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1.
Front Endocrinol (Lausanne) ; 15: 1422599, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38832352

RESUMEN

RNA biology has revolutionized cancer understanding and treatment, especially in endocrine-related malignancies. This editorial highlights RNA's crucial role in cancer progression, emphasizing its influence on tumor heterogeneity and behavior. Processes like alternative splicing and noncoding RNA regulation shape cancer biology, with microRNAs, long noncoding RNAs, and circular RNAs orchestrating gene expression dynamics. Aberrant RNA signatures hold promise as diagnostic and prognostic biomarkers in endocrine-related cancers. Recent findings, such as aberrant PI3Kδ splice isoforms and epithelial-mesenchymal transition-related lncRNA signatures, unveil potential therapeutic targets for personalized treatments. Insights into m6A-associated lncRNA prognostic models and the function of lncRNA LINC00659 in gastric cancer represents ongoing research in this field. As understanding of RNA's role in cancer expands, personalized therapies offer transformative potential in managing endocrine-related malignancies. This signifies a significant stride towards precision oncology, fostering innovation for more effective cancer care.


Asunto(s)
Neoplasias , Humanos , Neoplasias/genética , Neoplasias/terapia , Regulación Neoplásica de la Expresión Génica , ARN Largo no Codificante/genética , Biomarcadores de Tumor/genética , MicroARNs/genética , Medicina de Precisión/métodos , ARN/genética , ARN Circular/genética , Animales
2.
Gigascience ; 132024 Jan 02.
Artículo en Inglés | MEDLINE | ID: mdl-38837942

RESUMEN

BACKGROUND: RNA-RNA interactions are key to a wide range of cellular functions. The detection of potential interactions helps to understand the underlying processes. However, potential interactions identified via in silico or experimental high-throughput methods can lack precision because of a high false-positive rate. RESULTS: We present CheRRI, the first tool to evaluate the biological relevance of putative RNA-RNA interaction sites. CheRRI filters candidates via a machine learning-based model trained on experimental RNA-RNA interactome data. Its unique setup combines interactome data and an established thermodynamic prediction tool to integrate experimental data with state-of-the-art computational models. Applying these data to an automated machine learning approach provides the opportunity to not only filter data for potential false positives but also tailor the underlying interaction site model to specific needs. CONCLUSIONS: CheRRI is a stand-alone postprocessing tool to filter either predicted or experimentally identified potential RNA-RNA interactions on a genomic level to enhance the quality of interaction candidates. It is easy to install (via conda, pip packages), use (via Galaxy), and integrate into existing RNA-RNA interaction pipelines.


Asunto(s)
Biología Computacional , Aprendizaje Automático , ARN , Programas Informáticos , ARN/metabolismo , Biología Computacional/métodos , Sitios de Unión , Humanos
3.
Folia Biol (Praha) ; 70(1): 62-73, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38830124

RESUMEN

Germline DNA testing using the next-gene-ration sequencing (NGS) technology has become the analytical standard for the diagnostics of hereditary diseases, including cancer. Its increasing use places high demands on correct sample identification, independent confirmation of prioritized variants, and their functional and clinical interpretation. To streamline these processes, we introduced parallel DNA and RNA capture-based NGS using identical capture panel CZECANCA, which is routinely used for DNA analysis of hereditary cancer predisposition. Here, we present the analytical workflow for RNA sample processing and its analytical and diagnostic performance. Parallel DNA/RNA analysis allowed credible sample identification by calculating the kinship coefficient. The RNA capture-based approach enriched transcriptional targets for the majority of clinically relevant cancer predisposition genes to a degree that allowed analysis of the effect of identified DNA variants on mRNA processing. By comparing the panel and whole-exome RNA enrichment, we demonstrated that the tissue-specific gene expression pattern is independent of the capture panel. Moreover, technical replicates confirmed high reproducibility of the tested RNA analysis. We concluded that parallel DNA/RNA NGS using the identical gene panel is a robust and cost-effective diagnostic strategy. In our setting, it allows routine analysis of 48 DNA/RNA pairs using NextSeq 500/550 Mid Output Kit v2.5 (150 cycles) in a single run with sufficient coverage to analyse 226 cancer predisposition and candidate ge-nes. This approach can replace laborious Sanger confirmatory sequencing, increase testing turnaround, reduce analysis costs, and improve interpretation of the impact of variants by analysing their effect on mRNA processing.


Asunto(s)
Predisposición Genética a la Enfermedad , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Neoplasias/genética , Neoplasias/diagnóstico , ARN/genética , Reproducibilidad de los Resultados , Análisis de Secuencia de ADN/métodos , Análisis de Secuencia de ARN/métodos , ADN/genética
4.
Biochemistry (Mosc) ; 89(4): 688-700, 2024 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-38831505

RESUMEN

Eukaryotic cells are characterized by a high degree of compartmentalization of their internal contents, which ensures precise and controlled regulation of intracellular processes. During many processes, including different stages of transcription, dynamic membraneless compartments termed biomolecular condensates are formed. Transcription condensates contain various transcription factors and RNA polymerase and are formed by high- and low-specificity interactions between the proteins, DNA, and nearby RNA. This review discusses recent data demonstrating important role of nonspecific multivalent protein-protein and RNA-protein interactions in organization and regulation of transcription.


Asunto(s)
Transcripción Genética , Humanos , Factores de Transcripción/metabolismo , ARN Polimerasas Dirigidas por ADN/metabolismo , ADN/metabolismo , ADN/química , ARN/metabolismo , ARN/química , Condensados Biomoleculares/metabolismo , Condensados Biomoleculares/química , Animales , Regulación de la Expresión Génica
5.
Biochemistry (Mosc) ; 89(4): 737-746, 2024 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-38831509

RESUMEN

Identification of genes and molecular pathways with congruent profiles in the proteomic and transcriptomic datasets may result in the discovery of promising transcriptomic biomarkers that would be more relevant to phenotypic changes. In this study, we conducted comparative analysis of 943 paired RNA and proteomic profiles obtained for the same samples of seven human cancer types from The Cancer Genome Atlas (TCGA) and NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) [two major open human cancer proteomic and transcriptomic databases] that included 15,112 protein-coding genes and 1611 molecular pathways. Overall, our findings demonstrated statistically significant improvement of the congruence between RNA and proteomic profiles when performing analysis at the level of molecular pathways rather than at the level of individual gene products. Transition to the molecular pathway level of data analysis increased the correlation to 0.19-0.57 (Pearson) and 0.14-057 (Spearman), or 2-3-fold for some cancer types. Evaluating the gain of the correlation upon transition to the data analysis the pathway level can be used to refine the omics data by identifying outliers that can be excluded from the comparison of RNA and proteomic profiles. We suggest using sample- and gene-wise correlations for individual genes and molecular pathways as a measure of quality of RNA/protein paired molecular data. We also provide a database of human genes, molecular pathways, and samples related to the correlation between RNA and protein products to facilitate an exploration of new cancer transcriptomic biomarkers and molecular mechanisms at different levels of human gene expression.


Asunto(s)
Neoplasias , Humanos , Neoplasias/genética , Neoplasias/metabolismo , Proteómica/métodos , Transcriptoma , Bases de Datos Genéticas , ARN/metabolismo , ARN/genética , Perfilación de la Expresión Génica , Exactitud de los Datos , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Regulación Neoplásica de la Expresión Génica
6.
J Chem Phys ; 160(21)2024 Jun 07.
Artículo en Inglés | MEDLINE | ID: mdl-38832749

RESUMEN

Biomolecular condensates play a key role in cytoplasmic compartmentalization and cell functioning. Despite extensive research on the physico-chemical, thermodynamic, or crowding aspects of the formation and stabilization of the condensates, one less studied feature is the role of external perturbative fluid flow. In fact, in living cells, shear stress may arise from streaming or active transport processes. Here, we investigate how biomolecular condensates are deformed under different types of shear flows. We first model Couette flow perturbations via two-way coupling between the condensate dynamics and fluid flow by deploying Lattice Boltzmann Molecular Dynamics. We then show that a simplified approach where the shear flow acts as a static perturbation (one-way coupling) reproduces the main features of the condensate deformation and dynamics as a function of the shear rate. With this approach, which can be easily implemented in molecular dynamics simulations, we analyze the behavior of biomolecular condensates described through residue-based coarse-grained models, including intrinsically disordered proteins and protein/RNA mixtures. At lower shear rates, the fluid triggers the deformation of the condensate (spherical to oblated object), while at higher shear rates, it becomes extremely deformed (oblated or elongated object). At very high shear rates, the condensates are fragmented. We also compare how condensates of different sizes and composition respond to shear perturbation, and how their internal structure is altered by external flow. Finally, we consider the Poiseuille flow that realistically models the behavior in microfluidic devices in order to suggest potential experimental designs for investigating fluid perturbations in vitro.


Asunto(s)
Condensados Biomoleculares , Simulación de Dinámica Molecular , Condensados Biomoleculares/química , Condensados Biomoleculares/metabolismo , Proteínas Intrínsecamente Desordenadas/química , Proteínas Intrínsecamente Desordenadas/metabolismo , ARN/química , Resistencia al Corte
7.
Wiley Interdiscip Rev RNA ; 15(3): e1854, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38831585

RESUMEN

Leukodystrophies are a class of rare heterogeneous disorders which affect the white matter of the brain, ultimately leading to a disruption in brain development and a damaging effect on cognitive, motor and social-communicative development. These disorders present a great clinical heterogeneity, along with a phenotypic overlap and this could be partially due to contributions from environmental stimuli. It is in this context that there is a great need to investigate what other factors may contribute to both disease insurgence and phenotypical heterogeneity, and novel evidence are raising the attention toward the study of epigenetics and transcription mechanisms that can influence the disease phenotype beyond genetics. Modulation in the epigenetics machinery including histone modifications, DNA methylation and non-coding RNAs dysregulation, could be crucial players in the development of these disorders, and moreover an aberrant RNA maturation process has been linked to leukodystrophies. Here, we provide an overview of these mechanisms hoping to supply a closer step toward the analysis of leukodystrophies not only as genetically determined but also with an added level of complexity where epigenetic dysregulation is of key relevance. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNA RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.


Asunto(s)
Epigénesis Genética , Humanos , ARN/metabolismo , ARN/genética , Animales
8.
BMC Biol ; 22(1): 131, 2024 Jun 03.
Artículo en Inglés | MEDLINE | ID: mdl-38831263

RESUMEN

BACKGROUND: Fine characterization of gene expression patterns is crucial to understand many aspects of embryonic development. The chicken embryo is a well-established and valuable animal model for developmental biology. The period spanning from the third to sixth embryonic days (E3 to E6) is critical for many organ developments. Hybridization chain reaction RNA fluorescent in situ hybridization (HCR RNA-FISH) enables multiplex RNA detection in thick samples including embryos of various animal models. However, its use is limited by tissue opacity. RESULTS: We optimized HCR RNA-FISH protocol to efficiently label RNAs in whole mount chicken embryos from E3.5 to E5.5 and adapted it to ethyl cinnamate (ECi) tissue clearing. We show that light sheet imaging of HCR RNA-FISH after ECi clearing allows RNA expression analysis within embryonic tissues with good sensitivity and spatial resolution. Finally, whole mount immunofluorescence can be performed after HCR RNA-FISH enabling as exemplified to assay complex spatial relationships between axons and their environment or to monitor GFP electroporated neurons. CONCLUSIONS: We could extend the use of HCR RNA-FISH to older chick embryos by optimizing HCR RNA-FISH and combining it with tissue clearing and 3D imaging. The integration of immunostaining makes possible to combine gene expression with classical cell markers, to correlate expressions with morphological differentiation and to depict gene expressions in gain or loss of function contexts. Altogether, this combined procedure further extends the potential of HCR RNA-FISH technique for chicken embryology.


Asunto(s)
Hibridación Fluorescente in Situ , Animales , Embrión de Pollo , Hibridación Fluorescente in Situ/métodos , Técnica del Anticuerpo Fluorescente/métodos , Imagenología Tridimensional/métodos , ARN/metabolismo , ARN/genética , Regulación del Desarrollo de la Expresión Génica
9.
Brief Bioinform ; 25(4)2024 May 23.
Artículo en Inglés | MEDLINE | ID: mdl-38855913

RESUMEN

MOTIVATION: Coding and noncoding RNA molecules participate in many important biological processes. Noncoding RNAs fold into well-defined secondary structures to exert their functions. However, the computational prediction of the secondary structure from a raw RNA sequence is a long-standing unsolved problem, which after decades of almost unchanged performance has now re-emerged due to deep learning. Traditional RNA secondary structure prediction algorithms have been mostly based on thermodynamic models and dynamic programming for free energy minimization. More recently deep learning methods have shown competitive performance compared with the classical ones, but there is still a wide margin for improvement. RESULTS: In this work we present sincFold, an end-to-end deep learning approach, that predicts the nucleotides contact matrix using only the RNA sequence as input. The model is based on 1D and 2D residual neural networks that can learn short- and long-range interaction patterns. We show that structures can be accurately predicted with minimal physical assumptions. Extensive experiments were conducted on several benchmark datasets, considering sequence homology and cross-family validation. sincFold was compared with classical methods and recent deep learning models, showing that it can outperform the state-of-the-art methods.


Asunto(s)
Biología Computacional , Aprendizaje Profundo , Conformación de Ácido Nucleico , ARN , ARN/química , ARN/genética , Biología Computacional/métodos , Algoritmos , Redes Neurales de la Computación , Termodinámica
10.
Brief Bioinform ; 25(4)2024 May 23.
Artículo en Inglés | MEDLINE | ID: mdl-38856171

RESUMEN

The identification of protein complexes from protein interaction networks is crucial in the understanding of protein function, cellular processes and disease mechanisms. Existing methods commonly rely on the assumption that protein interaction networks are highly reliable, yet in reality, there is considerable noise in the data. In addition, these methods fail to account for the regulatory roles of biomolecules during the formation of protein complexes, which is crucial for understanding the generation of protein interactions. To this end, we propose a SpatioTemporal constrained RNA-protein heterogeneous network for Protein Complex Identification (STRPCI). STRPCI first constructs a multiplex heterogeneous protein information network to capture deep semantic information by extracting spatiotemporal interaction patterns. Then, it utilizes a dual-view aggregator to aggregate heterogeneous neighbor information from different layers. Finally, through contrastive learning, STRPCI collaboratively optimizes the protein embedding representations under different spatiotemporal interaction patterns. Based on the protein embedding similarity, STRPCI reweights the protein interaction network and identifies protein complexes with core-attachment strategy. By considering the spatiotemporal constraints and biomolecular regulatory factors of protein interactions, STRPCI measures the tightness of interactions, thus mitigating the impact of noisy data on complex identification. Evaluation results on four real PPI networks demonstrate the effectiveness and strong biological significance of STRPCI. The source code implementation of STRPCI is available from https://github.com/LI-jasm/STRPCI.


Asunto(s)
Mapas de Interacción de Proteínas , ARN , ARN/metabolismo , ARN/química , Proteínas/metabolismo , Proteínas/química , Biología Computacional/métodos , Algoritmos , Mapeo de Interacción de Proteínas/métodos , Humanos
11.
ACS Nano ; 18(23): 15013-15024, 2024 Jun 11.
Artículo en Inglés | MEDLINE | ID: mdl-38822455

RESUMEN

Electrophoretic transport plays a pivotal role in advancing sensing technologies. So far, systematic studies have focused on the translocation of canonical B-form or A-form nucleic acids, while direct RNA analysis is emerging as the new frontier for nanopore sensing and sequencing. Here, we compare the less-explored dynamics of noncanonical RNA:DNA hybrids in electrophoretic transport to the well-researched transport of B-form DNA. Using DNA/RNA nanotechnology and solid-state nanopores, the translocation of RNA:DNA (RD) and DNA:DNA (DD) duplexes was examined. Notably, RD duplexes were found to translocate through nanopores faster than DD duplexes, despite containing the same number of base pairs. Our experiments reveal that RD duplexes present a noncanonical helix, with distinct transport properties from B-form DD molecules. We find that RD and DD molecules, with the same contour length, move with comparable velocity through nanopores. We examined the physical characteristics of both duplex forms using atomic force microscopy, atomistic molecular dynamics simulations, agarose gel electrophoresis, and dynamic light scattering measurements. With the help of coarse-grained and molecular dynamics simulations, we find the effective force per unit length applied by the electric field to a fragment of RD or DD duplex in nanopores with various geometries or shapes to be approximately the same. Our results shed light on the significance of helical form in nucleic acid translocation, with implications for RNA sensing, sequencing, and the molecular understanding of electrophoretic transport.


Asunto(s)
ADN , Electroforesis , Simulación de Dinámica Molecular , Nanoporos , ARN , ARN/química , ADN/química , Conformación de Ácido Nucleico , Nanotecnología/métodos
12.
Artículo en Inglés | MEDLINE | ID: mdl-38872612

RESUMEN

Recent success of AlphaFold2 in protein structure prediction relied heavily on co-evolutionary information derived from homologous protein sequences found in the huge, integrated database of protein sequences (Big Fantastic Database). In contrast, the existing nucleotide databases were not consolidated to facilitate wider and deeper homology search. Here, we built a comprehensive database by incorporating the non-coding RNA (ncRNA) sequences from RNAcentral, the transcriptome assembly and metagenome assembly from metagenomics RAST (MG-RAST), the genomic sequences from Genome Warehouse (GWH), and the genomic sequences from MGnify, in addition to the nucleotide (nt) database and its subsets in National Center of Biotechnology Information (NCBI). The resulting Master database of All possible RNA sequences (MARS) is 20-fold larger than NCBI's nt database or 60-fold larger than RNAcentral. The new dataset along with a new split-search strategy allows a substantial improvement in homology search over existing state-of-the-art techniques. It also yields more accurate and more sensitive multiple sequence alignments (MSAs) than manually curated MSAs from Rfam for the majority of structured RNAs mapped to Rfam. The results indicate that MARS coupled with the fully automatic homology search tool RNAcmap will be useful for improved structural and functional inference of ncRNAs and RNA language models based on MSAs. MARS is accessible at https://ngdc.cncb.ac.cn/omix/release/OMIX003037, and RNAcmap3 is accessible at http://zhouyq-lab.szbl.ac.cn/download/.


Asunto(s)
Bases de Datos de Ácidos Nucleicos , Alineación de Secuencia , ARN no Traducido/genética , ARN no Traducido/química , Análisis de Secuencia de ARN/métodos , ARN/genética , ARN/química , Programas Informáticos , Bases de Datos Genéticas
13.
Clin Transl Med ; 14(6): e1666, 2024 Jun.
Artículo en Italiano | MEDLINE | ID: mdl-38880983

RESUMEN

Dysregulated RNA modifications, stemming from the aberrant expression and/or malfunction of RNA modification regulators operating through various pathways, play pivotal roles in driving the progression of haematological malignancies. Among RNA modifications, N6-methyladenosine (m6A) RNA modification, the most abundant internal mRNA modification, stands out as the most extensively studied modification. This prominence underscores the crucial role of the layer of epitranscriptomic regulation in controlling haematopoietic cell fate and therefore the development of haematological malignancies. Additionally, other RNA modifications (non-m6A RNA modifications) have gained increasing attention for their essential roles in haematological malignancies. Although the roles of the m6A modification machinery in haematopoietic malignancies have been well reviewed thus far, such reviews are lacking for non-m6A RNA modifications. In this review, we mainly focus on the roles and implications of non-m6A RNA modifications, including N4-acetylcytidine, pseudouridylation, 5-methylcytosine, adenosine to inosine editing, 2'-O-methylation, N1-methyladenosine and N7-methylguanosine in haematopoietic malignancies. We summarise the regulatory enzymes and cellular functions of non-m6A RNA modifications, followed by the discussions of the recent studies on the biological roles and underlying mechanisms of non-m6A RNA modifications in haematological malignancies. We also highlight the potential of therapeutically targeting dysregulated non-m6A modifiers in blood cancer.


Asunto(s)
Neoplasias Hematológicas , Humanos , Neoplasias Hematológicas/genética , Neoplasias Hematológicas/metabolismo , Neoplasias Hematológicas/patología , Procesamiento Postranscripcional del ARN/genética , ARN/genética , ARN/metabolismo , Adenosina/análogos & derivados , Adenosina/metabolismo , Adenosina/genética
14.
ACS Nano ; 18(24): 15477-15486, 2024 Jun 18.
Artículo en Inglés | MEDLINE | ID: mdl-38831645

RESUMEN

DNA droplets, artificial liquid-like condensates of well-engineered DNA sequences, allow the critical aspects of phase-separated biological condensates to be harnessed programmably, such as molecular sensing and phase-state regulation. In contrast, their RNA-based counterparts remain less explored despite more diverse molecular structures and functions ranging from DNA-like to protein-like features. Here, we design and demonstrate computational RNA droplets capable of two-input AND logic operations. We use a multibranched RNA nanostructure as a building block comprising multiple single-stranded RNAs. Its branches engaged in RNA-specific kissing-loop (KL) interaction enables the self-assembly into a network-like microstructure. Upon two inputs of target miRNAs, the nanostructure is programmed to break up into lower-valency structures that are interconnected in a chain-like manner. We optimize KL sequences adapted from viral sequences by numerically and experimentally studying the base-wise adjustability of the interaction strength. Only upon receiving cognate microRNAs, RNA droplets selectively show a drastic phase-state change from liquid to dispersed states due to dismantling of the network-like microstructure. This demonstration strongly suggests that the multistranded motif design offers a flexible means to bottom-up programming of condensate phase behavior. Unlike submicroscopic RNA-based logic operators, the macroscopic phase change provides a naked-eye-distinguishable readout of molecular sensing. Our computational RNA droplets can be applied to in situ programmable assembly of computational biomolecular devices and artificial cells from transcriptionally derived RNA within biological/artificial cells.


Asunto(s)
ARN , ARN/química , Conformación de Ácido Nucleico , MicroARNs/química , MicroARNs/genética , Nanoestructuras/química
15.
ACS Nano ; 18(24): 15729-15743, 2024 Jun 18.
Artículo en Inglés | MEDLINE | ID: mdl-38839059

RESUMEN

Lipid nanoparticles (LNP) have emerged as pivotal delivery vehicles for RNA therapeutics. Previous research and development usually assumed that LNPs are homogeneous in population, loading density, and composition. Such perspectives are difficult to examine due to the lack of suitable tools to characterize these physicochemical properties at the single-nanoparticle level. Here, we report an integrated spectroscopy-chromatography approach as a generalizable strategy to dissect the complexities of multicomponent LNP assembly. Our platform couples cylindrical illumination confocal spectroscopy (CICS) with single-nanoparticle free solution hydrodynamic separation (SN-FSHS) to simultaneously profile population identity, hydrodynamic size, RNA loading levels, and distributions of helper lipid and PEGylated lipid of LNPs at the single-particle level and in a high-throughput manner. Using a benchmark siRNA LNP formulation, we demonstrate the capability of this platform by distinguishing seven distinct LNP populations, quantitatively characterizing size distribution and RNA loading level in wide ranges, and more importantly, resolving composition-size correlations. This SN-FSHS-CICS analysis provides critical insights into a substantial degree of heterogeneity in the packing density of RNA in LNPs and size-dependent loading-size correlations, explained by kinetics-driven assembly mechanisms of RNA LNPs.


Asunto(s)
Lípidos , Nanopartículas , Tamaño de la Partícula , Nanopartículas/química , Lípidos/química , ARN/química , Cromatografía/métodos , ARN Interferente Pequeño/química , Análisis Espectral/métodos , Liposomas
16.
Mil Med Res ; 11(1): 36, 2024 Jun 11.
Artículo en Inglés | MEDLINE | ID: mdl-38863031

RESUMEN

BACKGROUND: Dysregulation of enhancer transcription occurs in multiple cancers. Enhancer RNAs (eRNAs) are transcribed products from enhancers that play critical roles in transcriptional control. Characterizing the genetic basis of eRNA expression may elucidate the molecular mechanisms underlying cancers. METHODS: Initially, a comprehensive analysis of eRNA quantitative trait loci (eRNAQTLs) was performed in The Cancer Genome Atlas (TCGA), and functional features were characterized using multi-omics data. To establish the first eRNAQTL profiles for colorectal cancer (CRC) in China, epigenomic data were used to define active enhancers, which were subsequently integrated with transcription and genotyping data from 154 paired CRC samples. Finally, large-scale case-control studies (34,585 cases and 69,544 controls) were conducted along with multipronged experiments to investigate the potential mechanisms by which candidate eRNAQTLs affect CRC risk. RESULTS: A total of 300,112 eRNAQTLs were identified across 30 different cancer types, which exert their influence on eRNA transcription by modulating chromatin status, binding affinity to transcription factors and RNA-binding proteins. These eRNAQTLs were found to be significantly enriched in cancer risk loci, explaining a substantial proportion of cancer heritability. Additionally, tumor-specific eRNAQTLs exhibited high responsiveness to the development of cancer. Moreover, the target genes of these eRNAs were associated with dysregulated signaling pathways and immune cell infiltration in cancer, highlighting their potential as therapeutic targets. Furthermore, multiple ethnic population studies have confirmed that an eRNAQTL rs3094296-T variant decreases the risk of CRC in populations from China (OR = 0.91, 95%CI 0.88-0.95, P = 2.92 × 10-7) and Europe (OR = 0.92, 95%CI 0.88-0.95, P = 4.61 × 10-6). Mechanistically, rs3094296 had an allele-specific effect on the transcription of the eRNA ENSR00000155786, which functioned as a transcriptional activator promoting the expression of its target gene SENP7. These two genes synergistically suppressed tumor cell proliferation. Our curated list of variants, genes, and drugs has been made available in CancereRNAQTL ( http://canernaqtl.whu.edu.cn/#/ ) to serve as an informative resource for advancing this field. CONCLUSION: Our findings underscore the significance of eRNAQTLs in transcriptional regulation and disease heritability, pinpointing the potential of eRNA-based therapeutic strategies in cancers.


Asunto(s)
Elementos de Facilitación Genéticos , Neoplasias , Sitios de Carácter Cuantitativo , Humanos , Elementos de Facilitación Genéticos/genética , Neoplasias/genética , Variación Genética/genética , Estudio de Asociación del Genoma Completo/métodos , Neoplasias Colorrectales/genética , Estudios de Casos y Controles , ARN/genética , China , ARN Potenciadores
17.
Artículo en Inglés | MEDLINE | ID: mdl-38862427

RESUMEN

Since its establishment in 2013, BioLiP has become one of the widely used resources for protein-ligand interactions. Nevertheless, several known issues occurred with it over the past decade. For example, the protein-ligand interactions are represented in the form of single chain-based tertiary structures, which may be inappropriate as many interactions involve multiple protein chains (known as quaternary structures). We sought to address these issues, resulting in Q-BioLiP, a comprehensive resource for quaternary structure-based protein-ligand interactions. The major features of Q-BioLiP include: (1) representing protein structures in the form of quaternary structures rather than single chain-based tertiary structures; (2) pairing DNA/RNA chains properly rather than separation; (3) providing both experimental and predicted binding affinities; (4) retaining both biologically relevant and irrelevant interactions to alleviate the wrong justification of ligands' biological relevance; and (5) developing a new quaternary structure-based algorithm for the modelling of protein-ligand complex structure. With these new features, Q-BioLiP is expected to be a valuable resource for studying biomolecule interactions, including protein-small molecule interaction, protein-metal ion interaction, protein-peptide interaction, protein-protein interaction, protein-DNA/RNA interaction, and RNA-small molecule interaction. Q-BioLiP is freely available at https://yanglab.qd.sdu.edu.cn/Q-BioLiP/.


Asunto(s)
Unión Proteica , Proteínas , Ligandos , Proteínas/química , Proteínas/metabolismo , Estructura Cuaternaria de Proteína , ADN/metabolismo , ADN/química , Bases de Datos de Proteínas , ARN/metabolismo , ARN/química , Algoritmos
18.
Nat Commun ; 15(1): 4814, 2024 Jun 11.
Artículo en Inglés | MEDLINE | ID: mdl-38862469

RESUMEN

A detailed understanding of how spaceflight affects human health is essential for long-term space exploration. Liquid biopsies allow for minimally-invasive multi-omics assessments that can resolve the molecular heterogeneity of internal tissues. Here, we report initial results from the JAXA Cell-Free Epigenome Study, a liquid biopsy study with six astronauts who resided on the International Space Station (ISS) for more than 120 days. Analysis of plasma cell-free RNA (cfRNA) collected before, during, and after spaceflight confirms previously reported mitochondrial dysregulation in space. Screening with 361 cell surface marker antibodies identifies a mitochondrial DNA-enriched fraction associated with the scavenger receptor CD36. RNA-sequencing of the CD36 fraction reveals tissue-enriched RNA species, suggesting the plasma mitochondrial components originated from various tissues. We compare our plasma cfRNA data to mouse plasma cfRNA data from a previous JAXA mission, which had used on-board artificial gravity, and discover a link between microgravity and the observed mitochondrial responses.


Asunto(s)
Antígenos CD36 , Ácidos Nucleicos Libres de Células , ADN Mitocondrial , Vuelo Espacial , Ingravidez , ADN Mitocondrial/genética , ADN Mitocondrial/sangre , Humanos , Ácidos Nucleicos Libres de Células/sangre , Animales , Ratones , Antígenos CD36/metabolismo , Antígenos CD36/genética , Mitocondrias/metabolismo , Mitocondrias/genética , Masculino , Astronautas , ARN/metabolismo , ARN/genética , Biopsia Líquida/métodos , ARN Mitocondrial/metabolismo , ARN Mitocondrial/genética , Femenino , Persona de Mediana Edad , Adulto
19.
Sci Adv ; 10(24): eadk4387, 2024 Jun 14.
Artículo en Inglés | MEDLINE | ID: mdl-38865460

RESUMEN

The function of TERRA in the regulation of telomerase in human cells is still debated. While TERRA interacts with telomerase, how it regulates telomerase function remains unknown. Here, we show that TERRA colocalizes with the telomerase RNA subunit hTR in the nucleoplasm and at telomeres during different phases of the cell cycle. We report that TERRA transcripts relocate away from chromosome ends during telomere lengthening, leading to a reduced number of telomeric TERRA-hTR molecules and consequent increase in "TERRA-free" telomerase molecules at telomeres. Using live-cell imaging and super-resolution microscopy, we show that upon transcription, TERRA relocates from its telomere of origin to long chromosome ends. Furthermore, TERRA depletion by antisense oligonucleotides promoted hTR localization to telomeres, leading to increased residence time and extended half-life of hTR molecules at telomeres. Overall, our findings indicate that telomeric TERRA transcripts inhibit telomere elongation by telomerase acting in trans, impairing telomerase access to telomeres that are different from their chromosome end of origin.


Asunto(s)
Telomerasa , Telómero , Telomerasa/metabolismo , Telomerasa/genética , Humanos , Telómero/metabolismo , Telómero/genética , Homeostasis del Telómero , Células HeLa , ARN/metabolismo , ARN/genética , Transcripción Genética , Proteínas de Unión a Telómeros/metabolismo , Proteínas de Unión a Telómeros/genética , Ciclo Celular/genética , Cromosomas Humanos/metabolismo , Cromosomas Humanos/genética , Proteínas de Unión al ADN , Factores de Transcripción
20.
Bioinformatics ; 40(6)2024 Jun 03.
Artículo en Inglés | MEDLINE | ID: mdl-38837395

RESUMEN

MOTIVATION: Tissue context and molecular profiling are commonly used measures in understanding normal development and disease pathology. In recent years, the development of spatial molecular profiling technologies (e.g. spatial resolved transcriptomics) has enabled the exploration of quantitative links between tissue morphology and gene expression. However, these technologies remain expensive and time-consuming, with subsequent analyses necessitating high-throughput pathological annotations. On the other hand, existing computational tools are limited to predicting only a few dozen to several hundred genes, and the majority of the methods are designed for bulk RNA-seq. RESULTS: In this context, we propose HE2Gene, the first multi-task learning-based method capable of predicting tens of thousands of spot-level gene expressions along with pathological annotations from H&E-stained images. Experimental results demonstrate that HE2Gene is comparable to state-of-the-art methods and generalizes well on an external dataset without the need for re-training. Moreover, HE2Gene preserves the annotated spatial domains and has the potential to identify biomarkers. This capability facilitates cancer diagnosis and broadens its applicability to investigate gene-disease associations. AVAILABILITY AND IMPLEMENTATION: The source code and data information has been deposited at https://github.com/Microbiods/HE2Gene.


Asunto(s)
Transcriptoma , Humanos , Perfilación de la Expresión Génica/métodos , Biología Computacional/métodos , Aprendizaje Automático , ARN/metabolismo
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