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Pacific Biosciences, GeneDx, UW Collaborate on Google-Funded Study of WGS in Neonatal Care

NEW YORK – Pacific Biosciences and GeneDx said on Monday that they are collaborating with the University of Washington to study long-read, whole-genome sequencing-based diagnostics in neonatal care.

Under the collaboration, with funding from Google, the partners will study the capabilities of PacBio's HiFi long-read sequencing technology to increase diagnostic rates in pediatric patients with genetic conditions. GeneDx, formerly known as Sema4, will use PacBio's new Revio instrument to perform whole-genome sequencing and analysis of 350 samples, including from 120 sick newborns enrolled in the SeqFirst study at Seattle Children's Hospital. Sequencing of biological parents will be done as samples are available.

Researchers will explore whether novel variants underlie certain genetic conditions, especially those not detected with short-read sequencing, which will also be applied to the samples.

Google will develop informatics methods and provide an undisclosed amount of funding for certain aspects of the project, including reagents.

"For more than 20 years, we have pioneered the development of clinical diagnostics, with the goal of ending the diagnostic odyssey for patients with rare genetic diseases," said GeneDx CSO Gustavo Stolovitzky. "We are excited to bring together GeneDx with PacBio and the University of Washington to explore the potential of innovative methods such as long-read sequencing to improve our ability to deliver a precise genetic diagnosis for these young children."

PacBio is also involved with efforts for rare disease diagnostics and newborn sequencing in collaboration with Rady Children's; the University of California, Los AngelesBoston Children's HospitalChildren's Mercy Hospital; and the Care4Rare Canada Consortium.

PacBio has previously partnered with Google to implement the DeepConsensus deep learning method on the Revio system and to improve long-read whole-genome sequencing performance with the variant calling algorithm DeepVariant.

Last month, a paper in the Journal of the American Medical Association suggested that WGS outperformed targeted gene panels in diagnosing newborns with suspected genetic conditions.

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