-A+ selection yielded 327 and 773 more unique lncRNA transcripts for liver and parietal lobe, respectively. More lncRNA were found to be unique to poly-A+ selected libraries, and rRNA-depletion identified small nucleolar RNA (snoRNA) to have a higher relative expression than in the poly-A+ selected libraries. Overall, poly-A+ selection provides a more thorough identification of total lncRNA in equine tissues while rRNA-depletion may allow for easier detection of snoRNAs.

Recommendations for bacterial ribosome profiling experiments based on bioinformatic evaluation of published data

Ribosome profiling (RIBO-Seq) has improved our understanding of bacterial translation, including finding many unannotated genes. However, protocols for RIBO-Seq and corresponding data analysis are not yet standardized. Here, we analyzed 48 RIBO-Seq samples from nine studies of Escherichia coli K12 grown in lysogeny broth medium and particularly focused on the size-selection step. We show that for conventional expression analysis, a size range between 22 and 30 nucleotides is sufficient to obtain protein-coding fragments, which has the advantage of removing many unwanted rRNA and tRNA reads. More specific analyses may require longer reads and a corresponding improvement in rRNA/tRNA depletion. There is no consensus about the appropriate sequencing depth for RIBO-Seq experiments in prokaryotes, and studies vary significantly in total read number. Our analysis suggests that 20 million reads that are not mapping to rRNA/tRNA are required for global detection of translated annotated genes. We also highlight the influence of drug-induced ribosome stalling, which causes bias at translation start sites. The resulting accumulation of reads at the start site may be especially useful for detecting weakly expressed genes. As different methods suit different questions, it may not be possible to produce a "one-size-fits-all" ribosome profiling data set. Therefore, experiments should be carefully designed in light of the scientific questions of interest. We propose some basic characteristics that should be reported with any new RIBO-Seq data sets. Careful attention to the factors discussed should improve prokaryotic gene detection and the comparability of ribosome profiling data sets.

RNA-Seq of human whole blood: Evaluation of globin RNA depletion on Ribo-Zero library method

Peripheral blood is a highly accessible biofluid providing a rich source of information about human physiology and health status. However, for studies of the blood transcriptome with RNA sequencing (RNA-Seq) techniques, high levels of hemoglobin mRNAs (hgbRNA) present in blood can occupy valuable sequencing space, impacting detection and quantification of non-hgbRNAs. In this study, we evaluated two methods for preparing ribosomal RNA (rRNA)-depleted sequencing libraries for RNA-Seq of whole blood, one of which is also designed to deplete hgbRNAs. Two experiments were performed: one evaluating library performance across 6 human blood samples and the other examining library reproducibility and performance in a two-subject subset. We find that addition of hgbRNA depletion to the rRNA-depletion protocol for library preparation from blood RNA effectively reduces highly abundant hgbRNA reads; however, it does not result in a statistically significant increase in differentially expressed genes in our patient-control study. Bioinformatic removal of globin gene counts in non-hgbRNA depleted libraries provides improvement in overall performance of these libraries. We conclude that use of a standard ribosomal RNA depletion method for library preparation coupled with bioinformatic removal of globin gene counts is sufficient for reproducible and sensitive measurement of both coding and noncoding RNAs in the blood transcriptome.

RNA sequencing by direct tagmentation of RNA/DNA hybrids

RNA sequencing is widely used to measure gene expression in biomedical research; therefore, improvements in the simplicity and accuracy of the technology are desirable. All existing RNA sequencing methods rely on the conversion of RNA into double-stranded DNA through reverse transcription followed by second-strand synthesis. The latter step requires additional enzymes and purification, and introduces sequence-dependent bias. Here, we show that Tn5 transposase, which randomly binds and cuts double-stranded DNA, can directly fragment and prime the RNA/DNA heteroduplexes generated by reverse transcription. The primed fragments are then subject to PCR amplification. This provides an approach for simple and accurate RNA characterization and quantification.

Transcriptome profiling by RNA sequencing (RNA-seq) has been widely used to characterize cellular status, but it relies on second-strand complementary DNA (cDNA) synthesis to generate initial material for library preparation. Here we use bacterial transposase Tn5, which has been increasingly used in various high-throughput DNA analyses, to construct RNA-seq libraries without second-strand synthesis. We show that Tn5 transposome can randomly bind RNA/DNA heteroduplexes and add sequencing adapters onto RNA directly after reverse transcription. This method, Sequencing HEteRo RNA-DNA-hYbrid (SHERRY), is versatile and scalable. SHERRY accepts a wide range of starting materials, from bulk RNA to single cells. SHERRY offers a greatly simplified protocol and produces results with higher reproducibility and GC uniformity compared with prevailing RNA-seq methods.

Characterizing the nuclear and cytoplasmic transcriptomes in developing and mature human cortex uncovers new insight into psychiatric disease gene regulation

Transcriptome compartmentalization by the nuclear membrane provides both stochastic and functional buffering of transcript activity in the cytoplasm, and has recently been implicated in neurodegenerative disease processes. Although many mechanisms regulating transcript compartmentalization are also prevalent in brain development, the extent to which subcellular localization differs as the brain matures has yet to be addressed. To characterize the nuclear and cytoplasmic transcriptomes during brain development, we sequenced both RNA fractions from homogenate prenatal and adult human postmortem cortex using poly(A)+ and Ribo-Zero library preparation methods. We find that while many genes are differentially expressed by fraction and developmental expression changes are similarly detectable in nuclear and cytoplasmic RNA, the compartmented transcriptomes become more distinct as the brain matures, perhaps reflecting increased utilization of nuclear retention as a regulatory strategy in adult brain. We examined potential mechanisms of this developmental divergence including alternative splicing, RNA editing, nuclear pore composition, RNA-binding protein motif enrichment, and RNA secondary structure. Intron retention is associated with greater nuclear abundance in a subset of transcripts, as is enrichment for several splicing factor binding motifs. Finally, we examined disease association with fraction-regulated gene sets and found nuclear-enriched genes were also preferentially enriched in gene sets associated with neurodevelopmental psychiatric disorders. These results suggest that although gene-level expression is globally comparable between fractions, nuclear retention of transcripts may play an underappreciated role in developmental regulation of gene expression in brain, particularly in genes whose dysregulation is related to neuropsychiatric disorders.

Antibody cross-reactivity accounts for widespread appearance of m1A in 5'UTRs

N1-methyladenosine (m1A) was proposed to be a highly prevalent modification in mRNA 5'UTRs based on mapping studies using an m1A-binding antibody. We developed a bioinformatic approach to discover m1A and other modifications in mRNA throughout the transcriptome by analyzing preexisting ultra-deep RNA-Seq data for modification-induced misincorporations. Using this approach, we detected appreciable levels of m1A only in one mRNA: the mitochondrial MT-ND5 transcript. As an alternative approach, we also developed an antibody-based m1A-mapping approach to detect m1A at single-nucleotide resolution, and confirmed that the commonly used m1A antibody maps sites to the transcription-start site in mRNA 5'UTRs. However, further analysis revealed that these were false-positives caused by binding of the antibody to the m7G-cap. A different m1A antibody that lacks cap-binding cross-reactivity does not show enriched binding in 5'UTRs. These results demonstrate that high-stoichiometry m1A sites are exceedingly rare in mRNAs and that previous mappings of m1A to 5'UTRs were the result of antibody cross-reactivity to the 5' cap.

Technical differences between sequencing and microarray platforms impact transcriptomic subtyping of colorectal cancer

Gene expression profiling has increasing relevance in the molecular screening of patients with colorectal cancer (CRC). We investigated potential platform-specific effects on transcriptomic subtyping according to established frameworks by comparisons of expression profiles from RNA sequencing and exon-resolution microarrays in 126 primary microsatellite stable CRCs. There was a strong platform correspondence in global gene expression levels, albeit with systematic technical bias likely attributed to few sequencing reads covering short (<2000 nucleotides) and/or lowly expressed genes (<1 FPKM), as well as over-saturation of highly expressed genes on microarrays. Classification concordances according to both the consensus molecular subtypes and CRC intrinsic subtypes (CRIS) were also strong, but with disproportionate subtype distributions between platforms caused by frequent disagreements in adherence to sample classification thresholds. Subtypes defined largely by genes expressed at low levels, including the CRIS-D subtype and the estimated level of tumor-infiltrating cytotoxic lymphocytes, had a weaker correspondence in classification metrics between platforms. In conclusion, even subtle differences between platforms suggest that clinical translation of transcriptomic CRC subtyping frameworks is dependent on assay standardization, and systematic technical biases reinforce the need for careful selection of classifier genes.

Monoallelic, antisense and total RNA transcription in an in vitro neural differentiation system based on F1 hybrid mice

We developed an in vitro system to differentiate embryonic stem cells (ESCs) derived from reciprocally crossed F1 hybrid mice into neurons, and used it to investigate poly(A)+ and total RNA transcription at different stages of cell differentiation. By comparing expression profiles of transcripts assembled from 20 RNA sequencing datasets [2 alleles×(2 cell lines×4 time-points+2 mouse brains)], the relative influence of strain, cell and parent specificities to overall expression could be assessed. Divergent expression profiles of ESCs converged tightly at neural progenitor stage. Patterns of temporal variation of monoallelically expressed transcripts and antisense transcripts were quantified. Comparison of sense and antisense transcript pairs within the poly(A)+ sample, within the total RNA sample, and across poly(A)+ and total RNA samples revealed distinct rates of pairs showing anti-correlated expression variation. Unique patterns of sharing of poly(A)+ and poly(A)- transcription were identified in distinct RNA species. Regulation and functionality of monoallelic expression, antisense transcripts and poly(A)- transcription remain elusive. We demonstrated the effectiveness of our approach to capture these transcriptional activities, and provided new resources to elucidate the mammalian developmental transcriptome.