Tag Team: At DFCI, Pippin and Nextera Make Better Libraries

Over at the Dana-Farber Cancer Institute, scientists have been doing some really interesting work pairing the Pippin Prep with Illumina’s Nextera kit for library preparation.

Zach Herbert, associate director of the Molecular Biology Core Facilites at DFCI, says that he incorporated Pippin size selection when it became clear that the genomic libraries generated by Nextera could use some additional optimization. “It’s really beneficial to have a narrower size range than the Nextera kit generates on its own,” he says.

Herbert uses the efficient Nextera for much of the small genome work and some of the larger amplicon projects that are sent to his core lab. In order to optimize reproducibility, flow cell clustering on the MiSeq, and downstream analysis, Herbert added a Pippin step to generate very tightly sized libraries after the Nextera tagmentation protocol.

The Pippin/Nextera tag team also shows value beyond de novo assemblies. “Having a narrow and known size distribution makes calculating the molarity a lot easier so you can get a better cluster density and maximize the number of reads,” Herbert says. It’s also a boon for pooling samples. Attempting to pool samples with a broad size range in equimolar amounts is very tricky — “but if all those libraries are the same size, then we’re much more likely to get an even distribution of that pool.”

To learn more about Herbert’s work pairing Nextera and Pippin, read our case study here.

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