Tag-Seq

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.

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

Workflow of Our Library Construction

Library Construction of Tag-Seq – CD Genomics

Features

Low Cost High Compatibility Wide Range High Sensitivity
This method is not available as a kit, it costs about half or less compared to standard RNA-seq. This method can be used to degrade RNA samples, such as FFPE derived RNA. This method is much higher dynamic range compared to microarrays. This method has >99% strand-specific.

Project Workflow

Sample Preparation

1. Sample Preparation

Library Preparation

2. Library Preparation

Sequencing

3. Sequencing

Data Analysis

4. Data Analysis & Delivery

Data 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.
* For Research Use Only. Not for use in diagnostic procedures.


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