Previously, genomic approaches to transcriptional regulation have mainly focused on establishing connections between TFs and their targets, for example, by systematic ChIP-chip, TF deletion/overexpression profiling (Harbison et al, 2004
; Chua et al, 2006
; Hu et al, 2007
), or by in vitro
characterization of the DNA-binding profile of TFs (Badis et al, 2008
; Berger and Bulyk, 2009
). Quantitative genetic data provide complementary information as they describe functional relationships among TFs. A challenging task is to systematically reconstruct the regulatory circuits, inferring both connections and the input/output relationships. Given that the cellular regulatory networks could be quite complex due to possible regulatory cascades, the involvement of both activators and repressors, and the possibilities of various types of input/output relationships with multiple inputs, it is likely that more than one model will be consistent with the observed genetic interaction patterns. Thus, it is important to integrate other sources of information, such as the wiring diagrams and prior knowledge of the functions and regulation of the proteins involved, and to impose physical constraints on what can be implemented at the molecular level. We have demonstrated that this integrated approach enables us to explore the principles of global and local organization of the transcriptional apparatus in budding yeast. In particular, we have illustrated this approach by analyzing pairs of STFs that co-regulate the same sets of genes.
One intriguing observation from this study is that STF pairs sharing regulatory targets predominantly exhibit negative genetic interaction, and gene expression profiling of the TF mutants indicate that quite often such pairs regulate their target genes in a redundant manner. Could this be a general principle of regulatory design? Although we have grown yeast in only one set of conditions, there is no particular reason to believe that additional genetic interactions observed in different environmental conditions would alter the balance of the types of regulatory logic that are observed. Previous studies on the evolution of transcriptional circuits suggest that transition through an intermediate with redundant regulation may be a general mechanism to achieve large-scale rewiring without having to cross huge fitness barriers (Tanay et al, 2005
; Tsong et al, 2006
). Genome-wide analysis of the binding site patterns in yeast promoters also provides evidence that novel binding sites tend to appear in specific promoters that are already associated with multiple sites (Bilu and Barkai, 2005
), consistent with the interpretation that redundant regulation through multiple sites makes the promoter more evolvable.
Although ChIP-chip analyses had been used to infer regulatory hierarchies for the STFs of S. cerevisiae
(Lee et al, 2002
; Harbison et al, 2004
), such cascades appeared to have a relatively minor effect in cell growth under the condition we studied. We have systematically analyzed STF pairs with a regulator-target relationship (STF1 directly regulates STF2, derived from previously reported target predictions (MacIsaac et al, 2006
) using ChIP-chip data (Harbison et al, 2004
)) and found no enrichment of either positive or negative genetic interactions (see Supplementary Table 9
; Supplementary Figure 4
). Microarray analyses of gene expression in STF-deletion strains (Hu et al, 2007
) also indicated that regulation through extended cascades involving STFs may be relatively rare.
Certain global network features of this transcription factor E-MAP, such as overall interaction density and the ratio of positive-to-negative interactions, are significantly different from those observed in previous E-MAPs (Schuldiner et al, 2005
; Collins et al, 2007
; Fiedler et al, 2009
). For example, we have recently carried out a genetic study of the signaling apparatus (i.e. kinases/phosphatases) and observe the opposite trend we see with the STFs, that is an enrichment of positive over negative genetic interactions (Fiedler et al, 2009
). Based on this, we argue that, unlike STFs, enzymes that regulate phosphorylation more often function in linear pathways or in a coordinated manner. Although negative genetic interactions are often observed with factors working in the same pathway when it is essential in nature (Wilmes et al, 2008
), the majority of kinases, phosphatases, and TFs are non-essential, suggesting our interpretations are appropriate. It will be of great interest to determine whether the striking difference in the genetic architecture within the signaling apparatus and the transcriptional machinery is evolutionarily conserved and to fully characterize the genetic relationship between these two unique sets of genes. Comparison of different E-MAPs suggests that functionally distinct subnetworks are subject to alternative regulatory arrangements that best serve their purpose in the cell. For example, the cell cycle apparatus is largely responsible for ensuring that conditions are favorable for the cell to progress through successive steps of the cell division cycle. Thus, go/no-go decision points (checkpoints) largely define a linear sequence of events. Such an arrangement would be expected to result in increased occurrence of positive epistatic interactions, because these reflect shared linear pathways or protein complexes operating within the same pathway. Transcriptional responses, in contrast, are more likely to be modified by external environmental conditions, with different STFs driving gene expression in different directions that all contribute to the cell's fitness, a situation expected to result in increased numbers of negative epistatic interactions among STFs, just as we observed in this study.
These observations may be especially apparent among budding yeast STFs, because these organisms need to respond sensitively and rapidly to changing nutritional conditions (e.g. between oxidative and fermentative metabolism) (Johnston, 1999
). The map of epistatic interactions we generated should not be static: within a single organism, the nature (magnitude and polarity) of the genetic interactions should be dependent on the particular environmental conditions. Furthermore, other organisms may show different patterns of epistatic interaction among their STFs, as transcription network rewiring is a quite general phenomenon (Tuch et al, 2008
). Indeed, our preliminary comparative analysis between S. cerevisiae
and an evolutionary distinct yeast species Schizosaccharomyces pombe
(Roguev et al, 2008
; Beltrao et al, 2009
) indicates that GTF–GTF interactions are much more conserved than STF–STF interactions and, despite the changes, the general observation that STF pairs are more likely to interact negatively holds true for both species (unpublished data). Therefore, quantitative genetic profiling has considerable potential for the discovery of conserved/species-specific and environment-dependent interactions between genes and pathways. It will be very interesting and challenging to extend the E-MAP approach to metazoans, where sequence analyses indicate that functional enhancer elements often have clusters of binding sites of different TFs, which lead to the suggestion that cooperative binding of TFs are required for function. There, the pattern of genetic interaction may show a striking difference from what is observed in yeast.