Sometimes evolution repeats itself. For example, independent butterfly species can evolve the same warning pattern to ward off predators. In many cases, the reason that a certain trait crops up again and again in parallel evolution is unknown.

One example is from the evolution of fungi, where a particular DNA sequence appeared several times independently in a large range of genes in different fungus species. This DNA sequence binds to a protein called Mcm1, which regulates nearby genes. Exactly why this DNA sequence has evolved in parallel so often in fungi has not been clear until now.

Researchers want to find out what is so special about this DNA binding sequence for Mcm1, as there are many other proteins that could do the same job. Now, Sorrells et al. investigated this further by testing whether a binding site for another protein Rap1 often found close by had a role to play. Experiments using 162 different fungus species showed that Mcm1 binding sites had evolved 12 times in parallel. Rap1 and Mcm1 did indeed turn out to work together to regulate nearby genes. The two proteins interact with a large protein complex critical for activating genes.

As a result, Mcm1 binding sites are more likely to evolve and play a role in gene regulation in different species when they are located near Rap1 binding sites. This could explain why this particular DNA sequence has evolved in parallel so many times. The same principle may apply to other genetic sequences involved in parallel evolution. With this understanding, it could be possible to predict when and where this event might occur in the future in fungi. This could be particularly useful for working towards being able to predict and anticipate the evolution of drug-resistant fungal pathogens.

Contingency is widespread in evolution, with chance historical changes dictating the repertoire of future possibilities (Bershtein et al., 2006; Bloom et al., 2006; Blount et al., 2012; Ortlund et al., 2007; Sorrells et al., 2015; Starr et al., 2017). Nevertheless, repeated evolutionary events in different lineages demonstrate that evolution is, at least in some instances, predictable. Repeatability is broadly referred to as convergent evolution, and when a trait arises repeatedly by a similar molecular mechanism, it is referred to as parallel evolution (Stern, 2013). Beginning with Darwin (Darwin, 1883), convergence has been taken as evidence for adaptation, but it can also be caused by drift within the constraints that arise from the properties of biological systems (Losos, 2011). Instances of repeated events can be thought of as natural experimental replicates for finding general principles that result in convergent evolution, and this information could be used to predict which evolutionary paths are most probable.

Genomic studies have found sets of genes that underlie convergent evolution of a wide variety of traits from across the tree of life (Bellott et al., 2010; Denoeud et al., 2014; Gallant et al., 2014; Mycorrhizal Genomics Initiative Consortium et al., 2015; Marvig et al., 2015; McCutcheon et al., 2009; Nagy et al., 2014; Pfenning et al., 2014; Sherwood et al., 2014; Soria-Carrasco et al., 2014). Such sets of genes tend to evolve in functionally related groups and are controlled by cis-regulatory sequences for particular transcription regulators, forming a transcription network. One way that an entire network can be up- or down-regulated is through alterations in the expression of a ‘master’ regulator, propagating a new expression level to all of its downstream target genes (Chan et al., 2010; McGregor et al., 2007; Rebeiz et al., 2009; Reed et al., 2011). However, in many cases—instead of changing the expression pattern of a master regulator—each gene in the network independently acquires the same cis-regulatory sequence, requiring hundreds of mutations across the genome (Booth et al., 2010; Borneman et al., 2007; Gasch et al., 2004; Kasowski et al., 2010; Lowe et al., 2011; Paris et al., 2013; Piasecki et al., 2010; Schmidt et al., 2010; Tanay et al., 2005; Tuch et al., 2008b). An outstanding question is how this process occurs.

Several molecular mechanisms for gene-by-gene rewiring have been proposed (Britten and Davidson, 1971; Tuch et al., 2008b). Hitchhiking of a cis-regulatory site on a transposable element is a mechanism well-documented in plant and animal evolution, and can rapidly bring genes under new regulatory control (Bourque et al., 2008; Chuong et al., 2016; Kunarso et al., 2010; Lynch et al., 2011; Schmidt et al., 2012). Alternatively, one transcription regulator can gain a protein-protein interaction with another, followed by the evolution of cis-regulatory sequences (Baker et al., 2012; Lynch et al., 2008; Pérez et al., 2014; Tsong et al., 2006). This latter mechanism is able, at least in principle, to rewire an entire set of genes at once upon evolution of the new protein-protein interaction; the individual gains of binding sites could occur secondarily. Nevertheless, many—if not most—examples of network rewiring seem to have occurred in the absence of evidence for either of these two mechanisms (Borneman et al., 2007; Gasch et al., 2004; Kasowski et al., 2010; Lowe et al., 2011; Paris et al., 2013; Piasecki et al., 2010; Schmidt et al., 2010; Tanay et al., 2005; Tuch et al., 2008a).

Here, we studied an example of transcription network rewiring in which ~100 ribosomal protein genes gained binding sites for the Mcm1 transcription regulator, and we describe evidence supporting a new mechanism for the concerted gains. The gain of Mcm1 binding sites in the ribosomal protein genes occurred in parallel in two respects: (1) the cis-regulatory sites were gained upstream of a large proportion of the ribosomal proteins in each species; and (2) they were gained independently approximately 12 – 13 times during Ascomycete evolution. At each gene, several point mutations were probably necessary to produce a close match to the 16-basepair Mcm1 binding site, thus requiring several hundred mutations across the entire gene set.

Based on results from a variety of experimental approaches, we argue that the gain of Mcm1 sites was potentiated in several different clades by the presence of an ancestral transcription regulator of the ribosomal protein genes, Rap1. We demonstrate that Rap1 and Mcm1 have the intrinsic ability to cooperate in the activation of transcription, even when artificially introduced in species in which their sites are not found together. Biochemical and genetic experiments show that both regulators interact with the general transcription factor TFIID. We propose that the intrinsic, ancient ability of both proteins to interact with a common component of the general transcription machinery facilitated the repeated evolution of the Mcm1 sites in independent lineages.

Here we have investigated an example of parallel evolution where binding sites for a particular transcription regulator (Mcm1) were gained in a large group of genes (the ribosomal protein genes, RPGs). These gains occurred repeatedly in several independent fungal lineages. In three of these lineages, Mcm1 binding sites were gained a fixed distance from the sites for another transcription regulator, Rap1, and we show that these newly acquired Mcm1 sites are required for full activation of the RPGs. We also show that Mcm1 and Rap1 cooperatively activate these genes. The direct interaction of both of these regulators with a common target, the general transcription factor TFIID, provides a plausible mechanism for this cooperative transcription activation. It also explains why the ability of Rap1 and Mcm1 to work together was ancestral to the more recent gains of Mcm1 sites adjacent to Rap1 sites at the RPGs.

How do these observations account for the fact that Mcm1 sites (as opposed to sites for other regulators) were repeatedly gained in parallel next to the Rap1 site at the RPGs? And how do they account for the distance constraints? One common explanation for parallelism is a specific environmental adaptation that occurs through a similar molecular mechanism. However, the yeast species with Mcm1 sites at the RPGs are from diverse ecological niches (e.g. plant leaves, mangrove sediment, the human body, soil) and utilize different nutrient sources (e.g. lactate, xylose, feline skin, nematode predation), defying a specific environmental adaptation explanation. Consistent with this view is our observation, based on analyzing interspecies hybrids, that a species in which the Mcm1 sites were gained at the RPGs does not express these genes at higher levels than related species that evolved fewer Mcm1 sites.

The model that best fits all of our data holds that the parallel gains arose from the ease with which the functional Mcm1 sites (and not the sites of other regulators) appeared in evolution, rather than selective pressure for particular adaptation. Specifically, we propose that, in the Kluyveromyces-Saccharomyces ancestor (before the parallel gains of Mcm1 sites) Rap1 bound to the ribosomal protein genes and activated transcription through interactions with TFIID, as it does in extant species. We further propose that, in the ancestor, Mcm1 activated non-ribosomal genes by interaction with a second site on TFIID, as it does in the extant species S. cerevisiae. Any suboptimal Mcm1 site that arose by chance point mutation at a specified distance from a Rap1 site would immediately be functional (Figure 7) because, as we show, even a weak Mcm1 DNA interaction would be stabilized by Mcm1’s intrinsic ability to directly bind TFIID (see Figure 4C and 6A). In this way, even suboptimal cis-regulatory sequences (which are much more likely to appear by chance than optimal sites [Dermitzakis and Clark, 2002; Stone and Wray, 2001]) could form under selection. The appearance of Mcm1 sites likely occurred concomitantly with the gradual losses of other cis-regulatory sites in the RPGs; in other words, the Mcm1 cis-regulatory sites would fall under selection as other cis-regulatory sites deteriorated by mutation. In essence, we propose that the free energy gained from the intrinsic interaction between Mcm1 and TFIID would favor formation of new Mcm1 sites at the expense of pre-existing cis-regulatory sequences, particularly since the latter provide a larger target for inactivating mutations. This model accounts for why Mcm1 sites (and not those of other transcription regulators) were repeatedly gained at the RPGs and why the distance between Rap1 and Mcm1 sites is constrained in those species in which the gains occurred.

Figure 7

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Numerous experimental observations support this model and rule out alternative explanations: (1) in extant species, Rap1 and Mcm1 both interact with TFIID; (2) They interact with different parts of TFIID; (3) cooperative transcriptional activation by Mcm1 and Rap1 requires the activation domain of Rap1, which is known to interact with TFIID; (4) the spacing between Rap1 and Mcm1 sites in the ribosomal protein genes places the proteins on the same side of the helix but at least 50 bp apart, consistent with a physical interaction with a large complex; (5) engineered suboptimal Mcm1 sites are functional as long as they are adjacent to Rap1 sites; (6) Mcm1 and Rap1 have the intrinsic ability to cooperate (through interactions with TFIID) even in a species where Mcm1 sites were not gained at the RPGs.

We note that this model does not require any change in Rap1 or Mcm1 during the gains of Mcm1 sites at the RPGs. Presumably, Rap1 and Mcm1 activated many genes separately in the ancestor, thus preserving by stabilizing selection their ability to interact with TFIID. This idea is consistent with the observation that the two proteins were able to cooperate on artificial constructs introduced into S. cerevisiae even though their binding sites are not found together at the RPGs. Mutations that alter the function of transcription regulators (for example, creating a new protein-protein interaction) can be pleiotropic, decreasing the likelihood that they can arise without disrupting the proteins' ancestral functions (Carroll, 2005; Stern and Orgogozo, 2008). (We note that the transcriptional output was slightly more cooperative in Kl. lactis than in S. cerevisiae, leaving open the possibility that additional fine-scale evolutionary changes may have occurred in how these proteins interact.) According to our model, the ability of the two regulators to work together was ancestral, part of each protein’s intrinsic mechanism of transcriptional activation; therefore, their coupling at the RPGs would avoid such pleiotropic changes.

How does this model account for the gains of Mcm1 sites observed in clades where Rap1 does not regulate the RPGs? In these cases, Mcm1 cis-regulatory sequences also show preferred spacing relative to known regulators of the RPGs, specifically Tbf1 and Rrn7, and we propose that the same type of cooperativity with TFIID can also account for these cases. These two regulators are reported to interact with TFIID (Knutson et al., 2014; Mallick and Whiteway, 2013). Indeed, TFIID occupies the promoters of RPGs in human cell lines as well (ENCODE Project Consortium et al., 2012), raising the possibility that TFIID is a conserved general activator of the RPGs across fungi and animals, while the specific transcription regulators that interact with TFIID simply interchange over this timescale.

While our cooperative activation model provides an explanation for the parallel acquisition of Mcm1 cis-regulatory site evolution, selection must have operated to preserve the Mcm1 sites as they arose in the population. As described earlier, we favor a model where the gains of Mcm1 sites compensated for the degradation of other cis-regulatory sequences and thereby fell under selection. The allelic expression data (Figure 2) strongly supports this model for one clade, represented by Kluyveromyces species. However, it is also possible that, in other clades or over shorter timescales, the Mcm1 sites could have been gained due to selection for higher levels of RPG expression. The widespread differences in RPG expression revealed by the published interspecies hybrid experiments suggest that RPG expression may experience strong and shifting selection, helping to account for the surprising observation that transcriptional regulators that control the RPGs vary substantially across species (Gasch et al., 2004; Lavoie et al., 2010; Mallick and Whiteway, 2013; Tanay et al., 2005; Tuch et al., 2008a; Zeevi et al., 2014; Zeevi et al., 2011). We note that the intrinsic cooperativity model is sufficient to explain the gain of Mcm1 sites whether or not any change in selection occurs: if functional Mcm1 sites are relatively easy to form (because of intrinsic cooperativity) they will be favored over gains of other cis-regulatory sequences by mutational processes alone. Mutations creating Mcm1 sites and weakening other sites could occur sequentially in either order or simultaneously (on the same haplotype), depending on the expression requirements of the RPG at that point in its evolutionary history. We feel that it is likely that most or all of the selection scenarios outlined above have occurred in at least one RPG at some point during the multiple and ongoing gains of Mcm1 sites over millions of years of fungal evolution. While the precise circumstances of each Mcm1 site gain are unknown, intrinsic cooperativity biases the RPGs as a whole toward gaining these sites.

In conclusion, we have proposed a mechanism, supported by multiple lines of experimental evidence, to account for convergent regulatory evolution of a large set of genes. Although, on the surface, the parallel gains of Mcm1 sites at the ribosomal genes would seem to require a special evolutionary explanation, our model does not require an extraordinary mechanism beyond individual point mutations in the cis-regulatory region of each gene. However, the ancestral ability of the two key regulators to activate transcription simplifies the path to gaining these sites by producing a phenotypic output from even non-optimal sites. Mcm1, because of its intrinsic ability to cooperate with Rap1, can significantly activate transcription at the ribosomal proteins more easily than it would elsewhere in the genome; likewise, Mcm1 (or another regulator that interacted with TFIID) would be preferred at the RPGs over regulators that did not share this common direct protein interaction. Thus, the intrinsic cooperativity of Rap1 and Mcm1 ‘channels’ random mutations into functional Mcm1 cis-regulatory sequences, accounting for the observed parallel evolution. We speculate that gene activation through intrinsic cooperativity may be a general mechanism to explain the rapid and ubiquitous rewiring of transcription networks.

Interspecies hybrid expression data is available at the Gene Expression Omnibus (GEO) repository under accession number GSE108389. Flow cytometry data is available at Flow Repository under accession numbers FR-FCM-ZYWS, FR-FCM-ZYWT, FR-FCM-ZYWU, FR-FCM-ZYWV, FR-FCM-ZYJZ, FR-FCM-ZYJY, and FR-FCM-ZYJ2. Code used in computational analyses is available at doi.org/10.5281/zenodo.1341284.

1. 1. Trevor R Sorrells

   (2018) Interspecies hybrid expression data

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   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE108389
2. 1. Trevor R Sorrells

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3. 1. Trevor R Sorrells

   (2018) Flow cytometry data for Figure 3E Rps23

   Publicly available at FlowRepository (accession no. FR-FCM-ZYWT).

   https://flowrepository.org/id/FR-FCM-ZYWT
4. 1. Trevor R Sorrells

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5. 1. Trevor R Sorrells

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   https://flowrepository.org/id/FR-FCM-ZYWV
6. 1. Trevor R Sorrells

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7. 1. Trevor R Sorrells

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Thank you for submitting your article "Intrinsic cooperativity potentiates parallel cis-regulatory evolution" for consideration by eLife. Your article has been reviewed by Patricia Wittkopp as the Senior Editor, a Reviewing Editor, and three reviewers. The following individual involved in review of your submission has agreed to reveal his identity: Brian P.H. Metzger (Reviewer #2).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

All three reviewers were overwhelmingly positive and believe that this manuscript is an important and rigorous contribution that presents a novel mechanism by which transcriptional regulatory networks can evolve.

Essential revisions:

The consensus is that no additional experiments or analyses are required. Nonetheless, the authors should revise the manuscript in the following ways:

1) Provide a more specific model(s) about how new Mcm1 binding sites could have been selected for and/or maintained, even if this model(s) should be tested in more detail by future studies.

2) Clearly document the sources of all genome sequences analyzed and, for unpublished data, verify that the present analyses meet any terms of use the authors may have agreed to.

3) Provide sufficient detail about the phylogenetic analyses that the results can be replicated.

Reviewer #1:

Several cases have been observed where large regulatory networks have acquired binding sites for the same transcription factor (TF) across dozens of genes during evolution. In previous cases, these seemingly improbable events have been shown to occur through facilitation by transposable elements or protein-protein interactions among TFs. The present work provides an attractive new model where the interactions of two TFs with a third protein (TFIID) seem to have facilitated the acquisition of binding sites.

In general, the model was well articulated, and the experiments performed were insightful and rigorous. The diverse methods included hybridization, gene expression analyses, protein biochemistry, genetic reporter tests of cooperativity, and a particularly insightful test of the importance of the second TF in allowing weak binding sites from the first TF to have a stronger effect (Figure 6A).

Nonetheless several major issues should be addressed:

The phylogenetic and ancestral state reconstruction analyses are not sufficiently documented, do not appear to be up to modern standards, and do not discuss conflicts with published phylogenomic analyses that are likely more rigorous.

Subsection “Gains of functional Mcm1 cis-regulatory sites”, "data not shown" does not meet eLife reporting standards for any type of data or analyses.

The trend of gene expression for K. lactis versus the other species is in the opposite direction from what one might have expected under a simple model where binding sites were adaptively added to increase expression. The authors propose a compensatory model in subsection “Gains of functional Mcm1 cis-regulatory sites”, but they do not explore or discuss much how this would work, which somewhat undermines an otherwise neat and tidy story.

Were promoters analyzed separately that had TATA boxes versus those that were TATA-less? How would this impact conclusions?

Can the authors clarify that JGI is specifically allowing their unpublished genomes to be analyzed for this purpose? Downloading genomes from MycoCosm requires users to agree to terms of use. The list of investigators acknowledged suggests the authors have sought the necessary permissions, but it would be best to be certain, especially since JGI often considers phylogenomic analyses to be reserved for the publication of the genome.

No table of genome versions and citations is provided.

Reviewer #2:

The paper by Sorrells et al. addresses how binding sites for the same transcription factor can be gained across dozens of genes in independent lineages. The paper hypothesizes and tests a novel mechanism that the shared binding of two TFs with mediators of transcription can result in a bias of mutations towards functional effects on expression. Overall the paper is excellent, using multiple lines of evidence from genomics through functional tests to suggest that this mechanism may be important not only for the specific example studied but also more generally. I have only a few concerns that I believe are easily addressed.

1) A false dichotomy is set up in subsection “Gains of functional Mcm1 cis-regulatory sites”. It may be that Mcm1 doesn't change the overall expression, but instead changes regulation. This is addressed slightly in the next session, but the given impression is too clean given the lack of data that directly addresses this question.

2) Regardless of this concern, I like the experimental design. However, the species aren't that different in Mcm1 binding gains, i.e. both are in the full gain group. An alternative explanation for the results is that the organisms chosen simply aren't that different in their RPG regulation compared to what would happen upon the initial gain of Mcm1 binding sites. I believe that this needs to be acknowledged.

3) Compensation seems to imply an order, i.e. that the Mcm1 gain was after the loss of some other TF binding site. It seems more likely it was the other way around, that an Mcm1 gain permitted the loss of other binding sites. However, the extent to which the addition of Mcm1 binding site alone directly influenced expression isn't tested (i.e. adding a Mcm1 binding site to a promoter from a species without the Mcm1 gain). If the simple addition of Mcm1 alters expression, it becomes unclear how the authors think evolution proceeded given the strong purifying selection on RPG expression.

4) The figures don't show that Rap1^AS7Ala doesn't act cooperatively as stated.

5) The experiments only address the mediator binding hypothesis from the Rap1 perspective, not Mcm1 (which is the thing that is new), nor TFIID. While these experiments aren't necessary, I think this omission needs to be acknowledged.

Reviewer #3:

This is a convincing and enjoyable manuscript that presents evidence that multiple independent co-options of the transcription factor Mcm1 to regulate ribosomal protein genes (RPGs) occurred in different yeast clades (about 7-9 independent occurrences), building on the authors' previous work in Tuch et al. (2008a). The proposed mechanism is a pre-existing ability of Mcm1 to cooperate with Rap1, through their separate interactions with TFIID. The authors' evolutionary model is convincing and provides an explanation for several otherwise puzzling aspects such as the recurrence of particular spacings between Mcm1 and Rap1 sites. As always with Johnson lab papers, this one is very well written, the figures are excellent, and the experiments are rigorous. The work is of broad significance, because it provides a general rationale for how a cis-regulatory motif can abruptly emerge in a large set of genes such as the RPGs.

The one question that the manuscript did not seem to answer adequately is what is the selective pressure to maintain Mcm1 sites in RPG genes after they arise by chance (model in Figure 7)? Since these sites do not contribute to increased transcription of RPGs, I cannot see what prevents them from decaying again. The text mentions this issue: the Discussion section says that new Mcm1 sites at RPGs "would fall under selection as other cis-regulatory sites deteriorated by mutation" (citing Figure 7, though Figure 7 doesn't illustrate this situation) but leaves me wondering what TFs bind to these other sites, or if there is evidence to support this idea. In principle, if the idea is correct, the deterioration of the other sites should be evident in Figure 1—figure supplement 1. For example, Sfp1 sites seem to disappear in the Kluyveromyces clade around the same time as Mcm1 sites appear, so is Sfp1 a candidate?

Summary:

All three reviewers were overwhelmingly positive and believe that this manuscript is an important and rigorous contribution that presents a novel mechanism by which transcriptional regulatory networks can evolve.

Essential revisions:

The consensus is that no additional experiments or analyses are required. Nonetheless, the authors should revise the manuscript in the following ways:

1) Provide a more specific model(s) about how new Mcm1 binding sites could have been selected for and/or maintained, even if this model(s) should be tested in more detail by future studies.

A model for how Mcm1 binding sites could be selected for requires two things: that the Mcm1 site is functional and that there is an evolutionary force that tends to preserve the site. We have focused primarily on a mechanism (intrinsic cooperativity) that causes weak Mcm1 sites to be functional in RPGs as they arise by mutation.

We can think of two plausible mechanisms explaining the preservation of Mcm1 sites once they arise. One mechanism would be direct selection for the increase of expression of the RPG, or the RPGs as a whole. This is plausible because the selection that acts on RPG expression as a whole changes significantly between species (as evidenced by our interspecies hybrid experiment as well as others). The selection acting on individual RPGs also probably changes on short timescales, potentially resulting on selection for a subset RPGs to have increased expression levels. However, we have no direct evidence for selection for increased expression of RPGs leading to the gain of Mcm1 sites.

We have direct evidence for a second model: a compensatory model in which the Mcm1 sites counteract losses of other regulatory elements. This is supported by the hybrid experiment results and cis-regulatory site analysis. The compensatory model is not incompatible with the first model (for example if selection for increased expression of RPGs alternated with relaxed selection or selection to reduce expression of RPGs). However, it could also be effected by neutral forces: if Mcm1 sites are allowed to be weak, they could present a smaller “mutational target” than the strong sites for another transcription regulator, resulting over time in the increase in Mcm1 sites at the expense of the other regulator due to mutational processes.

Compensatory changes could plausibly occur in multiple different orders on the scale of individual mutations, cis-regulatory sites, and genes. For example, mutations affecting the cis-regulatory sites could be fixed simultaneously (on the same haplotype) or alternate between strengthening the Mcm1 sites and weakening a second site. Alternatively, the Mcm1 site could become fixed some period of time before the loss of a second site (or vice-versa). We suspect that the precise order may differ for each gene as the Mcm1 sites were gained over millions of years.

We have done our best to indicate these scenarios in the text of the manuscript while making it clear what we have direct evidence for. We have modified Figure 7 to indicate the types of selection that could maintain Mcm1 sites, but because there are multiple plausible scenarios we have not directly illustrated them.

2) Clearly document the sources of all genome sequences analyzed and, for unpublished data, verify that the present analyses meet any terms of use the authors may have agreed to.

We have added Supplementary file 3 which includes the sources and versions of the genome assemblies and annotations used. The principle investigators of all of the unpublished genomes used in this study were contacted and shown an example analysis (or the final analysis) and consented to the use of the genomic data for the purpose of this publication. This consent was obtained prior to the preprint and initial submission of the manuscript. In all, 24 genomes of interest were excluded from the analysis because investigators did not consent to their use. Consent from a subset of the investigators was confirmed during revision and all gave the same response.

3) Provide sufficient detail about the phylogenetic analyses that the results can be replicated.

Additional detail was added to the methods to facilitate replication of the phylogenetic analyses. Specifically, we have added details about the tree construction, scoring of intergenic regions for cis-regulatory sites, and the newly added stochastic character mapping analysis to more rigorously estimate gains and losses. In addition to the scripts included in the initial submission, we have included Supplementary file 3 with the genome versions and Supplementary file 4 with the position weight matrices used for identifying the cis-regulatory sequences. We have also included a list of the ribosomal protein genes in each species and the presence of Mcm1 sites in Supplementary file 5.

Reviewer #1:

[…]

The phylogenetic and ancestral state reconstruction analyses are not sufficiently documented, do not appear to be up to modern standards, and do not discuss conflicts with published phylogenomic analyses that are likely more rigorous.

We have provided a reference and additional details in the methods on how the phylogenetic tree was created. Because we focus on the mechanism of parallel evolution and transcription activation, a detailed discussion of the tree topology is beyond the scope of the present study. Several differences in topology when compared to published studies may be ascribed to the use of unpublished genomes, but discussion of this is reserved for the principal investigators of these genome sequencing projects.

In response to this comment we have also implemented a new estimation of gains and losses to better quantify the uncertainty in this analysis. The model for evolution of binding sites is one of the most challenging questions we faced. In the end, rather than choosing a model specific to cis-regulatory sites whose assumptions were violated by the data we had, we chose a simple model of character evolution. (To be specific, the only sequence-independent model of binding site evolution we are aware of is CRETO from Otto et al. (2009) and to give an accurate estimate of evolutionary rates, it requires that the half-life of binding sites is on the order of the length of the tree from root to tip, whereas in our data Mcm1 site turnover is happening many times from root to tip.) Because of the large evolutionary distance, we decided to categorize species into presence or absence of Mcm1 sites and treat this as a discrete character under two different models. We strongly encourage the development of better computational models for cis-regulatory site evolution by experts in that area.

Subsection “Gains of functional Mcm1 cis-regulatory sites”, "data not shown" does not meet eLife reporting standards for any type of data or analyses.

We have further explained these results in the text of the manuscript and removed the assertion about phylogenetic branches because we did not rerun the analysis under multiple different tree topologies.

The trend of gene expression for K. lactis versus the other species is in the opposite direction from what one might have expected under a simple model where binding sites were adaptively added to increase expression. The authors propose a compensatory model in subsection “Gains of functional Mcm1 cis-regulatory sites”, but they do not explore or discuss much how this would work, which somewhat undermines an otherwise neat and tidy story.

Our intention was to present the results without trying to force them into a neat and tidy story. However, as suggested by all reviewers, we provide additional details about how a compensatory model may work, the details of which would need to be tested in future studies. Briefly, the scale of evolution between the interspecies hybrid may be much longer than selection for increased expression of the genes, or the model could involve neutral mutational processes alone.

Were promoters analyzed separately that had TATA boxes versus those that were TATA-less? How would this impact conclusions?

We analyzed whether Rap1 or Mcm1 sites showed a relationship with the strength or location of TBP/Spt15 binding sites, but no clear pattern was observed. In general, yeast ribosomal protein genes lack strong TATA boxes which may explain their dependence on transcription regulators such as Rap1 and Mcm1 that can directly interact with TFIID.

Can the authors clarify that JGI is specifically allowing their unpublished genomes to be analyzed for this purpose? Downloading genomes from MycoCosm requires users to agree to terms of use. The list of investigators acknowledged suggests the authors have sought the necessary permissions, but it would be best to be certain, especially since JGI often considers phylogenomic analyses to be reserved for the publication of the genome.

No table of genome versions and citations is provided.

See our response to the essential revisions.

Reviewer #2:

[…]

1) A false dichotomy is set up in subsection “Gains of functional Mcm1 cis-regulatory sites”. It may be that Mcm1 doesn't change the overall expression, but instead changes regulation. This is addressed slightly in the next session, but the given impression is too clean given the lack of data that directly addresses this question.

We agree that this seems simplistic because we do not discuss broad vs. condition-specific expression of Mcm1 until a later section. We have modified the text to specify that these hypotheses apply only to the function of Mcm1 during the rapid growth conditions used for the experiments in Figure 1 and Figure 2.

2) Regardless of this concern, I like the experimental design. However, the species aren't that different in Mcm1 binding gains, i.e. both are in the full gain group. An alternative explanation for the results is that the organisms chosen simply aren't that different in their RPG regulation compared to what would happen upon the initial gain of Mcm1 binding sites. I believe that this needs to be acknowledged.

We were indeed disappointed that we were unable to recover hybrids between species with larger differences in the number of Mcm1 binding sites (attempts are described in the methods). Unfortunately, we aren’t aware of any intermating species with a difference greater than that between Kl. lactis and Kl. wickerhamii (23% more RPGs have Mcm1 sites in Kl. lactis). Reports of distantly related species mating are probably due to misidentification of the species before molecular techniques existed.

We have modified the text to indicate our experiments address the question of evolution over the timescale of the divergence between each pair of species. This is a scale in which a significant fraction of RPGs can gain Mcm1 binding sites, suggesting that the gains aren’t completed by this time. One approach to capture the “initial gain” of Mcm1 sites as you suggest would be to measure allele-specific expression in hybrids between species such as S. cerevisiae and S. mikatae which show a slight difference between the levels of Mcm1 sites at the RPGs. However, we feel this is less informative because there is no guarantee that S. mikatae will go on to gain Mcm1 sites at a large fraction of its RPGs as we know happened in Kluyveromyces.

3) Compensation seems to imply an order, i.e. that the Mcm1 gain was after the loss of some other TF binding site. It seems more likely it was the other way around, that an Mcm1 gain permitted the loss of other binding sites. However, the extent to which the addition of Mcm1 binding site alone directly influenced expression isn't tested (i.e. adding a Mcm1 binding site to a promoter from a species without the Mcm1 gain). If the simple addition of Mcm1 alters expression, it becomes unclear how the authors think evolution proceeded given the strong purifying selection on RPG expression.

The best way to do this experiment would be to perform ancestral reconstruction on all intergenic sequences to see the effect of each gain of Mcm1 binding site along with other changes that happened in close evolutionary proximity, but this is unfortunately not possible because of the fast rate of evolution of intergenic regions. We suspect however, that the answer of order may differ between each gene depending on where the actual expression of the gene falls in the range of acceptable expression levels. See also our other responses regarding more details about the compensatory model.

4) The figures don't show that Rap1^AS7Ala doesn't act cooperatively as stated.

Thank you for pointing this out—we have changed the conclusion to “these mutations strongly reduced 3-AT resistant growth, indicating that efficient expression requires an intact Rap1 activation domain.”

5) The experiments only address the mediator binding hypothesis from the Rap1 perspective, not Mcm1 (which is the thing that is new), nor TFIID. While these experiments aren't necessary, I think this omission needs to be acknowledged.

The experiments that identified the point mutations disrupting the Rap1-TFIID interaction comprised an entire publication (Johnson and Weil, 2017), so doing so with Mcm1 and TFIID is beyond the scope of our current study. Because the intrinsic cooperativity model requires interactions between TFIID and both Rap1 and Mcm1, we feel that disrupting either interaction is a sufficient test of the model.

Reviewer #3:

This is a convincing and enjoyable manuscript that presents evidence that multiple independent co-options of the transcription factor Mcm1 to regulate ribosomal protein genes (RPGs) occurred in different yeast clades (about 7-9 independent occurrences), building on the authors' previous work in Tuch et al. (2008a). The proposed mechanism is a pre-existing ability of Mcm1 to cooperate with Rap1, through their separate interactions with TFIID. The authors' evolutionary model is convincing and provides an explanation for several otherwise puzzling aspects such as the recurrence of particular spacings between Mcm1 and Rap1 sites. As always with Johnson lab papers, this one is very well written, the figures are excellent, and the experiments are rigorous. The work is of broad significance, because it provides a general rationale for how a cis-regulatory motif can abruptly emerge in a large set of genes such as the RPGs.

The one question that the manuscript did not seem to answer adequately is what is the selective pressure to maintain Mcm1 sites in RPG genes after they arise by chance (model in Figure 7)? Since these sites do not contribute to increased transcription of RPGs, I cannot see what prevents them from decaying again. The text mentions this issue: the Discussion section says that new Mcm1 sites at RPGs "would fall under selection as other cis-regulatory sites deteriorated by mutation" (citing Figure 7, though Figure 7 doesn't illustrate this situation) but leaves me wondering what TFs bind to these other sites, or if there is evidence to support this idea. In principle, if the idea is correct, the deterioration of the other sites should be evident in Figure 1—figure supplement 1. For example, Sfp1 sites seem to disappear in the Kluyveromyces clade around the same time as Mcm1 sites appear, so is Sfp1 a candidate?

Your hypothesis is exactly what we think is happening—in some clades where Mcm1 sites are gained you can find some other regulator site that seems to be at lower levels in that clade (e.g. Fhl1, Sfp1, and Rrn7 in Kluyveromyces, Cbf1 in Pachysolen tannophilus, Tbf1 in Yarrowia lipolytica, Hmo1 in Hanseniaspora uvarum). However, there are also species and clades where there is no clear loss associated with Mcm1 site gains. A study from Saccharomyces found the differences in overall nucleotide composition of the promoter contributes greatly to expression divergence of RPG expression (Zeevi, 2014) so this may explain these additional species. We have now described this idea more explicitly several places in the manuscript.

Author details

1. Trevor R Sorrells

   1. Department of Biochemistry and Biophysics, Tetrad Graduate Program, University of California, San Francisco, United States
   2. Department of Microbiology and Immunology, University of California, San Francisco, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   trevorsorrells@gmail.com

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3527-8622

2. Amanda N Johnson

   Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee

   Contribution

   Conceptualization, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

3. Conor J Howard

   1. Department of Biochemistry and Biophysics, Tetrad Graduate Program, University of California, San Francisco, United States
   2. Department of Microbiology and Immunology, University of California, San Francisco, United States

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5375-6248

4. Candace S Britton

   1. Department of Biochemistry and Biophysics, Tetrad Graduate Program, University of California, San Francisco, United States
   2. Department of Microbiology and Immunology, University of California, San Francisco, United States

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

5. Kyle R Fowler

   1. Department of Biochemistry and Biophysics, Tetrad Graduate Program, University of California, San Francisco, United States
   2. Department of Microbiology and Immunology, University of California, San Francisco, United States

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

6. Jordan T Feigerle

   Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee

   Contribution

   Resources, Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

7. P Anthony Weil

   Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Writing—review and editing

   Competing interests

   No competing interests declared

8. Alexander D Johnson

   1. Department of Biochemistry and Biophysics, Tetrad Graduate Program, University of California, San Francisco, United States
   2. Department of Microbiology and Immunology, University of California, San Francisco, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Writing—original draft, Writing—review and editing

   For correspondence

   ajohnson@cgl.ucsf.edu

   Competing interests

   No competing interests declared

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