RNA sequencing (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 Escherichia coli with more accurate and reproducible 
quantification than conventional RNA-Seq.