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Guest Post: What’s Coming Next in Genome Sequencing

By Emma Chory, Chemical Engineering Ph.D candidate at Stanford University School of Medicine: 

Due to the massively lowered cost of genome sequencing, sequencing start-ups have become some of the hottest and most anticipated ventures. For the first time in 2014, Y-Cominbator announced that it would be accepting 6 bio-based start-ups into its summer accelerator program. Aspiring biotech entrepreneurs around the world rejoiced. No longer were the woes of high capital costs, burn rates, failure rates, and long returns on investment…. no more! That same year, biotechs represented a quarter of all US IPOs and multiple new accelerators like IndieBio and Breakout Labs emerged to keep the momentum going on these young bio-centric ventures. Much like how Lily Ventures spun out of Eli Lily to keep up with the growing demand for emerging pharmaceuticals, Illumina recently started its own accelerator to stay apace with the rapidly evolving landscape of genome-based therapeutics and diagnostics.

In my last post, I mentioned advances in genome sequencing which is an umbrella term for fields that relate to genomics. Today I want to shed more light on a few of these quite diverse fields.

Improvements in Wet-Lab Sciences

The first and most commonly thought-of field relates to technologies that improve the chemistry of genome sequencing—microfluidics, image processing, cell culture, to name a few. Improvements in this kind of “wet-lab” science are critical in order to extend the advancements of sequencing beyond the run-of-the-mill human genome.

Fluidigm, NanoString and others, pioneered the miniaturization of genome sequencing with techniques like putting DNA into tiny nano-sized droplets, while recent others have improved the ability to isolate a very specific cell from a larger population (Xcell Bio). The ability to isolate a single cell is required for applications such as sequencing a single cancer cell (that differs by patient), examining a dangerous bacterium within a heterogeneous group in the gut, or even prenatal diagnostics where only a finite number of cells circulating in the mother’s blood stream belong to her offspring.

Improvements in Downstream Processing

Beyond advances in the “wet-lab” sciences, improvements in downstream processing are critical in order to make genome sequencing cheaper and more accessible.

Many of the early developers of genome sequencing technologies used to joke that even though their machines could sequence a genome in less than an hour, it would take the full length of a PhD to analyze it. This still holds true today. Despite the ability to access genomic data quickly, there is very little sense for what these “strings of letters” mean, without months of banging your head against a keyboard and limitless computational power.

Companies like DNAnexus and Tute Genomics are putting genomics into the cloud, DNA-seq Alliance are applying machine-learning on cancer patient data, and even open-source genome data aggregators like Memorial Sloan Kettering’s “cBioPortal for Cancer Genomics” are striving to make sequence analysis more accessible. Providing tools for generating straightforward, meaningful, and medically applicable genomic data are attempting to make sequencing more accessible.

The Final Frontier …

Naturally, the final advancements in genome sequencing will come from translation of the science and analysis into the clinic.

One Illumina incubatee, Epibiome Inc., is using genome sequencing to identify and quantify mixed populations of bacteria, allowing them to develop novel and tailored drug cocktails based on their findings. Similar strategies have been coupled with social networking in order to understand outbreaks of tuberculosis, identify multiple cases of C. difficile in hospitals, and uncover certain drug resistant bacteria that can guide the course of treatment for infected individuals. These same single-cell technologies may be used to diagnose a specific type of cancer and ascertain whether it is growing, changing or acquiring its own drug resistance, as many forms of cancer do.

Improving genome-sequencing and advanced analytics are in themselves grand challenges. When these tools are coupled with the creation of novel and actionable courses of treatment, the outcomes will not only pay off for patients and families but also for the investors and incubators who had the foresight to place confidence in these ideas.

You can read Emma’s previous post about genome assembly here and her blog about cancer immunotherapy here.

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Deep Technology Guest Post
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