Research Terms
This integrated DNA test kit helps diagnose disease by measuring methylation and chromatin structure at the same time, giving it an edge over disease detection kits that employ separate evaluations. Locked inside every tissue sample is valuable information about a person’s health. By studying the language of cells, genes and proteins, researchers can better understand disease development, including how cancer progresses. DNA methylation, which helps control gene expression, and chromatin structures, protein-DNA interactions in eukaryotes, can undergo cancer-induced changes. Evaluating these gene reactions and changes at multiple loci together rather than in isolation can lead to more accurate diagnoses. Simultaneous analysis, however, tends to be costly using available technology. University of Florida researchers have developed a test kit that merges methyltransferase footprinting (MAPit) and targeted-bisulfite-sequencing (bisulfite patch PCR) into what they call "MAPit-patch." This technology allows for parallel measurement at single-molecule resolution of DNA methylation and chromatin structure at the same time across several genomic loci and samples with minimal DNA input requirements. The inexpensive test kit has numerous clinical applications and will prove useful in any research laboratory that has a need for multi-locus and multi-sample processing. The national market for genetic testing, which now stands at around $5 billion a year, could reach $25 billion by 2012.
Test kit for identifying biomarkers that indicate disease, especially cancers
Researchers at the University of Florida merged available technologies to create a MAPit-patch test kit that permits simultaneous assessment of DNA methylation and chromatin structure. It can process several biological samples with hundreds of genes at once and requires only small DNA inputs. The test kit’s targeted (rather than genome-wide) approach is appropriate for clinical applications where assessment of particular disease biomarkers is required. The MAPit-patch may have already identified a new class of cancer biomarkers.
