Construction and phenotypic profiling of a transcriptional regulator knockout library
The list of candidate genes for inclusion in our transcriptional regulator knockout (TRKO) library was compiled from multiple sources (Dataset S1
). We defined transcriptional regulators as any protein that binds DNA in and around a gene and influences its transcription rate. We placed an emphasis on proteins with sequence-specific DNA binding domains, and did not include proteins that influence the transcription of most genes in the cell (e.g. histones, subunits of mediator, and the general transcription factors).
To create the TRKO strains, we utilized a fusion-PCR based approach 
that employs long stretches of flanking homology to maximize recombination (; see Materials and Methods
). C. albicans
is diploid, and the construction of each knockout strain thus required two rounds of gene disruption. Although not used in this study, signature tags were incorporated into each knockout strain to enable strains to be screened in groups. Because it is not straightforward to perform back-crosses with C. albicans 
(and thereby ensure that a given phenotype segregates with a gene disruption), we created two fully independent knockout strains for each TR. This strategy greatly increases the likelihood that a phenotype observed in both strain isolates resulted from the gene knockout rather than an unrelated mutation that arose during the gene disruption procedure. This is an important consideration, as we estimate that as many as 10% of gene knockouts have additional mutations that produce at least moderate phenotypes (see Text S2
). Our approach, coupled with the phenotypic screen described below, yielded high-quality TRKOs for 143 of the 184 TRs in our original list. To be classified as high-quality, two independently derived knockout strains must exhibit the same set of phenotypes. (In some cases, additional isolates were created to resolve inter-isolate inconsistencies.) An additional 23 TRKOs are included in our collection, but are classified as lower confidence. In some cases (11 TRKOs) only a single deletion strain was obtained, and in others (12 TRKOs), the independent isolates produced overlapping but distinct phenotypes. The combined collection containing the 143 high-confidence KOs and the 23 lower-confidence KOs contains 166 KOs, represented by 365 total strains. In the following discussions, we focus on the high-confidence TRKOs.
Overview of experimental design.
Phenotypic profiles for each TRKO were established by a large primary screen of 55 conditions augmented by a series of case-by-case supplemental screens (; Materials and Methods
). Phenotyping media were selected to probe a broad spectrum of regulatory networks. We used nutritional cues, temperature, signals that induce morphological changes, antifungal drugs, and a variety of stress conditions. When possible, drug/toxin/nutrient concentrations were calibrated such that both impairment and enhancement of growth relative to wild-type could be observed. A summary of the media utilized in this study, including commentary on their known properties (e.g. modes of action of drugs), is provided as supporting information (Text S1
In the primary screen, independent isolates of each TRKO were plated as 1× and 5× dilutions on a wide range of solid media using a bolt-replicator and then photographed several times over the course of growth. These images were processed and archived using custom Java software () and scored for growth and morphological phenotypes by comparison to a wild-type control strain included on the same plate. This approach generated over 100,000 individual growth and morphology scores, which were then merged – across time-points and across the knockout isolates of each TR – into single growth and morphology scores for each TRKO on each growth medium (Dataset S2
). The scoring system classified the strength of the reduction or enhancement of both growth and morphology relative to wild-type (see Text S2
and legend). Because we observed growth of all strains at two different dilutions and repeatedly over several days, we could easily score subtle phenotypes that might not have been apparent from a single concentration and time-point.
Phenotypes of C. albicans transcriptional regulator knockout strains.
We paid particular attention to colony morphology as a phenotype. On most solid media, colonies of C. albicans
are composed of three types of cells: budding yeast (round cells), pseudohyphae (strings of ellipsoidal cells that remain attached to one another following cell division), and hyphae (highly elongated cylindrical cells that remain attached following cell division). All three forms are also found in infected tissues, and the transition between these forms is key for normal pathogenesis (reviewed by Biswas et al. 
and Whiteway and Bachewich 
). Colony morphology serves as a sensitive assay for differences in the way cells regulate the transition between the three morphological forms. By observing the collection of TRKO mutants on a variety of media over time courses of several days, we were able to identify a broad spectrum of differences in colony morphology.
All images generated in this study will be made available via a Java application hosted by the Candida Genome Database (CGD) 
. We have also hand-annotated a phenotypic overview of each TRKO (Dataset S2
Identifying key associations between phenotype and regulator in a large dataset
The primary phenotypic screen identified at least one moderate phenotype for over 50% of the tested TRKOs and at least one strong phenotype for over 40% of the tested TRKOs. Many of these transcriptional regulators were completely uncharacterized, and this study presents the first direct experimental data relevant to their function.
The phenotypic profiles generated by the primary screen are provided in . The assay conditions have been separated into the broad categories of nutrition (), stress (), and morphology (), with the understanding that these categories do not have precisely defined boundaries. The color scale represents a range of phenotype strength from strong enhancement of growth or morphology (blue circles) to strong reduction of growth or morphology (red circles). In order to highlight phenotypes that are more likely to reflect a direct role of a given TR, we scaled the diameter of the circles to reflect a “specificity score”. A high specificity score (large diameter) indicates that the TR deletion shows a strong phenotype under the indicated condition and an overall low level of pleiotropy (i.e. few phenotypes overall) relative to the other TRKOs that exhibited a phenotype under the given growth condition. This approach thus deemphasizes a highly pleiotropic TRKO (small diameter) if other less pleiotropic TRKOs share the phenotype in question. The calculation of the specificity score (Text S2
) was conducted independently for enhancement and reduction phenotypes, and only strong phenotypes were considered.
A high specificity score (large diameter circle) serves as a visual marker for those TRs that are likely to control relatively small and discrete circuits. In other words, the TR is likely to regulate a small set of genes whose misregulation in the deletion mutant causes a restricted set of phenotypes. In contrast, a low specificity score could indicate that (1) the TR directly controls many genes involved in many different biological processes, (2) the regulator regulates one or more TRs with higher specificity scores, or (3) that the regulator directly controls a relatively small circuit but that disruption of the circuit causes many indirect phenotypes.
The TRKOs with high specificity scores and strong phenotypes form the basis of much of our analysis. In the following three sections, we discuss, through specific examples, general ways in which the phenotypic profiles can be applied to problems in C. albicans biology. Although we cite specific examples as support, we do so primarily to illustrate the generality of these approaches. These three sections are followed by a more focused discussion of the regulation of C. albicans morphology. We conclude with a discussion of the evolution of transcriptional circuits based on a comparison of biological roles of orthologous regulators in C. albicans and S. cerevisiae.
“Transposing” a well-studied transcription network from S. cerevisiae to C. albicans
is a particularly well-studied eukaryotic organism, and observations made in this species have often been used as the starting point for studies in C. albicans
. This approach has had mixed success; the failures often result from homologous proteins playing markedly different biological roles in the two species. Our results can help reveal the extent to which a transcriptional circuit worked out in detail in S. cerevisiae
is directly applicable to the understudied species C. albicans
. As an example, we discuss the collection of C. albicans
mutants that affected the TOR pathway, a critical regulator of cell growth (reviewed in 
When nutrients are abundant, the TOR pathway promotes cell growth and represses genes involved in the utilization of non-preferred nutrient sources. Conversely, when nutrients are limiting, the TOR pathway slows cell growth and redirects cellular resources to scavenge for nutrients. Although components of the TOR pathway are conserved across the eukaryotic lineage, the extent of TOR pathway conservation between C. albicans and S. cerevisiae was not known with certainty; nor was it known how additional features of C. albicans might be connected to the TOR signaling pathway.
The drugs rapamycin and caffeine both inhibit function of the Tor1 kinase 
, resulting in an artificial signal of cell starvation. In our primary screen, we assayed the deletion collection for sensitivity and resistance to caffeine to identify TRs connected to TOR function. We subsequently tested caffeine-sensitive and -resistant mutants with rapamycin and found a near-perfect correspondence (Dataset S2
, and see below), providing additional support for a growing consensus that the primary mechanism of action of caffeine is interference with TOR function rather than disruption of cAMP signaling 
. The screens identified 22 TRKOs with moderate or strong caffeine () and rapamycin (Dataset S2
A detailed analysis of these genes is provided in the supporting materials (Text S3
), and here we emphasize four points that emerged from the C. albicans
comparison. First, the core regulatory network governing TOR function is highly conserved between the two species. Specifically, orthologs of five of the six TRs known to interact with Tor1 in S. cerevisiae 
have strong caffeine and rapamycin phenotypes in C. albicans
(the sixth has no clear ortholog in C. albicans
; see Text S3
for details). Second, the caffeine screen identified eight additional regulators in C. albicans
that are homologous to regulators of nutritional pathways in S. cerevisiae
. These results support the prevailing model that Tor1 signaling is governed by a core regulatory network with additional regulators governing specific nutritional inputs and outputs; these additional regulators appear to be largely the same in C. albicans
and S. cerevisiae
. Third, five of the C. albicans
TRKOs with altered caffeine sensitivity also showed profound alterations in colony morphology, indicating an intimate connection between the TOR pathway and the large cell morphology network (see below). It has been previously reported that rapamycin can both inhibit hyphal formation on solid medium 
and promote flocculation and aggregation in liquid medium 
in C. albicans 
. Our results support this connection and further identify the transcriptional regulators likely to mediate it. Finally, although an excellent correspondence between caffeine and rapamycin phenotypes was observed, we did identify one mutant (ΔΔorf19.4166
) where this correspondence was lost: the mutant exhibits heightened sensitivity to caffeine, but not rapamycin (Dataset S2
). It is possible that this TR regulates genes influencing the import, export, or degradation of caffeine but not rapamycin. Alternatively, this TR may regulate a caffeine-specific cellular target.
In summary, comparing the S. cerevisiae TOR regulatory network with homologous regulators in C. albicans reveals a strong conserved core pathway that is closely connected to transcriptional circuits governing colony morphology. In general, this approach provides a rapid means of identifying core regulators in C. albicans, and in this case it indicates that most of the work on the TOR pathway in S. cerevisiae can be directly superimposed onto C. albicans.
Uncovering examples of circuit rewiring
Although the TOR pathway regulators exhibit a high degree of functional conservation between S. cerevisiae
and C. albicans
, there are multiple examples of C. albicans
homologs (and even orthologs) of S. cerevisiae
transcriptional regulators that have different biological roles in the two species 
. These case studies illustrate the danger in assigning biological roles to C. albicans
TRs based solely on homology arguments.
A comparison of the phenotypic data presented here with the extensive sets of data available for S. cerevisiae
can experimentally validate homology assignments (as for the TOR pathway discussed above); it can also reveal examples of rewiring of a regulatory circuit. As an example of the latter, we consider the regulatory networks governing iron acquisition. The sources and abundance of available iron vary greatly with microenvironment, and iron-acquisition and homeostasis is a special challenge for microorganisms such as C. albicans
that compete for iron in a mammalian host (reviewed by Sutak et al. 
In , we have integrated the data from our phenotypic screen with data from previous studies of iron acquisition in both S. cerevisiae
(reviewed by 
and also 
) and C. albicans 
to highlight differences in the regulation of iron acquisition and homeostasis between these two species. The data from the screen is based on three growth phenotypes associated with perturbation of iron homeostasis (). The first and most direct phenotype, sensitivity to the iron chelator bathophenanthroline disulfonate (BPS), likely reflects a defect in the iron acquisition circuitry. The second phenotype, sensitivity to elevated copper levels, is linked to iron homeostasis by virtue of the strong inter-connection between copper and iron homeostasis networks: copper is a critical cofactor for high affinity iron uptake 
. The final phenotype is sensitivity to alkaline pH. Studies in S. cerevisiae
have established that copper and iron become limiting nutrients in an alkaline growth environment 
A model of the differences in iron homeostasis regulation between S. cerevisiae and C. albicans.
The phenotypic analysis provides strong support for the idea that the iron acquisition circuit has undergone a major change in regulation since S. cerevisiae
and C. albicans
last shared a common ancestor. As shown in , the circuit is positively regulated by Aft1 in S. cerevisiae
and negatively regulated by Sfu1 in C. albicans
(see Text S4
). This is most easily seen by comparing the effects of a Sfu1 deletion in C. albicans
() with that of an Aft1 deletion in S. cerevisiae
). Incidentally, our results also add a new regulatory branch to the iron-acquisition model, one controlled by the transcriptional regulator SEF1
(). Sef1 was identified in our C. albicans
screen as a positive regulator of iron acquisition and, although it had not been previously reported, we found a similar role for the Sef1 from S. cerevisiae
Using phenotypic profiles to probe features of C. albicans directly applicable to medicine
As assays for specific aspects of C. albicans pathogenesis are developed and refined, new genetic screens can be carried out using our set of deletion strains. This strategy can provide an entry point into studying a particular problem. As an example, we consider the action of two antifungal drugs.
The primary screen included resistance and sensitivity to two antifungal agents, fluconazole and fenpropimorph, which block different steps of the ergosterol biosynthetic pathway 
. We identified 34 TRKO strains with enhanced or reduced sensitivities to these drugs, only five of which (Upc2 
, Ndt80 
, Crz1 
, Tac1 
, and Rim101 
) had been previously described (). We note an unexpected discordance between the fluconazole and fenpropimorph phenotypes in some TRKOs. In many cases resistance or sensitivity was only observed with one of the two drugs, and in a few cases resistance to one drug was accompanied by sensitivity to the other.
Of the 34 TRKOs with decreased or increased drug sensitivity, eight had high specificity scores (). Of these, only UPC2
exhibited a strong defect in growth under anaerobic growth conditions (Dataset S2
), a phenotype consistent with a strong defect in ergosterol biosynthesis. We predict that the other seven TRs influence resistance/sensitivity through mechanisms other than activation of ergosterol biosynthetic pathways. Four of these seven TR knockouts – ΔΔaaf1
, and ΔΔorf19.5133
– acquire resistance
to fluconazole or fenpropimorph, a phenotype that – to our knowledge – has not been previously described in either C. albicans
or S. cerevisiae
. Although the mechanism of this resistance is not known, several additional observations in the literature link these TRs to drug resistance. AAF1
is upregulated in response to the antifungal drug caspofungin 
, suggesting that this TR may serve a general role in antifungal response. MNL1
has been shown to activate stress response genes 
is similar to S. cerevisiae PDR1
, a known master regulator of drug resistance 
. For ORF19.5133
, the observed high-specificity fenpropimorph resistance is the first description of this regulator.
Given that over 20% of the TRKOs screened affected resistance to either fluconazole or fenpropimorph, it seems clear that a large number of genomic targets, only a few of which have been previously described, can contribute to acquisition of resistance to these compounds. Although these antifungal agents have specific and focused mechanisms of action, we conclude that susceptibility to them can be influenced by perturbations of a surprisingly large number of transcriptional circuits. We regard these observations as a starting point for more exhaustive studies of these regulators.
The regulatory network governing colony morphogenesis and invasive growth
A central feature of C. albicans
is its ability to grow in three distinctive morphological forms: budding yeast, pseudohyphae, and hyphae. All three forms are found at sites of infection, and the transition appears to be closely linked to pathogenesis. On solid media, C. albicans
exhibits a variety of colony morphologies which reflect the transitions among these three cell forms 
. A number of transcriptional regulators of colony morphology have been identified in C. albicans
, and a subset has been extensively studied (reviewed by Whiteway and Bachewich 
). In screening the knockout library, we noticed that a significant fraction of the TRKOs (over 25%), including many that had not been previously characterized, exhibited distinctive colony morphology phenotypes. Because of the importance of cell morphology to C. albicans
interaction with its human host, we paid particular attention to this phenotype and its analysis.
As colonies grow, different microenvironments are formed and the different cells of the colony respond accordingly, giving a progression of colony phenotypes over time. C. albicans
colonies are complex structures that can be described in terms of both invasiveness and colony structure. Invasive growth – penetration into the agar surface by pseudohyphae and hyphae – was scored by examination of the colony perimeter and by observing cell retention after washing the colony from the agar surface. As colonies developed, the wild-type strain exhibited invasive growth on a variety of media. The wild-type strain also exhibited a range of colony structures, depending on the time-point and media composition. The two extremes in colony structure were “wrinkled” and “smooth”. The “wrinkled” structure was characterized by heavily ridged colonies consisting of yeast, pseudohyphal and hyphal cell types. These colonies had the consistency of rubber, likely due to extensive extracellular matrix deposition, as has been described for both C. albicans 
and S. cerevisiae 
. As these colonies grew, the invasion into the agar described above took place. The “smooth” colony structure was characterized by dome-shaped colonies consisting primarily of yeast cells and having a paste-like consistency, likely reflecting the absence of an extensive extracellular matrix.
The primary phenotypic screen captured the progression of colony morphology across multiple days of growth (), and was supplemented by a more detailed screen of colonies derived from single cells instead of patches (). 28% of the TRKOs in our collection exhibited altered colony morphology in at least one growth condition. Although the data are extensive, several generalizations can be made. About half of the TRKOs with altered colony morphology showed a reduction in a morphological characteristic such as wrinkling or invasion, and the remaining half showed an enhancement of these features. The likely explanation, supported by a number of studies in the literature (see reviews 
), is that these morphological transitions are under both negative and positive transcriptional control. Indeed, TRs previously known to control morphology (e.g. the negative regulators of filamentous growth NRG1
and the positive regulator TEC1
) exhibited high specificity scores. Our screen identified 20 additional transcriptional regulators that had not previously been implicated in this network.
Single-cell–derived colony morphology phenotypes of C. albicans transcriptional regulator knockout strains.
Our results also indicate that the parameters of colony morphology can be controlled independently. For example, we observed colonies with enhanced invasion (e.g. ΔΔorf19.6874
; see the colony periphery in at 30°C on day 7), colonies with wild-type levels of invasion but minimal wrinkling (e.g. ΔΔcsr1
), colonies with enhanced wrinkling but no peripheral invasion (e.g. ΔΔfgr15
), and colonies exhibiting neither invasion nor wrinkling (e.g. ΔΔgat2
). Our results also indicate that some TRs can be assigned to specific features of colony development, while others act more broadly. For example, Gat2 and Orf19.4988 appear to act more generally. Deletion of either of these regulators resulted in smooth colonies with almost no invasion under all conditions tested (). GAT2
has been previously identified as a positive regulator of colony morphology 
, and ORF19.4998
is a previously uncharacterized zinc finger TR. The broad phenotypic effects of these two TRs suggest that they regulate (perhaps together) a core pathway governing the formation of colony wrinkling, extracellular matrix production, and invasion. In contrast, many other transcriptional regulators have more specific effects and are likely involved in the transmission of specific environmental signals. For example, ΔΔorf19.1685
showed a colony morphology defect only on Spider medium, and ΔΔorf19.2748
showed a defect only on Lee's medium (). The former deletion strain, ΔΔorf19.1685
, is also deficient in the utilization of mannitol as a carbon source (), and mannitol is the primary carbon source of Spider medium. Similarly, the latter deletion strain (ΔΔorf19.2748
) is unable to utilize proline as a nitrogen source (), and proline is highly abundant in Lee's medium. Thus these two regulators appear to link specific cues in the environment to colony phenotype.
Many other examples of TRKOs that affected colony morphology are given in . These results contribute to the goal of a complete description of the very large transcription circuit that controls morphological development in C. albicans. The results support a model in which a core pathway regulates the formation of a multi-cellular colony – consisting of different types of cells held together by an extracellular matrix – and is impinged upon by environmental cues to determine the overall output of the circuit. A next step in the analysis would be to determine, by full genome chromatin IP, the target genes for each of the core regulators. This analysis would reveal not only the transcriptional connections between the regulators themselves, but also the structural and enzymatic proteins that execute the program.
Comparative functional analysis of orthologous S. cerevisiae and C. albicans TRs
The phenotypic analysis of the C. albicans TRKO collection provided an opportunity to systematically examine the conservation of transcriptional regulator function between C. albicans and S. cerevisiae. A few specific examples were discussed above, and in this section we examine the question more systematically. Specifically, we determined whether orthologous regulators in the two species controlled similar or different phenotypes. We use the term orthologous in its conventional sense, to indicate genes in the two species that derived from a single gene in the last common ancestor.
Before proceeding, we discuss several difficulties inherent to these inter-species comparisons, and how we addressed them. First, for the comparison to be valid, the phenotypic assays compared between species must employ similar conditions and methodologies. Although several high-throughput phenotypic analyses of S. cerevisiae
have been conducted (e.g. 
), the extent of concordance between these studies is sufficiently low that these data are not suitable for inter-species comparison. To enable a more meaningful comparison, we conducted a limited phenotyping of S. cerevisiae
TRKO mutants (, Dataset S3
) using the same basic conditions that we employed for the C. albicans
phenotyping. A second complication in phenotypic comparison is that baseline sensitivities to environmental cues (e.g. nutrient deprivation or drug exposure) may vary between species. Although these differences may have interesting explanations, they can result in false negatives, where the absence of phenotype in one species may simply reflect insufficient concentrations of the agent. To address this issue, our phenotypic assays of both yeasts tested a range of concentrations of agents such as caffeine, rapamycin, fluconazole, and fenpropimorph. As described in the supplemental materials (Text S2
), this approach was used to select appropriate concentrations of agents for the screens. A third issue concerns confidence in the assignment of true orthologs given the gene duplications and losses that have occurred in the ascomycete lineage. In order to identify high-confidence orthologs (as opposed to mere homologs) in C. albicans
and S. cerevisiae
, we employed a combination of two different algorithms, SYNERGY 
and INPARANOID 
supplemented by case-by-case orthology assignments (Dataset S1
; described in Text S2
). For our comparison, we considered only ortholog pairs that: (1) produced a strong knockout phenotype in at least one of the two species, and (2) had been reliably assayed on the medium of interest in both species. These criteria produced a set of 24 1-to-1 orthologs for further analyses ().
Conservation of transcriptional regulator phenotypes.
The results show that most TRs with clear orthology between C. albicans
and S. cerevisiae
exhibit the same basic phenotype upon deletion. The conserved phenotypes ranged from the specific, such as impaired utilization of a nitrogen source or sensitivity to EDTA, to less defined phenotypes such as strongly impaired growth on rich medium (see Text S5
for details). Of the 24 pairs included in the analysis, we identified 11 cases of clear phenotypic conservation and an additional 8 cases where primary phenotype(s) were present in both species but where one or more additional phenotypes were exhibited by one species but not the other.
Despite the trend toward similar phenotypes produced by orthologous TRKOs, we did find exceptions, which likely reveal instances of major network rewiring. In particular, we found five cases in which a TRKO phenotype was evident in only one of the two species. One of these TRs, GAL4
, has been previously described as a case of network rewiring 
. S. cerevisiae
mutants deleted for GAL4
are unable to use galactose as a carbon source, but deletion of the C. albicans GAL4
ortholog does not produce this phenotype (
and Dataset S2
). A second example is seen with the regulator RTG1
. Deletion of this regulator in S. cerevisiae
results in glutamate and aspartate auxotrophies 
, yet deletion of the C. albicans
ortholog does not. Although the 1-to-1 orthology between these genes is not entirely certain (a 2-to-1 relationship may exist, with EDS1
included as a second ortholog in S. cerevisiae
), this regulator appears to have undergone either an acquisition or loss of metabolic regulatory function since C. albicans
and S. cerevisiae
shared a common ancestor. It is of course possible that C. albicans
has a redundant regulator that masks the true role of RTG1
; however, this would still indicate that a rewiring event had occurred. Three additional differences, each suggestive of network rewiring, are listed in .
The data can also be used to address phenotypic conservation for orthology relationships more complex than a simple 1-to-1. Because the gene pairs that arose from the whole genome duplication (WGD) in the S. cerevisiae
branch of the ascomycetes have been carefully curated 
, it is also possible to identify with high confidence the 1-to-2 (C. albicans
to S. cerevisiae
) orthologous relationships that arose from this event. Such a comparison allows us to ask whether zero, one, or both of the two S. cerevisiae
duplicates have the same overall role as the single gene in C. albicans
We analyzed eight high-confidence 1-to-2 orthologous relationships, and found several patterns of conservation (). First, we observed cases (exemplified by C. albicans SKN7 and the two S. cerevisiae orthologs SKN7 and HMS2) where the likely ancestral function was preserved in one S. cerevisiae gene but apparently lost in the other. Deletion of C. albicans SKN7 and S. cerevisiae SKN7 both result in sensitivity to oxidative stress, whereas deletion of S. cerevisiae HMS2 does not. Thus, HMS2 appears to have diverged (at least in the phenotypes its deletion produces) from the ancestral gene.
A second type of relationship is seen with the S. cerevisiae MET31 and MET32 genes relative to the single C. albicans ortholog, ORF19.1757. Deletion of either MET31 or MET32 from S. cerevisiae reveals no major phenotypes, whereas the double deletion produces a methionine auxotrophy. In our screen, deletion of C. albicans ORF19.1757 does not produce a methionine auxotrophy or any other tested phenotype. Thus, it is likely that either the C. albicans gene or the S. cerevisiae genes retain the ancestral function and the function has changed in the other species.
A third scenario is exemplified by comparison of the C. albicans gene ORF19.5026 with the two S. cerevisiae orthologs YML081w and RSF2. Of these three genes, only YML081w exhibited a phenotype (impaired growth in rich medium) under the range of conditions tested.
While far from complete, our data represent a first step towards a systematic approach to the analysis of the phenotypic output of regulatory networks in divergent species. We found an overall conservation of phenotypic output in the majority of clear 1-to-1 orthologs, but also noted several differences. Even with the small number of 1-to-2 orthologs, we observed several different phenotypic relationships, indicating that there is likely no stereotypical pattern; instead, each case must be individually explored by experiment. We are aware that the set of high-confidence orthologs is biased against orthologs that have diverged to the extent that their assignment becomes ambiguous. Nonetheless, even our high-confidence orthologs exhibit considerable divergence, and yet the phenotypic outputs are largely conserved.
Given the significant rewiring of transcriptional networks documented in the fungal lineages 
, the high degree of phenotypic conservation we observed between S. cerevisiae
and C. albicans
orthologs may seem unexpected. However, we know that transcriptional rewiring can take place without losing an ancestral connection between a transcriptional regulator and a process. For example, the mating circuitry between C. albicans
and S. cerevisiae
has undergone extensive evolutionary rewiring 
, but the same (orthologous) regulators still govern mating in both species. Likewise, the transcriptional regulator STE12
controls the pheromone response in S. cerevisiae
and likely also in C. albicans
, yet the direct target genes of STE12
, as well as the pheromone response itself, differs significantly between the two yeasts 
. Our results indicate that despite the rewiring that has taken place, the overall function of transcriptional regulators (defined broadly by the phenotypes caused by their deletion) often remains preserved from the common ancestor.