As we move into the era of personalized medicine, it may not be too far off that a visit to our doctor includes a number of genome-scale “seq” experiments to diagnose disease and estimate our likelihood of response to an array of possible treatments. One such experiment measures the cell’s total RNA abundance (its transcriptome) which provides a snapshot of a cellular activity or state. For decades global gene expression levels and changes in expression have been used to identify disease and drug response markers. This has been enabled by technological advances such as “whole-exome” sequencing which can home in on biomarker genes that define cellular states. These approaches were first designed to survey protein-coding gene (PCG) levels of expression and have uncovered numerous PCG biomarkers, led to advances in how drugs are screened, and generated insights into how gene pathways are misregulated in disease.

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