RNA Biology最新文献

Non-coding RNAs (ncRNAs) modulate protein-protein interactions (PPIs) by shaping the structural context in which binding occurs, rather than acting as direct inhibitors or enhancers. Using an integrative framework combining catRAPID RNA-protein interaction prediction and AlphaFold3-based structural modelling, we analysed RNA-dependent modulation of interaction states across physiological and oncogenic protein complexes. At the network level, physiological PPIs exhibit high shared ncRNA buffering capacity, whereas oncogenic interactions are characterized by reduced or absent RNA overlap. AlphaFold3 modelling of mutant IDH1/2 complexes illustrates how loss of RNA buffering permits excessive stabilization of enzyme-associated interfaces, reflected by directional changes in buried surface area (ΔBSA) and contact heterogeneity.

In response to stress, cells undergo gene expression reprogramming to cope with external stimuli. Cells utilize a conserved stress response mechanism called global downregulation of translation, leading to the storage of translationally repressed mRNAs in RNA granules. During oxidative stress induced by H2O2, genes responsible for combating oxidative stress, such as catalases, are strongly induced. However, the post-transcriptional regulatory events affecting these genes during H2O2 stress are not well-explored. Scd6, an RGG-motif-containing protein in yeast, acts as a translational repressor through its interaction with eIF4G1. This study identifies the role of Scd6 in oxidative stress response by regulating cytoplasmic catalase T1 (CTT1). We observe that peroxide stress induces the assembly of Scd6 puncta, which do not colocalize with P-bodies or stress granules. Scd6 overexpression increased sensitivity, while deletion enhanced tolerance to H2O2 treatment. Increased ROS accumulation and decreased Ctt1 protein levels were observed upon Scd6 overexpression due to translation repression of CTT1 mRNA. CTT1 mRNA interacts with Scd6. smFISH analysis and RNA immunoprecipitation studies reveal that localization of Scd6 to puncta upon peroxide stress reduces its interaction with CTT1 mRNA, allowing derepression. The role of Scd6 in peroxide stress response is conserved since the human homolog LSm14A also localizes to puncta upon H2O2 stress, and its overexpression reduces survival in response to peroxide stress. Overall, this study identifies a unique example of translation regulation whereby stress-induced localization of the translation repressor protein to puncta leads to derepression of the target mRNA.

Tuberculosis, caused by Mycobacterium tuberculosis, is an infectious disease linked to high mortality and can stay in the host cell longer when inactive. Multiple factors are linked to disease prognosis, including microRNAs. It is a diminutive single-stranded RNA that regulates the expression of its target mRNAs. It consists of a brief nucleotide sequence, often 19-25 nucleotides in length, of non-coding RNA. It is also essential for early embryonic development, invasion, cell migration, apoptosis, and cell death. The review aims to analyse the transcriptome characteristics of various miRNAs in the tuberculosis prognosis. However, miR-155, miR-29, circ-miRNA, and lncRNAs regulate gene expression. In TB patients' serum exosomes, miRNA-146 expression was noticeably higher than in healthy individuals. Drug-resistant tuberculosis was related to miR-548 m, miR-631, miR-328-3p, and miR-let-7e-5p, as well as let-7b-5p, miR-30a-3p, IL-27, and CXCL9/10/11 in TB patients' lesion tissue and peripheral blood. Therefore, further miRNA research will focus on TB progression.

5' RNA capping is one of the major post-transcriptional modifications for the mobility and stability of RNA molecules. Measuring 5' caps of RNAs can help quantify expression levels of mRNAs and lncRNAs. One of the most successful RNAseq methods that have used capping as a tool to quantify expression of transcription is Cap Analysis of Gene Expression(CAGE). Computational prediction of capping can therefore be used as a precursor to the prediction of transcriptional expression. Unfortunately, there is hardly any computational technique that has focused purely on predicting 5' capping. We have developed a transformer-based method for computational prediction of capping from DNA sequences. Our Llama and ReLoRA-based pre-training model, and Llama and LoRA-based fine-tuning model predict capping associated regions. We have used Leave-one-chromosome-out-cross-validation for our model. The average accuracy, and F1-score after fine-tuning the human genome hg19(mouse genome mm9) for sequence classification is 79.12%(78.09%), and 78.11%(76.17%), respectively. We noted attention peak-based motifs having an aggregate Wilcoxon rank-sum p-value of 1.075e-10 between the attention peak region and the entire context window for the predicted positive motifs; an aggregate p-value of 7.17e-18 for the predicted negative motifs; and an aggregate p-value of 6.70e-08 between the attention peaks of the predicted positive and the predicted negative motifs. Our Llama-based approach aims to create a sequence-based framework to identify capping associated regions corresponding to CAGE peaks. Our analysis reveals statistically significant motifs from the regions of peak attention scores, which demonstrates biological relevance for some through their resident sites matching with known TF motifs.

Tumorigenesis is commonly driven by genetic mutations and disruptions in cellular signalling pathways. Here we show that the oncogenic overexpression of the RNase L inhibitor ABCE1, a component of interferon signalling, leads to distinct and extensive deviations in cancer transcriptomes. RNase L is a cellular endonuclease that cleaves RNA molecules at specific UU and UA dinucleotide sites. Typically, it is activated by viral infections and interferon signalling leading to targeting and destruction of UU/UA-rich viral and cellular mRNA. RNase L has also homoeostatic and tumour suppressive roles. Relying on patient transcriptomic data, we show that ABCE1 is extensively overexpressed in colorectal cancer (CRC) and to a lesser extent in lung cancer. This upregulation was strongly associated with the co-upregulation of almost all UU/UA rich transcripts and downregulation of those that are UU/UA-poor. Many of upregulated mRNAs code for proteins involved in cell cycle regulation and mitosis. Accordingly, the knockdown of ABCE1 in the CRC cell line HT29 led to reduced proliferation. Surprisingly, the very high ABCE1 levels were associated with improved patient survival in CRC. This observation might be related to an anti-ABCE1-specific immune response due to the induction of tumour-reactive cytotoxic T lymphocytes by ABCE1 as previously reported. In lung cancer ABCE1 overexpression is milder and is associated with poor survival. We report a measurable, specific, and extensive modulation of cancer transcriptomes by the oncogenic overexpression of a component of interferon signalling with unexpected outcomes on patient survival.

The epitranscriptome comprises chemical modifications found on RNA molecules that play essential roles in co- and post-transcriptional gene regulation. Dysregulation of these modifications has been implicated in various diseases, fuelling interest in evaluating them as emerging biomarkers and therapeutic targets. Nanopore direct RNA sequencing provides a powerful platform for profiling diverse RNA modifications at single-molecule resolution, but the complexity of the signals requires advanced computational approaches for interpretation. Artificial intelligence, particularly deep learning (DL), has become central to this effort. While classical DL architectures such as convolutional and recurrent neural networks have been widely applied, more recent approaches employ specialized learning frameworks and ensemble strategies to address challenges of data scarcity, noise, and biological variability while providing higher resolution output. In this review, we summarize these developments and highlight future multidisciplinary opportunities at the intersection of artificial intelligence and biology for characterizing the epitranscriptome obtained with direct RNA nanopore sequencing.

HNRNPA2B1 contains two RRM domains and has been investigated for its possible role as an m⁶A reader protein. The targetome of HNRNPA2B1 was shown to overlap with the m⁶A methylation motif, but further investigations of its binding affinity for m⁶A-containing RNAs have been less clear on the relative selectivity of HNRNPA2B1 for methylated transcripts. Our computational and experimental studies depict that when an m⁶A modification is positioned in between the two RRM domains, and in the context of the GGACU motif that can be written by methyltransferases, the binding affinity is nearly identical and slightly less favourable to the unmodified sequence. Our study suggests that HNRNPA2B1 is not a (selective) reader but has high affinity for m⁶A in sequence-dependent manner. This can be attributed to the strong interactions conferred by AGG and UAG motifs rather than adenine or m⁶A in the GGACU motif which are predicted to interact weakly, intercalating between the two RRMs or positioned outwards. Overall, our findings highlight the higher complexity of HNRNPA2B1 and RRM recognition properties compared to well-studied YTH domains in the recognition of m⁶A, as well as modified and unmodified sequences.

Polycystic ovary syndrome (PCOS) is a complex endocrine disorder whose pathophysiological mechanisms remain incompletely understood. Alternative splicing of transcription factors (TFs) may lead to significant functional consequences in the pathogenesis of PCOS. This study investigated genome-wide AS patterns and the expression of key TFs in PCOS to identify functionally relevant splicing events in a human dataset and validate them in a mouse model. Bioinformatics analysis of a PCOS RNA-seq dataset revealed 42 differentially spliced TFs, with enrichment in transcriptional regulation and metabolic pathways. Subsequent validation in a PCOS mouse model highlighted significant upregulation of Nfkb1 and Nfkb2, along with a specific exon-skipping event in Nfkb1 ;(Nfkb1-ES1496). Our findings demonstrate altered AS of critical TFs in PCOS, implicating dysregulated NF-κB signalling through splicing modulation as a potential contributor to the disorder, which may offer novel biomarker or therapeutic avenues.

Cervical cancer is a leading cause of cancer-related deaths, with cervical squamous cell carcinoma (CSCC) accounting for a majority of cases. Circular RNAs (circRNAs) have been repeatedly suggested as crucial effectors in modulating the development of multiple malignancies. The expression of circ_0002762 was predicted to be high in CSCC tissues in GEO dataset, but the functional role and underlying regulatory mechanism of circ_0002762 in CSCC was unclear. By series of functional assays and mechanism assays, supported by bioinformatics analysis, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) analysis and western blot assays, we identified that circ_0002762 aberrantly up-regulated in CSCC, promoting CSCC cell migration and invasion. Mechanically, circ_0002762 was transcriptionally activated by Fork head box A1 (FOXA1). Moreover, the involvement of nuclear factor kappa B (NF-kB) signalling in circ_0002762 regulation mechanism in CSCC cells was ascertained. Additionally, circ_0002762, predominantly accumulated in cell cytoplasm, was proved to recruit Mov10 RISC complex RNA helicase (MOV10) to enhance RelA mRNA stability, thus affecting CSCC cell migration and invasion. In summary, FOXA1-mediated circ_0002762 up-regulation could enhance the migratory and invasive abilities of CSCC cells via the MOV10/RelA/NF-kB pathway.