Is Genetic Sequencing a Scientific Crutch?
The sequencing of the human genome began in 1990 to great fanfare. There was a high-profile race between two scientific approaches, the eye-glazing price tag of $3 billion, and, of course, the promise that by deciphering the code of our most fundamental instruction booklet, it would be possible to unlock a number of medical cures. The 21st century was here, and surely flying cars and personal assistant robots were just around the corner.
Of course, the link between genetic sequence and real-world physiological results turned out to be more complicated than most scientists would have imagined. The enormous amount of data generated by the project proved difficult to interpret, and understanding how genes interact, what “nonsense” patches of DNA really do, and how regulation works are all fields in their infancy.
Nonetheless, the practice of sequencing genes (genomics) – and then proteins (proteomics) and RNA (transcriptomics) – has only accelerated as costs have plummeted and the myth of an easily interpretable data set has persisted. But just how useful is sequencing? It’s an easy first step to take – more data to work with rarely seems like a bad thing – but would more targeted experiments answer specific questions more effectively? In a recent issue of the journal Nature, microbiologists Janet Jansson and James Prosser debate these questions, which have become increasingly relevant across a range of microbiologically relevant fields.
Jansson contends that omics-based experiments have given us proteorhodopsin (a new-to-science light-harvesting system), ammonia-oxidizing archaea, and a mechanism to predict biodiversity from environmental features. This technique is particularly useful in studying unculturable organisms (the vast majority of microbes on the planet): without the option of isolation and genetic manipulation, disentangling the network of genes and proteins is the best hope for understanding microbial roles in the system.
Prosser, on the other hand, notes the asymmetry between technological advances allowing genomic and proteomic studies and our knowledge of microbial ecology writ large. He characterizes the reliance on omics data sets as lazy, promoting instead the “courage and intellectual effort in the construction and explicit stating of hypotheses, and critical and focused experimental testing of predictions.” Prosser also notes that the once-removed experimental testing of predictions – not the initial firehose-style observations themselves – provide a more robust result.
Obviously, using both techniques in concert is the optimal way forward, since the collection of large data sets generates testable hypotheses that a more targeted experiment would subsequently examine. But if one is forced to choose, it seems shortsighted to neglect a cost efficient source of data. From the forest, it’s still possible to see the trees, but cataloguing individual trees is a tough way to understand an entire forest.
Omics data sets capture a moment in time, and although they’re not exactly comprehensive (proteomics runs tend to capture an estimated 30% of the proteins present, for example), there is a lot of latent data awaiting interpretation. It’s possible to comb through the data, develop a hypothesis, and re-search the results for information that supports or rejects your proposed story. In this way, a single dataset represents many experiments in one: doing the analogous work in customized experiments would be an arduous process, and since each experimental condition is always slightly different from the one before, you could never be sure you’re testing the same parameters.
The era of big data in microbial ecology is irreversibly upon us, and the real challenge now is how to use this new reality not as a crutch, but as a truly useful tool.
Jeff Marlow is a graduate student in Geological and Planetary Sciences at the California Institute of Technology where he studies exotic microbial metabolisms in an attempt to understand the limits of life on Earth and beyond.
Follow @jj_marlow on Twitter.