RNA structure framework: automated transcriptome-wide reconstruction of RNA secondary structures from high-throughput structure probing data

RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical analysis of the real RNA secondary structures of all 480 sequences from RNA STRAND, which are validated by NMR or X-ray. The length ratios of domains in these sequences are approximately 0.382L, 0.5L, 0.618L, andL, whereLis the sequence length. These points are just the important golden sections of sequence. With this characteristic, an algorithm is designed to predict RNA hierarchical structures and simulate RNA folding by dynamically folding RNA structures according to the above golden section points. The sensitivity and number of predicted pseudoknots of our algorithm are better than those of the Mfold, HotKnots, McQfold, ProbKnot, and Lhw-Zhu algorithms. Experimental results reflect the folding rules of RNA from a new angle that is close to natural folding.

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Differential BUM-HMM: a robust statistical modelling approach for detecting RNA flexibility changes in high-throughput structure probing data

10.1101/2020.07.30.229179 ◽

2020 ◽

Author(s):

Paolo Marangio ◽

Ka Ying Toby Law ◽

Guido Sanguinetti ◽

Sander Granneman

Keyword(s):

Protein Binding ◽

High Throughput ◽

Conformational Changes ◽

Binding Sites ◽

Rna Structure ◽

Structural Changes ◽

High Throughput Sequencing ◽

Structural Information ◽

Protein Binding Sites ◽

Structure Probing

Combining RNA structure probing with high-throughput sequencing technologies has greatly enhanced our ability to analyze RNA structure at transcriptome scale. However, the high level of noise and variability encountered in these data call for the development of computational tools that robustly extract RNA structural information. Here we present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. DiffBUM-HMM is compatible with a wide variety of high-throughput RNA structure probing data, taking into consideration biological variation, sequence coverage and sequence representation biases. We demonstrate that, compared to the existing approaches, diffBUM-HMM displays higher sensitivity while calling virtually no false positives. DiffBUM-HMM analysis of ex vivo and in vivo Xist SHAPE-MaP data detected many more RNA structural differences, involving mostly single-stranded nucleotides located at or near protein-binding sites. Collectively, our analyses demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and reinforce the notion that RNA structure probing is a very powerful tool for identifying protein-binding sites.

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diffBUM-HMM: a robust statistical modeling approach for detecting RNA flexibility changes in high-throughput structure probing data

Genome Biology ◽

10.1186/s13059-021-02379-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Paolo Marangio ◽

Ka Ying Toby Law ◽

Guido Sanguinetti ◽

Sander Granneman

Keyword(s):

High Throughput ◽

Conformational Changes ◽

Rna Structure ◽

Structural Changes ◽

Rna Binding ◽

Structural Information ◽

Sequence Coverage ◽

Structure Probing ◽

Generation Sequencing ◽

Higher Sensitivity

AbstractAdvancing RNA structural probing techniques with next-generation sequencing has generated demands for complementary computational tools to robustly extract RNA structural information amidst sampling noise and variability. We present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. diffBUM-HMM is widely compatible, accounting for sampling variation and sequence coverage biases, and displays higher sensitivity than existing methods while robust against false positives. Our analyses of datasets generated with a variety of RNA probing chemistries demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and RNA-binding protein binding sites.

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Computational identification of protein binding sites on RNAs using high-throughput RNA structure-probing data

Bioinformatics ◽

10.1093/bioinformatics/btt757 ◽

2013 ◽

Vol 30 (8) ◽

pp. 1049-1055 ◽

Cited By ~ 4

Author(s):

Xihao Hu ◽

Thomas K. F. Wong ◽

Zhi John Lu ◽

Ting Fung Chan ◽

Terrence Chi Kong Lau ◽

...

Keyword(s):

Protein Binding ◽

High Throughput ◽

Binding Sites ◽

Rna Structure ◽

Protein Binding Sites ◽

Structure Probing ◽

Computational Identification

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High-throughput RNA structure probing reveals critical folding events during early 60S ribosome assembly in yeast

Nature Communications ◽

10.1038/s41467-017-00761-8 ◽

2017 ◽

Vol 8 (1) ◽

Cited By ~ 16

Author(s):

Elena Burlacu ◽

Fredrik Lackmann ◽

Lisbeth-Carolina Aguilar ◽

Sergey Belikov ◽

Rob van Nues ◽

...

Keyword(s):

High Throughput ◽

Rna Structure ◽

Ribosome Assembly ◽

Structure Probing

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In Vivo and In Vitro Genome-Wide Profiling of RNA Secondary Structures Reveals Key Regulatory Features in Plasmodium falciparum

Frontiers in Cellular and Infection Microbiology ◽

10.3389/fcimb.2021.673966 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yanwei Qi ◽

Yuhong Zhang ◽

Guixing Zheng ◽

Bingxia Chen ◽

Mengxin Zhang ◽

...

Keyword(s):

Secondary Structure ◽

Rna Structure ◽

Rna Secondary Structure ◽

Secondary Structures ◽

Rna Structures ◽

Trophozoite Stage ◽

Rna Secondary Structures ◽

Biological Programme

It is widely accepted that the structure of RNA plays important roles in a number of biological processes, such as polyadenylation, splicing, and catalytic functions. Dynamic changes in RNA structure are able to regulate the gene expression programme and can be used as a highly specific and subtle mechanism for governing cellular processes. However, the nature of most RNA secondary structures in Plasmodium falciparum has not been determined. To investigate the genome-wide RNA secondary structural features at single-nucleotide resolution in P. falciparum, we applied a novel high-throughput method utilizing the chemical modification of RNA structures to characterize these structures. Structural data from parasites are in close agreement with the known 18S ribosomal RNA secondary structures of P. falciparum and can help to predict the in vivo RNA secondary structure of a total of 3,396 transcripts in the ring-stage and trophozoite-stage developmental cycles. By parallel analysis of RNA structures in vivo and in vitro during the Plasmodium parasite ring-stage and trophozoite-stage intraerythrocytic developmental cycles, we identified some key regulatory features. Recent studies have established that the RNA structure is a ubiquitous and fundamental regulator of gene expression. Our study indicate that there is a critical connection between RNA secondary structure and mRNA abundance during the complex biological programme of P. falciparum. This work presents a useful framework and important results, which may facilitate further research investigating the interactions between RNA secondary structure and the complex biological programme in P. falciparum. The RNA secondary structure characterized in this study has potential applications and important implications regarding the identification of RNA structural elements, which are important for parasite infection and elucidating host-parasite interactions and parasites in the environment.

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Comparative analysis of coronavirus genomic RNA structure reveals conservation in SARS-like coronaviruses

10.1101/2020.06.15.153197 ◽

2020 ◽

Cited By ~ 10

Author(s):

Wes Sanders ◽

Ethan J. Fritch ◽

Emily A. Madden ◽

Rachel L. Graham ◽

Heather A. Vincent ◽

...

Keyword(s):

Secondary Structure ◽

Rna Structure ◽

Rna Secondary Structure ◽

Molecular Mechanisms ◽

Selective Pressure ◽

Secondary Structures ◽

Rna Structures ◽

Rna Secondary Structures ◽

The Past ◽

Novel Strategy

AbstractCoronaviruses, including SARS-CoV-2 the etiological agent of COVID-19 disease, have caused multiple epidemic and pandemic outbreaks in the past 20 years1–3. With no vaccines, and only recently developed antiviral therapeutics, we are ill equipped to handle coronavirus outbreaks4. A better understanding of the molecular mechanisms that regulate coronavirus replication and pathogenesis is needed to guide the development of new antiviral therapeutics and vaccines. RNA secondary structures play critical roles in multiple aspects of coronavirus replication, but the extent and conservation of RNA secondary structure across coronavirus genomes is unknown5. Here, we define highly structured RNA regions throughout the MERS-CoV, SARS-CoV, and SARS-CoV-2 genomes. We find that highly stable RNA structures are pervasive throughout coronavirus genomes, and are conserved between the SARS-like CoV. Our data suggests that selective pressure helps preserve RNA secondary structure in coronavirus genomes, suggesting that these structures may play important roles in virus replication and pathogenesis. Thus, disruption of conserved RNA secondary structures could be a novel strategy for the generation of attenuated SARS-CoV-2 vaccines for use against the current COVID-19 pandemic.

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Faculty Opinions recommendation of Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726936997.793529235 ◽

2017 ◽

Author(s):

Janusz Bujnicki

Keyword(s):

Statistical Modeling ◽

High Throughput ◽

Rna Structure ◽

Structure Probing

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