Adjacent Codons Act in Concert to Modulate Translation Efficiency in Yeast.

Translation elongation efficiency is largely thought of as the sum of decoding efficiencies for individual codons. Here, we find that adjacent codon pairs modulate translation efficiency. Deploying an approach in Saccharomyces cerevisiae that scored the expression of over 35,000 GFP variants in which three adjacent codons were randomized, we have identified 17 pairs of adjacent codons associated with reduced expression. For many pairs, codon order is obligatory for inhibition, implying a more complex interaction than a simple additive effect. Inhibition mediated by adjacent codons occurs during translation itself as GFP expression is restored by increased tRNA levels or by non-native tRNAs with exact-matching anticodons. Inhibition operates in endogenous genes, based on analysis of ribosome profiling data. Our findings suggest translation efficiency is modulated by an interplay between tRNAs at adjacent sites in the ribosome and that this concerted effect needs to be considered in predicting the functional consequences of codon choice.

Plant enhancers exhibit both cooperative and additive interactions among their functional elements.

Enhancers are cis-regulatory elements that shape gene expression in response to numerous developmental and environmental cues. In animals, several models have been proposed to explain how enhancers integrate the activity of multiple transcription factors. However, it remains largely unclear how plant enhancers integrate transcription factor activity. Here, we use Plant STARR-seq to characterize 3 light-responsive plant enhancers-AB80, Cab-1, and rbcS-E9-derived from genes associated with photosynthesis. Saturation mutagenesis revealed mutations, many of which clustered in short regions, that strongly reduced enhancer activity in the light, in the dark, or in both conditions. When tested in the light, these mutation-sensitive regions did not function on their own; rather, cooperative interactions with other such regions were required for full activity. Epistatic interactions occurred between mutations in adjacent mutation-sensitive regions, and the spacing and order of mutation-sensitive regions in synthetic enhancers affected enhancer activity. In contrast, when tested in the dark, mutation-sensitive regions acted independently and additively in conferring enhancer activity. Taken together, this work demonstrates that plant enhancers show evidence for both cooperative and additive interactions among their functional elements. This knowledge can be harnessed to design strong, condition-specific synthetic enhancers.

Impact on splicing in Saccharomyces cerevisiae of random 50-base sequences inserted into an intron.

Intron splicing is a key regulatory step in gene expression in eukaryotes. Three sequence elements required for splicing-5' and 3' splice sites and a branchpoint-are especially well-characterized in Saccharomyces cerevisiae, but our understanding of additional intron features that impact splicing in this organism is incomplete, due largely to its small number of introns. To overcome this limitation, we constructed a library in S. cerevisiae of random 50-nt (N50) elements individually inserted into the intron of a reporter gene and quantified canonical splicing and the use of cryptic splice sites by sequencing analysis. More than 70% of approximately 140,000 N50 elements reduced splicing by at least 20%. N50 features, including higher GC content, presence of GU repeats, and stronger predicted secondary structure of its pre-mRNA, correlated with reduced splicing efficiency. A likely basis for the reduced splicing of such a large proportion of variants is the formation of RNA structures that pair N50 bases-such as the GU repeats-with other bases specifically within the reporter pre-mRNA analyzed. However, multiple models were unable to explain more than a small fraction of the variance in splicing efficiency across the library, suggesting that complex nonlinear interactions in RNA structures are not accurately captured by RNA structure prediction methods. Our results imply that the specific context of a pre-mRNA may determine the bases allowable in an intron to prevent secondary structures that reduce splicing. This large data set can serve as a resource for further exploration of splicing mechanisms.

Mapping functional regions of essential bacterial proteins with dominant-negative protein fragments.

Massively parallel measurements of dominant-negative inhibition by protein fragments have been used to map protein interaction sites and discover peptide inhibitors. However, the underlying principles governing fragment-based inhibition have thus far remained unclear. Here, we adapted a high-throughput inhibitory fragment assay for use in Escherichia coli, applying it to a set of 10 essential proteins. This approach yielded single amino acid resolution maps of inhibitory activity, with peaks localized to functionally important interaction sites, including oligomerization interfaces and folding contacts. Leveraging these data, we performed a systematic analysis to uncover principles of fragment-based inhibition. We determined a robust negative correlation between susceptibility to inhibition and cellular protein concentration, demonstrating that inhibitory fragments likely act primarily by titrating native protein interactions. We also characterized a series of trade-offs related to fragment length, showing that shorter peptides allow higher-resolution mapping but suffer from lower inhibitory activity. We employed an unsupervised statistical analysis to show that the inhibitory activities of protein fragments are largely driven not by generic properties such as charge, hydrophobicity, and secondary structure, but by the more specific characteristics of their bespoke macromolecular interactions. Overall, this work demonstrates fundamental characteristics of inhibitory protein fragment function and provides a foundation for understanding and controlling protein interactions in vivo.

Identification of Plant Enhancers and Their Constituent Elements by STARR-seq in Tobacco Leaves.

Genetic engineering of cis-regulatory elements in crop plants is a promising strategy to ensure food security. However, such engineering is currently hindered by our limited knowledge of plant cis-regulatory elements. Here, we adapted self-transcribing active regulatory region sequencing (STARR-seq)-a technology for the high-throughput identification of enhancers-for its use in transiently transformed tobacco (Nicotiana benthamiana) leaves. We demonstrate that the optimal placement in the reporter construct of enhancer sequences from a plant virus, pea (Pisum sativum) and wheat (Triticum aestivum), was just upstream of a minimal promoter and that none of these four known enhancers was active in the 3' untranslated region of the reporter gene. The optimized assay sensitively identified small DNA regions containing each of the four enhancers, including two whose activity was stimulated by light. Furthermore, we coupled the assay to saturation mutagenesis to pinpoint functional regions within an enhancer, which we recombined to create synthetic enhancers. Our results describe an approach to define enhancer properties that can be performed in potentially any plant species or tissue transformable by Agrobacterium and that can use regulatory DNA derived from any plant genome.

Yeast life span extension by depletion of 60s ribosomal subunits is mediated by Gcn4.

In nearly every organism studied, reduced caloric intake extends life span. In yeast, span extension from dietary restriction is thought to be mediated by the highly conserved, nutrient-responsive target of rapamycin (TOR), protein kinase A (PKA), and Sch9 kinases. These kinases coordinately regulate various cellular processes including stress responses, protein turnover, cell growth, and ribosome biogenesis. Here we show that a specific reduction of 60S ribosomal subunit levels slows aging in yeast. Deletion of genes encoding 60S subunit proteins or processing factors or treatment with a small molecule, which all inhibit 60S subunit biogenesis, are each sufficient to significantly increase replicative life span. One mechanism by which reduced 60S subunit levels leads to life span extension is through induction of Gcn4, a nutrient-responsive transcription factor. Genetic epistasis analyses suggest that dietary restriction, reduced 60S subunit abundance, and Gcn4 activation extend yeast life span by similar mechanisms.

High-throughput identification of dominant negative polypeptides in yeast.

Dominant negative polypeptides can inhibit protein function by binding to a wild-type subunit or by titrating a ligand. Here we use high-throughput sequencing of libraries composed of fragments of yeast genes to identify polypeptides that act in a dominant negative manner, in that they are depleted during cell growth. The method can uncover numerous inhibitory polypeptides for a protein and thereby define small inhibitory regions, even pinpointing individual residues with critical functional roles.

MaveRegistry: a collaboration platform for multiplexed assays of variant effect.

SUMMARY: Multiplexed assays of variant effect (MAVEs) are capable of experimentally testing all possible single nucleotide or amino acid variants in selected genomic regions, generating 'variant effect maps', which provide biochemical insight and functional evidence to enable more rapid and accurate clinical interpretation of human variation. Because the international community applying MAVE approaches is growing rapidly, we developed the online MaveRegistry platform to catalyze collaboration, reduce redundant efforts, allow stakeholders to nominate targets and enable tracking and sharing of progress on ongoing MAVE projects. AVAILABILITY AND IMPLEMENTATION: MaveRegistry service: https://registry.varianteffect.org. MaveRegistry source code: https://github.com/kvnkuang/maveregistry-front-end.

Dynamics of Gene Expression in Single Root Cells of Arabidopsis thaliana.

Single cell RNA sequencing can yield high-resolution cell-type-specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach to Arabidopsis (Arabidopsis thaliana) root cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type-specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. We assess and interpret changes in total RNA expression along developmental trajectories and show that trajectory branch points mark developmental decisions. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat-shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.

Identification of the determinants of tRNA function and susceptibility to rapid tRNA decay by high-throughput in vivo analysis.

Sequence variation in tRNA genes influences the structure, modification, and stability of tRNA; affects translation fidelity; impacts the activity of numerous isodecoders in metazoans; and leads to human diseases. To comprehensively define the effects of sequence variation on tRNA function, we developed a high-throughput in vivo screen to quantify the activity of a model tRNA, the nonsense suppressor SUP4oc of Saccharomyces cerevisiae. Using a highly sensitive fluorescent reporter gene with an ochre mutation, fluorescence-activated cell sorting of a library of SUP4oc mutant yeast strains, and deep sequencing, we scored 25,491 variants. Unexpectedly, SUP4oc tolerates numerous sequence variations, accommodates slippage in tertiary and secondary interactions, and exhibits genetic interactions that suggest an alternative functional tRNA conformation. Furthermore, we used this methodology to define tRNA variants subject to rapid tRNA decay (RTD). Even though RTD normally degrades tRNAs with exposed 5' ends, mutations that sensitize SUP4oc to RTD were found to be located throughout the sequence, including the anti-codon stem. Thus, the integrity of the entire tRNA molecule is under surveillance by cellular quality control machinery. This approach to assess activity at high throughput is widely applicable to many problems in tRNA biology.

A Multiplex Homology-Directed DNA Repair Assay Reveals the Impact of More Than 1,000 BRCA1 Missense Substitution Variants on Protein Function.

Loss-of-function pathogenic variants in BRCA1 confer a predisposition to breast and ovarian cancer. Genetic testing for sequence changes in BRCA1 frequently reveals a missense variant for which the impact on cancer risk and on the molecular function of BRCA1 is unknown. Functional BRCA1 is required for the homology-directed repair (HDR) of double-strand DNA breaks, a critical activity for maintaining genome integrity and tumor suppression. Here, we describe a multiplex HDR reporter assay for concurrently measuring the effects of hundreds of variants of BRCA1 for their role in DNA repair. Using this assay, we characterized the effects of 1,056 amino acid substitutions in the first 192 residues of BRCA1. Benchmarking these results against variants with known effects on DNA repair function or on cancer predisposition, we demonstrate accurate discrimination of loss-of-function versus benign missense variants. We anticipate that this assay can be used to functionally characterize BRCA1 missense variants at scale, even before the variants are observed in results from genetic testing.

Preferences in a trait decision determined by transcription factor variants.

Few mechanisms are known that explain how transcription factors can adjust phenotypic outputs to accommodate differing environments. In Saccharomyces cerevisiae, the decision to mate or invade relies on environmental cues that converge on a shared transcription factor, Ste12. Specificity toward invasion occurs via Ste12 binding cooperatively with the cofactor Tec1. Here, we determine the range of phenotypic outputs (mating vs. invasion) of thousands of DNA-binding domain variants in Ste12 to understand how preference for invasion may arise. We find that single amino acid changes in the DNA-binding domain can shift the preference of yeast toward either mating or invasion. These mutations define two distinct regions of this domain, suggesting alternative modes of DNA binding for each trait. We characterize the DNA-binding specificity of wild-type Ste12 to identify a strong preference for spacing and orientation of both homodimeric and heterodimeric sites. Ste12 mutants that promote hyperinvasion in a Tec1-independent manner fail to bind cooperative sites with Tec1 and bind to unusual dimeric Ste12 sites composed of one near-perfect and one highly degenerate site. We propose a model in which Ste12 alone may have evolved to activate invasion genes, which could explain how preference for invasion arose in the many fungal pathogens that lack Tec1.

Deep learning of the regulatory grammar of yeast 5' untranslated regions from 500,000 random sequences.

Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the protein expression of the 5' untranslated region (UTR) of mRNAs in the yeast Saccharomyces cerevisiae. We constructed a library of half a million 50-nucleotide-long random 5' UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on protein expression of Kozak sequence composition, upstream open reading frames (uORFs), and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the protein expression of both a held-out set of the random 5' UTRs as well as native S. cerevisiae 5' UTRs. The model additionally was used to computationally evolve highly active 5' UTRs. We confirmed experimentally that the great majority of the evolved sequences led to higher protein expression rates than the starting sequences, demonstrating the predictive power of this model.

Widespread temperature sensitivity and tRNA decay due to mutations in a yeast tRNA.

Microorganisms have universally adapted their RNAs and proteins to survive at a broad range of temperatures and growth conditions. However, for RNAs, there is little quantitative understanding of the effects of mutations on function at high temperatures. To understand how variant tRNA function is affected by temperature change, we used the tRNA nonsense suppressor SUP4oc of the yeast Saccharomyces cerevisiae to perform a high-throughput quantitative screen of tRNA function at two different growth temperatures. This screen yielded comparative values for 9243 single and double variants. Surprisingly, despite the ability of S. cerevisiae to grow at temperatures as low as 15°C and as high as 39°C, the vast majority of variants that could be scored lost half or more of their function when evaluated at 37°C relative to 28°C. Moreover, temperature sensitivity of a tRNA variant was highly associated with its susceptibility to the rapid tRNA decay (RTD) pathway, implying that RTD is responsible for most of the loss of function of variants at higher temperature. Furthermore, RTD may also operate in a met22Δ strain, which was previously thought to fully inhibit RTD. Consistent with RTD acting to degrade destabilized tRNAs, the stability of a tRNA molecule can be used to predict temperature sensitivity with high confidence. These findings offer a new perspective on the stability of tRNA molecules and their quality control at high temperature.

Conditional accumulation of toxic tRNAs to cause amino acid misincorporation.

To develop a system for conditional amino acid misincorporation, we engineered tRNAs in the yeast Saccharomyces cerevisiae to be substrates of the rapid tRNA decay (RTD) pathway, such that they accumulate when RTD is turned off. We used this system to test the effects on growth of a library of tRNASer variants with all possible anticodons, and show that many are lethal when RTD is inhibited and the tRNA accumulates. Using mass spectrometry, we measured serine misincorporation in yeast containing each of six tRNA variants, and for five of them identified hundreds of peptides with serine substitutions at the targeted amino acid sites. Unexpectedly, we found that there is not a simple correlation between toxicity and the level of serine misincorporation; in particular, high levels of serine misincorporation can occur at cysteine residues without obvious growth defects. We also showed that toxic tRNAs can be used as a tool to identify sequence variants that reduce tRNA function. Finally, we generalized this method to another tRNA species, and generated conditionally toxic tRNATyr variants in a similar manner. This method should facilitate the study of tRNA biology and provide a tool to probe the effects of amino acid misincorporation on cellular physiology.

Engineering an allosteric transcription factor to respond to new ligands.

Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl ß-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits.

Massively parallel single-amino-acid mutagenesis.

Random mutagenesis methods only partially cover the mutational space and are constrained by DNA synthesis length limitations. Here we demonstrate programmed allelic series (PALS), a single-volume, site-directed mutagenesis approach using microarray-programmed oligonucleotides. We created libraries including nearly every missense mutation as singleton events for the yeast transcription factor Gal4 (99.9% coverage) and human tumor suppressor p53 (93.5%). PALS-based comprehensive missense mutational scans may aid structure-function studies, protein engineering, and the interpretation of variants identified by clinical sequencing.

Combining natural sequence variation with high throughput mutational data to reveal protein interaction sites.

Many protein interactions are conserved among organisms despite changes in the amino acid sequences that comprise their contact sites, a property that has been used to infer the location of these sites from protein homology. In an inter-species complementation experiment, a sequence present in a homologue is substituted into a protein and tested for its ability to support function. Therefore, substitutions that inhibit function can identify interaction sites that changed over evolution. However, most of the sequence differences within a protein family remain unexplored because of the small-scale nature of these complementation approaches. Here we use existing high throughput mutational data on the in vivo function of the RRM2 domain of the Saccharomyces cerevisiae poly(A)-binding protein, Pab1, to analyze its sites of interaction. Of 197 single amino acid differences in 52 Pab1 homologues, 17 reduce the function of Pab1 when substituted into the yeast protein. The majority of these deleterious mutations interfere with the binding of the RRM2 domain to eIF4G1 and eIF4G2, isoforms of a translation initiation factor. A large-scale mutational analysis of the RRM2 domain in a two-hybrid assay for eIF4G1 binding supports these findings and identifies peripheral residues that make a smaller contribution to eIF4G1 binding. Three single amino acid substitutions in yeast Pab1 corresponding to residues from the human orthologue are deleterious and eliminate binding to the yeast eIF4G isoforms. We create a triple mutant that carries these substitutions and other humanizing substitutions that collectively support a switch in binding specificity of RRM2 from the yeast eIF4G1 to its human orthologue. Finally, we map other deleterious substitutions in Pab1 to inter-domain (RRM2-RRM1) or protein-RNA (RRM2-poly(A)) interaction sites. Thus, the combined approach of large-scale mutational data and evolutionary conservation can be used to characterize interaction sites at single amino acid resolution.

Engineering allostery.

Allosteric proteins have great potential in synthetic biology, but our limited understanding of the molecular underpinnings of allostery has hindered the development of designer molecules, including transcription factors with new DNA-binding or ligand-binding specificities that respond appropriately to inducers. Such allosteric proteins could function as novel switches in complex circuits, metabolite sensors, or as orthogonal regulators for independent, inducible control of multiple genes. Advances in DNA synthesis and next-generation sequencing technologies have enabled the assessment of millions of mutants in a single experiment, providing new opportunities to study allostery. Using the classic LacI protein as an example, we describe a genetic selection system using a bidirectional reporter to capture mutants in both allosteric states, allowing the positions most crucial for allostery to be identified. This approach is not limited to bacterial transcription factors, and could reveal new mechanistic insights and facilitate engineering of other major classes of allosteric proteins such as nuclear receptors, two-component systems, G protein-coupled receptors, and protein kinases.

Deep mutational scanning: a new style of protein science.

Mutagenesis provides insight into proteins, but only recently have assays that couple genotype to phenotype been used to assess the activities of as many as 1 million mutant versions of a protein in a single experiment. This approach-'deep mutational scanning'-yields large-scale data sets that can reveal intrinsic protein properties, protein behavior within cells and the consequences of human genetic variation. Deep mutational scanning is transforming the study of proteins, but many challenges must be tackled for it to fulfill its promise.