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Recent advances in genomics present new opportunities for enhancing knowledge about gene regulation and function across a wide spectrum of organisms and species. Understanding and evaluating this information at the individual gene level is challenging, and not only requires extracting, collating and interpreting data from public genetic repositories, but also recognizing that much of the information has been developed through implementation of computationally based exon-calling algorithms, and thus may be inaccurate. Moreover, as these data usually have not been validated experimentally, results also may be incomplete and incorrect. This has created a quality-control problem for scientists who want to use individual gene-specific information in their research. Here, I describe a simple experimental strategy that takes advantage of the large amounts of untapped primary experimental data for characterizing gene expression that have been deposited in the Sequence Read Archive of the National Center for Biotechnology Information. The approach consists of a readily adaptable pipeline that may be used to confirm exons, to define 5' and 3' un-translated regions and the beginnings and ends of individual genes, and to quantify alternative RNA splicing. The series of experimental strategies described offers effective replacements for older molecular biological methods, and can rapidly and reproducibly resolve major gene mapping problems.

Gene mapping by RNA-sequencing: a direct way to characterize genes and gene expression through targeted queries of large public databases