Meta-Analysis of Drosophila Circadian Microarray Studies Identifies a Novel Set of Rhythmically Expressed Genes

Abstract

Five independent groups have reported microarray studies that identify dozens of rhythmically expressed genes in the fruit fly Drosophila melanogaster. Limited overlap among the lists of discovered genes makes it difficult to determine which, if any, exhibit truly rhythmic patterns of expression. We reanalyzed data from all five reports and found two sources for the observed discrepancies, the use of different expression pattern detection algorithms and underlying variation among the datasets. To improve upon the methods originally employed, we developed a new analysis that involves compilation of all existing data, application of identical transformation and standardization procedures followed by ANOVA-based statistical prescreening, and three separate classes of post hoc analysis: cross-correlation to various cycling waveforms, autocorrelation, and a previously described fast Fourier transform–based technique [1–3]. Permutation-based statistical tests were used to derive significance measures for all post hoc tests. We find application of our method, most significantly the ANOVA prescreening procedure, significantly reduces the false discovery rate relative to that observed among the results of the original five reports while maintaining desirable statistical power. We identify a set of 81 cycling transcripts previously found in one or more of the original reports as well as a novel set of 133 transcripts not found in any of the original studies. We introduce a novel analysis method that compensates for variability observed among the original five Drosophila circadian array reports. Based on the statistical fidelity of our meta-analysis results, and the results of our initial validation experiments (quantitative RT-PCR), we predict many of our newly found genes to be bona fide cyclers, and suggest that they may lead to new insights into the pathways through which clock mechanisms regulate behavioral rhythms.

Deep sequencing the circadian and diurnal transcriptome of Drosophila brain

“…These studies individually discovered between several dozen and several hundred rhythmic transcripts, but outside of a restricted set of key genes underlying the circadian oscillator mechanism, there was surprisingly little agreement in the identities of these rhythmic transcripts (Jackson and Schroeder 2001;Etter and Ramaswami 2002;Duffield 2003). A variety of reasons likely underlie these differences, including methods of data condensation (Walker and Hogenesch 2005), statistical approaches for discovering rhythmic transcripts (Wijnen et al 2006;Keegan et al 2007), and time-point sampling density (Hughes et al 2007). To reconcile these differences, two meta-analyses have standardized data condensation and statistical analyses while leveraging the additional statistical power afforded by the consolidation of multiple data sets (Wijnen et al 2006;Keegan et al 2007).…”

“…A variety of reasons likely underlie these differences, including methods of data condensation (Walker and Hogenesch 2005), statistical approaches for discovering rhythmic transcripts (Wijnen et al 2006;Keegan et al 2007), and time-point sampling density (Hughes et al 2007). To reconcile these differences, two meta-analyses have standardized data condensation and statistical analyses while leveraging the additional statistical power afforded by the consolidation of multiple data sets (Wijnen et al 2006;Keegan et al 2007). Taken together, 45 genes (;60%) were found to be rhythmic by both meta-analyses, thus comprising a canonical set of circadian-regulated genes, many of which have been further validated by Northern blot analysis and quantitative PCR (qPCR) (Wijnen et al 2006;Keegan et al 2007).…”

“…To reconcile these differences, two meta-analyses have standardized data condensation and statistical analyses while leveraging the additional statistical power afforded by the consolidation of multiple data sets (Wijnen et al 2006;Keegan et al 2007). Taken together, 45 genes (;60%) were found to be rhythmic by both meta-analyses, thus comprising a canonical set of circadian-regulated genes, many of which have been further validated by Northern blot analysis and quantitative PCR (qPCR) (Wijnen et al 2006;Keegan et al 2007). Additionally, more than 100 transcripts were identified that show statistically significant oscillations in at least one of the two meta-analyses, providing a secondary list of high-confidence candidates for clock regulation.…”

Alternative Tasks of Drosophila Tan in Neurotransmitter Recycling Versus Cuticle Sclerotization Disclosed by Kinetic Properties

“…If Tan processing reveals the same stringent dependence on the GlyCys motif, activation of enzymatic activity might also depend on this process and maturation of activity might require a certain time period. In light of the reported circadian expression of tan this should shift the daily rise of activity (23).…”

A master CLOCK hard at work brings rhythm to the transcriptome: Figure 1.

“…This also revealed that, in general, the highest-amplitude circadian cyclers are clock transcripts and that many of the downstream ccgs have low amplitudes wherein their classification as bona fide circadian is more prone to differences in algorithms and/or slight variations in experimental conditions (e.g., Wijnen et al 2005;Keegan et al 2007). Thus, it appears that the transcriptional oscillatory potential generated within the core clock mechanism is somewhat dissipated for the majority of ccgs.…”