||We report the development of a simplified Cap Analysis of Gene Expression (CAGE) protocol adapted for single molecule sequencers which avoids second strand synthesis, ligation, digestion and PCR. HeliScopeCAGE directly sequences the 3â end of cap trapped first strand cDNAs. As with previous versions of CAGE, we better define transcription start sites (TSS) than known models, identify novel regions of transcription and alternative promoters, and find two major classes of TSS signal, sharp peaks and broad regions. However using this protocol we observe reproducible evidence of regulation at the much finer level of individual TSS positions. The libraries are quantitative over 5 orders of magnitude and highly reproducible (pearsonâs correlation coefficient of 0.987). We have also scaled down the sample requirement to 5ug total RNA for a standard HeliScopeCAGE library and 100ng for a low quantity version. When the same RNA was run as 5ug and 100ng versions, the 100ng was still able to detect expression for ~60% of the 13468 loci detected by a 5ug library using the same threshold, allowing comparative analysis of even rare cell populations. Testing the protocol for differential gene expression measurements on triplicate HeLa and THP-1 samples, we find the log fold change compared to Illumina microarray measurements is highly correlated (0.871). In addition, HeliScopeCAGE finds differential expression for 1000s more loci including those with probes on the array. Finally although the majority of tags are 5â associated we also observe a low level of signal on exons which is useful for defining gene-structures. HeliScopeCAGE protocol: First strand cDNA is generated from total RNA using an excess of random primer. 5â end complete first strand cDNAs are captured for capped RNAs. First strand cDNA is polyA tailed and blocked and then loaded directly onto the HeliScope flow cell for sequencing. Data processing: After the filtering with filterSMS in HeliSphere package, the obtained reads are aligned to the human genome (hg18) with indexDPgenomic and only the alignments with the best alignment score in unique location are selected.