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RNA-Seq Blog: End-Seq

At Eclipse BioInnovations (Eclipse Bio), we create tools that simplify, accelerate and advance RNA research. End-Seq technology is a recent development at Eclipse Bio, which we are excited to officially launch this month. Eclipse’s End-Seq products enable researchers to map both 5’ and 3’ transcript ends genome-wide at single nucleotide resolution in just 3 short days, and overcome several drawbacks associated with previous methods used to map transcript ends like long protocols and low-resolution data.

To overcome these drawbacks, we kept three key specifications in mind while developing a new approach:

  1. Low RNA input
  2. An easy protocol
  3. Precise and reproducible transcript end data

The new approach hits the mark on all three! Both our 5’ and 3’ End-Seq protocols are compatible with 3 ug total RNA starting material, take about three days to complete (both protocols in parallel) and provide genome-wide transcript end data at single nucleotide resolution. Not only is the protocol efficient and easy to use, but it also has an outstanding data analysis package, which enables the end user to detect all active transcription start sites (TSS) and poly-A-sites, detect novel poly-A-sites with high confidence based on false positive poly-A-site filtering, and further use this data to understand differential gene expression and potentially detect biomarkers in diseased samples.

How does this new approach compare to current transcript-end mapping methods? Take as an example CAGE-seq, a commonly used method to map 5’ ends[1]. CAGE-Seq is a rather labor- and cost-intensive protocol, requiring 5ug total RNA, taking up to 8 days to complete and costing around $4,000 for an 8-sample kit, excluding the cost for sequencing and data analysis. In contrast, the new method needs only 3ug of total RNA, takes 3 days to complete and costs less than half for an 8-sample kit including data analysis.

On the contrary, 3’ end sequencing technologies are known for their low cost, fast protocols and low input requirements. However, many of the 3’ end protocols are based on oligodT-primed reverse transcription (RT), allowing for the occurrence of low confidence poly-A-sites by priming internal A-rich sequences. Eclipse’s 3’ End-seq improves this by relying on efficient adapter ligations instead of oligodT-primed RT. In addition, we have developed a data analysis package to filter out any false positive 3’ ends. The most revolutionizing aspect of this new approach is the fact that the sequencing reads start at the poly-A-sites and read toward the 3’ UTR, as opposed to starting somewhere in the 3’ UTR and sequencing towards the poly-A-sites like other 3’ end sequencing technologies such as MACE-Seq do[2]. This allows us to define each poly-A-site with single nucleotide resolution.


End-Seq applications for RNA drug discovery and clinical biomarkers. This new technology was developed with the RNA drug discovery and biomarker field in mind. Alternative TSS and poly-A-site usage are known hallmarks of certain human diseases like cancer. Being able to identify such usage genome-wide across multiple samples, at single nucleotide resolution, is a powerful tool in biomarker discovery. Similarly, TSS and poly-A-sites are excellent targets for both anti-sense oligos and small molecule drugs, requiring absolute nucleotide locations of transcript ends.

We are very excited to launch Eclipse Bio End-Seq technology this month and look forward to the results achieved by researchers using it to advance the next generation of trail blazing RNA discoveries. For more information about other RNA genomics products from Eclipse Bio, visit our website ( We also have technologies that investigate RNA-binding protein (RBP)-RNA interactions (RBP-eCLIP), m6A-modifications in RNA (m6A-eCLIP), microRNA-mRNA interactions (miR-eCLIP), and active translation (ribo-eCLIP). In addition, stay tuned for even more exciting new technologies in RNA structure probing (i.e., SHAPE), and more coming soon.


  1. Shiraki, T., et al., Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage. Proc Natl Acad Sci U S A, 2003. 100(26): p. 15776-81.
  2. Boneva, S., et al., 3′ MACE RNA-sequencing allows for transcriptome profiling in human tissue samples after long-term storage. Lab Invest, 2020. 100(10): p. 1345-1355.