Unraveling the influences of sequence and position on yeast uORF activity using massively parallel reporter systems and machine learning

The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis

The 5' UTRs of mRNAs are critical for translation regulation during development, but their in vivo regulatory features are poorly characterized. Here, we report the regulatory landscape of 5' UTRs during early zebrafish embryogenesis using a massively parallel reporter assay of 18,154 sequences coupled to polysome profiling. We found that the 5' UTR suffices to confer temporal dynamics to translation initiation and identified 86 motifs enriched in 5' UTRs with distinct ribosome recruitment capabilities. A quantitative deep learning model, Danio Optimus 5-Prime (DaniO5P), identified a combined role for 5' UTR length, translation initiation site context, upstream AUGs, and sequence motifs on ribosome recruitment. DaniO5P predicts the activities of maternal and zygotic 5' UTR isoforms and indicates that modulating 5' UTR length and motif grammar contributes to translation initiation dynamics. This study provides a first quantitative model of 5' UTR-based translation regulation in development and lays the foundation for identifying the underlying molecular effectors.

The maternal-to-zygotic transition: reprogramming of the cytoplasm and nucleus

A fertilized egg is initially transcriptionally silent and relies on maternally provided factors to initiate development. For embryonic development to proceed, the oocyte-inherited cytoplasm and the nuclear chromatin need to be reprogrammed to create a permissive environment for zygotic genome activation (ZGA). During this maternal-to-zygotic transition (MZT), which is conserved in metazoans, transient totipotency is induced and zygotic transcription is initiated to form the blueprint for future development. Recent technological advances have enhanced our understanding of MZT regulation, revealing common themes across species and leading to new fundamental insights about transcription, mRNA decay and translation.

CRISPR-Cas9 Screening Reveals Microproteins Regulating Adipocyte Proliferation and Lipid Metabolism

Small open reading frames (smORFs) encode microproteins that play crucial roles in various biological processes, yet their functions in adipocyte biology remain largely unexplored. In a previous study, we identified thousands of smORFs in white and brown adipocytes derived from the stromal vascular fraction (SVF) of mice using ribosome profiling (Ribo-Seq). Here, we expand on this work by identifying additional smORFs related to adipocytes using the in vitro 3T3-L1 preadipocyte model. To systematically investigate the functional relevance of these smORFs, we designed a custom CRISPR/Cas9 guide RNA (sgRNA) library and screened for smORFs influencing adipocyte proliferation and differentiation. Through a dropout screen and fluorescence-assisted cell sorting (FACS) of lipid droplets, we identified dozens of smORFs that regulate either cell proliferation or lipid accumulation. Among these, we validated a novel microprotein as a key regulator of adipocyte differentiation. These findings highlight the potential of CRISPR/Cas9-based screening to uncover functional smORFs and provide a framework for further exploration of microproteins in adipocyte biology and metabolic regulation.

Significance

Obesity and its associated metabolic disorders pose significant public health challenges, yet the molecular mechanisms regulating adipocyte function remain incompletely understood. Small open reading frames (smORFs) and their encoded microproteins represent an emerging class of regulatory elements with potential roles in metabolism. Here, we leveraged CRISPR/Cas9 screening to functionally characterize smORFs in adipocytes, identifying novel regulators of cell proliferation and lipid metabolism. Our findings demonstrate that conservation is not a prerequisite for smORF function, as we validated a mouse-specific microprotein that modulates adipocyte differentiation. This work establishes a robust pipeline for unbiased smORF discovery and highlights the potential for species-specific microproteins to regulate adipose biology. Future studies in human adipocytes may uncover additional microproteins with therapeutic relevance for obesity and metabolic disease.

Deciphering the landscape of cis-acting sequences in natural yeast transcript leaders

Protein synthesis is a vital process that is highly regulated at the initiation step of translation. Eukaryotic 5' transcript leaders (TLs) contain a variety of cis-acting features that influence translation and messenger RNA stability. However, the relative influences of these features in natural TLs are poorly characterized. To address this, we used massively parallel reporter assays (MPRAs) to quantify RNA levels, ribosome loading, and protein levels from 11,027 natural yeast TLs in vivo and systematically compared the relative impacts of their sequence features on gene expression. We found that yeast TLs influence gene expression over two orders of magnitude. While a leaky scanning model using Kozak contexts (-4 to +1 around the AUG start) and upstream AUGs (uAUGs) explained half of the variance in expression across TLs, the addition of other features explained ∼80% of gene expression variation. Our analyses detected key cis-acting sequence features, quantified their effects in vivo, and compared their roles to motifs reported from an in vitro study of ribosome recruitment. In addition, our work quantitated the effects of alternative transcription start site usage on gene expression in yeast. Thus, our study provides new quantitative insights into the roles of TL cis-acting sequences in regulating gene expression.

Multilevel Gene Expression Changes in Lineages Containing Adaptive Copy Number Variants

Copy number variants (CNVs) are an important class of genetic variation that can mediate rapid adaptive evolution. Whereas, CNVs can increase the relative fitness of the organism, they can also incur a cost due to the associated increased gene expression and repetitive DNA. We previously evolved populations of Saccharomyces cerevisiae over hundreds of generations in glutamine-limited (Gln-) chemostats and observed the recurrent evolution of CNVs at the GAP1 locus. To understand the role that gene expression plays in adaptation, both in relation to the adaptation of the organism to the selective condition and as a consequence of the CNV, we measured the transcriptome, translatome, and proteome of 4 strains of evolved yeast, each with a unique CNV, and their ancestor in Gln- chemostats. We find CNV-amplified genes correlate with higher mRNA abundance; however, this effect is reduced at the level of the proteome, consistent with post-transcriptional dosage compensation. By normalizing each level of gene expression by the abundance of the preceding step we were able to identify widespread differences in the efficiency of each level of gene expression. Genes with significantly different translational efficiency were enriched for potential regulatory mechanisms including either upstream open reading frames, RNA-binding sites for Ssd1, or both. Genes with lower protein expression efficiency were enriched for genes encoding proteins in protein complexes. Taken together, our study reveals widespread changes in gene expression at multiple regulatory levels in lineages containing adaptive CNVs highlighting the diverse ways in which genome evolution shapes gene expression.

Predicting the translation efficiency of messenger RNA in mammalian cells

The degree to which translational control is specified by mRNA sequence is poorly understood in mammalian cells. Here, we constructed and leveraged a compendium of 3,819 ribosomal profiling datasets, distilling them into a transcriptome-wide atlas of translation efficiency (TE) measurements encompassing >140 human and mouse cell types. We subsequently developed RiboNN, a multitask deep convolutional neural network, and classic machine learning models to predict TEs in hundreds of cell types from sequence-encoded mRNA features, achieving state-of-the-art performance (r=0.79 in human and r=0.78 in mouse for mean TE across cell types). While the majority of earlier models solely considered 5' UTR sequence1, RiboNN integrates contributions from the full-length mRNA sequence, learning that the 5' UTR, CDS, and 3' UTR respectively possess ~67%, 31%, and 2% per-nucleotide information density in the specification of mammalian TEs. Interpretation of RiboNN revealed that the spatial positioning of low-level di- and tri-nucleotide features (i.e., including codons) largely explain model performance, capturing mechanistic principles such as how ribosomal processivity and tRNA abundance control translational output. RiboNN is predictive of the translational behavior of base-modified therapeutic RNA, and can explain evolutionary selection pressures in human 5' UTRs. Finally, it detects a common language governing mRNA regulatory control and highlights the interconnectedness of mRNA translation, stability, and localization in mammalian organisms.

NaP-TRAP reveals the regulatory grammar in 5'UTR-mediated translation regulation during zebrafish development

The cis-regulatory elements encoded in an mRNA determine its stability and translational output. While there has been a considerable effort to understand the factors driving mRNA stability, the regulatory frameworks governing translational control remain more elusive. We have developed a novel massively parallel reporter assay (MPRA) to measure mRNA translation, named Nascent Peptide Translating Ribosome Affinity Purification (NaP-TRAP). NaP-TRAP measures translation in a frame-specific manner through the immunocapture of epitope tagged nascent peptides of reporter mRNAs. We benchmark NaP-TRAP to polysome profiling and use it to quantify Kozak strength and the regulatory landscapes of 5' UTRs in the developing zebrafish embryo and in human cells. Through this approach we identified general and developmentally dynamic cis-regulatory elements, as well as potential trans-acting proteins. We find that U-rich motifs are general enhancers, and upstream ORFs and GC-rich motifs are global repressors of translation. We also observe a translational switch during the maternal-to-zygotic transition, where C-rich motifs shift from repressors to prominent activators of translation. Conversely, we show that microRNA sites in the 5' UTR repress translation following the zygotic expression of miR-430. Together these results demonstrate that NaP-TRAP is a versatile, accessible, and powerful method to decode the regulatory functions of UTRs across different systems.

Tiny but mighty: Diverse functions of uORFs that regulate gene expression

Upstream open reading frames (uORFs) are critical cis-acting regulators of downstream gene expression. Specifically, uORFs regulate translation by disrupting translation initiation or mediating mRNA decay. We herein summarize the effects of several uORFs that regulate gene expression in microbes to illustrate the detailed mechanisms mediating uORF functions. Microbes are ideal for uORF studies because of their prompt responses to stimuli. Recent studies revealed uORFs are ubiquitous in higher eukaryotes. Moreover, they influence various physiological processes in mammalian cells by regulating gene expression, mostly at the translational level. Research conducted using rapidly evolving methods for ribosome profiling combined with protein analyses and computational annotations showed that uORFs in mammalian cells control gene expression similar to microbial uORFs, but they also have unique tumorigenesis-related roles because of their protein-encoding capacities. We briefly introduce cutting-edge research findings regarding uORFs in mammalian cells.

Decoding biology with massively parallel reporter assays and machine learning

Massively parallel reporter assays (MPRAs) are powerful tools for quantifying the impacts of sequence variation on gene expression. Reading out molecular phenotypes with sequencing enables interrogating the impact of sequence variation beyond genome scale. Machine learning models integrate and codify information learned from MPRAs and enable generalization by predicting sequences outside the training data set. Models can provide a quantitative understanding of cis-regulatory codes controlling gene expression, enable variant stratification, and guide the design of synthetic regulatory elements for applications from synthetic biology to mRNA and gene therapy. This review focuses on cis-regulatory MPRAs, particularly those that interrogate cotranscriptional and post-transcriptional processes: alternative splicing, cleavage and polyadenylation, translation, and mRNA decay.

Ribosome Profiling and RNA Sequencing Reveal Translation and Transcription Regulation under Acute Heat Stress in Rainbow Trout (Oncorhynchus mykiss, Walbaum, 1792) Liver

Rainbow trout (Oncorhynchus mykiss, Walbaum, 1792) is an important economic cold-water fish that is susceptible to heat stress. To date, the heat stress response in rainbow trout is more widely understood at the transcriptional level, while little research has been conducted at the translational level. To reveal the translational regulation of heat stress in rainbow trout, in this study, we performed a ribosome profiling assay of rainbow trout liver under normal and heat stress conditions. Comparative analysis of the RNA-seq data with the ribosome profiling data showed that the folding changes in gene expression at the transcriptional level are moderately correlated with those at the translational level. In total, 1213 genes were significantly altered at the translational level. However, only 32.8% of the genes were common between both levels, demonstrating that heat stress is coordinated across both transcriptional and translational levels. Moreover, 809 genes exhibited significant differences in translational efficiency (TE), with the TE of these genes being considerably affected by factors such as the GC content, coding sequence length, and upstream open reading frame (uORF) presence. In addition, 3468 potential uORFs in 2676 genes were identified, which can potentially affect the TE of the main open reading frames. In this study, Ribo-seq and RNA-seq were used for the first time to elucidate the coordinated regulation of transcription and translation in rainbow trout under heat stress. These findings are expected to contribute novel data and theoretical insights to the international literature on the thermal stress response in fish.

Multilevel gene expression changes in lineages containing adaptive copy number variants

Copy-number variants (CNVs) are an important class of recurrent variants that mediate adaptive evolution. While CNVs can increase the relative fitness of the organism, they can also incur a cost. We previously evolved populations of Saccharomyces cerevisiae over hundreds of generations in glutamine-limited (Gln-) chemostats and observed the recurrent evolution of CNVs at the GAP1 locus. To understand the role that expression plays in adaptation, both in relation to the adaptation of the organism to the selective condition, and as a consequence of the CNV, we measured the transcriptome, translatome, and proteome of 4 strains of evolved yeast, each with a unique CNV, and their ancestor in Gln- conditions. We find CNV-amplified genes correlate with higher RNA abundance; however, this effect is reduced at the level of the proteome, consistent with post-transcriptional dosage compensation. By normalizing each level of expression by the abundance of the preceding step we were able to identify widespread divergence in the efficiency of each step in the gene in the efficiency of each step in gene expression. Genes with significantly different translational efficiency were enriched for potential regulatory mechanisms including either upstream open reading frames, RNA binding sites for SSD1, or both. Genes with lower protein expression efficiency were enriched for genes encoding proteins in protein complexes. Taken together, our study reveals widespread changes in gene expression at multiple regulatory levels in lineages containing adaptive CNVs highlighting the diverse ways in which adaptive evolution shapes gene expression.

Deciphering the cis-regulatory landscape of natural yeast Transcript Leaders

Protein synthesis is a vital process that is highly regulated at the initiation step of translation. Eukaryotic 5' transcript leaders (TLs) contain a variety of cis-regulatory features that influence translation and mRNA stability. However, the relative influences of these features in natural TLs are poorly characterized. To address this, we used massively parallel reporter assays (MPRAs) to quantify RNA levels, ribosome loading, and protein levels from 11,027 natural yeast TLs in vivo and systematically compared the relative impacts of their sequence features on gene expression. We found that yeast TLs influence gene expression over two orders of magnitude. While a leaky scanning model using Kozak contexts and uAUGs explained half of the variance in expression across transcript leaders, the addition of other features explained ~70% of gene expression variation. Our analyses detected key cis-acting sequence features, quantified their effects in vivo, and compared their roles to motifs reported from an in vitro study of ribosome recruitment. In addition, our work quantitated the effects of alternative transcription start site usage on gene expression in yeast. Thus, our study provides new quantitative insights into the roles of TL cis-acting sequences in regulating gene expression.

Integrated multiplexed assays of variant effect reveal determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase or decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

Natural uORF variation in plants

Taking advantage of natural variation promotes our understanding of phenotypic diversity and trait evolution, ultimately accelerating plant breeding, in which the identification of causal variations is critical. To date, sequence variations in the coding region and transcription level polymorphisms caused by variations in the promoter have been prioritized. An upstream open reading frame (uORF) in the 5' untranslated region (5' UTR) regulates gene expression at the post-transcription or translation level. In recent years, studies have demonstrated that natural uORF variations shape phenotypic diversity. This opinion article highlights recent researches and speculates on future directions for natural uORF variation in plants.

Yeast eIF2A has a minimal role in translation initiation and uORF-mediated translational control in vivo

Initiating translation of most eukaryotic mRNAs depends on recruitment of methionyl initiator tRNA (Met-tRNAi) in a ternary complex (TC) with GTP-bound eukaryotic initiation factor 2 (eIF2) to the small (40S) ribosomal subunit, forming a 43S preinitiation complex (PIC) that attaches to the mRNA and scans the 5'-untranslated region (5' UTR) for an AUG start codon. Previous studies have implicated mammalian eIF2A in GTP-independent binding of Met-tRNAi to the 40S subunit and its recruitment to specialized mRNAs that do not require scanning, and in initiation at non-AUG start codons, when eIF2 function is attenuated by phosphorylation of its α-subunit during stress. The role of eIF2A in translation in vivo is poorly understood however, and it was unknown whether the conserved ortholog in budding yeast can functionally substitute for eIF2. We performed ribosome profiling of a yeast deletion mutant lacking eIF2A and isogenic wild-type (WT) cells in the presence or absence of eIF2α phosphorylation induced by starvation for amino acids isoleucine and valine. Whereas starvation of WT confers changes in translational efficiencies (TEs) of hundreds of mRNAs, the eIF2AΔ mutation conferred no significant TE reductions for any mRNAs in non-starved cells, and it reduced the TEs of only a small number of transcripts in starved cells containing phosphorylated eIF2α. We found no evidence that eliminating eIF2A altered the translation of mRNAs containing putative internal ribosome entry site (IRES) elements, or harboring uORFs initiated by AUG or near-cognate start codons, in non-starved or starved cells. Thus, very few mRNAs (possibly only one) appear to employ eIF2A for Met-tRNAi recruitment in yeast cells, even when eIF2 function is attenuated by stress.

Yeast eIF2A has a minimal role in translation initiation and uORF-mediated translational control in vivo

Initiating translation of most eukaryotic mRNAs depends on recruitment of methionyl initiator tRNA (Met-tRNAi) in a ternary complex (TC) with GTP-bound eukaryotic initiation factor 2 (eIF2) to the small (40S) ribosomal subunit, forming a 43S preinitiation complex (PIC) that attaches to the mRNA and scans the 5'-untranslated region (5' UTR) for an AUG start codon. Previous studies have implicated mammalian eIF2A in GTP-independent binding of Met-tRNAi to the 40S subunit and its recruitment to specialized mRNAs that do not require scanning, and in initiation at non-AUG start codons, when eIF2 function is attenuated by phosphorylation of its α-subunit during stress. The role of eIF2A in translation in vivo is poorly understood however, and it was unknown whether the conserved ortholog in budding yeast can functionally substitute for eIF2. We performed ribosome profiling of a yeast deletion mutant lacking eIF2A and isogenic wild-type (WT) cells in the presence or absence of eIF2α phosphorylation induced by starvation for amino acids isoleucine and valine. Whereas starvation of WT confers changes in translational efficiencies (TEs) of hundreds of mRNAs, the eIF2AΔ mutation conferred no significant TE reductions for any mRNAs in non-starved cells, and it reduced the TEs of only a small number of transcripts in starved cells containing phosphorylated eIF2α. We found no evidence that eliminating eIF2A altered the translation of mRNAs containing putative IRES elements, or harboring uORFs initiated by AUG or near-cognate start codons, in non-starved or starved cells. Thus, very few mRNAs (possibly only one) appear to employ eIF2A for Met-tRNAi recruitment in yeast cells, even when eIF2 function is attenuated by stress.

The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis

The 5' UTRs of mRNAs are critical for translation regulation, but their in vivo regulatory features are poorly characterized. Here, we report the regulatory landscape of 5' UTRs during early zebrafish embryogenesis using a massively parallel reporter assay of 18,154 sequences coupled to polysome profiling. We found that the 5' UTR is sufficient to confer temporal dynamics to translation initiation, and identified 86 motifs enriched in 5' UTRs with distinct ribosome recruitment capabilities. A quantitative deep learning model, DaniO5P, revealed a combined role for 5' UTR length, translation initiation site context, upstream AUGs and sequence motifs on in vivo ribosome recruitment. DaniO5P predicts the activities of 5' UTR isoforms and indicates that modulating 5' UTR length and motif grammar contributes to translation initiation dynamics. This study provides a first quantitative model of 5' UTR-based translation regulation in early vertebrate development and lays the foundation for identifying the underlying molecular effectors.

Pervasive downstream RNA hairpins dynamically dictate start-codon selection

Translational reprogramming allows organisms to adapt to changing conditions. Upstream start codons (uAUGs), which are prevalently present in mRNAs, have crucial roles in regulating translation by providing alternative translation start sites1-4. However, what determines this selective initiation of translation between conditions remains unclear. Here, by integrating transcriptome-wide translational and structural analyses during pattern-triggered immunity in Arabidopsis, we found that transcripts with immune-induced translation are enriched with upstream open reading frames (uORFs). Without infection, these uORFs are selectively translated owing to hairpins immediately downstream of uAUGs, presumably by slowing and engaging the scanning preinitiation complex. Modelling using deep learning provides unbiased support for these recognizable double-stranded RNA structures downstream of uAUGs (which we term uAUG-ds) being responsible for the selective translation of uAUGs, and allows the prediction and rational design of translating uAUG-ds. We found that uAUG-ds-mediated regulation can be generalized to human cells. Moreover, uAUG-ds-mediated start-codon selection is dynamically regulated. After immune challenge in plants, induced RNA helicases that are homologous to Ded1p in yeast and DDX3X in humans resolve these structures, allowing ribosomes to bypass uAUGs to translate downstream defence proteins. This study shows that mRNA structures dynamically regulate start-codon selection. The prevalence of this RNA structural feature and the conservation of RNA helicases across kingdoms suggest that mRNA structural remodelling is a general feature of translational reprogramming.