Multiomics dissection of hierarchical translatome reprogramming
via regulome- and epitranscriptome-mediated translational control

BASIC INFORMATION: 

TRANSREP is a basic research project aimed at advancing fundamental mechanistic understanding of the interplay between reactome-mediated translational control (RMTC) and epitranscriptome-mediated translational control (EMTRAC) in driving translatome reprogramming, with direct relevance to biomedical innovation.

KEYWORDS: Transcriptome, epitranscriptome, epitranscriptomics, RNA methylation, regulome, translational control, translatome, translatome reprogramming, translatomic paradox, proteome, metabolome, cancer translatome, cis-acting elements, trans-acting factors, cap-dependent, cap-independent translation, 5’UTR, integrated stress response (ISR), 2′-O-methylation, m6A, m6Am, m1A, m5C, m7G, snoRNA,  ribosome profiling, single-cell multi-omics, tumor microenvironment, metabolic reprogramming, EMT, tumor-educated cells, TEPs, biomarkers, molecular targets, systems biology, precision medicine, molecular diagnostics, pharmacogenomics, gene therapy, medical biotechnology, FBL, METTL3, FTO, THRB, SAM/SAH. 

Disease models: cancer and other non-communicable diseases within the human diseasome.
Key Biological Pathways: and programs critically dependent on translational control include: integrated stress response (ISR)–driven epithelial–mesenchymal transition (EMT) programs, cellular plasticity and stemness programs, vascular remodeling, thyroid hormone–mediated metabolic differentiation, Warburg-like metabolic reprogramming, translation-dependent tumor-educated cells (TECs), including tumor-educated platelets (TEPs), as well as exosome-mediated intercellular communication.
Selected technologies: Ribosome profiling (Ribo-seq), RNA-seq, single-cell multiomics, quantitative proteomics, RNA modification profiling (m⁶A-seq / MeRIP-seq or direct RNA sequencing), polysome profiling / TRAP-seq, and proprietary author-developed technology dGoligo/eRNA for regulome-level interrogation of translational control.

BACKROUND

Translational control (TC) is a post-transcriptional regulatory mechanism of gene expression that enables the fastest cellular and subcellular responses to environmental cues. Its dysregulation is linked to major civilization diseases, including cancer, neurodegenerative and cardiovascular diseases, as well as aging. Accumulating evidence demonstrates that transcriptomic changes alone fail to explain disease-associated proteomic states, particularly in stress-adapted cells, thereby identifying translation as a critical yet underexplored regulatory layer. Acting downstream of transcription, TC directly shapes the set of actively translated proteins (the translatome), enabling rapid and selective protein synthesis independently of mRNA abundance. This gives rise to a translatomic paradox, whereby global protein synthesis can be suppressed while selected transcripts or transcript cohorts remain efficiently translated, leading to profound changes in cellular proteome composition. Carcinogenesis represents a paradigmatic pathological process characterized by extensive translatome reprogramming that favors oncogenic drivers over tumour suppressors.

TC is executed through multiple mechanistically distinct but interacting layers, including RNA methylation–dependent mechanisms that define Epitranscriptome-Mediated Translational Control (EMTRAC), as well as cis-regulatory logic decoded by dedicated trans-acting machineries, collectively referred to here as Regulome-Mediated Translational Control (RMTC). Increasing evidence indicates that translational control is hierarchically organized across three interconnected levels—global, intermediate, and local—at which EMTRAC and RMTC operate in complementary but non-redundant roles.

Three interacting levels of CT across the EMTRAC and RMTC layers

At the global level, EMTRAC defines the dominant mode of translation initiation across the translatome through m⁷G-cap–dependent and cap-independent mechanisms, thereby setting overall initiation logic and translational permissiveness. This layer is regulated by trans-acting signaling pathways, including the mTORC1–4E-BP–eIF4E axis, and does not confer sequence-based selectivity. Superimposed on this regime, RMTC introduces a global kinetic constraint through regulation of ternary complex availability via stress-induced phosphorylation of eIF2α, selectively permitting translation of transcripts encoding intrinsic uORF-based initiation sensors without invoking regulon logic.

At the intermediate level, EMTRAC operates through ribosome programming driven by small nucleolar RNA (snoRNA)–guided ribosomal RNA (rRNA) modifications, including 2′-O-methylation (2′-O-Me) and pseudouridylation (Ψ), which generate functionally specialized ribosomes. These programmed ribosomes do not alter global protein synthesis rates but bias translational competence toward transcripts with defined architectural features, such as long, highly structured 5′ untranslated regions (5′UTRs). At the same depth, RMTC organizes translation into translational regulons (TRs)—cohorts of mRNAs sharing common cis-acting elements that are coordinately decoded by compatible ribosomes and shared protein trans-acting factors. Together, EMTRAC-driven ribosome specialization and RMTC-defined regulons reshape pathway-level protein output independently of transcript abundance.

At the local level, translational regulation becomes transcript-specific and sequence-encoded. Local EMTRAC is mediated by position- and context-dependent RNA modifications, including N6-methyladenosine (m⁶A), N6,2′-O-dimethyladenosine (m⁶Am), N1-methyladenosine (m¹A), and 5-methylcytosine (m⁵C), which fine-tune translation efficiency, elongation dynamics, and isoform-specific protein output. In parallel, local RMTC decodes cis-acting RNA elements through recruitment of dedicated trans-acting factors, including RNA-binding proteins, microRNAs, and regulatory long non-coding RNAs. This level integrates EMTRAC-imposed RNA modification states with regulon-encoded cis logic to achieve precise, context-dependent control of individual proteins.

Major knowledge gaps

Major knowledge gaps: Although comprehensive epitranscriptome databases for model organisms and reference physiological conditions exist—such as RMBase v3.0, which catalogs RNA modification sites across species and healthy reference models—there is currently no integrated resource capturing cell state– or disease-driven EMTRAC- and RMTC-mediated translatome reprogramming. This gap precludes systematic identification of functional, targetable translational vulnerabilities.

Most mRNAs harbor regulatory sequences within their 5′UTRs, coding sequences (CDSs), and 3′UTRs, collectively referred to as cis-acting elements. These elements encode translational logic that is decoded by RMTC through shared trans-acting factors, while RNA methylation within these regions modulates ribosome engagement and translational efficiency via EMTRAC. In parallel, a large diversity of non-coding RNAs—including long non-coding RNAs, pseudogene-derived transcripts, snoRNAs, small non-coding RNAs, and microRNAs—actively participate in translational regulation, forming a multilayered regulatory architecture that governs protein synthesis in a context-dependent manner.

 It is well established that transcripts characterized by short, m⁷G-capped, weakly structured, and AT-rich 5′UTRs are efficiently translated under basal conditions and are preferentially suppressed during mitosis or cellular stress. In contrast, the expression dynamics, regulatory mechanisms, and functional relevance of long, GC-rich, highly structured mRNA isoforms that are inefficiently translated under basal conditions remain poorly understood. This knowledge gap underscores the need for systematic, multi-omics approaches to dissect how epitranscriptome-mediated (EMTRAC) and reactome-mediated translational control (RMTC) hierarchically cooperate to reprogram the translatome in health and disease.

HYPOTHESIS

Based on previous findings (see References), it can be hypothesized that, at the RMTC-defined cis-regulatory layer, transcripts characterized by long, GC-rich, and highly structured 5′UTRs containing upstream open reading frames (uORFs), internal ribosome entry sites (IRESs), and other inhibitory motifs constitute a pool of translationally inactive or weakly translated mRNAs that can be selectively mobilized for rapid protein synthesis under defined physiological or pathological conditions such as mitosis or ISR. Furthermore, it can be hypothesized that this selective recruitment can be enabled by EMTRAC-driven RNA modification states that modulate RMTC-defined cis-regulatory architectures by increasing or decreasing the extent of RNA modifications, thereby promoting context-dependent recruitment of sequence- and modification-specific trans-acting factors. This framework assigns a previously unrecognized functional role to structurally complex mRNA variants, frequently observed in oncogenes and tumor suppressor genes, whose translational potential has remained largely unexplored.

AIMS

The primary aim of this project is to define the mechanistic principles by which EMTRAC and RMTC cooperatively enable selective recruitment and activation of transcripts, particularly structurally complex mRNA variants with long, regulatory-rich 5′UTRs. Specifically, the project aims to dissect how global, intermediate, and local layers of translational regulation—including ribosome programming driven by snoRNA-guided rRNA modifications, translational regulon logic, and transcript-specific RNA methylation—cooperate to reprogram the translatome independently of transcript abundance in health and disease.

METHODS

The proposed hypothesis will be tested using an integrated multi-omics framework combined with targeted functional perturbations to dissect hierarchical translational control mediated by EMTRAC and RMTC. Transcriptome- and translatome-wide analyses, including alternative transcript isoforms, will integrate ribosome profiling (Ribo-seq), polysome profiling and TRAP-seq with bulk RNA-seq and single-cell multiomics to quantify global, intermediate, and transcript-specific translational outputs. Epitranscriptomic regulation will be interrogated using RNA modification profiling (m⁶A-seq / MeRIP-seq or direct RNA sequencing), complemented by metabolomic analyses as determinants of RNA methylation capacity and quantitative proteomics to validate functional protein output. Mechanistic interrogation will involve modulation of cap-dependent and cap-independent translation initiation, targeted perturbation of rRNA-specific modifications (e.g. 2′-O-methylation), and transcript- and isoform-specific modulation of RNA methylation states.

Functional mechanistic validation will be performed in vitro and in vivo. Regulome-driven translational control will be causally tested using a proprietary author-developed 5′UTR-targeted oligonucleotide-based platform (dGoligo/eRNA) enabling gene-specific modulation of translation.

OUTPUT

The project will generate health-, disease-, and cell-type–specific libraries of (a) epitranscriptomic states, (b) cis-element–resolved transcript architectures, and (c) associated trans-acting regulatory factors, integrated into a comprehensive open-access database of EMTRAC- and RMTC-mediated translatome reprogramming across the human diseasome. Ultimately, this work will produce a unified TRANSREP Atlas enabling the identification of novel biomarkers and therapeutic targets and providing a foundation for the selective enhancement of native protein synthesis from endogenous transcripts.

IMPACT

This project will establish a unified conceptual and mechanistic framework positioning EMTRAC and RMTC as hierarchically organized and experimentally targetable layers of gene expression regulation. By integrating multi-omics datasets into a mechanism-aware architecture, it will address critical gaps in understanding how epitranscriptomic modifications and regulon-encoded cis-regulatory logic cooperate to reprogram the translatome independently of transcript abundance. The resulting atlas will complement existing resources, such as RMBase v3.0, and enable the discovery of disease-associated translational vulnerabilities, thereby supporting the development of precision medicine strategies targeting translational control and next-generation oligonucleotide therapeutics.

For further details of the TRANSREP concept, see Translational control in Tables.

For a detailed discussion of translational control mechanisms underlying this framework, see our related PUBLICATIONS,  INVENTIONS,  and  RESEARCH.

NUMIEP is a related project entitled: Multiomics-guided mechanistic understanding of gut microbiome-mediated epigenome reprogramming in response to functional food–based dietary intervention. NCN OPUS-LAP project — My role: scientific concept co-author (microbiome–epigenome–transcriptome axis), USA consortium partner (in-kind contribution), scientific advisor.

RMBase v3.0

RNA Modification Base (RMBase) is a comprehensive database that integrates multidimensional epitranscriptome sequencing data from healthy human samples and multiple model species to map, mechanistically characterise and functionally annotate RNA modifications. RMBase provides analytical modules for modification landscape exploration, mechanistic inference, interactome analysis, co-localisation with histone marks and regulatory protein associations; no disease-specific models are included. Xuan JJ et al. RMBase v3.0: decode the landscape, mechanisms and functions of RNA modifications. Nucleic Acids Research (2023).

UTRdb

UTRdb is a curated database of eukaryotic 5′ and 3′ untranslated regions (UTRs) derived from experimentally supported transcript annotations. The resource integrates sequence features, regulatory motifs and functional elements involved in post-transcriptional and translational control, including binding sites for RNA-binding proteins and regulatory sequence patterns. UTRdb can be used as a starting point for identifying translational regulons within the regulome, while not providing direct disease-specific or functional perturbation models.

Grillo G et al. UTRdb and UTRsite (RELEASE 2010): a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs. Nucleic Acids Research 38(Database issue):D75–D80 (2010).

AURA

AURA (Atlas of UTR Regulatory Activity) is a specialised database dedicated to the annotation and functional characterisation of cis-acting regulatory elements within the 5′ and 3′ untranslated regions (UTRs) and interacting with them trans-acting factors that may help in bilding the Atlas of Regulome Mediated Translational Control (RMTC).

Dassi E, Malossini A, Re A, et al. AURA: Atlas of UTR Regulatory Activity. Bioinformatics. 2012;28(1):142–143. 

Omics in Precision Medicine

Proteogenomics Research: On the Frontier of Precision Medicine.

By linking genetic alterations with protein expression and modification patterns, this approach reveals functional consequences of mutations, identifies clinically relevant pathways, and supports more precise patient stratification. Such insights contribute to improved biomarker discovery and more targeted therapeutic strategies in oncology.