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To investigate gene specificity at the level of translation in both the human genome and viruses, we devised a high-throughput bicistronic assay to quantify cap-independent translation. We uncovered thousands of novel cap-independent translation sequences, and we provide insights on the landscape of translational regulation in both humans and viruses. We find extensive translational elements in the 3' untranslated region of human transcripts and the polyprotein region of uncapped RNA viruses. Through the characterization of regulatory elements underlying cap-independent translation activity, we identify potential mechanisms of secondary structure, short sequence motif, and base pairing with the 18S ribosomal RNA (rRNA). Furthermore, we systematically map the 18S rRNA regions for which reverse complementarity enhances translation. Thus, we make available insights into the mechanisms of translational control in humans and viruses.

SARS-CoV-2 is a coronavirus responsible for the COVID-19 pandemic. In order to understand its pathogenicity, antigenic potential and to develop diagnostic and therapeutic tools, it is essential to portray the full repertoire of its expressed proteins. The SARS-CoV-2 coding capacity map is currently based on computational predictions and relies on homology to other coronaviruses. Since coronaviruses differ in their protein array, especially in the variety of accessory proteins, it is crucial to characterize the specific collection of SARS-CoV-2 translated open reading frames (ORF)s in an unbiased and open-ended manner. Utilizing a suit of ribosome profiling techniques, we present a high-resolution map of the SARS-CoV-2 coding regions, allowing us to accurately quantify the expression of canonical viral ORFs and to identify 23 novel unannotated viral ORFs. These ORFs include several in-frame internal ORFs lying within existing ORFs, resulting in N-terminally truncated products, as well as internal out-of-frameORFs, which generate novel polypeptides. Finally, we detected a prominent initiation at a CUG codon located in the 5'UTR. Although this codon is shared by all SARS-CoV-2 transcripts, the initiation was specific to the genomic RNA, indicating that the genomic RNA harbors unique features that may affect ribosome engagement. Overall, our work reveals the full coding capacity of SARS-CoV-2 genome, providing a rich resource, which will form the basis of future functional studies and diagnostic efforts.

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T cell-mediated immunity plays an important role in controlling SARS-CoV-2 infection, but the repertoire of naturally processed and presented viral epitopes on class I human leukocyte antigen (HLA-I) remains uncharacterized. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two cell lines at different times post infection using mass spectrometry. We found HLA-I peptides derived not only from canonical open reading frames (ORFs) but also from internal out-of-frame ORFs in spike and nucleocapsid not captured by current vaccines. Some peptides from out-of-frame ORFs elicited T cell responses in a humanized mouse model and individuals with COVID-19 that exceeded responses to canonical peptides, including some of the strongest epitopes reported to date. Whole-proteome analysis of infected cells revealed that early expressed viral proteins contribute more to HLA-I presentation and immunogenicity. These biological insights, as well as the discovery of out-of-frame ORF epitopes, will facilitate selection of peptides for immune monitoring and vaccine development.

Despite much research, our understanding of the architecture and cis-regulatory elements of human promoters is still lacking. Here, we devised a high-throughput assay to quantify the activity of approximately 15,000 fully designed sequences that we integrated and expressed from a fixed location within the human genome. We used this method to investigate thousands of native promoters and preinitiation complex (PIC) binding regions followed by in-depth characterization of the sequence motifs underlying promoter activity, including core promoter elements and TF binding sites. We find that core promoters drive transcription mostly unidirectionally and that sequences originating from promoters exhibit stronger activity than those originating from enhancers. By testing multiple synthetic configurations of core promoter elements, we dissect the motifs that positively and negatively regulate transcription as well as the effect of their combinations and distances, including a 10-bp periodicity in the optimal distance between the TATA and the initiator. By comprehensively screening 133 TF binding sites, we find that in contrast to core promoters, TF binding sites maintain similar activity levels in both orientations, supporting a model by which divergent transcription is driven by two distinct unidirectional core promoters sharing bidirectional TF binding sites. Finally, we find a striking agreement between the effect of binding site multiplicity of individual TFs in our assay and their tendency to appear in homotypic clusters throughout the genome. Overall, our study systematically assays the elements that drive expression in core and proximal promoter regions and sheds light on organization principles of regulatory regions in the human genome.

Translational regulation of the p53 mRNA can determine the ratio between p53 and its N-terminal truncated isoforms and therefore has a significant role in determining p53-regulated signaling pathways. Although its importance in cell fate decisions has been demonstrated repeatedly, little is known about the regulatory mechanisms that determine this ratio. Two internal ribosome entry sites (IRESs) residing within the 5'UTR and the coding sequence of p53 mRNA drive the translation of full-length p53 and Δ40p53 isoform, respectively. Here, we report that DAP5, a translation initiation factor shown to positively regulate the translation of various IRES containing mRNAs, promotes IRES-driven translation of p53 mRNA. Upon DAP5 depletion, p53 and Δ40p53 protein levels were decreased, with a greater effect on the N-terminal truncated isoform. Functional analysis using bicistronic vectors driving the expression of a reporter gene from each of these two IRESs indicated that DAP5 preferentially promotes translation from the second IRES residing in the coding sequence. Furthermore, p53 mRNA expressed from a plasmid carrying this second IRES was selectively shifted to lighter polysomes upon DAP5 knockdown. Consequently, Δ40p53 protein levels and the subsequent transcriptional activation of the 14-3-3σ gene, a known target of Δ40p53, were strongly reduced. In addition, we show here that DAP5 interacts with p53 IRES elements in in vitro and in vivo binding studies, proving for the first time that DAP5 directly binds a target mRNA. Thus, through its ability to regulate IRES-dependent translation of the p53 mRNA, DAP5 may control the ratio between different p53 isoforms encoded by a single mRNA.

Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications.