Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

High throughput error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing

ABSTRACT: 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.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE162053 | GEO | 2021/01/31

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Anchor-Enhanced Bead Design for Reduced Oligonucleotide Synthesis Errors in Single-cell sequencing

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

ESPRESSO: Robust discovery and quantification of transcript isoforms from error-prone long-read RNA-seq data

Project description:Long-read RNA sequencing (RNA-seq) holds great potential for characterizing transcriptome variation and full-length transcript isoforms, but the relatively high error rate of current long-read sequencing platforms poses a major challenge. We present ESPRESSO, a computational tool for robust discovery and quantification of transcript isoforms from error-prone long reads. ESPRESSO jointly considers alignments of all long reads aligned to a gene and uses error profiles of individual reads to improve the identification of splice junctions and the discovery of their corresponding transcript isoforms. On both a synthetic spike-in RNA sample and human RNA samples, ESPRESSO outperforms multiple contemporary tools in not only transcript isoform discovery but also transcript isoform quantification. In total, we generated and analyzed ~1.1 billion nanopore RNA-seq reads covering 30 human tissue samples and three human cell lines. ESPRESSO and its companion dataset provide a useful resource for studying the RNA repertoire of eukaryotic transcriptomes.

2022-10-14 | GSE192955 | GEO

The comparison of high-throughput single-cell RNA-seq methods

Project description:Here we compare the performance of these three approaches (inDrop, Drop-seq and 10x) using the same kind of sample with a unified data processing pipeline. We generated 2-3 replicates for each method using lymphoblastoid cell line GM12891. The average sequencing depth was around 50-60k reads per cell barcode. We also developed a versatile and rapid data processing workflow and applied it for all datasets. Cell capture efficiency, effective read ratio, barcode detection error and transcript detection sensitivity were analyzed as well.

2018-06-14 | GSE111912 | GEO

Monosome and disome profiling of Flag-STAU1 Flp-In 293 T-REx cells

Project description:Monosome and disome profiling was performed on Flag-STAU1 Flp-In 293 T-REx to study the causes of ribosomal collisions, and whether this may be modulated by the presence/absence of Staufen-1. Cells were treated with either an siRNA targeting STAU1 transcript (4x samples) or a control siRNA (2x samples). Two of the four samples treated with the STAU1 siRNA had siRNA-resistant STAU1 mRNA expression induced by doxycycline (rescue). Sequencing libraries from monosome and disome fractions were generated in parallel from the same samples. Note that unique molecular identifiers/random barcodes (UMIs/RBCs) were included in the sequencing experiment. Each UMI has been moved to the fastq read name of each read. For example \\"xxxxxxrbc:AGCCAAT\\" in the read name signifies that the given read had a UMI of \\"AGCCAAT\\". Using these UMIs, PCR duplicates can be removed with UMI-Tools following read alignment.

2023-04-30 | E-MTAB-9669 | biostudies-arrayexpress

High-throughput error corrected Nanopore single cell transcriptome sequencing

Project description:E18 mouse brain single cell profiling using the 10x Genomics Chromium instrument workflow with either Illumina short read sequencing for the standard gene profiling and Nanopore PromethION long read sequencing for isoform profiling.

2020-07-10 | GSE130708 | GEO

LoRTIS: A long read method for analysis of large transposon mutant libraries

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

Transcriptome innovations in primates revealed by single-molecule long-read sequencing

Project description:We produced an extensive transcript catalog for LCLs of 5 primate species by leveraging isoform sequencing and short-read RNA-seq. The curated transcriptomes were used to assist mass spectrometry protein identifications.

2022-05-31 | PXD031213 | Pride

Scalable Microfluidics for Single Cell RNA Printing and Sequencing

Project description:Single cell transcriptomics has emerged as a powerful approach to dissecting phenotypic heterogeneity in complex, unsynchronized cellular populations. However, many important biological questions demand quantitative analysis of large numbers of individual cells. Hence, new tools are urgently needed for efficient, inexpensive, and parallel manipulation of RNA from individual cells. We report a simple microfluidic platform for trapping single cell lysates in sealed, picoliter microwells capable of “printing” RNA on glass or capturing RNA on polymer beads. To demonstrate the utility of our system for single cell transcriptomics, we developed a highly scalable technology for genome-wide, single cell RNA-Seq. The current implementation of our device is pipette-operated, profiles hundreds of individual cells in parallel with library preparation costs of ~$0.10-$0.20/cell, and includes five lanes for simultaneous experiments. We anticipate that this system will ultimately serve as a general platform for large-scale single cell transcriptomics, compatible with both imaging and sequencing readouts.!Series_type = Expression profiling by high throughput sequencing A microfluidic device that pairs sequence-barcoded mRNA capture beads with individual cells was used to barcode cDNA from individual cells which was then pre-amplified by in vitro transcription in a pool and converted into an Illumina RNA-Seq library. Libraries were generated from ~600 individual cells in parallel and extensive analysis was done on 396 cells from the U87 and MCF10a cell lines and from ~500 individual cells with extensive analysis on 247 cells from the U87 and WI-38 cell lines. Sequencing was done on the 3'-end of the transcript molecules. The first read contains cell-identifying barcodes that were present on the capture bead and the second read contains a unique molecular identifier (UMI) barcode, a lane-identifying barcode, and then the sequence of the transcript.

2015-05-21 | E-GEOD-66357 | biostudies-arrayexpress

Determination of isoform-specific RNA structure with nanopore long reads

Project description:Current methods for determening RNA structure with short-read sequencing cannot capture most differences between distinct transcript isoforms. Here, we present RNA structure analysis using nanopore sequencing (PORE-cupine),which combines structure probing using chemical modifications with direct long-read RNA sequencing and machine learning to detect secondary structures in cellular RNAs. PORE-cupine also captures global structural features, such as RNA binding protein (RBP) binding sites and reactivity differences at single nucleotide variants (SNVs). We show that shared sequences in different transcript isoforms of the same gene can fold into different structures, highlighting the importance of long-read sequencing for obtaining phase information. We also demonstrate that structural differences between transcript isoforms of the same gene lead to differences in translation efficiency. By revealing isoform-specific RNA structure, PORE-cupine will deepen our understanding of the role of structures in controlling gene regulation.

2020-09-09 | GSE133361 | GEO

Whole-chromosome methylation patterns of the mouse inactive X

Project description:Using long-read nanopore sequencing, we obtained chromosome-wide phased methylomes of the active and inactive X in mouse placenta and neural stem cells (NSCs), overcoming the limitations if short-read bisulfite sequencing in allelic resolution. We also conducted quantitative analysis of methylation properties like symmetry and entropy, providing a more comprehensive view of epigenetic silencing in X chromosome inactivation. We also resolved the allele-specific genetics and epigenetics of structural macrosatellite Dxz4 and other repeats.

2024-03-12 | E-MTAB-13706 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data