Library quantification is a critical step for achieving uniform sample pooling and obtaining optimal cluster density when sequencing. On non-patterned flow cells, cluster density has a significant impact on run performance, specifically, data quality and total data output. On patterned flow cells, the percentage of data passing filter is directly linked to the flow cell occupancy.While underclustering/underloading can maintain high data quality, it results in lower data output. Alternatively, overclustering/overloading can lead to run failure, poor run performance, lower Q30 scores, introduction of sequencing artifacts, and lower total data output.
The most common cause of under- and overclustering is inaccurate library quantification. Different methods of quantification are recommended for different types of libraries (see here). This bulletin describes the three most common quantification methods.
qPCR selectively quantifies full-length library fragments by using primers that anneal to the p5 and p7 sequences. Only fragments with both p5 and p7 sequences can bind to the flow cell and form clusters.
Figure 1: Only full-length libraries (on the right) are quantified by qPCR. Incomplete libraries (on the left) are not quantified.
Best practices include using triplicates for each sample and at least two separate dilutions (eg, 1:10,000 and 1:20,000).
A positive control is highly recommended, such as a previously sequenced library. (This does not refer to qPCR standards, which are required to set up the standard curve.)
The Illumina qPCR guide recommends using KAPA qPCR kits, which include six DNA standards to generate the standard curve. qPCR primers are included and work with all Illumina adapters. Different qPCR kits are available for different qPCR chemistries, such as DNA binding dyes (eg, SYBR Green) and hydrolysis probes (eg, TaqMan probes). qPCR kits for Illumina libraries are also available from other third-party vendors.
Figure 2. Different Real-Time PCR Chemistries
Fluorometric systems such as Qubit and PicoGreen use fluorescence-based dyes that selectively bind to either double stranded DNA (dsDNA), single stranded DNA (ssDNA), or RNA. dsDNA assays are used for most library types.
Fluorometric methods are the best option for libraries with broad fragment size distributions such as Nextera XT libraries.
A fluorometric method risks overestimating the library concentration because this method measures all dsDNA in the pool. This includes partially constructed fragments (incomplete library fragments) and residual primer dimers from PCR.
Use of a positive control (such as a previously sequenced library or a commercial gDNA control) is recommended.
Bioanalyzer / Fragment Analyzer and equivalent instruments
Microfluidics-based automated electrophoresis systems are commonly used in library preparation workflows. These include the Bioanalyzer, TapeStation, and Fragment Analyzer.
These instruments are recommended for quality control (eg, checking the library size distribution). Only use these instruments for quantifying libraries with narrow size distributions such as TruSeq™ Small RNA libraries, TruSeq Targeted RNA Expression libraries, or AmpliSeq for Illumina libraries.
The Bioanalyzer and comparable instruments are not optimal for quantifying other library types due to decreasing accuracy with increasing library fragment size distributions.
Figure 3: A. Libraries with narrow size distribution (eg, TruSeq Small RNA libraries) can be quantified by Bioanalyzer or comparable instruments. B. Libraries with broad size distributions (eg, Nextera™ XT libraries) must NOT be quantified by Bioanalyzer or comparable instruments.
Quantification Methods to Avoid
UV Spectrophotometry: Library quantification using spectrophotometry-based methods are subject to overestimation of library concentration and should be avoided. UV spec methods quantify single stranded nucleic acids and free nucleotides along with complete, dsDNA library fragments and are not appropriate for sequencing applications.
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