Illumina Workflow: Pippin for Massively Parallel Genotyping

With so many Sage customers using their Pippin instruments in an Illumina sequencer pipeline, we’re taking a look at various applications enabled by the Sage + Illumina combination. Today we check out double-digest RADseq, which could not work without precise and reproducible size selection.

The approach was first nailed down by scientists in Hopi Hoekstra’s lab at Harvard University, which focuses on population genetics, development, speciation, and behavioral genetics. Their innovation, a new version of the popular reduced-representation genome sequencing (commonly called RADseq), introduced a second restriction enzyme step as well as Pippin Prep size selection. The result: a validated protocol for massively parallel genotyping that allows researchers to study hundreds or thousands of genetic loci across hundreds of thousands of samples — without any prior knowledge of the organism’s genome.

Essentially, scientists use ddRADseq to study a sliver of the genome in each sample; with Pippin sizing and the double restriction enzymes, they ensure that they’re looking at the same sliver across all samples. Then they can assess genetic variation within those regions for various applications, such as evolutionary development, population studies, and QTL mapping.

We talked to Brant Peterson, PhD, a postdoctoral fellow in the Hoekstra lab and lead author on the ddRADseq paper, to learn more about the work. He told us that the team’s usual method of size selection — manual gel extraction — was simply not reproducible enough to make the ddRADseq results meaningful. After switching to Pippin Prep, Peterson told us, “There’s very little difference from one sizing reaction to the next, which is the key to this approach working.”

In the time since the original paper came out, other labs have adopted the ddRADseq approach. One is GenCore, the genomics sequencing core at New York University’s Center for Genomics and Systems Biology. GenCore Manager Paul Scheid learned the method and offers it as a service for core clients. “We use the Pippin when constructing those ddRAD libraries to control the amount of loci that we hit from a given library,” he told us. “It’s very nice for fine-tuning that parameter.”

Next we’ll have the final post in our blog series. Check back to learn about how Pippin products are being used with Illumina sequencers to generate higher-accuracy assemblies.

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