Kaja Wasik’s mission is to get you to want your genomic DNA sequenced. “The world is moving toward including genomic data,” Kaja explains, citing the already normalized use of genetic testing in prenatal care and disease diagnoses. However, exactly who can access genomic data, and how it can be?
However, exactly who can access genomic data and how it can be used has sparked debates among medical, ethical, and business communities. The people whose DNA data is being used often don’t even have the ability to use it themselves. Kaja is out to change that. Giving people access to their own DNA sequences “empowers people,” she says.
Kaja (co-founder, CSO) and her co-founders, Tomaz Berisa (co-founder, CTO) and Joe Pickrell (co-founder, CEO), have developed a new sequencing platform at Gencove, their New York City-based start-up company. Gencove prepares genomic content from participants’ saliva for genome sequencing.
They’ve improved upon other genome sequencing services in three ways:
1 – Using low coverage whole genome sequencing, rather than SNP chips (more on this below).
2 – Providing information about participants’ oral microbiomes.
3 – Open API access to all their genomic data.
Participants get all this plus the standard set of ancestral and health-related data for the competitive price of $60 (compared to $79 or $199 for Ancestry.com or 23andMe, companies that also provide ancestry information based on DNA sequencing).
One of the most innovative features of Gencove is its interface. In addition to its simplicity and ease of use, the platform gives users the ability to upload and analyze genomic data from any file format. This means participants can compare data they’ve generated using other companies, which may be in any of 40 unique formats, with the sequences generated by Gencove. In fact, people with genomic data can upload it and analyze it using Gencove’s API even without using Gencove’s sequencing services, giving users the ability to get more information from their existing data.
The free and open-source API is also a benefit for researchers interested in searching for unique associations of characteristics with a particular genotype or DNA sequence. Researchers interested in finding, for example, a gene associated with the ability to smell roses, have previously either had to build their own research project from the sequence up, or to partner with a genome-sequencing company, taking time and money for data licensing. Now, using genomes from consenting participants (Kaja is very clear that each research project will require user consent for their de-identified sequences to be used), researchers can build algorithms asking their particular research questions, be it trivial like scent detection or more substantial, such as finding rare genetic diseases.
This last question is one that drives Kaja and the Gencove team – the search for a better understanding of genetic diseases. Only a handful of diseases are associated with genetic inheritance. The power of Gencove is in its aggregation of all sorts of genomic data onto one platform, giving researchers many, many more sequences to interrogate. “We think that those large cohort studies will help us find people with very low-frequency mutations, such as rare, one-in-400-million cases,” Kaja says. “We hope that as the data set grows bigger and bigger, we’ll be able to find those.”
The search for rare mutations is helped by the technique Gencove is using: using low-coverage whole-genome sequencing (WGS), which opens up parts of the genome that haven’t been studied using the single-nucleotide-polymorphism (SNP) arrays employed by other genomic companies. Low-coverage WGS means that Gencove sequences 10-20% of a participant’s genome at random and imputes the rest using sequences from existing databases. Genetic imputation (using algorithms to find the unread DNA sequences most likely to be associated with the sequenced regions) increases the power and resolution of low-coverage WGS and increases prediction accuracy, providing information about the entire genome with extremely high probability of accuracy.
Gencove is also working to increase genomic representation within their database, which will further enrich their data. “A lot of genomics research has been done on white Europeans – it’s just not very diverse,” says Kaja. One of Gencove’s partnerships is with an Indian sequencing company: “Today, we have basically the most accurate reference genomes for an Indian population,” she says. Increasing database diversity may help pinpoint inherited diseases that are more prevalent in non-European genetic backgrounds.
Kaja welcomes partnerships with those who want to gather a large number of people and sequence them from scratch be they individuals, academics, startups, or pharma companies. These projects will not only answer specific research questions, but also add to the growing data that can serve as a resource for those whose projects may involve a new algorithm looking for associations.
The OT-One S is the first stop in Gencove’s automated pipeline. The OT-One S pipettes saliva samples out of the spit-tubes customers send into a 96 well plate to be further processed downstream. The pipeline also uses a Formulatrix Mantis for plate filling and an Agilent Bravo for parallel NGS library prep.
For Kaja, part of the appeal of the Opentrons OT-One is its affordability. “It’s shocking how expensive lab automation is,” she says. “For a robot that does what the OT-One does, I was quoted $200,000-350,000 dollars. When we’re a start-up of three people, I can’t invest in something that expensive. Opentrons gave us the opportunity to be accurate and predictable without the huge price tag.”
Back at the New York Genome Center (before Gencove started), Kaja was testing out her low-coverage sequencing protocol on friend and family volunteers. When using a hand-held pipette it’s really easy to make an error. “I tested my husband’s dad and his results suggested that he was unrelated to my husband, and my Nigerian friend’s ancestry was Northern European – so I immediately knew that I messed up. All this made me realize that we have to eliminate the human component from the process!” Since the protocol has been fully developed and automated, nothing like that has ever happened.
Gencove has also found the flexibility of the Opentrons platform to be important. Other platforms were more rigid, and Kaja found it difficult to automate the saliva extraction protocol – something her beta testing had demonstrated would be important for sample integrity. “You can make Opentrons do anything you want!” says Kaja. With a few programming changes, Gencove was able to manipulate the sample handling and movement exactly as their protocol needed.
Kaja is an Opentrons enthusiast and has been encouraging other friends with start-up companies to try the affordable, efficient robot that Gencove is using. Integration of the Opentrons and Gencove technologies has been a big step toward the open-source, accessible biotech that sits at the foundational core of both companies. Says Kaja: “We love Opentrons!”