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.
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.
Project description:Expression profiles of wild-type and SgrR mutant E. coli strains under aMG and 2-DG-induced stress. Expression profiles of E. coli overexpressing SgrS sRNA.
Project description:Expression profiles of wild-type and SgrR mutant E. coli strains under aMG and 2-DG-induced stress. Expression profiles of E. coli overexpressing SgrS sRNA. Illumina RNA-Seq of total RNA extracted from wild-type, SgrR/SgrS mutant and SgrS overexpressing E. coli strains grown in different conditions.
Project description:Mature tRNA pools were measured using an adaptation of YAMAT-seq (Shigematsu et al., 2017; doi:10.1093/nar/gkx005 ) and further described in (Ayan et al., 2020; doi:10.7554/eLife.57947) in 10 strain-medium combinations (all strains dervied from the model bacterium E. coli MG1655). The aim of the experiment was to investigate the effect of reducing tRNA gene copy number on mature tRNA pools in rich and poor media.
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.