Tag-Seq is a high-throughput sequencing approach that is primarily used for characterizing gene expression levels and identifying novel transcripts. The data generated by the service can be useful for a wide range of applications, including gene expression studies, biomarker discovery, and transcriptome annotation.

Overview of Our Tag-Seq Service

Tag-Seq stands for "transcriptome analysis with the aid of next-generation sequencing." It was developed as an alternative to RNA-Seq, which typically involves sequencing the entire length of RNA molecules to obtain information about gene expression levels. Tag-Seq instead uses a shorter "tag" sequence, typically 20-30 nucleotides in length, that is specific to the 3' end of each RNA molecule. These tags can be efficiently sequenced using high-throughput sequencing technologies, allowing for the detection of gene expression levels in a cost-effective manner.

One advantage of Tag-Seq is that it simplifies the computational analysis of gene expression data, since only a single tag sequence needs to be processed for each RNA molecule. This can be especially useful for studies involving large numbers of samples, as it reduces the computational burden and allows for faster data analysis. Additionally, because tag counts are independent of gene length, Tag-Seq is a more powerful tool for differential gene expression analysis than RNA-Seq, which can be biased towards longer transcripts.

Fig.1 Schematic of Tag-seq (Dar, 2016)

Workflow of Our Library Construction

Project Workflow

Data analysis

• Mapping to genome reference
• Identification of differentially expressed genes (DEGs)
• Alternative polyadenylation (APA) analysis
• Allele Specific Expression (ASE) analysis

Deliverable: FastQ, BAM, QC report, Differential Expression Table, MDS plot from DE analysis, Custom bioinformatics analysis.

References:

1. Meyer, E., et al. Profiling gene expression responses of coral larvae (Acropora millepora) to elevated temperature and settlement inducers using a novel RNA-Seq procedure. Molecular ecology 20.17 (2011): 3599-3616.
2. Morrissy, A. Sorana, et al. Next-generation tag sequencing for cancer gene expression profiling. Genome research 19.10 (2009): 1825-1835.
3. Jang, Jin Sung, et al. Application of the 3′ mRNA-Seq using unique molecular identifiers in highly degraded RNA derived from formalin-fixed, paraffin-embedded tissue. BMC genomics 22.1 (2021): 1-9.