The Seed Biology Place

The Plant Cell 23: 2045-2063 (2011)

A Guideline to Family-wide Comparative State-of-the-art qRT-PCR Analysis Exemplified with a Brassicaceae Cross-species Seed Germination Case Study ^[W][OA]

Kai Graeber*, Ada Linkies*, Andrew T.A. Wood, Gerhard Leubner-Metzger
* Both authors contributed equally to this work

University of Freiburg, Faculty of Biology, Institute for Biology II, Botany / Plant Physiology, D-79104 Freiburg, Germany, Web: 'The Seed Biology Place' http://www.seedbiology.de (K.G., A.L., G.L.-M.)
The University of Nottingham, Division of Statistics, School of Mathematical Sciences, University Park, Nottingham NG7 2RD, United Kingdom (A.T.A.W.)

Received February 8, 2011; revised May 6, 2011; accepted May 27, 2011; published June 10, 2011.
www.plantcell.org/cgi/doi/10.1105/tpc.111.084103

Table 3. Factors Influencing PCR Efficiency as Determined by ANOVA F-Tests on Efficiencies Obtained from 687 qRT-PCR Reactions of Lepidium sativum.

Factor^a	Degrees of Freedom	F-value^b	Approximate Z-value^c	R^{2 d}	Adjusted R^{2 e}

Time	4	13.03	5.98	0.071	0.066
Tissue	2	67.92	9.57	0.166	0.163
Treatment	1	20.48	4.15	0.029	0.028
Sample	59	2.48	5.83	0.190	0.113
Replicate	14	10.00	9.29	0.172	0.155
Gene	11	90.75	24.72	0.597	0.590

^aDependence of PCR efficiency on different multi-level factors was tested. Corresponding to Figure 3 these factors are time in hours (0, 8, 18, 30, 96), tissue (CAP, RAD, CAP&RAD), treatment (CON, ABA), individual sample, biological replicates and the amplified gene. ^bF-values were obtained by testing the linear model for PCR efficiency with each factor included individually against the null model which includes the constant term only. ^cThe approximate Z-values were obtained by applying the Wilson-Hilferty cube-root normalising transformation to the F-values and then standardising, noting that because the denominator degrees of freedom is large in each case, the theoretical F distribution is effectively a scaled X² distribution. The approximate Z-values of different factors can be more directly compared than F-values. Larger Z-values indicate higher importance of a factor in explaining PCR efficiency variation. ^dR² is the square of the correlation between the observed PCR efficiency values and the fitted values under each model. A value close to 1 corresponds to a high level of agreement between the fitted model and the observed values. ^eAdjusted R² is defined in similar fashion to R²but tends to be smaller than R²when the model has a large number of parameters, as is the case with the factor Sample. The table shows that the amplified gene is by some way the most important factor in explaining PCR efficiency variation in our dataset. We have not reported p-values as all were very small (less than 10^-6 in all cases and less than 10^-16 in some cases) and therefore are not useful for comparing the importance of the different factors.

Synopsis: Developmental processes like seed germination are characterised by massive transcriptome changes. This study compares seed transcriptome datasets of different Brassicaceae to identify stable expressed reference genes for cross-species qRT-PCR normalisation. A workflow is presented for improving RNA quality, qRT-PCR performance, and normalisation when analysing expression changes across species.

Article in PDF format (1.2 MB)
Supplemental data file (156 KB)

Fig. 1
Fig. 6
Abstract

Fig. 2
Tab. 1
Fig. S1

Fig. 3
Tab. 2
Tab. S1

Fig. 4
Tab. 3
Tab. S2

Fig. 5
Tab. 4

Hyperlink to
Supplemental
Datasets 1 to 3

Webdesign Gerhard Leubner 2000
Best viewed with browser version 4 and 800x600 pixel
This page was last updated on 30 July, 2011

The Plant Cell 23: 2045-2063 (2011)

A Guideline to Family-wide Comparative State-of-the-art qRT-PCR Analysis Exemplified with a Brassicaceae Cross-species Seed Germination Case Study [W][OA]

A Guideline to Family-wide Comparative State-of-the-art qRT-PCR Analysis Exemplified with a Brassicaceae Cross-species Seed Germination Case Study ^[W][OA]