Meta-analysis of Diurnal Transcriptomics in Mouse Liver Reveals Low Repeatability of Rhythm Analyses.
Thomas G BrooksAditi ManjrekarAntonijo MrcˇelaGregory R GrantPublished in: Journal of biological rhythms (2023)
To assess the consistency of biological rhythms across studies, 57 public mouse liver tissue timeseries totaling 1096 RNA-seq samples were obtained and analyzed. Only the control groups of each study were included, to create comparable data. Technical factors in RNA-seq library preparation were the largest contributors to transcriptome-level differences, beyond biological or experiment-specific factors such as lighting conditions. Core clock genes were remarkably consistent in phase across all studies. Overlap of genes identified as rhythmic across studies was generally low, with no pair of studies having over 60% overlap. Distributions of phases of significant genes were remarkably inconsistent across studies, but the genes that consistently identified as rhythmic had acrophase clustering near ZT0 and ZT12. Despite the discrepancies between single-study analyses, cross-study analyses found substantial consistency. Running compareRhythms on each pair of studies identified a median of only 11% of the identified rhythmic genes as rhythmic in only 1 of the 2 studies. Data were integrated across studies in a joint and individual variance estimate (JIVE) analysis, which showed that the top 2 components of joint within-study variation are determined by time of day. A shape-invariant model with random effects was fit to the genes to identify the underlying shape of the rhythms, consistent across all studies, including identifying 72 genes with consistently multiple peaks.
Keyphrases
- rna seq
- case control
- single cell
- genome wide
- systematic review
- healthcare
- genome wide identification
- emergency department
- dna methylation
- blood pressure
- randomized controlled trial
- atrial fibrillation
- machine learning
- mass spectrometry
- big data
- artificial intelligence
- meta analyses
- high intensity
- molecularly imprinted
- data analysis
- drug induced
- adverse drug