Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans

Evaluation of Eukaryotic mRNA Coding Potential

It is widely discussed that eukaryotic mRNAs can encode several functional polypeptides. Recent progress in NGS and proteomics techniques has resulted in a huge volume of information on potential alternative translation initiation sites and open reading frames (altORFs). However, these data are still incomprehensive, and the vast majority of eukaryotic mRNAs annotated in conventional databases (e.g., GenBank) contain a single ORF (CDS) encoding a protein larger than some arbitrary threshold (commonly 100 amino acid residues). Indeed, some gene functions may relate to the polypeptides encoded by unannotated altORFs, and insufficient information in nucleotide sequence databanks may limit the interpretation of genomics and transcriptomics data. However, despite the need for special experiments to predict altORFs accurately, there are some simple methods for their preliminary mapping.

Translation of genome-wide association study: from genomic signals to biological insights

Since the turn of the 21st century, genome-wide association study (GWAS) have successfully identified genetic signals associated with a myriad of common complex traits and diseases. As we transition from establishing robust genetic associations with diverse phenotypes, the central challenge is now focused on characterizing the underlying functional mechanisms driving these signals. Previous GWAS efforts have revealed multiple variants, each conferring relatively subtle susceptibility, collectively contributing to the pathogenesis of various common diseases. Such variants can further exhibit associations with multiple other traits and differ across ancestries, plus disentangling causal variants from non-causal due to linkage disequilibrium complexities can lead to challenges in drawing direct biological conclusions. Combined with cellular context considerations, such challenges can reduce the capacity to definitively elucidate the biological significance of GWAS signals, limiting the potential to define mechanistic insights. This review will detail current and anticipated approaches for functional interpretation of GWAS signals, both in terms of characterizing the underlying causal variants and the corresponding effector genes.

Acute and prolonged effects of interleukin-33 on cytokines in human cord blood-derived mast cells

Mast cells are multifaceted cells localized in tissues and possess various surface receptors that allow them to respond to inner and external threat signals. Interleukin-33 (IL-33) is a cytokine released by structural cells in response to parasitic infections, mechanical damage, and cell death. IL-33 can activate mast cells, causing them to release an array of mediators. This study aimed to identify the different cytokines released by human cord blood-derived mast cells (hCBMCs) in response to acute and prolonged stimulation with IL-33. For this purpose, a hCBMC model was established and stimulated with 10 ng and 20 ng of recombinant human IL-33 (rhIL-33) for 6 h and 24 h. Total RNA was hybridized using a high-density oligonucleotide microarray. A multiplex assay was performed to assess the released cytokines. Acute exposure to rhIL-33 increased the expression of IL-1α, IL-1β, IL-6, and IL-13, whereas prolonged exposure increased the expression of IL-5 and IL-10, and cytokines were detected in the culture supernatant. WebGestalt analysis revealed that rhIL-33 induces pathways and biological processes related to the immune system and the acute inflammatory response. This study demonstrates that rhIL-33 can activate hCBMCs to release pro- and anti-inflammatory cytokines, eliciting distinct acute and prolonged responses unique to hCBMCs.

Long-read RNA sequencing reveals allele-specific N6-methyladenosine modifications

Long-read sequencing technology enables highly accurate detection of allele-specific RNA expression, providing insights into the effects of genetic variation on splicing and RNA abundance. Furthermore, the ability to directly sequence RNA promises the detection of RNA modifications in tandem with ascertaining the allelic origin of each molecule. Here, we leverage these advantages to determine allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNA. We utilized human and mouse cells with known genetic variants to assign allelic origin of each mRNA molecule combined with a supervised machine learning model to detect read-level m6A modification ratios. Our analyses revealed the importance of sequences adjacent to the DRACH-motif in determining m6A deposition, in addition to allelic differences that directly alter the motif. Moreover, we discovered allele-specific m6A modification (ASM) events with no genetic variants in close proximity to the differentially modified nucleotide, demonstrating the unique advantage of using long reads and surpassing the capabilities of antibody-based short-read approaches. This technological advancement promises to advance our understanding of the role of genetics in determining mRNA modifications.

Cleavage and polyadenylation factors are potential regulators of adipogenesis

OBJECTIVE

Alternative polyadenylation (APA) is a co-transcriptional process that leads to isoform diversity in the 3' ends of mRNAs. APA is known to occur during differentiation, and its dysregulation is observed in diseases like cancer and autoimmune disorders. It has been previously reported that differentiation of 3T3-L1 cells to adipocytes leads to an overall lengthening of mRNAs, but the proteins involved in this regulation have not been identified. The expression levels of subunits of the cleavage and polyadenylation (C/P) complex can regulate the choice of poly(A) site, which in turn can affect different cellular activities. In this paper, we studied the change in levels of C/P proteins during 3T3-L1 differentiation.

RESULTS

We observed that while the RNA expression of these proteins is unchanged during differentiation, the protein levels of some subunits do change, including a decrease in levels of CPSF73, the nuclease that cuts at the poly(A) site. However, overexpression of CPSF73 alone does not affect the efficiency and rate of differentiation.

Translation efficiency covariation across cell types is a conserved organizing principle of mammalian transcriptomes

Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.

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 sequence, 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.

RiboGraph: an interactive visualization system for ribosome profiling data at read length resolution

MOTIVATION

Ribosome profiling is a widely-used technique for measuring ribosome occupancy at nucleotide resolution. However, the need to analyze this data at nucleotide resolution introduces unique challenges in data visualization and analyses.

RESULTS

In this study, we introduce RiboGraph, a dedicated visualization tool designed to work with .ribo files, a specialized and efficient format for ribosome occupancy data. Unlike existing solutions that rely on large alignment files and time-consuming preprocessing steps, RiboGraph operates on a purpose designed compact file type. This efficiency allows for interactive, real-time visualization at ribosome-protected fragment length resolution. By providing an integrated toolset, RiboGraph empowers researchers to conduct comprehensive visual analysis of ribosome occupancy data.

AVAILABILITY AND IMPLEMENTATION

Source code, step-by-step installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling/ribograph. On the same page, we provide test files and a step-by-step tutorial highlighting the key features of RiboGraph.

Cytosolic Ribosomal Protein Haploinsufficiency affects Mitochondrial Morphology and Respiration

The interplay between ribosomal protein composition and mitochondrial function is essential for sustaining energy homeostasis. Precise stoichiometric production of ribosomal proteins is crucial to maximize protein synthesis efficiency while reducing the energy costs to the cell. However, the impact of this balance on mitochondrial ATP generation, morphology and function remains unclear. Particularly, the loss of a single copy ribosomal protein gene is observed in Mendelian disorders like Diamond Blackfan Anemia and is common in somatic tumors, yet the implications of this imbalance on mitochondrial function and energy dynamics are still unclear. In this study, we investigated the impact of haploinsufficiency for four ribosomal protein genes implicated in ribosomopathy disorders (rps-10, rpl-5, rpl-33, rps-23) in Caenorhabditis elegans and corresponding reductions in human lymphoblast cells. Our findings uncover significant, albeit variably penetrant, mitochondrial morphological differences across these mutants, alongside an upregulation of glutathione transferases, and SKN-1 dependent increase in oxidative stress resistance, indicative of increased ROS production. Specifically, loss of a single copy of rps-10 in C. elegans led to decreased mitochondrial activity, characterized by lower energy levels and reduced oxygen consumption. A similar reduction in mitochondrial activity and energy levels was observed in human leukemia cells with a 50% reduction in RPS10 transcript levels. Importantly, we also observed alterations in the translation efficiency of nuclear and mitochondrial electron transport chain components in response to reductions in ribosomal protein genes' expression in both C. elegans and human cells. This suggests a conserved mechanism whereby the synthesis of components vital for mitochondrial function are adjusted in the face of compromised ribosomal machinery. Finally, mitochondrial membrane and cytosolic ribosomal components exhibited significant covariation at the RNA and translation efficiency level in lymphoblastoid cells across a diverse group of individuals, emphasizing the interplay between the protein synthesis machinery and mitochondrial energy production. By uncovering the impact of ribosomal protein haploinsufficiency on the translation efficiency of electron transport chain components, mitochondrial physiology, and the adaptive stress responses, we provide evidence for an evolutionarily conserved strategy to safeguard cellular functionality under genetic stress.

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.

Enhancement of SARS-CoV-2 mRNA Vaccine Efficacy through the Application of TMSB10 UTR for Superior Antigen Presentation and Immune Activation

The development of effective vaccines against SARS-CoV-2 remains a critical challenge amidst the ongoing global pandemic. This study introduces a novel approach to enhancing mRNA vaccine efficacy by leveraging the untranslated region (UTR) of TMSB10, a gene identified for its significant mRNA abundance in antigen-presenting cells. Utilizing the GEO database, we identified TMSB10 among nine genes, with the highest mRNA abundance in dendritic cell subtypes. Subsequent experiments revealed that TMSB10's UTR significantly enhances the expression of a reporter gene in both antigen-presenting and 293T cells, surpassing other candidates and a previously optimized natural UTR. A comparative analysis demonstrated that TMSB10 UTR not only facilitated a higher reporter gene expression in vitro but also showed marked superiority in vivo, leading to enhanced specific humoral and cellular immune responses against the SARS-CoV-2 Delta variant RBD antigen. Specifically, vaccines incorporating TMSB10 UTR induced significantly higher levels of specific IgG antibodies and promoted a robust T-cell immune response, characterized by the increased secretion of IFN-γ and IL-4 and the proliferation of CD4+ and CD8+ T cells. These findings underscore the potential of TMSB10 UTR as a strategic component in mRNA vaccine design, offering a promising avenue to bolster vaccine-induced immunity against SARS-CoV-2 and, potentially, other pathogens.

Transcriptional and translational landscape fine-tune genome annotation and explores translation control in cotton

INTRODUCTION

The unavailability of intergenic region annotation in whole genome sequencing and pan-genomics hinders efforts to enhance crop improvement.

OBJECTIVES

Despite advances in research, the impact of post-transcriptional regulation on fiber development and translatome profiling at different stages of fiber growth in cotton (G. hirsutum) remains unexplored.

METHODS

We utilized a combination of reference-guided de novo transcriptome assembly and ribosome profiling techniques to uncover the hidden mechanisms of translational control in eight distinct tissues of upland cotton.

RESULTS

Our study identified P-site distribution at three-nucleotide periodicity and dominant ribosome footprint at 27 nucleotides. Specifically, we have detected 1,589 small open reading frames (sORFs), including 1,376 upstream ORFs (uORFs) and 213 downstream ORFs (dORFs), as well as 552 long non-coding RNAs (lncRNAs) with potential coding functions, which fine-tune the annotation of the cotton genome. Further, we have identified novel genes and lncRNAs with strong translation efficiency (TE), while sORFs were found to affect mRNA transcription levels during fiber elongation. The reliability of these findings was confirmed by the high consistency in correlation and synergetic fold change between RNA-sequencing (RNA-seq) and Ribosome-sequencing (Ribo-seq) analyses. Additionally, integrated omics analysis of the normal fiber ZM24 and short fiber pag1 cotton mutant revealed several differentially expressed genes (DEGs), and fiber-specific expressed (high/low) genes associated with sORFs (uORFs and dORFs). These findings were further supported by the overexpression and knockdown of GhKCS6, a gene associated with sORFs in cotton, and demonstrated the potential regulation of the mechanism governing fiber elongation on both the transcriptional and post-transcriptional levels.

CONCLUSION

Reference-guided transcriptome assembly and the identification of novel transcripts fine-tune the annotation of the cotton genome and predicted the landscape of fiber development. Our approach provided a high-throughput method, based on multi-omics, for discovering unannotated ORFs, hidden translational control, and complex regulatory mechanisms in crop plants.

Navigating the blurred path of mixed neuroimmune signaling

Evolution has created complex mechanisms to sense environmental danger and protect tissues, with the nervous and immune systems playing pivotal roles. These systems work together, coordinating local and systemic reflexes to restore homeostasis in response to tissue injury and infection. By sharing receptors and ligands, they influence the pathogenesis of various diseases. Recently, a less-explored aspect of neuroimmune communication has emerged: the release of neuropeptides from immune cells and cytokines/chemokines from sensory neurons. This article reviews evidence of this unique neuroimmune interplay and its impact on the development of allergy, inflammation, itch, and pain. We highlight the effects of this neuroimmune signaling on vital processes such as host defense, tissue repair, and inflammation resolution, providing avenues for exploration of the underlying mechanisms and therapeutic potential of this signaling.

RiboGraph: An interactive visualization system for ribosome profiling data at read length resolution

Ribosome profiling is a widely-used technique for measuring ribosome occupancy at nucleotide resolution. However, the need to analyze this data at nucleotide resolution introduces unique challenges in data visualization and analyses. In this study, we introduce RiboGraph, a dedicated visualization tool designed to work with .ribo files, a specialized and efficient format for ribosome occupancy data. Unlike existing solutions that rely on large alignment files and time-consuming preprocessing steps, RiboGraph operates on a purpose designed compact file type and eliminates the need for data preprocessing. This efficiency allows for interactive, real-time visualization at ribosome-protected fragment length resolution. By providing an integrated toolset, RiboGraph empowers researchers to conduct comprehensive visual analysis of ribosome occupancy data.

Availability and Implementation

Source code, step-by-step installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling/ribograph. On the same page, we provide test files and a step-by-step tutorial highlighting the key features of RiboGraph.

Deficiency of the ribosomal protein uS10 (RPS20) reorganizes human cells translatome according to the abundance, CDS length and GC content of mRNAs

Ribosomal protein uS10, a product of the RPS20 gene, is an essential constituent of the small (40S) subunit of the human ribosome. Disruptive mutations in its gene are associated with a predisposition to hereditary colorectal carcinoma. Here, using HEK293T cells, we show that a deficiency of this protein leads to a decrease in the level of ribosomes (ribosomal shortage). RNA sequencing of the total and polysome-associated mRNA samples reveals hundreds of genes differentially expressed in the transcriptome (t)DEGs and translatome (p)DEGs under conditions of uS10 deficiency. We demonstrate that the (t)DEG and (p)DEG sets partially overlap, determine genes with altered translational efficiency (TE) and identify cellular processes affected by uS10 deficiency-induced ribosomal shortage. We reveal that translated mRNAs of upregulated (p)DEGs and genes with altered TE in uS10-deficient cells are generally more abundant and that their GC contents are significantly lower than those of the respective downregulated sets. We also observed that upregulated (p)DEGs have longer coding sequences. Based on our findings, we propose a combinatorial model describing the process of reorganization of mRNA translation under conditions of ribosomal shortage. Our results reveal rules according to which ribosomal shortage reorganizes the transcriptome and translatome repertoires of actively proliferating cells.

3'-tRF-CysGCA overexpression in HEK-293 cells alters the global expression profile and modulates cellular processes and pathways

tRNA fragments (tRFs) are small non-coding RNAs generated through specific cleavage of tRNAs and involved in various biological processes. Among the different types of tRFs, the 3'-tRFs have attracted scientific interest due to their regulatory role in gene expression. In this study, we investigated the role of 3'-tRF-CysGCA, a tRF deriving from cleavage in the T-loop of tRNACysGCA, in the regulation of gene expression in HEK-293 cells. Previous studies have shown that 3'-tRF-CysGCA is incorporated into the RISC complex and interacts with Argonaute proteins, suggesting its involvement in the regulation of gene expression. However, the general role and effect of the deregulation of 3'-tRF-CysGCA levels in human cells have not been investigated so far. To fill this gap, we stably overexpressed 3'-tRF-CysGCA in HEK-293 cells and performed transcriptomic and proteomic analyses. Moreover, we validated the interaction of this tRF with putative targets, the levels of which were found to be affected by 3'-tRF-CysGCA overexpression. Lastly, we investigated the implication of 3'-tRF-CysGCA in various pathways using extensive bioinformatics analysis. Our results indicate that 3'-tRF-CysGCA overexpression led to changes in the global gene expression profile of HEK-293 cells and that multiple cellular pathways were affected by the deregulation of the levels of this tRF. Additionally, we demonstrated that 3'-tRF-CysGCA directly interacts with thymopoietin (TMPO) transcript variant 1 (also known as LAP2α), leading to modulation of its levels. In conclusion, our findings suggest that 3'-tRF-CysGCA plays a significant role in gene expression regulation and highlight the importance of this tRF in cellular processes.

Integrated multiplexed assays of variant effect reveal cis-regulatory 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 and 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.

The impact of common variants on gene expression in the human brain: from RNA to protein to schizophrenia risk

Background

The impact of genetic variants on gene expression has been intensely studied at the transcription level, yielding in valuable insights into the association between genes and the risk of complex disorders, such as schizophrenia (SCZ). However, the downstream impact of these variants and the molecular mechanisms connecting transcription variation to disease risk are not well understood.

Results

We quantitated ribosome occupancy in prefrontal cortex samples of the BrainGVEX cohort. Together with transcriptomics and proteomics data from the same cohort, we performed cis-Quantitative Trait Locus (QTL) mapping and identified 3,253 expression QTLs (eQTLs), 1,344 ribosome occupancy QTLs (rQTLs), and 657 protein QTLs (pQTLs) out of 7,458 genes quantitated in all three omics types from 185 samples. Of the eQTLs identified, only 34% have their effects propagated to the protein level. Further analysis on the effect size of prefrontal cortex eQTLs identified from an independent dataset showed clear post-transcriptional attenuation of eQTL effects. To investigate the biological relevance of the attenuated eQTLs, we identified 70 expression-specific QTLs (esQTLs), 51 ribosome-occupancy-specific QTLs (rsQTLs), and 107 protein-specific QTLs (psQTLs). Five of these omics-specific QTLs showed strong colocalization with SCZ GWAS signals, three of them are esQTLs. The limited number of GWAS colocalization discoveries from omics-specific QTLs and the apparent prevalence of eQTL attenuation prompted us to take a complementary approach to investigate the functional relevance of attenuated eQTLs. Using S-PrediXcan we identified 74 SCZ risk genes, 34% of which were novel, and 67% of these risk genes were replicated in a MR-Egger test. Notably, 52 out of 74 risk genes were identified using eQTL data and 70% of these SCZ-risk-gene-driving eQTLs show little to no evidence of driving corresponding variations at the protein level.

Conclusion

The effect of eQTLs on gene expression in the prefrontal cortex is commonly attenuated post-transcriptionally. Many of the attenuated eQTLs still correlate with SCZ GWAS signal. Further investigation is needed to elucidate a mechanistic link between attenuated eQTLs and SCZ disease risk.

SGLT1/2 inhibition improves glycemic control and multi-organ protection in type 1 diabetes

Sodium glucose cotransporters (SGLTs) are transport proteins that are expressed throughout the body. Inhibition of SGLTs is a relatively novel therapeutic strategy to improve glycemic control and has been shown to promote cardiorenal benefits. Dual SGLT1/2 inhibitors (SGLT1/2i) such as sotagliflozin target both SGLT1 and 2 proteins. Sotagliflozin or vehicle was administered to diabetic Akimba mice for 8 weeks at a dose of 25 mg/kg/day. Urine glucose levels, water consumption, and body weight were measured weekly. Serum, kidney, pancreas, and brain tissue were harvested under terminal anesthesia. Tissues were assessed using immunohistochemistry or ELISA techniques. Treatment with sotagliflozin promoted multiple metabolic benefits in diabetic Akimba mice resulting in decreased blood glucose and improved polydipsia. Sotagliflozin also prevented mortalities associated with diabetes. Our data suggests that there is the possibility that combined SGLT1/2i may be superior to SGLT2i in controlling glucose homeostasis and provides protection of multiple organs affected by diabetes.

Pyruvate Kinase M (PKM) binds ribosomes in a poly-ADP ribosylation dependent manner to induce translational stalling

In light of the numerous studies identifying post-transcriptional regulators on the surface of the endoplasmic reticulum (ER), we asked whether there are factors that regulate compartment specific mRNA translation in human cells. Using a proteomic survey of spatially regulated polysome interacting proteins, we identified the glycolytic enzyme Pyruvate Kinase M (PKM) as a cytosolic (i.e. ER-excluded) polysome interactor and investigated how it influences mRNA translation. We discovered that the PKM-polysome interaction is directly regulated by ADP levels-providing a link between carbohydrate metabolism and mRNA translation. By performing enhanced crosslinking immunoprecipitation-sequencing (eCLIP-seq), we found that PKM crosslinks to mRNA sequences that are immediately downstream of regions that encode lysine- and glutamate-enriched tracts. Using ribosome footprint protection sequencing, we found that PKM binding to ribosomes causes translational stalling near lysine and glutamate encoding sequences. Lastly, we observed that PKM recruitment to polysomes is dependent on poly-ADP ribosylation activity (PARylation)-and may depend on co-translational PARylation of lysine and glutamate residues of nascent polypeptide chains. Overall, our study uncovers a novel role for PKM in post-transcriptional gene regulation, linking cellular metabolism and mRNA translation.

Multi-Omics Profiling for Health

The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.

Evolutionary trade-off and mutational bias could favor transcriptional over translational divergence within paralog pairs

How changes in the different steps of protein synthesis-transcription, translation and degradation-contribute to differences of protein abundance among genes is not fully understood. There is however accumulating evidence that transcriptional divergence might have a prominent role. Here, we show that yeast paralogous genes are more divergent in transcription than in translation. We explore two causal mechanisms for this predominance of transcriptional divergence: an evolutionary trade-off between the precision and economy of gene expression and a larger mutational target size for transcription. Performing simulations within a minimal model of post-duplication evolution, we find that both mechanisms are consistent with the observed divergence patterns. We also investigate how additional properties of the effects of mutations on gene expression, such as their asymmetry and correlation across levels of regulation, can shape the evolution of paralogs. Our results highlight the importance of fully characterizing the distributions of mutational effects on transcription and translation. They also show how general trade-offs in cellular processes and mutation bias can have far-reaching evolutionary impacts.

satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect

The impact of millions of individual genetic variants on molecular phenotypes in coding sequences remains unknown. Multiplexed assays of variant effect (MAVEs) are scalable methods to annotate relevant variants, but existing software lacks standardization, requires cumbersome configuration, and does not scale to large targets. We present satmut_utils as a flexible solution for simulation and variant quantification. We then benchmark MAVE software using simulated and real MAVE data. We finally determine mRNA abundance for thousands of cystathionine beta-synthase variants using two experimental methods. The satmut_utils package enables high-performance analysis of MAVEs and reveals the capability of variants to alter mRNA abundance.

Exercise builds the scaffold of life: muscle extracellular matrix biomarker responses to physical activity, inactivity, and aging

Skeletal muscle extracellular matrix (ECM) is critical for muscle force production and the regulation of important physiological processes during growth, regeneration, and remodelling. ECM remodelling is a tightly orchestrated process, sensitive to multi-directional tensile and compressive stresses and damaging stimuli, and its assessment can convey important information on rehabilitation effectiveness, injury, and disease. Despite its profound importance, ECM biomarkers are underused in studies examining the effects of exercise, disuse, or aging on muscle function, growth, and structure. This review examines patterns of short- and long-term changes in the synthesis and concentrations of ECM markers in biofluids and tissues, which may be useful for describing the time course of ECM remodelling following physical activity and disuse. Forces imposed on the ECM during physical activity critically affect cell signalling while disuse causes non-optimal adaptations, including connective tissue proliferation. The goal of this review is to inform researchers, and rehabilitation, medical, and exercise practitioners better about the role of ECM biomarkers in research and clinical environments to accelerate the development of targeted physical activity treatments, improve ECM status assessment, and enhance function in aging, injury, and disease.

Selective ribosome profiling as a tool to study interactions of translating ribosomes in mammalian cells

The processing, membrane targeting and folding of newly synthesized polypeptides is closely linked to their synthesis at the ribosome. A network of enzymes, chaperones and targeting factors engages ribosome-nascent chain complexes (RNCs) to support these maturation processes. Exploring the modes of action of this machinery is critical for our understanding of functional protein biogenesis. Selective ribosome profiling (SeRP) is a powerful method for interrogating co-translational interactions of maturation factors with RNCs. It provides proteome-wide information on the factor's nascent chain interactome, the timing of factor binding and release during the progress of translation of individual nascent chain species, and the mechanisms and features controlling factor engagement. SeRP is based on the combination of two ribosome profiling (RP) experiments performed on the same cell population. In one experiment the ribosome-protected mRNA footprints of all translating ribosomes of the cell are sequenced (total translatome), while the other experiment detects only the ribosome footprints of the subpopulation of ribosomes engaged by the factor of interest (selected translatome). The codon-specific ratio of ribosome footprint densities from selected over total translatome reports on the factor enrichment at specific nascent chains. In this chapter, we provide a detailed SeRP protocol for mammalian cells. The protocol includes instructions on cell growth and cell harvest, stabilization of factor-RNC interactions, nuclease digest and purification of (factor-engaged) monosomes, as well as preparation of cDNA libraries from ribosome footprint fragments and deep sequencing data analysis. Purification protocols of factor-engaged monosomes and experimental results are exemplified for the human ribosomal tunnel exit-binding factor Ebp1 and chaperone Hsp90, but the protocols are readily adaptable to other co-translationally acting mammalian factors.

Translational landscape in human early neural fate determination

Gene expression regulation in eukaryotes is a multi-level process, including transcription, mRNA translation and protein turnover. Many studies have reported sophisticated transcriptional regulation during neural development, but the global translational dynamics are still ambiguous. Here, we differentiate human embryonic stem cells (ESCs) into neural progenitor cells (NPCs) with high efficiency and perform ribosome sequencing and RNA sequencing on both ESCs and NPCs. Data analysis reveals that translational controls engage in many crucial pathways and contribute significantly to regulation of neural fate determination. Furthermore, we show that the sequence characteristics of the untranslated region (UTR) might regulate translation efficiency. Specifically, genes with short 5'UTR and intense Kozak sequence are associated with high translation efficiency in human ESCs, whereas genes with long 3'UTR are related to high translation efficiency in NPCs. In addition, we have identified four biasedly used codons (GAC, GAT, AGA and AGG) and dozens of short open reading frames during neural progenitor differentiation. Thus, our study reveals the translational landscape during early human neural differentiation and provides insights into the regulation of cell fate determination at the translational level.

Detection of COVID-19-related biomarkers by electrochemical biosensors and potential for diagnosis, prognosis, and prediction of the course of the disease in the context of personalized medicine

As a more efficient and effective way to address disease diagnosis and intervention, cutting-edge technologies, devices, therapeutic approaches, and practices have emerged within the personalized medicine concept depending on the particular patient's biology and the molecular basis of the disease. Personalized medicine is expected to play a pivotal role in assessing disease risk or predicting response to treatment, understanding a person's health status, and, therefore, health care decision-making. This work discusses electrochemical biosensors for monitoring multiparametric biomarkers at different molecular levels and their potential to elucidate the health status of an individual in a personalized manner. In particular, and as an illustration, we discuss several aspects of the infection produced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a current health care concern worldwide. This includes SARS-CoV-2 structure, mechanism of infection, biomarkers, and electrochemical biosensors most commonly explored for diagnostics, prognostics, and potentially assessing the risk of complications in patients in the context of personalized medicine. Finally, some concluding remarks and perspectives hint at the use of electrochemical biosensors in the frame of other cutting-edge converging/emerging technologies toward the inauguration of a new paradigm of personalized medicine.

Cytosolic and mitochondrial ribosomal proteins mediate the locust phase transition via divergence of translational profiles

The phase transition from solitary to gregarious locusts is crucial in outbreaks of locust plague, which threaten agricultural yield and food security. Research on the regulatory mechanisms of phase transition in locusts has focused primarily on the transcriptional or posttranslational level. However, the translational regulation of phase transition is unexplored. Here, we show a phase-dependent pattern at the translation level, which exhibits different polysome profiles between gregarious and solitary locusts. The gregarious locusts exhibit significant increases in 60S and polyribosomes, while solitary locusts possess higher peaks of the monoribosome and a specific "halfmer." The polysome profiles, a molecular phenotype, respond to changes in population density. In gregarious locusts, ten genes involved in the cytosolic ribosome pathway exhibited increased translational efficiency (TE). In solitary locusts, five genes from the mitochondrial ribosome pathway displayed increased TE. The high expression of large ribosomal protein 7 at the translational level promotes accumulation of the free 60S ribosomal subunit in gregarious locusts, while solitary locusts employ mitochondrial small ribosomal protein 18c to induce the assembly of mitochondrial ribosomes, causing divergence of the translational profiles and behavioral transition. This study reveals the translational regulatory mechanism of locust phase transition, in which the locusts employ divergent ribosome pathways to cope with changes in population density.

Ribosome biogenesis in disease: new players and therapeutic targets

The ribosome is a multi-unit complex that translates mRNA into protein. Ribosome biogenesis is the process that generates ribosomes and plays an essential role in cell proliferation, differentiation, apoptosis, development, and transformation. The mTORC1, Myc, and noncoding RNA signaling pathways are the primary mediators that work jointly with RNA polymerases and ribosome proteins to control ribosome biogenesis and protein synthesis. Activation of mTORC1 is required for normal fetal growth and development and tissue regeneration after birth. Myc is implicated in cancer development by enhancing RNA Pol II activity, leading to uncontrolled cancer cell growth. The deregulation of noncoding RNAs such as microRNAs, long noncoding RNAs, and circular RNAs is involved in developing blood, neurodegenerative diseases, and atherosclerosis. We review the similarities and differences between eukaryotic and bacterial ribosomes and the molecular mechanism of ribosome-targeting antibiotics and bacterial resistance. We also review the most recent findings of ribosome dysfunction in COVID-19 and other conditions and discuss the consequences of ribosome frameshifting, ribosome-stalling, and ribosome-collision. We summarize the role of ribosome biogenesis in the development of various diseases. Furthermore, we review the current clinical trials, prospective vaccines for COVID-19, and therapies targeting ribosome biogenesis in cancer, cardiovascular disease, aging, and neurodegenerative disease.

A network approach for low dimensional signatures from high throughput data

One of the main objectives of high-throughput genomics studies is to obtain a low-dimensional set of observables-a signature-for sample classification purposes (diagnosis, prognosis, stratification). Biological data, such as gene or protein expression, are commonly characterized by an up/down regulation behavior, for which discriminant-based methods could perform with high accuracy and easy interpretability. To obtain the most out of these methods features selection is even more critical, but it is known to be a NP-hard problem, and thus most feature selection approaches focuses on one feature at the time (k-best, Sequential Feature Selection, recursive feature elimination). We propose DNetPRO, Discriminant Analysis with Network PROcessing, a supervised network-based signature identification method. This method implements a network-based heuristic to generate one or more signatures out of the best performing feature pairs. The algorithm is easily scalable, allowing efficient computing for high number of observables ([Formula: see text]-[Formula: see text]). We show applications on real high-throughput genomic datasets in which our method outperforms existing results, or is compatible with them but with a smaller number of selected features. Moreover, the geometrical simplicity of the resulting class-separation surfaces allows a clearer interpretation of the obtained signatures in comparison to nonlinear classification models.

The missing link between genetic association and regulatory function

The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic datasets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene-trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic expression QTLs, suggesting that better models are needed. The field must confront this deficit and pursue this 'missing regulation.'

The Emerging Role of uORF-Encoded uPeptides and HLA uLigands in Cellular and Tumor Biology

Recent technological advances have facilitated the detection of numerous non-canonical human peptides derived from regulatory regions of mRNAs, long non-coding RNAs, and other cryptic transcripts. In this review, we first give an overview of the classification of these novel peptides and summarize recent improvements in their annotation and detection by ribosome profiling, mass spectrometry, and individual experimental analysis. A large fraction of the novel peptides originates from translation at upstream open reading frames (uORFs) that are located within the transcript leader sequence of regular mRNA. In humans, uORF-encoded peptides (uPeptides) have been detected in both healthy and malignantly transformed cells and emerge as important regulators in cellular and immunological pathways. In the second part of the review, we focus on various functional implications of uPeptides. As uPeptides frequently act at the transition of translational regulation and individual peptide function, we describe the mechanistic modes of translational regulation through ribosome stalling, the involvement in cellular programs through protein interaction and complex formation, and their role within the human leukocyte antigen (HLA)-associated immunopeptidome as HLA uLigands. We delineate how malignant transformation may lead to the formation of novel uORFs, uPeptides, or HLA uLigands and explain their potential implication in tumor biology. Ultimately, we speculate on a potential use of uPeptides as peptide drugs and discuss how uPeptides and HLA uLigands may facilitate translational inhibition of oncogenic protein messages and immunotherapeutic approaches in cancer therapy.

Tandem repeats ubiquitously flank and contribute to translation initiation sites

Background

While the evolutionary divergence of cis-regulatory sequences impacts translation initiation sites (TISs), the implication of tandem repeats (TRs) in TIS selection remains largely elusive. Here, we employed the TIS homology concept to study a possible link between TRs of all core lengths and repeats with TISs.

Methods

Human, as reference sequence, and 83 other species were selected, and data was extracted on the entire protein-coding genes (n = 1,611,368) and transcripts (n = 2,730,515) annotated for those species from Ensembl 102. Following TIS identification, two different weighing vectors were employed to assign TIS homology, and the co-occurrence pattern of TISs with the upstream flanking TRs was studied in the selected species. The results were assessed in 10-fold cross-validation.

Results

On average, every TIS was flanked by 1.19 TRs of various categories within its 120 bp upstream sequence, per species. We detected statistically significant enrichment of non-homologous human TISs co-occurring with human-specific TRs. On the contrary, homologous human TISs co-occurred significantly with non-human-specific TRs. 2991 human genes had at least one transcript, TIS of which was flanked by a human-specific TR. Text mining of a number of the identified genes, such as CACNA1A, EIF5AL1, FOXK1, GABRB2, MYH2, SLC6A8, and TTN, yielded predominant expression and functions in the human brain and/or skeletal muscle.

Conclusion

We conclude that TRs ubiquitously flank and contribute to TIS selection at the trans-species level. Future functional analyses, such as a combination of genome editing strategies and in vitro protein synthesis may be employed to further investigate the impact of TRs on TIS selection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01075-5.

METTL14 is required for exercise-induced cardiac hypertrophy and protects against myocardial ischemia-reperfusion injury

RNA m⁶A modification is the most widely distributed RNA methylation and is closely related to various pathophysiological processes. Although the benefit of regular exercise on the heart has been well recognized, the role of RNA m⁶A in exercise training and exercise-induced physiological cardiac hypertrophy remains largely unknown. Here, we show that endurance exercise training leads to reduced cardiac mRNA m⁶A levels. METTL14 is downregulated by exercise, both at the level of RNA m⁶A and at the protein level. In vivo, wild-type METTL14 overexpression, but not MTase inactive mutant METTL14, blocks exercise-induced physiological cardiac hypertrophy. Cardiac-specific METTL14 knockdown attenuates acute ischemia-reperfusion injury as well as cardiac dysfunction in ischemia-reperfusion remodeling. Mechanistically, silencing METTL14 suppresses Phlpp2 mRNA m⁶A modifications and activates Akt-S473, in turn regulating cardiomyocyte growth and apoptosis. Our data indicates that METTL14 plays an important role in maintaining cardiac homeostasis. METTL14 downregulation represents a promising therapeutic strategy to attenuate cardiac remodeling.

Gender-related differentially expressed genes in pancreatic cancer: possible culprits or accomplices?

Pancreatic cancer (PC) is one of the leading causes of cancer mortality worldwide, and its incidence and mortality rate in several regions is higher in male patients. Although numerous efforts have been made to enhance the clinical outcomes of existing therapeutic regimens, their efficiency is still low, and drug resistance usually occurs in many patients. In addition, the exact underlying molecular basis that makes PC slightly more prevalent among males remains unknown. Providing information regarding the possible association between gender and PC tumorigenesis may offer important clues for how certain molecular cross-talks can affect PC initiation and/or progression. In this study, we used several microarray expression data to identify the common up- and downregulated genes within one specific gender, which were also specified to have binding sites for androgen and/or estrogen receptors. Using functional enrichment analysis among the others, for all the gene sets found in this study, we have shed light on the plausible importance of the androgenic effectors in tumorigenesis, such as the androgen-regulated expression of the GLI transcription factor and the potential role of testosterone in the extracellular matrix (ECM)–cell interaction, which are known for their importance in tumorigenesis. Moreover, we demonstrated that the biological process axon guidance was highlighted regarding the upregulated genes in male patients. Overall, identification of gene candidates as the possible link between gender and PC progression or survival rates may help in developing strategies to reduce the incidence of this cancer.

Developing high-affinity decoy receptors to treat multiple myeloma and diffuse large B cell lymphoma

Disease relapse and treatment-induced immunotoxicity pose significant clinical challenges for patients with hematological cancers. Here, we reveal distinctive requirements for neutralizing TNF receptor ligands APRIL and BAFF and their receptor activity in MM and DLBCL, impacting protein translation and production in MM cells and modulating the translation efficiency of the ATM interactor (ATMIN/ACSIZ). Therapeutically, we investigated the use of BCMA decoy receptor (sBCMA-Fc) as an inhibitor of APRIL and BAFF. While wild-type sBCMA-Fc effectively blocked APRIL signaling in MM, it lacked activity in DLBCL due to its weak BAFF binding. To expand the therapeutic utility of sBCMA-Fc, we engineered an affinity-enhanced mutant sBCMA-Fc fusion molecule (sBCMA-Fc V3) 4- and 500-fold stronger in binding to APRIL and BAFF, respectively. The mutant sBCMA-Fc V3 clone significantly enhanced antitumor activity against both MM and DLBCL. Importantly, we also demonstrated an adequate toxicity profile and on-target mechanism of action in nonhuman primate studies.

Proteomics approaches to characterize the immune responses in cancer

Despite the dynamic development of cancer research, annually millions of people die of cancer. The human immune system is the major 'guard' against tumor development. Unfortunately, cancer cells have the ability to evade the immune system and continue to grow. The proper understanding of the intricate immune response in tumorigenesis remains the holy grail of cancer immunology and designing effective immunotherapy. To decode the immune responses in cancer, in recent years, proteomics studies have received considerable attention. Proteomics studies focus on the detection and quantification of proteins, which are the effectors of biological functions, and as such, are proven to reflect the cell state more accurately, in comparison to genomic or transcriptomic studies. In this review, we discuss the proteomics studies applied to characterize the immune responses in cancer and tumor immune microenvironment heterogeneity. Further, we describe emerging single-cell proteomics approaches that have the potential to be applied in cancer immunity studies.

Light Scattering Technology-Combined Ligation-Dependent Loop-Mediated Isothermal Amplification (LL-LAMP) for Sensitive Detection of RNA

Loop-mediated isothermal amplification (LAMP) has been widely used in nucleic acid assay because of its high specificity, sensitivity, and isothermal property. However, the complexity of amplification product detection is still a major challenge for its wide applications. Herein, we developed a light scattering technology-assisted, low-cost, and simple detection manner of LAMP products without expensive reagents and complicated instruments. Only needing to add a kind of strong acid to the amplification products, the amplification products can aggregate into large particles in a strongly acidic medium, and large particles can produce strong light scattering, which shows a good proportional relationship with the number of amplification products in a wide range. The proposed method shows excellent sensitivity and high specificity that can quantify RNA as low as 100 aM with a single-base resolution.

Variation in upstream open reading frames contributes to allelic diversity in maize protein abundance

SignificanceProteins are the machinery which execute essential cellular functions. However, measuring their abundance within an organism can be difficult and resource-intensive. Cells use a variety of mechanisms to control protein synthesis from mRNA, including short open reading frames (uORFs) that lie upstream of the main coding sequence. Ribosomes can preferentially translate uORFs instead of the main coding sequence, leading to reduced translation of the main protein. In this study, we show that uORF sequence variation between individuals can lead to different rates of protein translation and thus variable protein abundances. We also demonstrate that natural variation in uORFs occurs frequently and can be linked to whole-plant phenotypes, indicating that uORF sequence variation likely contributes to plant adaptation.

Optimization of Ribosome Footprinting Conditions for Ribo-Seq in Human and Drosophila melanogaster Tissue Culture Cells

Our understanding of mRNA translation and its regulation has been transformed by the development of ribosome profiling. This approach relies upon RNase footprinting of translating ribosomes in a precise manner to generate an accurate snapshot of ribosome positions with nucleotide resolution. Here we tested a variety of conditions, which contribute to the preciseness of ribosome footprinting and therefore the success of ribosome profiling. We found that NaCl concentration, RNaseI source, RNaseI amount, and temperature of footprinting all contributed to the quality of ribosome footprinting in human neuroblastoma SH-SY5Y cells. These ideal conditions for footprinting also improved footprint quality when used with Drosophila melanogaster S2 cells. Footprinting under the same conditions generated different footprints sizes and framing patterns in human and D. melanogaster cells. We also found that treatment of S2 cells with cycloheximide prior to footprinting impacted the distribution of footprints across ORFs, without affecting overall read length distribution and framing pattern, as previously found in other organisms. Together our results indicate that a variety of factors affect ribosome footprint quality and the nature of precise footprinting varies across species.

CRYPTOCHROMES promote daily protein homeostasis

The daily organisation of most mammalian cellular functions is attributed to circadian regulation of clock-controlled protein expression, driven by daily cycles of CRYPTOCHROME-dependent transcriptional feedback repression. To test this, we used quantitative mass spectrometry to compare wild-type and CRY-deficient fibroblasts under constant conditions. In CRY-deficient cells, we found that temporal variation in protein, phosphopeptide, and K+ abundance was at least as great as wild-type controls. Most strikingly, the extent of temporal variation within either genotype was much smaller than overall differences in proteome composition between WT and CRY-deficient cells. This proteome imbalance in CRY-deficient cells and tissues was associated with increased susceptibility to proteotoxic stress, which impairs circadian robustness, and may contribute to the wide-ranging phenotypes of CRY-deficient mice. Rather than generating large-scale daily variation in proteome composition, we suggest it is plausible that the various transcriptional and post-translational functions of CRY proteins ultimately act to maintain protein and osmotic homeostasis against daily perturbation.

The Glypican-1/HGF/C-Met and Glypican-1/VEGF/VEGFR2 Ternary Complexes Regulate Hair Follicle Angiogenesis

The hair renewal involves changes in the morphology of the hair follicle and its micro-vascularization. In alopecia, the hair cycle is accelerated, resulting in the formation of thinner and shorter hair. In addition, alopecia is associated with a decrease in the micro-vascularization of the hair follicles. In this study, the role of glypicans (GPCs) was analyzed in the regulation of the angiogenesis of human dermal microvascular endothelial cells (HDMEC). The analysis of glypican gene expression showed that GPC1 is the major glypican expressed by human keratinocytes of outer root sheath (KORS), human hair follicle dermal papilla cells (HHFDPC) and HDMEC. KORS were demonstrated to secrete VEGF and HGF. The HDMEC pseudotube formation was induced by KORS conditioned media (KORS_CM). It was totally abrogated after GPC1 siRNA transfection of HDMEC. Moreover, when cleaved by phospholipase C (PLC), GPC1 promotes the proliferation of HDMEC. Finally, GPC1 was shown to interact directly with VEGFR2 or c-Met to regulate angiogenesis induced by the activation of these receptors. Altogether, these results showed that GPC1 is a key regulator of microvascular endothelial cell angiogenesis induced by VEGF and HGF secreted by KORS. Thus, GPC1 might constitute an interesting target to tackle alopecia in dermatology research.

Analysis of eukaryotic lincRNA sequences indicates signatures of hindered translation linked to selection pressure

Long intergenic noncoding RNAs (lincRNAs) represent a large fraction of transcribed loci in eukaryotic genomes. Although classified as noncoding, most lincRNAs contain open reading frames (ORFs), and it remains unclear why cytoplasmic lincRNAs are not or very inefficiently translated. Here, we analyzed signatures of hindered translation in lincRNA sequences from five eukaryotes, covering a range of natural selection pressures. In fission yeast and Caenorhabditis elegans, that is, species under strong selection, we detected significantly shorter ORFs, a suboptimal sequence context around start codons for translation initiation, and trinucleotides (“codons”) corresponding to less abundant tRNAs than for neutrally evolving control sequences, likely impeding translation elongation. For human, we detected signatures for cell-type-specific hindrance of lincRNA translation, in particular codons in abundant cytoplasmic lincRNAs corresponding to lower expressed tRNAs than control codons, in three out of five human cell lines. We verified that varying tRNA expression levels between cell lines are reflected in the amount of ribosomes bound to cytoplasmic lincRNAs in each cell line. We further propose that codons at ORF starts are particularly important for reducing ribosome-binding to cytoplasmic lincRNA ORFs. Altogether, our analyses indicate that in species under stronger selection lincRNAs evolved sequence features generally hindering translation and support cell-type-specific hindrance of translation efficiency in human lincRNAs. The sequence signatures we have identified may improve predicting peptide-coding and genuine noncoding lincRNAs in a cell type.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

Unraveling the hidden role of a uORF-encoded peptide as a kinase inhibitor of PKCs

Approximately 40% of human messenger RNAs (mRNAs) contain upstream open reading frames (uORFs) in their 5' untranslated regions. Some of these uORF sequences, thought to attenuate scanning ribosomes or lead to mRNA degradation, were recently shown to be translated, although the function of the encoded peptides remains unknown. Here, we show a uORF-encoded peptide that exhibits kinase inhibitory functions. This uORF, upstream of the protein kinase C-eta (PKC-η) main ORF, encodes a peptide (uPEP2) containing the typical PKC pseudosubstrate motif present in all PKCs that autoinhibits their kinase activity. We show that uPEP2 directly binds to and selectively inhibits the catalytic activity of novel PKCs but not of classical or atypical PKCs. The endogenous deletion of uORF2 or its overexpression in MCF-7 cells revealed that the endogenously translated uPEP2 reduces the protein levels of PKC-η and other novel PKCs and restricts cell proliferation. Functionally, treatment of breast cancer cells with uPEP2 diminished cell survival and their migration and synergized with chemotherapy by interfering with the response to DNA damage. Furthermore, in a xenograft of MDA-MB-231 breast cancer tumor in mice models, uPEP2 suppressed tumor progression, invasion, and metastasis. Tumor histology showed reduced proliferation, enhanced cell death, and lower protein expression levels of novel PKCs along with diminished phosphorylation of PKC substrates. Hence, our study demonstrates that uORFs may encode biologically active peptides beyond their role as translation regulators of their downstream ORFs. Together, we point to a unique function of a uORF-encoded peptide as a kinase inhibitor, pertinent to cancer therapy.

Regulation of gene expression via translational buffering

Translation of an mRNA represents a critical step during the expression of protein-coding genes. As mechanisms governing post-transcriptional regulation of gene expression are progressively unveiled, it is becoming apparent that transcriptional programs are not fully reflected in the proteome. Herein, we highlight a previously underappreciated post-transcriptional mode of regulation of gene expression termed translational buffering. In principle, translational buffering opposes the impact of alterations in mRNA levels on the proteome. We further describe three types of translational buffering: compensation, which maintains protein levels e.g. across species or individuals; equilibration, which retains pathway stoichiometry; and offsetting, which acts as a reversible mechanism that maintains the levels of selected subsets of proteins constant despite genetic alteration and/or stress-induced changes in corresponding mRNA levels. While mechanisms underlying compensation and equilibration have been reviewed elsewhere, the principal focus of this review is on the less-well understood mechanism of translational offsetting. Finally, we discuss potential roles of translational buffering in homeostasis and disease.

Chromatin accessibility associates with protein-RNA correlation in human cancer

Although alterations in chromatin structure are known to exist in tumors, how these alterations relate to molecular phenotypes in cancer remains to be demonstrated. Multi-omics profiling of human tumors can provide insight into how alterations in chromatin structure are propagated through the pathway of gene expression to result in malignant protein expression. We applied multi-omics profiling of chromatin accessibility, RNA abundance, and protein abundance to 36 human thyroid cancer primary tumors, metastases, and patient-match normal tissue. Through quantification of chromatin accessibility associated with active transcription units and global protein expression, we identify a local chromatin structure that is highly correlated with coordinated RNA and protein expression. In particular, we identify enhancers located within gene-bodies as predictive of correlated RNA and protein expression, that is independent of overall transcriptional activity. To demonstrate the generalizability of these findings we also identify similar results in an independent cohort of human breast cancers. Taken together, these analyses suggest that local enhancers, rather than distal enhancers, are likely most predictive of cancer gene expression phenotypes. This allows for identification of potential targets for cancer therapeutic approaches and reinforces the utility of multi-omics profiling as a methodology to understand human disease.

Genes with 5' terminal oligopyrimidine tracts preferentially escape global suppression of translation by the SARS-CoV-2 Nsp1 protein

Viruses rely on the host translation machinery to synthesize their own proteins. Consequently, they have evolved varied mechanisms to co-opt host translation for their survival. SARS-CoV-2 relies on a nonstructural protein, Nsp1, for shutting down host translation. However, it is currently unknown how viral proteins and host factors critical for viral replication can escape a global shutdown of host translation. Here, using a novel FACS-based assay called MeTAFlow, we report a dose-dependent reduction in both nascent protein synthesis and mRNA abundance in cells expressing Nsp1. We perform RNA-seq and matched ribosome profiling experiments to identify gene-specific changes both at the mRNA expression and translation levels. We discover that a functionally coherent subset of human genes is preferentially translated in the context of Nsp1 expression. These genes include the translation machinery components, RNA binding proteins, and others important for viral pathogenicity. Importantly, we uncovered a remarkable enrichment of 5' terminal oligo-pyrimidine (TOP) tracts among preferentially translated genes. Using reporter assays, we validated that 5' UTRs from TOP transcripts can drive preferential expression in the presence of Nsp1. Finally, we found that LARP1, a key effector protein in the mTOR pathway, may contribute to preferential translation of TOP transcripts in response to Nsp1 expression. Collectively, our study suggests fine-tuning of host gene expression and translation by Nsp1 despite its global repressive effect on host protein synthesis.

A p53-dependent translational program directs tissue-selective phenotypes in a model of ribosomopathies

In ribosomopathies, perturbed expression of ribosome components leads to tissue-specific phenotypes. What accounts for such tissue-selective manifestations as a result of mutations in the ribosome, a ubiquitous cellular machine, has remained a mystery. Combining mouse genetics and in vivo ribosome profiling, we observe limb-patterning phenotypes in ribosomal protein (RP) haploinsufficient embryos, and we uncover selective translational changes of transcripts that controlling limb development. Surprisingly, both loss of p53, which is activated by RP haploinsufficiency, and augmented protein synthesis rescue these phenotypes. These findings are explained by the finding that p53 functions as a master regulator of protein synthesis, at least in part, through transcriptional activation of 4E-BP1. 4E-BP1, a key translational regulator, in turn, facilitates selective changes in the translatome downstream of p53, and this thereby explains how RP haploinsufficiency may elicit specificity to gene expression. These results provide an integrative model to help understand how in vivo tissue-specific phenotypes emerge in ribosomopathies.

Large-scale translatome profiling annotates the functional genome and reveals the key role of genic 3' untranslated regions in translatomic variation in plants

The translatome, a profile of the translational status of genetic information within cells, provides a new perspective on gene expression. Although many plant genomes have been sequenced, comprehensive translatomic annotations are not available for plants due to a lack of efficient translatome profiling techniques. Here, we developed a new technique termed 3' ribosome-profiling sequencing (3'Ribo-seq) for reliable, robust translatomic profiling. 3'Ribo-seq combines polysome profiling and 3' selection with a barcoding and pooling strategy. Systematic translatome profiling of different tissues of Arabidopsis, rice, and maize using conventional ribosome profiling (Ribo-seq) and 3'Ribo-seq revealed many novel translational genomic loci, thereby complementing functional genome annotation in plants. Using the low-cost, efficient 3'Ribo-seq technique and genome-wide association mapping of translatome expression (eGWAS), we performed a population-level dissection of the translatomes of 159 diverse maize inbred lines and identified 1,777 translational expression quantitative trait loci (eQTLs). Notably, local eQTLs are significantly enriched in the 3' untranslated regions of genes. Detailed eQTL analysis suggested that sequence variation around the polyadenylation (polyA) signal motif plays a key role in translatomic variation. Our study provides a comprehensive translatome annotation of plant functional genomes and introduces 3'Ribo-seq, which paves the way for deep translatomic analysis at the population level.