Project description:Higher-order chromatin structure arises from the combinatorial physical interactions of many genomic loci. To investigate this aspect of genome architecture we developed Pore-C, which couples chromatin conformation capture with Oxford Nanopore Technologies (ONT) long reads to directly sequence multi-way chromatin contacts without amplification.
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: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 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: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:Alternative splicing is widely acknowledged to be a crucial regulator of gene expression and is a key contributor to both normal developmental processes and disease states. While cost-effective and accurate for quantification, short-read RNA-seq lacks the ability to resolve full-length transcript isoforms despite increasingly sophisticated computational methods. Long-read sequencing platforms such as Pacific Biosciences (PacBio) and Oxford Nanopore (ONT) bypass the transcript reconstruction challenges of short-reads. Here we describe TALON, the ENCODE4 pipeline for analyzing PacBio cDNA and ONT direct-RNA transcriptomes. We apply TALON to three human ENCODE Tier 1 cell lines and show that while both technologies perform well at full-transcript discovery and quantification, each technology has its distinct artifacts. We further apply TALON to mouse cortical and hippocampal transcriptomes and find that a substantial proportion of neuronal genes have more reads associated with novel isoforms than annotated ones. The TALON pipeline for technology-agnostic, long-read transcriptome discovery and quantification tracks both known and novel transcript models as well as expression levels across datasets for both simple studies and larger projects such as ENCODE that seek to decode transcriptional regulation in the human and mouse genomes to predict more accurate expression levels of genes and transcripts than possible with short-reads alone.
Project description:Sequencing was performed to assess the ability of Nanopore direct cDNA and native RNA sequencing to characterise human transcriptomes. Total RNA was extracted from either HAP1 or HEK293 cells, and the polyA+ fraction isolated using oligodT dynabeads. Libraries were prepared using Oxford Nanopore Technologies (ONT) kits according to manufacturers instructions. Samples were then sequenced on ONT R9.4 flow cells to generate fast5 raw reads in the ONT MinKNOW software. Fast5 reads were then base-called using the ONT Albacore software to generate Fastq reads.