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Has anyone had any luck trying to quantify Nextera XT libraries using qPCR? I have tried it twice with no success. I have been able to quantify TruSeq libraries and they have been working just right. It looks like primer sequences are correct, so I don't know what could be causing the problem.
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Yes, we got a library, already normalized and eluted as single strands using the kit protocol. The protocol called for us to just heat denature it, snap cool and immediately load into the reagent cassette for sequencing. But we did a KAPA qPCR kit (not the Illumina-specific kit, just the generic one) using normal flow cell oligo primers. The result looked fairly reasonable, so we proceeded. Basically just did what the protocol asked. (Okay, I spiked in phiX out of paranoia -- but otherwise the followed the instructions on the box.)
Worked okay.
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Phillip -
You've had luck with the bead normalization? I've never been able to get it to work. Anytime I use the beads I get a uneven distribution of up to 50%. That's why I'm relying on qPCR to quantify my library.Comment
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You get better than 0.5x variation in read numbers using qPCR? Like you have several samples in a pool and the lowest one gave you 20 million and the highest gave you 30 million? That would be close enough to perfect to satisfy me!
I did not do the bead normalization myself -- we just got a Nextera XT pool from a customer and ran it. There were >20 different index pairs in it. I generally call it a "win" if the lowest sample gives > 1/2 the number of reads as the highest sample. So by that criteria, it was good. Actually, if I remember correctly, it was better than that.
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PhillipComment
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Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
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With the launch of new single-cell sequencing platforms in 2026, the field stands at an exciting inflection point. This article surveys the most impactful advances in the field and discusses how they’re reshaping research in cancer, immunology, and beyond.
Introduction
Single-cell sequencing technologies have undergone remarkable advances over the past decade, transitioning from low-throughput experimental approaches to highly scalable platforms capable of...05-22-2026, 06:42 AM
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