Synthetic construct
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA374740 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Several template DNA molecules with random base molecular barcodes were amplified and sequenced, and the efficacy of the random base barcode for digital counting was shown.
2017-10-19 | GSE94895 | GEO
Project description:RNA-Seq is a powerful tool for transcriptome profiling, but is hampered by sequence-dependent bias and inaccuracy at low copy numbers intrinsic to exponential PCR amplification. We developed a simple strategy for mitigating these complications, allowing truly digital RNA-Seq. Following reverse transcription, a large set of barcode sequences is added in excess, and nearly every cDNA molecule is uniquely labeled by random attachment of barcode sequences to both ends. After PCR, we applied paired-end deep sequencing to read the two barcodes and cDNA sequences. Rather than counting the number of reads, RNA abundance is measured based on the number of unique barcode sequences observed for a given cDNA sequence. We optimized the barcodes to be unambiguously identifiable even in the presence of multiple sequencing errors. This method allows counting with single copy resolution despite sequence-dependent bias and PCR amplification noise, and is analogous to digital PCR but amendable to quantifying a whole transcriptome. We demonstrated transcriptome profiling of E. coli with more accurate and reproducible quantification than conventional RNA-Seq. We analyzed two replicates of the same bulk E. coli transcriptome sample. In each sample, we included internal standards to demonstrate that the digital RNA-Seq system may accurately count fragments correctly.
2012-01-07 | E-GEOD-34449 | biostudies-arrayexpress
Project description:RNA-Seq is a powerful tool for transcriptome profiling, but is hampered by sequence-dependent bias and inaccuracy at low copy numbers intrinsic to exponential PCR amplification. We developed a simple strategy for mitigating these complications, allowing truly digital RNA-Seq. Following reverse transcription, a large set of barcode sequences is added in excess, and nearly every cDNA molecule is uniquely labeled by random attachment of barcode sequences to both ends. After PCR, we applied paired-end deep sequencing to read the two barcodes and cDNA sequences. Rather than counting the number of reads, RNA abundance is measured based on the number of unique barcode sequences observed for a given cDNA sequence. We optimized the barcodes to be unambiguously identifiable even in the presence of multiple sequencing errors. This method allows counting with single copy resolution despite sequence-dependent bias and PCR amplification noise, and is analogous to digital PCR but amendable to quantifying a whole transcriptome. We demonstrated transcriptome profiling of E. coli with more accurate and reproducible quantification than conventional RNA-Seq.
2012-01-07 | GSE34449 | GEO
Project description:Sequencing random oligonucleotides using standard GA II protocol
| PRJNA153413 | ENA
Project description:Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes sequences? that are critical for the removal of PCR amplification biases within both bulk and single-cell sequencing experiments. However, the impact that PCR and sequencing errors have on the accuracy of generating absolute counts of RNA molecules is underappreciated. We demonstrate that PCR errors and not sequencing errors are the main source of inaccuracy in sequencing data and that the use of UMIs synthesized with homotrimeric nucleoside building blocks provides a solution to pinpoint and remove errors, allowing absolute counting of sequenced molecules.
2023-06-01 | GSE218899 | GEO
Project description:Unique Molecular Identifiers (UMIs) are random oligonucleotide barcodes sequences? that are critical for the removal of PCR amplification biases within both bulk and single-cell sequencing experiments. However, the impact that PCR and sequencing errors have on the accuracy of generating absolute counts of RNA molecules is underappreciated. We demonstrate that PCR errors and not sequencing errors are the main source of inaccuracy in sequencing data and that the use of UMIs synthesized with homotrimeric nucleoside building blocks provides a solution to pinpoint and remove errors, allowing absolute counting of sequenced molecules.
2023-06-01 | GSE218901 | GEO
Project description:We retrospectively analysed the expression of 579 immunological genes in 60 COVID-19 subjects (SARS +ve) and 59 COVID-negative (SARS -ve) subjects using the NanoString nCounter (Immunology panel), a technology based on multiplexed single-molecule counting. Biobanked Human peripheral blood mononuclear cells (PBMCs) samples underwent Nucleic Acid extraction and digital detection of mRNA to evaluate changes in antiviral gene expression between SARS -ve controls and patients with mild (SARS +ve Mild) and moderate/severe (SARS +ve Mod/Sev) disease.
2023-05-11 | GSE227080 | GEO
Project description:Implementing nucleic acid barcodes for a DNA virus
| PRJNA791340 | ENA
Project description:A highly complex set of 264 molecular spikes, based on 11 unique spike sequences spanning different lengths (570 to 3070 nts) and GC contents (40-60%) was designed. In order to be able to precisely evaluate quantification over different expression levels, transcript lengths and GC contents, barcodes of 7 nucleotides in 2-fold abundance steps were cloned into each spike sequence (12 steps in duplicates; 24 barcodes per sequence) creating a standard curve for each spike sequence. To determine the molecular abundance of each of the 264 molecular spike-ins (i.e., the ‘ground truth’), we performed an exhaustive sequencing across the spike barcodes and spUMIs and determined the total complexity in the pool to be 76 million unique molecules
2022-02-16 | E-MTAB-11448 | biostudies-arrayexpress
Project description:20 random DNA barcodes were designed in silico and transfected into PC3 cells. Barcodes were sequenced using Illumina-Miseq technology to find the sequence and their respective copy numbers. Current file contains the raw data of these DNA barcodes in fastq format Validating an algorithm called SRiD that generates random DNA barcodes that do not match a genome of interest, in this case human genome. 20 DNA barcodes were used for this validation.
2016-03-31 | E-GEOD-67441 | biostudies-arrayexpress