Microarray technology provides us with a powerful tool for monitoring transcriptional activities of cells under certain conditions. In an earlier report, we analysed the expression profiles of the three long-lived yeast strains ras2Δ, tor1Δ
mutants together with the wild type at one point after the diauxic shift, and identified several expression patterns common to all three long-lived strains (25
). The expression results are in agreement with not only the free radical theory (2
) but also the programmed longevity theory (7
). In this study, we performed the experiments to measure the gene expression profiles of the wild-type and the long-lived sch9Δ
mutant from 12 to 120 h. Our goal was to identify the modifications of cellular activities and biological pathways that accounted for the longevity of the sch9Δ
mutant. The success of the expression comparative analyses hinged on unbiased and accurate measurement of the mRNA abundances. A large fraction of genes were possibly differentially expressed in both strains. An appropriate data processing method needs to detect the expression differentiations while reducing random variation. We chose the reference–target pairs in three overlapped time windows (Supplementary Table S1
) for sub-array normalization and carried out summarization based on the recently developed three-factor PTR model.
It has been reported that the overall transcription level declines dramatically as yeast cells approach stationary phase in the YPD medium (40
). In the SDC medium, we did observe a substantial increase between 12 and 24 h and a substantial decline during the 48- to 60-h period in the wild type (C). The observation matched our earlier understanding of the diauxic shift and post-diauxic phase of wild-type cells in SDC medium (17
). In contrast, the global up- then down-regulation pattern was not observed in the sch9Δ
mutant (D). Since the TF and RNAP II activity can reflect the overall transcription to a great extent, we drew the median gene expression curves for gene sets: basal TFs (KEGG), transcriptional factor activity (GO) and RNAP II (GO) (Supplementary Figure S8
). Their expression patterns were in concert with the global expression changes (C).
A fraction of the genes accounting for the difference between the wild type and the sch9Δ
mutant encode MRPs or relate to the mitochondrial activity. After compiling over 1000 published microarrays, Ihmels et al.
) reported that expressions for MRPs and CRPs are uncorrelated (even weakly anti-correlated) in S. cerevisiae
while they are strongly correlated in Candida albicans
, which is another form of yeast that primarily grows aerobically (67
). They argued that the change of MRP gene expression in S. cerevisiae
is connected to the emergence of the capacity for rapid anaerobic growth. Further upstream sequence analysis confirmed that MRP and CRP genes are subject to different regulatory mechanisms in S. cerevisiae
). In this study, the different regulatory patterns of MRP and CRP genes were clearly observed in the wild type from the time-course expression profiles (A). However, the difference was almost lost in the sch9Δ
mutant (B). In other words, the deletion of SCH9
modified the transcription regulation of MRP genes during chronological ageing.
The aerobic metabolism of S. cerevisiae
takes place in the mitochondria and the majority of harmful ROS may be generated during this process (68
). ROS have been shown to be sufficient to induce apoptosis (69
) and accelerate yeast chronological ageing (17
). The change of MRP gene expressions suggested that in the sch9Δ
mutant, the mitochondria did not require additional activity during the PDS. The early down-regulation of gene sets related to electron transport, oxidative phosphorylation and TCA further suggested that there were changes of chemical reactions on the electron transport chain that could lead to the reduction of ROS generation, in agreement with our experimental results showing that sch9Δ
cells have less age-dependent increase of ROS-induced damage (21
). In addition, we also observed that the stress response genes were up-regulated by larger fold changes in the sch9Δ
mutant, which is in agreement with our recent data showing that the sch9Δ
cells have enhanced cellular protection against oxidative stress (70
). These findings suggest that the change in metabolic pathways together with the enhanced cellular protection through the regulation of stress resistance genes contribute to the longevity of the sch9Δ
The rRNA locus (rDNA) is a region of fluctuation because it is the primary site of repeated recombination (71
). Quantitatively, we defined the volatility score for each gene and found indeed that rRNA processing genes were volatile, especially in the sch9Δ
mutant. In contrast, the expressions of CRPs were more stable. One of the primary functions of Sch9 is to regulate ribosome biosynthesis (49
). In yeast, the production of cytosolic ribosome, including the synthesis of mature rRNA and ribosomal proteins, demands numerous resources (72
). Thus the regulation of ribosome synthesis is critical for the determination of growth rate and cell size (49
). In this time-course expression profiles, the gene expressions related to rRNA synthesis were more volatile than that of ribosomal proteins. This was particularly true in the sch9Δ
mutant and supports the hypothesis that the control of rRNA synthesis is the primary target of regulatory mechanisms, and the regulation of ribosomal protein synthesis is a consequence of rRNA production regulation (73
A portion of genes exhibited increased expression volatility in sch9Δ
while other genes were expressed stably. One explanation is that the volatile genes are directly and actively regulated in response to the environmental changes such as nutrition and stress. We identified three cis
-regulatory elements enriched in the most volatile genes in the sch9Δ
mutant. Among them, transcriptional activities via PAC and rRPE elements are involved in rRNA processing and RiBi (56
). In the sch9Δ
mutant, the expressions of the genes containing both PAC and rRPE motifs were co-expressed more tightly than the genes with rRPE only, and the positions of rRPE were much closer to the genes when they also contained the PAC element. Recently, Pbf1 and Pbf2 (also known as Dot6) were identified as PAC-binding factors (74
). Stb3 also has been discovered as one rRPE-binding protein, but it only binds to a small portion of rRPE-containing gene (61
). The verification of these binding factors in volatile genes and their regulations are under further investigation.
The discovery of the GRE motif in these volatile genes was particularly interesting. The known factor Azf1 binds to GRE, and its well-known target, CLN3, showed the similar volatile expression pattern as the rRNA processing genes in the sch9Δ mutant, which provided evidence that Azf1 binds to these volatile genes. We have conducted the lifespan assay of the azf1Δ mutant and the sch9Δazf1Δ double mutant. The experimental results indicate that phenotypes of the sch9Δ mutant including lifespan extension and cell size are associated with the regulation of Azf1.
Many studies supported the importance of rDNA in the ageing process. For example, ERCs are formed in the rDNA regions (55
). Some recent suggestions and discussions regarding the importance of rDNA to ageing can also be found in Kobayashi (71
). With the observation of the striking opposite expression differentiation over time between rRNA processing genes and electron transport, oxidative phosporylation and TCA, it is conceivable that in the non-dividing condition the up-regulation of aerobic respiration is counter-balanced by the down-regulation of rRNA synthesis and it is a possible way to protect the rDNA region from the ROS damage in the sch9Δ
Our comparative analyses of the time-course expression profiles of the sch9Δ mutant and the wild type indicated that the sch9Δ cells followed a different metabolic path during chronological ageing. We believe that the lack of SCH9 promotes entry into a longevity programme that extends the lifespan through metabolic changes and the activation of protective systems.