Longread_umi
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB39791 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Enabling high-accuracy long-read amplicon sequences using unique molecular identifiers with Nanopore or PacBio sequencing
| PRJEB32674 | ENA
Project description:Droplet-based single-cell sequencing techniques have provided unprecedented insight into cellular heterogeneities within tissues. However, these approaches only allow for the measurement of the distal parts of a transcript following short-read sequencing. Therefore, splicing and sequence diversity information is lost for the majority of the transcript. The application of long-read Nanopore sequencing to droplet-based methods is challenging because of the low base-calling accuracy currently associated with Nanopore sequencing. Although several approaches that use additional short-read sequencing to error-correct the barcode and UMI sequences have been developed, these techniques are limited by the requirement to sequence a library using both short- and long-read sequencing. Here we introduce a novel approach termed single-cell Barcode UMI Correction sequencing (scBUC-seq) to efficiently error-correct barcode and UMI oligonucleotide sequences synthesized by using blocks of dimeric nucleotides. The method can be applied to correct both short-read and long-read sequencing, thereby allowing users to recover more reads per cell that permits direct single-cell Nanopore sequencing for the first time. We illustrate our method by using species-mixing experiments to evaluate barcode assignment accuracy and multiple myeloma cell lines to evaluate differential isoform usage and Ewing’s sarcoma cells to demonstrate Ig fusion transcript analysis.
2021-01-31 | GSE162053 | GEO
Project description:Nanopore sequencing has revolutionized genetic analysis by offering linkage information across megabase-scale genomes. However, the high intrinsic error rate of nanopore sequencing impedes the analysis of complex heterogeneous samples, such as viruses, bacteria, and edited cell lines. Achieving high accuracy in single-molecule sequence identification would significantly advance the study of quasi-species genomic populations, crucial for fields like immunology, pathology, epidemiology, and synthetic biology, where clonal isolation is traditionally employed for complete genomic frequency analysis. Here, we introduce ConSeqUMI, an innovative experimental and analytical pipeline designed to address long-read sequencing error rates using unique molecular indices for precise consensus sequence determination. ConSeqUMI processes nanopore sequencing data without the need for reference sequences, enabling accurate assembly of individual molecular sequences from complex mixtures. We establish robust benchmarking criteria for this platform’s performance and demonstrate its utility across diverse experimental contexts, including mixed plasmid pools, recombinant adeno-associated virus genome integrity, and CRISPR/Cas9-induced genomic alterations. Furthermore, ConSeqUMI enables detailed profiling of human pathogenic infections, as shown by our analysis of SARS-CoV-2 spike protein variants, revealing substantial intra-patient genetic heterogeneity. Lastly, we demonstrate how individual clonal isolates can be extracted directly from sequencing libraries at low cost, allowing for post-sequencing identification validation of observed variants. Our findings highlight the robustness of ConSeqUMI in processing sequencing data from degenerate UMI-labeled molecules, offering a critical tool for advancing genomic research.
2025-04-11 | GSE288938 | GEO
Project description:Single-cell transcriptomics, reliant on the incorporation of barcodes and unique molecular identifiers (UMIs) into captured polyA+ mRNA, faces a significant challenge due to synthesis errors in oligonucleotide capture sequences. These inaccuracies, which are especially problematic in long-read sequencing, impair the precise identification of sequences and result in inaccuracies in UMI deduplication. To mitigate this issue, we have modified the oligonucleotide capture design, which integrates an interposed anchor between the barcode and UMI, and a 'V' base anchor adjacent to the polyA capture region. This configuration is devised to ensure compatibility with both short and long-read sequencing technologies, facilitating improved UMI recovery and enhanced feature detection, thereby improving the efficacy of droplet-based sequencing methods.
2024-04-09 | GSE263458 | GEO
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.
2025-05-23 | GSE295932 | GEO
Project description:Long-read sequencing technologies such as Iso-Seq (PacBio Inc.) generate highly accurate sequences of full-length mRNA transcript isoforms. Long-read transcriptomics may be especially useful in the context of lymphocyte functional plasticity as it relates to human health and disease. However, no long-read isoform-aware reference transcriptomes of human circulating lymphocytes seem to be publicly available despite being valuable as benchmarks in a variety of transcriptomic studies. To begin to fill this gap, we purified four lymphocyte subsets (CD4 T, CD8 T, NK, and Pan B cells) from the peripheral blood of a healthy male donor and obtained high-quality RNA (RIN>8) for PacBio Iso-Seq analysis and parallel RNA-Seq analysis.
2022-09-16 | GSE202328 | GEO
Project description:Long-read sequencing technologies such as Iso-Seq (PacBio Inc.) generate highly accurate sequences of full-length mRNA transcript isoforms. Long-read transcriptomics may be especially useful in the context of lymphocyte functional plasticity as it relates to human health and disease. However, no long-read isoform-aware reference transcriptomes of human circulating lymphocytes seem to be publicly available despite being valuable as benchmarks in a variety of transcriptomic studies. To begin to fill this gap, we purified four lymphocyte subsets (CD4 T, CD8 T, NK, and Pan B cells) from the peripheral blood of a healthy male donor and obtained high-quality RNA (RIN>8) for PacBio Iso-Seq analysis and parallel RNA-Seq analysis.
2022-09-16 | GSE202327 | GEO
Project description:Transposon insertion site sequencing (TIS) is a powerful method for associating genotype to phenotype. However, all TIS methods described to date use short nucleotide sequence reads which cannot uniquely determine the locations of transposon insertions within repeating genomic sequences where the repeat units are longer than the sequence read length. To overcome this limitation, we have developed a TIS method using Oxford Nanopore sequencing technology that generates and uses long nucleotide sequence reads; we have called this method LoRTIS (Long Read Transposon Insertion-site Sequencing). This experiment data contains sequence files generated using Nanopore and Illumina platforms. Biotin1308.fastq.gz and Biotin2508.fastq.gz are fastq files generated from nanopore technology. Rep1-Tn.fastq.gz and Rep1-Tn.fastq.gz are fastq files generated using Illumina platform. In this study, we have compared the efficiency of two methods in identification of transposon insertion sites.
2022-05-30 | E-MTAB-11351 | biostudies-arrayexpress
Project description:Grass pea seeds and seedlings protein extracts were chromatographically fractionated. To identify the β-ODAP synthase enzyme, active fractions, as determined by a colorimetric assay that detects the presence of a derivative of free L-α,β-diaminopropionic acid (L-DAPA), were subjected to tryptic digestion and LC-MS/MS and searched against a database containing translated sequences from a long-read PacBio mRNA sequencing of grass pea seeds and seedlings.
2022-05-19 | PXD030847 | Pride
Project description:We used the nanopore Cas9 targeted sequencing (nCATS) strategy to specifically sequence 125 L1HS-containing loci in parallel and measure their DNA methylation levels using nanopore long-read sequencing. Each targeted locus is sequenced at high coverage (~45X) with unambiguously mapped reads spanning the entire L1 element, as well as its flanking sequences over several kilobases. The genome-wide profile of L1 methylation was also assessed by bs-ATLAS-seq in the same cell lines (E-MTAB-10895).
2023-09-22 | E-MTAB-12247 | biostudies-arrayexpress