Publications

Transcription factors (TFs) are proteins crucial for regulating gene expression. Effective regulation requires the TFs to rapidly bind to their correct target, enabling the cell to respond efficiently to stimuli such as nutrient availability or the presence of toxins. However, the search process is hindered by slow diffusive movement and the presence of false targets DNA segments that are similar to the true target. In eukaryotic cells, most TFs contain an intrinsically disordered region (IDR), which is commonly assumed to behave as a long, flexible polymeric tail composed of hundreds of amino acids. Recent experimental findings indicate that the IDR of certain TFs plays a pivotal role in the search process. However, the principles underlying the IDRs role remain unclear. Here, we reveal key design principles of the IDR related to TF binding affinity and search time. Our results demonstrate that the IDR significantly enhances both of these aspects. Furthermore, our model shows good agreement with experimental results, and we propose further experiments to validate the models predictions.

Short tandem repeats (STRs) are enriched in regulatory regions and can bind transcription factors (TFs), as shown for selected examples in vitro. Here, we use a library-based assay to systematically measure TF binding to STRs of 25 bp units within budding yeast cells. We examined STR binding by four TFs, including Msn2, and further tested six Msn2 mutants, including two that contained only the DNA-binding domain (DBD) or only the 642-aa intrinsically disordered region (IDR). We find substantial STR effects on motif-dependent and motif-independent binding, which varied between TFs. For Msn2, STR association was explained by the DBD binding at motif half-sites and the IDR favoring homopurine-homopyrimidine and AT-rich repeats. TF-preferred STRs are enriched in the human genome but remain at low frequency at yeast promoters. We discuss the implications of our results for understanding the role of STRs and their crosstalk with TF IDRs in regulating TF binding across genomes.

Transcription factors (TFs) contribute to organismal development and function by regulating gene expression. Despite decades of research, the factors determining the specificity and speed at which eukaryotic TFs detect their target binding sites remain poorly understood. Recent studies have pointed to intrinsically disordered regions (IDRs) within TFs as key regulators of the process by which TFs find their target sites on DNA (the TF target search). However, IDRs are challenging to study because they can confer specificity despite low sequence complexity and can be functionally conserved despite rapid sequence divergence. Nevertheless, emerging computational and experimental approaches are beginning to elucidate the sequencefunction relationship within the IDRs of TFs. Additional insights are informing potential mechanisms underlying the IDR-directed search for the DNA targets of TFs, including incorporation into biomolecular condensates, facilitating TF co-localization, and the hypothesis that IDRs recognize and directly interact with specific genomic regions.

Transcription factors select their genomic binding sites in genomes depending on their DNA binding domain (DBD) but also on regions outside the DBD (nonDBD). However, it remains challenging to define these determinants within nonDBDs and reveal their mechanism of action. Towards this, we introduce here an in-vivo method for parallel analysis of thousands of designed peptides for binding a DNA sequence of interest (Protein Massively Parallel Binding Assay, pMPBA). We apply it to scan the full sequence space of budding yeast TFs and generate a detailed map of DNA localizing determinants. Within the set of predicted DBDs, we reveal a large variation in DNA binding affinities, depending on the family and on different sequence characteristics, including charge. Strong signals were not confined to predicted DBDs but included a considerable fraction of nonDBD peptides, most of which were predicted as intrinsically disordered. pMPBA opens new possibilities for high-throughput analysis of peptide-DNA binding within cells.Competing Interest StatementThe authors have declared no competing interest.

A recent study that systematically mapped genomic bindings and regulatory effects of transcription factors (TFs) reported a surprisingly low overlap between TF binding and regulatory targets in Saccharomyces cerevisiae1. Our analysis suggests that this conclusion depends on the permissive definition of binding targets, which includes a large fraction of weakly bound sites.Competing Interest StatementThe authors have declared no competing interest.

RNA-binding proteins (RBPs) are composed of RNA-binding domains (RBDs) often linked via intrinsically disordered regions (IDRs). Structural and biochemical analyses have shown that disordered linkers contribute to RNA binding by orienting the adjacent RBDs and also characterized certain disordered repeats that directly contact the RNA. However, the relative contribution of IDRs and predicted RBDs to the in vivo binding pattern is poorly explored. Here, we upscaled the RNA-tagging method to map the transcriptome-wide binding of 16 RBPs in budding yeast. We then performed extensive sequence mutations to distinguish binding determinants within predicted RBDs and the surrounding IDRs in eight of these. The majority of the predicted RBDs tested were not individually essential for mRNA binding. However, multiple IDRs that lacked predicted RNA-binding potential appeared essential for binding affinity or specificity. Our results provide new insights into the function of poorly studied RBPs and emphasize the complex and distributed encoding of RBPRNA interaction in vivo.

Activation domains (ADs) within transcription factors (TFs) induce gene expression by recruiting coactivators such as the Mediator complex. Coactivators lack DNA binding domains (DBDs) and are assumed to passively follow their recruiting TFs. This is supported by direct AD-coactivator interactions seen in vitro but has not yet been tested in living cells. To examine that, we targeted two Med15-recruiting ADs to a range of budding yeast promoters through fusion with different DBDs. The DBD-AD fusions localized to hundreds of genomic sites but recruited Med15 and induced transcription in only a subset of bound promoters, characterized by a fuzzy-nucleosome architecture. Direct DBD-Med15 fusions shifted DBD localization towards fuzzy-nucleosome promoters, including promoters devoid of the endogenous Mediator. We propose that Med15, and perhaps other coactivators, possess inherent promoter preference and thus actively contribute to the selection of TF-induced genes.

DNA-binding domains (DBDs) within transcription factors (TFs) recognize short sequence motifs that are highly abundant in genomes. In vivo, TFs bind only a small subset of motif occurrences, which is often attributed to the cooperative binding of interacting TFs at proximal motifs. However, large-scale testing of this model is still lacking. Here, we describe a novel method allowing parallel measurement of TF binding to thousands of designed sequences within yeast cells and apply it to quantify the binding of dozens of TFs to libraries of regulatory regions containing clusters of binding motifs, systematically mutating all motif combinations. With few exceptions, TF occupancies were well explained by independent binding to individual motifs, with motif cooperation being of only limited effects. Our results challenge the general role of motif combinatorics in directing TF genomic binding and open new avenues for exploring the basis of proteinDNA interactions within cells.

Intrinsically disordered regions (IDRs) guide transcription factors (TFs) to their genomic binding sites, raising the question of how structure-lacking regions encode for complex binding patterns. We investigated this using the TF Gln3, revealing sets of IDR-embedded determinants that direct Gln3 binding to respective groups of functionally related promoters, and enable tuning binding preferences between environmental conditions, phospho-mimicking mutations, and orthologs. Through targeted mutations, we defined the role of short linear motifs (SLiMs) and co-binding TFs (Hap2) in stabilizing Gln3 at respiration-chain promoters, while providing evidence that Gln3 binding at nitrogen-associated promoters is encoded by the IDR amino-acid composition, independent of SLiMs or co-binding TFs. Therefore, despite their apparent simplicity, TF IDRs can direct and regulate complex genomic binding patterns through a combination of SLiM-mediated and composition-encoded interactions.

Chromatin endogenous cleavage coupled with high-throughput sequencing (ChEC-seq) is a profiling method for protein-DNA interactions that can detect binding locations in vivo, does not require antibodies or fixation, and provides genome-wide coverage at near nucleotide resolution.The core of this method is an MNase fusion of the target protein, which allows it, when triggered by calcium exposure, to cut DNA at its binding sites and to generate small DNA fragments that can be readily separated from the rest of the genome and sequenced.Improvements since the original protocol have increased the ease, lowered the costs, and multiplied the throughput of this method to enable a scale and resolution of experiments not available with traditional methods such as ChIP-seq. This method describes each step from the initial creation and verification of the MNase-tagged yeast strains, over the ChEC MNase activation and small fragment purification procedure to the sequencing library preparation. It also briefly touches on the bioinformatic steps necessary to create meaningful genome-wide binding profiles.

Contact-sites are specialized zones of proximity between two organelles, essential for organelle communication and coordination. The formation of contacts between the Endoplasmic Reticulum (ER), and other organelles, relies on a unique membrane environment enriched in sterols. However, how these sterol-rich domains are formed and maintained had not been understood. We found that the yeast membrane protein Yet3, the homolog of human BAP31, is localized to multiple ER contact sites. We show that Yet3 interacts with all the enzymes of the post-squalene ergosterol biosynthesis pathway and recruits them to create sterol-rich domains. Increasing sterol levels at ER contacts causes its depletion from the plasma membrane leading to a compensatory reaction and altered cell metabolism. Our data shows that Yet3 provides on-demand sterols at contacts thus shaping organellar structure and function. A molecular understanding of this proteins functions gives new insights into the role of BAP31 in development and pathology.Competing Interest StatementThe authors have declared no competing interest.

The Origin Recognition Complex (ORC) seeds replication-fork formation by binding to DNA replication origins, which in budding yeast contain a 17bp DNA motif. High resolution structure of the ORC-DNA complex revealed two base-interacting elements: a disordered basic patch (Orc1-BP4) and an insertion helix (Orc4-IH). To define the ORC elements guiding its DNA binding in vivo, we mapped genomic locations of 38 designed ORC mutants, revealing that different ORC elements guide binding at different sites. At silencing-associated sites lacking the motif, ORC binding and activity were fully explained by a BAH domain. Within replication origins, we reveal two dominating motif variants showing differential binding modes and symmetry: a non-repetitive motif whose binding requires Orc1-BP4 and Orc4-IH, and a repetitive one where another basic patch, Orc1-BP3, can replace Orc4-IH. Disordered basic patches are therefore key for ORC-motif binding in vivo, and we discuss how these conserved, minor-groove interacting elements can guide specific ORC-DNA recognition.

Intrinsically disordered regions (IDRs) are abundant in eukaryotic proteins, but their sequence-function relationship remains poorly understood. IDRs of transcription factors (TFs) can direct promoter selection and recruit coactivators, as shown for the budding yeast TF Msn2. To examine how IDRs encode both these functions, we compared genomic binding specificity, coactivator recruitment, and gene induction amongst a large set of designed Msn2-IDR mutants. We find that both functions depend on multiple regions across the > 600AA IDR. Yet, transcription activity was readily disrupted by mutations that showed no effect on the Msn2 binding specificity. Our data attribute this differential sensitivity to the integration of a relaxed, composition-based code directing binding specificity with a more stringent, motif-based code controlling the recruitment of coactivators and transcription activity. Therefore, Msn2 utilizes interwoven sequence grammars for encoding multiple functions, suggesting a new IDR design paradigm of potentially general use.

Eviction of histones from nucleosomes and their exchange with newly synthesized or alternative variants is a central epigenetic determinant. Here, we define the genome-wide incorporation and exchange pattern of canonical and non-canonical histone variants in mouse embryonic stem cells by implementing a recently established, genetically encoded exchange sensor. While exchange of all measured variants scales with transcription, we describe variant-specific associations with transcription elongation and Polycomb binding. We found considerable exchange of H3.1 and H2B variants in heterochromatin and repeat elements, contrasting the stable incorporation and little exchange of H3.3 in these regions. This unexpected association between H3.3 incorporation and exchange of canonical variants is also evident in active promoters and enhancers, and further validated by reduced H3.1 dynamics following depletion of the HIRA H3.3-specific chaperone. The sensor system provides a powerful tool for studying regulation of histone dynamics toward understanding its role in shaping the epigenetic landscape in vivo.

DNA packaging within chromatin depends on histone chaperones and remodelers that form and position nucleosomes. Cells express multiple such chromatin regulators with overlapping in-vitro activities. Defining specific in-vivo activities requires monitoring histone dynamics during regulator depletion, which has been technically challenging. We have recently generated histone-exchange sensors in Saccharomyces cerevisiae, which we now use to define the contributions of 15 regulators to histone dynamics genome-wide. While replication-independent exchange in unperturbed cells maps to promoters, regulator depletions primarily affected gene bodies. Depletion of Spt6, Spt16 or Chd1 sharply increased nucleosome replacement sequentially at the beginning, middle or end of highly expressed gene bodies. They further triggered re-localization of chaperones to affected gene body regions, which compensated for nucleosome loss during transcription complex passage, but concurred with extensive TF binding in gene bodies. We provide a unified quantitative screen highlighting regulator roles in retaining nucleosome binding during transcription and preserving genomic packaging.

The binding of transcription factors (TFs) along genomes is restricted to a subset of sites containing their preferred motifs. TF-binding specificity is often attributed to the co-binding of interacting TFs; however, apart from specific examples, this model remains untested. Here, we define dependencies among budding yeast TFs that localize to overlapping promoters by profiling the genome-wide consequences of co-depleting multiple TFs. We describe unidirectional interactions, revealing Msn2 as a central factor allowing TF binding at its target promoters. By contrast, no case of mutual cooperation was observed. Particularly, Msn2 retained binding at its preferred promoters upon co-depletion of fourteen similarly bound TFs. Overall, the consequences of TF co-depletions were moderate, limited to a subset of promoters, and failed to explain the role of regions outside the DNA-binding domain in directing TF-binding preferences. Our results call for re-evaluating the role of cooperative interactions in directing TF-binding preferences.

Intrinsically disordered regions (IDRs) direct transcription factors (TFs) towards selected genomic occurrences of their binding motif, as exemplified by budding yeast's Msn2. However, the sequence basis of IDR-directed TF binding selectivity remains unknown. To reveal this sequence grammar, we analyze the genomic localizations of >100 designed IDR mutants, each carrying up to 122 mutations within this 567-AA region. Our data points at multivalent interactions, carried by hydrophobic-mostly aliphatic-residues dispersed within a disordered environment and independent of linear sequence motifs, as the key determinants of Msn2 genomic localization. The implications of our results for the mechanistic basis of IDR-based TF binding preferences are discussed.

DNA binding domains (DBDs) of transcription factors (TFs) recognize DNA sequence motifs that are highly abundant in genomes. Within cells, TFs bind a subset of motif-containing sites as directed by either their DBDs or DBD-external (nonDBD) sequences. To define the relative roles of DBDs and nonDBDs in directing binding preferences, we compared the genome-wide binding of 48 (∼30%) budding yeast TFs with their DBD-only, nonDBD-truncated, and nonDBD-only mutants. With a few exceptions, binding locations differed between DBDs and TFs, resulting from the cumulative action of multiple determinants mapped mostly to disordered nonDBD regions. Furthermore, TFs preferences for promoters of the fuzzy nucleosome architecture were lost in DBD-only mutants, whose binding spread across promoters, implicating nonDBDs preferences in this hallmark of budding yeast regulatory design. We conclude that DBDs and nonDBDs employ complementary DNA-targeting strategies, whose balance defines TF binding specificity along genomes.

DNA replication perturbs chromatin by triggering the eviction, replacement, and incorporation of nucleosomes. How this dynamic is orchestrated in time and space is poorly understood. Here, we apply a genetically encoded sensor for histone exchange to follow the time-resolved histone H3 exchange profile in budding yeast cells undergoing slow synchronous replication in nucleotide-limiting conditions. We find that new histones are incorporated not only behind, but also ahead of the replication fork. We provide evidence that Rtt109, the S-phase-induced acetyltransferase, stabilizes nucleosomes behind the fork but promotes H3 replacement ahead of the fork. Increased replacement ahead of the fork is independent of the primary Rtt109 acetylation target H3K56 and rather results from Vps75-dependent Rtt109 activity toward the H3 N terminus. Our results suggest that, at least under nucleotide-limiting conditions, selective incorporation of differentially modified H3s behind and ahead of the replication fork results in opposing effects on histone exchange, likely reflecting the distinct challenges for genome stability at these different regions.

Variations in noncoding regulatory sequences play a central role in evolution. Interpreting such variations, however, remains difficult even in the context of defined attributes such as transcription factor (TF) binding sites. Here, we systematically link variations in cis-regulatory sequences to TF binding by profiling the allele-specific binding of 27 TFs expressed in a yeast hybrid, in which two related genomes are present within the same nucleus. TFs localize preferentially to sites containing their known consensus motifs but occupy only a small fraction of the motif-containing sites available within the genomes. Differential binding of TFs to the orthologous alleles was well explained by variations that alter motif sequence, whereas differences in chromatin accessibility between alleles were of little apparent effect. Motif variations that abolished binding when present in only one allele were still bound when present in both alleles, suggesting evolutionary compensation, with a potential role for sequence conservation at the motifs vicinity. At the level of the full promoter, we identify cases of binding-site turnover, in which binding sites are reciprocally gained and lost, yet most interspecific differences remained uncompensated. Our results show the flexibility of TFs to bind imprecise motifs and the fast evolution of TF binding sites between related species.

Peroxisomes host essential metabolic enzymes and are crucial for human health and survival. Although peroxisomes were first described over 60 years ago, their entire proteome has not yet been identified. As a basis for understanding the variety of peroxisomal functions, we used a high-throughput screen to discover peroxisomal proteins in yeast. To visualize low abundance proteins, we utilized a collection of strains containing a peroxisomal marker in which each protein is expressed from the constitutive and strong TEF2 promoter. Using this approach, we uncovered 18 proteins that were not observed in peroxisomes before and could show their metabolic and targeting factor dependence for peroxisomal localization. We focus on one newly identified and uncharacterized matrix protein, Ynl097c-b, and show that it localizes to peroxisomes upon lysine deprivation and that its localization to peroxisomes depends on the lysine biosynthesis enzyme, Lys1. We demonstrate that Ynl097c-b affects the abundance of Lys1 and the lysine biosynthesis pathway. We have therefore renamed this protein Pls1 for Peroxisomal Lys1 Stabilizing 1. Our work uncovers an additional layer of regulation on the central lysine biosynthesis pathway. More generally it highlights how the discovery of peroxisomal proteins can expand our understanding of cellular metabolism.

Throughout evolution, new transcription factors (TFs) emerge by gene duplication, promoting growth and rewiring of transcriptional networks. How TF duplicates diverge was studied in a few cases only. To provide a genome-scale view, we considered the set of budding yeast TFs classified as whole-genome duplication (WGD)-retained paralogs (~35% of all specific TFs). Using high-resolution profiling, we find that ~60% of paralogs evolved differential binding preferences. We show that this divergence results primarily from variations outside the DNA-binding domains (DBDs), while DBD preferences remain largely conserved. Analysis of non-WGD orthologs revealed uneven splitting of ancestral preferences between duplicates, and the preferential acquiring of new targets by the least conserved paralog (biased neo/sub-functionalization). Interactions between paralogs were rare, and, when present, occurred through weak competition for DNA-binding or dependency between dimer-forming paralogs. We discuss the implications of our findings for the evolutionary design of transcriptional networks.

Transcription factors (TFs) must bind at specific genomic locations to accurately regulate gene expression. The ability of TFs to recognize specific DNA sequence motifs arises from the inherent preferences of their globular DNA-binding domains (DBDs). Yet, these preferences are insufficient to explain the in vivo TF binding site selection. TFs are enriched with intrinsically disordered regions (IDRs), most of which are poorly characterized. While not generally considered as determinants of TF binding specificity, IDRs guide protein-protein interactions within transcriptional condensates, and multiple examples exist in which short IDRs flanking the DBD contribute to binding specificity via direct contact with the DNA. We recently reported that long IDRs, present away from the DBD, act as major specificity determinants at the genomic scale. Here, we discuss mechanisms through which IDRs contribute to DNA binding specificity, highlighting the role of long IDRs in dictating the in vivo binding site selection.

Morphogen gradients are known to subdivide a naive cell field into distinct zones of gene expression. Here, we examine whether morphogens can also induce a graded response within such domains. To this end, we explore the role of the Dorsal protein nuclear gradient along the dorsoventral axis in defining the graded pattern of actomyosin constriction that initiates gastrulation in early Drosophila embryos. Two complementary mechanisms for graded accumulation of mRNAs of crucial zygotic Dorsal target genes were identified. First, activation of target-gene expression expands over time from the ventral-most region of high nuclear Dorsal to lateral regions, where the levels are lower, as a result of a Dorsal-dependent activation probability of transcription sites. Thus, sites that are activated earlier will exhibit more mRNA accumulation. Second, once the sites are activated, the rate of RNA Polymerase II loading is also dependent on Dorsal levels. Morphological restrictions require that translation of the graded mRNA be delayed until completion of embryonic cell formation. Such timing is achieved by large introns, which provide a delay in production of the mature mRNAs. Spatiotemporal regulation of key zygotic genes therefore shapes the pattern of gastrulation.

Upon replication stress, budding yeast checkpoint kinase Mec1^ATR triggers the downregulation of transcription, thereby reducing the level of RNA polymerase (RNAP) on chromatin to facilitate replication fork progression. Here, we identify a hydroxyurea-induced phosphorylation site on Mec1, Mec1-S1991, that contributes to the eviction of RNAPII and RNAPIII during replication stress. The expression of the non-phosphorylatable mec1-S1991A mutant reduces replication fork progression genome-wide and compromises survival on hydroxyurea. This defect can be suppressed by destabilizing chromatin-bound RNAPII through a TAP fusion to its Rpb3 subunit, suggesting that lethality in mec1-S1991A mutants arises from replicationtranscription conflicts. Coincident with a failure to repress gene expression on hydroxyurea in mec1-S1991A cells, highly transcribed genes such as GAL1 remain bound at nuclear pores. Consistently, we find that nuclear pore proteins and factors controlling RNAPII and RNAPIII are phosphorylated in a Mec1-dependent manner on hydroxyurea. Moreover, we show that Mec1 kinase also contributes to reduced RNAPII occupancy on chromatin during an unperturbed S phase by promoting degradation of the Rpb1 subunit.

Histone exchange between histones carrying position-specific marks and histones bearing general marks is important for gene regulation, but understanding of histone exchange remains incomplete. To overcome the poor time resolution of conventional pulsechase histone labeling, we present a genetically encoded histone exchange timer sensitive to the duration that two tagged histone subunits co-reside at an individual genomic locus. We apply these sensors to map genome-wide patterns of histone exchange in yeast using single samples. Comparing H3 exchange in cycling and G1-arrested cells suggests that replication-independent H3 exchange occurs at several hundred nucleosomes (

Transcription factors (TFs) regulate gene expression by binding DNA sequences recognized by their DNA-binding domains (DBDs). DBD-recognized motifs are short and highly abundant in genomes. The ability of TFs to bind a specific subset of motif-containing sites, and to do so rapidly upon activation, is fundamental for gene expression in all eukaryotes. Despite extensive interest, our understanding of the TF-target search process is fragmented; although binding specificity and detection speed are two facets of this same process, trade-offs between them are rarely addressed. In this opinion article, we discuss potential speedspecificity trade-offs in the context of existing models. We further discuss the recently described distributed specificity paradigm, suggesting that intrinsically disordered regions (IDRs) promote specificity while reducing the TF-target search time.

Gene regulatory variations accumulate during evolution and alter gene expression. While the importance of expression variation in phenotypic evolution is well established, the molecular basis remains largely unknown. Here, we examine two closely related yeast species, Saccharomyces cerevisiae and Saccharomyces paradoxus, which show phenotypical differences in morphology and cell cycle progression when grown in the same environment. By profiling the cell cycle transcriptome and binding of key transcription factors (TFs) in the two species and their hybrid, we show that changes in expression levels and dynamics of oscillating genes are dominated by upstream trans-variations. We find that multiple cell cycle regulators show both cis- and trans-regulatory variations, which alters their expression in favor of the different cell cycle phenotypes. Moreover, we show that variations in the cell cycle TFs, Fkh1, and Fkh2 affect both the expression of target genes, and the binding specificity of an interacting TF, Ace2. Our study reveals how multiple variations accumulate and propagate through the gene regulatory network, alter TFs binding, contributing to phenotypic changes in cell cycle progression.

The wrapping of DNA around histone octamers challenges processes that use DNA as their template. In vitro, DNA replication through chromatin depends on histone modifiers, raising the possibility that cells modify histones to optimize fork progression. Rtt109 is an acetyl transferase that acetylates histone H3 before its DNA incorporation on the K56 and N-terminal residues. We previously reported that, in budding yeast, a wave of histone H3 K9 acetylation progresses ∼3-5 kb ahead of the replication fork. Whether this wave contributes to replication dynamics remained unknown. Here, we show that the replication fork velocity increases following deletion of RTT109, the gene encoding the enzyme required for the prereplication H3 acetylation wave. By using histone H3 mutants, we find that Rtt109-dependent N-terminal acetylation regulates fork velocity, whereas K56 acetylation contributes to replication dynamics only when N-terminal acetylation is compromised. We propose that acetylation of newly synthesized histones slows replication by promoting replacement of nucleosomes evicted by the incoming fork, thereby protecting genome integrity.

Multicellular organisms develop through a sequence of patterning events, in which cells adopt distinct cell fates. In many instances, patterns are established by morphogen gradients that determine cell fates according to the position of cells within a uniform field. On pages 327 and 321 of this issue, Toda et al. (1) and Stapornwongkul et al. (2), respectively, use synthetic approaches to study morphogen gradients. Why are synthetic approaches helpful? Patterning systems operate in complex biological settings, and synthetic reconstitution isolates and defines the key players. Because the features of such systems depend directly on quantitative parameters, synthetic approaches allow reconstituting systems in which parameters can be precisely tuned and their effects measured with precision. Additionally, the regulation of patterning systems relies on different feedback loops, and synthetic rewiring highlights the logic of the critical circuits. Overall, the key parameters and players can be examined from different angles.

Approximately half of eukaryotic proteins reside in organelles. To reach their correct destination, such proteins harbor targeting signals recognized by dedicated targeting pathways. It has been shown that differences in targeting signals alter the efficiency in which proteins are recognized and targeted. Since multiple proteins compete for any single pathway, such differences can affect the priority for which a protein is catered. However, to date the entire repertoire of proteins with targeting priority, and the mechanisms underlying it, have not been explored for any pathway. Here we developed a systematic tool to study targeting priority and used the Pex5-mediated targeting to yeast peroxisomes as a model. We titrated Pex5 out by expressing high levels of a Pex5-cargo protein and examined how the localization of each peroxisomal protein is affected. We found that while most known Pex5 cargo proteins were outcompeted, several cargo proteins were not affected, implying that they have high targeting priority. This priority group was dependent on metabolic conditions. We dissected the mechanism of priority for these proteins and suggest that targeting priority is governed by different parameters, including binding affinity of the targeting signal to the cargo factor, the number of binding interfaces to the cargo factor, and more. This approach can be modified to study targeting priority in various organelles, cell types, and organisms.

Cell growth is driven by the synthesis of proteins, genes, and other cellular components. Defining processes that limit biosynthesis rates is fundamental for understanding the determinants of cell physiology. Here, we analyze the consequences of engineering cells to express extremely high levels of mCherry proteins, as a tool to define limiting processes that fail to adapt upon increasing biosynthetic demands. Protein-burdened cells were transcriptionally and phenotypically similar to mutants of the Mediator, a transcription coactivator complex. However, our binding data suggest that the Mediator was not depleted from endogenous promoters. Burdened cells showed an overall increase in the abundance of the majority of endogenous transcripts, except for highly expressed genes. Our results, supported by mathematical modeling, suggest that wild-type cells transcribe highly expressed genes at the maximal possible rate, as defined by the transcription machinery's physical properties. We discuss the possible cellular benefit of maximal transcription rates to allow a coordinated optimization of cell size and cell growth.

Transcription factors (TFs) that bind common DNA motifs in vitro occupy distinct sets of promoters in vivo, raising the question of how binding specificity is achieved. TFs are enriched with intrinsically disordered regions (IDRs). Such regions commonly form promiscuous interactions, yet their unique properties might also benefit specific binding-site selection. We examine this using Msn2 and Yap1, TFs of distinct families that contain long IDRs outside their DNA-binding domains. We find that these IDRs are both necessary and sufficient for localizing to the majority of target promoters. This IDR-directed binding does not depend on any localized domain but results from a multitude of weak determinants distributed throughout the entire IDR sequence. Furthermore, IDR specificity is conserved between distant orthologs, suggesting direct interaction with multiple promoters. We propose that distribution of sensing determinants along extended IDRs accelerates binding-site detection by rapidly localizing TFs to broad DNA regions surrounding these sites.

Changes in gene expression drive novel phenotypes, raising interest in how gene expression evolves. In contrast to the static genome, cells modulate gene expression in response to changing environments. Previous comparative studies focused on specific conditions, describing interspecies variation in expression levels, but providing limited information about variation across different conditions. To close this gap, we profiled mRNA levels of two related yeast species in hundreds of conditions and used coexpression analysis to distinguish variation in the dynamic pattern of gene expression from variation in expression levels. The majority of genes whose expression varied between the species maintained a conserved dynamic pattern. Cases of diverged dynamic pattern correspond to genes that were induced under distinct subsets of conditions in the two species. Profiling the interspecific hybrid allowed us to distinguish between genes with predominantly cis- or trans-regulatory variation. We find that trans-varying alleles are dominantly inherited, and that cis-variations are often complemented by variations in trans. Based on these results, we suggest that gene expression diverges primarily through changes in expression levels, but does not alter the pattern by which these levels are dynamically regulated.

Genome replication perturbs the DNA regulatory environment by displacing DNA-bound proteins, replacing nucleosomes, and introducing dosage imbalance between regions replicating at different S-phase stages. Recently, we showed that these effects are integrated to maintain transcription homeostasis: replicated genes increase in dosage, but their expression remains stable due to replication-dependent epigenetic changes that suppress transcription. Here, we examine whether reduced transcription from replicated DNA results from limited accessibility to regulatory factors by measuring the time-resolved binding of RNA polymerase II (Pol II) and specific transcription factors (TFs) to DNA during S phase in budding yeast. We show that the Pol II binding pattern is largely insensitive to DNA dosage, indicating limited binding to replicated DNA. In contrast, binding of three TFs (Reb1, Abf1, and Rap1) to DNA increases with the increasing DNA dosage. We conclude that the replication-specific chromatin environment remains accessible to regulatory factors but suppresses RNA polymerase recruitment.

Buffering variability in morphogen distribution is essential for reproducible patterning. A theoretically proposed class of mechanisms, termed "distal pinning," achieves robustness by combining local sensing of morphogen levels with global modulation of gradient spread. Here, we demonstrate a critical role for morphogen sensing by a gene enhancer, which ultimately determines the final global distribution of the morphogen and enables reproducible patterning. Specifically, we show that, while the pattern of Toll activation in the early Drosophila embryo is robust to gene dosage of its locally produced regulator, WntD, it is sensitive to a single-nucleotide change in the wntD enhancer. Thus, enhancer properties of locally produced WntD directly impinge on the global morphogen profile.

Gene duplication promotes adaptive evolution in two main ways: allowing one duplicate to evolve a new function and splitting ancestral functions between the duplicates. The second scenario may resolve adaptive conflicts that can rise when one gene performs different functions. In an apparent departure from both scenarios, low-expressing transcription factor (TF) duplicates commonly bind to the same DNA motifs and act in overlapping conditions. To examine for possible benefits of this apparent redundancy, we examined the Msn2 and Msn4 duplicates in budding yeast. We show that Msn2,4 function as one unit by inducing the same set of target genes in overlapping conditions. Yet, the two-factor composition allows this unit's expression to be both environmentally responsive and with low noise, resolving an adaptive conflict that limits expression of single genes. We propose that duplication can provide adaptive benefit through cooperation rather than functional divergence, allowing two-factor dynamics with beneficial properties that cannot be achieved by a single gene.

Central to understanding cellular behaviour in multi-cellular organisms is the question of how a cell exits one transcriptional state to adopt and eventually become committed to another. Fibroblast growth factor-extracellular signal-regulated kinase (FGF-ERK) signalling drives differentiation of mouse embryonic stem cells (ES cells) and pre-implantation embryos towards primitive endoderm, and inhibiting ERK supports ES cell self-renewal(1). Paracrine FGF-ERK signalling induces heterogeneity, whereby cells reversibly progress from pluripotency towards primitive endoderm while retaining their capacity to re-enter self-renewal(2). Here we find that ERK reversibly regulates transcription in ES cells by directly affecting enhancer activity without requiring a change in transcription factor binding. ERK triggers the reversible association and disassociation of RNA polymerase II and associated co-factors from genes and enhancers with the mediator component MED24 having an essential role in ERK-dependent transcriptional regulation. Though the binding of mediator components responds directly to signalling, the persistent binding of pluripotency factors to both induced and repressed genes marks them for activation and/or reactivation in response to fluctuations in ERK activity. Among the repressed genes are several core components of the pluripotency network that act to drive their own expression and maintain the ES cell state; if their binding is lost, the ability to reactivate transcription is compromised. Thus, as long as transcription factor occupancy is maintained, so is plasticity, enabling cells to distinguish between transient and sustained signals. If ERK signalling persists, pluripotency transcription factor levels are reduced by protein turnover and irreversible gene silencing and commitment can occur.

Establishment of morphogen gradients in the early Drosophila embryo is challenged by a diffusible extracellular milieu, and by rapid nuclear divisions that occur at the same time. To understand how a sharp gradient is formed within this dynamic environment, we followed the generation of graded nuclear Dorsal protein, the hallmark of pattern formation along the dorso-ventral axis, in live embryos. The dynamics indicate that a sharp extracellular gradient is formed through diffusion-based shuttling of the Spaetzle (Spz) morphogen that progresses through several nuclear divisions. Perturbed shuttling in wntD mutant embryos results in a flat activation peak and aberrant gastrulation. Reentry of Dorsal into the nuclei at the final division cycle plays an instructive role, as the residence time of Dorsal in each nucleus is translated to the amount of zygotic transcript that will be produced, thereby guiding graded accumulation of specific zygotic transcripts that drive patterned gastrulation. We conclude that diffusion-based ligand shuttling, coupled with dynamic readout, establishes a refined pattern within the diffusible environment of early embryos.

Oscillating gene expression is crucial for correct timing and progression through cell cycle. In Saccharomyces cerevisiae, G1 cyclins Cln1-3 are essential drivers of the cell cycle and have an important role for temporal fine-tuning. We measured time-resolved transcriptome-wide gene expression for wild type and cyclin single and double knockouts over cell cycle with and without osmotic stress. Clustering of expression profiles, peak time detection of oscillating genes, integration with transcription factor network dynamics, and assignment to cell cycle phases allowed us to quantify the effect of genetic or stress perturbations on the duration of cell cycle phases. Cln1 and Cln2 showed functional differences, especially affecting later phases. Deletion of Cln3 led to a delay of START followed by normal progression through later phases. Our data and network analysis suggest mutual effects of cyclins with the transcriptional regulators SBF and MBF.

Cells control their size by coordinating cell cycle progression with volume growth. Size control is typically studied at specific cell cycle transitions that are delayed or accelerated depending on size. This focus is well suited for revealing mechanisms acting at these transitions, but neglects the dynamics in other cell cycle phases, and is therefore inherently limited for studying how the characteristic cell size is determined. We address this limitation through a formalism that intuitively visualizes the characteristic size emerging from integrated cell cycle dynamics of individual cells. Applying this formalism to budding yeast, we describe the contributions of the un-budded (G1) and budded (S-G2-M) phase to size adjustments following environmental or genetic perturbations. We show that although the budded phase can be perturbed with little consequences for G1 dynamics, perturbations in G1 propagate to the budded phase. Our study provides an integrated view on cell size determinants in budding yeast.

Biological timers synchronize patterning processes during embryonic development. In the Drosophila embryo, neural progenitors (neuroblasts; NBs) produce a sequence of unique neurons whose identities depend on the sequential expression of temporal transcription factors (TTFs). The stereotypy and precision of NB lineages indicate reproducible TTF timer progression. We combine theory and experiments to define the timer mechanism. The TTF timer is commonly described as a relay of activators, but its regulatory circuit is also consistent with a repressor-decay timer, where TTF expression begins when its repressor decays. Theory shows that repressor-decay timers are more robust to parameter variations than activator-relay timers. This motivated us to experimentally compare the relative importance of the relay and decay interactions in vivo. Comparing WT and mutant NBs at high temporal resolution, we show that the TTF sequence progresses primarily by repressor-decay. We suggest that need for robust performance shapes the evolutionary-selected designs of biological circuits.

DNA replication introduces a dosage imbalance between early and late replicating genes. In budding yeast, buffering gene expression against this imbalance depends on marking replicated DNA by H3K56 acetylation (H3K56ac). Whether additional processes are required for suppressing transcription from H3K56ac-labeled DNA remains unknown. Here, using a database-guided candidate screen, we find that COMPASS, the H3K4 methyltransferase, and its upstream effector, PAF1C, act downstream of H3K56ac to buffer expression. Replicated genes show reduced abundance of the transcription activating mark H3K4me3 and accumulate the transcription inhibitory mark H3K4me2 near transcription start sites. Notably, in hydroxyurea-exposed cells, the S phase checkpoint stabilizes H3K56ac and becomes essential for buffering. We suggest that H3K56ac suppresses transcription of replicated genes by interfering with post-replication recovery of epigenetic marks and assign a new function for the S phase checkpoint in stabilizing this mechanism during persistent dosage imbalance.

Robustness and evolvability are defining properties of biological systems. Robustness promotes reproducibility of central biological functions, primarily by maintaining low mutation frequency and small mutational effects. By contrast, evolvability is possible only when mutations are frequent enough and lead to selectable functional effects. What is the tradeoff between robustness and evolvability? Here, we explore several cellular strategies used to regulate the balance between robustness and evolvability by modulating mutational impact or frequency. These mechanisms span the gene promoter level, biochemical pathways, single cells and whole organism levels. In particular, we discuss a recently discovered mechanism implemented at the single cell level, in which phenotypic stress-persistence and DNA damage are mechanistically coupled. This coupling increases genetic diversity specifically among individual cells that survive harsh conditions, in which evolvability may be beneficial. Taken together, these mechanisms suggest that robustness and the ability to tune mutation effects promote, rather than limit, the capacity to evolve.

During evolution, mutations produce new lineages that gradually diverge in sequence and regulatory properties. Related strains or species can hybridize to produce viable offspring. Hybrids often outperform their parents, producing more biomass or growing more rapidly. This superior performance, termed heterosis, contrasts the more expected clash between the genomes, and has puzzled geneticists and evolutionary biologists for many years. In this review, we describe two classes of models explaining heterosis: the prevailing view attributes heterosis to rapid repair or enhancement of growth promoting pathways. An alternative view attributes heterosis to the impairment of growth-limiting pathways. The two classes are not mutually exclusive and can result from similar types of genetic interactions. We discuss the possible implications of heterosis on tradeoffs in species evolution.

Growing cells are subject to cycles of nutrient depletion and repletion. A shortage of nutrients activates a starvation program that promotes growth in limiting conditions. To examine whether nutrient-deprived cells prepare also for their subsequent recovery, we followed the transcription program activated in budding yeast transferred to low-phosphate media and defined its contribution to cell growth during phosphate limitation and upon recovery. An initial transcription wave was induced by moderate phosphate depletion that did not affect cell growth. A second transcription wave followed when phosphate became growth limiting. The starvation program contributed to growth only in the second, growth-limiting phase. Notably, the early response, activated at moderate depletion, promoted recovery from starvation by increasing phosphate influx upon transfer to rich medium. Our results suggest that cells subject to nutrient depletion prepare not only for growth in the limiting conditions but also for their predicted recovery once nutrients are replenished.

This month: relating single cells to populations (Cao/Packer, Wu/Altschuler, O'Brien, Friedman), an excess of ribosomes (Barkai), human pathology atlas (Uhlen), signatures of feedback (Rahi), and major genome redesign (Baumgart). This month: relating single cells to populations (Cao/Packer, Wu/Altschuler, O'Brien, Friedman), an excess of ribosomes (Barkai), human pathology atlas (Uhlen), signatures of feedback (Rahi), and major genome redesign (Baumgart).

Growing cells coordinate protein translation with metabolic rates. Central to this coordination is ribosome production. Ribosomes drive cell growth, but translation of ribosomal proteins competes with production of non-ribosomal proteins. Theory shows that cell growth is maximized when all expressed ribosomes are constantly translating. To examine whether budding yeast function at this limit of full ribosomal usage, we profiled the proteomes of cells growing in different environments. We find that cells produce excess ribosomal proteins, amounting to a constant ≈8% of the proteome. Accordingly, ≈25% of ribosomal proteins expressed in rapidly growing cells does not contribute to translation. Further, this fraction increases as growth rate decreases and these excess ribosomal proteins are employed when translation demands unexpectedly increase. We suggest that steadily growing cells prepare for conditions that demand increased translation by producing excess ribosomes, at the expense of lower steady-state growth rate.

Keywords: Developmental Biology

Cells grow on a wide range of carbon sources by regulating substrate flow through the metabolic network. Incoming sugar, for example, can be fermented or respired, depending on the carbon identity, cell type, or growth conditions. Despite this genetically-encoded flexibility of carbon metabolism, attempts to exogenously manipulate central carbon flux by rational design have proven difficult, suggesting a robust network structure. To examine this robustness, we characterized the ethanol yield of 411 regulatory and metabolic mutants in budding yeast. The mutants showed little variation in ethanol productivity when grown on glucose or galactose, yet diversity was revealed during growth on xylulose, a rare pentose not widely available in nature. While producing ethanol at high yield, cells grown on xylulose produced ethanol at high yields, yet induced expression of respiratory genes, and were dependent on them. Analysis of mutants that affected ethanol productivity suggested that xylulose fermentation results from metabolic overflow, whereby the flux through glycolysis is higher than the maximal flux that can enter respiration. We suggest that this overflow results from a suboptimal regulatory adjustment of the cells to this unfamiliar carbon source.

Background: The merging of genomes in inter-specific hybrids can result in novel phenotypes, including increased growth rate and biomass yield, a phenomenon known as heterosis. Heterosis is typically viewed as the opposite of hybrid incompatibility. In this view, the superior performance of the hybrid is attributed to heterozygote combinations that compensate for deleterious mutations accumulating in each individual genome, or lead to new, over-dominating interactions with improved performance. Still, only fragmented knowledge is available on genes and processes contributing to heterosis.Results: We describe a budding yeast hybrid that grows faster than both its parents under different environments. Phenotypically, the hybrid progresses more rapidly through cell cycle checkpoints, relieves the repression of respiration in fast growing conditions, does not slow down its growth when presented with ethanol stress, and shows increased signs of DNA damage. A systematic genetic screen identified hundreds of S. cerevisiae alleles whose deletion reduced growth of the hybrid. These growth-affecting alleles were condition-dependent, and differed greatly from alleles that reduced the growth of the S. cerevisiae parent.Conclusions: Our results define a budding yeast hybrid that is perturbed in multiple regulatory processes but still shows a clear growth heterosis. We propose that heterosis results from incompatibilities that perturb regulatory mechanisms, which evolved to protect cells against damage or prepare them for future challenges by limiting cell growth.

Morphogen gradients determine tissue pattern by triggering differential cell responses to distinct morphogen concentrations. The strict quantitative dependence of the emerging patterns on morphogen distribution raises the challenge of buffering variability in morphogen profile to ensure a reproducible outcome. We describe the underlying principles of two modules for buffering morphogen distribution: buffering morphogen amplitude by storing excess morphogen in a limited spatial region, and buffering morphogen spread by pinning morphogen levels at a distal position through global feedback that adjusts morphogen diffusion or degradation across the tissue. We also present concrete examples of patterning systems that implement these modules.

Eukaryotic cells initiate DNA synthesis by sequential firing of hundreds of origins. This ordered replication is described by replication profiles, which measure the DNA content within a cell population. Here, we show that replication dynamics can be deduced from replication profiles of free-cycling cells. While such profiles lack explicit temporal information, they are sensitive to fork velocity and initiation capacity through the passive replication pattern, namely the replication of origins by forks emanating elsewhere. We apply our model-based approach to a compendium of profiles that include most viable budding yeast mutants implicated in replication. Predicted changes in fork velocity or initiation capacity are verified by profiling synchronously replicating cells. Notably, most mutants implicated in late (or early) origin effects are explained by global modulation of fork velocity or initiation capacity. Our approach provides a rigorous framework for analyzing DNA replication profiles of free-cycling cells.

Cells process information using bio-molecular circuits of interacting proteins and genes. A remarkable property of these circuits is their ability to function in highly variable biological environments: Biochemical processes are stochastic, environmental conditions fluctuate, and genetic polymorphisms are abundant. How is variability buffered to maintain a robust output? Can variability be exploited to allow computations not possible by deterministic dynamics? These questions lie at the heart of contemporary systems biology. We argue here that biological variability is fundamental for understanding principles underlying design and function of biological circuits. As concrete examples, we will discuss the buffering of variability during embryonic patterning, and the incorporation of variability in microbial responses to changing conditions.

Mutation rate balances the need to protect genome integrity with the advantage of evolutionary innovations. Microorganisms increase their mutation rate when stressed, perhaps addressing the growing need for evolutionary innovation. Such a strategy, however, is only beneficial under moderate stresses that allow cells to divide and realize their mutagenic potential. In contrast, severe stresses rapidly kill the majority of the population with the exception of a small minority of cells that are in a phenotypically distinct state termed persistence. Although persisters were discovered many decades ago, the stochastic event triggering persistence is poorly understood. We report that spontaneous DNA damage triggers persistence in Saccharomyces cerevisiae by activating the general stress response, providing protection against a range of harsh stress and drug environments. We further show that the persister subpopulation carries an increased load of genetic variants in the form of insertions, deletions or large structural variations, which are unrelated to their stress survival. This coupling of DNA damage to phenotypic persistence may increase genetic diversity specifically in severe stress conditions, where diversity is beneficial but the ability to generate de novo mutations is limited.

Activation of extracellular signal regulated kinase (ERK) is used by many signaling pathways to control tissue patterning in a broad range of multicellular organisms. In this issue of Developmental Cell, Johnson et al. (2017) provide an optogenetic approach to manipulate this pathway with high precision and explore its signaling code.

Tissue stem cells produce a constant flux of differentiated cells with distinct proportions. Here, we show that stem cells in colonic crypts differentiate early to form precisely 1:3 ratio of secretory to absorptive cells. This precision is surprising, as there are only eight stem cells making irreversible fate decisions, and so large stochastic effects of this small pool should have yielded much larger noise in cell proportions. We use single molecule FISH, lineage-tracing mice and simulations to identify the homeostatic mechanisms facilitating robust proportions. We find that Delta-Notch lateral inhibition operates in a restricted spatial zone to reduce initial noise in cell proportions. Increased dwell time and dispersive migration of secretory cells further averages additional variability added during progenitor divisions and breaks up continuous patches of same-fate cells. These noise-reducing mechanisms resolve the trade-off between early commitment and robust differentiation and ensure spatially uniform spread of secretory cells. Our findings may apply to other cases where small progenitor pools expand to give rise to precise tissue cell proportions.

The minimal description of a growing cell consists of self-replicating ribosomes translating the cellular proteome. While neglecting all other cellular components, this model provides key insights into the control and limitations of growth rate. It shows, for example, that growth rate is maximized when ribosomes work at full capacity, explains the linear relation between growth rate and the ribosome fraction of the proteome and defines the maximal possible growth rate. This ribosome-centered model also highlights the challenge of coordinating cell growth with related processes such as cell division or nutrient production. Coordination is promoted when ribosomes don't translate at maximal capacity, as it allows escaping strict exponential growth. Recent data support the notion that multiple cellular processes limit growth. In particular, increasing transcriptional demand may be as deleterious as increasing translational demand, depending on growth conditions. Consistent with the idea of trade-off, cells may forgo maximal growth to enable more efficient interprocess coordination and faster adaptation to changing conditions.

DNA replication perturbs the dosage balance between genes that replicate early during S phase and those that replicate late. If propagated to influence protein content, this dosage imbalance could influence cellular functions. In bacteria, mechanisms have evolved to use this imbalance to tune certain processes with the rate of cell growth. By contrast, eukaryotes buffer this dosage imbalance to ensure gene expression homeostasis also during S phase. Here, we outline classical and more recent studies describing how different organisms deal with this replication-dependent dosage imbalance, and describe recent results linking the eukaryotic buffering mechanism to replication-dependent histone acetylation. Finally, we discuss the possible implications of this buffering mechanism and speculate why it is specific to eukaryote cells.

Chromatin is composed of DNA and histones, which provide a unified platform for regulating DNA-related processes, mostly through their post- Translational modification. During DNA replication, histone arrangement is perturbed, first to allow progression of DNA polymerase and then during repackaging of the replicated DNA. To study how DNA replication influences the pattern of histone modification, we followed the cell-cycle dynamics of 10 histone marks in budding yeast. We find that histones deposited on newly replicatedDNAare modified at different rates: While some marks appear immediately upon replication (e.g., H4K16ac, H3K4me1), others increase with transcription-dependent delays (e.g., H3K4me3, H3K36me3). Notably, H3K9ac was deposited as a wave preceding the replication fork by ∼5-6 kb. This replication-guided H3K9ac was fully dependent on the acetyltransferase Rtt109, while expression-guided H3K9ac was deposited by Gcn5. Further, topoisomerase depletion intensified H3K9ac in front of the replication fork and in sites where RNA polymerase II was trapped, suggesting supercoiling stresses trigger H3K9 acetylation. Our results assign complementary roles for DNA replication and gene expression in defining the pattern of histone modification.

Background: Cells constantly adapt to changes in their environment. When environment shifts between conditions that were previously encountered during the course of evolution, evolutionary-programmed responses are possible. Cells, however, may also encounter a new environment to which a novel response is required. To characterize the first steps in adaptation to a novel condition, we studied budding yeast growth on xylulose, a sugar that is very rarely found in the wild. Results: We previously reported that growth on xylulose induces the expression of amino acid biosynthesis genes in multiple natural yeast isolates. This induction occurs despite the presence of amino acids in the growth medium and is a unique response to xylulose, not triggered by naturally available carbon sources. Propagating these strains for ~300 generations on xylulose significantly improved their growth rate. Notably, the most significant change in gene expression was the loss of amino acid biosynthesis gene induction. Furthermore, the reduction in amino-acid biosynthesis gene expression on xylulose was tightly correlated with the improvement in growth rate, suggesting that internal depletion of amino-acids presented a major bottleneck limiting growth in xylulose. Conclusions: We discuss the possible implications of our results for explaining how cells maintain the balance between supply and demand of amino acids during growth in evolutionary 'familiar' vs. 'novel' conditions.

Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities (noise) inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ∼800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ∼10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this noisy environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design. We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ∼10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations (noise) in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.

Genome replication introduces a stepwise increase in the DNA template available for transcription. Genes replicated early in S phase experience this increase before latereplicating genes, raising the question of how expression levels are affected by DNA replication. We show that in budding yeast, messenger RNA (mRNA) synthesis rate is buffered against changes in gene dosage during S phase. This expression homeostasis depends on acetylation of H3 on its internal K56 site by Rtt109/Asf1. Deleting these factors, mutating H3K56 or up-regulating its deacetylation, increases gene expression in S phase in proportion to gene replication timing. Therefore, H3K56 acetylation on newly deposited histones reduces transcription efficiency from replicated DNA, complementing its role in guarding genome stability. Our study provides molecular insight into the mechanism maintaining expression homeostasis during DNA replication.

Patterning by morphogen gradients relies on the capacity to generate reproducible distribution profiles. Morphogen spread depends on kinetic parameters, including diffusion and degradation rates, which vary between embryos, raising the question of how variability is controlled. We examined this in the context of Toll-dependent dorsoventral (DV) patterning of the Drosophila embryo. We find that low embryo-to-embryo variability in DV patterning relies on wntD, a Toll-target gene expressed initially at the posterior pole. WntD protein is secreted and disperses in the extracellular milieu, associates with its receptor Frizzled4, and inhibits the Toll pathway by blocking the Toll extracellular domain. Mathematical modeling predicts that WntD accumulates until the Toll gradient narrows to its desired spread, and we support this feedback experimentally. This circuit exemplifies a broadly applicable induction-contraction mechanism, which reduces patterning variability through a restricted morphogen-dependent expression of a secreted diffusible inhibitor.

Generation of periodic patterns is fundamental to the differentiation of multiple tissues during development. How such patterns form robustly is still unclear. The Drosophila eye comprises ∼750 units, whose crystalline order is set during differentiation of the eye imaginal disc: an activation wave sweeping across the disc is coupled to lateral inhibition, sequentially selecting pro-neural cells. Using mathematical modelling, here we show that this template-based lateral inhibition is highly sensitive to spatial variations in biochemical parameters and cell sizes. We reveal the basis of this sensitivity, and suggest that it can be overcome by assuming a short-range diffusible activator. Clonal experiments identify Scabrous, a previously implicated inhibitor, as the predicted activator. Our results reveal the mechanism by which periodic patterning in the fly eye is stabilized against spatial variations, highlighting how the need to maintain robustness shapes the design of patterning circuits.

The economy of protein production is central to cell physiology, being intimately linked with cell division rate and cell size. Attempts to model cellular physiology are limited by the scarcity of experimental data defining the molecular processes limiting protein expression. Here, we distinguish the relative contribution of gene transcription and protein translation to the slower proliferation of budding yeast producing excess levels of unneeded proteins. In contrast to widely held assumptions, rapidly growing cells are not universally limited by ribosome content. Rather, transcription dominates cost under some conditions (e.g., low phosphate), translation in others (e.g., low nitrogen), and both in other conditions (e.g., rich media). Furthermore, cells adapted to enforced protein production by becoming larger and increasing their endogenous protein levels, suggesting limited competition for common resources. We propose that rapidly growing cells do not exhaust their resources to maximize growth but maintain sufficient reserves to accommodate changing requirements. Kafri et al. investigate the processes that limit protein production. They find that enforcing either gene transcription or protein translation reduces growth rate, depending on growth conditions. Cells adapt by increasing their size and endogenous proteome content, suggesting that rapidly growing cells are not resource limited.

The extent to which carbon flux is directed toward fermentation versus respiration differs between cell types and environmental conditions. Understanding the basic cellular processes governing carbon flux is challenged by the complexity of the metabolic and regulatory networks. To reveal the genetic basis for natural diversity in channeling carbon flux, we applied quantitative trait loci analysis by phenotyping and genotyping hundreds of individual F2 segregants of budding yeast that differ in their capacity to ferment the pentose sugar xylulose. Causal alleles were mapped to the RXT3 and PHO23 genes, two components of the large Rpd3 histone deacetylation complex. We show that these allelic variants modulate the expression of SNF1/AMPK-dependent respiratory genes. Our results suggest that over close evolutionary distances, diversification of carbon flow is driven by changes in global regulators, rather than adaptation of specific metabolic nodes. Such regulators may improve the ability to direct metabolic fluxes for biotechnological applications.

Chromatin can function as an integrator of DNA-related processes, allowing communication, for example, between DNA replication and gene transcription. Such communication is needed to overcome the gene-dosage imbalance introduced during DNA replication, when certain genes are replicated prior to others. Increased transcription of early replicating genes could alter regulatory balances. This does not occur, suggesting a mechanism that suppresses expression from newly replicated DNA. Critical to this buffering is Rtt109, which acetylates the internal K56 residue of newly synthesized histone H3 prior to incorporation onto DNA. H3K56ac distinguishes replicated from non-replicated DNA, communicating this information to the transcription machinery to ensure expression homeostasis during S phase.

Errors in protein synthesis, so-called phenotypic mutations, are orders-of-magnitude more frequent than genetic mutations. Here, we provide direct evidence that alternative protein forms and phenotypic variability derived from translational errors paved the path to genetic, evolutionary adaptations via gene duplication. We explored the evolutionary origins of Saccharomyces cerevisiae IDP3 - an NADP-dependent isocitrate dehydrogenase mediating fatty acids beta-oxidation in the peroxisome. Following the yeast whole genome duplication, IDP3 diverged from a cytosolic ancestral gene by acquisition of a C-terminal peroxisomal targeting signal. We discovered that the pre-duplicated cytosolic IDPs are partially localized to the peroxisome owing to + 1 translational frameshifts that bypass the stop codon and unveil cryptic peroxisomal targeting signals within the 3'-UTR. Exploring putative cryptic signals in all 3'-UTRs of yeast genomes, we found that other enzymes related to NADPH production such as pyruvate carboxylase 1 (PYC1) might be prone to peroxisomal localization via cryptic signals. Using laboratory evolution we found that these translational frameshifts are rapidly imprinted via genetic single base deletions occurring within the very same gene location. Further, as exemplified here, the sequences that promote translational frameshifts are also more prone to genetic deletions. Thus, genotypes conferring higher phenotypic variability not only meet immediate challenges by unveiling cryptic 3'-UTR sequences, but also boost the potential for future genetic adaptations.

The rate of crossover, the reciprocal exchanges of homologous chromosomal segments, is not uniform along chromosomes differing between male and female meiocytes. To better understand the factors regulating this variable landscape, we performed a detailed genetic and epigenetic analysis of 737 crossover events in Arabidopsis thaliana. Crossovers were more frequent than expected in promoters. Three DNA motifs enriched in crossover regions and less abundant in crossover-poor pericentric regions were identified. One of these motifs, the CCN repeat, was previously unknown in plants. The A-rich motif was preferentially associated with promoters, while the CCN repeat and the CTT repeat motifs were preferentially associated with genes. Analysis of epigenetic modifications around the motifs showed, in most cases, a specific epigenetic architecture. For example, we show that there is a peak of nucleosome occupancy and of H3K4me3 around the CCN and CTT repeat motifs while nucleosome occupancy was lowest around the A-rich motif. Cytosine methylation levels showed a gradual decrease within 2 kb of the three motifs, being lowest at sites where crossover occurred. This landscape was conserved in the decreased DNA methylation1 mutant. In summary, the crossover motifs are associated with epigenetic landscapes corresponding to open chromatin and contributing to the nonuniformity of crossovers in Arabidopsis.

Growing cells adjust their division time with biomass accumulation to maintain growth homeostasis. Size control mechanisms, such as the size checkpoint, provide an inherent coupling of growth and division by gating certain cell cycle transitions based on cell size. We describe genetic manipulations that decouple cell division from cell size, leading to the loss of growth homeostasis, with cells becoming progressively smaller or progressively larger until arresting. This was achieved by modulating glucose influx independently of external glucose. Division rate followed glucose influx, while volume growth was largely defined by external glucose. Therefore, the coordination of size and division observed in wild-type cells reflects tuning of two parallel processes, which is only refined by an inherent feedback-dependent coupling. We present a class of size control models explaining the observed breakdowns of growth homeostasis. Synopsis Live microscopy of individual of cells growing in conditions that decouple nutrient sensing form nutrient influx reveals independent regulation of biomass accumulation and cell division. Two distinct types of arrest are described with implications for models of cell size control. We use genetic manipulations that enable modulating glucose influx independently of external glucose to interrogate the coordination of biomass accumulation and cell division cycle observed under normal conditions. Cell size follows external glucose, whereas division rate is controlled by glucose influx, leading to the loss of growth homeostasis. Cells continuously increase or decrease their size until arresting, challenging existing models of cell size control. Live microscopy of individual of cells growing in conditions that decouple nutrient sensing form nutrient influx reveals independent regulation of biomass accumulation and cell division. Two distinct types of arrest are described with implications for models of cell size control.

Various histone modifications are widely associated with gene expression, but their functional selectivity at individual genes remains to be characterized. Here, we identify widespread differences between genome-wide patterns of two prominent marks, H3K9ac and H3K4me3, in budding yeasts. As well as characteristic gene profiles, relative modification levels vary significantly amongst genes, irrespective of expression. Interestingly, we show that these differences couple to contrasting features: higher methylation to essential, periodically expressed, 'DPN' (Depleted Proximal Nucleosome) genes, and higher acetylation to non-essential, responsive, 'OPN' (Occupied Proximal Nucleosome) genes. Thus, H3K4me3 may generally associate with expression stability, and H3K9ac, with variability. To evaluate this notion, we examine their association with expression divergence between the closely related species, S. cerevisiae and S. paradoxus. Although individually well conserved at orthologous genes, changes between modifications are mostly uncorrelated, indicating largely non-overlapping regulatory mechanisms. Notably, we find that inter-species differences in methylation, but not acetylation, are well correlated with expression changes, thereby proposing H3K4me3 as a candidate regulator of expression divergence. Taken together, our results suggest distinct evolutionary roles for expression-linked modifications, wherein H3K4me3 may contribute to stabilize average expression, whilst H3K9ac associates with more indirect aspects such as responsiveness.

Cellular functionality is tightly coupled to the external environment. The type of nutrients available defines the internal metabolic flow, while their abundance often limits the rate of biomass production and energy available for growth. An abundance of toxins impede upon various aspects of cellular machinery, including metabolic capacity, protein stability or DNA integrity. Over evolutionary time scales, cells may encounter virtually endless environmental states at widely different frequencies. Maintaining optimal functionality in the presence of such external variability is a central evolutionary constraint.

Cells adapt to environmental changes through genetic mutations that stabilize novel phenotypes. Often, this adaptation involves regulatory changes which modulate gene expression. In the budding yeast, ribosomal-related gene expression correlates with cell growth rate across different environments. To examine whether the same relationship between gene expression and growth rate is observed also across natural populations, we measured gene expression, growth rate and ethanol production of twenty-four wild type yeast strains originating from diverse habitats, grown on the pentose sugar xylulose. We found that expression of ribosome-related genes did not correlate with growth rate. Rather, growth rate was correlated with the expression of amino acid biosynthesis genes. Searching other databases, we observed a similar correlation between growth rate and amino-acid biosyntehsis genes in a library of gene deletions. We discuss the implications of our results for understanding how cells coordinate their translation capacity with available nutrient resources.

Scaling of pattern with size has been described and studied for over a century, yet its molecular basis is understood in only a few cases. In a recent, elegant study, Inomata and colleagues proposed a new model explaining how bone morphogenic protein (BMP) activity gradient scales with embryo size in the early Xenopus laevis embryo. We discuss their results in conjunction with an alternative model we proposed previously. The expansion-repression mechanism (ExR) provides a conceptual framework unifying both mechanisms. Results of Inomata and colleagues implicate the chordin-stabilizing protein sizzled as the expander molecule enabling scaling, while we attributed this role to the BMP ligand Admp. The two expanders may work in concert, as suggested by the mathematical model of Inomata et al. We discuss approaches for differentiating the contribution of sizzled and Admp to pattern scaling.

Background: In budding yeast, perturbations that prolong S phase lead to a proportionate delay in the activation times of most origins. The DNA replication checkpoint was implicated in this scaling phenotype, as an intact checkpoint was shown to be required for the delayed activation of late origins in response to hydroxyurea treatment. In support of that, scaling is lost in cells deleted of mrc1, a mediator of the replication checkpoint signal. Mrc1p, however, also plays a role in normal replication. Results: To examine whether the replication checkpoint is required for scaling the replication profile with S phase duration we measured the genome-wide replication profile of different MRC1 alleles that separate its checkpoint function from its role in normal replication, and further analyzed the replication profiles of S phase mutants that are checkpoint deficient. We found that the checkpoint is not required for scaling; rather the unique replication phenotype of mrc1 deleted cells is attributed to the role of Mrc1 in normal replication. This is further supported by the replication profiles of tof1δ which functions together with Mrc1p in normal replication, and by the distinct replication profiles of specific POL2 alleles which differ in their interaction with Mrc1p. Conclusions: We suggest that the slow fork progression in mrc1 deleted cells reduces the likelihood of passive replication leading to the activation of origins that remain mostly dormant in wild-type cells.

Depletion of essential nutrients triggers regulatory programs that prolong cell growth and survival. Starvation- induced processes increase nutrient transport, mobilize nutrient storage, and recycle nutrients between cellular components. This leads to an effective increase in intracellular nutrients, which may act as a negative feedback that downregulates the starvation program. To examine how cells overcome this potential instability, we followed the transcription response of budding yeast transferred to medium lacking phosphate. Genes were induced in two temporal waves. The first wave was stably maintained and persisted even upon phosphate replenishment, indicating a positive feedback loop. This commitment was abolished after 2 hr with the induction of the second expression wave, coinciding with the reduction in cell growth rate. We show that the overall temporal stability of the expression response depends on the sequential pattern of gene induction. Our results emphasize the key role of gene expression dynamics in optimizing cellular adaptation.

Morphogen gradients guide the patterning of tissues and organs during the development of multicellular organisms. In many cases, morphogen signaling is also required for tissue growth. The consequences of this interplay between growth and patterning are not well understood. In the Drosophila wing imaginal disc, the morphogen Dpp guides patterning and is also required for tissue growth. In particular, it was recently reported that cell division in the disc correlates with the temporal increase in Dpp signaling. Here we mathematically model morphogen gradient formation in a growing tissue, accounting also for morphogen advection and dilution. Our analysis defines a new scaling mechanism, which we term the morphogen-dependent division rule (MDDR): when cell division depends on the temporal increase in morphogen signaling, the morphogen gradient scales with the growing tissue size, tissue growth becomes spatially uniform and the tissue naturally attains a finite size. This model is consistent with many properties of the wing disc. However, we find that the MDDR is not consistent with the phenotype of scaling-defective mutants, supporting the view that temporal increase in Dpp signaling is not the driver of cell division during late phases of disc development. More generally, our results show that local coupling of cell division with morphogen signaling can lead to gradient scaling and uniform growth even in the absence of global feedbacks. The MDDR scaling mechanism might be particularly beneficial during rapid proliferation, when global feedbacks are hard to implement.

Cell size is determined by a complex interplay between growth and division, involving multiple cellular pathways. To identify systematically processes affecting size control in G1 in budding yeast, we imaged and analyzed the cell cycle of millions of individual cells representing 591 mutants implicated in size control. Quantitative metric distinguished mutants affecting the mechanism of size control from the majority of mutants that have a perturbed size due to indirect effects modulating cell growth. Overall, we identified 17 negative and dozens positive size control regulators, with the negative regulators forming a small network centered on elements of mitotic exit network. Some elements of the translation machinery affected size control with a notable distinction between the deletions of parts of small and large ribosomal subunit: parts of small ribosomal subunit tended to regulate size control, while parts of the large subunit affected cell growth. Analysis of small cells revealed additional size control mechanism that functions in G2/M, complementing the primary size control in G1. Our study provides new insights about size control mechanisms in budding yeast.

Cells must rapidly adapt to changes in nutrient availability. In budding yeast, limitation of phosphate rapidly induces the expression of the Pho regulon genes [1-4]. This starvation program depends on the transcription factor Pho4, which translocates to the nucleus within minutes when cells are transferred to a low-phosphate medium [5]. Contrasting its rapid induction, we report that the Pho regulon can remain induced for dozens of generations in cells transferred back to high phosphate levels. For example, about 40% of the cells that were starved for 2 hr maintained PHO4-dependent expression for over eleven generations of growing in high phosphate. This commitment to activation of the Pho regulon depends on two feedback loops that reduce internal phosphate, one through induction of the PHM1-4 genes that increase phosphate storage in the vacuoles and the second by induction of SPL2, which reduces incoming flux by inhibiting low-affinity transporters. Noise in SPL2 expression allows stochastic repression of the Pho regulon in committed cells growing at high phosphate, as we demonstrate using a novel method, DAmP multiple copy array (DaMCA), that reduces intrinsic noise in gene expression while maintaining mean abundance. Commitment is an integral part of the dual-transporter motif that helps cells prepare for nutrient depletion.

Morphogen gradients are used to pattern a field of cells according to variations in the concentration of a signaling molecule. Typically, the morphogen emanates from a confined group of cells. During early embryogenesis, however, the ability to define a restricted source for morphogen production is limited. Thus, various early patterning systems rely on a broadly expressed morphogen that generates an activation gradient within its expression domain. Computational and experimental work has shed light on how a sharp and robust gradient can be established under those situations, leading to a mechanism termed 'morphogen shuttling'. This mechanism relies on an extracellular shuttling molecule that forms an inert, highly diffusible complex with the morphogen. Morphogen release from the complex following cleavage of the shuttling molecule by an extracellular protease leads to the accumulation of free ligand at the center of its expression domain and a graded activation of the developmental pathway that decreases significantly even within the morphogen-expression domain.

In this chapter, we focus on budding yeasts, a group of related species, with fully sequenced genomes. Haploids and diploids from these species can propagate asexually or mate to produce hybrids and polyploids. There are no zygotic barriers among budding yeasts. Thus, interspecific hybrids and polyploid yeasts are widespread in nature or in domesticated strains used for the making of wine, beer, cider, biofuel, and bread. This, together with all the advantages of being fast-growing unicellular organisms, makes yeasts ideally suited for contributing to the understanding of evolution in hybrids and polyploids. We describe the insights gained from the analysis of the ancient whole-genome duplication that occurred in yeast approximately 100 million years ago. Namely, we summarize lessons from the nonrandom retention of duplicated loci in the context of sub- and neofunctionalization of genes and of networks of genes and proteins. We discuss how experimental analysis of yeast evolution (a unique feature in the field of polyploidy research) has contributed to the debate on haploid versus diploid polyploid superiority, showing the complexity of the issue. We show how yeast hybrids have been used as tools to study the mechanisms of divergence between species with regard to gene expression, nucleosome occupancy, DNA replication, and RNA stability. Finally, we discuss the challenges and open questions in this field. This edition first published 2013

Accurate models of the cross-talk between signaling pathways and transcriptional regulatory networks within cells are essential to understand complex response programs. We present a new computational method that combines conditionspecific time-series expression data with general protein interaction data to reconstruct dynamic and causal stress response networks. These networks characterize the pathways involved in the response, their time of activation, and the affected genes. The signaling and regulatory components of our networks are linked via a set of common transcription factors that serve as targets in the signaling network and as regulators of the transcriptional response network. Detailed case studies of stress responses in budding yeast demonstrate the predictive power of our method. Our method correctly identifies the core signaling proteins and transcription factors of the response programs. It further predicts the involvement of additional transcription factors and other proteins not previously implicated in the response pathways. We experimentally verify several of these predictions for the osmotic stress response network. Our approach requires little condition-specific data: only a partial set of upstream initiators and time-series gene expression data, which are readily available for many conditions and species. Consequently, our method is widely applicable and can be used to derive accurate, dynamic response models in several species.

We report that when budding yeast are transferred to low-metal environment, they adopt a proliferation pattern in which division is restricted to the subpopulation of mother cells which were born in rich conditions, before the shift. Mother cells continue to divide multiple times following the shift, generating at each division a single daughter cell, which arrests in G1. The transition to a mother-restricted proliferation pattern is characterized by asymmetric segregation of the vacuole to the mother cell and requires the transcription repressor Whi5. Notably, while deletion of WHI5 alleviates daughter cell division arrest in low-zinc conditions, it results in a lower final population size, as cell division rate becomes progressively slower. Our data suggest a new stress-response strategy, in which the dilution of a limiting cellular resource is prevented by maintaining it within a subset of dividing cells, thereby increasing population growth.

Gene expression depends on the frequency of transcription events (burst frequency) and on the number of mRNA molecules made per event (burst size). Both processes are encoded in promoter sequence, yet their dependence on mutations is poorly understood. Theory suggests that burst size and frequency can be distinguished by monitoring the stochastic variation (noise) in gene expression: Increasing burst size will increase mean expression without changing noise, while increasing burst frequency will increase mean expression and decrease noise. To reveal principles by which promoter sequence regulates burst size and frequency, we randomly mutated 22 yeast promoters chosen to span a range of expression and noise levels, generating libraries of hundreds of sequence variants. In each library, mean expression (m) and noise (coefficient of variation, η) varied together, defining a scaling curve: η² = b/m + η_ext². This relation is expected if sequence mutations modulate burst frequency primarily. The estimated burst size (b) differed between promoters, being higher in promoter containing a TATA box and lacking a nucleosome-free region. The rare variants that significantly decreased b were explained by mutations in TATA, or by an insertion of an out-of-frame translation start site. The decrease in burst size due to mutations in TATA was promoter-dependent, but independent of other mutations. These TATA box mutations also modulated the responsiveness of gene expression to changing conditions. Our results suggest that burst size is a promoter-specific property that is relatively robust to sequence mutations but is strongly dependent on the interaction between the TATA box and promoter nucleosomes.

Morphogen gradients pattern tissues and organs during development. When morphogen production is spatially restricted, diffusion and degradation are sufficient to generate sharp concentration gradients. It is less clear how sharp gradients can arise within the source of a broadly expressed morphogen. A recent solution relies on localized production of an inhibitor outside the domain of morphogen production, which effectively redistributes (shuttles) and concentrates the morphogen within its expression domain. Here, we study how a sharp gradient is established without a localized inhibitor, focusing on early dorsoventral patterning of the Drosophila embryo, where an active ligand and its inhibitor are concomitantly generated in a broad ventral domain. Using theory and experiments, we show that a sharp Toll activation gradient is produced through "self-organized shuttling," which dynamically relocalizes inhibitor production to lateral regions, followed by inhibitor-dependent ventral shuttling of the activating ligand Spätzle. Shuttling may represent a general paradigm for patterning early embryos. PaperFlick:

Gene expression shows a significant variation (noise) between genetically identical cells. Noise depends on the gene expression process regulated by the chromatin environment. We screened for chromatin factors that modulate noise in S. cerevisiae and analyzed the results using a theoretical model that infers regulatory mechanisms from the noise versus mean relationship. Distinct activities of the Rpd3(L) and Set3 histone deacetylase complexes were predicted. Both HDACs repressed expression. Yet, Rpd3(L)C decreased the frequency of transcriptional bursts, while Set3C decreased the burst size, as did H2B monoubiquitination (ubH2B). We mapped the acetylation of H3 lysine 9 (H3K9ac) upon deletion of multiple subunits of Set3C and Rpd3(L)C and of ubH2B effectors. ubH2B and Set3C appear to function in the same pathway to reduce the probability that an elongating PolII produces a functional transcript (PolII processivity), while Rpd3(L)C likely represses gene expression at a step preceding elongation.

Primary microRNA cleavage by the Droshag-Dgcr8 'Microprocessor' complex is critical for microRNA biogenesis. Yet, the Microprocessor may also cleave other nuclear RNAs in a nonspecific manner. We studied Microprocessor function using mathematical modeling and experiments in mouse and human tissues. We found that the autoregulatory feedback on Microprocessor expression is instrumental for balancing the efficiency and specificity of its activity by effectively tuning Microprocessor levels to those of its pri-miRNA substrate.

Gene expression diverges rapidly between related species, playing a key role in the evolution of new phenotypes. The extent of divergence differs greatly between genes and is correlated to promoter nucleosome organization. We hypothesized that this may be partially explained by differential sensitivity of expression to mutations in the promoter region. We measured the sensitivity of 22 yeast promoters with varying nucleosome patterns to random mutations in sequence. Mutation sensitivity differed by up to 10-fold between promoters. This difference could not be explained by the abundance of transcription factor binding sites. Rather, mutation sensitivity positively correlated with the relative occupancy of nucleosomes at the proximal promoter region. Furthermore, mutation sensitivity was reduced upon introduction of a binding site for Reb1, a factor that blocks nucleosome formation, suggesting that nucleosome organization directly regulates mutation sensitivity. Our study suggests an important role for chromatin structure in the evolution of gene expression.

Understanding why genes evolve at different rates is fundamental to evolutionary thinking. In species of the budding yeast, the rate at which genes diverge in expression correlates with the organization of their promoter nucleosomes: genes lacking a nucleosome-free region (denoted OPN for "Occupied Proximal Nucleosomes") vary widely between the species, while the expression of those containing NFR (denoted DPN for "Depleted Proximal Nucleosomes") remains largely conserved. To examine if early evolutionary dynamics contributes to this difference in divergence, we artificially selected for high expression of GFP-fused proteins. Surprisingly, selection was equally successful for OPN and DPN genes, with ~80% of genes in each group stably increasing in expression by a similar amount. Notably, the two groups adapted by distinct mechanisms: DPN-selected strains duplicated large genomic regions, while OPN-selected strains favored trans mutations not involving duplications. When selection was removed, DPN (but not OPN) genes reverted rapidly to wild-type expression levels, consistent with their lower diversity between species. Our results suggest that promoter organization constrains the early evolutionary dynamics and in this way biases the path of long-term evolution.

Transcription factors (TFs) bind to specific DNA sequences to induce or repress gene expression. Expression levels can be tuned by changing TF concentrations, but the precision of such tuning is limited, since the fraction of time a TF occupies its binding site is subject to stochastic fluctuations. Bicoid (Bcd) is a TF that patterns the early Drosophila embryo by establishing an anterior-to-posterior concentration gradient and activating specific gene targets ("gap genes") in a concentration-dependent manner. Recently, the Bcd gradient and its in-vivo diffusion were quantified in live embryos, raising a quandary: the precision by which the Bcd target genes are defined (one-cell resolution) appeared to exceed the physical limits set by the stochastic binding of Bcd to DNA. We hypothesize that early readout of Bcd could account for the observed precision. Specifically, we consider the possibility that gap genes begin to be expressed earlier than typically measured experimentally, at a time when the distance between the nuclei is large. At this time, the difference in Bcd concentration between adjacent nuclei is large, enabling better tolerance for measurement imprecision. We show that such early decoding can indeed increase the accuracy of gap-gene expression, and that the initial pattern can be stabilized during subsequent divisions.

Yeast cells approach a mating partner by polarizing along a gradient of mating pheromones that are secreted by cells of the opposite mating type. The Bar1 protease is secreted by a-cells and, paradoxically, degrades the α-factor pheromones which are produced by cells of the opposite mating type and trigger mating in a-cells. This degradation may assist in the recovery from pheromone signaling but has also been shown to play a positive role in mating. Previous studies suggested that widely diffusing protease can bias the pheromone gradient towards the closest secreting cell. Here, we show that restricting the Bar1 protease to the secreting cell itself, preventing its wide diffusion, facilitates discrimination between equivalent mating partners. This may be mostly relevant during spore germination, where most mating events occur in nature.

Cells use transporters of different affinities to regulate nutrient influx. When nutrients are depleted, low-affinity transporters are replaced by high-affinity ones. High-affinity transporters are helpful when concentrations of nutrients are low, but the advantage of reducing their abundance when nutrients are abundant is less clear. When we eliminated such reduced production of the Saccharomyces cerevisiae high-affinity transporters for phosphate and zinc, the elapsed time from the initiation of the starvation program until the lack of nutrients limited growth was shortened, and recovery from starvation was delayed. The latter phenotype was rescued by constitutive activation of the starvation program. Dual-transporter systems appear to prolong preparation for starvation and to facilitate subsequent recovery, which may optimize sensing of nutrient depletion by integrating internal and external information about nutrient availability.

The patterning of multicellular organisms is robust to environmental, genetic, or stochastic fluctuations. Mathematical modeling is instrumental in identifying mechanisms supporting this robustness. The principle of lateral inhibition, whereby a differentiating cell inhibits its neighbors from adopting the same fate, is frequently used for selecting a single cell out of a cluster of equipotent cells. For example, Sensory Organ Precursors (SOP) in the fruit-fly Drosophila implement lateral inhibition by activating the Notch-Delta pathway. We discuss parameters affecting the rate of errors in this process, and the mechanism (inhibitory cis interaction between Notch and Delta) predicted to reduce this error.

Individuals of the same or closely related species can vary substantially in size. Still, the proportions within and between tissues are precisely kept. This adaptation of pattern with size termed scaling, is receiving a growing attention. We review experimental evidence for scaling, and describe theoretical models for mechanisms that scale morphogen gradients. We particularly note the Expansion-Repression mechanism, in which a diffusible molecule that positively regulates the morphogen gradient width is repressed by morphogen signaling. The Expansion-Repression circuit provides scaling in a robust manner and is readily implemented by a host of molecular mechanisms. We suggest means for identifying such a circuit in a system of interest.

To examine the role of nucleosome occupancy in the evolution of gene expression, we measured the genome-wide nucleosome profiles of four yeast species, three belonging to the Saccharomyces sensu stricto lineage and the more distantly related Candida glabrata. Nucleosomes and associated promoter elements at C. glabrata genes are typically shifted upstream by ~20 bp, compared to their orthologs from sensu stricto species. Nonetheless, all species display the same global organization features first described for Saccharomyces cerevisiae: a stereotypical nucleosome organization along genes and a division of promoters into those that contain or lack a pronounced nucleosome-depleted region (NDR), with the latter displaying a more dynamic pattern of gene expression. Despite this global similarity, however, nucleosome occupancy at specific genes diverged extensively between sensu stricto and C. glabrata orthologs (~50 million years). Orthologs with dynamic expression patterns tend to maintain their lack of NDR, but apart from that, sensu stricto and C. glabrata orthologs are nearly as similar in nucleosome occupancy patterns as nonorthologous genes. This extensive divergence in nucleosome occupancy contrasts with a conserved pattern of gene expression. Thus, while some evolutionary changes in nucleosome occupancy contribute to gene expression divergence, nucleosome occupancy often diverges extensively with apparently little impact on gene expression.

Closely related species show a high degree of differences in gene expression, but the functional significance of these differences remains unclear. Similarly, stress responses in yeast typically involve differential expression of numerous genes, and it is unclear how many of these are functionally significant. To address these issues, we compared the expression programs of four yeast species under different growth conditions, and found that the response of these species to stress has diverged extensively. On an individual gene basis, most transcriptional responses are not conserved in any pair of species, and there are very limited common responsesamong all four species. We present evidence that many evolutionary changes in stress responses are compensated either (i) by the response of related genes or (ii) by changes in the basal expression levels of the genes whose responses have diverged. Thus, stress-related genes are often induced upon stress in some species but maintain high levels even in the absence of stress at other species, indicating a transition between induced and constitutive activation. In addition, ∼15% of the stress responses are specific to only one of the four species, with no evidence for compensating effects or stress-related annotations, and these may reflect fortuitous regulation that is unimportant for the stress response (i.e., biological noise). Frequent compensatory changes and biological noise may explain how diverged expression responses support similar physiological responses.

Maintaining a proportionate body plan requires the adjustment or scaling of organ pattern with organ size. Scaling is a general property of developmental systems, yet little is known about its underlying molecular mechanisms. Using theoretical modeling, we examine how the Dpp activation gradient in the Drosophila wing imaginal disc scales with disc size. We predict that scaling is achieved through an expansion-repression mechanism [1] whose mediator is the widely diffusible protein Pentagone (Pent). Central to this mechanism is the repression of pent expression by Dpp signaling, which provides an effective size measurement, and the Pent-dependent expansion of the Dpp gradient, which adjusts the gradient with tissue size. We validate this mechanism experimentally by demonstrating that scaling requires Pent and further, that scaling is abolished when pent is ubiquitously expressed. The expansion-repression circuit can be readily implemented by a variety of molecular interactions, suggesting its general utilization for scaling morphogen gradients during development.

Keywords: Developmental Biology

The process by which transcription factors (TFs) locate specific DNA binding sites is stochastic and as such, is subject to a considerable level of noise. TFs diffuse in the three-dimensional nuclear space, but can also slide along the DNA. It was proposed that this sliding facilitates the TF molecules arriving to their binding site, by effectively reducing the dimensionality of diffusion. However, the possible implications of DNA sliding on the accuracy by which the nuclear concentration of TFs can be estimated were not examined. Here, we calculate the mean and the variance of the number of TFs that bind to their binding site in reduced and partially reduced diffusion dimensionality regimes.We find that a search process which combines three-dimensional diffusion in the nucleus with one-dimensional sliding along the DNA can reduce the noise in TF binding and in this way enables a better estimation of the TF concentration inside the nucleus.

Computational and biological systems are often distributed so that processors (cells) jointly solve a task, without any of them receiving all inputs or observing all outputs. Maximal independent set (MIS) selection is a fundamental distributed computing procedure that seeks to elect a set of local leaders in a network. A variant of this problem is solved during the development of the fly's nervous system, when sensory organ precursor (SOP) cells are chosen. By studying SOP selection, we derived a fast algorithm for MIS selection that combines two attractive features. First, processors do not need to know their degree; second, it has an optimal message complexity while only using one-bit messages. Our findings suggest that simple and efficient algorithms can be developed on the basis of biologically derived insights.

The number of sequenced species is increasing at a staggering rate, calling for new approaches for incorporating evolutionary information in the study of biological mechanisms. Evolutionary conservation is widely used for assigning a function to new proteins and for predicting functional coding or non-coding sequences. Here, we argue for a complementary approach that focuses on the divergence of regulatory programs. Regulatory mechanisms can be learned from patterns of evolutionary divergence in regulatory properties such as gene expression, transcription factor binding or nucleosome positioning. We review examples of this concept using yeast as a model system, and highlight a hybrid-based approach that is highly instrumental in this analysis.

Eukaryotic centromeres are maintained at specific chromosomal sites over many generations. In the budding yeast Saccharomyces cerevisiae, centromeres are genetic elements defined by a DNA sequence that is both necessary and sufficient for function; whereas, in most other eukaryotes, centromeres are maintained by poorly characterized epigenetic mechanisms in which DNA has a less definitive role. Here we use the pathogenic yeast Candida albicans as a model organism to study the DNA replication properties of centromeric DNA. By determining the genome-wide replication timing program of the C. albicans genome, we discovered that each centromere is associated with a replication origin that is the first to fire on its respective chromosome. Importantly, epigenetic formation of new ectopic centromeres (neocentromeres) was accompanied by shifts in replication timing, such that a neocentromere became the first to replicate and became associated with origin recognition complex (ORC) components. Furthermore, changing the level of the centromere-specific histone H3 isoform led to a concomitant change in levels of ORC association with centromere regions, further supporting the idea that centromere proteins determine origin activity. Finally, analysis of centromere-associated DNA revealed a replication-dependent sequence pattern characteristic of constitutively active replication origins. This strand-biased pattern is conserved, together with centromere position, among related strains and species, in a manner independent of primary DNA sequence. Thus, inheritance of centromere position is correlated with a constitutively active origin of replication that fires at a distinct early time. We suggest a model in which the distinct timing of DNA replication serves as an epigenetic mechanism for the inheritance of centromere position.

This is a conversation with Naama Barkai about a Research Article published in the 6 July 2010 issue of Science Signaling.

The pattern of the sensory bristles in the fruit fly Drosophila is remarkably reproducible. Each bristle arises from a sensory organ precursor (SOP) cell that is selected, through a lateral inhibition process, from a cluster of proneural cells. Although this process is well characterized, the mechanism ensuring its robustness remains obscure. Using probabilistic modeling, we defined the sources of error in SOP selection and examined how they depend on the underlying molecular circuit. We found that rapid inhibition of the neural differentiation of nonselected cells, coupled with high cell-to-cell variability in the timing of selection, is crucial for accurate SOP selection. Cell-autonomous interactions (cis interactions) between the Notch receptor and its ligands Delta or Serrate facilitate accurate SOP selection by shortening the effective delay between the time when the inhibitory signal is initiated in one cell and the time when it acts on neighboring cells, suggesting that selection relies on competition between cis and trans interactions of Notch with its ligands. The cis interaction model predicts that the increase in ectopic SOP selections observed with reduced Notch abundance can be compensated for by reducing the abundance of the Notch ligands Delta and Serrate. We validated this prediction experimentally by quantifying the frequency of ectopic bristles in flies carrying heterozygous null mutations of Notch, Delta, or Serrate or combinations of these alleles. We propose that susceptibility to errors distinguishes seemingly equivalent designs of developmental circuits regulating pattern formation.

We describe the DNA replication timing programs of 14 yeast mutants with an extended S phase identified by a novel genome-wide screen. These mutants are associated with the DNA replication machinery, cell-cycle control, and dNTP synthesis and affect different parts of S phase. In 13 of the mutants, origin activation time scales with the duration of S phase. A limited number of origins become inactive in these strains, with inactive origins characterized by small replicons and distributed throughout S phase. In sharp contrast, cells deleted of MRC1, a gene implicated in replication fork stabilization and in the replication checkpoint pathway, maintained wild-type firing times despite over twofold lengthening of S phase. Numerous dormant origins were activated in this mutant. Our data suggest that most perturbations that lengthen S phase affect the entire program of replication timing, rather than a specific subset of origins, maintaining the relative order of origin firing time and delaying firing with relative proportions. Mrc1 emerges as a regulator of this robustness of the replication program.

Background: The positions of nucleosomes along eukaryotic DNA are defined by the local DNA sequence and are further tuned by the activity of chromatin remodelers. While the genome-wide effect of most remodelers has not been described, recent studies in Saccharomyces cerevisiae have shown that Isw2 prevents ectopic expression of anti-sense and suppressed transcripts at gene ends.Results: We examined the genome-wide function of the Isw2 homologue, Isw1, by mapping nucleosome positioning in S. cerevisiae and Saccharomyces paradoxus strains deleted of ISW1. We found that Isw1 functions primarily within coding regions of genes, consistent with its putative role in transcription elongation. Upon deletion of ISW1, mid-coding nucleosomes were shifted upstream (towards the 5' ends) in about half of the genes. Isw1-dependent shifts were correlated with trimethylation of H3K79 and were enriched at genes with internal cryptic initiation sites.Conclusions: Our results suggest a division of labor between Isw1 and Isw2, whereby Isw2 maintains repressive chromatin structure at gene ends while Isw1 has a similar function at mid-coding regions. The differential specificity of the two remodelers may be specified through interactions with particular histone marks.

Despite substantial size variations, proportions of the developing body plan are maintained with a remarkable precision. Little is known about the mechanisms that ensure this adaptation (scaling) of pattern with size. Most models of patterning by morphogen gradients do not support scaling. In contrast, we show that scaling arises naturally in a general feedback topology, in which the range of the morphogen gradient increases with the abundance of some diffusible molecule, whose production, in turn, is repressed by morphogen signaling. We term this mechanism "expansion-repression" and show that it can function within a wide range of biological scenarios. The expansion-repression scaling mechanism is analogous to an integral-feedback controller, a key concept in engineering that is likely to be instrumental also in maintaining biological homeostasis.

Saccharomyces cerevisiae spore germination is the process in which dormant spores resume growth. Upon exposure to glucose and other essential nutrients, the spore gradually loses its spore characteristics and starts acquiring properties of a vegetative cell. Translation and transcription are initiated early in the germination process. Global gene expression analysis has revealed that germination can be divided into two stages prior to the first cell cycle. During the first stage, the transcriptional programme resembles the general response of yeast cells to glucose. During the second stage, the spores sense and respond also to other nutrients than glucose. In addition, genes involved in conjugation are upregulated in germinating spores and mating is initiated before the first mitotic cell cycle. Here, we review the current understanding of the cellular rearrangements and the genes and proteins involved in germination.

Gene expression varies widely between closely related species and strains, yet the genetic basis of most differences is still unknown. Several studies suggested that chromatin regulators have a key role in generating expression diversity, predicting a reduction in the interspecies differences on deletion of genes that influence chromatin structure or modifications. To examine this, we compared the genome-wide expression profiles of two closely related yeast species following the individual deletions of eight chromatin regulators and one transcription factor. In all cases, regulator deletions increased, rather than decreased, the expression differences between the species, revealing hidden genetic variability that was masked in the wild-type backgrounds. This effect was not observed for individual deletions of 11 enzymes involved in central metabolic pathways. The buffered variations were associated with trans differences, as revealed by allele-specific profiling of the interspecific hybrids. Our results support the idea that regulatory proteins serve as capacitors that buffer gene expression against hidden genetic variability.

Gene regulation differs greatly between related species, constituting a major source of phenotypic diversity. Recent studies characterized extensive differences in the gene expression programs of closely related species. In contrast, virtually nothing is known about the evolution of chromatin structure and how it influences the divergence of gene expression. Here, we compare the genome-wide nucleosome positioning of two closely related yeast species and, by profiling their inter-specific hybrid, trace the genetic basis of the observed differences into mutations affecting the local DNA sequences (cis effects) or the upstream regulators (trans effects). The majority (∼70%) of inter-species differences is due to cis effects, leaving a significant contribution (30%) for trans factors. We show that cis effects are well explained by mutations in nucleosome-disfavoring AT-rich sequences, but are not associated with divergence of nucleosome-favoring sequences. Differences in nucleosome positioning propagate to multiple adjacent nucleosomes, supporting the statistical positioning hypothesis, and we provide evidence that nucleosome-free regions, but not the 1 nucleosome, serve as stable border elements. Surprisingly, although we find that differential nucleosome positioning among cell types is strongly correlated with differential expression, this does not seem to be the case for evolutionary changes: divergence of nucleosome positioning is excluded from regulatory elements and is not correlated with gene expression divergence, suggesting a primarily neutral mode of evolution. Our results provide evolutionary insights to the genetic determinants and regulatory function of nucleosome positioning.

In the budding yeast, a large fraction of genes is coordinately regulated with growth rate. We argue that this correlation does not reflect a direct feedback from growth rate to gene expression. Rather, what appears to be a response to growth rate is dominated by environmental sensing. External parameters, such as nutrition or temperature, feed-forward to define gene expression pattern that is tuned to the evolutionary-predicted growth rate. While such a feed-forward strategy requires fine-tuning of signaling mechanisms, and is limited in the range of environments that can be monitored, it enables advanced preparation to physiological changes that predictably occur following environmental switching. The capacity to anticipate and prepare for changing conditions was probably a major selection force during yeast evolution.

Evolutionary changes in gene expression are a main driver of phenotypic evolution. In yeast, genes that have rapidly diverged in expression are associated with particular promoter features, including the presence of a TATA box, a nucleosome-covered promoter and unstable tracts of tandem repeats. Here, we discuss how these promoter properties may confer an inherent capacity for flexibility of expression.

Morphogen gradients play a key role in multiple differentiation processes. Both the formation of the gradient and its interpretation by the receiving cells need to occur at high precision to ensure reproducible patterning. This need for quantitative precision is challenged by fluctuations in the environmental conditions and by variations in the genetic makeup of the developing embryos. We discuss mechanisms that buffer morphogen profiles against variations in gene dosage. Self-enhanced morphogen degradation and pre-steady-state decoding provide general means for buffering the morphogen profile against fluctuations in morphogen production rate. A more specific "shuttling" mechanism, which establishes a sharp and robust activation profile of a widely expressed morphogen, and enables the adjustment of morphogen profile with embryo size, is also described. Finally, we consider the transformation of the smooth gradient profile into sharp borders of gene expression in the signal-receiving cells. The integration theory and experiments are increasingly used, providing key insights into the system-level functioning of the developmental system.

The Spindle Assembly Checkpoint (SAC) is an intracellular mechanism that ensures proper chromosome segregation. By inhibiting Cdc20, a co-factor of the Anaphase Promoting Complex (APC), the checkpoint arrests the cell cycle until all chromosomes are properly attached to the mitotic spindle. Inhibition of Cdc20 is mediated by a conserved network of interacting proteins. The individual functions of these proteins are well characterized, but understanding of their integrated function is still rudimentary. We here describe our attempts to reverse-engineer the SAC network based on gene deletion phenotypes. We begun by formulating a general model of the SAC which enables us to predict the rate of chromosomal missegregation for any putative set of interactions between the SAC proteins. Next the missegregation rates of seven yeast strains are measured in response to the deletion of one or two checkpoint proteins. Finally, we searched for the set of interactions that correctly predicted the observed missegregation rates of all deletion mutants. Remarkably, although based on only seven phenotypes, the consistent network we obtained successfully reproduces many of the known properties of the SAC. Further insights provided by our analysis are discussed.

Keywords: Developmental Biology

During evolution, novel phenotypes emerge through changes in gene expression, but the genetic basis is poorly understood. We compared the allele-specific expression of two yeast species and their hybrid, which allowed us to distinguish changes in regulatory sequences of the gene itself (cis) from changes in upstream regulatory factors (trans). Expression divergence between species was generally due to changes in cis. Divergence in trans reflected a differential response to the environment and explained the tendency of certain genes to diverge rapidly. Hybrid-specific expression, deviating from the parental range, occurred through novel cis-trans interactions or, more often, through modified trans regulation associated with environmental sensing. These results provide insights on the regulatory changes in cis and trans during the divergence of species and upon hybridization.

We discuss mechanisms that enable the scaling of pattern with size during the development of multicellular organisms. Recently, we analyzed scaling in the context of the early Xenopus embryo, focusing on the determination of the dorsal-ventral axis by a gradient of BMP activation. The ability of this system to withstand extreme perturbation was exemplified in classical experiments performed by Hans Spemann in the early 20th century. Quantitative analysis revealed that patterning is governed by a noncanonical 'shuttling-based' mechanism, and defined the feedback enabling the scaling of pattern with size. Robust scaling is due to molecular implementation of an integral-feedback controller, which adjusts the width of the BMP morphogen gradient with the size of the system. We present an 'expansion-repression' feedback topology which generalizes this concept for a wider range of patterning systems, providing a general, and potentially widely applicable model for the robust scaling of morphogen gradients with size.

Chromatin structure is central for the regulation of gene expression, but its genome-wide organization is only beginning to be understood. Here, we examine the connection between patterns of nucleosome occupancy and the capacity to modulate gene expression upon changing conditions, i.e., transcriptional plasticity. By analyzing genome-wide data of nucleosome positioning in yeast, we find that the presence of nucleosomes close to the transcription start site is associated with high transcriptional plasticity, while nucleosomes at more distant upstream positions are negatively correlated with transcriptional plasticity. Based on this, we identify two typical promoter structures associated with low or high plasticity, respectively. The first class is characterized by a relatively large nucleosome-free region close to the start site coupled with well-positioned nucleosomes further upstream, whereas the second class displays a more evenly distributed and dynamic nucleosome positioning, with high occupancy close to the start site. The two classes are further distinguished by multiple promoter features, including histone turnover, binding site locations, H2A.Z occupancy, expression noise, and expression diversity. Analysis of nucleosome positioning in human promoters reproduces the main observations. Our results suggest two distinct strategies for gene regulation by chromatin, which are selectively employed by different genes.

In groundbreaking experiments, Hans Spemann demonstrated that the dorsal part of the amphibian embryo can generate a well-proportioned tadpole, and that a small group of dorsal cells, the 'organizer', can induce a complete and well-proportioned twinned axis when transplanted into a host embryo. Key to organizer function is the localized secretion of inhibitors of bone morphogenetic protein (BMP), which defines a graded BMP activation profile. Although the central proteins involved in shaping this gradient are well characterized, their integrated function, and in particular how pattern scales with size, is not understood. Here we present evidence that in Xenopus, the BMP activity gradient is defined by a 'shuttling-based' mechanism, whereby the BMP ligands are translocated ventrally through their association with the BMP inhibitor Chordin. This shuttling, with feedback repression of the BMP ligand Admp, offers a quantitative explanation to Spemann's observations, and accounts naturally for the scaling of embryo pattern with its size.

We show that, in yeast, the divergence rate of gene expression is not correlated with that of its associated coding sequence. Gene essentiality influences both modes of evolution, but other properties related to protein structure or promoter composition are only correlated with coding-sequence divergence or gene expression divergence, respectively. Based on these findings, we discuss the possibilities of neutral evolution of gene expression and of different modes of evolution in unicellular versus multicellular organisms.

Interactions between genes and proteins are crucial for efficient processing of internal or external signals, but this connectivity also amplifies stochastic fluctuations by propagating noise between components. Linear (unbranched) cascades were shown to exhibit an interplay between the sensitivity to changes in input signals and the ability to buffer noise. We searched for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. Negative feedback can buffer this type of noise, but this buffering comes at the expense of an even greater reduction in signaling sensitivity. By systematically analyzing three-component circuits, we identify positive feedback as a central motif allowing for the buffering of propagated noise while maintaining sensitivity to long-term changes in input signals. We show analytically that noise reduction in the presence of positive feedback results from improved averaging of rapid fluctuations over time, and discuss in detail a particular implementation in the control of nutrient homeostasis in yeast. As the design of biological networks optimizes for multiple constraints, positive feedback can be used to improve sensitivity without a compromise in the ability to buffer propagated noise.

Recent studies have characterized significant differences in the cis-regulatory sequences of related organisms, but the impact of these differences on gene expression remains largely unexplored. Here, we show that most previously identified differences in transcription factor (TF)-binding sequences of yeasts and mammals have no detectable effect on gene expression, suggesting that compensatory mechanisms allow promoters to rapidly evolve while maintaining a stabilized expression pattern. To examine the impact of changes in cis-regulatory elements in a more controlled setting, we compared the genes induced during mating of three yeast species. This response is governed by a single TF (STE12), and variations in its predicted binding sites can indeed account for about half of the observed expression differences. The remaining unexplained differences are correlated with the increased divergence of the sequences that flank the binding sites and an apparent modulation of chromatin structure. Our analysis emphasizes the flexibility of promoter structure, and highlights the interplay between specific binding sites and general chromatin structure in the control of gene expression.

The need to perform sophisticated information processing in an environment that is variable and noisy restricts the functional design of biological networks. We discuss several of the strategies that cells and multicellular organisms have evolved to deal with this demand.

Background: Spore germination in the yeast Saccharomyces cerevisiae is a process in which non-dividing haploid spores re-enter the mitotic cell cycle and resume vegetative growth. To study the signals and pathways underlying spore germination we examined the global changes in gene expression and followed cell-cycle and germination markers during this process. Results: We find that the germination process can be divided into two distinct stages. During the first stage, the induced spores respond only to glucose. The transcription program during this stage recapitulates the general transcription response of yeast cells to glucose. Only during the second phase are the cells able to sense and respond to other nutritional components in the environment. Components of the mitotic machinery are involved in spore germination but in a distinct pattern. In contrast to the mitotic cell cycle, growth-related events during germination are not coordinated with nuclear events and are separately regulated. Thus, genes that are co-induced during G1/S of the mitotic cell cycle, the dynamics of the septin Cdc10 and the kinetics of accumulation of the cyclin Clb2 all exhibit distinct patterns of regulation during spore germination, which allow the separation of cell growth from nuclear events. Conclusion: Taken together, genome-wide expression profiling enables us to follow the progression of spore germination, thus dividing this process into two major stages, and to identify germination-specific regulation of components of the mitotic cell cycle machinery.

Comparative analysis is a fundamental tool in biology. Conservation among species greatly assists the detection and characterization of functional elements, whereas inter-species differences are probably the best indicators of biological adaptation. Traditionally, comparative approaches were applied to the analysis of genomic sequences. With the growing availability of functional genomic data, comparative paradigms are now being extended also to the study of other functional attributes, most notably the gene expression. Here we review recent works applying comparative analysis to large-scale gene expression datasets and discuss the central principles and challenges of such approaches.

In Saccharomyces cerevisiae, transcription factor binding sites are found preferentially ∼100-200 bp upstream of the start codon. Here, we show that this region is associated with rigid DNA in promoters lacking a TATA box, but not in TATA-containing promoters. The association of rigid DNA with transcription factor binding sites is conserved in TATA-less promoters from 11 yeast species, whereas the position of the rigid DNA varies substantially among species. Rigid DNA could influence nucleosome positioning and assist in the assembly of the transcriptional machinery at TATA-less promoters.

Background: DNA microarrays provide the ability to interrogate multiple genes in a single experiment and have revolutionized genomic research. However, the microarray technology suffers from various forms of biases and relatively low reproducibility. A particular source of false data has been described, in which non-random placement of gene probes on the microarray surface is associated with spurious correlations between genes. Results: In order to assess the prevalence of this effect and better understand its origins, we applied an autocorrelation analysis of the relationship between chromosomal position and expression level to a database of over 2000 individual yeast microarray experiments. We show that at least 60% of these experiments exhibit spurious chromosomal position-dependent gene correlations, which nonetheless appear in a stochastic manner within each experimental dataset. Using computer simulations, we show that large spatial biases caused in the microarray hybridization step and independently of printing procedures can exclusively account for the observed spurious correlations, in contrast to previous suggestions. Our data suggest that such biases may generate more than 15% false data per experiment. Importantly, spatial biases are expected to occur regardless of microarray design and over a wide range of microarray platforms, organisms and experimental procedures. Conclusions: Spatial biases comprise a major source of noise in microarray studies; revision of routine experimental practices and normalizations to account for these biases may significantly and comprehensively improve the quality of new as well as existing DNA microarray data.

Background: Gene duplication provides raw material for the generation of new functions, but most duplicates are rapidly lost due to the initial redundancy in gene function. How gene function diversifies following duplication is largely unclear. Previous studies analyzed the diversification of duplicates by characterizing their coding sequence divergence. However, functional divergence can also be attributed to changes in regulatory properties, such as protein localization or expression, which require only minor changes in gene sequence. Results: We developed a novel method to compare expression profiles from different organisms and applied it to analyze the expression divergence of yeast duplicated genes. The expression profiles of Saccharomyces cerevisiae duplicate pairs were compared with those of their pre-duplication orthologs in Candida albicans. Duplicate pairs were classified into two classes, corresponding to symmetric versus asymmetric rates of expression divergence. The latter class includes 43 duplicate pairs in which only one copy has a significant expression similarity to the C. albicans ortholog. These may present cases of regulatory neofunctionalization, as supported also by their dispensability and variability. Conclusion: Duplicated genes may diversify through regulatory neofunctionalization. Notably, the asymmetry of gene sequence evolution and the asymmetry of gene expression evolution are only weakly correlated, underscoring the importance of expression analysis to elucidate the evolution of novel functions.

Cells must adjust their gene expression in order to compete in a constantly changing environment. Two alternative strategies could in principle ensure optimal coordination of gene expression with physiological requirements. First, characters of the internal physiological state, such as growth rate, metabolite levels, or energy availability, could be feedback to tune gene expression. Second, internal needs could be inferred from the external environment, using evolutionary-tuned signaling pathways. Coordination of ribosomal biogenesis with the requirement for protein synthesis is of particular importance, since cells devote a large fraction of their biosynthetic capacity for ribosomal biogenesis. To define the relative contribution of internal vs. external sensing to the regulation of ribosomal biogenesis gene expression in yeast, we subjected S. cerevisiae cells to conditions which decoupled the actual vs. environmentally-expected growth rate. Gene expression followed the environmental signal according to the expected, but not the actual, growth rate. Simultaneous monitoring of gene expression and growth rate in continuous cultures further confirmed that ribosome biogenesis genes responded rapidly to changes in the environments but were oblivious to longer-term changes in growth rate. Our results suggest that the capacity to anticipate and prepare for environmentally-mediated changes in cell growth presented a major selection force during yeast evolution.

Morphogen gradients are established by the localized production and subsequent diffusion of signaling molecules. It is generally assumed that cell fates are induced only after morphogen profiles have reached their steady state. Yet, patterning processes during early development occur rapidly, and tissue patterning may precede the convergence of the gradient to its steady state. Here we consider the implications of pre-steady-state decoding of the Bicoid morphogen gradient for patterning of the anterior-posterior axis of the Drosophila embryo. Quantitative analysis of the shift in the expression domains of several Bicoid targets (gap genes) upon alteration of bcd dosage, as well as a temporal analysis of a reporter for Bicoid activity, suggest that a transient decoding mechanism is employed in this setting. We show that decoding the pre-steady-state morphogen profile can reduce patterning errors caused by fluctuations in the rate of morphogen production. This can explain the surprisingly small shifts in gap and pair-rule gene expression domains observed in response to alterations in bcd dosage.

Background: Doublecortin (DCX) domains serve as protein-interaction platforms. Mutations in members of this protein superfamily are linked to several genetic diseases. Mutations in the human DCX gene result in abnormal neuronal migration, epilepsy, and mental retardation; mutations in RPI are associated with a form of inherited blindness, and DCDC2 has been associated with dyslectic reading disabilities. Results: The DCX-repeat gene family is composed of eleven paralogs in human and in mouse. Its evolution was followed across vertebrates, invertebrates, and was traced to unicellular organisms, thus enabling following evolutionary additions and losses of genes or domains. The N-terminal and C-terminal DCX domains have undergone sub-specialization and divergence. Developmental in situ hybridization data for nine genes was generated. In addition, a novel co-expression analysis for most human and mouse DCX superfamily-genes was performed using high-throughput expression data extracted from Unigene. We performed an in-depth study of a complete gene superfamily using several complimentary methods. Conclusion: This study reveals the existence and conservation of multiple members of the DCX superfamily in different species. Sequence analysis combined with expression analysis is likely to be a useful tool to predict correlations between human disease and mouse models. The sub-specialization of some members due to restricted expression patterns and sequence divergence may explain the successful addition of genes to this family throughout evolution.

Phenotypic diversity is generated through changes in gene structure or gene regulation. The availability of full genomic sequences allows for the analysis of gene sequence evolution. In contrast, little is known about the principles driving the evolution of gene expression. Here we describe the differential transcriptional response of four closely related yeast species to a variety of environmental stresses. Genes containing a TATA box in their promoters show an increased interspecies variability in expression, independent of their functional association. Examining additional data sets, we find that this enhanced expression divergence of TATA-containing genes is consistent across all eukaryotes studied to date, including nematodes, fruit flies, plants and mammals. TATA-dependent regulation may enhance the sensitivity of gene expression to genetic perturbations, thus facilitating expression divergence at particular genetic loci.

Noise in gene expression is generated at multiple levels, such as transcription and translation, chromatin remodeling and pathway-specific regulation. Studies of individual promoters have suggested different dominating noise sources, raising the question of whether a general trend exists across a large number of genes and conditions. We examined the variation in the expression levels of 43 Saccharomyces cerevisiae proteins, in cells grown under 11 experimental conditions. For all classes of genes and under all conditions, the expression variance was approximately proportional to the mean; the same scaling was observed at steady state and during the transient responses to the perturbations. Theoretical analysis suggests that this scaling behavior reflects variability in mRNA copy number, resulting from random 'birth and death' of mRNA molecules or from promoter fluctuations. Deviation of coexpressed genes from this general trend, including high noise in stress-related genes and low noise in proteasomal genes, may indicate fluctuations in pathway-specific regulators or a differential activation pattern of the underlying gene promoters.

Genetically identical cells vary in the amount of expressed proteins even when growing under the same conditions. It is not yet clear how cellular information processing copes with such stochastic fluctuations in protein levels. Here we examine the capacity of the spindle assembly checkpoint to buffer temporal fluctuations in the expression of Cdc20, a critical checkpoint target whose activity is inhibited to prevent premature cell cycle progression. Using mathematical modeling, we demonstrate that the checkpoint can buffer significant fluctuations in Cdc20 production rate. Critical to this buffering capacity is the use of sequestering-based mechanism for inhibiting Cdc20, as apposed to inhibition by enhancing protein degradation. We propose that the design of biological networks is limited by the need to overcome noise in gene expression.

The doublecortin-like (DCX) domains serve as protein-interaction platforms. DCX tandem domains appear in the product of the X-linked doublecortin (DCX) gene, in retinitis pigmentosa-1 (RP1), as well as in other gene products. Mutations in the human DCX gene are associated with abnormal neuronal migration, epilepsy, and mental retardation; mutations in RP1 are associated with a form of inherited blindness, while DCDC2 has been associated with dyslectic reading disabilities. Motivated by the possible importance of this gene family, a thorough analysis to detect all family members in the mouse was conducted. The DCX-repeat gene superfamily is composed of eleven paralogs, and we cloned the DCX domains from nine different genes. Our study questioned which functions attributed to the DCX domain, are conserved among the different members. Our results suggest that the proteins with the DCX-domain have conserved and unique roles in microtubule regulation and signal transduction. All the tested proteins stimulated microtubule assembly in vitro. Proteins with tandem repeats stabilized the microtubule cytoskeleton in transfected cells, while those with single repeats localized to actin-rich subcellular structures, or the nucleus. All tested proteins interacted with components of the JNK/MAP-kinase pathway, while only a subset interacted with Neurabin 2, and a nonoverlapping group demonstrated actin association. The sub-specialization of some members due to confined intracellular localization, and protein interactions may explain the success of this superfamily.

Background: Meiosis in budding yeast is coupled to the process of sporulation, where the four haploid nuclei are packaged into a gamete. This differentiation process is characterized by a point of transition, termed commitment, when it becomes independent of the environment. Not much is known about the mechanisms underlying commitment, but it is often assumed that positive feedback loops stabilize the underlying gene-expression cascade. Results: We describe the gene-expression program of committed cells. Sporulating cells were transferred back to growth medium at different stages of the process, and their transcription response was characterized. Most sporulation-induced genes were immediately downregulated upon transfer, even in committed cells that continued to sporulate. Focusing on the metabolic-related transcription response, we observed that pre-committed cells, as well as mature spores, responded to the transfer to growth medium in essentially the same way that vegetative cells responded to glucose. In contrast, committed cells elicited a dramatically different response. Conclusion: Our results suggest that cells ensure commitment to sporulation not by stabilizing the process, but by modulating their gene-expression program in an active manner. This unique transcriptional program may optimize sporulation in an environment-specific manner.

Variation in gene expression levels on a genomic scale has been detected among different strains, among closely related species, and within populations of genetically identical cells. What are the driving forces that lead to expression divergence in some genes and conserved expression in others? Here we employ flux balance analysis to address this question for metabolic genes. We consider the genome-scale metabolic model of Saccharomyces cerevisiae, and its entire space of optimal and near-optimal flux distributions. We show that this space reveals underlying evolutionary constraints on expression regulation, as well as on the conservation of the underlying gene sequences. Genes that have a high range of optimal flux levels tend to display divergent expression levels among different yeast strains and species. This suggests that gene regulation has diverged in those parts of the metabolic network that are less constrained. In addition, we show that genes that are active in a large fraction of the space of optimal solutions tend to have conserved sequences. This supports the possibility that there is less selective pressure to maintain genes that are relevant for only a small number of metabolic states.

Current models of morphogen-induced patterning assume that morphogens undergo normal, or Fickian, diffusion, although the validity of this assumption has never been examined. Here we argue that the interaction of morphogens with the complex extracellular surrounding may lead to anomalous diffusion. We present a phenomenological model that captures this interaction, and derive the properties of the morphogen profile under conditions of anomalous (non-Fickian) diffusion. In this context we consider the continuous time random walk formalism and extend its application to account for degradation of morphogen particles. We show that within the anomalous diffusion model, morphogen profiles are fundamentally distinct from the corresponding Fickian profiles. Differences were found in several key aspects, including the role of degradation in determining the profile, the rate by which it spreads in time and its long-term behavior. We analyze the effect of an abrupt change in the extracellular environment on the concentration profiles. Furthermore, we discuss the robustness of the morphogen distribution to fluctuations in morphogen production rate, and describe a feedback mechanism that can buffer such fluctuations. Our study also provides rigorous criteria to distinguish experimentally between Fickian and anomalous modes of morphogen transport.

Recent experiments revealed large-scale differences in the transcription programs of related species, yet little is known about the genetic basis underlying the evolution of gene expression and its contribution to phenotypic diversity. Here we describe a large-scale modulation of the yeast transcription program that is connected to the emergence of the capacity for rapid anaerobic growth. Genes coding for mitochondrial and cytoplasmic ribosomal proteins display a strongly correlated expression pattern in Candida albicans, but this correlation is lost in the fermentative yeast Saccharomyces cerevisiae. We provide evidence that this change in gene expression is connected to the loss of a specific cis-regulatory element from dozens of genes following the apparent whole-genome duplication event. Our results shed new light on the genetic mechanisms underlying the large-scale evolution of transcriptional networks.

Background: The need to execute a sequence of events in an orderly and timely manner is central to many biological processes, including cell cycle progression and cell differentiation. For self-perpetuating systems, such as the cell cycle oscillator, delay times between events are defined by the network of interacting proteins that propagates the system. However, protein levels inside cells are subject to genetic and environmental fluctuations, raising the question of how reliable timing is maintained. Results: We compared the robustness of different mechanisms for encoding delay times to fluctuations in protein expression levels. Gradual accumulation and gradual decay of a regulatory protein have an equivalent capacity for defining delay times. Yet, we find that the former is highly sensitive to fluctuations in gene dosage, while the latter can buffer such perturbations. In particular, a positive feedback where the degrading protein auto-enhances its own degradation may render delay times practically insensitive to gene dosage. Conclusion: While our understanding of biological timing mechanisms is still rudimentary, it is clear that there is an ample use of degradation as well as self-enhanced degradation in processes such as cell cycle and circadian clocks. We propose that degradation processes, and specifically self-enhanced degradation, will be preferred in processes where maintaining the robustness of timing is important.

The mitotic spindle checkpoint halts the cell cycle until all chromosomes are attached to the mitotic spindles. Evidence suggests that the checkpoint prevents cell-cycle progression by inhibiting the activity of the APC-Cdc20 complex, but the precise mechanism underlying this inhibition is not yet known. Here, we use mathematical modeling to compare several mechanisms that could account for this inhibition. We describe the interplay between the capacities to strongly inhibit cell-cycle progression before spindle attachment on one hand and to rapidly resume cell-cycle progression once the last kinetochore is attached on the other hand. We find that inhibition that is restricted to the kinetochore region is not sufficient for supporting both requirements when realistic diffusion constants are considered. A mechanism that amplifies the checkpoint signal through autocatalyzed inhibition is also insufficient. In contrast, amplifying the signal through the release of a diffusible inhibitory complex can support reliable checkpoint function. Our results suggest that the design of the spindle checkpoint network is limited by physical constraints imposed by realistic diffusion constants and the relevant spatial and temporal dimensions where computation is performed.

Background: High-throughput methods identify an overwhelming number of protein-protein interactions. However, the limited accuracy of these methods results in the false identification of many spurious interactions. Accordingly, the resulting interactions are regarded as hypothetical and computational methods are needed to increase their confidence. Several methods have recently been suggested for this purpose including co-expression as a confidence measure for interacting proteins, but their performance is still quite poor. Results: We introduce a novel computational method for verification of protein-protein interactions based on the co-expression of orthologs of interacting partners. The performance of our method is analysed using known S. cerevisiae interactions, and is shown to overcome limitations of previous methods. We present specific examples of known and putative interactions that are detected by our method and not by previous methods, and suggest that they represent transient interactions that might have been conserved and stabilized in other species. Conclusion: Co-expression of orthologous protein-pairs can be used to increase the confidence of hypothetical protein-protein interactions in S. cerevisiae as well as in other species. This approach may be especially useful for species with no available expression profiles and for transient interactions.

Generating clones of mutated cells within a wild-type tissue is a powerful experimental paradigm for elucidating gene function. Recently, this approach was employed for identifying genes that shape morphogen profiles in the Drosophila wing-imaginal disc. Interpreting such experiments poses a theoretical challenge. We present a general framework that links specific features of the morphogen profile in the clone vicinity to three basic morphogen properties: diffusion, degradation, and binding to immobile elements. Our results provide rigorous criteria to examine existing data and can facilitate the design and interpretation of future clone experiments.

Differences in gene expression underlie many of the phenotypic variations between related organisms, yet approaches to characterize such differences on a genome-wide scale are not well developed. Here, we introduce the "differential clustering algorithm" for revealing conserved and diverged co-expression patterns. Our approach is applied at different levels of organization, ranging from pair-wise correlations within specific groups of functionally linked genes, to higher-order correlations between such groups. Using the differential clustering algorithm, we systematically compared the transcription program of the fungal pathogen Candida albicans with that of the model organism Saccharomyces cerevisiae. Many of the identified differences are related to the differential requirement for mitochondrial function in the two yeasts. Distinct regulation patterns of cell cycle genes and of amino acid metabolic genes were also revealed and, in some cases, could be linked to the differential appearance of cis-regulatory elements in the gene promoter regions. Our study provides a comprehensive framework for comparative gene expression analysis and a rich source of hypotheses for uncharacterized open reading frames and putative cis-regulatory elements in C. albicans. Copyright:

: BACKGROUND: Transcription factors regulate gene expression by binding to specific cis-regulatory elements in gene promoters. Although DNA sequences that serve as transcription-factor binding sites have been characterized and associated with the regulation of numerous genes, the principles that govern the design and evolution of such sites are poorly understood. RESULTS: Using the comprehensive mapping of binding-site locations available in Saccharomyces cerevisiae, we examined possible factors that may have an impact on binding-site design. We found that binding sites tend to be shorter and fuzzier when they appear in promoter regions that bind multiple transcription factors. We further found that essential genes bind relatively fewer transcription factors, as do divergent promoters. We provide evidence that novel binding sites tend to appear in specific promoters that are already associated with multiple sites. CONCLUSION: Two principal models may account for the observed correlations. First, it may be that the interaction between multiple factors compensates for the decreased specificity of each specific binding sequence. In such a scenario, binding-site fuzziness is a consequence of the presence of multiple binding sites. Second, binding sites may tend to appear in promoter regions that are subject to low selective pressure, which also allows for fuzzier motifs. The latter possibility may account for the relatively low number of binding sites found in promoters of essential genes and in divergent promoters.

Translating a graded morphogen distribution into tight response borders is central to all developmental processes. Yet, the molecular mechanisms generating such behavior are poorly understood. During patterning of the Drosophila embryonic ventral ectoderm, a graded mitogen-activated protein kinase (MAPK) activation is converted into an all-or-none degradation switch of the Yan transcriptional repressor. Replacing the cardinal phosphorylated amino acid of Yan by a phosphomimetic residue allowed its degradation in a MAPK-independent manner, consistent with Yan phosphorylation being the critical event in generating the switch. Several alternative threshold mechanisms that could, in principle, be realized by this phosphorylation, including first order, cooperativity, positive feedback and zero-order ultrasensitivity, were analyzed. We found that they can be distinguished by their kinetics and steady-state responses to Yan overexpression. In agreement with the predictions for zero-order kinetics, an increase in Yan levels did not shift the degradation border, but significantly elevated the time required to reach steady state. We propose that a reversible loop of Yan phosphorylation implements a zero-order ultrasensitivity-like threshold mechanism, with the capacity to form sharp thresholds that are independent of the level of Yan.

Motivation: Large-scale gene expression data comprising a variety of cellular conditions hold the promise of a global view on the transcription program. While conventional clustering algorithms have been successfully applied to smaller datasets, the utility of many algorithms for the analysis of large-scale data is limited by their inability to capture combinatorial and condition-specific co-regulation. In addition, there is an increasing need to integrate the rapidly accumulating body of other high-throughput biological data with the expression analysis. In a previous work, we introduced the signature algorithm, which overcomes the problems of conventional clustering and allows for intuitive integration of additional biological data. However, this approach is constrained by the comprehensiveness of relevant external data and its lacking ability to capture hierarchical modularity. Methods: We present a novel method for the analysis of large-scale expression data, which assigns genes into context-dependent and potentially overlapping regulatory units. We introduce the notion of a transcription module as a self-consistent regulatory unit consisting of a set of co-regulated genes as well as the experimental conditions that induce their co-regulation. Self-consistency is defined by a rigorous mathematical criterion. We propose an efficient algorithm to identify such modules, which is based on the iterative application of the signature algorithm. A threshold parameter that determines the resolution of the modular decomposition is introduced. Results: The method is applied systematically to over 1000 expression profiles of the yeast Saccharomyces cerevisiae, and the results are presented using two complementary visualization schemes we developed. The average biological coherence, as measured by the conservation of putative cis-regulatory motifs between four related yeast species, is higher for transcription modules than for clusters identified by other methods applied to the same dataset. Our method is related to singular value decomposition (SVD) and to the pairwise average linkage clustering algorithm. It extends SVD by filtering out noise in the expression data and offering variable resolution to reveal hierarchical organization. It furthermore has the advantage over both methods of capturing overlapping modules in the presence of combinatorial regulation.

Morphogen gradients play a pivotal role in most phases of developmental patterning. To ensure proper patterning, reproducible gradients are established under diverse environmental conditions and genetic backgrounds. We refer to the capacity to buffer fluctuations in gene dosage or environmental conditions as 'robustness'. By theoretical analysis of mechanisms that facilitate robustness, it is possible to unravel the machinery responsible for generating the spatial distribution of morphogens.

Cellular networks are subject to extensive regulation, which modifies the availability and efficiency of connections between components in response to external conditions. Thus far, studies of large-scale networks have focused on their connectivity, but have not considered how the modulation of this connectivity might also determine network properties. To address this issue, we analyzed how the coordinated expression of enzymes shapes the metabolic network of Saccharomyces cerevisiae. By integrating large-scale expression data with the structural description of the metabolic network, we systematically characterized the transcriptional regulation of metabolic pathways. The analysis revealed recurrent patterns, which may represent design principles of metabolic gene regulation. First, we find that transcription regulation biases metabolic flow toward linearity by coexpressing only distinct branches at metabolic branchpoints. Second, individual isozymes were often separately coregulated with distinct processes, providing a means of reducing crosstalk between pathways using a common reaction. Finally, transcriptional regulation defined a hierarchical organization of metabolic pathways into groups of varying expression coherence. These results emphasize the utility of incorporating regulatory information when analyzing properties of large-scale cellular networks.

Comparing genomic properties of different organisms is of fundamental importance in the study of biological and evolutionary principles. Although differences among organisms are often attributed to differential gene expression, genome-wide comparative analysis thus far has been based primarily on genomic sequence information. We present a comparative study of large datasets of expression profiles from six evolutionarily distant organisms: S. cerevisiae, C. elegans, E. coli, A. thaliana, D. melanogaster, and H. sapiens. We use genomic sequence information to connect these data and compare global and modular properties of the transcription programs. Linking genes whose expression profiles are similar, we find that for all organisms the connectivity distribution follows a power-law, highly connected genes tend to be essential and conserved, and the expression program is highly modular. We reveal the modular structure by decomposing each set of expression data into coexpressed modules. Functionally related sets of genes are frequently coexpressed in multiple organisms. Yet their relative importance to the transcription program and their regulatory relationships vary among organisms. Our results demonstrate the potential of combining sequence and expression data for improving functional gene annotation and expanding our understanding of how gene expression and diversity evolved.

Morphogen gradients provide long-range positional information by extending across a developing field. To ensure reproducible patterning, their profile is invariable despite genetic or environmental fluctuations. Common models assume a morphogen profile that decays exponentially. Here, we show that exponential profiles cannot, at the same time, buffer fluctuations in morphogen production rate and define long-range gradients. To comply with both requirements, morphogens should decay rapidly close to their source but at a significantly slower rate over most of the field. Numerical search revealed two network designs that support robustness to fluctuations in morphogen production rate. In both cases, morphogens enhance their own degradation, leading to a higher degradation rate close to their source. This is achieved through reciprocal interactions between the morphogen and its receptor. The two robust networks are consistent with properties of the Wg and Hh morphogens in the Drosophila wing disc and provide novel insights into their function.

We present an approach for the analysis of genome-wide expression data. Our method is designed to overcome the limitations of traditional techniques, when applied to large-scale data. Rather than alloting each gene to a single cluster, we assign both genes and conditions to context-dependent and potentially overlapping transcription modules. We provide a rigorous definition of a transcription module as the object to be retrieved from the expression data. An efficient algorithm, which searches for the modules encoded in the data by iteratively refining sets of genes and conditions until they match this definition, is established. Each iteration involves a linear map, induced by the normalized expression matrix, followed by the application of a threshold function. We argue that our method is in fact a generalization of singular value decomposition, which corresponds to the special case where no threshold is applied. We show analytically that for noisy expression data our approach leads to better classification due to the implementation of the threshold. This result is confirmed by numerical analyses based on in silico expression data. We discuss briefly results obtained by applying our algorithm to expression data from the yeast Saccharomyces cerevisiae.

Standard clustering methods can classify genes successfully when applied to relatively small data sets, but have limited use in the analysis of large-scale expression data, mainly owing to their assignment of a gene to a single cluster. Here we propose an alternative method for the global analysis of genome-wide expression data. Our approach assigns genes to context-dependent and potentially overlapping 'transcription modules', thus overcoming the main limitations of traditional clustering methods. We use our method to elucidate regulatory properties of cellular pathways and to characterize cis-regulatory elements. By applying our algorithm systematically to all of the available expression data on Saccharomyces cerevisiae, we identify a comprehensive set of overlapping transcriptional modules. Our results provide functional predictions for numerous genes, identify relations between modules and present a global view on the transcriptional network.

The EGF receptor pathway patterns the Drosophila egg and specifies the position of its dorsal appendages. A new mathematical analysis of this patterning network has highlighted its crucial features and provided novel insights into the spatial and temporal kinetics controlling patterning.

A wide range of organisms use circadian clocks to keep internal sense of daily time and regulate their behavior accordingly. Most of these clocks use intracellular genetic networks based on positive and negative regulatory elements. The integration of these "circuits" at the cellular level imposes strong constraints on their functioning and design. Here, we study a recently proposed model [Barkai, N. & Leibler, S. (2000) Nature (London), 403, 267-268] that incorporates just the essential elements found experimentally. We show that this type of oscillator is driven mainly by two elements: the concentration of a repressor protein and the dynamics of an activator protein forming an inactive complex with the repressor. Thus, the clock does not need to rely on mRNA dynamics to oscillate, which makes it especially resistant to fluctuations. Oscillations can be present even when the time average of the number of mRNA molecules goes below one. Under some conditions, this oscillator is not only resistant to but, paradoxically, also enhanced by the intrinsic biochemical noise.

Networks of interacting proteins orchestrate the responses of living cells to a variety of external stimuli, but how sensitive is the functioning of these protein networks to variations in their biochemical parameters? One possibility is that to achieve appropriate function, the reaction rate constants and enzyme concentrations need to be adjusted in a precise manner, and any deviation from these 'fine-tuned' values ruins the network's performance. An alternative possibility is that key properties of biochemical networks are robust; that is, they are insensitive to the precise values of the biochemical parameters. Here we address this issue in experiments using chemotaxis of Escherichia coli, one of the best-characterized sensory systems. We focus on how response and adaptation to attractant signals vary with systematic changes in the intracellular concentration of the components of the chemotaxis network. We find that some properties, such as steady- state behaviour and adaptation time, show strong variations in response to varying protein concentrations. In contrast, the precision of adaptation is robust and does not vary with the protein concentrations. This is consistent with a recently proposed molecular mechanism for exact adaptation, where robustness is a direct consequence of the network's architecture.