Gene expression from random libraries of yeast promoters

Massively Parallel Assays and Quantitative Sequence-Function Relationships

Over the last decade, a rich variety of massively parallel assays have revolutionized our understanding of how biological sequences encode quantitative molecular phenotypes. These assays include deep mutational scanning, high-throughput SELEX, and massively parallel reporter assays. Here, we review these experimental methods and how the data they produce can be used to quantitatively model sequence-function relationships. In doing so, we touch on a diverse range of topics, including the identification of clinically relevant genomic variants, the modeling of transcription factor binding to DNA, the functional and evolutionary landscapes of proteins, and cis-regulatory mechanisms in both transcription and mRNA splicing. We further describe a unified conceptual framework and a core set of mathematical modeling strategies that studies in these diverse areas can make use of. Finally, we highlight key aspects of experimental design and mathematical modeling that are important for the results of such studies to be interpretable and reproducible.

The development and characterization of synthetic minimal yeast promoters

Synthetic promoters, especially minimally sized, are critical for advancing fungal synthetic biology. Fungal promoters often span hundreds of base pairs, nearly ten times the amount of bacterial counterparts. This size limits large-scale synthetic biology efforts in yeasts. Here we address this shortcoming by establishing a methodical workflow necessary to identify robust minimal core elements that can be linked with minimal upstream activating sequences to develop short, yet strong yeast promoters. Through a series of library-based synthesis, analysis and robustness tests, we create a set of non-homologous, purely synthetic, minimal promoters for yeast. These promoters are comprised of short core elements that are generic and interoperable and 10 bp UAS elements that impart strong, constitutive function. Through this methodology, we are able to generate the shortest fungal promoters to date, which can achieve high levels of both inducible and constitutive expression with up to an 80% reduction in size.

Endogenous fungal gene promoters can be hundreds of base pairs long, limiting their use in synthetic biology and biotechnology. Here Redden and Alper screen a library of synthetic promoter elements to generate compact DNA sequences of ∼100 base pairs able to drive high levels of gene expression.

The grammar of transcriptional regulation

Eukaryotes employ combinatorial strategies to generate a variety of expression patterns from a relatively small set of regulatory DNA elements. As in any other language, deciphering the mapping between DNA and expression requires an understanding of the set of rules that govern basic principles in transcriptional regulation, the functional elements involved, and the ways in which they combine to orchestrate a transcriptional output. Here, we review the current understanding of various grammatical rules, including the effect on expression of the number of transcription factor binding sites, their location, orientation, affinity and activity; co-association with different factors; and intrinsic nucleosome organization. We review different methods that are used to study the grammar of transcription regulation, highlight gaps in current understanding, and discuss how recent technological advances may be utilized to bridge them.

Discrimination between thermodynamic models of cis-regulation using transcription factor occupancy data

Many studies have identified binding preferences for transcription factors (TFs), but few have yielded predictive models of how combinations of transcription factor binding sites generate specific levels of gene expression. Synthetic promoters have emerged as powerful tools for generating quantitative data to parameterize models of combinatorial cis-regulation. We sought to improve the accuracy of such models by quantifying the occupancy of TFs on synthetic promoters in vivo and incorporating these data into statistical thermodynamic models of cis-regulation. Using chromatin immunoprecipitation-seq, we measured the occupancy of Gcn4 and Cbf1 in synthetic promoter libraries composed of binding sites for Gcn4, Cbf1, Met31/Met32 and Nrg1. We measured the occupancy of these two TFs and the expression levels of all promoters in two growth conditions. Models parameterized using only expression data predicted expression but failed to identify several interactions between TFs. In contrast, models parameterized with occupancy and expression data predicted expression data, and also revealed Gcn4 self-cooperativity and a negative interaction between Gcn4 and Nrg1. Occupancy data also allowed us to distinguish between competing regulatory mechanisms for the factor Gcn4. Our framework for combining occupancy and expression data produces predictive models that better reflect the mechanisms underlying combinatorial cis-regulation of gene expression.

Promoters maintain their relative activity levels under different growth conditions

Most genes change expression levels across conditions, but it is unclear which of these changes represents specific regulation and what determines their quantitative degree. Here, we accurately measured activities of ~900 S. cerevisiae and ~1800 E. coli promoters using fluorescent reporters. We show that in both organisms 60-90% of promoters change their expression between conditions by a constant global scaling factor that depends only on the conditions and not on the promoter's identity. Quantifying such global effects allows precise characterization of specific regulation-promoters deviating from the global scale line. These are organized into few functionally related groups that also adhere to scale lines and preserve their relative activities across conditions. Thus, only several scaling factors suffice to accurately describe genome-wide expression profiles across conditions. We present a parameter-free passive resource allocation model that quantitatively accounts for the global scaling factors. It suggests that many changes in expression across conditions result from global effects and not specific regulation, and provides means for quantitative interpretation of expression profiles.

Measurements of the impact of 3' end sequences on gene expression reveal wide range and sequence dependent effects

A full understanding of gene regulation requires an understanding of the contributions that the various regulatory regions have on gene expression. Although it is well established that sequences downstream of the main promoter can affect expression, our understanding of the scale of this effect and how it is encoded in the DNA is limited. Here, to measure the effect of native S. cerevisiae 3′ end sequences on expression, we constructed a library of 85 fluorescent reporter strains that differ only in their 3′ end region. Notably, despite being driven by the same strong promoter, our library spans a continuous twelve-fold range of expression values. These measurements correlate with endogenous mRNA levels, suggesting that the 3′ end contributes to constitutive differences in mRNA levels. We used deep sequencing to map the 3′UTR ends of our strains and show that determination of polyadenylation sites is intrinsic to the local 3′ end sequence. Polyadenylation mapping was followed by sequence analysis, we found that increased A/T content upstream of the main polyadenylation site correlates with higher expression, both in the library and genome-wide, suggesting that native genes differ by the encoded efficiency of 3′ end processing. Finally, we use single cells fluorescence measurements, in different promoter activation levels, to show that 3′ end sequences modulate protein expression dynamics differently than promoters, by predominantly affecting the size of protein production bursts as opposed to the frequency at which these bursts occur. Altogether, our results lead to a more complete understanding of gene regulation by demonstrating that 3′ end regions have a unique and sequence dependent effect on gene expression.

A basic question in gene expression is the relative contribution of different regulatory layers and genomic regions to the differences in protein levels. In this work we concentrated on the effect of 3′ end sequences. For this, we constructed a library of yeast strains that differ only by a native 3′ end region integrated downstream to a reported gene driven by a constant inducible promoter. Thus we could attribute all differences in reporter expression between the strains to the different 3′ end sequences. Interestingly, we found that despite being driven by the same strong, inducible promoter, our library spanned a wide and continuous range of expression levels of more than twelve-fold. As these measurements represent the sole effect of the 3′ end region, we quantify the contribution of these sequences to the variance in mRNA levels by comparing our measurements to endogenous mRNA levels. We follow by sequence analysis to find a simple sequence signature that correlates with expression. In addition, single cell analysis reveals distinct noise dynamics of 3′ end mediated differences in expression compared to different levels of promoter activation leading to a more complete understanding of gene expression which also incorporates the effect of these regions.

Creation and characterization of component libraries for synthetic biology

Large numbers of well-described components are essential for advanced synthetic biology and model-guided design of pathways and regulatory networks. Here a method is presented for the creation of libraries of novel control elements. From these libraries, parts with well-defined properties can be selected and used in construction of finely tuned synthetic systems. The example of the PFY1 promoter in S. cerevisiae is used to describe library creation using degenerate synthetic oligos and the circular polymerase extension cloning (CPEC) method. Additionally the workflow of screening the raw library for functional parts is included to provide a full overview of the process of creating and characterizing a component library for synthetic biology.

Rapid synthesis of defined eukaryotic promoter libraries

Current gene synthesis methods allow the generation of long segments of dsDNA. We show that these techniques can be used to create synthetic regulatory elements and describe a method for the creation of completely defined, synthetic variants of the PHO5 promoter from the budding yeast Saccharomyces cerevisae. Overall, 128 promoters were assembled by high-temperature ligation, cloned into plasmids by isothermal assembly, maintained in E. coli, and consequently transformed into yeast by homologous recombination. Synthesis errors occurred at frequencies comparable to or lower than those achieved with current gene synthesis methods. The promoter synthesis method reported here is robust, fast, and readily accessible. Synthetically engineered promoter libraries will be useful tools for dissecting the intricacies of promoter input-output functions and may serve as tunable components for synthetic genetic networks.

Inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters

Despite much research, our understanding of the rules by which cis-regulatory sequences are translated into expression levels is still lacking. We devised a method for obtaining parallel and highly accurate expression measurements of thousands of fully designed promoters, and applied it to measure the effect of systematic changes to location, number, orientation, affinity and organization of transcription factor (TF) binding sites and of nucleosome disfavoring sequences. Our analyses reveal a clear relationship between expression and binding site number, and TF-specific dependencies of expression on the distance between sites and gene starts including a striking ~10bp periodic relationship. We also demonstrate the utility of our approach for measuring TF sequence specificities and sensitivity of TF sites to surrounding sequence context, and for profiling the activity of most yeast transcription factors. Our method is readily applicable for studying both the cis and trans effects of genotype on transcriptional, post-transcriptional, and translational control.

Tunable promoters in synthetic and systems biology

Synthetic and systems biologists need standardized, modular and orthogonal tools yielding predictable functions in vivo. In systems biology such tools are needed to quantitatively analyze the behavior of biological systems while the efficient engineering of artificial gene networks is central in synthetic biology. A number of tools exist to manipulate the steps in between gene sequence and functional protein in living cells, but out of these the most straight-forward approach is to alter the gene expression level by manipulating the promoter sequence. Some of the promoter tuning tools available for accomplishing such altered gene expression levels are discussed here along with examples of their use, and ideas for new tools are described. The road ahead looks very promising for synthetic and systems biologists as tools to achieve just about anything in terms of tuning and timing multiple gene expression levels using libraries of synthetic promoters now exist.

Compensation for differences in gene copy number among yeast ribosomal proteins is encoded within their promoters

Coordinate regulation of ribosomal protein (RP) genes is key for controlling cell growth. In yeast, it is unclear how this regulation achieves the required equimolar amounts of the different RP components, given that some RP genes exist in duplicate copies, while others have only one copy. Here, we tested whether the solution to this challenge is partly encoded within the DNA sequence of the RP promoters, by fusing 110 different RP promoters to a fluorescent gene reporter, allowing us to robustly detect differences in their promoter activities that are as small as ~10%. We found that single-copy RP promoters have significantly higher activities, suggesting that proper RP stoichiometry is indeed partly encoded within the RP promoters. Notably, we also partially uncovered how this regulation is encoded by finding that RP promoters with higher activity have more nucleosome-disfavoring sequences and characteristic spatial organizations of these sequences and of binding sites for key RP regulators. Mutations in these elements result in a significant decrease of RP promoter activity. Thus, our results suggest that intrinsic (DNA-dependent) nucleosome organization may be a key mechanism by which genomes encode biologically meaningful promoter activities. Our approach can readily be applied to uncover how transcriptional programs of other promoters are encoded.

Multiple sequence-specific factors generate the nucleosome-depleted region on CLN2 promoter

Nucleosome-depleted regions (NDRs) are ubiquitous on eukaryotic promoters. The formation of many NDRs cannot be readily explained by previously proposed mechanisms. Here, we carry out a focused study on a physiologically important NDR in the yeast CLN2 promoter (CLN2pr). We show that this NDR does not result from intrinsically unfavorable histone-DNA interaction. Instead, we identified eight conserved factor binding sites, including that of Reb1, Mcm1, and Rsc3, that cause the local nucleosome depletion. These nucleosome-depleting factors (NDFs) work redundantly, and simultaneously mutating all their binding sites eliminates CLN2pr NDR. The loss of the NDR induces unreliable "on/off" expression in individual cell cycles, but in the presence of the NDR, NDFs have little direct effect on transcription. We present bioinformatic evidence that the formation of many NDRs across the genome involves multiple NDFs. Our findings also provide significant insight into the composition and spatial organization of functional promoters.

TATA is a modular component of synthetic promoters

The expression of most genes is regulated by multiple transcription factors. The interactions between transcription factors produce complex patterns of gene expression that are not always obvious from the arrangement of cis-regulatory elements in a promoter. One critical element of promoters is the TATA box, the docking site for the RNA polymerase holoenzyme. Using a synthetic promoter system coupled to a thermodynamic model of combinatorial regulation, we analyze the effects of different strength TATA boxes on various aspects of combinatorial cis-regulation. The thermodynamic model explains 75% of the variance in gene expression in synthetic promoter libraries with different strength TATA boxes, suggesting that many of the salient aspects of cis-regulation are captured by the model. Our results demonstrate that the effect of changing the TATA box on gene expression is the same for all synthetic promoters regardless of the arrangement of cis-regulatory sites we studied. Our analysis also showed that in our synthetic system the strength of the RNA polymerase-TATA interaction does not alter the combinatorial interactions between transcription factors, or between transcription factors and RNA polymerase. Finally, we show that although stronger TATA boxes increase expression in a predictable fashion, stronger TATA boxes have very little effect on noise in our synthetic promoters, regardless of the arrangement of cis-regulatory sites. Our results support a modular model of promoter function, where cis-regulatory elements can be mixed and matched (programmed) with outcomes on expression that are predictable based on the rules of simple protein-protein and protein-DNA interactions.

Perspectives on synthetic promoters for biocatalysis and biotransformation

Acting on the transcriptional level, synthetic promoters have been useful tools for controlling gene expression and have applications in many fields. Here, we discuss synthetic promoters and libraries in regard to current and future applications in the field of biocatalysis or biotransformation. We also focus on synthetic promoter design principles and distinguish between prokaryotic and eukaryotic destinations. The natural toolboxes available for tuneable gene expression and the regulation of enzyme function are limited and primarily host specific. Synthetic biology offers generally applicable concepts and quick implementation. Smart alternatives to transcriptional regulation enrich the engineer's tool box for optimizing industrial enzyme production and host-cell physiology for whole-cell processes. Industrially applicable, tuneable enzyme cascades and artificial circuits for iterative up- and down-regulation will soon be achieved.

Using DNA mechanics to predict in vitro nucleosome positions and formation energies

In eukaryotic genomes, nucleosomes function to compact DNA and to regulate access to it both by simple physical occlusion and by providing the substrate for numerous covalent epigenetic tags. While competition with other DNA-binding factors and action of chromatin remodeling enzymes significantly affect nucleosome formation in vivo, nucleosome positions in vitro are determined by steric exclusion and sequence alone. We have developed a biophysical model, DNABEND, for the sequence dependence of DNA bending energies, and validated it against a collection of in vitro free energies of nucleosome formation and a set of in vitro nucleosome positions mapped at high resolution. We have also made a first ab initio prediction of nucleosomal DNA geometries, and checked its accuracy against the nucleosome crystal structure. We have used DNABEND to design both strong and weak histone- binding sequences, and measured the corresponding free energies of nucleosome formation. We find that DNABEND can successfully predict in vitro nucleosome positions and free energies, providing a physical explanation for the intrinsic sequence dependence of histone–DNA interactions.

Incorporating nucleosomes into thermodynamic models of transcription regulation

Transcriptional control is central to many cellular processes, and, consequently, much effort has been devoted to understanding its underlying mechanisms. The organization of nucleosomes along promoter regions is important for this process, since most transcription factors cannot bind nucleosomal sequences and thus compete with nucleosomes for DNA access. This competition is governed by the relative concentrations of nucleosomes and transcription factors and by their respective sequence binding preferences. However, despite its importance, a mechanistic understanding of the quantitative effects that the competition between nucleosomes and factors has on transcription is still missing. Here we use a thermodynamic framework based on fundamental principles of statistical mechanics to explore theoretically the effect that different nucleosome organizations along promoters have on the activation dynamics of promoters in response to varying concentrations of the regulating factors. We show that even simple landscapes of nucleosome organization reproduce experimental results regarding the effect of nucleosomes as general repressors and as generators of obligate binding cooperativity between factors. Our modeling framework also allows us to characterize the effects that various sequence elements of promoters have on the induction threshold and on the shape of the promoter activation curves. Finally, we show that using only sequence preferences for nucleosomes and transcription factors, our model can also predict expression behavior of real promoter sequences, thereby underscoring the importance of the interplay between nucleosomes and factors in determining expression kinetics.

Splicing of designer exons reveals unexpected complexity in pre-mRNA splicing

Pre-messengerRNA (mRNA) splicing requires the accurate recognition of splice sites by the cellular RNA processing machinery. In addition to sequences that comprise the branchpoint and the 3' and 5' splice sites, the cellular splicing machinery relies on additional information in the form of exonic and intronic splicing enhancer and silencer sequences. The high abundance of these motifs makes it difficult to investigate their effects using standard genetic perturbations, since their disruption often leads to the formation of yet new elements. To lessen this problem, we have designed synthetic exons comprised of multiple copies of a single prototypical exonic enhancer and a single prototypical exonic silencer sequence separated by neutral spacer sequences. The spacer sequences buffer the exon against the formation of new elements as the number and order of the original elements are varied. Over 100 such designer exons were constructed by random ligation of enhancer, silencer, and neutral elements. Each exon was positioned as the central exon in a 3-exon minigene and tested for exon inclusion after transient transfection. The level of inclusion of the test exons was seen to be dependent on the provision of enhancers and could be decreased by the provision of silencers. In general, there was a good quantitative correlation between the proportion of enhancers and splicing. However, widely varying inclusion levels could be produced by different permutations of the enhancer and silencer elements, indicating that even in this simplified system splicing decisions rest on complex interplays of yet to be determined parameters.

Analysis of combinatorial cis-regulation in synthetic and genomic promoters

Transcription factor binding sites (TFBS) are being discovered at a rapid pace1, 2. We must now begin to turn our attention towards understanding how these sites work in combination to influence gene expression. Quantitative models that accurately predict gene expression from promoter sequence3-5 will be a crucial part of solving this problem. Here we present such a model based on the analysis of synthetic promoter libraries in yeast. Thermodynamic models based only on the equilibrium binding of transcription factors to DNA and to each other captured a large fraction of the variation in expression in every library. Thermodynamic analysis of these libraries uncovered several phenomena in our system, including cooperativity and the effects of weak binding sites. When applied to the genome, a model of repression by Mig1, which was trained on synthetic promoters, predicts a number of Mig1 regulated genes that lack significant Mig1 binding sites in their promoters. The success of the thermodynamic approach suggests that the information encoded by combinations of cis-regulatory sites is interpreted primarily through simple protein-DNA and protein-protein interactions with complicated biochemical reactions, such as nucleosome modifications, being down stream events. Quantitative analyses of synthetic promoter libraries will be an important tool in unraveling the rules underlying combinatorial cis-regulation.

DNA-binding properties of the yeast Rgt1 repressor

The yeast HXT (glucose transporter gene) repressor Rgt1 lacks a dimerization domain and thus appears to bind as a monomer to its consensus binding site sequence (5'-CGGANNA-3'). The HXT1 promoter contains 8 Rgt1-binding sites, but its expression is not effectively repressed by Rgt1. In the present study, the Rgt1-binding sites in the HXT1 promoter were analyzed to examine how Rgt1 mediates transcriptional repression. It is seen that Rgt1 binds the HXT1 promoter, but does not significantly mediate repression. When engineered to be multimerized without the intervening sequences between the Rgt1-binding sites, however, 4 or more Rgt1-binding sites were required to provide sufficient Rgt1-dependent repression. These findings suggest that the intervening sequences between the Rgt1-binding sites are important for the regulation of Rgt1 function and that Rgt1 functions efficiently only through multiple binding sites.

A cis-regulatory logic simulator

Background

A major goal of computational studies of gene regulation is to accurately predict the expression of genes based on the cis-regulatory content of their promoters. The development of computational methods to decode the interactions among cis-regulatory elements has been slow, in part, because it is difficult to know, without extensive experimental validation, whether a particular method identifies the correct cis-regulatory interactions that underlie a given set of expression data. There is an urgent need for test expression data in which the interactions among cis-regulatory sites that produce the data are known. The ability to rapidly generate such data sets would facilitate the development and comparison of computational methods that predict gene expression patterns from promoter sequence.

Results

We developed a gene expression simulator which generates expression data using user-defined interactions between cis-regulatory sites. The simulator can incorporate additive, cooperative, competitive, and synergistic interactions between regulatory elements. Constraints on the spacing, distance, and orientation of regulatory elements and their interactions may also be defined and Gaussian noise can be added to the expression values. The simulator allows for a data transformation that simulates the sigmoid shape of expression levels from real promoters. We found good agreement between sets of simulated promoters and predicted regulatory modules from real expression data. We present several data sets that may be useful for testing new methodologies for predicting gene expression from promoter sequence.

Conclusion

We developed a flexible gene expression simulator that rapidly generates large numbers of simulated promoters and their corresponding transcriptional output based on specified interactions between cis-regulatory sites. When appropriate rule sets are used, the data generated by our simulator faithfully reproduces experimentally derived data sets. We anticipate that using simulated gene expression data sets will facilitate the direct comparison of computational strategies to predict gene expression from promoter sequence. The source code is available online and as additional material. The test sets are available as additional material.

Programming gene expression with combinatorial promoters

Promoters control the expression of genes in response to one or more transcription factors (TFs). The architecture of a promoter is the arrangement and type of binding sites within it. To understand natural genetic circuits and to design promoters for synthetic biology, it is essential to understand the relationship between promoter function and architecture. We constructed a combinatorial library of random promoter architectures. We characterized 288 promoters in Escherichia coli, each containing up to three inputs from four different TFs. The library design allowed for multiple −10 and −35 boxes, and we observed varied promoter strength over five decades. To further analyze the functional repertoire, we defined a representation of promoter function in terms of regulatory range, logic type, and symmetry. Using these results, we identified heuristic rules for programming gene expression with combinatorial promoters.

Enhancer responses to similarly distributed antagonistic gradients in development

Formation of spatial gene expression patterns in development depends on transcriptional responses mediated by gene control regions, enhancers. Here, we explore possible responses of enhancers to overlapping gradients of antagonistic transcriptional regulators in the Drosophila embryo. Using quantitative models based on enhancer structure, we demonstrate how a pair of antagonistic transcription factor gradients with similar or even identical spatial distributions can lead to the formation of distinct gene expression domains along the embryo axes. The described mechanisms are sufficient to explain the formation of the anterior and the posterior knirps expression, the posterior hunchback expression domain, and the lateral stripes of rhomboid expression and of other ventral neurogenic ectodermal genes. The considered principles of interaction between antagonistic gradients at the enhancer level can also be applied to diverse developmental processes, such as domain specification in imaginal discs, or even eyespot pattern formation in the butterfly wing.

The early development of the fruit fly embryo depends on an intricate but well-studied gene regulatory network. In fly eggs, maternally deposited gene products—morphogenes—form spatial concentration gradients. The graded distribution of the maternal morphogenes initiates a cascade of gene interactions leading to embryo development. Gradients of activators and repressors regulating common target genes may produce different outcomes depending on molecular mechanisms, mediating their function. Here, we describe quantitative mathematical models for the interplay between gradients of positive and negative transcriptional regulators—proteins, activating or repressing their target genes through binding the gene's regulatory DNA sequences. We predict possible spatial outcomes of the transcriptional antagonistic interactions in fly development and consider examples where the predicted cases may take place.