Digital counting of nucleic acid molecules using random base molecular barcodes
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct
PROVIDER: GSE94895 | GEO | 2017/10/19
SECONDARY ACCESSION(S): PRJNA374740
REPOSITORIES: GEO
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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: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.
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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.
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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:Digital counting of nucleic acid molecules using random base molecular barcodes
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Project description:Accurate quantification of biomolecules in system-wide measurements is in high demand, especially for systems with limited sample amounts such as single cells. Because of this, digital quantification of nucleic acid molecules using molecular barcodes has been developed, making, e.g., transcriptome analysis highly reproducible and quantitative. This counting scheme was shown to work using sequence-restricted barcodes, and non-sequence-restricted (random-base) barcodes that may provide a much higher dynamic range at significantly lower cost have been widely used. However, the efficacy of random-base barcodes is significantly affected by base changes due to amplification and/or sequencing errors and has not been investigated experimentally or quantitatively. Here, we show experimentally that random-base barcodes enable absolute and digital quantification of DNA molecules with high dynamic range (from one to more than 104, potentially up to 1015 molecules) conditional on our barcode design and variety, a certain range of sequencing depths, and computational analyses. Moreover, we quantitatively show further functional advantages of the molecular barcodes: the molecular barcodes enable one to find contaminants and misidentifications of target sequences. Our scheme here may be generally used to confirm that the digital quantification works in each platform.
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Project description:Counting absolute number of molecules using unique molecular identifiers
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Project description:LNPs have been demonstrated to hold great promise for the clinical advancement of RNA therapeutics. Continued exploration of LNPs for application in new disease areas requires identification and optimisation of leads in a high throughput way. Currently available high throughput in vivo screening platforms are well suited to screen for cellular uptake but less so for functional cargo delivery. We report on a platform which measures functional delivery of LNPs using unique peptide ‘barcodes’. We describe the design and selection of the peptide barcodes and the evaluation of these for the screening of LNPs. We show that proteomic analysis of peptide barcodes correlates with quantification and efficacy of barcoded reporter proteins both in vitro and in vivo and, that the ranking of selected LNPs using peptide barcodes in a pool correlates with ranking using alternative methods in groups of animals treated with individual LNPs. We show that this system is sensitive, selective, and capable of reducing the size of an in vivo study by screening up to 10 unique formulations in a single pool, thus accelerating the discovery of new technologies for mRNA delivery.
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