Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling

The application status of sequencing technology in global respiratory infectious disease diagnosis

Next-generation sequencing (NGS) has revolutionized clinical microbiology, particularly in diagnosing respiratory infectious diseases and conducting epidemiological investigations. This narrative review summarizes conventional methods for routine respiratory infection diagnosis, including culture, smear microscopy, immunological assays, image techniques as well as polymerase chain reaction(PCR). In contrast to conventional methods, there is a new detection technology, sequencing technology, and here we mainly focus on the next-generation sequencing NGS, especially metagenomic NGS(mNGS). NGS offers significant advantages over traditional methods. Firstly, mNGS eliminates assumptions about pathogens, leading to faster and more accurate results, thus reducing diagnostic time. Secondly, it allows unbiased identification of known and novel pathogens, offering broad-spectrum coverage. Thirdly, mNGS not only identifies pathogens but also characterizes microbiomes, analyzes human host responses, and detects resistance genes and virulence factors. It can complement targeted sequencing for bacterial and fungal classification. Unlike traditional methods affected by antibiotics, mNGS is less influenced due to the extended survival of pathogen DNA in plasma, broadening its applicability. However, barriers to full integration into clinical practice persist, primarily due to cost constraints and limitations in sensitivity and turnaround time. Despite these challenges, ongoing advancements aim to improve cost-effectiveness and efficiency, making NGS a cornerstone technology for global respiratory infection diagnosis.

Systematic review and feasibility study on pre-analytical factors and genomic analyses on archival formalin-fixed paraffin-embedded breast cancer tissue

Formalin-fixed paraffin-embedded (FFPE) tissue represents a valuable source for translational cancer research. However, the widespread application of various downstream methods remains challenging. Here, we aimed to assess the feasibility of a genomic and gene expression analysis workflow using FFPE breast cancer (BC) tissue. We conducted a systematic literature review for the assessment of concordance between FFPE and fresh-frozen matched tissue samples derived from patients with BC for DNA and RNA downstream applications. The analytical performance of three different nucleic acid extraction kits on FFPE BC clinical samples was compared. We also applied a newly developed targeted DNA Next-Generation Sequencing (NGS) 370-gene panel and the nCounter BC360® platform on simultaneously extracted DNA and RNA, respectively, using FFPE tissue from a phase II clinical trial. Of the 3701 initial search results, 40 articles were included in the systematic review. High degree of concordance was observed in various downstream application platforms. Moreover, the performance of simultaneous DNA/RNA extraction kit was demonstrated with targeted DNA NGS and gene expression profiling. Exclusion of variants below 5% variant allele frequency was essential to overcome FFPE-induced artefacts. Targeted genomic analyses were feasible in simultaneously extracted DNA/RNA from FFPE material, providing insights for their implementation in clinical trials/cohorts.

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

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

Dual RNA-seq in filarial nematodes and Wolbachia endosymbionts using RNase H based ribosomal RNA depletion

Lymphatic filariasis is caused by parasitic nematodes and is a leading cause of disability worldwide. Many filarial worms contain the bacterium Wolbachia as an obligate endosymbiont. RNA sequencing is a common technique used to study their molecular relationships and to identify potential drug targets against the nematode and bacteria. Ribosomal RNA (rRNA) is the most abundant RNA species, accounting for 80-90% of the RNA in a sample. To reduce sequencing costs, it is necessary to remove ribosomal reads through poly-A enrichment or ribosomal depletion. Bacterial RNA does not contain a poly-A tail, making it difficult to sequence both the nematode and Wolbachia from the same library preparation using standard poly-A selection. Ribosomal depletion can utilize species-specific oligonucleotide probes to remove rRNA through pull-down or degradation methods. While species-specific probes are commercially available for many commonly studied model organisms, there are currently limited depletion options for filarial parasites. Here, we performed total RNA sequencing from Brugia malayi containing the Wolbachia symbiont (wBm) and designed ssDNA depletion probes against their rRNA sequences. We compared the total RNA library to poly-A enriched, Terminator 5'-Phosphate-Dependent Exonuclease treated, NEBNext Human/Bacteria rRNA depleted and our custom nematode probe depleted libraries. The custom nematode depletion library had the lowest percentage of ribosomal reads across all methods, with a 300-fold decrease in rRNA when compared to the total RNA library. The nematode depletion libraries also contained the highest percentage of Wolbachia mRNA reads, resulting in a 16-1,000-fold increase in bacterial reads compared to the other enrichment and depletion methods. Finally, we found that the Brugia malayi depletion probes can remove rRNA from the filarial worm Dirofilaria immitis and the majority of rRNA from the more distantly related free living nematode Caenorhabditis elegans. These custom filarial probes will allow for future dual RNA-seq experiments between nematodes and their bacterial symbionts from a single sequencing library.

snRNAs from Radical Prostatectomy Specimens Have the Potential to Serve as Prognostic Factors for Clinical Recurrence after Biochemical Recurrence in Patients with High-Risk Prostate Cancer

In patients with high-risk prostate cancer (HRPC) after radical prostatectomy (RP), biochemical recurrence (BCR) increases the risk of distant metastasis. Accordingly, additional prognostic biomarkers are required to identify the subpopulation of patients with HRPC who develop clinical recurrence (CR) after BCR. The objective of this study was to identify biomarkers in formalin-fixed paraffin-embedded (FFPE) RP samples that are prognostic for CR in patients with HRPC who experience BCR after RP (post-RP BCR). First, we performed a preliminary RNA sequencing analysis to comprehensively profile RNA expression in FFPE RP samples obtained from patients with HRPC who developed CR after post-RP BCR and found that many snRNAs were very abundant in preserved FFPE samples. Subsequently, we used quantitative polymerase chain reaction (qPCR) to compare the expression levels of highly abundant snRNAs in FFPE RP samples from patients with HRPC with and without CR after post-RP BCR (21 CR patients and 46 non-CR patients who had more than 5 years of follow-up after BCR). The qPCR analysis revealed that the expression levels of snRNA RNU1-1/1-2 and RNU4-1 were significantly higher in patients with CR than in patients without CR. These snRNAs were significantly correlated with clinical recurrence-free survival (RFS) in patients with HRPC who experienced post-RP BCR. Furthermore, snRNA RNU1-1/1-2 could serve as an independent prognostic factor for clinical RFS in post-RP BCR of HRPC cases where known prognostic factors (e.g., Gleason score) cannot distinguish between CR and non-CR patients. Our findings provide new insights into the involvement of snRNAs in prostate cancer progression.

Plasma-Free Blood as a Potential Alternative to Whole Blood for Transcriptomic Analysis

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples that are generally considered less useful byproducts during the processes of plasma and serum separation, respectively. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the suitability of employing PFB or SFB samples as an alternative RNA source in transcriptomic analysis. We performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples than SFB samples in terms of protein-coding gene expression patterns, detection of differentially expressed genes, and immunological characterizations, suggesting that PFB can serve as a viable alternative to WB for transcriptomic analysis. Our study contributes to the optimization of blood sample utilization and the advancement of precision medicine research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00121-1.

Evaluating the mode of action of perfluorooctanoic acid-induced liver tumors in male Sprague-Dawley rats using a toxicogenomic approach

The mode of action (MOA) underlying perfluorooctanoic acid (PFOA)-induced liver tumors in rats is proposed to involve peroxisome proliferator-activated receptor α (PPARα) agonism. Despite clear PPARα activation evidence in rodent livers, the mechanisms driving cell growth remain elusive. Herein, we used dose-responsive apical endpoints and transcriptomic data to examine the proposed MOA. Male Sprague-Dawley rats were treated with 0, 1, 5, and 15 mg/kg PFOA for 7, 14, and 28 days via oral gavage. We showed PFOA induced hepatomegaly along with hepatocellular hypertrophy in rats. PPARα was activated in a dose-dependent manner. Toxicogenomic analysis revealed six early biomarkers (Cyp4a1, Nr1d1, Acot1, Acot2, Ehhadh, and Vnn1) in response to PPARα activation. A transient rise in hepatocellular DNA synthesis was demonstrated while Ki-67 labeling index showed no change. Transcriptomic analysis indicated no significant enrichment in pathways related to DNA synthesis, apoptosis, or the cell cycle. Key cyclins including Ccnd1, Ccnb1, Ccna2, and Ccne2 were dose-dependently suppressed by PFOA. Oxidative stress and the nuclear factor-κB signaling pathway were unaffected. Overall, evidence for PFOA-induced hepatocellular proliferation was transient within the studied timeframe. Our findings underscore the importance of considering inter-species differences and chemical-specific effects when evaluating the carcinogenic risk of PFOA in humans.

Genomes in clinical care

In the era of precision medicine, genome sequencing (GS) has become more affordable and the importance of genomics and multi-omics in clinical care is increasingly being recognized. However, how to scale and effectively implement GS on an institutional level remains a challenge for many. Here, we present Genome First and Ge-Med, two clinical implementation studies focused on identifying the key pillars and processes that are required to make routine GS and predictive genomics a reality in the clinical setting. We describe our experience and lessons learned for a variety of topics including test logistics, patient care processes, data reporting, and infrastructure. Our model of providing clinical care and comprehensive genomic analysis from a single source may be used by other centers with a similar structure to facilitate the implementation of omics-based personalized health concepts in medicine.

Evaluation of Muscle Long Non-Coding RNA Profile during Rearing and Finishing Phase of Bulls Subjected to Different Prenatal Nutritional Strategies

Maternal nutrition has the ability of influence critical processes in fetal life, including muscle development. Also, in this period, epigenetic sensitivity to external stimuli is higher and produces long-lasting effects. Thus, the aim of this study was to investigate epigenetic mechanisms, including the identification and characterization of long non-coding RNA (lncRNA) from animals that had undergone different strategies of prenatal supplementation. A group of Nellore cows (n = 126) were separated into three nutritional plans: NP (control)-Not Programmed, without protein-energy supplementation; PP-Partially Programmed, protein-energy supplementation in the final third of pregnancy; and CP-Complete Programming, protein-energy supplementation during the full period of gestation. A total of 63 male offspring were used in this study, of which 15 (5 per treatment) had Longissimus thoracis muscle at 15 (biopsy) and 22 months (slaughter). Biopsy samples were subjected to RNA extraction and sequencing. Differential expression (DE) of remodeling factors and chromatin-modifying enzyme genes were performed. For the identification and characterization of lncRNA, a series of size filters and protein coding potential tests were performed. The lncRNAs identified had their differential expression and regulatory potential tested. Regarding DE of epigenetic mechanisms, no differentially expressed gene was found (p > 0.1). Identification of potential lncRNA was successful, identifying 1823 transcripts at 15 months and 1533 at 22 months. Among these, four were considered differentially expressed between treatments at 15 months and 6 were differentially expressed at 22 months. Yet, when testing regulatory potential, 13 lncRNAs were considered key regulators in the PP group, and 17 in the CP group. PP group lncRNAs possibly regulate fat-cell differentiation, in utero embryonic development, and transforming growth factor beta receptor, whereas lncRNA in the CP group regulates in utero embryonic development, fat-cell differentiation and vasculogenesis. Maternal nutrition had no effect on differential expression of epigenetic mechanisms; however, it seems to impair lncRNA regulation of epigenetics.

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

Direct RNA sequencing coupled with adaptive sampling enriches RNAs of interest in the transcriptome

Abundant cellular transcripts occupy most of the sequencing reads in the transcriptome, making it challenging to assay for low-abundant transcripts. Here, we utilize the adaptive sampling function of Oxford Nanopore sequencing to selectively deplete and enrich RNAs of interest without biochemical manipulation before sequencing. Adaptive sampling performed on a pool of in vitro transcribed RNAs resulted in a net increase of 22-30% in the proportion of transcripts of interest in the population. Enriching and depleting different proportions of the Candida albicans transcriptome also resulted in a 11-13.5% increase in the number of reads on target transcripts, with longer and more abundant transcripts being more efficiently depleted. Depleting all currently annotated Candida albicans transcripts did not result in an absolute enrichment of remaining transcripts, although we identified 26 previously unknown transcripts and isoforms, 17 of which are antisense to existing transcripts. Further improvements in the adaptive sampling of RNAs will allow the technology to be widely applied to study RNAs of interest in diverse transcriptomes.

Using Publicly Available RNA-seq Data for Expression Analysis of Genes of Interest

RNA-seq data in publicly available repositories enable the efficient reanalysis of transcript abundances in existing experiments. Graphical user interfaces usually only allow the visual inspection of a single gene and of predefined experiments. Here, we describe how experiments are selected from the Sequence Read Archive or the European Nucleotide Archive, how data is efficiently mapped onto a reference transcriptome, and how global transcript abundances and patterns are inspected. We exemplarily apply this analysis pipeline to study the expression of photorespiration-related genes in photosynthetic organisms, such as cyanobacteria, and to identify conditions under which photorespiratory transcript abundances are enhanced.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.

Next-Generation Sequencing for the Detection of Microbial Agents in Avian Clinical Samples

Direct-targeted next-generation sequencing (tNGS), with its undoubtedly superior diagnostic capacity over real-time PCR (RT-PCR), and direct-non-targeted NGS (ntNGS), with its higher capacity to identify and characterize multiple agents, are both likely to become diagnostic methods of choice in the future. tNGS is a rapid and sensitive method for precise characterization of suspected agents. ntNGS, also known as agnostic diagnosis, does not require a hypothesis and has been used to identify unsuspected infections in clinical samples. Implemented in the form of multiplexed total DNA metagenomics or as total RNA sequencing, the approach produces comprehensive and actionable reports that allow semi-quantitative identification of most of the agents present in respiratory, cloacal, and tissue samples. The diagnostic benefits of the use of direct tNGS and ntNGS are high specificity, compatibility with different types of clinical samples (fresh, frozen, FTA cards, and paraffin-embedded), production of nearly complete infection profiles (viruses, bacteria, fungus, and parasites), production of "semi-quantitative" information, direct agent genotyping, and infectious agent mutational information. The achievements of NGS in terms of diagnosing poultry problems are described here, along with future applications. Multiplexing, development of standard operating procedures, robotics, sequencing kits, automated bioinformatics, cloud computing, and artificial intelligence (AI) are disciplines converging toward the use of this technology for active surveillance in poultry farms. Other advances in human and veterinary NGS sequencing are likely to be adaptable to avian species in the future.

Decoding mitochondrial-nuclear (epi)genome interactions: the emerging role of ncRNAs

Bidirectional communication between the mitochondria and the nucleus is required for several physiological processes, and the nuclear epigenome is a key mediator of this relationship. ncRNAs are an emerging area of discussion for their roles in cellular function and regulation. In this review, we highlight the role of mitochondrial-encoded ncRNAs as mediators of communication between the mitochondria and the nuclear genome. We focus primarily on retrograde signaling, a process in which the mitochondrion relays ncRNAs to translate environmental stress signals to changes in nuclear gene expression, with implications on stress responses that may include disease(s). Other biological roles of mitochondrial-encoded ncRNAs, such as mitochondrial import of proteins and regulation of cell signaling, will also be discussed.

RNA-seq RNAaccess identified as the preferred method for gene expression analysis of low quality FFPE samples

Clinical tumor tissues that are preserved as formalin-fixed paraffin-embedded (FFPE) samples result in extensive cross-linking, fragmentation, and chemical modification of RNA, posing significant challenges for RNA-seq-based gene expression profiling. This study sought to define an optimal RNA-seq protocol for FFPE samples. We employed a common RNA extraction method and then compared RNA-seq library preparation protocols including RNAaccess, RiboZero and PolyA in terms of sequencing quality and concordance of gene expression using FFPE and case-matched fresh-frozen (FF) triple-negative breast cancer (TNBC) tissues. We found that RNAaccess, a method based on exome capture, produced the most concordant results. Applying RNAaccess to FFPE gastric cancer tissues, we established a minimum RNA DV200 requirement of 10% and a RNA input amount of 10ng that generated highly reproducible gene expression data. Lastly, we demonstrated that RNAaccess and NanoString platforms produced highly concordant expression profiles from FFPE samples for shared genes; however, RNA-seq may be preferred for clinical biomarker discovery work because of the broader coverage of the transcriptome. Taken together, these results support the selection of RNA-seq RNAaccess method for gene expression profiling of FFPE samples. The minimum requirements for RNA quality and input established here may allow for inclusion of clinical FFPE samples of sub-optimal quality in gene expression analyses and ultimately increasing the statistical power of such analyses.

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.

Linking extreme seasonality and gene expression in Arctic marine protists

At high latitudes, strong seasonal differences in light availability affect marine organisms and regulate the timing of ecosystem processes. Marine protists are key players in Arctic aquatic ecosystems, yet little is known about their ecological roles over yearly cycles. This is especially true for the dark polar night period, which up until recently was assumed to be devoid of biological activity. A 12 million transcripts catalogue was built from 0.45 to 10 μm protist assemblages sampled over 13 months in a time series station in an Arctic fjord in Svalbard. Community gene expression was correlated with seasonality, with light as the main driving factor. Transcript diversity and evenness were higher during polar night compared to polar day. Light-dependent functions had higher relative expression during polar day, except phototransduction. 64% of the most expressed genes could not be functionally annotated, yet up to 78% were identified in Arctic samples from Tara Oceans, suggesting that Arctic marine assemblages are distinct from those from other oceans. Our study increases understanding of the links between extreme seasonality and biological processes in pico- and nanoplanktonic protists. Our results set the ground for future monitoring studies investigating the seasonal impact of climate change on the communities of microbial eukaryotes in the High Arctic.

Haptoglobin Gene Expression and Anthracycline-Related Cardiomyopathy in Childhood Cancer Survivors: A COG-ALTE03N1 Report

Background

Anthracycline-related cardiomyopathy is a leading cause of premature death in childhood cancer survivors. The high interindividual variability in risk suggests the need to understand the underlying pathogenesis.

Objectives

The authors interrogated differentially expressed genes (DEGs) to identify genetic variants serving regulatory functions or genetic variants not easily identified when using genomewide array platforms. Using leads from DEGs, candidate copy number variants (CNVs) and single-nucleotide variants (SNVs) were genotyped.

Methods

Messenger RNA sequencing was performed on total RNA from peripheral blood of 40 survivors with cardiomyopathy (cases) and 64 matched survivors without cardiomyopathy (control subjects). Conditional logistic regression analysis adjusting for sex, age at cancer diagnosis, anthracycline dose, and chest radiation was used to assess the associations between gene expression and cardiomyopathy and between CNVs and SNVs and cardiomyopathy.

Results

Haptoglobin (HP) was identified as the top DEG. Participants with higher HP gene expression had 6-fold greater odds of developing cardiomyopathy (OR: 6.4; 95% CI: 1.4-28.6). The HP2-specific allele among the HP genotypes (HP1-1, HP1-2, and HP2-2) had higher transcript levels, as did the G allele among SNVs previously reported to be associated with HP gene expression (rs35283911 and rs2000999). The HP1-2 and HP2-2 genotypes combined with the G/G genotype for rs35283911 and/or rs2000999 placed the survivors at 4-fold greater risk (OR: 3.9; 95% CI: 1.0-14.5) for developing cardiomyopathy.

Conclusions

These findings provide evidence of a novel association between HP2 allele and cardiomyopathy. HP binds to free hemoglobin to form an HP-hemoglobin complex, thereby preventing oxidative damage from free heme iron, thus providing biological plausibility to the mechanistic basis of the present observation.

The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens

Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.

CRISPR-Cas9-based repeat depletion for high-throughput genotyping of complex plant genomes

High-throughput genotyping enables the large-scale analysis of genetic diversity in population genomics and genome-wide association studies that combine the genotypic and phenotypic characterization of large collections of accessions. Sequencing-based approaches for genotyping are progressively replacing traditional genotyping methods because of the lower ascertainment bias. However, genome-wide genotyping based on sequencing becomes expensive in species with large genomes and a high proportion of repetitive DNA. Here we describe the use of CRISPR-Cas9 technology to deplete repetitive elements in the 3.76-Gb genome of lentil (Lens culinaris), 84% consisting of repeats, thus concentrating the sequencing data on coding and regulatory regions (single-copy regions). We designed a custom set of 566,766 gRNAs targeting 2.9 Gbp of repeats and excluding repetitive regions overlapping annotated genes and putative regulatory elements based on ATAC-seq data. The novel depletion method removed ∼40% of reads mapping to repeats, increasing those mapping to single-copy regions by ∼2.6-fold. When analyzing 25 million fragments, this repeat-to-single-copy shift in the sequencing data increased the number of genotyped bases of ∼10-fold compared to nondepleted libraries. In the same condition, we were also able to identify ∼12-fold more genetic variants in the single-copy regions and increased the genotyping accuracy by rescuing thousands of heterozygous variants that otherwise would be missed because of low coverage. The method performed similarly regardless of the multiplexing level, type of library or genotypes, including different cultivars and a closely related species (L. orientalis). Our results showed that CRISPR-Cas9-driven repeat depletion focuses sequencing data on single-copy regions, thus improving high-density and genome-wide genotyping in large and repetitive genomes.

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.

Study on the use of Nanostring nCounter to analyze RNA extracted from formalin-fixed-paraffin-embedded and fresh frozen bladder cancer tissues

Formalin-fixed paraffin-embedded (FFPE) tissue is the most common source of archived material for genomic medicine. However, FFPE tissue is suboptimal for high-throughput analyses, such as RNA sequencing, because the quality of nucleic acids in FFPE tissues is low. We compared RNA-seq with the nCounter system to evaluate use of FFPE tissue for genomic medicine. Twelve fresh frozen bladder cancer samples were analyzed by both RNA sequencing and nCounter, and matched FFPE samples, by nCounter. Gene-expression values obtained by these two platforms were compared by calculating Pearson correlation coefficients for each sample (across the set of matched genes) and for each matched gene (across the set of samples). For each sample, gene-expression levels measured by RNA sequencing highly correlated with those measured by nCounter (all Pearson's R > 0.8, P < 0.0001), as seen by hierarchical clustering. RNA sequencing results for fresh frozen tissues positively correlated with nCounter results for FFPE tissues (R ranged from 0.675 to 0.873, all P < 0.0001). Correlation and hierarchical-clustering analyses of nCounter data from the two specimens demonstrated a strong positive correlation between each group (R ranged from 0.779 to 0.977, all P < 0.0001). Our findings suggest that the nCounter system is useful for assaying archived-FFPE samples and that the gene-expression signatures obtained from FFPE samples represent those from fresh frozen tissues.

Whole Transcriptome Sequencing Reveals Cancer-Related, Prognostically Significant Transcripts and Tumor-Infiltrating Immunocytes in Mantle Cell Lymphoma

Mantle cell lymphoma (MCL) is an aggressive B-cell non-Hodgkin lymphoma (NHL) subtype characterized by overexpression of CCND1 and SOX11 genes. It is generally associated with clinically poor outcomes despite recent improvements in therapeutic approaches. The genes associated with the development and prognosis of MCL are still largely unknown. Through whole transcriptome sequencing (WTS), we identified mRNAs, lncRNAs, and alternative transcripts differentially expressed in MCL cases compared with reactive tonsil B-cell subsets. CCND1, VCAM1, and VWF mRNAs, as well as MIR100HG and ROR1-AS1 lncRNAs, were among the top 10 most significantly overexpressed, oncogenesis-related transcripts. Survival analyses with each of the top upregulated transcripts showed that MCL cases with high expression of VWF mRNA and low expression of FTX lncRNA were associated with poor overall survival. Similarly, high expression of MSTRG.153013.3, an overexpressed alternative transcript, was associated with shortened MCL survival. Known tumor suppressor candidates (e.g., PI3KIP1, UBXN) were significantly downregulated in MCL cases. Top differentially expressed protein-coding genes were enriched in signaling pathways related to invasion and metastasis. Survival analyses based on the abundance of tumor-infiltrating immunocytes estimated with CIBERSORTx showed that high ratios of CD8⁺ T-cells or resting NK cells and low ratios of eosinophils are associated with poor overall survival in diagnostic MCL cases. Integrative analysis of tumor-infiltrating CD8⁺ T-cell abundance and overexpressed oncogene candidates showed that MCL cases with high ratio CD8⁺ T-cells and low expression of FTX or PCA3 can potentially predict high-risk MCL patients. WTS results were cross-validated with qRT-PCR of selected transcripts as well as linear correlation analyses. In conclusion, expression levels of oncogenesis-associated transcripts and/or the ratios of microenvironmental immunocytes in MCL tumors may be used to improve prognostication, thereby leading to better patient management and outcomes.

The Transcriptomic Landscape of Pediatric Astrocytoma

Central nervous system tumors are the most common solid neoplasia during childhood and represent one of the leading causes of cancer-related mortality. Tumors arising from astrocytic cells (astrocytomas) are the most frequently diagnosed, and according to their histological and pathological characteristics, they are classified into four categories. However, an additional layer of molecular classification considering the DNA sequence of the tumorigenesis-associated genes IDH1/2 and H3F3A has recently been incorporated into the classification guidelines. Although mutations in H3F3A are found exclusively in a subtype of grade IV pediatric astrocytoma, mutations in IDH1/2 genes are very rare in children under 14 years of age. The transcriptomic profiles of astrocytoma in adults and children have been extensively studied. However, there is scarce information on these profiles in pediatric populations considering the status of tumorigenesis-associated genes. Therefore, here we report the transcriptomic landscape of the four grades of pediatric astrocytoma by RNA sequencing. We found several well-documented biological functions associated with the misregulated genes in the four grades of astrocytoma, as well as additional biological pathways. Among the four grades of astrocytoma, we found shared misregulated genes that could have implications in tumorigenesis. Finally, we identified a transcriptional signature for almost all grades of astrocytoma that could be used as a transcription-based identification method.

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.

Cancer cell histone density links global histone acetylation, mitochondrial proteome and histone acetylase inhibitor sensitivity

Chromatin metabolism is frequently altered in cancer cells and facilitates cancer development. While cancer cells produce large amounts of histones, the protein component of chromatin packaging, during replication, the potential impact of histone density on cancer biology has not been studied systematically. Here, we show that altered histone density affects global histone acetylation, histone deactylase inhibitor sensitivity and altered mitochondrial proteome composition. We present estimates of nuclear histone densities in 373 cancer cell lines, based on Cancer Cell Line Encyclopedia data, and we show that a known histone regulator, HMGB1, is linked to histone density aberrations in many cancer cell lines. We further identify an E3 ubiquitin ligase interactor, DCAF6, and a mitochondrial respiratory chain assembly factor, CHCHD4, as histone modulators. As systematic characterization of histone density aberrations in cancer cell lines, this study provides approaches and resources to investigate the impact of histone density on cancer biology.

Elevated histone density is associated with global histone acetylation, histone deacetylase inhibitor sensitivity and altered mitochondrial proteome composition, with histone regulator HMGB1 linked to histone density aberrations in many cancer cell lines.

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

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

Integrated DNA and RNA Sequencing Reveals Drivers of Endocrine Resistance in Estrogen Receptor-Positive Breast Cancer

PURPOSE

Endocrine therapy resistance (ETR) remains the greatest challenge in treating patients with hormone receptor-positive breast cancer. We set out to identify molecular mechanisms underlying ETR through in-depth genomic analysis of breast tumors.

EXPERIMENTAL DESIGN

We collected pre-treatment and sequential on-treatment tumor samples from 35 patients with estrogen receptor-positive breast cancer treated with neoadjuvant then adjuvant endocrine therapy; 3 had intrinsic resistance, 19 acquired resistance, and 13 remained sensitive. Response was determined by changes in tumor volume neoadjuvantly and by monitoring for adjuvant recurrence. Twelve patients received two or more lines of endocrine therapy, with subsequent treatment lines being initiated at the time of development of resistance to the previous endocrine therapy. DNA whole-exome sequencing and RNA sequencing were performed on all samples, totalling 169 unique specimens. DNA mutations, copy-number alterations, and gene expression data were analyzed through unsupervised and supervised analyses to identify molecular features related to ETR.

RESULTS

Mutations enriched in ETR included ESR1 and GATA3. The known ESR1 D538G variant conferring ETR was identified, as was a rarer E380Q variant that confers endocrine hypersensitivity. Resistant tumors which acquired resistance had distinct gene expression profiles compared with paired sensitive tumors, showing elevated pathways including ER, HER2, GATA3, AKT, RAS, and p63 signaling. Integrated analysis in individual patients highlighted the diversity of ETR mechanisms.

CONCLUSIONS

The mechanisms underlying ETR are multiple and characterized by diverse changes in both somatic genetic and transcriptomic profiles; to overcome resistance will require an individualized approach utilizing genomic and genetic biomarkers and drugs tailored to each patient.

Comprehensive Analysis of the Immunogenomics of Triple-Negative Breast Cancer Brain Metastases From LCCC1419

Background

Triple negative breast cancer (TNBC) is an aggressive variant of breast cancer that lacks the expression of estrogen and progesterone receptors (ER and PR) and HER2. Nearly 50% of patients with advanced TNBC will develop brain metastases (BrM), commonly with progressive extracranial disease. Immunotherapy has shown promise in the treatment of advanced TNBC; however, the immune contexture of BrM remains largely unknown. We conducted a comprehensive analysis of TNBC BrM and matched primary tumors to characterize the genomic and immune landscape of TNBC BrM to inform the development of immunotherapy strategies in this aggressive disease.

Methods

Whole-exome sequencing (WES) and RNA sequencing were conducted on formalin-fixed, paraffin-embedded samples of BrM and primary tumors of patients with clinical TNBC (n = 25, n = 9 matched pairs) from the LCCC1419 biobank at UNC—Chapel Hill. Matched blood was analyzed by DNA sequencing as a comparison for tumor WES for the identification of somatic variants. A comprehensive genomics assessment, including mutational and copy number alteration analyses, neoantigen prediction, and transcriptomic analysis of the tumor immune microenvironment were performed.

Results

Primary and BrM tissues were confirmed as TNBC (23/25 primaries, 16/17 BrM) by immunohistochemistry and of the basal intrinsic subtype (13/15 primaries and 16/19 BrM) by PAM50. Compared to primary tumors, BrM demonstrated a higher tumor mutational burden. TP53 was the most frequently mutated gene and was altered in 50% of the samples. Neoantigen prediction showed elevated cancer testis antigen- and endogenous retrovirus-derived MHC class I-binding peptides in both primary tumors and BrM and predicted that single-nucleotide variant (SNV)-derived peptides were significantly higher in BrM. BrM demonstrated a reduced immune gene signature expression, although a signature associated with fibroblast-associated wound healing was elevated in BrM. Metrics of T and B cell receptor diversity were also reduced in BrM.

Conclusions

BrM harbored higher mutational burden and SNV-derived neoantigen expression along with reduced immune gene signature expression relative to primary TNBC. Immune signatures correlated with improved survival, including T cell signatures. Further research will expand these findings to other breast cancer subtypes in the same biobank. Exploration of immunomodulatory approaches including vaccine applications and immune checkpoint inhibition to enhance anti-tumor immunity in TNBC BrM is warranted.

Organellar transcripts dominate the cellular mRNA pool across plants of varying ploidy levels

Mitochondrial and plastid functions depend on coordinated expression of proteins encoded by genomic compartments that have radical differences in copy number of organellar and nuclear genomes. In polyploids, doubling of the nuclear genome may add challenges to maintaining balanced expression of proteins involved in cytonuclear interactions. Here, we use ribo-depleted RNA sequencing (RNA-seq) to analyze transcript abundance for nuclear and organellar genomes in leaf tissue from four different polyploid angiosperms and their close diploid relatives. We find that even though plastid genomes contain <1% of the number of genes in the nuclear genome, they generate the majority (69.9 to 82.3%) of messenger RNA (mRNA) transcripts in the cell. Mitochondrial genes are responsible for a much smaller percentage (1.3 to 3.7%) of the leaf mRNA pool but still produce much higher transcript abundances per gene compared to nuclear genome. Nuclear genes encoding proteins that functionally interact with mitochondrial or plastid gene products exhibit mRNA expression levels that are consistently more than 10-fold lower than their organellar counterparts, indicating an extreme cytonuclear imbalance at the RNA level despite the predominance of equimolar interactions at the protein level. Nevertheless, interacting nuclear and organellar genes show strongly correlated transcript abundances across functional categories, suggesting that the observed mRNA stoichiometric imbalance does not preclude coordination of cytonuclear expression. Finally, we show that nuclear genome doubling does not alter the cytonuclear expression ratios observed in diploid relatives in consistent or systematic ways, indicating that successful polyploid plants are able to compensate for cytonuclear perturbations associated with nuclear genome doubling.

Transcriptome analysis of SerpinB2-deficient breast tumors provides insight into deciphering SerpinB2-mediated roles in breast cancer progression

Background

SerpinB2 is highly expressed in immune and tumor cells and is involved in multiple biological functions, including cell survival and remodeling for disease progression. This study prepared SerpinB2-deficient mice and analyzed the differentially expressed genes (DEGs) to determine if loss of this protein delays mammary tumor progression.

Results

A total of 305 DEGs (75 upregulated and 230 downregulated; > 1.5-fold difference, P < 0.05) were identified in SB2−/−;PyMT tumors compared with PyMT tumors. The DEGs were mainly involved in immune and inflammatory responses related to T cell differentiation, IFN-γ production, and lymphocyte chemotaxis based on 61 enriched GO terms, hierarchical clustering, KEGG pathways, and a functionally grouped annotation network. The significantly changed DEGs (Anxa3, Ccl17, Cxcl13, Cxcr3, IFN-γ, Nr4a1, and Sema3a) annotated with at least two GO categories in SB2−/−;PyMT tumors was validated by qRT-PCR.

Conclusions

SerpinB2 deficiency alters the expression of multiple genes in mammary tumors, which might cause a delay in PyMT-induced mammary tumor progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08704-4.

Poly(A) capture full length cDNA sequencing improves the accuracy and detection ability of transcript quantification and alternative splicing events

The full-length double-strand cDNA sequencing, one of the RNA-Seq methods, is a powerful method used to investigate the transcriptome status of a gene of interest, such as its transcription level and alternative splicing variants. Furthermore, full-length double-strand cDNA sequencing has the advantage that it can create a library from a small amount of sample and the library can be applied to long-read sequencers in addition to short-read sequencers. Nevertheless, one of our previous studies indicated that the full-length double-strand cDNA sequencing yields non-specific genomic DNA amplification, affecting transcriptome analysis, such as transcript quantification and alternative splicing analysis. In this study, it was confirmed that it is possible to produce the RNA-Seq library from only genomic DNA and that the full-length double-strand cDNA sequencing of genomic DNA yielded non-specific genomic DNA amplification. To avoid non-specific genomic DNA amplification, two methods were examined, which are the DNase I-treated full-length double-strand cDNA sequencing and poly(A) capture full-length double-strand cDNA sequencing. Contrary to expectations, the non-specific genomic DNA amplification was increased and the number of the detected expressing genes was reduced in DNase I-treated full-length double-strand cDNA sequencing. On the other hand, in the poly(A) capture full-length double-strand cDNA sequencing, the non-specific genomic DNA amplification was significantly reduced, accordingly the accuracy and the number of detected expressing genes and splicing events were increased. The expression pattern and percentage spliced in index of splicing events were highly correlated. Our results indicate that the poly(A) capture full-length double-strand cDNA sequencing improves transcript quantification accuracy and the detection ability of alternative splicing events. It is also expected to contribute to the determination of the significance of DNA variants to splicing events.

Analysis of estrogen-regulated enhancer RNAs identifies a functional motif required for enhancer assembly and gene expression

To better understand the functions of non-coding enhancer RNAs (eRNAs), we annotated the estrogen-regulated eRNA transcriptome in estrogen receptor α (ERα)-positive breast cancer cells using PRO-cap and RNA sequencing. We then cloned a subset of the eRNAs identified, fused them to single guide RNAs, and targeted them to their ERα enhancers of origin using CRISPR/dCas9. Some of the eRNAs tested modulated the expression of cognate, but not heterologous, target genes after estrogen treatment by increasing ERα recruitment and stimulating p300-catalyzed H3K27 acetylation at the enhancer. We identified a ∼40 nucleotide functional eRNA regulatory motif (FERM) present in many eRNAs that was necessary and sufficient to modulate gene expression, but not the specificity of activation, after estrogen treatment. The FERM interacted with BCAS2, an RNA-binding protein amplified in breast cancers. The ectopic expression of a targeted eRNA controlling the expression of an oncogene resulted in increased cell proliferation, demonstrating the regulatory potential of eRNAs in breast cancer.

Analysis of m6A Methylation Modification Patterns and Tumor Immune Microenvironment in Breast Cancer

Increasing evidence indicates that the abnormal expression of N6-methyladenosine (m6A) modification is closely related to the epigenetic regulation of immune response in breast cancer (BC). However, the potential roles of m6A modification in the tumor microenvironment (TME) of BC remain unclear. For addressing this issue, we comprehensively analyzed the m6A modification patterns in 983 samples and correlated these modification patterns with TME immune cell infiltration, based on 23 kinds of m6A regulators. Principal component analysis (PCA) was used to construct the m6A scoring system to quantify the modification pattern of m6A of BC individuals. Consequently, three different m6A modification patterns were identified, and the infiltrating characteristics of TME cells were consistent with the three immune phenotypes, including immune rejection, immune inflammation, and immune desert. Besides, our analysis showed that the prognosis of patients could be predicted by evaluating the m6A modification pattern in the tumor. The low m6Ascore corresponded to increased mutation burden and immune activation, while stroma activation and lack of immune infiltration were observed in high m6Ascore subtypes. In addition, a low m6Ascore was associated with enhanced response to anti-PD-1/PD-L1 immunotherapy. In conclusion, the m6A modification pattern was closely related to the BC immune landscape. This well-validated score model of the m6A modification patterns will provide a valuable tool to depict the tumor immune state and guide effective tumor immunotherapy for combating BC.

Evaluation of methods to detect circular RNAs from single-end RNA-sequencing data

Background

Circular RNA (circRNA), a class of RNA molecule with a loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers of human diseases. Most of the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize the mapping information of paired-end (PE) reads to eliminate false positives. However, much of the practical RNA-Seq data such as cross-linking immunoprecipitation sequencing (CLIP-Seq) data usually contain single-end (SE) reads. It is not clear how well these tools perform on SE RNA-Seq data.

Results

In this study, we present a systematic evaluation of six advanced RNA-based methods and two CLIP-Seq based methods for detecting circRNAs from SE RNA-Seq data. The performances of the methods are rigorously assessed based on precision, sensitivity, F1 score, and true discovery rate. We investigate the impacts of read length, false positive ratio, sequencing depth and PE mapping information on the performances of the methods using simulated SE RNA-Seq simulated datasets. The real datasets used in this study consist of four experimental RNA-Seq datasets with ≥100bp read length and 124 CLIP-Seq samples from 45 studies that contain mostly short-read (≤50bp) RNA-Seq data. The simulation study shows that the sensitivities of most of the methods can be improved by increasing either read length or sequencing depth, and that the levels of false positive rates significantly affect the precision of all methods. Furthermore, the PE mapping information can improve the method’s precision but can not always guarantee the increase of F1 score. Overall, no method is dominant for all SE RNA-Seq data. The RNA-based methods perform better for the long-read datasets but are worse for the short-read datasets. In contrast, the CLIP-Seq based methods outperform the RNA-Seq based methods for all the short-read samples. Combining the results of these methods can significantly improve precision in the CLIP-Seq data.

Conclusions

The results provide a systematic evaluation of circRNA detection methods on SE RNA-Seq data that would facilitate researchers’ strategies in circRNA analysis.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08329-7).

Wholistic approach - transcriptomic analysis and beyond using archival material for molecular diagnosis

Many neoplasms remain unclassified after histopathological examination, which requires further molecular analysis. To this regard, mesenchymal neoplasms are particularly challenging due to the combination of their rarity and the large number of subtypes, and many entities still lack robust diagnostic hallmarks. RNA transcriptomic profiles have proven to be a reliable basis for the classification of previously unclassified tumors and notably for mesenchymal neoplasms. Using exome-based RNA capture sequencing on more than 5000 samples of archival material (FFPE), the combination of expression profiles analyzes (including several clustering methods), fusion genes, and small nucleotide variations has been developed at the Centre Léon Bérard (CLB) in Lyon for the molecular diagnosis of challenging neoplasms and the discovery of new entities. The molecular basis of the technique, the protocol, and the bioinformatics algorithms used are described herein, as well as its advantages and limitations.

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

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

Sequences to Differences in Gene Expression: Analysis of RNA-Seq Data

RNA-Seq is now a routinely employed assay to measure gene expression. As the technique matured over the last decade, so have dedicated analytic tools. In this chapter, we first describe the mainstream as well as the most up-to-date protocols and their implications on downstream analysis. We then detail the steps entailing RNA-Seq analysis in three main stages: (i) preprocessing and data preparation, (ii) upstream processing, and (iii) high-level analyses. We review the most recent and relevant tools as one workflow following a stepwise order. The chapter further encompasses in-depth features of these tools. Details of the required code are made available throughout the chapter, as well as of the underlying statistics. We illustrate these steps with analysis of publicly available RNA-Seq data.

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.

Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data

BACKGROUND

Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non-poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints.

RESULTS

We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA-minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG-positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq.

CONCLUSION

By using the full potential of non-poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.

Ion Channel and Ubiquitin Differential Expression during Erythromycin-Induced Anhidrosis in Foals

Macrolide drugs are the treatment of choice for Rhodococcus equi infections, despite severe side-effects temporary anhidrosis as a. To better understand the molecular biology leading to macrolide induced anhidrosis, we performed skin biopsies and Quantitative Intradermal Terbutaline Sweat Tests (QITSTs) in six healthy pony-cross foals for three different timepoints during erythromycin administration-pre-treatment (baseline), during anhidrosis and post-recovery. RNA sequencing of biopsies followed by differential gene expression analysis compared both pre and post normal sweating timepoints to the erythromycin induced anhidrosis episode. After Bonferroni correction for multiple testing, 132 gene transcripts were significantly differentially expressed during the anhidrotic timepoint. Gene ontology analysis of the full differentially expressed gene set identified over-represented biological functions for ubiquitination and ion-channel function, both biologically relevant to sweat production. These same mechanisms were previously implicated in heritable equine idiopathic anhidrosis and sweat gland function and their involvement in macrolide-induced temporary anhidrosis warrants further investigation.

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.

Application of the 3' mRNA-Seq using unique molecular identifiers in highly degraded RNA derived from formalin-fixed, paraffin-embedded tissue

Background

Archival formalin-fixed, paraffin-embedded (FFPE) tissue samples with clinical and histological data are a singularly valuable resource for developing new molecular biomarkers. However, transcriptome analysis remains challenging with standard mRNA-seq methods as FFPE derived-RNA samples are often highly modified and fragmented. The recently developed 3′ mRNA-seq method sequences the 3′ region of mRNA using unique molecular identifiers (UMI), thus generating gene expression data with minimal PCR bias. In this study, we evaluated the performance of 3′ mRNA-Seq using Lexogen QuantSeq 3′ mRNA-Seq Library Prep Kit FWD with UMI, comparing with TruSeq Stranded mRNA-Seq and RNA Exome Capture kit. The fresh-frozen (FF) and FFPE tissues yielded nucleotide sizes range from 13 to > 70% of DV200 values; input amounts ranged from 1 ng to 100 ng for validation.

Results

The total mapped reads of QuantSeq 3′ mRNA-Seq to the reference genome ranged from 99 to 74% across all samples. After PCR bias correction, 3 to 56% of total sequenced reads were retained. QuantSeq 3′ mRNA-Seq data showed highly reproducible data across replicates in Universal Human Reference RNA (UHR, R > 0.94) at input amounts from 1 ng to 100 ng, and FF and FFPE paired samples (R = 0.92) at 10 ng. Severely degraded FFPE RNA with ≤30% of DV200 value showed good concordance (R > 0.87) with 100 ng input. A moderate correlation was observed when directly comparing QuantSeq 3′ mRNA-Seq data with TruSeq Stranded mRNA-Seq (R = 0.78) and RNA Exome Capture data (R > 0.67).

Conclusion

In this study, QuantSeq 3′ mRNA-Seq with PCR bias correction using UMI is shown to be a suitable method for gene quantification in both FF and FFPE RNAs. 3′ mRNA-Seq with UMI may be applied to severely degraded RNA from FFPE tissues generating high-quality sequencing data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08068-1.

Comparative analysis of RNA enrichment methods for preparation of Cryptococcus neoformans RNA sequencing libraries

RNA sequencing (RNA-Seq) experiments focused on gene expression involve removal of ribosomal RNA (rRNA) because it is the major RNA constituent of cells. This process, called RNA enrichment, is done primarily to reduce cost: without rRNA removal, deeper sequencing must be performed to compensate for the sequencing reads wasted on rRNA. The ideal RNA enrichment method removes all rRNA without affecting other RNA in the sample. We tested the performance of three RNA enrichment methods on RNA isolated from Cryptococcus neoformans, a fungal pathogen of humans. We find that the RNase H depletion method is more efficient in depleting rRNA and more specific in recapitulating non-rRNA levels present in unenriched controls than the commonly-used Poly(A) isolation method. The RNase H depletion method is also more effective than the Ribo-Zero depletion method as measured by rRNA depletion efficiency and recapitulation of protein-coding RNA levels present in unenriched controls, while the Ribo-Zero depletion method more closely recapitulates annotated non-coding RNA (ncRNA) levels. Finally, we leverage these data to accurately map the C. neoformans mitochondrial rRNA genes, and also demonstrate that RNA-Seq data generated with the RNase H and Ribo-Zero depletion methods can be used to explore novel C. neoformans long non-coding RNA genes.

Metabolic turnover and dynamics of modified ribonucleosides by 13C labeling

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

Tissue-specific transcriptional patterns underlie seasonal phenotypes in honey bees (Apis mellifera)

Faced with adverse conditions, such as winter in temperate regions or hot and dry conditions in tropical regions, many insect species enter a state of diapause, a period of dormancy associated with a reduction or arrest of physical activity, development and reproduction. Changes in common physiological pathways underlie diapause phenotypes in different insect species. However, most transcriptomic studies of diapause have not simultaneously evaluated and compared expression patterns in different tissues. Honey bees (Apis mellifera) represent a unique model system to study the mechanisms underpinning diapause-related phenotypes. In winter, honey bees exhibit a classic diapause phenotype, with reduced metabolic activity, increased physiological nutritional resources and altered hormonal profiles. However, winter bees actively heat their colony by vibrating their wing muscles; thus, this tissue is not quiescent. Here, we evaluated the transcriptional profiles of flight muscle tissue and fat body tissue (involved in nutrient storage, metabolism and immune function) of winter bees. We also evaluated two behavioural phenotypes of summer bees: nurses, which exhibit high nutritional stores and low flight activity, and foragers, which exhibit low nutritional stores and high flight activity. We found winter bees and nurses have similar fat body transcriptional profiles, whereas winter bees and foragers have similar flight muscle transcriptional profiles. Additionally, differentially expressed genes were enriched in diapause-related gene ontology terms. Thus, honey bees exhibit tissue-specific transcriptional profiles associated with seasonal phenotypes, laying the groundwork for future studies evaluating the mechanisms, evolution and consequences of this tissue-specific regulation.

Urinary extracellular vesicles: Assessment of pre-analytical variables and development of a quality control with focus on transcriptomic biomarker research

Urinary extracellular vesicles (uEV) are a topical source of non-invasive biomarkers for health and diseases of the urogenital system. However, several challenges have become evident in the standardization of uEV pipelines from collection of urine to biomarker analysis. Here, we studied the effect of pre-analytical variables and developed means of quality control for uEV isolates to be used in transcriptomic biomarker research. We included urine samples from healthy controls and individuals with type 1 or type 2 diabetes and normo-, micro- or macroalbuminuria and isolated uEV by ultracentrifugation. We studied the effect of storage temperature (-20°C vs. -80°C), time (up to 4 years) and storage format (urine or isolated uEV) on quality of uEV by nanoparticle tracking analysis, electron microscopy, Western blotting and qPCR. Urinary EV RNA was compared in terms of quantity, quality, and by mRNA or miRNA sequencing. To study the stability of miRNA levels in samples isolated by different methods, we created and tested a list of miRNAs commonly enriched in uEV isolates. uEV and their transcriptome were preserved in urine or as isolated uEV even after long-term storage at -80°C. However, storage at -20°C degraded particularly the GC-rich part of the transcriptome and EV protein markers. Transcriptome was preserved in RNA samples extracted with and without DNAse, but read distributions still showed some differences in e.g. intergenic and intronic reads. MiRNAs commonly enriched in uEV isolates were stable and concordant between different EV isolation methods. Analysis of never frozen uEV helped to identify surface characteristics of particles by EM. In addition to uEV, qPCR assays demonstrated that uEV isolates commonly contained polyoma viruses. Based on our results, we present recommendations how to store and handle uEV isolates for transcriptomics studies that may help to expedite standardization of the EV biomarker field.

Systematic detection of m6A-modified transcripts at single-molecule and single-cell resolution

Epigenetic modifications control the stability and translation of mRNA molecules. Here, we present a microscopy-based platform for quantifying modified RNA molecules and for relating the modification patterns to single-cell phenotypes. We directly capture mRNAs from cell lysates on oligo-dT-coated coverslips, then visually detect and sequence individual m6A-immunolabled transcripts without amplification. Integration of a nanoscale device enabled us to isolate single cells on the platform, and thereby relate single-cell m6A modification states to gene expression signatures and cell surface markers. Application of the platform to MUTZ3 leukemia cells revealed a marked reduction in cellular m6A levels as CD34+ leukemic progenitors differentiate to CD14+ myeloid cells. We then coupled single-molecule m6A detection with fluorescence in situ hybridization (FISH) to relate mRNA and m6A levels of individual genes to single-cell phenotypes. This single-cell multi-modal assay suite can empower investigations of RNA modifications in rare populations and single cells.

Whence CRIPTO: The Reemergence of an Oncofetal Factor in 'Wounds' That Fail to Heal

There exists a set of factors termed oncofetal proteins that play key roles in ontogeny before they decline or disappear as the organism's tissues achieve homeostasis, only to then re-emerge in cancer. Although the unique therapeutic potential presented by such factors has been recognized for more than a century, their clinical utility has yet to be fully realized1. This review highlights the small signaling protein CRIPTO encoded by the tumor derived growth factor 1 (TDGF1/Tdgf1) gene, an oft cited oncofetal protein whose presence in the cancer literature as a tumor promoter, diagnostic marker and viable therapeutic target continues to grow. We touch lightly on features well established and well-reviewed since its discovery more than 30 years ago, including CRIPTO's early developmental roles and modulation of SMAD2/3 activation by a selected set of transforming growth factor β (TGF-β) family ligands. We predominantly focus instead on more recent and less well understood additions to the CRIPTO signaling repertoire, on its potential upstream regulators and on new conceptual ground for understanding its mode of action in the multicellular and often stressful contexts of neoplastic transformation and progression. We ask whence it re-emerges in cancer and where it 'hides' between the time of its fetal activity and its oncogenic reemergence. In this regard, we examine CRIPTO's restriction to rare cells in the adult, its potential for paracrine crosstalk, and its emerging role in inflammation and tissue regeneration-roles it may reprise in tumorigenesis, acting on subsets of tumor cells to foster cancer initiation and progression. We also consider critical gaps in knowledge and resources that stand between the recent, exciting momentum in the CRIPTO field and highly actionable CRIPTO manipulation for cancer therapy and beyond.