Genomic signature sequences used by clinical researchers to detect, quantify and diagnose nucleic acid sequences are not inclusive enough. New research shows that many published sequences are of unacceptably low sensitivity for most clinical applications.
According to Shea Gardner of the Lawrence Livermore National Laboratory, California, lead author of the study, "In recent years, real-time polymerase chain reaction (RT-PCR) has become a leading technique for nucleic acid detection and quantification. In our analysis of the RT-PCR signatures described in recent literature, we found that many published sequences have a high specificity but only a very low sensitivity".
Gardner and co-author, Gordon Lemmon, suggest that a rigorous approach involving false positive and false negative analysis should be the standard by which an initial assessment of signature quality is made. They write, "Signatures must be reassessed as new sequence data becomes available. For targets with wide nucleotide diversity, such as influenza viruses, it is necessary to develop a set of signatures with a minimal set clustering approach that may also include signatures with degenerate/inosine bases".
Gardner comments, "The rapidly growing availability of sequence data for pathogens from across the globe means that we can better predict how robustly a signature will detect all the intended targets. Using a computational approach to design and pre-screen signatures can improve the quality of sequence-based diagnostics and save time and money in lab testing".
The above post is reprinted from materials provided by Annals of Clinical Microbiology and Antimicrobials. Note: Content may be edited for style and length.
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