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Detecting somatic single nucleotide variations in single cells

20 Mar 2017
Detecting somatic single nucleotide variations in single cells

SingulOmics Corporation, a recently established genomic research and service company, announced today the publication of data validating the company's core mission of producing a new, high quality amplification method and computational pipeline for single cell sequencing.

The data demonstrate that the company's new system -- AccuSomatic Amplification for Single Cell Sequencing -- enables accurate detection of somatic single nucleotide variations (SNVs) in single cells not possible with any prior methods.

The data are presented in a paper published online on March 20, 2017 in Nature Methods.

While single cell sequencing holds great promise for studying genetic heterogeneity in cancer and normal tissues, existing methods suffer from multiple sources of artefacts that can result in more than 20,000 false somatic SNV calls per cell and >90% false positive results. 

According to the research data, this new amplification technique eliminates >99% of errors in somatic SNV calls while maintaining the same detection sensitivity.

"This is really a game changer for our research." says Jan Vijg, Ph.D., Chair, Department of Genetics, Albert Einstein College of Medicine and an investor and co-founder of SingulOmics. "We are interested in studying low, physiological levels of somatic SNVs and other mutations in single cells, but these were simply drowning in the high background we experienced with published protocols or commercially available systems."

"We are entering a single cell genomics era as the cost of human genome sequencing plummets. This new method allows researchers to unlock the full potential of single cell sequencing in cancer, drug development, and aging research and greatly expands the capability of researchers to explore the landscapes of somatic mutations in human and other organisms beyond the reach of other amplification techniques available to date."

Source: SingulOmics