Open Access Highly Accessed Methodology article

Performance of high-throughput DNA quantification methods

Kashif A Haque1*, Ruth M Pfeiffer2, Michael B Beerman1, Jeff P Struewing3, Stephen J Chanock4 and Andrew W Bergen5

Author Affiliations

1 Core Genotyping Facility, SAIC-Frederick, Inc., National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA

2 Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA

3 Laboratory of Population Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA

4 Section on Genomic Variation, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20879, USA

5 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA

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BMC Biotechnology 2003, 3:20  doi:10.1186/1472-6750-3-20

Published: 28 October 2003

Abstract

Background

The accuracy and precision of estimates of DNA concentration are critical factors for efficient use of DNA samples in high-throughput genotype and sequence analyses. We evaluated the performance of spectrophotometric (OD) DNA quantification, and compared it to two fluorometric quantification methods, the PicoGreen® assay (PG), and a novel real-time quantitative genomic PCR assay (QG) specific to a region at the human BRCA1 locus. Twenty-Two lymphoblastoid cell line DNA samples with an initial concentration of ~350 ng/uL were diluted to 20 ng/uL. DNA concentration was estimated by OD and further diluted to 5 ng/uL. The concentrations of multiple aliquots of the final dilution were measured by the OD, QG and PG methods. The effects of manual and robotic laboratory sample handling procedures on the estimates of DNA concentration were assessed using variance components analyses.

Results

The OD method was the DNA quantification method most concordant with the reference sample among the three methods evaluated. A large fraction of the total variance for all three methods (36.0–95.7%) was explained by sample-to-sample variation, whereas the amount of variance attributable to sample handling was small (0.8–17.5%). Residual error (3.2–59.4%), corresponding to un-modelled factors, contributed a greater extent to the total variation than the sample handling procedures.

Conclusion

The application of a specific DNA quantification method to a particular molecular genetic laboratory protocol must take into account the accuracy and precision of the specific method, as well as the requirements of the experimental workflow with respect to sample volumes and throughput. While OD was the most concordant and precise DNA quantification method in this study, the information provided by the quantitative PCR assay regarding the suitability of DNA samples for PCR may be an essential factor for some protocols, despite the decreased concordance and precision of this method.