Kapa Biosystems has announced that Color Genomics has implemented Kapa’s high performance library construction reagents into its NGS workflow. The reagents provide a fully automatable, streamlined process, saving time and allowing Color to return results faster to healthcare providers. Color Genomics offers a clinical-grade, physician-ordered genetic test for 19 genes related to breast and ovarian cancer risk, including BRCA1 and BRCA2.
This laboratory-developed test 1 (LDT) is run in a CAP-accredited and CLIA-certified lab and costs a fraction of other NGS-based tests for hereditary cancer. After rigorous evaluation and validation, the company selected library construction kits from Kapa, which uses a proprietary directed-evolution platform to engineer enzymes for optimal performance in NGS sample preparation.
Color Genomics has implemented the KAPA2HyperPlus Kit, which eliminates mechanical shearing and performs enzymatic DNA fragmentation and library preparation in a single tube to save time and generate high-quality results — particularly from low-input and challenging samples.
“Our mission is to democratize access to high-quality genetic testing,” said Dianne Keen-Kim, PhD, FACMG, Lab Director at Color Genomics. “Combining the rapid library preparation technology developed by Kapa with Agilent’s robust Sure Select Target Enrichment technology has allowed our team to deliver reliable answers faster while meeting the very strict cost requirements that keep our test affordable.”
KAPA Hyper Plus Kits offer a unique combination of high-efficiency library construction and low amplification bias to improve the depth and uniformity of sequencing coverage. This enhances coverage across target regions and contributes to lower sequencing costs.
“We’re delighted that our innovative sample prep reagents were selected by Color Genomics,” said Maryke Appel, PhD., Technical Director at Kapa Biosystems. “Supporting customers like this is why our team is so dedicated to developing products that expand the pool of samples that can be processed with high and predictable success rates in shorter turnaround times.”