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Abstract 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 occupancy and exchange pattern of canonical and non-canonical histone variants in mouse embryonic stem cells by genetically encoded exchange sensors. 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 occupancy and little exchange of H3.3 in these regions. This unexpected association between H3.3 occupancy and exchange of canonical variants is also evident in active promoters and enhancers, and further validated by reduced H3.1 dynamics following depletion of H3.3-specific chaperone, HIRA. Finally, analyzing transgenic mice harboring H3.1 or H3.3 sensors demonstrates the vast potential of this system for studying histone exchange and its impact on gene expression regulation in vivo.

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.

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.

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.

Summary: 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. : During genome replication, mRNA synthesis from replicated genes is inhibited. Bar-Ziv et al. find that transcription factors (TFs) are recruited to replicated promoters but RNA polymerase II (Pol II) binding is buffered. Their work suggests that the unique chromatin environment during DNA replication limits the ability of TFs to recruit Pol II. Keywords: transcription, replication, chromatin, DNA, transcription factor, RNA polymerase

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.

Abstract 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.

Abstract 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.

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.

Summary: 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. : Jonas et al. develop a visual framework to understand the emergence of cell size from the cooperation of multiple size control mechanisms during the cell cycle. With this framework they analyze the size changes after environmental and genetic perturbations and probe the interaction between size control at different cell cycle phases. Keywords: cell size, dynamical systems, single cell, cell cycle, S. cerevisiae

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.

Patterning in the Drosophila eye is achieved by a series of signalling cascades over several cell distances. Here Gavish et al.model lateral inhibition in the developing eye to understand how developmental noise refines such patterning, identifying a novel activator required for buffering spatial variability.

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.

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.

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.

Abstract 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.

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.

Abstract 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.

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.

Abstract 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.

Abstract 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.

Abstract 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.

Abstract 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.

Abstract 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.

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 ß-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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.