Ambry Genetics launches StemArray for high resolution characterization of human stem cells

11 February 2010

Ambry Genetics has introduced their new StemArray product and services utilizing aCGH technology to cover the entire genome. The Ambry StemArray offers a higher resolution approach to standard karyotyping for stem cells at comparable costs.

The 44K array offers increased coverage in known stem cell and cancer associated genes to further enhance the resolution in these functionally important regions.

"The StemArray is the solution for stem cell scientists that are working with Human embryonic stem cells and induced pluripotent stem cells in order to detect genomic abnormalities found in stem cells that would be missed by low resolution karyotyping," said Ardy Arianpour, Ambry’s Director of Business Development.

"We are offering the StemArray at a comparable cost to traditional karyotyping and strongly believe that the product and our service will help scientists with new discoveries within this market.”

Human embryonic stem (hES) cells and induced pluripotent stem (iPS) cells that are cultured for an extended period of time are susceptible to chromosomal instability, which is a big concern for researchers.

Currently, stem cells have been characterized mainly through traditional low-resolution karyotypic analyses, which can only identify large scale aneuploidies over 5 MB in size. The Ambry StemArray has an average resolution of 43KB throughout the genome and 24KB in RefSeq genes. Resolution is even further enhanced, to the exonic level, in stem cells and cancer related genes.

“As human stem cells begin to make their way into clinical studies, it is essential that the cell lines be thoroughly characterized, added Dr. Aaron Elliott, Ambry’s R&D Scientist, Genomics. Using the StemArray scientists will not only detect the extremely large copy number changes that can be found by karyotype, but also identify very small aberrations that occur during culture that could decrease the reproducibility and reliability of experimental data.”

 

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