LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Detection of low-abundance point mutations by competitive strand assisted endonuclease IV signal amplification system

Photo from archive.org

SummaryGenetic mutations are important molecular biomarkers for cancer diagnosis and surveillance. Therefore, the development of methods for mutation detection characterized with straightforward, highly specific and sensitive to low-level mutations within… Click to show full abstract

SummaryGenetic mutations are important molecular biomarkers for cancer diagnosis and surveillance. Therefore, the development of methods for mutation detection characterized with straightforward, highly specific and sensitive to low-level mutations within various sequence contexts is extremely needed. Although some of the currently available methods have shown very encouraging results, their discrimination efficiency is still very low. Herein, we demonstrate a fluorescent probe coupled with blocker and property of melting temperature discrimination, which is able to identify the presence of known or unknown single-base variations at abundances down to 0.1% within 20 min. The discrimination factors between the perfect-match target and single-base mismatched target are determined to be 10.15–38.48. The method is sequence independent, which assures a wide range of application. The new method would be an ideal choice for high-throughput in vitro diagnosis and precise clinical treatment.

Keywords: detection; mutations competitive; point mutations; detection low; low abundance; abundance point

Journal Title: Current Medical Science
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.