Ribosomal RNA depletion for efficient use of RNA-seq capacity

Nucleocytoplasmic transport rates are regulated by cellular processes that modulate GTP availability

Nucleocytoplasmic transport (NCT), the facilitated diffusion of cargo molecules between the nucleus and cytoplasm through nuclear pore complexes (NPCs), enables numerous fundamental eukaryotic cellular processes. Ran GTPase uses cellular energy in the direct form of GTP to create a gradient across the nuclear envelope (NE) that drives the majority of NCT. We report here that changes in GTP availability resulting from altered cellular physiology modulate the rate of NCT, as monitored using synthetic and natural cargo, and the dynamics of Ran itself. Cell migration, cell spreading, and/or modulation of the cytoskeleton or its connection to the nucleus alter GTP availability and thus rates of NCT, regulating RNA export and protein synthesis. These findings support a model in which changes in cellular physiology that alter GTP availability can regulate the rate of NCT, impacting fundamental cellular processes that extensively utilize NCT.

Exploring the enigma: history, present, and future of long non-coding RNAs in cancer

Long noncoding RNAs (lncRNAs), which are more than 200 nucleotides in length and do not encode proteins, play crucial roles in governing gene expression at both the transcriptional and posttranscriptional levels. These molecules demonstrate specific expression patterns in various tissues and developmental stages, suggesting their involvement in numerous developmental processes and diseases, notably cancer. Despite their widespread acknowledgment and the growing enthusiasm surrounding their potential as diagnostic and prognostic biomarkers, the precise mechanisms through which lncRNAs function remain inadequately understood. A few lncRNAs have been studied in depth, providing valuable insights into their biological activities and suggesting emerging functional themes and mechanistic models. However, the extent to which the mammalian genome is transcribed into functional noncoding transcripts is still a matter of debate. This review synthesizes our current understanding of lncRNA biogenesis, their genomic contexts, and their multifaceted roles in tumorigenesis, highlighting their potential in cancer-targeted therapy. By exploring historical perspectives alongside recent breakthroughs, we aim to illuminate the diverse roles of lncRNA and reflect on the broader implications of their study for understanding genome evolution and function, as well as for advancing clinical applications.

A normalization method that controls for total RNA abundance affects the identification of differentially expressed genes, revealing bias toward morning-expressed responses

RNA-Sequencing is widely used to investigate changes in gene expression at the transcription level in plants. Most plant RNA-Seq analysis pipelines base the normalization approaches on the assumption that total transcript levels do not vary between samples. However, this assumption has not been demonstrated. In fact, many common experimental treatments and genetic alterations affect transcription efficiency or RNA stability, resulting in unequal transcript abundance. The addition of synthetic RNA controls is a simple correction that controls for variation in total mRNA levels. However, adding spike-ins appropriately is challenging with complex plant tissue, and carefully considering how they are added is essential to their successful use. We demonstrate that adding external RNA spike-ins as a normalization control produces differences in RNA-Seq analysis compared to traditional normalization methods, even between two times of day in untreated plants. We illustrate the use of RNA spike-ins with 3' RNA-Seq and present a normalization pipeline that accounts for differences in total transcriptional levels. We evaluate the effect of normalization methods on identifying differentially expressed genes in the context of identifying the effect of the time of day on gene expression and response to chilling stress in sorghum.

Rna Buffering Fluorogenic Probe for Nucleolar Morphology Stable Imaging And Nucleolar Stress-Generating Agents Screening

In the realm of cell research, membraneless organelles have become a subject of increasing interest. However, their ever-changing and amorphous morphological characteristics have long presented a formidable challenge when it comes to studying their structure and function. In this paper, a fluorescent probe Nu-AN is reported, which exhibits the remarkable capability to selectively bind to and visualize the nucleolus morphology, the largest membraneless organelle within the nucleus. Nu-AN demonstrates a significant enhancement in fluorescence upon its selective binding to nucleolar RNA, due to the inhibited twisted intramolecular charge-transfer (TICT) and reduced hydrogen bonding with water. What sets Nu-AN apart is its neutral charge and weak interaction with nucleolus RNA, enabling it to label the nucleolus selectively and reversibly. This not only reduces interference but also permits the replacement of photobleached probes with fresh ones outside the nucleolus, thereby preserving imaging photostability. By closely monitoring morphology-specific changes in the nucleolus with this buffering fluorogenic probe, screenings for agents are conducted that induce nucleolar stress within living cells.

An ultra high-throughput, massively multiplexable, single-cell RNA-seq platform in yeasts

Yeasts are naturally diverse, genetically tractable, and easy to grow such that researchers can investigate any number of genotypes, environments, or interactions thereof. However, studies of yeast transcriptomes have been limited by the processing capabilities of traditional RNA sequencing techniques. Here we optimize a powerful, high-throughput single-cell RNA sequencing (scRNAseq) platform, SPLiT-seq (Split Pool Ligation-based Transcriptome sequencing), for yeasts and apply it to 43,388 cells of multiple species and ploidies. This platform utilizes a combinatorial barcoding strategy to enable massively parallel RNA sequencing of hundreds of yeast genotypes or growth conditions at once. This method can be applied to most species or strains of yeast for a fraction of the cost of traditional scRNAseq approaches. Thus, our technology permits researchers to leverage "the awesome power of yeast" by allowing us to survey the transcriptome of hundreds of strains and environments in a short period of time and with no specialized equipment. The key to this method is that sequential barcodes are probabilistically appended to cDNA copies of RNA while the molecules remain trapped inside of each cell. Thus, the transcriptome of each cell is labeled with a unique combination of barcodes. Since SPLiT-seq uses the cell membrane as a container for this reaction, many cells can be processed together without the need to physically isolate them from one another in separate wells or droplets. Further, the first barcode in the sequence can be chosen intentionally to identify samples from different environments or genetic backgrounds, enabling multiplexing of hundreds of unique perturbations in a single experiment. In addition to greater multiplexing capabilities, our method also facilitates a deeper investigation of biological heterogeneity, given its single-cell nature. For example, in the data presented here, we detect transcriptionally distinct cell states related to cell cycle, ploidy, metabolic strategies, and so forth, all within clonal yeast populations grown in the same environment. Hence, our technology has two obvious and impactful applications for yeast research: the first is the general study of transcriptional phenotypes across many strains and environments, and the second is investigating cell-to-cell heterogeneity across the entire transcriptome.

RNA fluorescence in situ hybridization (FISH) as a method to visualize bacterial colonization in the C. elegans gut

Caenorhabditis elegans is an excellent model to study host-microbe interactions as it is easy to visualize bacterial presence in their intestine. However, previous studies have shown that utilizing transgenic, fluorescent protein-expressing bacteria is not a reliable method to distinguish living bacteria from dead bacteria in the lumen of C. elegans . In this study, we compared methods for visualizing bacterial presence within the C. elegans intestine and found that RNA f luorescent i n s itu h ybridization (RNA FISH) could distinguish the difference between intact and dead bacteria. Thus, we propose RNA FISH as the preferred method to visualize live bacterial presence in the intestines of C. elegans prior to fixation.

Assessment of different enrichment methods revealed the optimal approach to identify bovine circRnas

Although circular RNAs (circRNAs) play important roles in regulating gene expression, the understanding of circRNAs in livestock animals is scarce due to the significant challenge to characterize them from a biological sample. In this study, we assessed the outcomes of bovine circRNA identification using six enrichment approaches with the combination of ribosomal RNAs removal (Ribo); linear RNAs degradation (R); linear RNAs and RNAs with structured 3' ends degradation (RTP); ribosomal RNAs coupled with linear RNAs elimination (Ribo-R); ribosomal RNA, linear RNAs and RNAs with poly (A) tailing elimination (Ribo-RP); and ribosomal RNA, linear RNAs and RNAs with structured 3' ends elimination (Ribo-RTP), respectively. RNA-sequencing analysis revealed that different approaches led to varied ratio of uniquely mapped reads, false-positive rate of identifying circRNAs, and the number of circRNAs per million clean reads (Padj <0.05). Out of 2,285 and 2,939 highly confident circRNAs identified in liver and rumen tissues, respectively, 308 and 260 were commonly identified from five methods, with Ribo-RTP method identified the highest number of circRNAs. Besides, 507 of 4,051 identified bovine highly confident circRNAs had shared splicing sites with human circRNAs. The findings from this work provide optimized methods to identify bovine circRNAs from cattle tissues for downstream research of their biological roles in cattle.

Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors

BACKGROUND

Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-scale analytical strategy. Many algorithms can deconvolve these tumors using single-cell profiles to infer their composition. While experimental choices do not change the true underlying composition of the tumor, they can affect the measurements produced by the assay.

RESULTS

We generated a dataset of high-grade serous ovarian tumors with paired expression profiles from using multiple strategies to examine the extent to which experimental factors impact the results of downstream tumor deconvolution methods. We find that pooling samples for single-cell sequencing and subsequent demultiplexing has a minimal effect. We identify dissociation-induced differences that affect cell composition, leading to changes that may compromise the assumptions underlying some deconvolution algorithms. We also observe differences across mRNA enrichment methods that introduce additional discrepancies between the two data types. We also find that experimental factors change cell composition estimates and that the impact differs by method.

CONCLUSIONS

Previous benchmarks of deconvolution methods have largely ignored experimental factors. We find that methods vary in their robustness to experimental factors. We provide recommendations for methods developers seeking to produce the next generation of deconvolution approaches and for scientists designing experiments using deconvolution to study tumor heterogeneity.

Sex differences in the transcriptome of extracellular vesicles secreted by fetal neural stem cells and effects of chronic alcohol exposure

BACKGROUND

Prenatal alcohol (ethanol) exposure (PAE) results in brain growth restriction, in part, by reprogramming self-renewal and maturation of fetal neural stem cells (NSCs) during neurogenesis. We recently showed that ethanol resulted in enrichment of both proteins and pro-maturation microRNAs in sub-200-nm-sized extracellular vesicles (EVs) secreted by fetal NSCs. Moreover, EVs secreted by ethanol-exposed NSCs exhibited diminished efficacy in controlling NSC metabolism and maturation. Here we tested the hypothesis that ethanol may also influence the packaging of RNAs into EVs from cell-of-origin NSCs.

METHODS

Sex-specified fetal murine iso-cortical neuroepithelia from three separate pregnancies were maintained ex vivo, as neurosphere cultures to model the early neurogenic niche. EVs were isolated by ultracentrifugation from NSCs exposed to a dose range of ethanol. RNA from paired EV and cell-of-origin NSC samples was processed for ribosomal RNA-depleted RNA sequencing. Differential expression analysis and exploratory weighted gene co-expression network analysis (WGCNA) identified candidate genes and gene networks that were drivers of alterations to the transcriptome of EVs relative to cells.

RESULTS

The RNA content of EVs differed significantly from cell-of-origin NSCs. Biological sex contributed to unique transcriptome variance in EV samples, where > 75% of the most variant transcripts were also sex-variant in EVs but not in cell-of-origin NSCs. WGCNA analysis also identified sex-dependent enrichment of pathways, including dopamine receptor binding and ectoderm formation in female EVs and cell-substrate adhesion in male EVs, with the top significant DEGs from differential analysis of overall individual gene expressions, i.e., Arhgap15, enriched in female EVs, and Cenpa, enriched in male EVs, also serving as WCGNA hub genes of sex-biased EV WGCNA clusters. In addition to the baseline RNA content differences, ethanol exposure resulted in a significant dose-dependent change in transcript expression in both EVs and cell-of-origin NSCs that predominantly altered sex-invariant RNAs. Moreover, at the highest dose, ~ 73% of significantly altered RNAs were enriched in EVs, but depleted in NSCs.

CONCLUSIONS

The EV transcriptome is distinctly different from, and more sex-variant than, the transcriptome of cell-of-origin NSCs. Ethanol, a common teratogen, results in dose-dependent sorting of RNA transcripts from NSCs to EVs which may reprogram the EV-mediated endocrine environment during neurogenesis.

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.

Genomic, epigenomic, and transcriptomic signatures of prostate cancer between African American and European American patients

Prostate cancer is the second most common cancer in men in the United States, and racial disparities are greatly observed in the disease. Specifically, African American (AA) patients have 60% higher incidence and mortality rates, in addition to higher grade and stage prostate tumors, than European American (EA) patients. In order to narrow the gap between clinical outcomes for these two populations, genetic and molecular signatures contributing to this disparity have been characterized. Over the past decade, profiles of prostate tumor samples from different ethnic groups have been developed using molecular and functional assays coupled with next generation sequencing or microarrays. Comparative genome-wide analyses of genomic, epigenomic, and transcriptomic profiles from prostate tumor samples have uncovered potential race-specific mutations, copy number alterations, DNA methylation, and gene expression patterns. In this study, we reviewed over 20 published studies that examined the aforementioned molecular contributions to racial disparities in AA and EA prostate cancer patients. The reviewed genomic studies revealed mutations, deletions, amplifications, duplications, or fusion genes differentially enriched in AA patients relative to EA patients. Commonly reported genomic alterations included mutations or copy number alterations of FOXA1, KMT2D, SPOP, MYC, PTEN, TP53, ZFHX3, and the TMPRSS2-ERG fusion. The reviewed epigenomic studies identified that CpG sites near the promoters of PMEPA1, RARB, SNRPN, and TIMP3 genes were differentially methylated between AA and EA patients. Lastly, the reviewed transcriptomic studies identified genes (e.g. CCL4, CHRM3, CRYBB2, CXCR4, GALR1, GSTM3, SPINK1) and signaling pathways dysregulated between AA and EA patients. The most frequently found dysregulated pathways were involved in immune and inflammatory responses and neuroactive ligand signaling. Overall, we observed that the genomic, epigenomic, and transcriptomic alterations evaluated between AA and EA prostate cancer patients varied between studies, highlighting the impact of using different methods and sample sizes. The reported genomic, epigenomic, and transcriptomic alterations do not only uncover molecular mechanisms of tumorigenesis but also provide researchers and clinicians valuable resources to identify novel biomarkers and treatment modalities to improve the disparity of clinical outcomes between AA and EA patients.

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.

Strategy for RNA-Seq Experimental Design and Data Analysis

Ribonucleic acids (RNAs) are fundamental molecules that control regulation and expression of the genome and therefore the function of a cell. Robust analysis and quantification of RNA transcripts hold critical importance in understanding cell function, altered phenotypes in different biological context, for understanding and targeting diseases. The development of RNA-sequencing (RNA-Seq) now provides opportunities to analyze the expression and function of RNA molecules at an unprecedented scale. However, the strategy for RNA-Seq experimental design and data analysis can substantially differ depending on the biological application. The design choice could also have significant impact for downstream results and interpretation of data. Here we describe key critical considerations required for RNA-Seq experimental design and also describe a step-by-step bioinformatics workflow detailing the different steps required for RNA-Seq data analysis. We believe this article will be a valuable guide for designing and analyzing RNA-Seq data to address a wide range of different biological questions.

Identification of Novel Genes and Proteoforms in Angiostrongylus costaricensis through a Proteogenomic Approach

RNA sequencing (RNA-Seq) and mass-spectrometry-based proteomics data are often integrated in proteogenomic studies to assist in the prediction of eukaryote genome features, such as genes, splicing, single-nucleotide (SNVs), and single-amino-acid variants (SAAVs). Most genomes of parasite nematodes are draft versions that lack transcript- and protein-level information and whose gene annotations rely only on computational predictions. Angiostrongylus costaricensis is a roundworm species that causes an intestinal inflammatory disease, known as abdominal angiostrongyliasis (AA). Currently, there is no drug available that acts directly on this parasite, mostly due to the sparse understanding of its molecular characteristics. The available genome of A. costaricensis, specific to the Costa Rica strain, is a draft version that is not supported by transcript- or protein-level evidence. This study used RNA-Seq and MS/MS data to perform an in-depth annotation of the A. costaricensis genome. Our prediction improved the reference annotation with (a) novel coding and non-coding genes; (b) pieces of evidence of alternative splicing generating new proteoforms; and (c) a list of SNVs between the Brazilian (Crissiumal) and the Costa Rica strain. To the best of our knowledge, this is the first time that a multi-omics approach has been used to improve the genome annotation of A. costaricensis. We hope this improved genome annotation can assist in the future development of drugs, kits, and vaccines to treat, diagnose, and prevent AA caused by either the Brazil strain (Crissiumal) or the Costa Rica strain.

An Evidence-Based Narrative Review of Mechanisms of Resistance Exercise-Induced Human Skeletal Muscle Hypertrophy

Skeletal muscle plays a critical role in physical function and metabolic health. Muscle is a highly adaptable tissue that responds to resistance exercise (RE; loading) by hypertrophying, or during muscle disuse, RE mitigates muscle loss. Resistance exercise training (RET)-induced skeletal muscle hypertrophy is a product of external (e.g., RE programming, diet, some supplements) and internal variables (e.g., mechanotransduction, ribosomes, gene expression, satellite cells activity). RE is undeniably the most potent nonpharmacological external variable to stimulate the activation/suppression of internal variables linked to muscular hypertrophy or countering disuse-induced muscle loss. Here, we posit that despite considerable research on the impact of external variables on RET and hypertrophy, internal variables (i.e., inherent skeletal muscle biology) are dominant in regulating the extent of hypertrophy in response to external stimuli. Thus, identifying the key internal skeletal muscle-derived variables that mediate the translation of external RE variables will be pivotal to determining the most effective strategies for skeletal muscle hypertrophy in healthy persons. Such work will aid in enhancing function in clinical populations, slowing functional decline, and promoting physical mobility. We provide up-to-date, evidence-based perspectives of the mechanisms regulating RET-induced skeletal muscle hypertrophy.

Application of RtcB ligase to monitor self-cleaving ribozyme activity by RNA-seq

Self-cleaving ribozymes are catalytic RNAs and can be found in all domains of life. They catalyze a site-specific cleavage that results in a 5' fragment with a 2',3' cyclic phosphate (2',3' cP) and a 3' fragment with a 5' hydroxyl (5' OH) end. Recently, several strategies to enrich self-cleaving ribozymes by targeted biochemical methods have been introduced by us and others. Here, we develop an alternative strategy in which 5' OH RNAs are specifically ligated by RtcB ligase, which first guanylates the 3' phosphate of the adapter and then ligates it directly to RNAs with 5' OH ends. Our results demonstrate that adapter ligation to highly structured ribozyme fragments is much more efficient using the thermostable RtcB ligase from Pyrococcus horikoshii than the broadly applied Escherichia coli enzyme. Moreover, we investigated DNA, RNA and modified RNA adapters for their suitability in RtcB ligation reactions. We used the optimized RtcB-mediated ligation to produce RNA-seq libraries and captured a spiked 3' twister ribozyme fragment from E. coli total RNA. This RNA-seq-based method is applicable to detect ribozyme fragments as well as other cellular RNAs with 5' OH termini from total RNA.

Diversity and evolution of the animal virome

The COVID-19 pandemic has given the study of virus evolution and ecology new relevance. Although viruses were first identified more than a century ago, we likely know less about their diversity than that of any other biological entity. Most documented animal viruses have been sampled from just two phyla - the Chordata and the Arthropoda - with a strong bias towards viruses that infect humans or animals of economic and social importance, often in association with strong disease phenotypes. Fortunately, the recent development of unbiased metagenomic next-generation sequencing is providing a richer view of the animal virome and shedding new light on virus evolution. In this Review, we explore our changing understanding of the diversity, composition and evolution of the animal virome. We outline the factors that determine the phylogenetic diversity and genomic structure of animal viruses on evolutionary timescales and show how this impacts assessment of the risk of disease emergence in the short term. We also describe the ongoing challenges in metagenomic analysis and outline key themes for future research. A central question is how major events in the evolutionary history of animals, such as the origin of the vertebrates and periodic mass extinction events, have shaped the diversity and evolution of the viruses they carry.

Aging Does Not Exacerbate Muscle Loss During Denervation and Lends Unique Muscle-Specific Atrophy Resistance With Akt Activation

Sarcopenia, or age-related skeletal muscle atrophy and weakness, imposes significant clinical and economic burdens on affected patients and societies. Neurological degeneration, such as motoneuron death, has been recognized as a key contributor to sarcopenia. However, little is known about how aged/sarcopenic muscle adapts to this denervation stress. Here, we show that mice at 27months of age exhibit clear signs of sarcopenia but no accelerated denervation-induced muscle atrophy when compared to 8-month-old mice. Surprisingly, aging lends unique atrophy resistance to tibialis anteria muscle, accompanied by an increase in the cascade of mammalian target of rapamycin complex 1 (mTORC1)-independent anabolic events involving Akt signaling, rRNA biogenesis, and protein synthesis during denervation. These results expand our understanding of age-dependent stress responses and may help develop better countermeasures to sarcopenia.

cyPhyRNA-seq: a genome-scale RNA-seq method to detect active self-cleaving ribozymes by capturing RNAs with 2',3' cyclic phosphates and 5' hydroxyl ends

Self-cleaving ribozymes are catalytically active RNAs that cleave themselves into a 5′-fragment with a 2′,3′-cyclic phosphate and a 3′-fragment with a 5′-hydroxyl. They are widely applied for the construction of synthetic RNA devices and RNA-based therapeutics. However, the targeted discovery of self-cleaving ribozymes remains a major challenge. We developed a transcriptome-wide method, called cyPhyRNA-seq, to screen for ribozyme cleavage fragments in total RNA extract. This approach employs the specific ligation-based capture of ribozyme 5′-fragments using a variant of the Arabidopsis thaliana tRNA ligase we engineered. To capture ribozyme 3′-fragments, they are enriched from total RNA by enzymatic treatments. We optimized and enhanced the individual steps of cyPhyRNA-seq in vitro and in spike-in experiments. Then, we applied cyPhyRNA-seq to total RNA isolated from the bacterium Desulfovibrio vulgaris and detected self-cleavage of the three predicted type II hammerhead ribozymes, whose activity had not been examined to date. cyPhyRNA-seq can be used for the global analysis of active self-cleaving ribozymes with the advantage to capture both ribozyme cleavage fragments from total RNA. Especially in organisms harbouring many self-cleaving RNAs, cyPhyRNA-seq facilitates the investigation of cleavage activity. Moreover, this method has the potential to be used to discover novel self-cleaving ribozymes in different organisms.

Advances in Non-Coding RNA Sequencing

Non-coding RNAs (ncRNAs) comprise a set of abundant and functionally diverse RNA molecules. Since the discovery of the first ncRNA in the 1960s, ncRNAs have been shown to be involved in nearly all steps of the central dogma of molecular biology. In recent years, the pace of discovery of novel ncRNAs and their cellular roles has been greatly accelerated by high-throughput sequencing. Advances in sequencing technology, library preparation protocols as well as computational biology helped to greatly expand our knowledge of which ncRNAs exist throughout the kingdoms of life. Moreover, RNA sequencing revealed crucial roles of many ncRNAs in human health and disease. In this review, we discuss the most recent methodological advancements in the rapidly evolving field of high-throughput sequencing and how it has greatly expanded our understanding of ncRNA biology across a large number of different organisms.

Mining the Microbiome and Microbiota-Derived Molecules in Inflammatory Bowel Disease

The intestinal microbiota is a complex community that consists of an ecosystem with a dynamic interplay between bacteria, fungi, archaea, and viruses. Recent advances in model systems have revealed that the gut microbiome is critical for maintaining homeostasis through metabolic digestive function, immune regulation, and intestinal barrier integrity. Taxonomic shifts in the intestinal microbiota are strongly correlated with a multitude of human diseases, including inflammatory bowel disease (IBD). However, many of these studies have been descriptive, and thus the understanding of the cause and effect relationship often remains unclear. Using non-human experimental model systems such as gnotobiotic mice, probiotic mono-colonization, or prebiotic supplementation, researchers have defined numerous species-level functions of the intestinal microbiota that have produced therapeutic candidates for IBD. Despite these advances, the molecular mechanisms responsible for the function of much of the microbiota and the interplay with host cellular processes remain areas of tremendous research potential. In particular, future research will need to unlock the functional molecular units of the microbiota in order to utilize this untapped resource of bioactive molecules for therapy. This review will highlight the advances and remaining challenges of microbiota-based functional studies and therapeutic discovery, specifically in IBD. One of the limiting factors for reviewing this topic is the nascent development of this area with information on some drug candidates still under early commercial development. We will also highlight the current and evolving strategies, including in the biotech industry, used for the discovery of microbiota-derived bioactive molecules in health and disease.

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.

The Transcriptome of SH-SY5Y at Single-Cell Resolution: A CITE-Seq Data Analysis Workflow

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) is a recently established multimodal single cell analysis technique combining the immunophenotyping capabilities of antibody labeling and cell sorting with the resolution of single-cell RNA sequencing (scRNA-seq). By simply adding a 12-bp nucleotide barcode to antibodies (cell hashing), CITE-seq can be used to sequence antibody-bound tags alongside the cellular mRNA, thus reducing costs of scRNA-seq by performing it at the same time on multiple barcoded samples in a single run. Here, we illustrate an ideal CITE-seq data analysis workflow by characterizing the transcriptome of SH-SY5Y neuroblastoma cell line, a widely used model to study neuronal function and differentiation. We obtained transcriptomes from a total of 2879 single cells, measuring an average of 1600 genes/cell. Along with standard scRNA-seq data handling procedures, such as quality checks and cell filtering procedures, we performed exploratory analyses to identify most stable genes to be possibly used as reference housekeeping genes in qPCR experiments. We also illustrate how to use some popular R packages to investigate cell heterogeneity in scRNA-seq data, namely Seurat, Monocle, and slalom. Both the CITE-seq dataset and the code used to analyze it are freely shared and fully reusable for future research.

Bias in RNA-seq Library Preparation: Current Challenges and Solutions

Although RNA sequencing (RNA-seq) has become the most advanced technology for transcriptome analysis, it also confronts various challenges. As we all know, the workflow of RNA-seq is extremely complicated and it is easy to produce bias. This may damage the quality of RNA-seq dataset and lead to an incorrect interpretation for sequencing result. Thus, our detailed understanding of the source and nature of these biases is essential for the interpretation of RNA-seq data, finding methods to improve the quality of RNA-seq experimental, or development bioinformatics tools to compensate for these biases. Here, we discuss the sources of experimental bias in RNA-seq. And for each type of bias, we discussed the method for improvement, in order to provide some useful suggestions for researcher in RNA-seq experimental.

Optimized design of antisense oligomers for targeted rRNA depletion

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

From Transcriptomics to Treatment in Inherited Optic Neuropathies

Inherited optic neuropathies, including Leber Hereditary Optic Neuropathy (LHON) and Dominant Optic Atrophy (DOA), are monogenetic diseases with a final common pathway of mitochondrial dysfunction leading to retinal ganglion cell (RGC) death and ultimately loss of vision. They are, therefore, excellent models with which to investigate this ubiquitous disease process-implicated in both common polygenetic ocular diseases (e.g., Glaucoma) and late-onset central nervous system neurodegenerative diseases (e.g., Parkinson disease). In recent years, cellular and animal models of LHON and DOA have matured in parallel with techniques (such as RNA-seq) to determine and analyze the transcriptomes of affected cells. This confluence leaves us at a particularly exciting time with the potential for the identification of novel pathogenic players and therapeutic targets. Here, we present a discussion of the importance of inherited optic neuropathies and how transcriptomic techniques can be exploited in the development of novel mutation-independent, neuroprotective therapies.

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.

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.

Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols

In recent years, RNA-sequencing (RNA-seq) has emerged as a powerful technology for transcriptome profiling. For a given gene, the number of mapped reads is not only dependent on its expression level and gene length, but also the sequencing depth. To normalize these dependencies, RPKM (reads per kilobase of transcript per million reads mapped) and TPM (transcripts per million) are used to measure gene or transcript expression levels. A common misconception is that RPKM and TPM values are already normalized, and thus should be comparable across samples or RNA-seq projects. However, RPKM and TPM represent the relative abundance of a transcript among a population of sequenced transcripts, and therefore depend on the composition of the RNA population in a sample. Quite often, it is reasonable to assume that total RNA concentration and distributions are very close across compared samples. Nevertheless, the sequenced RNA repertoires may differ significantly under different experimental conditions and/or across sequencing protocols; thus, the proportion of gene expression is not directly comparable in such cases. In this review, we illustrate typical scenarios in which RPKM and TPM are misused, unintentionally, and hope to raise scientists' awareness of this issue when comparing them across samples or different sequencing protocols.

CoCo: RNA-seq read assignment correction for nested genes and multimapped reads

Motivation

Next-generation sequencing techniques revolutionized the study of RNA expression by permitting whole transcriptome analysis. However, sequencing reads generated from nested and multi-copy genes are often either misassigned or discarded, which greatly reduces both quantification accuracy and gene coverage.

Results

Here we present count corrector (CoCo), a read assignment pipeline that takes into account the multitude of overlapping and repetitive genes in the transcriptome of higher eukaryotes. CoCo uses a modified annotation file that highlights nested genes and proportionally distributes multimapped reads between repeated sequences. CoCo salvages over 15% of discarded aligned RNA-seq reads and significantly changes the abundance estimates for both coding and non-coding RNA as validated by PCR and bedgraph comparisons.

Availability and implementation

The CoCo software is an open source package written in Python and available from http://gitlabscottgroup.med.usherbrooke.ca/scott-group/coco.

Supplementary information

Supplementary data are available at Bioinformatics online.

Transposable elements, circular RNAs and mitochondrial transcription in age-related genomic regulation

Our understanding of the molecular regulation of aging and age-related diseases is still in its infancy, requiring in-depth characterization of the molecular landscape shaping these complex phenotypes. Emerging classes of molecules with promise as aging modulators include transposable elements, circRNAs and the mitochondrial transcriptome. Analytical complexity means that these molecules are often overlooked, even though they exhibit strong associations with aging and, in some cases, may directly contribute to its progress. Here, we review the links between these novel factors and age-related phenotypes, and we suggest tools that can be easily incorporated into existing pipelines to better understand the aging process.

Alterations in Patterns of Gene Expression and Perturbed Pathways in the Gut-Brain Axis Are Associated With Chemotherapy-Induced Nausea

CONTEXT

Despite current advances in antiemetic treatments, approximately 50% of oncology patients experience chemotherapy-induced nausea (CIN).

OBJECTIVES

The purpose of this study was to evaluate for differentially expressed genes and perturbed pathways associated with the gut-brain axis (GBA) across two independent samples of oncology patients who did and did not experience CIN.

METHODS

Oncology patients (n = 735) completed study questionnaires in the week before their second or third cycle of chemotherapy. CIN occurrence was assessed using the Memorial Symptom Assessment Scale. Gene expression analyses were performed in two independent samples using ribonucleic acid sequencing (Sample 1, n = 357) and microarray (Sample 2, n = 352) methodologies. Fisher's combined probability method was used to determine genes that were differentially expressed and pathways that were perturbed between the two nausea groups across both samples.

RESULTS

CIN was reported by 63.6% of the patients in Sample 1 and 48.9% of the patients in Sample 2. Across the two samples, 703 genes were differentially expressed, and 37 pathways were found to be perturbed between the two CIN groups. We identified nine perturbed pathways that are involved in mechanisms associated with alterations in the GBA (i.e., mucosal inflammation, disruption of gut microbiome).

CONCLUSION

Persistent CIN remains a significant clinical problem. Our study is the first to identify novel GBA-related pathways associated with the occurrence of CIN. Our findings warrant confirmation and suggest directions for future clinical studies to decrease CIN occurrence.

Single-molecule analysis of nucleic acid biomarkers - A review

Nucleic acids are important biomarkers for disease detection, monitoring, and treatment. Advances in technologies for nucleic acid analysis have enabled discovery and clinical implementation of nucleic acid biomarkers. However, challenges remain with technologies for nucleic acid analysis, thereby limiting the use of nucleic acid biomarkers in certain contexts. Here, we review single-molecule technologies for nucleic acid analysis that can be used to overcome these challenges. We first discuss the various types of nucleic acid biomarkers important for clinical applications and conventional technologies for nucleic acid analysis. We then discuss technologies for single-molecule in vitro and in situ analysis of nucleic acid biomarkers. Finally, we discuss other ultra-sensitive techniques for nucleic acid biomarker detection.

Efficient depletion of ribosomal RNA for RNA sequencing in planarians

BACKGROUND

The astounding regenerative abilities of planarian flatworms prompt steadily growing interest in examining their molecular foundation. Planarian regeneration was found to require hundreds of genes and is hence a complex process. Thus, RNA interference followed by transcriptome-wide gene expression analysis by RNA-seq is a popular technique to study the impact of any particular planarian gene on regeneration. Typically, the removal of ribosomal RNA (rRNA) is the first step of all RNA-seq library preparation protocols. To date, rRNA removal in planarians was primarily achieved by the enrichment of polyadenylated (poly(A)) transcripts. However, to better reflect transcriptome dynamics and to cover also non-poly(A) transcripts, a procedure for the targeted removal of rRNA in planarians is needed.

RESULTS

In this study, we describe a workflow for the efficient depletion of rRNA in the planarian model species S. mediterranea. Our protocol is based on subtractive hybridization using organism-specific probes. Importantly, the designed probes also deplete rRNA of other freshwater triclad families, a fact that considerably broadens the applicability of our protocol. We tested our approach on total RNA isolated from stem cells (termed neoblasts) of S. mediterranea and compared ribodepleted libraries with publicly available poly(A)-enriched ones. Overall, mRNA levels after ribodepletion were consistent with poly(A) libraries. However, ribodepleted libraries revealed higher transcript levels for transposable elements and histone mRNAs that remained underrepresented in poly(A) libraries. As neoblasts experience high transposon activity this suggests that ribodepleted libraries better reflect the transcriptional dynamics of planarian stem cells. Furthermore, the presented ribodepletion procedure was successfully expanded to the removal of ribosomal RNA from the gram-negative bacterium Salmonella typhimurium.

CONCLUSIONS

The ribodepletion protocol presented here ensures the efficient rRNA removal from low input total planarian RNA, which can be further processed for RNA-seq applications. Resulting libraries contain less than 2% rRNA. Moreover, for a cost-effective and efficient removal of rRNA prior to sequencing applications our procedure might be adapted to any prokaryotic or eukaryotic species of choice.

Next generation sequencing and RNA-seq characterization of adipose tissue in the Nile crocodile (Crocodylus niloticus) in South Africa: Possible mechanism(s) of pathogenesis and pathophysiology of pansteatitis

BACKGROUND

Concerted efforts to identify the pathogenesis and mechanism(s) involved in pansteatitis, (a generalized inflammation of the adipose tissue), that was attributed to the recent crocodile die off in the Olifants River and Loskop Dam in Kruger National Park, Mpumalanga, South Africa have been in the forefront of research in recent time. As part of the efforts, molecular characterization of healthy and pansteatitis adipose tissue was carried out by RNA sequencing (RNA-Seq) using Next Generation Sequencing (NGS) and de novo assembly of the adipose transcriptome, followed by differential gene expression analysis.

METHODOLOGY

Healthy adipose tissue consisting of fifty samples was collected from the subcutaneous, visceral, intermuscular adipose tissues and the abdominal fat body of ten 4 years old juvenile crocodiles from a local crocodile farm in Pretoria, South Africa. Ten pansteatitis samples were collected from visceral and intermuscular adipose tissues of five crocodiles that were dying of pansteatitis.

RESULTS

Forty-two thousand, two hundred and one (42,201) transcripts were assembled, out of which 37, 835 had previously been characterized. The de novo assembled transcriptome had an N50 (average sequence) of 436 bp, percentage GC content of 43.92, which compared well with previously assembled transcripts in the saltwater crocodile. Seventy genes were differentially expressed and upregulated in pansteatitis. These included genes coding for extracellular matrix (ECM) signaling ligands, inflammatory cytokines and tumour necrosis factor alpha (TNFα) receptors, fatty acid synthase and fatty acid binding proteins, peroxisome proliferator-activated receptor gamma (PPARγ), nuclear factor and apoptosis signaling ligands, and mitogen activated protein kinase enzymes among others. Majority (88.6%) of the upregulated genes were found to be involved in hypoxia inducible pathways for activation of NFkβ and inflammation, apoptosis, Toll-like receptor pathway and PPARγ. Bicaudal homologous 2 Drosophila gene (BICD2) associated with spinal and lower extremity muscle atrophy was also upregulated in pansteatitis while Sphingosine -1-phosphate phosphatase 2 (SGPP2) involved in Sphingosine -1- phosphate metabolism was downregulated. Futhermore, Doublesex-mab-related transcription factor 1 (DMRT1) responsible for sex gonad development and germ cell differentiation was also downregulated.

CONCLUSION

Thus, from the present study, based on differentially expressed genes in pansteatitis, affected Nile crocodiles might have died partly due to their inability to utilize stored triglycerides as a result of inflammation induced insulin resistance, leading to starvation in the midst of plenty. Affected animals may have also suffered muscular atrophy of the lower extremities and poor fertility.

Non-invasive Potential Circulating mRNA Markers for Colorectal Adenoma Using Targeted Sequencing

We have developed an optimized protocol for plasma targeted mRNA sequencing in our previous study. Here, we performed plasma targeted mRNA sequencing for 40 colorectal adenoma patients and 39 colonoscopy-proven normal controls in order to find potential circulating mRNA markers for colorectal adenoma. Results showed that GSK3A and RHOA were differential expressed genes identified by a cut-off of fold change >2 and adjusted P value < 0.05. More detailed analysis showed that the expression of both GSK3A (0.01-fold with adjusted P < 1 × 10^-6) and RHOA (0.35-fold with adjusted P < 0.01) in adenoma patients was significantly lower than those in normal healthy subjects. Based on the enrichment analysis of biological process for potential markers, we found that the regulation of programmed cell death (GO: 0043067; GO: 0043069), regulation of cell death (GO: 0010941; GO: 0060548) and cell differentiation (GO: 0021861) were the main processes involved in adenoma formation. In summary, this study is a cutting-edge research on the detection of plasma mRNA in colorectal adenoma patients and normal healthy subjects.

MOTS-c: A Mitochondrial-Encoded Regulator of the Nucleus

Mitochondria are increasingly being recognized as information hubs that sense cellular changes and transmit messages to other cellular components, such as the nucleus, the endoplasmic reticulum (ER), the Golgi apparatus, and lysosomes. Nonetheless, the interaction between mitochondria and the nucleus is of special interest because they both host part of the cellular genome. Thus, the communication between genome-bearing organelles would likely include gene expression regulation. Multiple nuclear-encoded proteins have been known to regulate mitochondrial gene expression. On the contrary, no mitochondrial-encoded factors are known to actively regulate nuclear gene expression. MOTS-c (mitochondrial open reading frame of the 12S ribosomal RNA type-c) is a recently identified peptide encoded within the mitochondrial 12S ribosomal RNA gene that has metabolic functions. Notably, MOTS-c can translocate to the nucleus upon metabolic stress (e.g., glucose restriction and oxidative stress) and directly regulate adaptive nuclear gene expression to promote cellular homeostasis. It is hypothesized that cellular fitness requires the coevolved mitonuclear genomes to coordinate adaptive responses using gene-encoded factors that cross-regulate the opposite genome. This suggests that cellular gene expression requires the bipartite split genomes to operate as a unified system, rather than the nucleus being the sole master regulator.

The Nucleolus: A Multiphase Condensate Balancing Ribosome Synthesis and Translational Capacity in Health, Aging and Ribosomopathies

The nucleolus is the largest membrane-less structure in the eukaryotic nucleus. It is involved in the biogenesis of ribosomes, essential macromolecular machines responsible for synthesizing all proteins required by the cell. The assembly of ribosomes is evolutionarily conserved and is the most energy-consuming cellular process needed for cell growth, proliferation, and homeostasis. Despite the significance of this process, the intricate pathophysiological relationship between the nucleolus and protein synthesis has only recently begun to emerge. Here, we provide perspective on new principles governing nucleolar formation and the resulting multiphase organization driven by liquid-liquid phase separation. With recent advances in the structural analysis of ribosome formation, we highlight the current understanding of the step-wise assembly of pre-ribosomal subunits and the quality control required for proper function. Finally, we address how aging affects ribosome genesis and how genetic defects in ribosome formation cause ribosomopathies, complex diseases with a predisposition to cancer.

Comparison of library construction kits for mRNA sequencing in the Illumina platform

BACKGROUND

The emergence of next-generation sequencing (NGS) technologies has made a tremendous contribution to the deciphering and significance of transcriptome analysis in biological fields. Since the advent of NGS technology in 2007, Illumina, Inc. has provided one of the most widely used sequencing platforms for NGS analysis.

OBJECTIVE

Although reagents and protocols provided by Illumina are adequately performed in transcriptome sequencing, recently, alternative reagents and protocols which are relatively cost effective are accessible. However, the kits derived from various manufacturers have advantages and disadvantages when researchers carry out the transcriptome library construction.

METHODS

We compared them using a variety of protocols to produce Illumina-compatible libraries based on transcriptome. Three different mRNA sequencing kits were selected for this study: TruSeq^® RNA Sample Preparation V2 (Illumina, Inc., USA), Universal Plus mRNA-Seq (NuGEN, Ltd., UK), and NEBNext^® Ultra™ Directional RNA Library Prep Kit for Illumina^® (New England BioLabs, Ltd., USA). We compared them focusing on cost, experimental time, and data output.

RESULTS

The quality and quantity of sequencing data obtained through the NGS technique were strongly influenced by the type of the sequencing library kits. It suggests that for transcriptome studies, researchers should select a suitable library construction kit according to the goal and resources of experiments.

CONCLUSION

The present work will help researchers to choose the right sequencing library construction kit for transcriptome analyses.

Systematic evaluation of RNA-Seq preparation protocol performance

Background

RNA-Seq is currently the most widely used tool to analyze whole-transcriptome profiles. There are numerous commercial kits available to facilitate preparing RNA-Seq libraries; however, it is still not clear how some of these kits perform in terms of: 1) ribosomal RNA removal; 2) read coverage or recovery of exonic vs. intronic sequences; 3) identification of differentially expressed genes (DEGs); and 4) detection of long non-coding RNA (lncRNA). In RNA-Seq analysis, understanding the strengths and limitations of commonly used RNA-Seq library preparation protocols is important, as this technology remains costly and time-consuming.

Results

In this study, we present a comprehensive evaluation of four RNA-Seq kits. We used three standard input protocols: Illumina TruSeq Stranded Total RNA and mRNA kits, a modified NuGEN Ovation v2 kit, and the TaKaRa SMARTer Ultra Low RNA Kit v3. Our evaluation of these kits included quality control measures such as overall reproducibility, 5′ and 3′ end-bias, and the identification of DEGs, lncRNAs, and alternatively spliced transcripts. Overall, we found that the two Illumina kits were most similar in terms of recovering DEGs, and the Illumina, modified NuGEN, and TaKaRa kits allowed identification of a similar set of DEGs. However, we also discovered that the Illumina, NuGEN and TaKaRa kits each enriched for different sets of genes.

Conclusions

At the manufacturers’ recommended input RNA levels, all the RNA-Seq library preparation protocols evaluated were suitable for distinguishing between experimental groups, and the TruSeq Stranded mRNA kit was universally applicable to studies focusing on protein-coding gene profiles. The TruSeq protocols tended to capture genes with higher expression and GC content, whereas the modified NuGEN protocol tended to capture longer genes. The SMARTer Ultra Low RNA Kit may be a good choice at the low RNA input level, although it was inferior to the TruSeq mRNA kit at standard input level in terms of rRNA removal, exonic mapping rates and recovered DEGs. Therefore, the choice of RNA-Seq library preparation kit can profoundly affect data outcomes. Consequently, it is a pivotal parameter to consider when designing an RNA-Seq experiment.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5953-1) contains supplementary material, which is available to authorized users.

Cloudy with a Chance of Insights: Context Dependent Gene Regulation and Implications for Evolutionary Studies

Research in various fields of evolutionary biology has shown that divergence in gene expression is a key driver for phenotypic evolution. An exceptional contribution of cis-regulatory divergence has been found to contribute to morphological diversification. In the light of these findings, the analysis of genome-wide expression data has become one of the central tools to link genotype and phenotype information on a more mechanistic level. However, in many studies, especially if general conclusions are drawn from such data, a key feature of gene regulation is often neglected. With our article, we want to raise awareness that gene regulation and thus gene expression is highly context dependent. Genes show tissue- and stage-specific expression. We argue that the regulatory context must be considered in comparative expression studies.

Clinical metagenomics

Clinical metagenomic next-generation sequencing (mNGS), the comprehensive analysis of microbial and host genetic material (DNA and RNA) in samples from patients, is rapidly moving from research to clinical laboratories. This emerging approach is changing how physicians diagnose and treat infectious disease, with applications spanning a wide range of areas, including antimicrobial resistance, the microbiome, human host gene expression (transcriptomics) and oncology. Here, we focus on the challenges of implementing mNGS in the clinical laboratory and address potential solutions for maximizing its impact on patient care and public health.

RNA-sequencing in ophthalmology research: considerations for experimental design and analysis

High-throughput, massively parallel sequence analysis has revolutionized the way that researchers design and execute scientific investigations. Vast amounts of sequence data can be generated in short periods of time. Regarding ophthalmology and vision research, extensive interrogation of patient samples for underlying causative DNA mutations has resulted in the discovery of many new genes relevant to eye disease. However, such analysis remains functionally limited. RNA-sequencing accurately snapshots thousands of genes, capturing many subtypes of RNA molecules, and has become the gold standard for transcriptome gene expression quantification. RNA-sequencing has the potential to advance our understanding of eye development and disease; it can reveal new candidates to improve our molecular diagnosis rates and highlight therapeutic targets for intervention. But with a wide range of applications, the design of such experiments can be problematic, no single optimal pipeline exists, and therefore, several considerations must be undertaken for optimal study design. We review the key steps involved in RNA-sequencing experimental design and the downstream bioinformatic pipelines used for differential gene expression. We provide guidance on the application of RNA-sequencing to ophthalmology and sources of open-access eye-related data sets.

Identification and genetic characterization of a novel Orthobunyavirus species by a straightforward high-throughput sequencing-based approach

Identification and characterization of novel unknown viruses is of great importance. The introduction of high-throughput sequencing (HTS)-based methods has paved the way for genomics-based detection of pathogens without any prior assumptions about the characteristics of the organisms. However, the use of HTS for the characterization of viral pathogens from clinical samples remains limited. Here, we report the identification of a novel Orthobunyavirus species isolated from horse plasma. The identification was based on a straightforward HTS approach. Following enrichment in cell culture, RNA was extracted from the growth medium and rapid library preparation, HTS and primary bioinformatic analyses were performed in less than 12 hours. Taxonomical profiling of the sequencing reads did not reveal sequence similarities to any known virus. Subsequent application of de novo assembly tools to the sequencing reads produced contigs, of which three showed some similarity to the L, M, and S segments of viruses belonging to the Orthobunyavirus genus. Further refinement of these contigs resulted in high-quality, full-length genomic sequences of the three genomic segments (L, M and S) of a novel Orthobunyavirus. Characterization of the genomic sequence, including the prediction of open reading frames and the inspection of consensus genomic termini and phylogenetic analysis, further confirmed that the novel virus is indeed a new species, which we named Ness Ziona virus.

Mapping the dsRNA World

Long double-stranded RNAs (dsRNAs) are abundantly expressed in animals, in which they frequently occur in introns and 3' untranslated regions of mRNAs. Functions of long, cellular dsRNAs are poorly understood, although deficiencies in adenosine deaminases that act on RNA, or ADARs, promote their recognition as viral dsRNA and an aberrant immune response. Diverse dsRNA-binding proteins bind cellular dsRNAs, hinting at additional roles. Understanding these roles is facilitated by mapping the genomic locations that express dsRNA in various tissues and organisms. ADAR editing provides a signature of dsRNA structure in cellular transcripts. In this review, we detail approaches to map ADAR editing sites and dsRNAs genome-wide, with particular focus on high-throughput sequencing methods and considerations for their successful application to the detection of editing sites and dsRNAs.

Regulation of Ribosome Biogenesis in Skeletal Muscle Hypertrophy

The ribosome is the enzymatic macromolecular machine responsible for protein synthesis. The rates of protein synthesis are primarily dependent on translational efficiency and capacity. Ribosome biogenesis has emerged as an important regulator of skeletal muscle growth and maintenance by altering the translational capacity of the cell. Here, we provide evidence to support a central role for ribosome biogenesis in skeletal muscle growth during postnatal development and in response to resistance exercise training. Furthermore, we discuss the cellular signaling pathways regulating ribosome biogenesis, discuss how myonuclear accretion affects translational capacity, and explore future areas of investigation within the field.

Fundamentals of RNA Analysis on Biobanked Specimens

Compared to DNA, analysis of RNA is one step closer on the central dogma of biology to assessing cellular function. This makes it an extremely valuable target for research and clinical testing in nearly all areas of molecular biology. Most RNA molecules are ephemeral by nature. They exist as temporary intermediates, ostensibly enabling data transfer between the genome and the organism. Their ribose backbone renders them sensitive to simple degradation over time and they are the target molecule for numerous and abundant ribonucleases which have evolved to chop them to pieces with extreme efficiency. At the biochemical level, this means that they degrade rapidly in most physiological and laboratory conditions and are thus challenging to study. When considering specimen banking, it is critical to keep this reality in mind, as some commonly used banking modalities will not adequately preserve the relevant RNA molecules in a measureable state.In this chapter, we explore the broad range of RNA testing methodologies in current use, with particular focus on how specimen preparation impacts analysis. Following an overview in the introduction, Subheading 2 covers the major specimen types amenable to RNA analysis in the context of biobanking. Subheading 3 discusses the applications of various RNA analysis modalities to research and clinical testing.