Deep learning, or artificial neural networks, is a type of machine learning algorithm that can de... more Deep learning, or artificial neural networks, is a type of machine learning algorithm that can decipher underlying relationships from large volumes of data and has been successfully applied to solve structural biology questions, such as RNA structure. RNA can fold into complex RNA structures by forming hydrogen bonds, thereby playing an essential role in biological processes. While experimental effort has enabled resolving RNA structure at the genome-wide scale, deep learning has been more recently introduced for studying RNA structure and its functionality. Here, we discuss successful applications of deep learning to solve RNA problems, including predictions of RNA structures, non-canonical G-quadruplex, RNA-protein interactions and RNA switches. Following these cases, we give a general guide to deep learning for solving RNA structure problems.
Additional file 5: TableS4. The list of riboSNitch between homoeologs of A and B subgenome in tet... more Additional file 5: TableS4. The list of riboSNitch between homoeologs of A and B subgenome in tetraploid Kronos.
Liquid–liquid phase separation plays an important role in a variety of cellular processes, includ... more Liquid–liquid phase separation plays an important role in a variety of cellular processes, including the formation of membrane-less organelles, the cytoskeleton, signalling complexes, and many other biological supramolecular assemblies. Studies on the molecular basis of phase separation in cells have focused on protein-driven phase separation. In contrast, there is limited understanding on how RNA specifically contributes to phase separation. Here, we described a phase-separation-like phenomenon that SHORT ROOT (SHR) RNA undergoes in cells. We found that an RNA G-quadruplex (GQ) forms in SHR mRNA and is capable of triggering RNA phase separation under physiological conditions, suggesting that GQs might be responsible for the formation of the SHR phase-separation-like phenomenon in vivo. We also found the extent of GQ-triggered-phase-separation increases on exposure to conditions which promote GQ. Furthermore, GQs with more G-quartets and longer loops are more likely to form phase se...
Cellular RNAs are heterogeneous with respect to their alternative processing and secondary struct... more Cellular RNAs are heterogeneous with respect to their alternative processing and secondary structures, but the functional importance of this complexity is still poorly understood. A set of alternatively processed antisense non-coding transcripts, which are collectively called COOLAIR, are generated at the Arabidopsis floral-repressor locus FLOWERING LOCUS C (FLC)1. Different isoforms of COOLAIR influence FLC transcriptional output in warm and cold conditions2–7. Here, to further investigate the function of COOLAIR, we developed an RNA structure-profiling method to determine the in vivo structure of single RNA molecules rather than the RNA population average. This revealed that individual isoforms of the COOLAIR transcript adopt multiple structures with different conformational dynamics. The major distally polyadenylated COOLAIR isoform in warm conditions adopts three predominant structural conformations, the proportions and conformations of which change after cold exposure. An alter...
Additional file 5. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per n... more Additional file 5. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in in vivo libraries.
Additional file 8. A detailed list of alternative poly(A) sites with high coverage (more than 1 R... more Additional file 8. A detailed list of alternative poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in deproteinized libraries.
Additional file 1: Figure S1. Assessment of nucleus isolation. Figure S2. The step-by-step proced... more Additional file 1: Figure S1. Assessment of nucleus isolation. Figure S2. The step-by-step procedure of SHAPE-Structure-Seq library construction. Figure S3. Summary of SHAPE-Structure-Seq libraries. Figure S4. High reads coverages of the nuclear SHAPE-Structure-Seq libraries. Figure S5. Average Pearson correlation coefficient (PCC) of SHAPE reactivities between the two biological replicates of the in vivo nuclear and cytosolic SHAPE-Structure-Seq libraries for mRNAs with different RT-stop reads counts. Figure S6. Comparison of SHAPE reactivity profiles with previously published mRNA secondary structure models. Figure S7. The high enrichment of pre-mRNAs in the nuclear SHAPE-Structure-Seq libraries. Figure S8. The formula for calculating the splicing efficiency and the identification of spliced and unspliced events. Figure S9. Similar nucleotide composition between spliced and unspliced events. Figure S10. Heatmaps showing the SHAPE reactivities across 5'ss for spliced and unspli...
Additional file 7. A detailed list of alternative poly(A) sites with high coverage (more than 1 R... more Additional file 7. A detailed list of alternative poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in in vivo libraries.
Additional file 6. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per n... more Additional file 6. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in deproteinized libraries.
Additional file 1: Figure S1. rG4-seq libraries with high reproducibility. Figure S2. rG4-seq pro... more Additional file 1: Figure S1. rG4-seq libraries with high reproducibility. Figure S2. rG4-seq profiles and predicted secondary structure of the undetected G-rich region on AT4G24820. Figure S3. NAI probing of Arabidopsis 18S rRNA in vitro and in vivo, and high reproducible SHALiPE-Seq libraries. Figure S4. Comparison of Gini values of SHALiPE-seq on in vitro folded RG4s. Figure S5. Landscape of RG4s folded in vivo in Arabidopsis. Figure S6. Gene Ontology (GO) analysis reveals enrichment of genes with similar molecular functions in Arabidopsis and rice for the genes containing RG4s. Figure S7. RG4 on HIRD11 modulates plant growth and translation. Figure S8. Dual luciferase reporting assay reveals that the RG4 on the 3'UTR of HIRD11 regulates translation.
Additional file 2: Table S1. G-rich regions with folding potential identified by rG4-seq with K+.... more Additional file 2: Table S1. G-rich regions with folding potential identified by rG4-seq with K+. TableS2. G-rich regions with folding potential identified by rG4-seq with K++PDS. TableS3. Gini index of SHALiPE profiles in vitro in the presence of Li+ and K+. TableS4. In vivo folding scores of Arabidopsis G-rich regions. TableS5. In vivo folding scores of rice G-rich regions. TableS6. Gene pairs of orthologues with RG4s in Arabidopsis and rice. TableS7. Primers used in this study.
The SARS-CoV-2 virus contains an unusually large, single-stranded RNA genome that is punctuated w... more The SARS-CoV-2 virus contains an unusually large, single-stranded RNA genome that is punctuated with structured elements of unknown function, such as the s2m element located in the 3 untranslated region. The evolutionary conservation of the s2m element and its occurrence in all viral subgenomic transcripts implicates a key role in the viral infection cycle. In order to exploit this element as a potential therapeutic target, we have designed antisense "gapmer" oligonucleotides that efficiently base-pair to the s2m region. These oligonucleotides, composed of locked nucleic acids (LNA) flanking a central DNA core, successfully remodel the s2m structure and induce sequence-specific RNA cleavage by RNase H in vitro. Gapmers are also effective in human cells as they reduce the fluorescence signal in GFP reporter assays and cause a dose-dependent reduction in replication in a model replicon system based on a human astrovirus. Overall, these oligonucleotides show promise as anti-v...
The hepatitis C virus internal ribosome entry site (IRES) element contains a three-way junction t... more The hepatitis C virus internal ribosome entry site (IRES) element contains a three-way junction that is important in the overall RNA conformation, and for its role in the internal initiation of translation. The junction also illustrates some important conformational principles in the folding of three-way helical junctions. It is formally a 3HS4 junction, with the possibility of two alternative stacking conformers. However, in principle, the junction can also undergo two steps of branch migration that would form 2HS1HS3 and 2HS2HS2 junctions. Comparative gel electrophoresis and ensemble fluorescence resonance energy transfer (FRET) studies show that the junction is induced to fold by the presence of Mg ions in low micromolar concentrations, and suggest that the structure adopted is based on coaxial stacking of the two helices that do not terminate in a hairpin loop (i.e., helix IIId). Single-molecule FRET studies confirm this conclusion, and indicate that there is no minor conformer ...
RNA folding is an intrinsic property of RNA that serves a key role in every step of post-transcri... more RNA folding is an intrinsic property of RNA that serves a key role in every step of post-transcriptional regulation of gene expression, from RNA maturation to translation in plants. Recent developments of genome-wide RNA structure profiling methods have transformed research in this area enabling focus to shift from individual molecules to the study of tens of thousands of RNAs. Here, we provide a comprehensive review of recent advances in the field. We discuss these new insights of RNA structure functionality within the context of post-transcriptional regulation including mRNA maturation, translation, and RNA degradation in plants. Notably, we also provide an overview of how plants exhibit different RNA structures in response to environmental changes.
Deep learning, or artificial neural networks, is a type of machine learning algorithm that can de... more Deep learning, or artificial neural networks, is a type of machine learning algorithm that can decipher underlying relationships from large volumes of data and has been successfully applied to solve structural biology questions, such as RNA structure. RNA can fold into complex RNA structures by forming hydrogen bonds, thereby playing an essential role in biological processes. While experimental effort has enabled resolving RNA structure at the genome-wide scale, deep learning has been more recently introduced for studying RNA structure and its functionality. Here, we discuss successful applications of deep learning to solve RNA problems, including predictions of RNA structures, non-canonical G-quadruplex, RNA-protein interactions and RNA switches. Following these cases, we give a general guide to deep learning for solving RNA structure problems.
Additional file 5: TableS4. The list of riboSNitch between homoeologs of A and B subgenome in tet... more Additional file 5: TableS4. The list of riboSNitch between homoeologs of A and B subgenome in tetraploid Kronos.
Liquid–liquid phase separation plays an important role in a variety of cellular processes, includ... more Liquid–liquid phase separation plays an important role in a variety of cellular processes, including the formation of membrane-less organelles, the cytoskeleton, signalling complexes, and many other biological supramolecular assemblies. Studies on the molecular basis of phase separation in cells have focused on protein-driven phase separation. In contrast, there is limited understanding on how RNA specifically contributes to phase separation. Here, we described a phase-separation-like phenomenon that SHORT ROOT (SHR) RNA undergoes in cells. We found that an RNA G-quadruplex (GQ) forms in SHR mRNA and is capable of triggering RNA phase separation under physiological conditions, suggesting that GQs might be responsible for the formation of the SHR phase-separation-like phenomenon in vivo. We also found the extent of GQ-triggered-phase-separation increases on exposure to conditions which promote GQ. Furthermore, GQs with more G-quartets and longer loops are more likely to form phase se...
Cellular RNAs are heterogeneous with respect to their alternative processing and secondary struct... more Cellular RNAs are heterogeneous with respect to their alternative processing and secondary structures, but the functional importance of this complexity is still poorly understood. A set of alternatively processed antisense non-coding transcripts, which are collectively called COOLAIR, are generated at the Arabidopsis floral-repressor locus FLOWERING LOCUS C (FLC)1. Different isoforms of COOLAIR influence FLC transcriptional output in warm and cold conditions2–7. Here, to further investigate the function of COOLAIR, we developed an RNA structure-profiling method to determine the in vivo structure of single RNA molecules rather than the RNA population average. This revealed that individual isoforms of the COOLAIR transcript adopt multiple structures with different conformational dynamics. The major distally polyadenylated COOLAIR isoform in warm conditions adopts three predominant structural conformations, the proportions and conformations of which change after cold exposure. An alter...
Additional file 5. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per n... more Additional file 5. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in in vivo libraries.
Additional file 8. A detailed list of alternative poly(A) sites with high coverage (more than 1 R... more Additional file 8. A detailed list of alternative poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in deproteinized libraries.
Additional file 1: Figure S1. Assessment of nucleus isolation. Figure S2. The step-by-step proced... more Additional file 1: Figure S1. Assessment of nucleus isolation. Figure S2. The step-by-step procedure of SHAPE-Structure-Seq library construction. Figure S3. Summary of SHAPE-Structure-Seq libraries. Figure S4. High reads coverages of the nuclear SHAPE-Structure-Seq libraries. Figure S5. Average Pearson correlation coefficient (PCC) of SHAPE reactivities between the two biological replicates of the in vivo nuclear and cytosolic SHAPE-Structure-Seq libraries for mRNAs with different RT-stop reads counts. Figure S6. Comparison of SHAPE reactivity profiles with previously published mRNA secondary structure models. Figure S7. The high enrichment of pre-mRNAs in the nuclear SHAPE-Structure-Seq libraries. Figure S8. The formula for calculating the splicing efficiency and the identification of spliced and unspliced events. Figure S9. Similar nucleotide composition between spliced and unspliced events. Figure S10. Heatmaps showing the SHAPE reactivities across 5'ss for spliced and unspli...
Additional file 7. A detailed list of alternative poly(A) sites with high coverage (more than 1 R... more Additional file 7. A detailed list of alternative poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in in vivo libraries.
Additional file 6. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per n... more Additional file 6. A detailed list of poly(A) sites with high coverage (more than 1 RT-stop per nucleotide) in deproteinized libraries.
Additional file 1: Figure S1. rG4-seq libraries with high reproducibility. Figure S2. rG4-seq pro... more Additional file 1: Figure S1. rG4-seq libraries with high reproducibility. Figure S2. rG4-seq profiles and predicted secondary structure of the undetected G-rich region on AT4G24820. Figure S3. NAI probing of Arabidopsis 18S rRNA in vitro and in vivo, and high reproducible SHALiPE-Seq libraries. Figure S4. Comparison of Gini values of SHALiPE-seq on in vitro folded RG4s. Figure S5. Landscape of RG4s folded in vivo in Arabidopsis. Figure S6. Gene Ontology (GO) analysis reveals enrichment of genes with similar molecular functions in Arabidopsis and rice for the genes containing RG4s. Figure S7. RG4 on HIRD11 modulates plant growth and translation. Figure S8. Dual luciferase reporting assay reveals that the RG4 on the 3'UTR of HIRD11 regulates translation.
Additional file 2: Table S1. G-rich regions with folding potential identified by rG4-seq with K+.... more Additional file 2: Table S1. G-rich regions with folding potential identified by rG4-seq with K+. TableS2. G-rich regions with folding potential identified by rG4-seq with K++PDS. TableS3. Gini index of SHALiPE profiles in vitro in the presence of Li+ and K+. TableS4. In vivo folding scores of Arabidopsis G-rich regions. TableS5. In vivo folding scores of rice G-rich regions. TableS6. Gene pairs of orthologues with RG4s in Arabidopsis and rice. TableS7. Primers used in this study.
The SARS-CoV-2 virus contains an unusually large, single-stranded RNA genome that is punctuated w... more The SARS-CoV-2 virus contains an unusually large, single-stranded RNA genome that is punctuated with structured elements of unknown function, such as the s2m element located in the 3 untranslated region. The evolutionary conservation of the s2m element and its occurrence in all viral subgenomic transcripts implicates a key role in the viral infection cycle. In order to exploit this element as a potential therapeutic target, we have designed antisense "gapmer" oligonucleotides that efficiently base-pair to the s2m region. These oligonucleotides, composed of locked nucleic acids (LNA) flanking a central DNA core, successfully remodel the s2m structure and induce sequence-specific RNA cleavage by RNase H in vitro. Gapmers are also effective in human cells as they reduce the fluorescence signal in GFP reporter assays and cause a dose-dependent reduction in replication in a model replicon system based on a human astrovirus. Overall, these oligonucleotides show promise as anti-v...
The hepatitis C virus internal ribosome entry site (IRES) element contains a three-way junction t... more The hepatitis C virus internal ribosome entry site (IRES) element contains a three-way junction that is important in the overall RNA conformation, and for its role in the internal initiation of translation. The junction also illustrates some important conformational principles in the folding of three-way helical junctions. It is formally a 3HS4 junction, with the possibility of two alternative stacking conformers. However, in principle, the junction can also undergo two steps of branch migration that would form 2HS1HS3 and 2HS2HS2 junctions. Comparative gel electrophoresis and ensemble fluorescence resonance energy transfer (FRET) studies show that the junction is induced to fold by the presence of Mg ions in low micromolar concentrations, and suggest that the structure adopted is based on coaxial stacking of the two helices that do not terminate in a hairpin loop (i.e., helix IIId). Single-molecule FRET studies confirm this conclusion, and indicate that there is no minor conformer ...
RNA folding is an intrinsic property of RNA that serves a key role in every step of post-transcri... more RNA folding is an intrinsic property of RNA that serves a key role in every step of post-transcriptional regulation of gene expression, from RNA maturation to translation in plants. Recent developments of genome-wide RNA structure profiling methods have transformed research in this area enabling focus to shift from individual molecules to the study of tens of thousands of RNAs. Here, we provide a comprehensive review of recent advances in the field. We discuss these new insights of RNA structure functionality within the context of post-transcriptional regulation including mRNA maturation, translation, and RNA degradation in plants. Notably, we also provide an overview of how plants exhibit different RNA structures in response to environmental changes.
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