SANTA CRUZ, Calif., February 9, 2016 – Somagenics has been awarded a second phase I SBIR grant from NIH to develop its resQ-RNA technology for quantitative real-time PCR of fragmented RNA samples.
Fragmentation of RNA is a particular problem in tissue samples that have been preserved and stored (e.g., formaldehyde-fixed, paraffin-embedded [FFPE] specimens) or collected under sub-optimal conditions (forensic samples or biofluids containing RNases). Fragmentation greatly limits the information that can be extracted from RNA samples using current methods of analysis, including the most accurate method, real-time quantitative PCR (qPCR), as the fragments can become shorter than the minimum length required for this technology.
SANTA CRUZ, Calif., October 6, 2015- SomaGenics, Inc. today announced the launch of its novel miR-ID® platform for detecting miRNA using a circularization-based RT-qPCR method. miR-ID® is highly sensitive, uses single-dye detection, and can discriminate miRNA isoforms with single nucleotide differences at any position along the molecule. The technology works well with all sample sources, including total RNA, cell lysates, and tissue lysates.
SANTA CRUZ, Calif., April 2015 – Somagenics has been awarded a two-year NIH grant to develop its novel RealSeq™–T technology for targeted next-generation sequencing (NGS) of small RNAs such as microRNA.
There is increasing interest in using NGS for miRNA biomarker discovery from biofluids such as blood plasma as well as for miRNA expression profiling and diagnostic purposes. There are many advantages to using NGS, including unlimited multiplexing, high sensitivity, sequence specificity and ability to detect miRNA sequence editing. Targeted NGS brings these advantages to the quantification of any specific group of sequences of interest. However, sequence bias in the construction of the small RNA libraries used in sequencing has so far limited the utility of NGS, both targeted and non-targeted. This bias gives distorted small RNA profiles and renders some species of RNA that might be good biomarkers unavailable for accurate quantification.