The Human RNA-Binding Proteome and Its Dynamics during Translational Arrest.

Proteins and RNA functionally and physically intersect in multiple biological processes, however, currently no universal method is available to purify protein-RNA complexes. Here, we introduce XRNAX, a method for the generic purification of protein-crosslinked RNA, and demonstrate its versatility to study the composition and dynamics of protein-RNA interactions by various transcriptomic and proteomic approaches. We show that XRNAX captures all RNA biotypes and use this to characterize the sub-proteomes that interact with coding and non-coding RNAs (ncRNAs) and to identify hundreds of protein-RNA interfaces. Exploiting the quantitative nature of XRNAX, we observe drastic remodeling of the RNA-bound proteome during arsenite-induced stress, distinct from autophagy-related changes in the total proteome. In addition, we combine XRNAX with crosslinking immunoprecipitation sequencing (CLIP-seq) to validate the interaction of ncRNA with lamin B1 and EXOSC2. Thus, XRNAX is a resourceful approach to study structural and compositional aspects of protein-RNA interactions to address fundamental questions in RNA-biology.

Dysregulated Expression of the Nuclear Exosome Targeting Complex Component Rbm7 in Nonhematopoietic Cells Licenses the Development of Fibrosis.

Fibrosis is an incurable disorder of unknown etiology. Segregated-nucleus-containing atypical monocytes (SatMs) are critical for the development of fibrosis. Here we examined the mechanisms that recruit SatMs to pre-fibrotic areas. A screen based on cytokine expression in the fibrotic lung revealed that the chemokine Cxcl12, which is produced by apoptotic nonhematopoietic cells, was essential for SatM recruitment. Analyses of lung tissues at fibrosis onset showed increased expression of Rbm7, a component of the nuclear exosome targeting complex. Rbm7 deletion suppressed bleomycin-induced fibrosis and at a cellular level, suppressed apoptosis of nonhematopoietic cells. Mechanistically, Rbm7 bound to noncoding (nc)RNAs that form subnuclear bodies, including Neat1 speckles. Dysregulated expression of Rbm7 resulted in the nuclear degradation of Neat1 speckles, the dispersion of the DNA repair protein BRCA1, and the triggering of apoptosis. Thus, Rbm7 in epithelial cells plays a critical role in the development of fibrosis by regulating ncRNA decay and thereby the production of chemokines that recruit SatMs.

The oncomicropeptide APPLE promotes hematopoietic malignancy by enhancing translation initiation.

Initiation is the rate-limiting step in translation, and its dysregulation is vital for carcinogenesis, including hematopoietic malignancy. Thus, discovery of novel translation initiation regulators may provide promising therapeutic targets. Here, combining Ribo-seq, mass spectrometry, and RNA-seq datasets, we discovered an oncomicropeptide, APPLE (a peptide located in ER), encoded by a non-coding RNA transcript in acute myeloid leukemia (AML). APPLE is overexpressed in various subtypes of AML and confers a poor prognosis. The micropeptide is enriched in ribosomes and regulates the initiation step to enhance translation and to maintain high rates of oncoprotein synthesis. Mechanically, APPLE promotes PABPC1-eIF4G interaction and facilitates mRNA circularization and eIF4F initiation complex assembly to support a specific pro-cancer translation program. Targeting APPLE exhibited broad anti-cancer effects in vitro and in vivo. This study not only reports a previously unknown function of micropeptides but also provides new opportunities for targeting the translation machinery in cancer cells.

Nucleosomes Stabilize ssRNA-dsDNA Triple Helices in Human Cells.

Chromatin-associated non-coding RNAs modulate the epigenetic landscape and its associated gene expression program. The formation of triple helices is one mechanism of sequence-specific targeting of RNA to chromatin. With this study, we show an important role of the nucleosome and its relative positioning to the triplex targeting site (TTS) in stabilizing RNA-DNA triplexes in vitro and in vivo. Triplex stabilization depends on the histone H3 tail and the location of the TTS close to the nucleosomal DNA entry-exit site. Genome-wide analysis of TTS-nucleosome arrangements revealed a defined chromatin organization with an enrichment of arrangements that allow triplex formation at active regulatory sites and accessible chromatin. We further developed a method to monitor nucleosome-RNA triplexes in vivo (TRIP-seq), revealing RNA binding to TTS sites adjacent to nucleosomes. Our data strongly support an activating role for RNA triplex-nucleosome complexes, pinpointing triplex-mediated epigenetic regulation in vivo.

Reaction Mechanisms of Pol IV, RDR2, and DCL3 Drive RNA Channeling in the siRNA-Directed DNA Methylation Pathway.

In eukaryotes with multiple small RNA pathways, the mechanisms that channel RNAs within specific pathways are unclear. Here, we reveal the reactions that account for channeling in the small interfering RNA (siRNA) biogenesis phase of the Arabidopsis RNA-directed DNA methylation pathway. The process begins with template DNA transcription by NUCLEAR RNA POLYMERASE IV (Pol IV), whose atypical termination mechanism, induced by nontemplate DNA base-pairing, channels transcripts to the associated RNA-dependent RNA polymerase RDR2. RDR2 converts Pol IV transcripts into double-stranded RNAs and then typically adds an extra untemplated 3' terminal nucleotide to the second strands. The dicer endonuclease DCL3 cuts resulting duplexes to generate 24- and 23-nt siRNAs. The 23-nt RNAs bear the untemplated terminal nucleotide of the RDR2 strand and are underrepresented among ARGONAUTE4-associated siRNAs. Collectively, our results provide mechanistic insights into Pol IV termination, Pol IV-RDR2 coupling, and RNA channeling, from template DNA transcription to siRNA strand discrimination.

RN7SL1 may be translated under oncogenic conditions.

RN7SL1 (RNA component of signal recognition particle 7SL1), a component of the signal recognition particle, is a non-coding RNA possessing a small ORF (smORF). However, whether it is translated into peptides is unknown. Here, we generated the RN7SL1-Green Fluorescent Protein (GFP) gene, in which the smORF of RN7SL1 was replaced by GFP, introduced it into 293T cells, and observed cells emitting GFP fluorescence. Furthermore, RNA-seq of GFP-positive cells revealed that they were in an oncogenic state, suggesting that RN7SL1 smORF may be translated under special conditions.

Noncoding RNAs improve the predictive power of network medicine.

Network medicine has improved the mechanistic understanding of disease, offering quantitative insights into disease mechanisms, comorbidities, and novel diagnostic tools and therapeutic treatments. Yet, most network-based approaches rely on a comprehensive map of protein-protein interactions (PPI), ignoring interactions mediated by noncoding RNAs (ncRNAs). Here, we systematically combine experimentally confirmed binding interactions mediated by ncRNA with PPI, constructing a comprehensive network of all physical interactions in the human cell. We find that the inclusion of ncRNA expands the number of genes in the interactome by 46% and the number of interactions by 107%, significantly enhancing our ability to identify disease modules. Indeed, we find that 132 diseases lacked a statistically significant disease module in the protein-based interactome but have a statistically significant disease module after inclusion of ncRNA-mediated interactions, making these diseases accessible to the tools of network medicine. We show that the inclusion of ncRNAs helps unveil disease-disease relationships that were not detectable before and expands our ability to predict comorbidity patterns between diseases. Taken together, we find that including noncoding interactions improves both the breath and the predictive accuracy of network medicine.

The degree of enhancer or promoter activity is reflected by the levels and directionality of eRNA transcription.

Gene expression is regulated by promoters, which initiate transcription, and enhancers, which control their temporal and spatial activity. However, the discovery that mammalian enhancers also initiate transcription questions the inherent differences between enhancers and promoters. Here, we investigate the transcriptional properties of enhancers during Drosophila embryogenesis using characterized developmental enhancers. We show that while the timing of enhancer transcription is generally correlated with enhancer activity, the levels and directionality of transcription are highly varied among active enhancers. To assess how this impacts function, we developed a dual transgenic assay to simultaneously measure enhancer and promoter activities from a single element in the same embryo. Extensive transgenic analysis revealed a relationship between the direction of endogenous transcription and the ability to function as an enhancer or promoter in vivo, although enhancer RNA (eRNA) production and activity are not always strictly coupled. Some enhancers (mainly bidirectional) can act as weak promoters, producing overlapping spatio-temporal expression. Conversely, bidirectional promoters often act as strong enhancers, while unidirectional promoters generally cannot. The balance between enhancer and promoter activity is generally reflected in the levels and directionality of eRNA transcription and is likely an inherent sequence property of the elements themselves.

The Hda1 histone deacetylase limits divergent non-coding transcription and restricts transcription initiation frequency.

Nucleosome-depleted regions (NDRs) at gene promoters support initiation of RNA polymerase II transcription. Interestingly, transcription often initiates in both directions, resulting in an mRNA and a divergent non-coding (DNC) transcript of unclear purpose. Here, we characterized the genetic architecture and molecular mechanism of DNC transcription in budding yeast. Using high-throughput reverse genetic screens based on quantitative single-cell fluorescence measurements, we identified the Hda1 histone deacetylase complex (Hda1C) as a repressor of DNC transcription. Nascent transcription profiling showed a genome-wide role of Hda1C in repression of DNC transcription. Live-cell imaging of transcription revealed that mutations in the Hda3 subunit increased the frequency of DNC transcription. Hda1C contributed to decreased acetylation of histone H3 in DNC transcription regions, supporting DNC transcription repression by histone deacetylation. Our data support the interpretation that DNC transcription results as a consequence of the NDR-based architecture of eukaryotic promoters, but that it is governed by locus-specific repression to maintain genome fidelity.

miProBERT: identification of microRNA promoters based on the pre-trained model BERT.

Accurate prediction of promoter regions driving miRNA gene expression has become a major challenge due to the lack of annotation information for pri-miRNA transcripts. This defect hinders our understanding of miRNA-mediated regulatory networks. Some algorithms have been designed during the past decade to detect miRNA promoters. However, these methods rely on biosignal data such as CpG islands and still need to be improved. Here, we propose miProBERT, a BERT-based model for predicting promoters directly from gene sequences without using any structural or biological signals. According to our information, it is the first time a BERT-based model has been employed to identify miRNA promoters. We use the pre-trained model DNABERT, fine-tune the pre-trained model on the gene promoter dataset so that the model includes information about the richer biological properties of promoter sequences in its representation, and then systematically scan the upstream regions of each intergenic miRNA using the fine-tuned model. About, 665 miRNA promoters are found. The innovative use of a random substitution strategy to construct a negative dataset improves the discriminative ability of the model and further reduces the false positive rate (FPR) to as low as 0.0421. On independent datasets, miProBERT outperformed other gene promoter prediction methods. With comparison on 33 experimentally validated miRNA promoter datasets, miProBERT significantly outperformed previously developed miRNA promoter prediction programs with 78.13% precision and 75.76% recall. We further verify the predicted promoter regions by analyzing conservation, CpG content and histone marks. The effectiveness and robustness of miProBERT are highlighted.

MFPred: prediction of ncRNA families based on multi-feature fusion.

Non-coding RNA (ncRNA) plays a critical role in biology. ncRNAs from the same family usually have similar functions, as a result, it is essential to predict ncRNA families before identifying their functions. There are two primary methods for predicting ncRNA families, namely, traditional biological methods and computational methods. In traditional biological methods, a lot of manpower and resources are required to predict ncRNA families. Therefore, this paper proposed a new ncRNA family prediction method called MFPred based on computational methods. MFPred identified ncRNA families by extracting sequence features of ncRNAs, and it possessed three primary modules, including (1) four ncRNA sequences encoding and feature extraction module, which encoded ncRNA sequences and extracted four different features of ncRNA sequences, (2) dynamic Bi_GRU and feature fusion module, which extracted contextual information features of the ncRNA sequence and (3) ResNet_SE module that extracted local information features of the ncRNA sequence. In this study, MFPred was compared with the previously proposed ncRNA family prediction methods using two frequently used public ncRNA datasets, NCY and nRC. The results showed that MFPred outperformed other prediction methods in the two datasets.

CoraL: interpretable contrastive meta-learning for the prediction of cancer-associated ncRNA-encoded small peptides.

NcRNA-encoded small peptides (ncPEPs) have recently emerged as promising targets and biomarkers for cancer immunotherapy. Therefore, identifying cancer-associated ncPEPs is crucial for cancer research. In this work, we propose CoraL, a novel supervised contrastive meta-learning framework for predicting cancer-associated ncPEPs. Specifically, the proposed meta-learning strategy enables our model to learn meta-knowledge from different types of peptides and train a promising predictive model even with few labeled samples. The results show that our model is capable of making high-confidence predictions on unseen cancer biomarkers with only five samples, potentially accelerating the discovery of novel cancer biomarkers for immunotherapy. Moreover, our approach remarkably outperforms existing deep learning models on 15 cancer-associated ncPEPs datasets, demonstrating its effectiveness and robustness. Interestingly, our model exhibits outstanding performance when extended for the identification of short open reading frames derived from ncPEPs, demonstrating the strong prediction ability of CoraL at the transcriptome level. Importantly, our feature interpretation analysis discovers unique sequential patterns as the fingerprint for each cancer-associated ncPEPs, revealing the relationship among certain cancer biomarkers that are validated by relevant literature and motif comparison. Overall, we expect CoraL to be a useful tool to decipher the pathogenesis of cancer and provide valuable information for cancer research. The dataset and source code of our proposed method can be found at https://github.com/Johnsunnn/CoraL.

CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation.

Dynamic tuning of the poly(A) tail is a crucial mechanism for controlling translation and stability of eukaryotic mRNA. Achieving a comprehensive understanding of how this regulation occurs requires unbiased abundance quantification of poly(A)-tail transcripts and simple poly(A)-length measurement using high-throughput sequencing platforms. Current methods have limitations due to complicated setups and elaborate library preparation plans. To address this, we introduce central limit theorem (CLT)-managed RNA-seq (CLT-seq), a simple and straightforward homopolymer-sequencing method. In CLT-seq, an anchor-free oligo(dT) primer rapidly binds to and unbinds from anywhere along the poly(A) tail string, leading to position-directed reverse transcription with equal probability. The CLT mechanism enables the synthesized poly(T) lengths, which correspond to the templated segment of the poly(A) tail, to distribute normally. Based on a well-fitted pseudogaussian-derived poly(A)-poly(T) conversion model, the actual poly(A)-tail profile is reconstructed from the acquired poly(T)-length profile through matrix operations. CLT-seq follows a simple procedure without requiring RNA-related pre-treatment, enrichment or selection, and the CLT-shortened poly(T) stretches are more compatible with existing sequencing platforms. This proof-of-concept approach facilitates direct homopolymer base-calling and features unbiased RNA-seq. Therefore, CLT-seq provides unbiased, robust and cost-efficient transcriptome-wide poly(A)-tail profiling. We demonstrate that CLT-seq on the most common Illumina platform delivers reliable poly(A)-tail profiling at a transcriptome-wide scale in human cellular contexts. We find that the poly(A)-tail-tuned ncRNA regulation undergoes a dynamic, complex process similar to mRNA regulation. Overall, CLT-seq offers a simplified, effective and economical approach to investigate poly(A)-tail regulation, with potential implications for understanding gene expression and identifying therapeutic targets.

Biogenesis of telomerase RNA from a protein-coding mRNA precursor.

Telomerase is a eukaryotic ribonucleoprotein (RNP) enzyme that adds DNA repeats onto chromosome ends to maintain genomic stability and confer cellular immortality in cancer and stem cells. The telomerase RNA (TER) component is essential for telomerase catalytic activity and provides the template for telomeric DNA synthesis. The biogenesis of TERs is extremely divergent across eukaryotic kingdoms, employing distinct types of transcription machinery and processing pathways. In ciliates and plants, TERs are transcribed by RNA polymerase III (Pol III), while animal and ascomycete fungal TERs are transcribed by RNA Pol II and share biogenesis pathways with small nucleolar RNA (snoRNA) and small nuclear RNA (snRNA), respectively. Here, we report an unprecedented messenger RNA (mRNA)-derived biogenesis pathway for the 1,291 nucleotide TER from the basidiomycete fungus Ustilago maydis. The U. maydis TER (UmTER) contains a 5'-monophosphate, distinct from the 5' 2,2,7-trimethylguanosine (TMG) cap common to animal and ascomycete fungal TERs. The mature UmTER is processed from the 3'-untranslated region (3'-UTR) of a larger RNA precursor that possesses characteristics of mRNA including a 5' 7-methyl-guanosine (m7G) cap, alternative splicing of introns, and a poly(A) tail. Moreover, this mRNA transcript encodes a protein called Early meiotic induction protein 1 (Emi1) that is conserved across dikaryotic fungi. A recombinant UmTER precursor expressed from an mRNA promoter is processed correctly to yield mature UmTER, confirming an mRNA-processing pathway for producing TER. Our findings expand the plethora of TER biogenesis mechanisms and demonstrate a pathway for producing a functional long noncoding RNA from a protein-coding mRNA precursor.

Integrated analysis of lncRNA, miRNA and mRNA expression profiles reveals regulatory pathways associated with pig testis function.

Long noncoding RNA (lncRNA) and microRNA (miRNA) are known to play pivotal roles in mammalian testicular function and spermatogenesis. However, their impact on porcine male reproduction has yet to be well unraveled. Here, we sequenced and identified lncRNA and miRNA expressed in the testes of Chinese indigenous Banna mini-pig inbred line (BMI) and introduced Western Duroc (DU) and Large White (LW) pigs. By pairwise comparison (BMI vs DU, BMI vs LW, and DU vs LW), we found the gene expression differences in the testes between Chinese local pigs and introduced Western commercial breeds were more striking than those between introduced commercial breeds. Furthermore, we found 1622 co-differentially expressed genes (co-DEGs), 122 co-differentially expressed lncRNAs (co-DELs), 39 co-differentially expressed miRNAs (co-DEMs) in BMI vs introduced commercial breeds (DU and LW). Functional analysis revealed that these co-DEGs and co-DELs/co-DEMs target genes were enriched in male sexual function pathways, including MAPK, AMPK, TGF-ß/Smad, Hippo, NF-kappa B, and PI3K/Akt signaling pathways. Additionally, we established 10,536 lncRNA-mRNA, 11,248 miRNA-mRNA pairs, and 62 ceRNA (lncRNA-miRNA-mRNA) networks. The ssc-miR-1343 had the most interactive factors in the ceRNA network, including 20 mRNAs and 3 lncRNAs, consisting of 56 ceRNA pairs. These factors played extremely important roles in the regulation of testis function as key nodes in the interactive regulatory network. Our results provide insight into the functional roles of lncRNAs and miRNAs in porcine testis and offer a valuable resource for understanding the differences between Chinese indigenous and introduced Western pigs.

Preliminary construction of non-coding RNAs and ceRNA regulatory networks mediated by exosomes in porcine follicular fluid.

BACKGROUND: Follicles are fundamental units of the ovary, regulated intricately during development. Exosomes and ovarian granulosa cells (OGCs) play pivotal roles in follicular development, yet the regulatory mechanisms governing exosomes remain elusive. RESULTS: High-throughput sequencing was employed to evaluate the complete transcript expression profiles of six samples (three porcine ovarian granulosa cells-exosome co-culture samples (GCE) and three porcine ovarian granulosa cells (POGCs) samples). Differential expression analysis revealed 924 lncRNAs, 35 circRNAs, 49 miRNAs, and 9823 mRNAs in the GCE group. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated enrichment of differentially expressed transcripts in pathways related to cell proliferation and apoptosis. Furthermore, a ceRNA regulatory network comprising 43 lncRNAs, 6 circRNAs, 11 miRNAs, and 126 mRNAs was constructed based on intergene co-expression correlations. Seven miRNAs associated with cell proliferation and apoptosis regulation were identified within this network, encompassing 92 subnet pairs as candidate genes for further exploration of exosome regulatory mechanisms. Additionally, preliminary verification at the cellular level demonstrated that exosomal miR-200b enhances the viability of POGCs. CONCLUSIONS: Transcriptome analysis unveiled a pivotal candidate ceRNA network potentially implicated in exosome-mediated regulation of granulosa cell proliferation and apoptosis, thereby influencing porcine follicular development. These findings offer insights into the molecular mechanisms of follicular fluid exosome regulation, encompassing both coding and non-coding RNA perspectives.

MFPINC: prediction of plant ncRNAs based on multi-source feature fusion.

Non-coding RNAs (ncRNAs) are recognized as pivotal players in the regulation of essential physiological processes such as nutrient homeostasis, development, and stress responses in plants. Common methods for predicting ncRNAs are susceptible to significant effects of experimental conditions and computational methods, resulting in the need for significant investment of time and resources. Therefore, we constructed an ncRNA predictor(MFPINC), to predict potential ncRNA in plants which is based on the PINC tool proposed by our previous studies. Specifically, sequence features were carefully refined using variance thresholding and F-test methods, while deep features were extracted and feature fusion were performed by applying the GRU model. The comprehensive evaluation of multiple standard datasets shows that MFPINC not only achieves more comprehensive and accurate identification of gene sequences, but also significantly improves the expressive and generalization performance of the model, and MFPINC significantly outperforms the existing competing methods in ncRNA identification. In addition, it is worth mentioning that our tool can also be found on Github ( https://github.com/Zhenj-Nie/MFPINC ) the data and source code can also be downloaded for free.

Unraveling the cross-talk between N6-methyladenosine modification and non-coding RNAs in breast cancer: Mechanisms and clinical implications.

In recent years, breast cancer (BC) has surpassed lung cancer as the most common malignant tumor worldwide and remains the leading cause of cancer death in women. The etiology of BC usually involves dysregulation of epigenetic mechanisms and aberrant expression of certain non-coding RNAs (ncRNAs). N6-methyladenosine (m6A), the most prevalent RNA modification in eukaryotes, widely exists in ncRNAs to affect its biosynthesis and function, and is an important regulator of tumor-related signaling pathways. Interestingly, ncRNAs can also regulate or target m6A modification, playing a key role in cancer progression. However, the m6A-ncRNAs regulatory network in BC has not been fully elucidated, especially the regulation of m6A modification by ncRNAs. Therefore, in this review, we comprehensively summarize the interaction mechanisms and biological significance of m6A modifications and ncRNAs in BC. Meanwhile, we also focused on the clinical application value of m6A modification in BC diagnosis and prognosis, intending to explore new biomarkers and potential therapeutic targets.

Expression of the non-coding RNA nc886 facilitates the development of tyrosine kinase inhibitor resistance in EGFR-mutated non-small-cell lung cancer cells.

Treatment of non-small-cell lung cancer (NSCLC) patients possessing EGFR-activating mutations with tyrosine kinase inhibitors (TKIs) can confer an initial promising response. However, TKI resistance inevitably arises. Numerous TKI resistance mechanisms are identified including EGFR secondary mutations, bypass receptor tyrosine kinase (RTK) signaling, and cellular transition e.g. epithelial-mesenchymal transition (EMT). To increase the knowledge of TKI resistance we performed an epigenetic screen to identify small non-coding (nc) genes with DNA methylation alterations in HCC827 NSCLC EGFR-mutated cells with acquired TKI resistance. We analyzed Infinium Methylation EPIC 850K Array data for DNA methylation changes present in both TKI-resistant HCC827 cells with EMT and MET-amplification. Hereby, we identified that the polymorphic maternal imprinted gene nc886 (vtRNA2-1) has a decrease in promoter DNA methylation in TKI-resistant cells. This epigenetic change was associated with an increase in the expression of nc886. The induction of EMT did not affect nc886 expression. CRISPR/Cas9-mediated distortion of the nc886 sequence increased the sensitivity of HCC827 cells towards TKI. Finally, nc886 sequence distortion hindered MET RTK activation and instead was EMT the endpoint TKI resistance mechanism. In conclusion, the expression of nc886 contributes to TKI resistance in the HCC827 NSCLC cell line by supporting cell survival and selection of the endpoint TKI resistance mechanism. We propose DNA methylation and expression changes for nc886 to constitute a novel TKI resistance contributing mechanism in NSCLC.

Ectopic enhancer-enhancer interactions as causal forces driving RNA-directed DNA methylation in gene regulatory regions.

Cis-regulatory elements (CREs) are integral to the spatiotemporal and quantitative expression dynamics of target genes, thus directly influencing phenotypic variation and evolution. However, many of these CREs become highly susceptible to transcriptional silencing when in a transgenic state, particularly when organised as tandem repeats. We investigated the mechanism of this phenomenon and found that three of the six selected flower-specific CREs were prone to transcriptional silencing when in a transgenic context. We determined that this silencing was caused by the ectopic expression of non-coding RNAs (ncRNAs), which were processed into 24-nt small interfering RNAs (siRNAs) that drove RNA-directed DNA methylation (RdDM). Detailed analyses revealed that aberrant ncRNA transcription within the AGAMOUS enhancer (AGe) in a transgenic context was significantly enhanced by an adjacent CaMV35S enhancer (35Se). This particular enhancer is known to mis-activate the regulatory activities of various CREs, including the AGe. Furthermore, an insertion of 35Se approximately 3.5 kb upstream of the AGe in its genomic locus also resulted in the ectopic induction of ncRNA/siRNA production and de novo methylation specifically in the AGe, but not other regions, as well as the production of mutant flowers. This confirmed that interactions between the 35Se and AGe can induce RdDM activity in both genomic and transgenic states. These findings highlight a novel epigenetic role for CRE-CRE interactions in plants, shedding light on the underlying forces driving hypermethylation in transgenes, duplicate genes/enhancers, and repetitive transposons, in which interactions between CREs are inevitable.