Methods detecting rhythmic gene expression are biologically relevant only for strong signal

Details

Serval ID
serval:BIB_C090B1967D37
Type
Article: article from journal or magazin.
Collection
Publications
Title
Methods detecting rhythmic gene expression are biologically relevant only for strong signal
Journal
PLOS Computational Biology
Author(s)
Laloum David, Robinson-Rechavi Marc
Publication state
Published
Issued date
03/2020
Volume
16
Number
3
Pages
1-23
Language
english
Abstract
Author summary To be active, genes have to be transcribed to RNA. For some genes, the transcription rate follows a circadian rhythm with a periodicity of approximately 24 hours; we call these genes “rhythmic”. In this study, we compared methods designed to detect rhythmic genes in gene expression data. The data are measures of the number of RNA molecules for each gene, given at several time-points, usually spaced 2 to 4 hours, over one or several periods of 24 hours. There are many such methods, but it is not known which ones work best to detect genes whose rhythmic expression is biologically functional. We compared these methods using a reference group of evolutionarily conserved rhythmic genes. We compared data from baboon, mouse, rat, zebrafish, fly, and mosquitoes. Surprisingly, no method was particularly effective. Furthermore, we found that only very strong rhythmic signals were relevant with each method. More precisely, when we use a usual cut-off to define rhythmic genes, the group of genes considered as rhythmic contains many genes whose rhythmicity cannot be confirmed to be biologically relevant. We also show that rhythmic genes mainly contain highly expressed genes. Finally, based on our results, we provide recommendations on which methods to use and how, and suggestions for future experimental designs.
Open Access
Yes
Create date
23/04/2020 9:57
Last modification date
29/05/2020 6:19
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