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Clinical Chemistry 53: 980-982, 2007. First published April 5, 2007; 10.1373/clinchem.2006.083691
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(Clinical Chemistry. 2007;53:980-982.)
© 2007 American Association for Clinical Chemistry, Inc.


Technical Briefs

Evaluation of a New Pooling Strategy Based on Leukocyte Count for Rapid Quantification of Allele Frequencies

Heidi Rossmann1,a, Elena Büchler1, Jürgen J. Wenzel1, Carolin Neukirch1, Jean-Baptist du Prel2 and Karl J. Lackner

1 Department of Clinical Chemistry and Laboratory Medicine and 2 Institute of Medical Biometry, Epidemiology, and Informatics (IMBEI), University of Mainz, Mainz, Germany

aAddress correspondence to this author at: University of Mainz, Langenbeckstr. 1, 55101 Mainz, Germany; fax 49-6131-17-6404; e-mail rossmann{at}zentrallabor.klinik.uni-mainz.de


Abstract

Background: Allele frequencies of single-nucleotide polymorphisms (SNPs) can be quantified from DNA pools. The conventional preparation of DNA pools requires DNA isolation and quantification for each blood sample. We hypothesized that pooling of whole blood samples according to their leukocyte count, which determines DNA content, would be as reliable as the conventional pooling method but much less tedious to perform.

Methods: We collected 100 whole blood samples and measured the leukocyte count. Samples were frozen until further use. After thawing, pools were generated by combining aliquots containing an equal number of leukocytes. In parallel, DNA was extracted from another aliquot, DNA concentration was measured, and DNA concentration-based pools were assembled. All original samples were genotyped directly using 4 different SNP assays to obtain the exact allele frequencies in the pool. In addition, samples of known genotypes were mixed according to the DNA concentration or the leukocyte count to generate artificial samples of known allele frequencies. We analyzed pools and mixes in triplicate by pyrosequencing and calculated allelic frequencies.

Results: Leukocyte and DNA pooling provided equally accurate and precise SNP frequencies comparable to published data.

Conclusion: DNA and leukocyte pooling are both suitable strategies to determine allele frequencies in frozen samples. The leukocyte pooling approach is much less tedious, quicker, and less expensive. It should be always considered if leukocyte counts are available.

The demand for simple and reliable methods to determine allele frequencies in many different populations is increasing. Allele quantification in DNA pools has been successfully used for this purpose. We hypothesized that pooling of whole blood according to the leukocyte count, which determines DNA content of the sample, may be a simple alternative to conventional pooling procedures. The major advantages are that only 1 DNA isolation is necessary from each blood pool and that hematology analyzers can generate leukocyte counts with high accuracy and precision. Therefore we compared a leukocyte count-based pooling strategy with conventional DNA-pooling.

Surplus whole blood from 100 complete blood counts ordered anonymously by the hospital staff occupational medicine service was collected and then stored at –20 °C until further use. The study design was in accordance with the guidelines of the local ethics committee. Leukocyte counts were measured with an Advia 120 instrument (Bayer Diagnostics). The imprecision (CV) in serial measurements was 2.41%.

We extracted DNA from 200 µL of each blood sample (QIAamp DNA Mini Kit, Qiagen) and analyzed genotypes by pyrosequencing for the following SNPs: lactase promoter polymorphisms (LCT) A(-22018)G and T(-13910)C, factor V Leiden (FV) (G1691A) polymorphism, and the prothrombin (F2; G20210A) gene mutation (see Figure 1 and Table 1 in the Data Supplement that accompanies the online version of this technical brief at http://www.clinchem.org/content/vol53/issue5). Finally, we calculated allele frequencies in the whole population.

To prepare DNA pools, DNA concentration was determined by a Nanodrop-System (NanoDrop Technologies). The median CV of triplicate measurements was 1.69%. An equivalent of 710 ng genomic DNA of each sample was used for pooling. Three DNA pools were prepared independently to control for pipetting errors.

For the leukocyte count based pools, we pipetted an equivalent of 710 400 leukocytes from the original, thawed, well-mixed whole blood sample into lysis buffer. Four independent leukocyte pools were assembled and DNA was extracted as described above.

Each pooled DNA was analyzed in triplicate by the pyrosequencing assays described above. The areas under the curves were determined, and the respective allele frequencies (given as percentage) for the analyzed SNPs were calculated by the instrument’s allele quantification software (Biotage). Because peaks caused by the dispensation of different nucleotides resulted in reproducible but not necessarily equal areas under the curve (see Fig. 1 in the online Data Supplement), calibration was required for all SNP assays. DNAs of known genotype were combined in the appropriate ratios to obtain suitable calibrators. These were analyzed in parallel with the pool samples. Calibration curves were linear (see Fig. 1A ) for each SNP assay with regression coefficients (Pearson’s correlation) r >0.997. Actual allele frequencies were deduced from the calibration curves. Results of the allele quantification experiments for DNA and leukocyte pools compared to direct genotyping results are shown in Table 1 .


Figure 1
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Figure 1. Allele quantification of the lactase promoter polymorphisms (LCT) A(-22018)G and T(-13910)C, the factor V Leiden (FV) (G1691A) polymorphism, and the prothrombin (F2; G20210A) gene mutation by pyrosequencing in DNA and leukocyte pools.

Because peaks caused by the dispensation of different nucleotides during pyrosequencing result in reproducible but not necessarily equal areas under the curve, calibration was required for all SNP assays. (A), calibration curves (determined allele frequencies plotted against expected allele frequencies) for exemplary SNP assays with regression coefficients and curve equations. (B), quantification of allele frequencies in DNA and leukocyte pools in comparison to the results of direct genotyping. For pool quantification experiments means are shown as hatched columns, single pool experiments are given as open boxes (numerical values: see Table 1Up ). (C), comparison between expected and determined allele frequencies <10% and >80%: two samples of known genotype were mixed (LCT T/C: sample 1 C/C, sample 2 T/C; FV sample 1 G/A, sample 2 G/G) based on the DNA concentration or the leukocyte count generating samples of known, gradually increasing allele frequencies. Single LCT T/C and FV experiments (open boxes) are visualized in scatter diagrams with 95% prediction and regression coefficient (Pearson’s correlation). Moreover, mean values are shown as filled boxes (numerical values: see Table 2 in the online Data Supplement).


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Table 1. Numeric data for allele quantification in DNA and leukocyte pools.

To evaluate the correlation between expected and determined allele frequencies <10% and >80%, 2 samples of known genotypes were mixed based on DNA concentration and leukocyte count, generating samples of known, gradually increasing allele frequencies (mix experiments: Fig. 1CUp and Table 2 in the online Data Supplement).

All SNP assays used for this study are in routine use in our laboratory and were adequate for allele quantification without further optimization. Considering the correlation coefficients, pool quantification results, and published data (1)(2)(3)(4)(5), all evaluated SNP tests performed appropriately. Means of 3 pool/mix experiments, each measured in triplicate, showed in most cases a deviation of <1.35% (Table 1Up and Fig. 1Up ) compared to the respective target value.

Our data show that leukocyte-based pools are equivalent to DNA-based pools for determination of allele frequencies, but are much less time-consuming and costly. For this study, 100 DNA isolations were necessary for the DNA pooling approach, but only 4 were necessary for the 4 leukocyte pools. We performed 100 leukocyte counts with an automated analyzer capable of measuring 120 samples per hour; 100 DNA concentrations were measured with the Nanodrop system by 1 person for 3 to 4 h. A limitation of the leukocyte pooling approach is that no individual DNA samples are available for genotyping, a shortcoming that may necessitate individual DNA preparations at a later time point. It should be noted, however, that leukocyte pooling is advantageous even when individual DNA has been prepared, because it obviates the need for time-consuming, highly accurate measurement of DNA concentrations, which is not needed for most other purposes. In summary, we believe that leukocyte pooling should always be considered if SNP analysis from pooled DNA is planned.


Acknowledgments

Grant/funding support: This work was supported by the research and education funds of the University Clinic of Mainz.

Financial disclosures: None declared.


References

  1. Sham P, Bader JS, Craig I, O’Donovan M, Owen M. DNA pooling: a tool for large-scale association studies. [Review]. Nat Rev Genet 2002;3:862-871.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  2. Alderborn A, Kristofferson A, Hammerling U. Determination of single-nucleotide polymorphisms by real-time pyrophosphate DNA sequencing. Genome Res 2000;10:1249-1258.[Abstract/Free Full Text]
  3. Neve B, Froguel P, Corset L, Vaillant E, Vatin V, Boutin P. Rapid SNP allele frequency determination in genomic DNA pools by pyrosequencing. Biotechniques 2002;32:1138-1142.[Web of Science][Medline] [Order article via Infotrieve]
  4. Shifman S, Pisante-Shalom A, Yakir B, Darvasi A. Quantitative technologies for allele frequency estimation of SNPs in DNA pools. Mol Cell Probes 2002;16:429-434.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]
  5. Lavebratt C, Sengul S, Jansson M, Schalling M. Pyrosequencing-based SNP allele frequency estimation in DNA pools. Hum Mutat 2004;23:92-97.[CrossRef][Web of Science][Medline] [Order article via Infotrieve]



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