At NYU’s Center for Genomics and Systems Biology, Pippin Allows for More Precise DNA Size Selection

At NYU’s Center for Genomics and Systems Biology (CGSB), the genomics sequencing core facility (GenCore) runs both infectious disease and model organism sequencing projects through its Illumina and Ion Torrent pipelines. In both workflows, they find Pippin Prep to be a handy tool for automated DNA sizing.

GenCore Manager Paul Scheid sees many different types of research projects come through the facility’s doors: de novo sequencing and double digest RAD-seq are two of the most common. GenCore clients are often studying the genetics and genomics of populations, not just an individual organism.

For both applications, Scheid says that Pippin automated sizing has been helpful to the lab, which has the HiSeq 2500, MiSeq, and PGM. The team uses Pippin for constructing regular libraries for de novo assembly, and also for tracking specific structural variants. “If we’re interested in eking out a specific indel and we want to be assured that that indel cannot possibly be created by a contiguous fragment in the population of fragments that go into library preparation, we can use Pippin to define a very narrow fragment range,” Scheid says.

The GenCore team also handles quite a bit of ddRAD-seq, a technique developed by the Hoekstra lab at Harvard. “We have a group that does a lot of ddRAD sequencing to isolate variants across the genome of their particular species of interest,” Scheid says. “We use the Pippin when constructing those ddRAD libraries to control the amount of loci that we hit from a given library. It’s very nice for fine-tuning that parameter.”

Automated size selection also works nicely with sequencing projects run on the PGM, “which is very sensitive to fragment sizes because of the emulsion PCR,” Scheid says. “So we use Pippin to make sure the libraries are in the exact range we want.”

Before getting the Pippin about a year ago, GenCore had several other methods for size selection. NYU CGSB decided to invest in the tool because it could accomplish things that the other methods couldn’t. “I just don’t think that there are any other platforms out there that allow the level of granularity that Pippin does in terms of size selection,” Scheid says.

This entry was posted in Blog. Bookmark the permalink.

Comments are closed.