In using this approach to study B. anthracis, Bergman and colleagues sequenced mRNA samples that were collected from B. anthracis cells growing in a variety of conditions. They collected more than 270 million sequence "tags," each of which corresponds to a short fragment of an RNA molecule, and pieced them together using a custom software tool that they developed for the project.
"Once the data were together, it was very easy to see transcript structure across the genome," said Bergman. "We could see clear boundaries between transcribed and non-transcribed regions of the genome, which represent where individual transcripts start and stop. This was really exciting, because transcript boundaries tell us precisely where to find the regulatory sequences that govern gene expression, and these sequences are extremely hard to find otherwise."
The researchers also found that since RNA-Seq is essentially just a very high-throughput counting technique, it also provides a way of determining how abundant each transcript is in the cell. They showed that this approach is a much more sensitive way of measuring gene expression than the more conventional microarray-based methods.
"We can very easily see which genes are the most highly expressed, but we were also able to detect very rare transcriptsthe ones that are only being produced by 1 in 100 or 1 in 1000 cellsand with this level of sensitivity we can actually get a glimpse of the random events that make individual cells different from one another," said Bergman.
Combining the structure and abundance information for every gene in a bacterial genome allows researchers to take a more rational approach to tasks like antibiotic discovery and microbial engineering, Bergman noted.
"Sequencing-based transcriptome profiling has several huge advantages over array-based profiling," sad Bergman. "Right now array-based methods are still a little less expensive, and
|Contact: David Terraso|
Georgia Institute of Technology