UC Berkeley

The advent of next generation sequencing (NGS) has fundamentally changed genetics research. Where researchers were once focused on sequencing the genome of a species, they now can sequence the genome of a particular tumor or even a single cell. NGS has also made it cost effective to sequence the RNA transcripts found within a cell, a collection of data known as the transcriptome. Unfortunately, current protocols for sequencing the genome and the transcriptome are incompatible. This leaves researchers with a choice: for a given sample you can examine either the DNA or the RNA. The work presented here makes it so that researchers no longer have to make this choice. This dissertation describes the development of a new protocol, known as Gel-Seq, that makes it possible to sequence both DNA and RNA from as few as 400 cells. This technology will allow researchers to directly examine the ways that changes in the genome impact the transcriptome. At the heart of the Gel-Seq protocol is the physical separation of DNA from RNA. This separation is achieved electrophoretically using a newly designed combination of polyacrylamide membranes that take advantage of the size differences between these molecules.

Two different device options were developed as a part of the Gel-Seq protocol. One device, designed for rapid adoption, was fabricated using standard equipment found inside of a biology laboratory. The second device, designed for separating low input samples, was fabricated using newly developed micro-scale fabrication techniques. In addition to the development of these physical devices, a biological protocol was developed to generate genome and transcriptome data using these devices. In order to validate this technology, a cell line with a stable genome and transcriptome was used. Comparing the Gel-Seq protocol to standard protocols, the results showed a high correlation for both the genome (R = 0.88) and transcriptome (R = 0.96) data. This supports the conclusion that the device can be used to produce correlated genome and transcriptome libraries. This dissertation reports on the development, optimization, and validation of the Gel-Seq protocol.