The QuantSeq 3’ mRNA-Seq Library Prep method generates Next Generation Sequencing (NGS) libraries from single sites close to the poly(A) tail of RNAs. Due to its fast and highly sensitive workflow this tag profiling method is ideal for the accurate quantification of gene expression, also from low-input and degraded samples. QuantSeq has been widely used for diverse studies and features in more than 150 peer-reviewed publications.

“Here we quantified mRNA expression from 299 maize lines that represent the genotypic and phenotypic diversity of modern inbred maize. We automated a 3′ mRNA sequencing method (QuantSeq, Lexogen GmbH), which is more efficient and accurate than mRNA sequencing and deals well with paralogues.” Kremling, K. A. G. et al. (2018) Dysregulation of expression correlates with rare-allele burden and fitness loss in maize. Nature. DOI: 10.1038/nature25966.

The determination of differential gene expression is a standard application and often complemented by gene set enrichment (GSEA) and pathway analyses to derive the network of differentially activated genes. Other applications include the determination of alternative polyadenylation sites and their differential usage, the 3’ (re)annotation of genes, and polysome profiling. The QuantSeq-Flex version is applied to profile non-polyadenylated RNA and to build custom gene expression profiling panels.

QuantSeq libraries are intended for a high degree of multiplexing. With the barcodes provided up to 9,216 libraries can be sequenced on an Illumina lane. This high level of multiplexing allows saving costs as the length restriction in QuantSeq saves sequencing space.

The straightforward procedure and the tremendously reduced sequencing depth requirements make the method highly cost efficient, and by adding robustness, sensitivity and versatility it is no wonder that QuantSeq has established itself as the most widely applied 3’ RNA-Seq protocol.


QuantSeq does not only save your time at the sample preparation stage, but it also resolves the data analysis bottleneck. Count transcripts instead of calculating FPKM values, let the automatic complementary pipeline do the job for you! Each QuantSeq kit is shipped with access codes for a free automated data analysis on the Bluebee Genomics Analysis Platform.

Watch the recent webinar talk of the QuantSeq and Bluebee user Dr. Dasgupta from the Dr. David Volz’s laboratory at the University of California, Riverside, USA:


The QuantSeq protocol readily accepts RNA samples of different origin and quality:

  • QuantSeq is used to assess gene expression in a wide variety of tissue and cells stemming from human, mouse, rat, fish, pig, fly, frog, plants, and others.
  • Globin Block Modules for QuantSeq allow for the depletion of globin mRNA by simply exchanging one solution in the QuantSeq standard work-flow. Gene expression in blood samples can now be analyzed with ease and high sensitivity.
  • QuantSeq gets your gene expression values right almost regardless of input RNA quality and integrity. The protocol requires only a small part of the mRNA for accurate quantification, and minor protocol modifications enable the preparation of QuantSeq libraries of highly degraded and FFPE samples.

Learn more about application of QuantSeq for low-quality FFPE samples in this recent webinar talk of Dr. Anne Krogsdam from the Innsbruck Medical University, Austria:

“The QuantSeq assay is highly sensitive and produces reliable results even for moderately degraded samples (valid down to RNA Integrity Number value of 3), and is thus particularly well suited for assay of DBS (dried blood spots)-derived RNA samples.“ Ross, K.M., Cole, S.W., Carroll, J.E., Dunkel Schetter, C. (2018). Elevated pro-inflammatory gene expression in the third trimester of pregnancy in mothers who experienced stressful life events. Brain Behav Immun. DOI: 10.1016/j.bbi.2018.11.009.


QuantSeq is ideal for preparing libraries from samples generated with the metabolic RNA labeling method SLAMseq. With SLAMseq, nascent RNA can be identified alongside the total RNA content without the need for pull-down experiments or biochemical isolation. QuantSeq provides the sensitivity and efficiency required for the RNA-Seq based read-out at the lowest possible cost, and the tag-counting based approach enables a highly robust data analysis of SLAMseq samples. Use the SLAMSeq / QuantSeq combination to analyze transcriptome-wide kinetics of RNA synthesis and turnover, to measure nascent RNA expression and stability, to enhance the resolution of differential expression, and to identify primary and secondary transcriptional targets.


Watch the recent webinar talk of Stefan Ameres, Ph.D. from the Institute of Molecular Biotechnology, Austria, and Johannes Zuber, M.D., Ph.D. from the Research Institute of Molecular Pathology, Austria, about applications of SLAMseq and QuantSeq in cancer research and beyond by registering at the webpage of Science.


Explore even more QuantSeq applications like poly(A) site mapping, and offerings such as Unique Molecular Identifiers (UMIs), dual indices and targeted approaches by visiting these web pages:

“Although 3’ READS (non-Lexogen) was highly effective in identifying pAs and could be used for quantification of the APA isoform expression, it was cumbersome and required a large amount of starting material. Therefore, in the following quantitative analysis on strain- or allele-specific pAs usage, we applied a simpler oligo-dT priming-based method ([QuantSeq] 3’ mRNA-seq from Lexogen).” Xiao, M.-S. et al. (2016) Global analysis of regulatory divergence in the evolution of mouse alternative polyadenylation. Molecular Systems Biology. DOI: 10.15252/msb.20167375.

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