RNAseq by Total RNA Library Identifies Additional RNAs Compared to Poly(A) RNA Library

An improved bacterial mRNA enrichment strategy in dual RNA sequencing to unveil the dynamics of plant-bacterial interactions

BACKGROUND

Dual RNA sequencing is a powerful tool that enables a comprehensive understanding of the molecular dynamics underlying plant-microbe interactions. RNA sequencing (RNA-seq) poses technical hurdles in the transcriptional analysis of plant-bacterial interactions, especially in bacterial transcriptomics, owing to the presence of abundant ribosomal RNA (rRNA), which potentially limits the coverage of essential transcripts. Therefore, to achieve cost-effective and comprehensive sequencing of the bacterial transcriptome, it is imperative to devise efficient methods for eliminating rRNA and enhancing the proportion of bacterial mRNA. In this study, we modified a strand-specific dual RNA-seq method with the goal of enriching the proportion of bacterial mRNA in the bacteria-infected plant samples. The enriched method involved the sequential separation of plant mRNA by poly A selection and rRNA removal for bacterial mRNA enrichment followed by strand specific RNA-seq library preparation steps. We assessed the efficiency of the enriched method in comparison to the conventional method by employing various plant-bacterial interactions, including both host and non-host resistance interactions with pathogenic bacteria, as well as an interaction with a beneficial rhizosphere associated bacteria using pepper and tomato plants respectively.

RESULTS

In all cases of plant-bacterial interactions examined, an increase in mapping efficiency was observed with the enriched method although it produced a lower read count. Especially in the compatible interaction with Xanthmonas campestris pv. Vesicatoria race 3 (Xcv3), the enriched method enhanced the mapping ratio of Xcv3-infected pepper samples to its own genome (15.09%; 1.45-fold increase) and the CDS (8.92%; 1.49-fold increase). The enriched method consistently displayed a greater number of differentially expressed genes (DEGs) than the conventional RNA-seq method at all fold change threshold levels investigated, notably during the early stages of Xcv3 infection in peppers. The Gene Ontology (GO) enrichment analysis revealed that the DEGs were predominantly enriched in proteolysis, kinase, serine type endopeptidase and heme binding activities.

CONCLUSION

The enriched method demonstrated in this study will serve as a suitable alternative to the existing RNA-seq method to enrich bacterial mRNA and provide novel insights into the intricate transcriptomic alterations within the plant-bacterial interplay.

Comparison of RNA-Sequencing Methods for Degraded RNA

RNA sequencing (RNA-Seq) is a powerful technique and is increasingly being used in clinical research and drug development. Currently, several RNA-Seq methods have been developed. However, the relative advantage of each method for degraded RNA and low-input RNA, such as RNA samples collected in the field of clinical setting, has remained unknown. The Standard method of RNA-Seq captures mRNA by poly(A) capturing using Oligo dT beads, which is not suitable for degraded RNA. Here, we used three commercially available RNA-Seq library preparation kits (SMART-Seq, xGen Broad-range, and RamDA-Seq) using random primer instead of Oligo dT beads. To evaluate the performance of these methods, we compared the correlation, the number of detected expressing genes, and the expression levels with the Standard RNA-Seq method. Although the performance of RamDA-Seq was similar to that of Standard RNA-Seq, the performance for low-input RNA and degraded RNA has decreased. The performance of SMART-Seq was better than xGen and RamDA-Seq in low-input RNA and degraded RNA. Furthermore, the depletion of ribosomal RNA (rRNA) improved the performance of SMART-Seq and xGen due to increased expression levels. SMART-Seq with rRNA depletion has relative advantages for RNA-Seq using low-input and degraded RNA.

Long non-coding RNAs mediate fish gene expression in response to ocean acidification

The majority of the transcribed genome does not have coding potential but these non-coding transcripts play crucial roles in transcriptional and post-transcriptional regulation of protein-coding genes. Regulation of gene expression is important in shaping an organism's response to environmental changes, ultimately impacting their survival and persistence as population or species face global change. However, the roles of long non-coding RNAs (lncRNAs), when confronted with environmental changes, remain largely unclear. To explore the potential role of lncRNAs in fish exposed to ocean acidification (OA), we analyzed publicly available brain RNA-seq data from a coral reef fish Acanthochromis polyacanthus. We annotated the lncRNAs in its genome and examined the expression changes of intergenic lncRNAs (lincRNAs) between A. polyacanthus samples from a natural CO2 seep and a nearby control site. We identified 4728 lncRNAs, including 3272 lincRNAs in this species. Remarkably, 93.03% of these lincRNAs were species-specific. Among the 125 highly expressed lincRNAs and 403 differentially expressed lincRNAs in response to elevated CO2, we observed that lincRNAs were either neighboring or potentially trans-regulating differentially expressed coding genes associated with pH regulation, neural signal transduction, and ion transport, which are known to be important in the response to OA in fish. In summary, lncRNAs may facilitate fish acclimation and mediate the responses of fish to OA by modulating the expression of crucial coding genes, which offers insight into the regulatory mechanisms underlying fish responses to environmental changes.

MEG3 Expression Indicates Lymph Node Metastasis and Presence of Cancer-Associated Fibroblasts in Papillary Thyroid Cancer

Papillary thyroid cancer is the most common endocrine malignancy, occurring at an incidence rate of 12.9 per 100,000 in the US adult population. While the overall 10-year survival of PTC nears 95%, the presence of lymph node metastasis (LNM) or capsular invasion indicates the need for extensive neck dissection with possible adjuvant radioactive iodine therapy. While imaging modalities such as ultrasound and CT are currently in use for the detection of suspicious cervical lymph nodes, their sensitivities for tumor-positive nodes are low. Therefore, advancements in preoperative detection of LNM may optimize the surgical and medical management of patients with thyroid cancer. To this end, we analyzed bulk RNA-sequencing datasets to identify candidate markers highly predictive of LNM. We identified MEG3, a long-noncoding RNA previously described as a tumor suppressor when expressed in malignant cells, as highly associated with LNM tissue. Furthermore, the expression of MEG3 was highly predictive of tumor infiltration with cancer-associated fibroblasts, and single-cell RNA-sequencing data revealed the expression of MEG3 was isolated to cancer-associated fibroblasts (CAFs) in the most aggressive form of thyroid cancers. Our findings suggest that MEG3 expression, specifically in CAFs, is highly associated with LNM and may be a driver of aggressive disease.

RNA Sequencing Unveils Very Small RNAs With Potential Regulatory Functions in Bacteria

RNA sequencing (RNA-seq) is the gold standard for the discovery of small non-coding RNAs. Following a long-standing approach, reads shorter than 16 nucleotides (nt) are removed from the small RNA sequencing libraries or datasets. The serendipitous discovery of an eukaryotic 12 nt-long RNA species capable of modulating the microRNA from which they derive prompted us to challenge this dogma and, by expanding the window of RNA sizes down to 8 nt, to confirm the existence of functional very small RNAs (vsRNAs <16 nt). Here we report the detailed profiling of vsRNAs in Escherichia coli, E. coli-derived outer membrane vesicles (OMVs) and five other bacterial strains (Pseudomonas aeruginosa PA7, P. aeruginosa PAO1, Salmonella enterica serovar Typhimurium 14028S, Legionella pneumophila JR32 Philadelphia-1 and Staphylococcus aureus HG001). vsRNAs of 8–15 nt in length [RNAs (8-15 nt)] were found to be more abundant than RNAs of 16–30 nt in length [RNAs (16–30 nt)]. vsRNA biotypes were distinct and varied within and across bacterial species and accounted for one third of reads identified in the 8–30 nt window. The tRNA-derived fragments (tRFs) have appeared as a major biotype among the vsRNAs, notably Ile-tRF and Ala-tRF, and were selectively loaded in OMVs. tRF-derived vsRNAs appear to be thermodynamically stable with at least 2 G-C basepairs and stem-loop structure. The analyzed tRF-derived vsRNAs are predicted to target several human host mRNAs with diverse functions. Bacterial vsRNAs and OMV-derived vsRNAs could be novel players likely modulating the intricate relationship between pathogens and their hosts.

A simple guide to de novo transcriptome assembly and annotation

A transcriptome constructed from short-read RNA sequencing (RNA-seq) is an easily attainable proxy catalog of protein-coding genes when genome assembly is unnecessary, expensive or difficult. In the absence of a sequenced genome to guide the reconstruction process, the transcriptome must be assembled de novo using only the information available in the RNA-seq reads. Subsequently, the sequences must be annotated in order to identify sequence-intrinsic and evolutionary features in them (for example, protein-coding regions). Although straightforward at first glance, de novo transcriptome assembly and annotation can quickly prove to be challenging undertakings. In addition to familiarizing themselves with the conceptual and technical intricacies of the tasks at hand and the numerous pre- and post-processing steps involved, those interested must also grapple with an overwhelmingly large choice of tools. The lack of standardized workflows, fast pace of development of new tools and techniques and paucity of authoritative literature have served to exacerbate the difficulty of the task even further. Here, we present a comprehensive overview of de novo transcriptome assembly and annotation. We discuss the procedures involved, including pre- and post-processing steps, and present a compendium of corresponding tools.

Noncoding RNAs in Papillary Thyroid Cancer: Interaction with Cancer-Associated Fibroblasts (CAFs) in the Tumor Microenvironment (TME) and Regulators of Differentiation and Lymph Node Metastasis

A large majority of all thyroid cancers are papillary thyroid carcinomas (PTC), named for the specific papillary architecture observed histologically. Despite the high rate of success with modern diagnostic and therapeutic algorithms, there are significant areas where the management of PTC can be improved. Aggressive PTC subtypes that are refractory to radioactive iodine (RAI) therapy carry a more severe prognosis and account for most of PTC-related deaths. As lymph node metastasis is present in roughly 40% of all adult PTC cases, higher specificity in these tests is a clinical need, especially since lymph node metastases are associated with reduced survival and higher recurrence rates. Additionally, this cancer can progress to more dedifferentiated and aggressive variants, such as poorly differentiated papillary thyroid cancer (PDPTC) and anaplastic thyroid cancer (ATC). Therefore, development of more sensitive and specific detection methods that allow unnecessary surgeries to be avoided is of the utmost importance. The body of large-scale, unbiased gene expression analysis in PTC has focused on the coding transcriptome, specifically mRNAs and microRNAs. However, there have been implications for the potential use of long noncoding RNAs (lncRNAs) in PTC diagnosis, prognosis, and treatment via the utilization of genome-wide studies of patient samples. lncRNAs have diverse regulatory potential in gene expression, alternative splicing, posttranscriptional mRNA modification, and epigenomic alterations. Many lncRNAs have tissue-specific expression and are demonstrated to play key roles in cancer progression and prognosis. However, lncRNAs are not being exploited as biomarkers or therapeutic targets currently, despite their elucidated effects on oncogenesis. These potent biomarkers would be revolutionary in detection at early stages, as this significantly increases the chances of survival. Their aberrant expression in cancer and correlation with steps in tumorigenesis as well as their role in differentiation would allow for a promising role as a prognostic and diagnostic biomarker in thyroid cancer. This would help prevent the more aggressive ATC that derives from dedifferentiation of the less aggressive PTC and FTC. The targeting of the specific lncRNAs could also pose a valuable treatment option via preventing or reversing this dedifferentiation process and making this usually refractory form of thyroid cancer more responsive to standard treatment options.

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.

ALKBH3 partner ASCC3 mediates P-body formation and selective clearance of MMS-induced 1-methyladenosine and 3-methylcytosine from mRNA

Background

Reversible enzymatic methylation of mammalian mRNA is widespread and serves crucial regulatory functions, but little is known to what degree chemical alkylators mediate overlapping modifications and whether cells distinguish aberrant from canonical methylations.

Methods

Here we use quantitative mass spectrometry to determine the fate of chemically induced methylbases in the mRNA of human cells. Concomitant alteration in the mRNA binding proteome was analyzed by SILAC mass spectrometry.

Results

MMS induced prominent direct mRNA methylations that were chemically identical to endogenous methylbases. Transient loss of 40S ribosomal proteins from isolated mRNA suggests that aberrant methylbases mediate arrested translational initiation and potentially also no-go decay of the affected mRNA. Four proteins (ASCC3, YTHDC2, TRIM25 and GEMIN5) displayed increased mRNA binding after MMS treatment. ASCC3 is a binding partner of the DNA/RNA demethylase ALKBH3 and was recently shown to promote disassembly of collided ribosomes as part of the ribosome quality control (RQC) trigger complex. We find that ASCC3-deficient cells display delayed removal of MMS-induced 1-methyladenosine (m¹A) and 3-methylcytosine (m³C) from mRNA and impaired formation of MMS-induced P-bodies.

Conclusions

Our findings conform to a model in which ASCC3-mediated disassembly of collided ribosomes allows demethylation of aberrant m¹A and m³C by ALKBH3. Our findings constitute first evidence of selective sanitation of aberrant mRNA methylbases over their endogenous counterparts and warrant further studies on RNA-mediated effects of chemical alkylators commonly used in the clinic.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02948-6.

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.

Functional long non-coding and circular RNAs in zebrafish

The utility of model organisms to understand the function of a novel transcript/genes has allowed us to delineate their molecular mechanisms in maintaining cellular homeostasis. Organisms such as zebrafish have contributed a lot in the field of developmental and disease biology. Attributable to advancement and deep transcriptomics, many new transcript isoforms and non-coding RNAs such as long noncoding RNA (lncRNA) and circular RNAs (circRNAs) have been identified and cataloged in multiple databases and many more are yet to be identified. Various methods and tools have been utilized to identify lncRNAs/circRNAs in zebrafish using deep sequencing of transcriptomes as templates. Functional analysis of a few candidates such as tie1-AS, ECAL1 and CDR1as in zebrafish provides a prospective outline to approach other known or novel lncRNA/circRNA. New genetic alteration tools like TALENS and CRISPRs have helped in probing for the molecular function of lncRNA/circRNA in zebrafish. Further latest improvements in experimental and computational techniques offer the identification of lncRNA/circRNA counterparts in humans and zebrafish thereby allowing easy modeling and analysis of function at cellular level.

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.

In Silico and In Vitro Analysis of lncRNA XIST Reveals a Panel of Possible Lung Cancer Regulators and a Five-Gene Diagnostic Signature

Simple Summary

Long non-coding RNAs (lncRNA) have been associated with a number of diseases including cancer. A well-studied lncRNA called XIST (X-inactive specific transcript) acts as a major effector of the X-inactivation process. It is expressed on the inactive X chromosome providing a dosage equivalence between males and females. Recently XIST has been implicated in the development of lung cancer. Using a bioinformatics approach, we demonstrate the XIST is over-expressed in female patients compared to males. When XIST gene was silenced in two different cell lines (of male and female origin), a number of genes were differentially expressed; playing a role in signal transduction pathways, energy balance and metabolism, thus providing a better insight of the role of this lncRNA in cancer. Finally, we showed that expression of XIST with another 4 genes provided a strong diagnostic potential to discriminate lung cancer from healthy controls.

Abstract

Long non-coding RNAs (lncRNAs) perform a wide functional repertoire of roles in cell biology, ranging from RNA editing to gene regulation, as well as tumour genesis and tumour progression. The lncRNA X-inactive specific transcript (XIST) is involved in the aetiopathogenesis of non-small cell lung cancer (NSCLC). However, its role at the molecular level is not fully elucidated. The expression of XIST and co-regulated genes TSIX, hnRNPu, Bcl-2, and BRCA1 analyses in lung cancer (LC) and controls were performed in silico. Differentially expressed genes (DEGs) were determined using RNA-seq in H1975 and A549 NSCLC cell lines following siRNA for XIST. XIST exhibited sexual dimorphism, being up-regulated in females compared to males in both control and LC patient cohorts. RNA-seq revealed 944 and 751 DEGs for A549 and H1975 cell lines, respectively. These DEGs are involved in signal transduction, cell communication, energy pathways, and nucleic acid metabolism. XIST expression associated with TSIX, hnRNPu, Bcl-2, and BRCA1 provided a strong collective feature to discriminate between controls and LC, implying a diagnostic potential. There is a much more complex role for XIST in lung cancer. Further studies should concentrate on sex-specific changes and investigate the signalling pathways of the DEGs following silencing of this lncRNA.

Covering all your bases: incorporating intron signal from RNA-seq data

RNA-seq datasets can contain millions of intron reads per library that are typically removed from downstream analysis. Only reads overlapping annotated exons are considered to be informative since mature mRNA is assumed to be the major component sequenced, especially for poly(A) RNA libraries. In this study, we show that intron reads are informative, and through exploratory data analysis of read coverage that intron signal is representative of both pre-mRNAs and intron retention. We demonstrate how intron reads can be utilized in differential expression analysis using our index method where a unique set of differentially expressed genes can be detected using intron counts. In exploring read coverage, we also developed the superintronic software that quickly and robustly calculates user-defined summary statistics for exonic and intronic regions. Across multiple datasets, superintronic enabled us to identify several genes with distinctly retained introns that had similar coverage levels to that of neighbouring exons. The work and ideas presented in this paper is the first of its kind to consider multiple biological sources for intron reads through exploratory data analysis, minimizing bias in discovery and interpretation of results. Our findings open up possibilities for further methods development for intron reads and RNA-seq data in general.

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.

Transcriptome Analysis Reveals the Molecular Mechanisms Underlying Adenosine Biosynthesis in Anamorph Strain of Caterpillar Fungus

Caterpillar fungus is a well-known fungal Chinese medicine. To reveal molecular changes during early and late stages of adenosine biosynthesis, transcriptome analysis was performed with the anamorph strain of caterpillar fungus. A total of 2,764 differentially expressed genes (DEGs) were identified (p ≤ 0.05, |log₂ Ratio| ≥ 1), of which 1,737 were up-regulated and 1,027 were down-regulated. Gene expression profiling on 4–10 d revealed a distinct shift in expression of the purine metabolism pathway. Differential expression of 17 selected DEGs which involved in purine metabolism (map00230) were validated by qPCR, and the expression trends were consistent with the RNA-Seq results. Subsequently, the predicted adenosine biosynthesis pathway combined with qPCR and gene expression data of RNA-Seq indicated that the increased adenosine accumulation is a result of down-regulation of ndk, ADK, and APRT genes combined with up-regulation of AK gene. This study will be valuable for understanding the molecular mechanisms of the adenosine biosynthesis in caterpillar fungus.

Temporal changes in the spinal cord transcriptome after peripheral nerve injury

Peripheral nerve injury may trigger changes in mRNA levels in the spinal cord. Finding key mRNAs is important for improving repair after nerve injury. This study aimed to investigate changes in mRNAs in the spinal cord following sciatic nerve injury by transcriptomic analysis. The left sciatic nerve denervation model was established in C57BL/6 mice. The left L4-6 spinal cord segment was obtained at 0, 1, 2, 4 and 8 weeks after severing the sciatic nerve. mRNA expression profiles were generated by RNA sequencing. The sequencing results of spinal cord mRNA at 1, 2, 4, and 8 weeks after severing the sciatic nerve were compared with those at 0 weeks by bioinformatic analysis. We identified 1915 differentially expressed mRNAs in the spinal cord, of which 4, 1909, and 2 were differentially expressed at 1, 4, and 8 weeks after sciatic nerve injury, respectively. Sequencing results indicated that the number of differentially expressed mRNAs in the spinal cord was highest at 4 weeks after sciatic nerve injury. These mRNAs were associated with the cellular response to lipid, ATP metabolism, energy coupled proton transmembrane transport, nuclear transcription factor complex, vacuolar proton-transporting V-type ATPase complex, inner mitochondrial membrane protein complex, tau protein binding, NADH dehydrogenase activity and hydrogen ion transmembrane transporter activity. Of these mRNAs, Sgk1, Neurturin and Gpnmb took part in cell growth and development. Pathway analysis showed that these mRNAs were mainly involved in aldosterone-regulated sodium reabsorption, oxidative phosphorylation and collecting duct acid secretion. Functional assessment indicated that these mRNAs were associated with inflammation and cell morphology development. Our findings show that the number and type of spinal cord mRNAs involved in changes at different time points after peripheral nerve injury were different. The number of differentially expressed mRNAs in the spinal cord was highest at 4 weeks after sciatic nerve injury. These results provide reference data for finding new targets for the treatment of peripheral nerve injury, and for further gene therapy studies of peripheral nerve injury and repair. The study procedures were approved by the Ethics Committee of the Peking University People's Hospital (approval No. 2017PHC004) on March 5, 2017.

Efficient and specific oligo-based depletion of rRNA

In most organisms, ribosomal RNA (rRNA) contributes to >85% of total RNA. Thus, to obtain useful information from RNA-sequencing (RNA-seq) analyses at reasonable sequencing depth, typically, mature polyadenylated transcripts are enriched or rRNA molecules are depleted. Targeted depletion of rRNA is particularly useful when studying transcripts lacking a poly(A) tail, such as some non-coding RNAs (ncRNAs), most bacterial RNAs and partially degraded or immature transcripts. While several commercially available kits allow effective rRNA depletion, their efficiency relies on a high degree of sequence homology between oligonucleotide probes and the target RNA. This restricts the use of such kits to a limited number of organisms with conserved rRNA sequences. In this study we describe the use of biotinylated oligos and streptavidin-coated paramagnetic beads for the efficient and specific depletion of trypanosomal rRNA. Our approach reduces the levels of the most abundant rRNA transcripts to less than 5% with minimal off-target effects. By adjusting the sequence of the oligonucleotide probes, our approach can be used to deplete rRNAs or other abundant transcripts independent of species. Thus, our protocol provides a useful alternative for rRNA removal where enrichment of polyadenylated transcripts is not an option and commercial kits for rRNA are not available.

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.

Multi-perspective quality control of Illumina RNA sequencing data analysis

Quality control (QC) is a critical step in RNA sequencing (RNA-seq). Yet, it is often ignored or conducted on a limited basis. Here, we present a multi-perspective strategy for QC of RNA-seq experiments. The QC of RNA-seq can be divided into four related stages: (1) RNA quality, (2) raw read data (FASTQ), (3) alignment and (4) gene expression. We illustrate the importance of conducting QC at each stage of an RNA-seq experiment and demonstrate our recommended RNA-seq QC strategy. Furthermore, we discuss the major and often neglected quality issues associated with the three major types of RNA-seq: mRNA, total RNA and small RNA. This RNA-seq QC overview provides comprehensive guidance for researchers who conduct RNA-seq experiments.

Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion

To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

Cross-site comparison of ribosomal depletion kits for Illumina RNAseq library construction

Background

Ribosomal RNA (rRNA) comprises at least 90% of total RNA extracted from mammalian tissue or cell line samples. Informative transcriptional profiling using massively parallel sequencing technologies requires either enrichment of mature poly-adenylated transcripts or targeted depletion of the rRNA fraction. The latter method is of particular interest because it is compatible with degraded samples such as those extracted from FFPE and also captures transcripts that are not poly-adenylated such as some non-coding RNAs. Here we provide a cross-site study that evaluates the performance of ribosomal RNA removal kits from Illumina, Takara/Clontech, Kapa Biosystems, Lexogen, New England Biolabs and Qiagen on intact and degraded RNA samples.

Results

We find that all of the kits are capable of performing significant ribosomal depletion, though there are differences in their ease of use. All kits were able to remove ribosomal RNA to below 20% with intact RNA and identify ~ 14,000 protein coding genes from the Universal Human Reference RNA sample at >1FPKM. Analysis of differentially detected genes between kits suggests that transcript length may be a key factor in library production efficiency.

Conclusions

These results provide a roadmap for labs on the strengths of each of these methods and how best to utilize them.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4585-1) contains supplementary material, which is available to authorized users.

Current Research on Non-Coding Ribonucleic Acid (RNA)

Non-coding ribonucleic acid (RNA) has without a doubt captured the interest of biomedical researchers. The ability to screen the entire human genome with high-throughput sequencing technology has greatly enhanced the identification, annotation and prediction of the functionality of non-coding RNAs. In this review, we discuss the current landscape of non-coding RNA research and quantitative analysis. Non-coding RNA will be categorized into two major groups by size: long non-coding RNAs and small RNAs. In long non-coding RNA, we discuss regular long non-coding RNA, pseudogenes and circular RNA. In small RNA, we discuss miRNA, transfer RNA, piwi-interacting RNA, small nucleolar RNA, small nuclear RNA, Y RNA, single recognition particle RNA, and 7SK RNA. We elaborate on the origin, detection method, and potential association with disease, putative functional mechanisms, and public resources for these non-coding RNAs. We aim to provide readers with a complete overview of non-coding RNAs and incite additional interest in non-coding RNA research.

Comprehensive evaluation of extracellular small RNA isolation methods from serum in high throughput sequencing

Background

DNA and RNA fractions from whole blood, serum and plasma are increasingly popular analytes that are currently under investigation for their utility in the diagnosis and staging of disease. Small non-coding ribonucleic acids (sRNAs), specifically microRNAs (miRNAs) and their variant isoforms (isomiRs), and transfer RNA (tRNA)-derived small RNAs (tDRs) comprise a repertoire of molecules particularly promising in this regard.

Results

In this designed study, we compared the performance of various methods and kits for isolating circulating extracellular sRNAs (ex-sRNAs). ex-sRNAs from one healthy individual were isolated using five different isolation kits: Qiagen Circulating Nucleic Acid Kit, ThermoFisher Scientific Ambion TRIzol LS Reagent, Qiagen miRNEasy, QiaSymphony RNA extraction kit and the Exiqon MiRCURY RNA Isolation Kit. Each isolation method was repeated four times. A total of 20 small RNA sequencing (sRNAseq) libraries were constructed, sequenced and compared using a rigorous bioinformatics approach. The Circulating Nucleic Acid Kit had the greatest miRNA isolation variability, but had the lowest isolation variability for other RNA classes (isomiRs, tDRs, and other miscellaneous sRNAs (osRNA). However, the Circulating Nucleic Acid Kit consistently generated the fewest number of reads mapped to the genome, as compared to the best-performing method, Ambion TRIzol, which mapped 10% of the miRNAs, 7.2% of the tDRs and 23.1% of the osRNAs. The other methods performed intermediary, with QiaSymphony mapping 14% of the osRNAs, and miRNEasy mapping 4.6% of the tDRs and 2.9% of the miRNAs, achieving the second best kit performance rating overall.

Conclusions

In summary, each isolation kit displayed different performance characteristics that could be construed as biased or advantageous, depending upon the downstream application and number of samples that require processing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3470-z) contains supplementary material, which is available to authorized users.

lncRNA expression in the auditory forebrain during postnatal development

The biological processes governing brain development and maturation depend on complex patterns of gene and protein expression, which can be influenced by many factors. One of the most overlooked is the long noncoding class of RNAs (lncRNAs), which are known to play important regulatory roles in an array of biological processes. Little is known about the distribution of lncRNAs in the sensory systems of the brain, and how lncRNAs interact with other mechanisms to guide the development of these systems. In this study, we profiled lncRNA expression in the mouse auditory forebrain during postnatal development at time points before and after the onset of hearing (P7, P14, P21, adult). First, we generated lncRNA profiles of the primary auditory cortex (A1) and medial geniculate body (MG) at each age. Then, we determined the differential patterns of expression by brain region and age. These analyses revealed that the lncRNA expression profile was distinct between both brain regions and between each postnatal age, indicating spatial and temporal specificity during maturation of the auditory forebrain. Next, we explored potential interactions between functionally-related lncRNAs, protein coding RNAs (pcRNAs), and associated proteins. The maturational trajectories (P7 to adult) of many lncRNA - pcRNA pairs were highly correlated, and predictive analyses revealed that lncRNA-protein interactions tended to be strong. A user-friendly database was constructed to facilitate inspection of the expression levels and maturational trajectories for any lncRNA or pcRNA in the database. Overall, this study provides an in-depth summary of lncRNA expression in the developing auditory forebrain and a broad-based foundation for future exploration of lncRNA function during brain development.

RNA Sequencing of Formalin-Fixed, Paraffin-Embedded Specimens for Gene Expression Quantification and Data Mining

Background. Proper rRNA depletion is crucial for the successful utilization of FFPE specimens when studying gene expression. We performed a study to evaluate two major rRNA depletion methods: Ribo-Zero and RNase H. RNAs extracted from 4 samples were treated with the two rRNA depletion methods in duplicate and sequenced (N = 16). We evaluated their reducibility, ability to detect RNA, and ability to molecularly subtype these triple negative breast cancer specimens. Results. Both rRNA depletion methods produced consistent data between the technical replicates. We found that the RNase H method produced higher quality RNAseq data as compared to the Ribo-Zero method. In addition, we evaluated the RNAseq data generated from the FFPE tissue samples for noncoding RNA, including lncRNA, enhancer/super enhancer RNA, and single nucleotide variation (SNV). We found that the RNase H is more suitable for detecting high-quality, noncoding RNAs as compared to the Ribo-Zero and provided more consistent molecular subtype identification between replicates. Unfortunately, neither method produced reliable SNV data. Conclusions. In conclusion, for FFPE specimens, the RNase H rRNA depletion method performed better than the Ribo-Zero. Neither method generates data sufficient for SNV detection.