QuantSeq-Pool Sample-Barcoded 3′ mRNA-Seq Library Prep Kit for Illumina

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QuantSeq-Pool is the optimal solution for gene expression profiling for large screening projects using sample barcoding, early pooling, and batch processing of up to 96 samples in one reaction providing a workflow that is easily scalable for multiplexing up to 36,864 samples.

QuantSeq-Pool is the newest addition to the QuantSeq product line combining the benefits of the well-established QuantSeq methodology with sample barcoding and early pooling. Due to the convenient workflow and scalable multiplexing capacities, QuantSeq-Pool is the optimal choice for completing gene expression profiling studies in the most cost- and time-efficient way. Not sure whether QuantSeq-Pool is the right version of QuantSeq for you? Please check the QuantSeq selection guide to find out (Fig. 1).

052_QS-Pool_Scheme-Decision Tree_V0100

Figure 1 | QuantSeq kit selection guide.

Increased Consistency and Reduced Technical Variability

QuantSeq-Pool contains the Illumina Read 1 linker sequence in the second strand synthesis primer, hence NGS reads are generated towards the poly(A) tail, directly reflecting the mRNA sequence. Sample-barcodes and Unique Molecular Identifiers (UMIs) are introduced in the first step and are accessible in Read 2 (see workflow). Early pooling and batch processing reduce technical variation in the complete workflow and allow consistent processing of up to 96 samples in parallel. Excellent reproducibility between replicates is shown in Fig. 2.

080_Correlation between replicates for individual samples in QuantSeq-Pool

Figure 2 | Excellent correlation between replicates for individual samples in QuantSeq-Pool. Libraries were prepared from 10 ng UHRR, sequenced, and correlated on gene level. R² was calculated by orthogonal regression.

Fastest Turnaround for Large-scale Projects

The streamlined QuantSeq-Pool workflow uses batch processing of up to 96 samples after the initial protocol step and allows generation of ready-to-sequence NGS libraries in less than 4.5 hours.

Flexibility of Throughput

The QuantSeq-Pool kit is set up in a 96 well plate format and can generate up to 36,864 triple indexed libraries combining 96 sample-barcodes with 384 unique dual index combinations. The efficiency of the early-pooling workflow and the ability to combine between 8 and 96 samples in one reaction provides full flexibility for projects of any size.

High Strand-Specificity

QuantSeq-Pool maintains exceptional strand-specificity of >99.9 % and allows to map reads to their corresponding strand on the genome, enabling the discovery and quantification of antisense transcripts and overlapping genes.

Robust Gene Detection at Low Sequencing Depth

QuantSeq-Pool reliably detects 7,500 to 9,000 highly expressed genes at very shallow read depths of 100 K to 1 M reads per sample (Fig. 3).


Figure 3 | QuantSeq-Pool enables robust and consistent gene detection already at low sequencing depth. Libraries were generated from 8 x 10 ng UHRR, sequenced, and gene detection was analyzed for 100 K, 0.5 M and 1 M reads / sample. Number of detected genes was counted at a threshold of > 10 Counts Per Million (CPM).

Cost Saving Multiplexing

QuantSeq-Pool libraries are intended for a high degree of multiplexing: 96 sample-barcodes (i1 indices) are included in the Kit (Cat. No. 139). Additional i5 and i7 indices are required for multiplexing more 96 samples for sequencing. Lexogen UDI 12 nt Sets with pre-mixed i5 and i7 indices offer superior error correction capacity and are recommended for massive multiplexing (Cat. No. 101 – 105, 156). Lexogen’s indices are provided in a convenient 96-well format for multiplexing of up to 9,216 samples per lane for each 96-well index plate. Lexogen UDI 12 nt Unique Dual Indexing Sets are available for up to 384 12 nt UDIs increasing the multiplexing capacity to 36,864 samples per sequencing lane. For further indexing options, please contact

Lexogen also offers 6 nt single indexing sets for i7 (Cat. No. 044.96) and i5 (Cat. No. 047.96). These 6 nt Index Sets can be used separately as single indexes for either i5 or i7, or can be combined for dual indexing.

This high level of multiplexing allows saving costs as the length restriction in QuantSeq saves sequencing space.

Direct Counting for Gene Expression Quantification

Just one fragment per transcript is produced; therefore, no length normalization is required. This allows more accurate determination of gene expression values and renders QuantSeq the best alternative to microarrays and conventional RNA-Seq in gene expression studies.

Simple Bioinformatics Analysis

Read mapping is simplified by skipping the junction detection. Reads are generated at the transcripts’ most 3′ end where nearly no junctions are located. Data processing can hence be accelerated by using e.g., Bowtie2 instead of TopHat2.

Unique Molecular Identifiers

UMIs are built-in for QuantSeq-Pool and are introduced in the very first step of the protocol. UMIs are 10 nucleotides long and read out at the start of Read 2. Use the UMI information to identify PCR duplicates and eliminate amplification bias.


Library Generation: Reverse Transcription
Step 1:
The kit uses total RNA as input, hence no prior poly(A) enrichment
or rRNA depletion is needed. For balanced read distribution
in the sequencing experiment the RNA input amount for reverse
transcription needs to be adjusted and normalized across all
samples that shall be pooled.
Library Generation: Reverse Transcription
Step 1:
Library generation is initiated by oligo(dT) priming. The primer
already contains a partial Illumina-specific Read 2 linker sequence,
Unique Molecular Identifiers (UMIs), and an i1 sample-barcode
to uniquely label each sample.
Library Generation: Pooling
Step 2:
After first strand synthesis, individual samples are combined
by pooling. The pool is purified to decrease the volume for
subsequent steps. All further reactions are carried out in batch
on the combined samples to save time and effort.
Library Generation: Removal of RNA
Step 3:
After pooling, the RNA template is removed from
all samples simultaneously.
Library Generation: Second-Strand Synthesis
Step 4:
Second strand synthesis is initiated by random priming
and a DNA polymerase. The random primer contains
the Illumina-specific Read 1 linker sequence.
Library Generation: Purification
Step 5:
Second strand synthesis is followed by a magnetic
bead-based purification step.
Library Amplification: PCR
Step 6:
During the library amplification step sequences required for
cluster generation are introduced. Optionally, i5 and i7 indices
can be introduced. These additional indices are required
for multiplexing more than 96 samples.
Library Amplification: PCR - Multiplexing
Step 6:
Multiplexing capacities can reach up to 9,216 samples when
96 additional i5 / i7 Unique Dual Indices (UDIs) are used or
up to 36,864 samples when 384 UDIs are used.
Library Amplification: Purification
Step 7:
The final purification elutes ready-to-sequence library pools
of up to 96 samples which directly correspond to the final
lane pool for a 96-plex sequencing experiment.
Step 8:
NGS reads are generated towards the poly(A) tail and directly
correspond to the mRNA sequence. The length distribution of
QuantSeq-Pool libraries supports all sequencing lengths.
Read 2 is required to read out the sequence information for
the UMI and the i1 sample-barcode. Therefore, at least a
limited Read 2 with a read length between 18 and 22 nucleotides
is mandatory for sequencing QuantSeq-Pool libraries.


Frequently Asked Questions

Please find a list of the most frequently asked questions below. If you cannot find the answer to your question here or want to know more about our products, please contact

In both standard QuantSeq and QuantSeq-Pool library generation is initiated by oligo(dT) priming, where the primer contains a partial Illumina-compatible linker sequence. However, in QuantSeq-Pool this primer also contains Unique Molecular Identifiers (UMIs) and an i1 sample-barcode. This early barcoding allows the samples to be combined by pooling after first strand synthesis. All subsequent steps of the protocol can thus be performed on pools containing up to 96 samples. Batch processing significantly shortens the overall library generation time and reduces technical variability between samples within one pool.

No, QuantSeq-Pool uses early pooling and thus equal read distribution in sequencing experiments requires normalization of the input RNA amount prior to starting library generation. This can be achieved best with high quality RNA (RIN > 6) with at least 10 ng per sample. The RNA input should be homogenous in terms of integrity, purity, and quantity across all samples. For further information please refer to the Appendix A in the QuantSeq-Pool Sample-Barcoded 3’ mRNA-Seq User Guide.

Formalin-Fixed, Paraffin-Embedded (FFPE) material is very heterogeneous and highly variable in terms of quality, degree of cross-linking, and accessibility of the mRNA. Therefore, processing degraded or FFPE RNA with QuantSeq-Pool may lead to uneven read distribution between samples in sequencing experiments. For best practice, the QuantSeq 3’ mRNA-Seq Library Prep Kit for Illumina (Cat. No. 015, 113 – 115, 129 – 131) is recommended for processing FFPE samples as it allows quality control and quantification of individual libraries. This offers the possibility to re-adjust individual samples for equimolar lane pooling and balanced read distribution during sequencing.

Lexogen’s QuantSeq-Pool 3’ mRNA library preparation protocol is designed to generate sequencing Illumina-compatible libraries from total RNA within 4.5 hours. When carrying out the protocol for the first time, please allow for more time, including time for performing the qPCR assay.

No. QuantSeq-Pool requires asymmetric paired-end sequencing, where Read 1 is generated towards the poly(A) tail and directly corresponds to the mRNA sequence. Read 2 will contain the Unique Molecular Identifier (UMI) followed by the i1 sample-barcode. Therefore, it is necessary to sequence Read 2 for sample identification, i1 barcode demultiplexing and UMI deduplication.

The kit includes a set of 96 i1 indices (i1 12 nt RT-Set for QuantSeq-Pool, dried-in sample barcodes in 96-well plate format), which allow up to 96 samples to be sequenced per lane on an Illumina flow cell.

For multiplexing of more than 96 samples, unique dual indexing for the individual pools (containing up to 96 sample-barcoded libraries) is recommended.

Lexogen offers various indexing systems that are fully compatible. We recommend using Lexogen’s 12nt Unique Dual Indexing System with QuantSeq-Pool experiments. Unique Dual Indices (UDIs) with pre-mixed i5 and i7 indices are available in a convenient 96-well format. UDIs are 12 nucleotides in length and provide superior error correction capability for massive multiplexing. The Lexogen UDI 12 nt Unique Dual Indexing Sets are available in sets of 96 (Cat. No. 101 – 105) for multiplexing of up to 9,216 samples per set, or 36,864 samples with just 384 UDIs (Cat. No. 156).

Lexogen also offers 6 nt single indexing sets for i7 (Cat. No. 044.96) and i5 (Cat. No. 047.96). These 6 nt Index Sets can be used separately as single indices for either i5 or i7, or can be combined for dual indexing.

The QuantSeq-Pool protocol yields library fragments longer than 600 bp, with inserts longer than 430 bp when prepared from high quality Universal Human Reference RNA (UHRR). Therefore, QuantSeq-Pool libraries are compatible with all common sequencing read lengths. Library shape and average insert size may vary, depending on the type of input sample (e.g., organism and/or cell type). Libraries may also appear different depending on the microfluidics platforms used for quality control e.g., in TapeStation traces, the shape of the electropherogram curves appears shorter than in Bioanalyzer traces from the same libraries (see Fig. 1, below).


Figure 1 | Bionalyzer and TapeStation traces from the same libraries. Library 1: 8x 10 ng UHRR per Second Strand Synthesis (SSS) reaction, 14 cycles, Library 2: 88x 10 ng Human Neural Progenitor Cells (hNPC) RNA per SSS, 11 cycles. Both libraries were run in a Bioanalyzer High Sensitivity DNA Chip (left plots) and in a TapeStation High Sensitivity D5000 ScreenTape (left right graphs). Average Size was calculated from 170 – 3500 bp using the region analysis feature from the software specific to each microfluidics device.

The electropherograms from TapeStation and Bioanalyzer platforms are not equivalent due to the different properties of their gel matrixes and the units displayed on the Y axis (Fluorescent Units (FU) for Bioanalyzer and Normalized FU in TapeStation). Therefore, we encourage customers not only to look at the shape of the electropherogram curves, but also at the Average Size of the libraries when assessing the quality of QuantSeq-Pool libraries. For more information, see QuantSeq-Pool Sample-Barcoded 3’ mRNA-Seq User Guide, Typical Results, Appendix D. If you have unsure about the size of your libraries, please contact

No, currently the QuantSeq data analysis pipelines on BlueBee are only compatible with standard QuantSeq FWD and REV. QuantSeq-Pool libraries contain the Read 1 linker sequence in the 5’ part of the second strand synthesis primer, hence NGS reads are generated towards the poly(A) tail. Following demultiplexing, all further steps for trimming, mapping, UMI processing, and counting can be integrated in standard data analysis pipelines. Lexogen offers a QuantSeq-Pool data analysis pipeline, which can be found on our GitHub page. For further questions about the pipeline, please contact

The Demultiplexing and Error Correction Tool, iDemux, is available in a command-line format using the Python or C++ programming language on GitHub. For details on the full QuantSeq-Pool data analysis pipeline, please click here. If you have any questions about iDemux or our QuantSeq-Pool pipeline, please contact us at

Yes, automation on liquid handling devices is possible for massive throughput. Please contact for further information. Early pooling and batch processing increases throughput capacity also for manual sample preps offering the possibility to complete large scale projects even without the need to invest in specialized automation equipment.

No, QuantSeq-Pool uses optimized reagents for pooled processing that differ from QuantSeq reagents. For blood samples, the QuantSeq 3’ mRNA-Seq Library Prep Kit for Illumina (Cat. No. 015) is recommended for use with Globin Block Modules. Alternatively, globin mRNA can be removed from blood samples prior to extraction, e.g., by using SPLIT for Blood (Cat. No. 099). RNA extracted with SPLIT for Blood, or similar extraction procedures is fully compatible with QuantSeq-Pool.


QuantSeq-Pool Sample-Barcoded 3′ mRNA-Seq Library Prep Kit for Illumina

pdf  User Guide – update 18.02.2021
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pdf  Product Flyer – release 19.08.2020
i1 12 nt RT-Set for QuantSeq-Pool Sample-Barcode Sequences for Illumina
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Data Analysis

QuantSeq-Pool libraries contain the Read 1 linker sequence in the 5’ part of the second strand synthesis primer, hence NGS reads are generated towards the poly(A) tail. Demultiplexing of i5 / i7 indices can be carried out by the standard Illumina pipeline. Lexogen i7 and i5 index sequences for 6 nt and 12 nt index systems are available for download at The i1 sample-barcode is located at the beginning of Read 2 and preceded by a 10 nt UMI sequence. Therefore, the i1 barcode is contained within bases at position 11 – 22 of Read 2, depending on the chosen index read out length of 8, 10 or 12 nucleotides. Demultiplexing of i1 sample-barcoded libraries can be performed using Lexogen’s Demultiplexing Tool. All further steps for Trimming, Mapping, UMI processing, and Counting can be integrated in standard data analysis pipelines. For further questions on QuantSeq-Pool data analysis, please contact

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