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Real-time relative qPCR without reference to control samples and estimation of run-specific PCR parameters from run-internal mini-standard curves.

Bernth Jensen JM, Petersen MS, Stegger M, Østergaard LJ, Møller BK - PLoS ONE (2010)

Bottom Line: In this study, we compared RIMS-based drqPCR with classical quantifications based on external standard curves and the "comparative Ct method".Compared with classical approaches, we found that RIMS-based drqPCR provided superior precision and comparable accuracy.Also, lab-to-lab comparability can be greatly simplified.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Immunology, University Hospital of Aarhus, Skejby, Denmark. jejensen@rm.dk

ABSTRACT

Background: Real-Time quantitative PCR is an important tool in research and clinical settings. Here, we describe two new approaches that broaden the scope of real-time quantitative PCR; namely, run-internal mini standard curves (RIMS) and direct real-time relative quantitative PCR (drqPCR). RIMS are an efficient alternative to traditional standard curves and provide both run-specific and target-specific estimates of PCR parameters. The drqPCR enables direct estimation of target ratios without reference to conventional control samples.

Methodology/principal findings: In this study, we compared RIMS-based drqPCR with classical quantifications based on external standard curves and the "comparative Ct method". Specifically, we used a raw real-time PCR dataset as the basis for more than two-and-a-half million simulated quantifications with various user-defined conditions. Compared with classical approaches, we found that RIMS-based drqPCR provided superior precision and comparable accuracy.

Conclusions/significance: The obviation of referencing to control samples is attractive whenever unpaired samples are quantified. This may be in clinical and research settings; for instance, studies on chimerism, TREC quantifications, copy number variations etc. Also, lab-to-lab comparability can be greatly simplified.

Show MeSH
Comparison of the quantitative precision of drqPCR based on RIMS, external standard curves, or the 2ΔΔCq-approach.Illustration of the precision of drqPCR (SD (LOG (Ris,Norm))) based on the 2ΔΔCq-approach (black bars), external standard curves (dark grey bars), and RIMS (exemplified by C = 105 and RIMS samples analyzed in duplicates). RIMS parameters were used in single-ratio drqPCR (horizontal broken, black line) and double-ratio drqPCR (white bars). External standard curve-based and 2ΔΔCq-based drqPCR where by the double-ratio approach only. As control sample data, we used the run-internal, identical-sample-position Cqs of ERV1 and TUPLE1. The remaining run-internal combinations of ERV1 and TUPLE1 for a given control sample pair were treated as interest samples. The number of quantifications was 61,236 (27·28·3) for the 2ΔΔCq-approach and 244,944 (272·28·3·4) for use of external standard curves. The LOG (Ris)s of the conventional approaches were normalized as those determined by RIMS-based drqPCR (Figure 2, legend). Asterisk and crosses indicates significantly (p<0.001) better precision in quantification based on single-ratios and double-ratios compared to conventional approaches, respectively. The § at X = 0 indicates the only X-value where external standard curves offered significantly better precision than single-ratio-based drqPCR.
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pone-0011723-g004: Comparison of the quantitative precision of drqPCR based on RIMS, external standard curves, or the 2ΔΔCq-approach.Illustration of the precision of drqPCR (SD (LOG (Ris,Norm))) based on the 2ΔΔCq-approach (black bars), external standard curves (dark grey bars), and RIMS (exemplified by C = 105 and RIMS samples analyzed in duplicates). RIMS parameters were used in single-ratio drqPCR (horizontal broken, black line) and double-ratio drqPCR (white bars). External standard curve-based and 2ΔΔCq-based drqPCR where by the double-ratio approach only. As control sample data, we used the run-internal, identical-sample-position Cqs of ERV1 and TUPLE1. The remaining run-internal combinations of ERV1 and TUPLE1 for a given control sample pair were treated as interest samples. The number of quantifications was 61,236 (27·28·3) for the 2ΔΔCq-approach and 244,944 (272·28·3·4) for use of external standard curves. The LOG (Ris)s of the conventional approaches were normalized as those determined by RIMS-based drqPCR (Figure 2, legend). Asterisk and crosses indicates significantly (p<0.001) better precision in quantification based on single-ratios and double-ratios compared to conventional approaches, respectively. The § at X = 0 indicates the only X-value where external standard curves offered significantly better precision than single-ratio-based drqPCR.

Mentions: The data of the six 28-samplestandard curves were used to generate 61,236 and 244,944 different quantifications by the 2ΔΔCq-approach and based on external standard curves, respectively. Quantifications were based on Eq. I.4. Control samples containing ERV1 and TUPLE1 in equal concentrations were used. Results were normalized by the theoretical ratio and compared with those obtained from RIMS based single- and double-ratio (Figure 4). RIMS based drqPCR offered potential for significantly better precision, regardless of X-size. The accuracy of the conventional approaches was overall within ±3% but ±7% if data were split according to the used standard curves.


Real-time relative qPCR without reference to control samples and estimation of run-specific PCR parameters from run-internal mini-standard curves.

Bernth Jensen JM, Petersen MS, Stegger M, Østergaard LJ, Møller BK - PLoS ONE (2010)

Comparison of the quantitative precision of drqPCR based on RIMS, external standard curves, or the 2ΔΔCq-approach.Illustration of the precision of drqPCR (SD (LOG (Ris,Norm))) based on the 2ΔΔCq-approach (black bars), external standard curves (dark grey bars), and RIMS (exemplified by C = 105 and RIMS samples analyzed in duplicates). RIMS parameters were used in single-ratio drqPCR (horizontal broken, black line) and double-ratio drqPCR (white bars). External standard curve-based and 2ΔΔCq-based drqPCR where by the double-ratio approach only. As control sample data, we used the run-internal, identical-sample-position Cqs of ERV1 and TUPLE1. The remaining run-internal combinations of ERV1 and TUPLE1 for a given control sample pair were treated as interest samples. The number of quantifications was 61,236 (27·28·3) for the 2ΔΔCq-approach and 244,944 (272·28·3·4) for use of external standard curves. The LOG (Ris)s of the conventional approaches were normalized as those determined by RIMS-based drqPCR (Figure 2, legend). Asterisk and crosses indicates significantly (p<0.001) better precision in quantification based on single-ratios and double-ratios compared to conventional approaches, respectively. The § at X = 0 indicates the only X-value where external standard curves offered significantly better precision than single-ratio-based drqPCR.
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Related In: Results  -  Collection

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pone-0011723-g004: Comparison of the quantitative precision of drqPCR based on RIMS, external standard curves, or the 2ΔΔCq-approach.Illustration of the precision of drqPCR (SD (LOG (Ris,Norm))) based on the 2ΔΔCq-approach (black bars), external standard curves (dark grey bars), and RIMS (exemplified by C = 105 and RIMS samples analyzed in duplicates). RIMS parameters were used in single-ratio drqPCR (horizontal broken, black line) and double-ratio drqPCR (white bars). External standard curve-based and 2ΔΔCq-based drqPCR where by the double-ratio approach only. As control sample data, we used the run-internal, identical-sample-position Cqs of ERV1 and TUPLE1. The remaining run-internal combinations of ERV1 and TUPLE1 for a given control sample pair were treated as interest samples. The number of quantifications was 61,236 (27·28·3) for the 2ΔΔCq-approach and 244,944 (272·28·3·4) for use of external standard curves. The LOG (Ris)s of the conventional approaches were normalized as those determined by RIMS-based drqPCR (Figure 2, legend). Asterisk and crosses indicates significantly (p<0.001) better precision in quantification based on single-ratios and double-ratios compared to conventional approaches, respectively. The § at X = 0 indicates the only X-value where external standard curves offered significantly better precision than single-ratio-based drqPCR.
Mentions: The data of the six 28-samplestandard curves were used to generate 61,236 and 244,944 different quantifications by the 2ΔΔCq-approach and based on external standard curves, respectively. Quantifications were based on Eq. I.4. Control samples containing ERV1 and TUPLE1 in equal concentrations were used. Results were normalized by the theoretical ratio and compared with those obtained from RIMS based single- and double-ratio (Figure 4). RIMS based drqPCR offered potential for significantly better precision, regardless of X-size. The accuracy of the conventional approaches was overall within ±3% but ±7% if data were split according to the used standard curves.

Bottom Line: In this study, we compared RIMS-based drqPCR with classical quantifications based on external standard curves and the "comparative Ct method".Compared with classical approaches, we found that RIMS-based drqPCR provided superior precision and comparable accuracy.Also, lab-to-lab comparability can be greatly simplified.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Immunology, University Hospital of Aarhus, Skejby, Denmark. jejensen@rm.dk

ABSTRACT

Background: Real-Time quantitative PCR is an important tool in research and clinical settings. Here, we describe two new approaches that broaden the scope of real-time quantitative PCR; namely, run-internal mini standard curves (RIMS) and direct real-time relative quantitative PCR (drqPCR). RIMS are an efficient alternative to traditional standard curves and provide both run-specific and target-specific estimates of PCR parameters. The drqPCR enables direct estimation of target ratios without reference to conventional control samples.

Methodology/principal findings: In this study, we compared RIMS-based drqPCR with classical quantifications based on external standard curves and the "comparative Ct method". Specifically, we used a raw real-time PCR dataset as the basis for more than two-and-a-half million simulated quantifications with various user-defined conditions. Compared with classical approaches, we found that RIMS-based drqPCR provided superior precision and comparable accuracy.

Conclusions/significance: The obviation of referencing to control samples is attractive whenever unpaired samples are quantified. This may be in clinical and research settings; for instance, studies on chimerism, TREC quantifications, copy number variations etc. Also, lab-to-lab comparability can be greatly simplified.

Show MeSH