Collecting mouse livers for transcriptome analysis of daily rhythms

Developmental Programming: Impact of Prenatal Exposure to Bisphenol A on Senescence and Circadian Mediators in the Liver of Sheep

Prenatal exposure to endocrine disruptors such as bisphenol A (BPA) plays a critical role in the developmental programming of liver dysfunction that is characteristic of nonalcoholic fatty liver disease (NAFLD). Circadian and aging processes have been implicated in the pathogenesis of NAFLD. We hypothesized that the prenatal BPA-induced fatty-liver phenotype of female sheep is associated with premature hepatic senescence and disruption in circadian clock genes. The expression of circadian rhythm and aging-associated genes, along with other markers of senescence such as telomere length, mitochondrial DNA copy number, and lipofuscin accumulation, were evaluated in the liver tissue of control and prenatal BPA groups. Prenatal BPA exposure significantly elevated the expression of aging-associated genes GLB1 and CISD2 and induced large magnitude differences in the expression of other aging genes-APOE, HGF, KLOTHO, and the clock genes PER2 and CLOCK-in the liver; the other senescence markers remained unaffected. Prenatal BPA-programmed aging-related transcriptional changes in the liver may contribute to pathological changes in liver function, elucidating the involvement of aging genes in the pathogenesis of liver steatosis.

Meta-analysis of Diurnal Transcriptomics in Mouse Liver Reveals Low Repeatability of Rhythm Analyses

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.