Project description:We report isoCirc, a long-read sequencing strategy coupled with an integrated computational pipeline to characterize full-length circular RNA (circRNA isoforms) using rolling circle amplification (RCA) followed by long-read sequencing. Applying isoCirc to 12 human tissues, we determined full-length structures and examined tissue specificities of circRNA isoforms in human transcriptomes.
Project description:Circular RNAs (circRNAs) have been found abundantly expressed in cancer. Their resistance to exonucleases enables them to have potentially stable interactions with with different types of biomolecules. Alternative splicing can create different circRNA isoforms that have different sequences and unequal interaction potentials. The study of circRNA function thus requires knowledge of complete circRNA sequences. Here we describe psirc, a method that can identify full-length circRNA isoforms and quantify their expression levels using RNA sequencing data. We confirm the effectiveness and computational efficiency of psirc using both simulated and actual experimental data. Applying psirc on transcriptome profiles from nasopharyngeal carcinoma and normal nasopharynx samples, we discovered circRNA isoforms differentially expressed between the two groups. Compared to the assumed circular isoforms derived from linear transcript annotations, some of the alternatively spliced circular isoforms have 100 times higher expression and contain fewer microRNA response elements, demonstrating the importance of quantifying full-length circRNA isoforms.
Project description:We developed a hybrid-sequencing workflow, combining next-generation and third-generation sequencing, to reconstruct full-length transcriptomes. Integrating with polysome profiling and ribosome footprinting data, we predicted isoform–specific translational status and reconstructed ORFeome. Moreover, we identified isoforms with specific subcellular localization pattern in neurons.
Project description:Alternative splicing generates differing RNA isoforms that govern phenotypic complexity of eukaryotes. Its malfunction underlies many diseases, including cancer and cardiovascular diseases. Comparative analysis of RNA isoforms at the genome-wide scale has been difficult. Here, we established an experimental and computational pipeline that accurately quantifies transcript isoforms in their entire length from cDNA sequences with a full-length isoform detection accuracy of 97.6%. We generated a searchable, quantitative human transcriptome annotation with 31,025 known and 5,740 novel transcript isoforms (http://steinmetzlab.embl.de/iBrowser/). By analyzing the isoforms in the presence of RNA Binding Motif Protein 20 (RBM20) mutations associated with aggressive dilated cardiomyopathy (DCM), we identified 121 differentially expressed transcript isoforms in 107 cardiac genes. By establishing an isoform-differential expression test, our approach revealed that 11 of these genes displayed no detectable change in overall RNA expression. However, significant differences in the expression of specific isoforms in these genes was observed. These isoform specific effects demonstrate the need of analyzing RNA isoform expression levels rather than total gene expression levels.
Project description:To identify aberrant splicing isoforms and potential neoantigens, we performed full-length cDNA sequencing of lung adenocarcinoma cell lines using a long-read sequencer MinION. We constructed a comprehensive catalog of aberrant splicing isoforms and detected isoform-specific peptides using proteome analysis.
Project description:While numerous studies have described the transcriptomes of EVs in different cellular contexts, these efforts have typically relied on sequencing methods requiring RNA fragmentation, which limits interpretations on the integrity and isoform diversity of EV-encapsulated RNA populations. Furthermore, it has been assumed that mRNA signatures in EVs are likely to be fragmentation products of the cellular mRNA material, and little is known about the extent to which full-length mRNAs are present within EVs. Using Oxford nanopore long-read RNA sequencing, we sought to characterize the full-length polyadenylated (poly-A) transcriptome of EVs released by human chronic myelogenous leukemia K562 cells. We detected 441 and 280 RNAs that were respectively enriched or depleted in EVs. EV-enriched poly-A transcripts consist of a variety of biotypes, including mRNAs, long non-coding RNAs, and pseudogenes. Our analysis revealed that 12.72% of all reads present in EVs corresponded to known full-length transcripts, 65.34% of which were mRNAs. We also observed that for many well-represented coding and non-coding genes, diverse full-length transcript isoforms were present in EV specimens, and these isoforms were reflective-of but often in different ratio compared to cellular samples. Here we report a full-length transcriptome from human EVs, as determined by long-read nanopore sequencing.
Project description:We optimized a protocol to enrich, digest and add poly(A) tail to the circular RNAs in order to make them compatible with the Oxfor Nanopore Technology for full-length sequencing
Project description:Brain cells release and take up small extracellular vesicles (sEVs) containing bioactive nucleic acids. sEV exchange is hypothesized to contribute to stereotyped spread of neuropathological changes in the diseased brain. We assessed mRNA from sEVs of non-diseased (ND) and Alzheimer’s disease (AD) human postmortem brain, using short- and long-read sequencing. sEV transcriptomes were distinct from bulk tissue, showing enrichment for multiple genes including mRNAs encoding ribosomal proteins and L1Hs transposable elements. AD versus ND sEVs showed enrichment of inflammation-related and depletion of synaptic signaling mRNAs. sEV mRNA from cultured murine primary neurons, astrocytes, or microglia showed similarities with human brain sEVs and revealed cell-type specific packaging. Nearly 80% of human brain sEV transcripts sequenced using long-read sequencing were full-length. Motif analyses of sEV-enriched full-length isoforms revealed RNA-binding proteins that may be associated with sEV loading. Collectively, we show that mRNA in brain sEVs is selectively-packaged and altered by disease state.