Software to Aid Genome Analysis for Cancer Therapies

John McDonald (Georgia Tech)

Researchers at Georgia Institute of Technology in Atlanta have developed software that analyzes ribonucleic acid (RNA) in the human genome to provide more useful data for generating personalized cancer therapies. The work of biology professor John McDonald (pictured left) and bioinformatics Ph.D. candidate Vinay Mittal is described and appears online in the journal Nucleic Acids Research.

The ability to quickly and inexpensively sequence the genomes of cancers can help identify specific mutations responsible for the disease in individual patients. However, this capability requires the processing of massive amounts of complex data, to be useful for scientists and clinicians. Among the most critical data in this task come from RNA sequencing.

RNA like DNA is a nucleic acid in the genome, but is transcribed by DNA by enzymes and is important to the synthesis of proteins. At least 23,000 pieces of RNA in the human genome encode the sequence of proteins, with millions of other pieces that help regulate the production of proteins. “A major bottleneck in the realization of the dream of personalized medicine is no longer technological,” says McDonald, “It’s computational.”

To meet this scale and complexity, Mittal and McDonald devised a software program called RNA-Seq Analysis Pipeline (R-SAP) with the ability to to analyze and compute high-throughput RNA sequencing data sets. The software has multi-threading capability, which means it can execute execute different sections of the code called threads simultaneously, which reduces the time needed to process the data.

R-SAP can quickly determine every gene’s level of RNA expression and provide information about variants and biomarkers. A few biomarkers, such as a mutation of the BRAC-1 gene, are already being used to identify women with a high risk of developing breast or ovarian cancer.

“R-SAP can make 100 million reads in just 90 minutes,” notes Mittal, adding that running the code simultaneously on multiple computers can reduce that time further. Data from an R-SAP analysis are expected to help researchers and clinicians compare RNA profiles, called transcriptomes, of normal cells with those of individual cancers. This analysis can then help develop a more customized therapeutic strategy.

R-SAP, now in version 1.1, carries a GNU General Public License and is available as a free download from McDonald’s lab at Georgia Tech.

Read more: Software Speeds Database Sequence Searches

*     *     *