DHMRI’s bioinformatics team worked with a federal agency to qualify and quantify the background tumor rates of their study animals. The project focused on the exomic structural changes of spontaneously occurring tumorgenesis as compared to induced tumorgenesis.
A two-step, paired-sample genomic study was designed that elucidated both exomic structural variations and gene expression to screen the spontaneous occurrences from downstream research. Using the collaborator’s large selection of preserved tissues, FFPE samples were compared to the standard fresh frozen protocols to differentiate any and all exomic structural changes between them. Both the targeted Exome-Seq and RNA-Seq samples were sequenced on a HiSeq2500 in the DHMRI Genomics laboratory. The Bioinformatics Team conducted in-depth quality control and applied multiple analytical tools including CLC Genomics Workbench, CASAVA, and open-source R, FastQC, and Bowtie2 to process and analyze both the exome data and the RNA-Seq data.
“Through this study, we determined FFPE did not significantly degrade the samples and that sequencing and analysis were still feasible,” said Garron Wright, DHMRI bioinformatics project leader. “The study saved the collaborator a significant amount of time, energy, and money in developing and analyzing new bioassays. As a secondary objective, we helped them ascertain gene expression analyses from the sample archives to create a database of large scale gene expression within these experimental animal models.”
DHMRI and the collaborator are continuing to investigate the pairwise exome and gene expression data. Plans are underway for additional experiments using this gene expression database.