Total RNA-seq Data Research Articles

Transcriptome-Wide Profiling of Nascent RNA in Neurons with Enriched H3K27ac Signal Elevates eRNA Identification Efficiency.

Growing evidence suggests that activity-dependent gene expression is crucial for neuronal plasticity and behavioral experience. Enhancer RNAs (eRNAs), a class of long noncoding RNAs, play a key role in these processes. However, eRNAs are highly dynamic and are often present at lower levels than their corresponding mRNAs, making them difficult to detect using total RNA-seq techniques. Nascent RNA sequencing, which separates nascent RNAs from the steady-state RNA population, has been shown to increase the ability to detect activity-induced eRNAs with a higher signal-to-noise ratio. However, there is a lack of bioinformatic tools or pipelines for detecting eRNAs utilizing nascent RNA-seq and other multiomics data sets. In this study, we addressed this gap by developing a novel bioinformatic framework, e-finder, for finding eRNAs and have made it available to the scientific community. Additionally, we reanalyzed our previous nascent RNA sequencing data and compared them with total RNA-seq data to identify activity-regulated RNAs in neuronal cell populations. Using H3K27 acetylome data, we characterized activity-dependent eRNAs that drive the transcriptional activity of the target genes. Our analysis identified a subset of eRNAs involved in mediating synapse organization, which showed increased activity-dependent transcription after the potassium chloride stimulation. Notably, our data suggest that nascent RNA-seq with an enriched H3K27ac signal exhibits high resolution to identify potential eRNAs in response to membrane depolarization. Our findings uncover the role of the eRNA-mediated gene activation network in neuronal systems, providing new insights into the molecular processes characterizing neurological diseases.

Accurate assembly of circular RNAs with TERRACE.

Circular RNA (circRNA) is a class of RNA molecules that forms a closed loop with their 5' and 3' ends covalently bonded. CircRNAs are known to be more stable than linear RNAs, have distinct properties and functions, and are promising biomarkers. Existing methods for assembling circRNAs heavily rely on the annotated transcriptomes, hence exhibiting unsatisfactory accuracy without a high-quality transcriptome. We present TERRACE, a new algorithm for full-length assembly of circRNAs from paired-end total RNA-seq data. TERRACE uses the splice graph as the underlying data structure that organizes the splicing and coverage information. We transform the problem of assembling circRNAs into finding paths that "bridge" the three fragments in the splice graph induced by back-spliced reads. We adopt a definition for optimal bridging paths and a dynamic programming algorithm to calculate such optimal paths. TERRACE features an efficient algorithm to detect back-spliced reads missed by RNA-seq aligners, contributing to its much-improved sensitivity. It also incorporates a new machine-learning approach trained to assign a confidence score to each assembled circRNA, which is shown to be superior to using abundance for scoring. On both simulations and biological data sets, TERRACE consistently outperforms existing methods by a large margin in sensitivity while achieving better or comparable precision. In particular, when the annotations are not provided, TERRACE assembles 123%-413% more correct circRNAs than state-of-the-art methods. TERRACE presents a significant advance in assembling full-length circRNAs from RNA-seq data, and we expect it to be widely used in future research on circRNAs.

Unique tRNA Fragment Upregulation with SARS-CoV-2 but Not with SARS-CoV Infection.

Unlike other coronaviruses, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly infected the global population, with some suffering long-term effects. Thanks to extensive data on SARS-CoV-2 made available through global, multi-level collaborative research, investigators are getting closer to understanding the mechanisms of SARS-CoV-2 infection. Here, using publicly available total and small RNAseq data of Calu3 cell lines, we conducted a comparative analysis of the changes in tRNA fragments (tRFs; regulatory small noncoding RNAs) in the context of severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2 infections. We found extensive upregulation of multiple tRFs in SARS-CoV-2 infection that was not present in SARS-CoV or other virus infections our group has studied. By comparing the total RNA changes in matching samples, we identified significant downregulation of TRDMT1 (tRNA methyltransferase), only in SARS-CoV-2 infection, a potential upstream event. We further found enriched neural functions among downregulated genes with SARS-CoV-2 infection. Interestingly, theoretically predicted targets of the upregulated tRFs without considering mRNA expression data are also enriched in neural functions such as axon guidance. Based on a combination of expression data and theoretical calculations, we propose potential targets for tRFs. For example, among the mRNAs downregulated with SARS-CoV-2 infection (but not with SARS-CoV infection), SEMA3C is a theoretically calculated target of multiple upregulated tRFs and a ligand of NRP1, a SARS-CoV-2 receptor. Our analysis suggests that tRFs contribute to distinct neurological features seen in SARS-CoV-2.

Profiling mitochondria-polyribosome lncRNAs associated with pluripotency

Pluripotent stem cells (PSCs) provide unlimited resources for regenerative medicine because of their potential for self-renewal and differentiation into many different cell types. The pluripotency of these PSCs is dynamically regulated at multiple cellular organelle levels. To delineate the factors that coordinate this inter-organelle crosstalk, we profiled those long non-coding RNAs (lncRNAs) that may participate in the regulation of multiple cellular organelles in PSCs. We have developed a unique strand-specific RNA-seq dataset of lncRNAs that may interact with mitochondria (mtlncRNAs) and polyribosomes (prlncRNAs). Among the lncRNAs differentially expressed between induced pluripotent stem cells (iPSCs), fibroblasts, and positive control H9 human embryonic stem cells, we identified 11 prlncRNAs related to stem cell reprogramming and exit from pluripotency. In conjunction with the total RNA-seq data, this dataset provides a valuable resource to examine the role of lncRNAs in pluripotency, particularly for studies investigating the inter-organelle crosstalk network involved in germ cell development and human reproduction.

Comprehensive profiling of enhancer RNA in stage II/III colorectal cancer defines two prognostic subtypes with implications for immunotherapy.

Recently, enhancer RNAs (eRNAs) have garnered attention as pivotal biomarkers for the onset and progression of cancer. However, the landscape of eRNAs and the implications of eRNA-based molecular subtypes in stage II/III colorectal cancer (CRC) remain largely unexplored. Comprehensive profiling of eRNAs was conducted on a public stage II/III CRC cohort with total RNA-seq data. We used unsupervised clustering of prognostic eRNAs to establish an eRNA-based subtyping system. Further evaluations included molecular characteristics, immune infiltration, clinical outcomes, and drug responses. Finally, we validated the eRNA-based subtyping system in The Cancer Genome Atlas (TCGA) CRC cohort. We identified a total of 6453 expressed eRNAs, among which 237 were prognostic. A global upregulation of eRNAs was observed in microsatellite-stable (MSS) CRCs when compared to microsatellite instability-high (MSI-H) CRCs. Through consensus clustering, two novel molecular subtypes, termed Cluster 1(C1) and Cluster 2(C2), were further identified. C1, associated with the activation of epithelial-mesenchymal transition (EMT), hypoxia, and KRAS signaling pathways, showed poorer prognosis. C2, correlated with the canonical CRC subtype, exhibited superior survival outcomes. In addition, C1 showed enrichment with immune infiltration and more sensitivity to immune checkpoint inhibitors. Our study unravels the molecular heterogeneity of stage II/III CRC at the eRNA level and highlights the potential applications of the novel eRNA-based subtyping system in predicting prognosis and guiding immunotherapy.

Circular stable intronic RNAs possess distinct biological features and are deregulated in bladder cancer.

Until recently, intronic lariats were regarded as short-lasting splicing byproducts with no apparent function; however, increasing evidence of stable derivatives suggests regulatory roles. Yet little is known about their characteristics, functions, distribution, and expression in healthy and tumor tissue. Here, we profiled and characterized circular stable intronic sequence RNAs (sisRNAs) using total RNA-Seq data from bladder cancer (BC; n= 457, UROMOL cohort), healthy tissue (n= 46), and fractionated cell lines (n = 5). We found that the recently-discovered full-length intronic circles and the stable lariats formed distinct subclasses, with a surprisingly high intronic circle fraction in BC (∼45%) compared to healthy tissues (0-20%). The stable lariats and their host introns were characterized by small transcript sizes, highly conserved BP regions, enriched BP motifs, and localization in multiple cell fractions. Additionally, circular sisRNAs showed tissue-specific expression patterns. We found nine circular sisRNAs as differentially expressed across early-stage BC patients with different prognoses, and sisHNRNPK expression correlated with progression-free survival. In conclusion, we identify distinguishing biological features of circular sisRNAs and point to specific candidates (incl. sisHNRNPK, sisWDR13and sisMBNL1) that were highly expressed, had evolutionary conserved sequences, or had clinical correlations, which may facilitate future studies and further insights into their functional roles.

Single-nucleus and Spatially Resolved Intratumor Subtype Heterogeneity in Bladder Cancer

BackgroundCurrent bulk transcriptomic classification systems for bladder cancer do not consider the level of intratumor subtype heterogeneity. ObjectiveTo investigate the extent and possible clinical impact of intratumor subtype heterogeneity across early and more advanced stages of bladder cancer. Design, setting, and participantsWe performed single-nucleus RNA sequencing (RNA-seq) of 48 bladder tumors and additional spatial transcriptomics for four of these tumors. Total bulk RNA-seq and spatial proteomics data were available from the same tumors for comparison, along with detailed clinical follow-up of the patients. Outcome measurements and statistical analysisThe primary outcome was progression-free survival for non–muscle-invasive bladder cancer. Cox regression analysis, log-rank tests, Wilcoxon rank-sum tests, Spearman correlation, and Pearson correlation were used for statistical analysis. Results and limitationsWe found that the tumors exhibited varying levels of intratumor subtype heterogeneity and that the level of subtype heterogeneity can be estimated from both single-nucleus and bulk RNA-seq data, with high concordance between the two. We found that a higher class 2a weight estimated from bulk RNA-seq data is associated with worse outcome for patients with molecular high-risk class 2a tumors. The sparsity of the data generated using the DroNc-seq sequencing protocol is a limitation. ConclusionsOur results indicate that discrete subtype assignments from bulk RNA-seq data may lack biological granularity and that continuous class scores may improve clinical risk stratification of patients with bladder cancer. Patient summaryWe found that several molecular subtypes can exist within a single bladder tumor and that continuous subtype scores can be used to identify a subgroup of patients with poor outcomes. Use of these subtype scores may improve risk stratification for patients with bladder cancer, which can help in making decisions on treatment.

Abstract 3307: A novel targeted RNA sequencing approach for identification of aggressive prostate cancer

Abstract Introduction: Prostate cancer (PC) is a highly heterogeneous disease and can be either aggressive, requiring immediate treatment, or remain slow growing and even without treatment present no significant symptoms throughout the man’s life. Currently, there is an unmet need for new tools that can clearly distinguish indolent from aggressive PC in order to guide treatment decisions.PC is a highly heritable disease and so far, approximately 450 genomic regions associated with PC risk have been defined in genome-wide association studies. Most of these regions are however devoid of annotated genes and consequently the underlying mechanisms behind the associations are not easily elucidated. Accordingly, yet uncharacterized genes in PC-associated regions could be involved in PC development/progression. Methods: We quantified gene expression levels by Kallisto on total RNAseq data from fresh frozen prostate tissue samples from 134 localized PCs, 33 matched adjacent normal (AN) areas as well as 15 PC cell lines. Furthermore, we performed targeted RNAseq covering approximately seven million base pairs divided among 101 PC-risk associated regions (GWAS hits) for in-depth transcriptomic analyses in the same set of samples. HISAT and StringTie were used to identify novel transcripts (genes) with the criteria that a given gene had to have at least 10 reads in more than 50% of all samples to be included. Patient genotyping was performed on Illumina’s global screening array. Results: In totalRNA seq data we observed significant dysregulation of 10,256 genes (5,685 up- and 4,571 downregulated) between AN and localized PC, including upregulation of know PC-associated genes such as SIM2, PCAT7, TDRD1, and TFF3. Interestingly, we found a correlation between high transcription of TFF3 and high risk of biochemical recurrence (BCR) after radical prostatectomy and furthermore a trans-acting eQTL, the PC-risk associated SNP rs1938781. Here, heterozygote patients with the risk-allele had higher risk of BCR than patients homozygous for the reference allele, indicating a potential functional relationship between the PC risk-SNP and TFF3. Additionally, we detected 207 previously unannotated non-coding genes in the capture RNAseq data, where 148 (71.5%) were undetectable in the matched total RNAseq data indicating the existence of stably albeit lowly expressed genes in the genomic areas containing PC-risk SNPs. Citation Format: Jacob Fredsøe, Christa Haldrup, Iver Nordentoft, Benedicte Ulhøi, Michael Borre, Karina D. Sørensen. A novel targeted RNA sequencing approach for identification of aggressive prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3307.

Abstract 3778: Genome-Scale CRISPRa and CRISPRi screening for lncRNA drivers of prostate cancer progression

Abstract Background: Overtreatment of indolent prostate cancer (PC) and delayed treatment of aggressive PC is common due to suboptimal risk stratification tools, thus warranting identification of novel prognostic biomarkers. Although a few long non-coding RNAs (lncRNAs) with biomarker potential in PC are known, the majority of lncRNAs remain uncharacterized. Here, we aimed to identify novel lncRNA biomarker candidates. We hypothesized that strong candidates would have a functional role in driving PC progression in addition to their expression being linked to PC prognosis, and we therefore combined functional CRISPR screening with lncRNA expression profiling of PC patients. Methods: Total RNA sequencing (RNAseq) data was generated from 31 adjacent normal (AN) and 125 tumor samples from 141 clinically localized PC patients, along with 17 primary tumor samples from metastatic PC patients. Raw reads were mapped to the hg38 reference genome and kallisto was used for quantification. CRISPR activating (CRISPRa) and CRISPR interference (CRISPRi) screens were performed in the LNCaP PC cell line stably expressing either dCas9-VP64 or dCas9-KRAB, respectively. Cells were transduced in duplicate with custom single guide RNA (sgRNA) libraries targeting 20,306 and 20,474 lncRNA transcripts of interest using 72,281 and 72,360 sgRNAs (CRISPRa and CRISPRi, respectively). Cells were harvested and DNA extracted from an early (day 4 post-transduction) and a late (day 17-21) timepoint and next-generation sequenced. MAGeCK was used for data analysis. Results: To identify lncRNAs with biomarker potential in PC, we analyzed lncRNA expression in total RNAseq data from 158 PC patients. Using differential expression analysis and cox regression analysis with biochemical recurrence as endpoint, we identified 6,928 lncRNAs with biomarker potential. To investigate if any of these had a functional role in driving PC progression, we performed CRISPRa and CRISPRi screens to assess how lncRNA activation/inhibition affected PC cell proliferation. Based on the screens, lncRNA candidates with the most prominent phenotypes (normalized read count difference >200 and log-fold change >33% between the early and late timepoint for ≥3 sgRNAs in both replicates) were selected for individual validation. This identified 7 (CRISPRa) and 8 (CRISPRi) negative hits (decreased cell proliferation) along with 5 (CRISPRa) and 2 (CRISPRi) positive hits (increased cell proliferation). Individually activated/inhibited LNCaP cell lines have been established for the 22 candidate lncRNAs and proliferation assays are performed to validate their functional role in PC progression. Conclusion: We identified numerous lncRNAs with biomarker potential and a possible driver role in PC progression. Citation Format: Simone Weiss, Allegra Lord, Bernhard Schmierer, Anne B. Rovsing, Emil A. Thomsen, Jacob G. Mikkelsen, Benedicte Ulhøi, Jakob S. Pedersen, Michael Borre, Karina D. Sørensen. Genome-Scale CRISPRa and CRISPRi screening for lncRNA drivers of prostate cancer progression. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3778.

The transcriptomic landscape of neurons carrying PSEN1 mutations reveals changes in extracellular matrix components and non-coding gene expression

Alzheimer's disease (AD) is a progressive and irreversible brain disorder, which can occur either sporadically, due to a complex combination of environmental, genetic, and epigenetic factors, or because of rare genetic variants in specific genes (familial AD, or fAD). A key hallmark of AD is the accumulation of amyloid beta (Aβ) and Tau hyperphosphorylated tangles in the brain, but the underlying pathomechanisms and interdependencies remain poorly understood. Here, we identify and characterise gene expression changes related to two fAD mutations (A79V and L150P) in the Presenilin-1 (PSEN1) gene. We do this by comparing the transcriptomes of glutamatergic forebrain neurons derived from fAD-mutant human induced pluripotent stem cells (hiPSCs) and their individual isogenic controls generated via precision CRISPR/Cas9 genome editing. Our analysis of Poly(A) RNA-seq data detects 1111 differentially expressed coding and non-coding genes significantly altered in fAD. Functional characterisation and pathway analysis of these genes reveal profound expression changes in constituents of the extracellular matrix, important to maintain the morphology, structural integrity, and plasticity of neurons, and in genes involved in calcium homeostasis and mitochondrial oxidative stress. Furthermore, by analysing total RNA-seq data we reveal that 30 out of 31 differentially expressed circular RNA genes are significantly upregulated in the fAD lines, and that these may contribute to the observed protein-coding gene expression changes. The results presented in this study contribute to a better understanding of the cellular mechanisms impacted in AD neurons, ultimately leading to neuronal damage and death.

Differential venom gland gene expression analysis of juvenile and adult scorpions Androctonus crassicauda

BackgroundThe Androctonus crassicauda, belonging to the genus Androctonus of the family Buthidae, is the most venomous scorpion in Middle East countries. However, the venom gland transcriptome profile of A. crassicauda scorpion has not yet been studied. In this study, we elucidated and compared the venom gland gene expression profiles of adult and juvenile male scorpion A. crassicauda using high-throughput transcriptome sequencing. This is the first report of transcriptional analysis of the venom glands of scorpions in different growth stages, with insights into the identification of the key genes during venom gland development.ResultsA total of 209,951 mRNA transcripts were identified from total RNA-seq data, of which 963 transcripts were differentially expressed (DE) in adult and juvenile scorpions (p < 0.01). Overall, we identified 558 up-regulated and 405 down-regulated transcripts in the adult compared to the juvenile scorpions, of which 397 and 269 unique unigenes were annotated, respectively. GO and KEGG enrichment analyses indicated that the metabolic, thermogenesis, cytoskeleton, estrogen signaling, GnRH signaling, growth hormone signaling, and melanogenesis pathways were affected by two different growth conditions and the results suggested that the DE genes related to those pathways are important genes associated with scorpion venom gland development, in which they may be important in future studies, including Chs, Elovl, MYH, RDX, ACTN, VCL, PIP5K, PP1C, FGFR, GNAS, EGFR, CREB, CoA, PLCB, CALM, CACNA, PKA and CAMK genes.ConclusionsThese findings broadened our knowledge of the differences between adult and juvenile scorpion venom and opened new perspectives on the application of comparative transcriptome analysis to identify the special key genes.

Metagenomics versus total RNA sequencing: most accurate data-processing tools, microbial identification accuracy and perspectives for ecological assessments.

Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine ecological assessments. However, these target-PCR-free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 672 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for target-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine ecological assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into ecological assessments.

Paired miRNA and RNA sequencing provides a first insight into molecular defense mechanisms of Scapharca broughtonii during ostreid herpesvirus-1 infection

Ostreid herpesvirus 1 (OsHV-1) infection caused mortalities with relevant economic losses in bivalve aquaculture industry worldwide. Initially described as an oyster pathogen, OsHV-1 can infect other bivalve species, like the blood clam Scapharca broughtonii. However, at present, little is known about the molecular interactions during OsHV-1 infection in the blood clam. We produced paired miRNA and total RNA-seq data to investigate the blood clam transcriptional changes from 0 to 72 h after experimental infection with OsHV-1. High-throughput miRNA sequencing of 24 libraries revealed 580 conserved and 270 new blood clam miRNAs, whereas no genuine miRNA was identified for OsHV-1. Total 88–203 differently expressed miRNAs were identified per time point, mostly up-regulated and mainly targeting metabolic pathways. Most of the blood clam mRNAs, in contrast, were down-regulated up to 60 h post-injection, with the trend analysis revealing the activation of immune genes only when comparing the early and latest stage of infection. Taken together, paired short and long RNA data suggested a miRNA-mediated down-regulation of host metabolic and energetic processes as a possible antiviral strategy during early infection stages, whereas antiviral pathways appeared upregulated only at late infection.

MP39-14 IDENTIFICATION OF RECURRENT SOMATIC SPLICE SITE VARIANTS ACROSS MULTIPLE CLEAR CELL RENAL CELL CARCINOMA COHORTS

You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology I (MP39)1 Sep 2021MP39-14 IDENTIFICATION OF RECURRENT SOMATIC SPLICE SITE VARIANTS ACROSS MULTIPLE CLEAR CELL RENAL CELL CARCINOMA COHORTS Nicholas Chakiryan, Timothy Robinson, Dongliang Du, Ali Hajiran, Logan Zemp, Youngchul Kim, Jad Chahoud, Philippe Spiess, Liang Wang, James Mule, and Brandon Manley Nicholas ChakiryanNicholas Chakiryan More articles by this author , Timothy RobinsonTimothy Robinson More articles by this author , Dongliang DuDongliang Du More articles by this author , Ali HajiranAli Hajiran More articles by this author , Logan ZempLogan Zemp More articles by this author , Youngchul KimYoungchul Kim More articles by this author , Jad ChahoudJad Chahoud More articles by this author , Philippe SpiessPhilippe Spiess More articles by this author , Liang WangLiang Wang More articles by this author , James MuleJames Mule More articles by this author , and Brandon ManleyBrandon Manley More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002054.14AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Splice-site variants (SV) are DNA mutations that ultimately result in abnormal mRNA splicing and a dramatically altered protein-coding sequence. SVs in clear cell renal cell carcinoma (ccRCC) have been largely unexplored. Our primary objective was to identify the most prevalent SVs in ccRCC, and determine their prevalence in other malignancies and adjacent normal kidney tissue. METHODS: Specific SVs were identified in RCC cell lines from the Broad Institute Cancer Cell Line Encyclopedia. Patients with a diagnosis of ccRCC were then identified in the Moffitt Cancer Center Total Cancer Care (TCC) cohort and RNA-seq data was utilized in a bioinformatics pipeline to identify the SVs among the TCC cohort. SVs identified in the TCC ccRCC cohort were then identified in TCC patients with non-ccRCC malignancies. This process was then repeated for the ccRCC RNA-seq data from CPTAC and TCGA, as well as from adjacent normal kidney tissue from these data sets. The most prevalent SVs among the ccRCC were selected for analysis, using a minimum SV read count threshold of 10. RESULTS: Among the three ccRCC datasets, 756 patients with ccRCC tumor samples were identified (N: TCC 104, CPTAC 111, TCGA 541). Eight distinct SVs were found to have high ccRCC prevalence and low prevalence in adjacent normal kidney tissue and non-ccRCC malignancies (Figure 1A). Genes with multiple distinct SVs were classified separately. The GAL3ST1-a and GAL3ST1-b SVs had the highest prevalence in ccRCC, as well as the highest read count per patient (Figure 1B). In the TCC ccRCC cohort, low read counts of SVs from the GAL3ST1 gene were associated with stage cM1. CONCLUSIONS: We identified eight novel SVs that are highly prevalent in ccRCC tumors and minimally prevalent in adjacent normal kidney tissue and other malignancies. Particularly striking were four distinct SVs affecting the the GAL3ST1 gene. These novel SVs warrant further investigation as potential biomarkers in ccRCC. Source of Funding: N/A © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e709-e710 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Nicholas Chakiryan More articles by this author Timothy Robinson More articles by this author Dongliang Du More articles by this author Ali Hajiran More articles by this author Logan Zemp More articles by this author Youngchul Kim More articles by this author Jad Chahoud More articles by this author Philippe Spiess More articles by this author Liang Wang More articles by this author James Mule More articles by this author Brandon Manley More articles by this author Expand All Advertisement Loading ...

Simple mapping-based quantification of a mock microbial community using total RNA-seq data.

Most microbes in the natural environment are difficult to cultivate. Thus, culture-independent analysis for microbial community structure is important for the understanding of its ecological functions. An immense ribosomal RNA sequence collection is available from phylogenetic research on organisms in all domains. These sequences are available for use in genetic research. However, the amplicon-seq process using PCR requires the construction of a sequence library. Construction can introduce bias into quantitative analyses, and each domain of species needs its own primer set. Total RNA sequencing has the advantage of analyzing an entire microbial community, including bacteria, archea, and eukaryote, at once. Such analysis yields large amounts of ribosomal RNA sequences that can be used for analysis without PCR bias. Evaluation using total RNA-seq for quantitative analysis of microbial communities and comparison with amplicon-seq is still rare. In the present study, we developed a mapping-based total RNA-seq analysis to obtain quantitative information on microbial community structure and compared our results with ordinary amplicon-seq methods. We read total RNA sequences from a commercially available mock community (ATCC MSA-2003) and divided reads into small subunit ribosomal RNA (ssrRNA) origin reads and others, such as mRNA origin reads. We then mapped ssrRNA origin reads on annotated assembled contigs and obtained quantitative results under several analysis strategies. Removal of low complexity sequences, sorting ssrRNA with paired-in mode, and performing homology-based taxonomical assignments (BLAST+ or vsearch) showed superior outcomes to other strategies. Results with this approach showed a median relative abundance among ten mock community members of ~10%; ordinary amplicon-seq showed a much lower percentage. Thus, total RNA-seq can be a powerful tool for analyzing microbial community structure and is not limited to analyzing gene expression profiling of microbiomes.

Loss of Cnot6l Impairs Inosine RNA Modifications in Mouse Oocytes.

Mammalian oocytes must degrade maternal transcripts through a process called translational mRNA decay, in which maternal mRNA undergoes translational activation, followed by deadenylation and mRNA decay. Once a transcript is translationally activated, it becomes deadenylated by the CCR4-NOT complex. Knockout of CCR4-NOT Transcription Complex Subunit 6 Like (Cnot6l), a deadenylase within the CCR4-NOT complex, results in mRNA decay defects during metaphase I (MI) entry. Knockout of B-cell translocation gene-4 (Btg4), an adaptor protein of the CCR4-NOT complex, results in mRNA decay defects following fertilization. Therefore, mechanisms controlling mRNA turnover have significant impacts on oocyte competence and early embryonic development. Post-transcriptional inosine RNA modifications can impact mRNA stability, possibly through a translation mechanism. Here, we assessed inosine RNA modifications in oocytes, eggs, and embryos from Cnot6l-/- and Btg4-/- mice, which display stabilization of mRNA and over-translation of the stabilized transcripts. If inosine modifications have a role in modulating RNA stability, we hypothesize that in these mutant backgrounds, we would observe changes or a disruption in inosine mRNA modifications. To test this, we used a computational approach to identify inosine RNA modifications in total and polysomal RNA-seq data during meiotic maturation (GV, MI, and MII stages). We observed pronounced depletion of inosine mRNA modifications in samples from Cnot6l-/-, but not in Btg4-/- mice. Additionally, analysis of ribosome-associated RNA revealed clearance of inosine modified mRNA. These observations suggest a novel mechanism of mRNA clearance during oocyte maturation, in which inosine-containing transcripts decay in an independent, but parallel mechanism to CCR4-NOT deadenylation.

Novel circRNA discovery in sheep shows evidence of high backsplice junction conservation

Circular RNAs (circRNAs) are covalently closed circular non-coding RNAs. Due to their structure, circRNAs are more stable and have longer half-lives than linear RNAs making them good candidates for disease biomarkers. Despite the scientific relevance of these molecules, the study of circRNAs in non-model organisms is still in its infancy. Here, we analyse total RNA-seq data to identify circRNAs in sheep from peripheral blood mononuclear cells (PBMCs) and parietal lobe cortex. Out of 2510 and 3403 circRNAs detected in parietal lobe cortex and in PBMCs, a total of 1379 novel circRNAs were discovered. Remarkably, around 63% of all detected circRNAs were found to be completely homologous to a circRNA annotated in human. Functional enrichment analysis was conducted for both tissues based on GO terms and KEGG pathways. The enriched terms suggest an important role of circRNAs from encephalon in synaptic functions and the involvement of circRNAs from PBMCs in basic immune system functions. In addition to this, we investigated the role of circRNAs in repetitive vaccination experiments via differential expression analysis and did not detect any significant relationship. At last, our results support both the miRNA sponge and the miRNA shuttle functions of CDR1-AS in sheep brain. To our knowledge, this is the first study on circRNA annotation in sheep PBMCs or parietal lobe cortex samples.

Genome-Wide Analysis of the Expression of Circular RNA Full-Length Transcripts and Construction of the circRNA-miRNA-mRNA Network in Cervical Cancer.

Increasing evidence suggests that circular RNA (circRNA) plays an important role in tumorigenesis by regulating gene expression at the transcriptional and post-transcriptional levels. Alternative splicing events permit multiple transcript isoforms of circRNA to be produced; however, changes in the expression of circRNA full-length transcripts in cervical cancer remain unclear. Here, we systematically explored the dysregulation circRNA full-length transcripts and constructed an improved circRNA-miRNA-mRNA regulatory network to provide potential biomarkers and possible treatment targets in cervical cancer. We identified 9359 circular full-length transcripts from RNase R-treated RNA-seq data in cervical cancer, of which 353 circular full-length transcripts were significantly differentially expressed (DE) between the tumor and normal group. A total of 881 DE mRNA transcript isoforms were also identified from total RNA-seq data in cervical cancer, of which 421 (47.8%) transcript isoforms were up-regulated, and 460 (52.2%) transcript isoforms were down-regulated in tumor samples. Two circRNA-miRNA-mRNA competitively regulated networks, including 33 circRNA transcripts, 2 miRNAs, and 189 mRNA transcripts were constructed. Three genes (COPE, RAB3B, and TFPI) in the network were significantly associated with overall survival (P < 0.05), which indicated that these genes could act as prognostic biomarkers for patients with cervical cancer. Our study revealed genome-wide differential expression of full-length circRNA transcripts and constructed a more accurate circRNA-miRNA-mRNA network at the full-length transcript expression level in cervical cancer. CircRNA may thus be involved in the development of cervical cancer by regulating the expression of COPE, RAB3B, and TFPI. However, the specific regulatory mechanism in cervical cancer requires further study.

A SINE-VNTR-Alu in the LRIG2 Promoter Is Associated with Gene Expression at the Locus.

The hominid SINE-VNTR-Alu (SVA) retrotransposons represent a repertoire of genomic variation which could have significant effects on genome function. A human-specific SVA in the promoter region of the gene leucine-rich repeats and immunoglobulin-like domains 2 (LRIG2), which we termed SVA_LRIG2, is a common retrotransposon insertion polymorphism (RIP), defined as an element which is polymorphic for its presence or absence in the genome. We hypothesised that this RIP might be associated with differential levels of expression of LRIG2. The RIP genotype of SVA_LRIG2 was determined in a subset of frontal cortex DNA samples from the North American Brain Expression Consortium (NABEC) cohort and was imputed for a larger set of that cohort. Utilising available frontal cortex total RNA-seq and CpG methylation data for this cohort, we observed that increased allele dosage of SVA_LRIG2 was non-significantly associated with a decrease in transcription from the region and significantly associated with increased methylation of the CpG probe nearest to SVA_LRIG2, i.e., SVA_LRIG2 is a significant methylation quantitative trait loci (mQTL) at the LRIG2 locus. These data are consistent with SVA_LRIG2 being a transcriptional regulator, which in part may involve epigenetic modulation.

Genome-wide dynamics of RNA synthesis, processing, and degradation without RNA metabolic labeling.

The quantification of the kinetic rates of RNA synthesis, processing, and degradation are largely based on the integrative analysis of total and nascent transcription, the latter being quantified through RNA metabolic labeling. We developed INSPEcT−, a computational method based on the mathematical modeling of premature and mature RNA expression that is able to quantify kinetic rates from steady-state or time course total RNA-seq data without requiring any information on nascent transcripts. Our approach outperforms available solutions, closely recapitulates the kinetic rates obtained through RNA metabolic labeling, improves the ability to detect changes in transcript half-lives, reduces the cost and complexity of the experiments, and can be adopted to study experimental conditions in which nascent transcription cannot be readily profiled. Finally, we applied INSPEcT− to the characterization of post-transcriptional regulation landscapes in dozens of physiological and disease conditions. This approach was included in the INSPEcT Bioconductor package, which can now unveil RNA dynamics from steady-state or time course data, with or without the profiling of nascent RNA.