BEAMing up for detection and quantification of rare sequence variants

Meng Li; Frank Diehl; Devin Dressman; Bert Vogelstein; Kenneth W. Kinzler

doi:10.1038/nmeth850

BEAMing up for detection and quantification of rare sequence variants

Meng Li, Frank Diehl, Devin Dressman, Bert Vogelstein, Kenneth W. Kinzler

School of Medicine

Research output: Contribution to journal › Article › peer-review

200 Scopus citations

Abstract

BEAMing allows the one-to-one conversion of a population of DNA fragments into a population of beads. We used rolling circle amplification to increase the number of copies bound to such beads by more than 100-fold. This allowed enumeration of mutant and wild-type sequences even when they were present at ratios less than 1:10,000 and was sensitive enough to directly quantify the error rate of DNA polymerases used for PCR.

Original language	English (US)
Pages (from-to)	95-97
Number of pages	3
Journal	Nature Methods
Volume	3
Issue number	2
DOIs	https://doi.org/10.1038/nmeth850
State	Published - Feb 2006

ASJC Scopus subject areas

Biotechnology
Biochemistry
Molecular Biology
Cell Biology

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10.1038/nmeth850

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title = "BEAMing up for detection and quantification of rare sequence variants",

abstract = "BEAMing allows the one-to-one conversion of a population of DNA fragments into a population of beads. We used rolling circle amplification to increase the number of copies bound to such beads by more than 100-fold. This allowed enumeration of mutant and wild-type sequences even when they were present at ratios less than 1:10,000 and was sensitive enough to directly quantify the error rate of DNA polymerases used for PCR.",

author = "Meng Li and Frank Diehl and Devin Dressman and Bert Vogelstein and Kinzler, {Kenneth W.}",

note = "Funding Information: We thank L. Meszler for the help with imaging, Y. He and S. Zhou for advice. This work was supported by the US National Colorectal Cancer Research Alliance, The Clayton Fund and National Institutes of Health grants CA43460, CA57345 and CA62924.",

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BEAMing up for detection and quantification of rare sequence variants

Abstract

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