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Assessing the utility of whole-genome amplified serum DNA for array-based high throughput genotyping.

Bucasas KL, Pandya GA, Pradhan S, Fleischmann RD, Peterson SN, Belmont JW - BMC Genet. (2009)

Bottom Line: Heterozygote dropouts explained the majority (>85% in technical replicates, 50% in paired genomic/serum samples) of discordant results.Genotyping performance on WGA serum DNA samples was improved by implementation of Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) algorithm but at the loss of many samples which failed to pass its quality threshold.We conclude that while it is possible to extract genomic DNA and subsequently perform whole-genome amplification from archived serum samples, WGA serum DNA did not perform well and appeared unsuitable for high-resolution genotyping on these arrays.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Immunology, Baylor College of Medicine, Houston, TX 77030, USA. lacuesta@bcm.edu

ABSTRACT

Background: Whole genome amplification (WGA) offers new possibilities for genome-wide association studies where limited DNA samples have been collected. This study provides a realistic and high-precision assessment of WGA DNA genotyping performance from 20-year old archived serum samples using the Affymetrix Genome-Wide Human SNP Array 6.0 (SNP6.0) platform.

Results: Whole-genome amplified (WGA) DNA samples from 45 archived serum replicates and 5 fresh sera paired with non-amplified genomic DNA were genotyped in duplicate. All genotyped samples passed the imposed QC thresholds for quantity and quality. In general, WGA serum DNA samples produced low call rates (45.00 +/- 2.69%), although reproducibility for successfully called markers was favorable (concordance = 95.61 +/- 4.39%). Heterozygote dropouts explained the majority (>85% in technical replicates, 50% in paired genomic/serum samples) of discordant results. Genotyping performance on WGA serum DNA samples was improved by implementation of Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) algorithm but at the loss of many samples which failed to pass its quality threshold. Poor genotype clustering was evident in the samples that failed the CRLMM confidence threshold.

Conclusions: We conclude that while it is possible to extract genomic DNA and subsequently perform whole-genome amplification from archived serum samples, WGA serum DNA did not perform well and appeared unsuitable for high-resolution genotyping on these arrays.

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Scattergram of call rates between serum technical replicates. Call rates between serum technical replicates were plotted against each other to assess consistency of performance of technical replicates on the SNP 6.0 genotyping platform.
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Figure 2: Scattergram of call rates between serum technical replicates. Call rates between serum technical replicates were plotted against each other to assess consistency of performance of technical replicates on the SNP 6.0 genotyping platform.

Mentions: To evaluate SNP 6.0 array genotyping efficiency on WGA serum DNA samples, we measured the proportion of SNPs with missing calls in the genotyped samples. Genomic DNA from peripheral whole blood paired with whole-genome amplified DNA from freshly isolated serum of 5 individuals were run on SNP 6.0 arrays as controls. Genotype data were inferred by implementing the Birdseed v2.0 algorithm at 0.1 confidence threshold in separate clusters of non-amplified and WGA DNA samples (see Additional File 1 and Additional File 2). Percent call rates from WGA serum DNA and genomic DNA are shown in Figure 1. Overall, WGA DNA samples from sera yielded significantly low call rates (mean +/- SD, 45.0 +/- 2.7%), which corresponded to 409,366 markers out of approximately 906,600 SNP markers represented on the SNP 6.0 array. In contrast to WGA serum DNA samples, non-amplified DNA samples from peripheral whole blood yielded excellent call rates, ranging from 96.9% to 99.5% (mean +/- SD, 98.0 +/- 1.1%). The average call rate of WGA DNA samples from archived sera (mean +/- SD, 44.6 +/2.7%) did not differ from WGA DNA samples from freshly isolated sera (mean +/- SD, 48.1 +/- 1.8%) (p = 6 × 10-5 ). Call rates between technical replicates were correlated (r2 = 0.71), thus demonstrating that high quality serum DNA samples consistently produce high genotyping call rates compared to samples with poor quality DNA(Figure 2).


Assessing the utility of whole-genome amplified serum DNA for array-based high throughput genotyping.

Bucasas KL, Pandya GA, Pradhan S, Fleischmann RD, Peterson SN, Belmont JW - BMC Genet. (2009)

Scattergram of call rates between serum technical replicates. Call rates between serum technical replicates were plotted against each other to assess consistency of performance of technical replicates on the SNP 6.0 genotyping platform.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2803178&req=5

Figure 2: Scattergram of call rates between serum technical replicates. Call rates between serum technical replicates were plotted against each other to assess consistency of performance of technical replicates on the SNP 6.0 genotyping platform.
Mentions: To evaluate SNP 6.0 array genotyping efficiency on WGA serum DNA samples, we measured the proportion of SNPs with missing calls in the genotyped samples. Genomic DNA from peripheral whole blood paired with whole-genome amplified DNA from freshly isolated serum of 5 individuals were run on SNP 6.0 arrays as controls. Genotype data were inferred by implementing the Birdseed v2.0 algorithm at 0.1 confidence threshold in separate clusters of non-amplified and WGA DNA samples (see Additional File 1 and Additional File 2). Percent call rates from WGA serum DNA and genomic DNA are shown in Figure 1. Overall, WGA DNA samples from sera yielded significantly low call rates (mean +/- SD, 45.0 +/- 2.7%), which corresponded to 409,366 markers out of approximately 906,600 SNP markers represented on the SNP 6.0 array. In contrast to WGA serum DNA samples, non-amplified DNA samples from peripheral whole blood yielded excellent call rates, ranging from 96.9% to 99.5% (mean +/- SD, 98.0 +/- 1.1%). The average call rate of WGA DNA samples from archived sera (mean +/- SD, 44.6 +/2.7%) did not differ from WGA DNA samples from freshly isolated sera (mean +/- SD, 48.1 +/- 1.8%) (p = 6 × 10-5 ). Call rates between technical replicates were correlated (r2 = 0.71), thus demonstrating that high quality serum DNA samples consistently produce high genotyping call rates compared to samples with poor quality DNA(Figure 2).

Bottom Line: Heterozygote dropouts explained the majority (>85% in technical replicates, 50% in paired genomic/serum samples) of discordant results.Genotyping performance on WGA serum DNA samples was improved by implementation of Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) algorithm but at the loss of many samples which failed to pass its quality threshold.We conclude that while it is possible to extract genomic DNA and subsequently perform whole-genome amplification from archived serum samples, WGA serum DNA did not perform well and appeared unsuitable for high-resolution genotyping on these arrays.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Immunology, Baylor College of Medicine, Houston, TX 77030, USA. lacuesta@bcm.edu

ABSTRACT

Background: Whole genome amplification (WGA) offers new possibilities for genome-wide association studies where limited DNA samples have been collected. This study provides a realistic and high-precision assessment of WGA DNA genotyping performance from 20-year old archived serum samples using the Affymetrix Genome-Wide Human SNP Array 6.0 (SNP6.0) platform.

Results: Whole-genome amplified (WGA) DNA samples from 45 archived serum replicates and 5 fresh sera paired with non-amplified genomic DNA were genotyped in duplicate. All genotyped samples passed the imposed QC thresholds for quantity and quality. In general, WGA serum DNA samples produced low call rates (45.00 +/- 2.69%), although reproducibility for successfully called markers was favorable (concordance = 95.61 +/- 4.39%). Heterozygote dropouts explained the majority (>85% in technical replicates, 50% in paired genomic/serum samples) of discordant results. Genotyping performance on WGA serum DNA samples was improved by implementation of Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) algorithm but at the loss of many samples which failed to pass its quality threshold. Poor genotype clustering was evident in the samples that failed the CRLMM confidence threshold.

Conclusions: We conclude that while it is possible to extract genomic DNA and subsequently perform whole-genome amplification from archived serum samples, WGA serum DNA did not perform well and appeared unsuitable for high-resolution genotyping on these arrays.

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