Nano3P-seq: charting the coding and noncoding transcriptome at single-molecule resolution.

RNA polyadenylation plays a central role in RNA maturation, fate, and stability. In response to developmental cues, polyA tail lengths can vary, affecting the translation efficiency and stability of mRNAs. Here we develop Nanopore 3′ end-capture sequencing (Nano3P-seq), a method that relies on nanopore cDNA sequencing to simultaneously quantify RNA abundance, tail composition, and tail length dynamics at per-read resolution. By employing a template-switching-based sequencing protocol, Nano3P-seq can sequence RNA molecule from its 3′ end, regardless of its polyadenylation status, without the need for PCR amplification or ligation of RNA adapters. We demonstrate that Nano3P-seq provides quantitative estimates of RNA abundance and tail lengths, and captures a wide diversity of RNA biotypes. We find that, in addition to mRNA and long non-coding RNA, polyA tails can be identified in 16S mitochondrial ribosomal RNA in both mouse and zebrafish models. Moreover, we show that mRNA tail lengths are dynamically regulated during vertebrate embryogenesis at an isoform-specific level, correlating with mRNA decay. Finally, we demonstrate the ability of Nano3P-seq in capturing non-A bases within polyA tails of various lengths, and reveal their distribution during vertebrate embryogenesis. Overall, Nano3P-seq is a simple and robust method for accurately estimating transcript levels, tail lengths, and tail composition heterogeneity in individual reads, with minimal library preparation biases, both in the coding and non-coding transcriptome.

Background Acute inflammation leads to increased myelopoiesis in the bone marrow and recruitment of immune cells to respective sites of injury. Yet, in certain cases of high demand such as acute tissue damage as in acute myocardial infarction (AMI), innate immune cells can be additionally recruited from lymphoid organs such as the spleen. Monocytes are important in both onset and resolution of inflammation comprising a huge repertoire of coding and non-coding RNA molecules regulating a fast-acting immune response. Long non-coding RNAs (lncRNA) emerge as novel regulatory cell-specific molecules, which are able to influence cell physiology in numerous ways. Purpose Delineate monocyte subpopulations from patients with AMI compared to healthy controls based on their non-coding transcriptome, different isoform usage and associated source of origin. Methods and results Next generation bulk RNA sequencing has been performed from human monocytes after pre-sorting for CD14 expression and subsequent separation into three major subpopulations based on their surface markers CD14 and CD16 using a FACS Aria II cell sorter. Non-coding RNA expression shows clear differences between cells from healthy controls versus patients with AMI and among subpopulations. Intensive bioinformatics analysis revealed numerous annotated lncRNA, antisense, pseudogene and circular RNAs displaying significant differences in their expression profiles. Some lncRNA show positive or negative correlations with their respective coding antisense gene or their convergent or divergent sense neighbouring gene, such as linc02207 vs MCTP2, SAP30-AS vs SAP30, BID-AS vs BID, HLX-AS vs HLX or TNFAIP3-AS vs TNFAIP3. We also identified the existence of different isoforms of certain lncRNA and a distinct preference thereof, such as linc02207- 217 isoform being most abundant. Real-time PCR was applied for validation of lncRNA expression profile and their nucleocytoplasmic distribution observing preferential nuclear expression for most lncRNA. In vitro assays for silencing and overexpression approaches as well as treatment with inflammatory stimuli and in silico bioinformatics analysis will help to unravel their functionality. Additionally mapping our bulk RNA data to deconvoluted single cell RNAseq data from publicly available human cell atlas (HCA), is applied to additionally unravel the origin of particular subpopulations within the AMI monocytes, associating their origin to either spleen or bone marrow. Conclusions High read depth bulk RNA sequencing revealed a human monocyte-specific long non-coding RNA transcriptome differentially expressed in three predefined subpopulations and disease stages. Distinct expression of lncRNA and associated coding genes as well as distinct isoform preference implies specific functionalities. Studying these molecules and their interaction partners will unravel functional participants in the development of therapeutic approaches for cardiovascular diseases. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): DZHK, SNF

Opposing Polymerase-Deadenylase Activities Regulate Cytoplasmic Polyadenylation

Sequence complexity and abundance classes of nuclear and polysomal polyadenylated RNA in Neurospora crassa

Introduction: Here, we demonstrate Protein Identification by Short-epitope Mapping (PrISM), which aims to provide comprehensive proteome analysis with broad dynamic range at single-molecule resolution by interrogating immobilized, intact proteins in parallel using multi-affinity probes. Improving the dynamic range and scale for protein analyses will enable a deeper understanding of low abundant protein in all stages of cancer progression. In addition, enabling the interrogation of single-molecules will provide a deeper understanding of protein diversity, such as the proteoforms resulting from non-canonical post-translational modifications inherent to cancer1. The combination of single-molecule sensitivity with comprehensive proteome coverage could also open the door for highly sensitive and specific diagnostics. Methods: PrISM uses non-traditional affinity reagents with high affinity and low specificity that bind to short epitopes in multiple proteins. Sample proteins were conjugated to DNA nanoparticles and deposited on a high-density patterned flow cell at optically resolvable locations. Multi-affinity probes were applied to sample proteins over multiple cycles to generate binding patterns for each single-molecule protein, which are translated to protein identifications and quantities using a custom machine learning approach. We acquired PrISM data on native biological and control samples using dozens of multi-affinity probes targeting trimer or tetramer sequences. Results: We report single-molecule deposition of over 1 billion DNA nanoparticle complexes on a flow cell. We demonstrate how the PrISM methodology identifies individual protein molecules through iterative probing with our multi-affinity probes. Further, we provide an analytical assessment of the sensitivity and specificity of PrISM and demonstrate the ability to accurately estimate the false identification rate of these proteins using a target-decoy based statistical approach. Conclusions: Combining single-molecule analysis, intact (non-digested) proteins, and iterative probing, PrISM provides a new tool for quantitative proteomics. We demonstrate linear and reproducible quantification of proteins using PrISM, potentially enabling detection of low abundant proteins and proteoforms associated with cancer. The ability to make comprehensive measurements of intact proteins at single-molecule resolution could accelerate basic cancer research through to the clinic.

Introduction: Serrated colon polyps are found in 15-20% of patients undergoing screening colonoscopy and may account for up to a third of all colorectal cancers (CRC). Sessile serrated adenomas/polyps (SSA/Ps) have a high risk for development into CRC. However, the molecular biology of serrated pathway to cancer is poorly understood. We describe multiple unique non-coding RNA differentially expressed in SSA/Ps and provide an insight into the potential pathways to serrated carcinoma. Methods: Small RNA sequencing was performed on 66 colon RNA samples including 13 SSA/P's, 9 Hyperplastic polyps, 7 Adenomas, 22 uninvolved colon and 15 control colon. The small (< 200 bases) RNA transcriptome of SSA/Ps and other polyp types were characterized to identify unique non-coding RNA expression in SSA/Ps. Gene targets for each of our differentially expressed microRNAs (miRNAs) were identified using multiple miRNA databases. Results: We found 104 small RNAs including 53 miRNA, 46 small nucleolar RNA and 5 nuclear RNA differentially expressed (Fold change >1.5, False discovery rate MIR31) was most differentially expressed (>6 fold) followed by MIR135B expression (>4-fold) in SSA/Ps. MIR378A was downregulated by twofold in SSA/Ps. We identified 14 gene targets for MIR378A that were statistically overexpressed in miRNA sequencing data, four of which are involved in insulin growth factor signaling. Conclusion: We describe a comprehensive analysis of the small non-coding RNA transcriptome in SSA/Ps and HPs. Increased expression of MIR31 has beendescribed in SSA/Ps and our data is consistent with recent studies. MIR135B overexpression and its role in the APC/Wnt pathway has been described in CRC and our study suggests disruption of Wnt signaling possibly playing a role in the serrated pathway. MIR378A is a tumor suppressor gene and we present the first evidence of decreased expression of MIR378A in SSA/Ps. 4 of the 14 MIR378A gene targets identified in our study are important in insulin growth factor signaling pathway which may be contributing to serrated cancer development. Our data provides insights into small RNA expression unique to SSA/Ps and potential oncological pathways which may help understand the molecular biology of progression of SSA/Ps into CRC.

Introduction: Ewing sarcoma family of tumors (EFT) is the second most common primary malignant bone tumor in children and adolescents. It features a characteristic chromosomal translocation; the most common being (t11;22)(q24;q12), which encodes for the chimeric EWS-FLI1 oncoprotein. The disease is highly invasive with a 30% 5-year survival rate for patients with metastatic disease. This study identifies and characterizes a non-coding locus that is unique to EFTs and mediates at least in part the role of the chimeric oncogene in EFT pathogenesis. This particular locus suggests that better understanding of the functional non-coding transcriptome of this developmental cancer can potentially assist in discovering biomarkers that improve the diagnosis and therapeutic management of the disease. Methods: Expression profiles from a panel of 500 tissue samples including over 100 EFTs, other primary tumors, and normal tissues were generated using Affymetrix Human Exon 1.0 ST microarrays. Data were analyzed using institutional software, Genetrix. RNAseq data was generated on two EFT cell lines derived from a primary tumor and its metastatic derivative. Data was validated by PCR on 33 cell lines including EFTs and other tumors. Functional studies on EFT cell lines were performed using various RNAi techniques and viral transductions. Additional characterization of the RNA was done by cellular fractionation studies and northern blots. Results: Expression microarray profiles showed unannotated transcripts to be the strongest discriminators of EFTs from all other tumor types. One such transcript, AK057037, was the most highly expressed RNA (1.07 × 10−20 in EFTs. In silico modeling and RNASeq analyses revealed that this transcript is a multi-exonic, presumably, long non-coding RNA (lncRNA) with a maximum predicted open reading frame of 137 amino acids that had no homology, protein domains, or characteristic motifs. Additionally, multiple variants of the transcript exist in both the nucleus and the cytoplasm. Validation studies confirmed that this lncRNA was exclusively expressed in EFTs. The EFT-specific oncoprotein, EWS-FLI1, regulates expression of this transcript by directly binding to its promoter region. Furthermore, functional data based on knocking down and overexpressing the transcript shows that AK057037 acts as an oncogene in EFT and enhances tumorigenicity by increasing the metastatic potential of the tumor cell lines. Conclusion: The study established that lncRNA AK057037 promotes EFT pathogenesis. Its exclusive presence in EFT suggests that expression of this lncRNA is tissue-specific and highly regulated. Targeting AK057037 in these tumors may help improve outcomes in children with metastatic disease. Further work on the non-coding transcriptome may reveal additional functional RNAs that contribute to the biology of this disease. Citation Format: Sheetal A. Mitra, Daniel H. Wai, William A. May, Jonathan D. Buckley, Philipp Kapranov, Robert J. Arceci, Timothy J. Triche. The transcribed non-coding genome modulates the biology of Ewing sarcoma family of tumors [abstract]. In: Proceedings of the AACR Special Conference on Noncoding RNAs and Cancer; 2012 Jan 8-11; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(2 Suppl):Abstract nr B18.

Developmental regulatin of RNA editing and polyadenylation in four life cycle stages of Trypanosoma congolense

Polyadenylation is a dynamic process that is important in cellular physiology, which has implications in messenger RNA decay rates, translation efficiency, and isoform-specific regulation. Oxford Nanopore Technologies direct RNA sequencing provides a strategy for sequencing the full-length RNA molecule and analysis of the transcriptome. Several tools are currently available for poly(A) tail length estimation, including well-established methods like tailfindr and nanopolish, as well as more recent deep learning models like Dorado. However, there has been limited benchmarking of the accuracy of these tools against gold-standard datasets. In this article, we present our novel deep learning poly(A) estimation tool—BoostNano—and compare with 3 existing tools—tailfindr, nanopolish, and Dorado. We evaluate the 4 poly(A) estimation tools, using 2 sets of synthetic in vitro transcribed RNA standards with known poly(A) tail lengths—Sequin (30 or 60 nucleotides) and enhanced green fluorescent protein (10–150 nucleotides) RNA. Analyzing datasets with known ground-truth values is a valuable approach to measuring the accuracy of poly(A) length estimation. The tools demonstrated length- and sample-dependent performance, and accuracy was enhanced by averaging over multiple reads via estimation of the peak of the density distribution. Overall, Dorado is recommended as the preferred approach due to its relatively fast runtimes, low mean error, and ease of use with integration with base-calling. These results provide a reference for poly(A) tail length estimation analysis, aiding in improving our understanding of the transcriptome and the relationship between poly(A) tail length and other transcriptional mechanisms, including transcript stability or quantification.

A consensus on the folding of the Escherichia coli 16-S ribosomal RNA is emerging and several complete nucleotide sequences of small ribosomal subunit RNAs, covering diverse types of organisms and organelles, are now available. We therefore investigated the extent of both nucleotide sequence and secondary structure conservation that may exist between the E. coli 16-S RNA and other ribosomal RNAs. All the RNA molecules examined could be folded into secondary structure schemes that illustrated remarkable preservation of many structural motifs as well as striking nucleotide sequence conservation compared with the E. coli molecule. This study presents a unitary scheme for the structural organization of the small ribosomal subunit RNAs. The evolutionary constraints on both primary and secondary structures most likely reveal the basic role of some restricted RNA regions in the function of the ribosome.

Deadenylation is a major process that regulates gene expression by shaping the length of mRNA poly(A) tails. Deadenylation is controlled by factors in trans that recruit or impede deadenylases, by theincorporation of non-adenosines during poly(A) tail synthesis, and by the posttranscriptional addition of 3' nucleotides to poly(A) tails. Deciphering the regulation of poly(A) tail shortening requires both transcriptome-wide approaches and more targeted methodologies, allowing deep analyses of specific mRNAs. In this chapter, we present Nano3'RACE, a nanopore-based cDNA sequencing method that allows in-depth analysis to precisely measure poly(A) tail length and detect 3' terminal nucleotide addition, such as uridylation, for mRNAs of interest.

The human transcriptome comprises a complex network of coding and non-coding RNAs implicated in a myriad of biological functions. Non-coding RNAs exhibit highly organized spatial and temporal expression patterns and are emerging as critical regulators of differentiation, homeostasis, and pathological states, including in the cardiovascular system. This review defines the current knowledge gaps, unmet methodological needs, and describes the challenges in dissecting and understanding the role and regulation of the non-coding transcriptome in cardiovascular disease. These challenges include poor annotation of the non-coding genome, determination of the cellular distribution of transcripts, assessment of the role of RNA processing and identification of cell-type specific changes in cardiovascular physiology and disease. We highlight similarities and differences in the hurdles associated with the analysis of the non-coding and protein-coding transcriptomes. In addition, we discuss how the lack of consensus and absence of standardized methods affect reproducibility of data. These shortcomings should be defeated in order to make significant scientific progress and foster the development of clinically applicable non-coding RNA-based therapeutic strategies to lessen the burden of cardiovascular disease.

Organization of tRNA and rRNA genes in N. crassa mitochondria: Intervening sequence in the large rRNA gene and strand distribution of the RNA genes

Early reports indicate that long non-coding RNAs (lncRNAs) are novel regulators of biological responses. However, their role in the human innate immune response, which provides the initial defence against infection, is largely unexplored. To address this issue, here we characterize the long non-coding RNA transcriptome in primary human monocytes using RNA sequencing. We identify 76 enhancer RNAs (eRNAs), 40 canonical lncRNAs, 65 antisense lncRNAs and 35 regions of bidirectional transcription (RBT) that are differentially expressed in response to bacterial lipopolysaccharide (LPS). Crucially, we demonstrate that knockdown of nuclear-localized, NF-κB-regulated, eRNAs (IL1β-eRNA) and RBT (IL1β-RBT46) surrounding the IL1β locus, attenuates LPS-induced messenger RNA transcription and release of the proinflammatory mediators, IL1β and CXCL8. We predict that lncRNAs can be important regulators of the human innate immune response.

Long noncoding RNAs (lncRNAs) are pervasively transcribed and critical regulators of the epigenome[1, 2]. These long, polyadenylated RNAs do not code for proteins, but function directly as RNAs, recruiting chromatin modifiers to mediate transcriptional changes in processes ranging from X-inactivation (XIST) to imprinting (H19)[3]. The recent discovery that lncRNA HOTAIR can link chromatin changes to cancer metastasis[4] furthers the relevance of lncRNAs to human disease. Here, we discuss lncRNAs as regulatory modules and explore the implications for disease pathogenesis. Although large-scale analyses of mammalian transcriptomes have revealed that more than 50% of transcripts have no protein coding potential[2, 5, 6], the functions of these putative transcripts are largely unknown. A subset of these noncoding transcripts are termed long noncoding RNAs (lncRNAs), based on an arbitrary minimum length of 200 nucleotides. LncRNAs are roughly classified based on their position relative to protein-coding genes: intergenic (between genes), intragenic/intronic (within genes), and antisense[2]. Initial efforts to characterize these molecules demonstrated that they function in cis, regulating their immediate genomic neighbors. Examples include AIR, XIST, and Kcnq1ot (reviewed in [1, 7, 8]), which recruit chromatin modifying complexes to silence adjacent sites. The scope of lncRNAs in gene regulation was advanced with the finding that lncRNA HOTAIR exhibited trans regulatory capacities. HOTAIR is transcribed at the intersection of opposing chromatin domains in the HOXC locus, but targets Polycomb Repressive Complex 2 (PRC2) to silence 40 kilobases of HOXD[9], a locus involved in developmental patterning. A subsequent study revealed that HOTAIR is overexpressed in approximately one quarter of human breast cancers, directing PRC2 to approximately 800 ectopic sites in the genome, which leads to histone H3 lysine 27 trimethylation and changes in gene expression[4]. The impacts of lncRNA-mediated chromatin changes are noteworthy: not only did HOTAIR drive metastasis in a mouse model, but HOTAIR expression in human breast cancer was found to be an independent prognostic marker for death and metastasis[4]. The fact that HOTAIR drives chromatin reprogramming genome-wide suggests that long-range regulation by lncRNAs may be a widespread mechanism. This is supported by a study showing that >20% of tested lncRNAs are bound by PRC2 and other chromatin modifiers[10]. Furthermore, this is an underestimate of the total RNAs involved in chromatin modification, as PRC2 target genes also transcribe smaller 50-200 nt RNAs that interact with SUZ12 to mediate gene repression[11]. These findings provoke questions regarding the initial triggers for HOTAIR overexpression and whether understanding of lncRNA mechanics may have clinical relevance.