Project description:Long-read sequencing has become a powerful tool for alternative splicing analysis. However, technical and computational challenges have limited our ability to couple long-read sequencing with single cell and spatial barcoding to explore alternative splicing in the single cell and spatial setting. Though Nanopore-based long reads sequencing are widelyhave been adopted applied to explore single cell alternative and spatially barcoded librariessplicing in recent research, there still exist technical issues have problems which could bias the hindered accurate single cell isoform-level quantification, which are not well addressed in such settings. First, Tthe relatively higher sequencing error of Nanopore long reads, despite the recent improvements, has limited the accuracy ofhinder cell barcode and unique molecular identifier (UMI) recovery, a necessary first step in the analysis of single cell/spatial sequencing data. Then Rread truncation and mapping errors, the latter exacerbated by the higher sequencing error rates, further leads to the false detection of spurious new isoformsdegrade quantification accuracy. We show that these technical issues persist despite the recent improvements in long read sequencing accuracy. Beyond the initial data pre-processing, in downstream analysis we are lacking a statistical framework to quantify splicing variation within and between cells/spots. In light of these multiple challenges, we developed Longcell, a statistical framework and computational pipeline for isoform quantification using single cell and spatial spot barcoded Nanopore long read sequencing data. Longcell performs computationally efficient cell/spot barcode extraction, UMI recovery, and UMI-based truncation- and mapping-error correction. Through a statistical model that accounts for varying read coverage across cells/spots, Longcell rigorously quantifies the level of inter-cell/spot versus intra-cell/ spot diversity in exon-usage and detects changes in splicing distributions between cell populations. Applying Longcell to single cell long-read data from multiple contexts, we found that intra-cell splicing heterogeneity, where multiple isoforms co-exist within the same cell, is ubiquitous for highly expressed genes. On matched single cell and Visium long read sequencing for a tissue of colorectal cancer metastasis to the liver, Longcell found concordant signals between the single cell and spatial data modalities. On Visium long read sequencing data for multiple tissues, Longcell allows accurate identification of spatial isoform switching. Finally, on a perturbation experiment for 9 splicing factors, Longcell identified regulatory targets that are validated by targeted sequencing.
Project description:Purpose: To generate a reference long-read transcriptomic data set for use in developing new analysis pipelines and comparing their performance with existing methods. Synthetic “sequin” RNA standards (Hardwick et al. 2016) were sequenced using the Oxford Nanopore Technologies (ONT) GridION platform.
Project description:This dataset contains Xdrop followed by oxford nanopore long read sequencing performed in target tRNA gene deletion (t8) and intergenic region deletion (i50) clones in HepG2 . By applying de novo assembly based approach to Xdrop-LRS data, we identified Cas9-induced on-target genomic alteration.
Project description:This project aims to leverage Oxford Nanopore Technologies (ONT) long-read RNA sequencing to achieve a comprehensive analysis of the human pancreatic cancer transcriptome. Traditional short-read sequencing methods often struggle with accurately reconstructing full-length transcripts and discerning complex splicing events due to their limited read lengths. In contrast, ONT's long-read sequencing can generate reads that span entire RNA molecules, facilitating precise identification of transcript isoforms, alternative splicing patterns, and poly(A) tail length. By applying this technology, we seek to enhance the annotation of the pancreatic cancer transcriptome, uncover novel transcripts, and gain deeper insights into gene expression dynamics. The findings from this study have the potential to advance our understanding of gene regulation and contribute to the development of novel therapeutic strategies.
Project description:Tuberous sclerosis complex (TSC) is a relatively common autosomal dominant disorder characterized by multiple dysplastic organ lesions and neuropsychiatric symptoms, caused by loss-of-function mutation of either TSC1 or TSC2. Target-capture full-length double-stranded cDNA sequencing using long-read sequencer Nanopore (Nanopore Long-read Target Sequencing) revealed that the various kinds of the TSC1 and TSC2 full-length transcripts and the novel intron retention transcripts of TSC2 in TSC patient. Our results indicate that the Nanopore Long-read Target Sequencing is useful for the detection of mutations and confers information on the full-length alternative splicing transcripts for the genetic diagnosis.
Project description:This dataset contains Xdrop followed by oxford nanopore long read sequencing performed in target tRNA gene deletion clones in HAP1 (t72) and HepG2 (t15). By applying de novo assembly based approach to Xdrop-LRS data, we identified Cas9-induced on-target genomic alteration.
Project description:To investigate the comprehensive function of PQBP1 in the regulation of RNA splicing, we established Dox-inducible PQBP1 knockdown HEY cell line. We then performed transcript expression profiling analysis using data obtained from long-read nanopore-seq of PQBP1 knockdown and control HEY cells (three biological replications of each sample).