Consequences of measurement error in qPCR telomere data: A simulation study

Abstract

The qPCR method provides an inexpensive, rapid method for estimating relative telomere length across a set of biological samples. Like all laboratory methods, it involves some degree of measurement error. The estimation of relative telomere length is done subjecting the actual measurements made (the Cq values for telomere and a control gene) to non-linear transformations and combining them into a ratio (the TS ratio). Here, we use computer simulations, supported by mathematical analysis, to explore how errors in measurement affect qPCR estimates of relative telomere length, both in cross-sectional and longitudinal data. We show that errors introduced at the level of Cq values are magnified when the TS ratio is calculated. If the errors at the Cq level are normally distributed and independent of true telomere length, those in the TS ratio are positively skewed and proportional to true telomere length. The repeatability of the TS ratio declines sharply with increasing error in measurement of the Cq values for telomere and/or control gene. In simulated longitudinal data, measurement error alone can produce a pattern of low correlation between successive measures of relative telomere length, coupled with a strong negative dependency of the rate of change on initial relative telomere length. Our results illustrate the importance of reducing measurement error: a small increase in error in Cq values can have large consequences for the power and interpretability of qPCR estimates of relative telomere length. The findings also illustrate the importance of characterising the measurement error in each dataset—coefficients of variation are generally unhelpful, and researchers should report standard deviations of Cq values and/or repeatabilities of TS ratios—and allowing for the known effects of measurement error when interpreting patterns of TS ratio change over time.

Methylation-Based Age Estimation in a Wild Mouse

“…For example, much past work on ageing in the wild has used telomere lengths as a marker of age (Belsky et al, 2017;Jylhävä et al, 2017). Whilst telomere attrition may differ between long and short-lived species (Foley et al, 2018), within species the relationship between telomere length and age appears weak (Belsky et al, 2017(Belsky et al, , 2017Fairlie et al, 2016;Foley et al, 2018;Jylhävä et al, 2017), and their use may be fraught with unresolved technical issues (Belsky et al, 2017;Nettle et al, 2019;Reichert et al, 2017). Telomere lengths may be good indicators of the state of an individual and thus predict mortality, but even this may be less accurate than what can be achieved with epigenetic clocks (Jylhävä et al, 2017).…”

Life-long telomere attrition predicts health and lifespan in a large mammal

“…DNA from whole blood samples was extracted with the DNeasy Blood and Tissue spin column kit (QIAGEN) and telomere length was measured by qPCR as previously described Seeker, Holland, Psifidi, Banos, & Nussey, 2015). The repeatability of the assay (see Supplementary File 2 for how repeatability was calculated) was 80% and therefore delivers robust results for further interpretation (Nettle, Seeker, Nussey, Froy, & Bateson, 2019). A full description of our DNA extraction and qPCR protocols including quality control steps can also be found in Supplementary File 2.…”

Standard guidelines for the publication of telomere qPCR results in evolutionary ecology

“…Finally, the best DNA amount for qPCR assays should be selected based on the dilutions that allowed the higher reaction precision, amplification efficiency and specificity. In the qPCR protocol for telomere measurement, samples are typically run in triplicate for both telomeres and single copy genes, with a maximal raw error standard deviation of 0.13 required for good reliability in a study with triplicate measurement (Nettle et al, 2019). Running samples in triplicate or even more takes into account the variability of the DNA amount added to reactions due to successive pipetting steps, which enables a carefully evaluation of the reaction precision for each sample.…”

“…If the parameter has never been evaluated and/or a particular species is being analysed for the first time, it is essential to evaluate the impact of these sources of variability. The standard deviation of the differences between Cq values recorded for each sample and/or repeatabilities of T/S ratios should be clearly reported to fully convey the magnitude and effect of measurement errors in the patterns of T/S ratio change over time (Nettle et al, 2019). Good technical and biological replicates are crucial for an accurate and reliable qPCR assay (Bustin et al, 2009;Goni, García, & Foissac, 2009).…”

“…Dozens of studies on telomere dynamics in a wide range of ecology and evolution topics have used qPCR approaches in the last decade (Table S1). The adoption of standard guidelines for experimental, analytical and reporting steps is crucial to ensure the reliability and validity of the qPCR telomere length assay (Martin-Ruiz et al, 2014;Nettle, Seeker, Nussey, Froy, & Bateson, 2019;Olsen, Bérubé, Robbins, & Palsbøll, 2012). Guidelines and recommendations for publication of qPCR results in general (Bustin et al, 2009), and for qPCR telomere assays in humans (Lin et al, 2019) were previously reported.…”