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Consistent global structures of complex RNA states through multidimensional chemical mapping.

Cheng CY, Chou FC, Kladwang W, Tian S, Cordero P, Das R - Elife (2015)

Bottom Line: Accelerating discoveries of non-coding RNA (ncRNA) in myriad biological processes pose major challenges to structural and functional analysis.Despite progress in secondary structure modeling, high-throughput methods have generally failed to determine ncRNA tertiary structures, even at the 1-nm resolution that enables visualization of how helices and functional motifs are positioned in three dimensions.This multidimensional chemical mapping (MCM) pipeline resolves unexpected tertiary proximities for cyclic-di-GMP, glycine, and adenosylcobalamin riboswitch aptamers without their ligands and a loose structure for the recently discovered human HoxA9D internal ribosome entry site regulon.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, Stanford University, Stanford, United States.

ABSTRACT
Accelerating discoveries of non-coding RNA (ncRNA) in myriad biological processes pose major challenges to structural and functional analysis. Despite progress in secondary structure modeling, high-throughput methods have generally failed to determine ncRNA tertiary structures, even at the 1-nm resolution that enables visualization of how helices and functional motifs are positioned in three dimensions. We report that integrating a new method called MOHCA-seq (Multiplexed •OH Cleavage Analysis with paired-end sequencing) with mutate-and-map secondary structure inference guides Rosetta 3D modeling to consistent 1-nm accuracy for intricately folded ncRNAs with lengths up to 188 nucleotides, including a blind RNA-puzzle challenge, the lariat-capping ribozyme. This multidimensional chemical mapping (MCM) pipeline resolves unexpected tertiary proximities for cyclic-di-GMP, glycine, and adenosylcobalamin riboswitch aptamers without their ligands and a loose structure for the recently discovered human HoxA9D internal ribosome entry site regulon. MCM offers a sequencing-based route to uncovering ncRNA 3D structure, applicable to functionally important but potentially heterogeneous states.

No MeSH data available.


Related in: MedlinePlus

Blind models generated for RNA-puzzles can attain 1-nm resolution or better but cannot predict the most accurate models.(A) M2-derived secondary structure of S. thermophilus adenosylcobalamin riboswitch aptamer, generated for the RNA-puzzle 6 challenge (Miao et al., 2015). Bootstrap support values for each helix are shown as percentages. Crystallographic Watson–Crick base pairs missing in the secondary structure are connected by yellow lines, and non-crystallographic Watson–Crick base pairs predicted in the secondary structure are connected by blue lines. (B–G) Blind 3D models of the S. thermophilus adenosylcobalamin riboswitch aptamer generated for the RNA-puzzle 6 challenge. Models were generated using (B) M2/Rosetta, 12.1 Å all-heavy-atom RMSD to crystal; (C) M2/Rosetta, 17.1 Å RMSD; (D) Vfold, 22.1 Å RMSD; (E) MC-Fold and MC-Sym, 23.4 Å RMSD; (F) DMD, 24.0 Å RMSD; (G) M2/Rosetta, 32.8 Å RMSD. Modeling methods were previously described in detail (Miao et al., 2015). For each modeling method, the most accurate submitted model to the crystal structure is shown (B, D–F). The ranks predicted by the modelers of their own submissions (‘submission rank’) are given below each model. (H) Crystal structure of the S. thermophilus adenosylcobalamin riboswitch aptamer (PDB ID 4GXY).DOI:http://dx.doi.org/10.7554/eLife.07600.013
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fig3s4: Blind models generated for RNA-puzzles can attain 1-nm resolution or better but cannot predict the most accurate models.(A) M2-derived secondary structure of S. thermophilus adenosylcobalamin riboswitch aptamer, generated for the RNA-puzzle 6 challenge (Miao et al., 2015). Bootstrap support values for each helix are shown as percentages. Crystallographic Watson–Crick base pairs missing in the secondary structure are connected by yellow lines, and non-crystallographic Watson–Crick base pairs predicted in the secondary structure are connected by blue lines. (B–G) Blind 3D models of the S. thermophilus adenosylcobalamin riboswitch aptamer generated for the RNA-puzzle 6 challenge. Models were generated using (B) M2/Rosetta, 12.1 Å all-heavy-atom RMSD to crystal; (C) M2/Rosetta, 17.1 Å RMSD; (D) Vfold, 22.1 Å RMSD; (E) MC-Fold and MC-Sym, 23.4 Å RMSD; (F) DMD, 24.0 Å RMSD; (G) M2/Rosetta, 32.8 Å RMSD. Modeling methods were previously described in detail (Miao et al., 2015). For each modeling method, the most accurate submitted model to the crystal structure is shown (B, D–F). The ranks predicted by the modelers of their own submissions (‘submission rank’) are given below each model. (H) Crystal structure of the S. thermophilus adenosylcobalamin riboswitch aptamer (PDB ID 4GXY).DOI:http://dx.doi.org/10.7554/eLife.07600.013

Mentions: (A) P4–P6 domain: M2/Rosetta model (left), 38.3 Å root-mean-squared-deviation (RMSD); crystal structure (PDB ID 1GID, center left); M2/MOHCA-seq/Rosetta (MCM) model (center right), 8.6 Å RMSD. (B) V. cholerae cyclic-di-GMP riboswitch aptamer: M2/Rosetta model (left), 11.3 Å RMSD; crystal structure (PDB ID 3IRW, center left); MCM model (center right), 7.6 Å RMSD. (C) F. nucleatum double glycine riboswitch ligand-binding domain: M2/Rosetta model (left), 30.5 Å RMSD; crystal structure (PDB ID 3P49, center left); MCM model (center right), 7.9 Å RMSD. (D) S. thermophilum adenosylcobalamin (AdoCbl) riboswitch aptamer: M2/Rosetta submission rank 1 of 10 for RNA-puzzle 6 (left), 17.1 Å RMSD; crystal structure (PDB ID 4GXY, center left); MCM model (center right), 11.9 Å RMSD. (E) Class I ligase: M2/Rosetta model (left), 26.3 Å global RMSD, and 14.0 Å core RMSD; crystal structure (PDB ID 3HHN, center left); MCM model (center right), 14.5 Å global RMSD and 11.1 Å core RMSD. (F) D. iridis lariat-capping ribozyme: M2/Rosetta submission rank 1 of 2 for RNA-puzzle 5 (left), 17.0 Å P2.1/P4–P6 RMSD and 9.6 Å global RMSD; crystal structure (PDB ID 4P8Z, center left); MCM model (center right), 11.2 Å P2.1/P4–P6 RMSD and 8.2 Å global RMSD. In (A–F), MOHCA-seq proximity maps with annotated helix elements (rounded rectangles) and tertiary hits (purple and pink circles) as in Figure 1D are shown at right. Full-size proximity maps, including 5′- and 3′-flanking sequences outside the region of interest, are shown in Figure 3—figure supplement 3. M2 analyses of AdoCbl riboswitch aptamer, class I ligase, and lariat-capping ribozyme are shown in Figure 3—figure supplements 1, 2, 7. Figure 3—figure supplement 4 shows comparisons of models generated by different computational methods for RNA-puzzle 6. Figure 3—figure supplements 5, 6 show comparisons of additional modeling runs for class I ligase and AdoCbl riboswitch aptamer to crystal structures.


Consistent global structures of complex RNA states through multidimensional chemical mapping.

Cheng CY, Chou FC, Kladwang W, Tian S, Cordero P, Das R - Elife (2015)

Blind models generated for RNA-puzzles can attain 1-nm resolution or better but cannot predict the most accurate models.(A) M2-derived secondary structure of S. thermophilus adenosylcobalamin riboswitch aptamer, generated for the RNA-puzzle 6 challenge (Miao et al., 2015). Bootstrap support values for each helix are shown as percentages. Crystallographic Watson–Crick base pairs missing in the secondary structure are connected by yellow lines, and non-crystallographic Watson–Crick base pairs predicted in the secondary structure are connected by blue lines. (B–G) Blind 3D models of the S. thermophilus adenosylcobalamin riboswitch aptamer generated for the RNA-puzzle 6 challenge. Models were generated using (B) M2/Rosetta, 12.1 Å all-heavy-atom RMSD to crystal; (C) M2/Rosetta, 17.1 Å RMSD; (D) Vfold, 22.1 Å RMSD; (E) MC-Fold and MC-Sym, 23.4 Å RMSD; (F) DMD, 24.0 Å RMSD; (G) M2/Rosetta, 32.8 Å RMSD. Modeling methods were previously described in detail (Miao et al., 2015). For each modeling method, the most accurate submitted model to the crystal structure is shown (B, D–F). The ranks predicted by the modelers of their own submissions (‘submission rank’) are given below each model. (H) Crystal structure of the S. thermophilus adenosylcobalamin riboswitch aptamer (PDB ID 4GXY).DOI:http://dx.doi.org/10.7554/eLife.07600.013
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fig3s4: Blind models generated for RNA-puzzles can attain 1-nm resolution or better but cannot predict the most accurate models.(A) M2-derived secondary structure of S. thermophilus adenosylcobalamin riboswitch aptamer, generated for the RNA-puzzle 6 challenge (Miao et al., 2015). Bootstrap support values for each helix are shown as percentages. Crystallographic Watson–Crick base pairs missing in the secondary structure are connected by yellow lines, and non-crystallographic Watson–Crick base pairs predicted in the secondary structure are connected by blue lines. (B–G) Blind 3D models of the S. thermophilus adenosylcobalamin riboswitch aptamer generated for the RNA-puzzle 6 challenge. Models were generated using (B) M2/Rosetta, 12.1 Å all-heavy-atom RMSD to crystal; (C) M2/Rosetta, 17.1 Å RMSD; (D) Vfold, 22.1 Å RMSD; (E) MC-Fold and MC-Sym, 23.4 Å RMSD; (F) DMD, 24.0 Å RMSD; (G) M2/Rosetta, 32.8 Å RMSD. Modeling methods were previously described in detail (Miao et al., 2015). For each modeling method, the most accurate submitted model to the crystal structure is shown (B, D–F). The ranks predicted by the modelers of their own submissions (‘submission rank’) are given below each model. (H) Crystal structure of the S. thermophilus adenosylcobalamin riboswitch aptamer (PDB ID 4GXY).DOI:http://dx.doi.org/10.7554/eLife.07600.013
Mentions: (A) P4–P6 domain: M2/Rosetta model (left), 38.3 Å root-mean-squared-deviation (RMSD); crystal structure (PDB ID 1GID, center left); M2/MOHCA-seq/Rosetta (MCM) model (center right), 8.6 Å RMSD. (B) V. cholerae cyclic-di-GMP riboswitch aptamer: M2/Rosetta model (left), 11.3 Å RMSD; crystal structure (PDB ID 3IRW, center left); MCM model (center right), 7.6 Å RMSD. (C) F. nucleatum double glycine riboswitch ligand-binding domain: M2/Rosetta model (left), 30.5 Å RMSD; crystal structure (PDB ID 3P49, center left); MCM model (center right), 7.9 Å RMSD. (D) S. thermophilum adenosylcobalamin (AdoCbl) riboswitch aptamer: M2/Rosetta submission rank 1 of 10 for RNA-puzzle 6 (left), 17.1 Å RMSD; crystal structure (PDB ID 4GXY, center left); MCM model (center right), 11.9 Å RMSD. (E) Class I ligase: M2/Rosetta model (left), 26.3 Å global RMSD, and 14.0 Å core RMSD; crystal structure (PDB ID 3HHN, center left); MCM model (center right), 14.5 Å global RMSD and 11.1 Å core RMSD. (F) D. iridis lariat-capping ribozyme: M2/Rosetta submission rank 1 of 2 for RNA-puzzle 5 (left), 17.0 Å P2.1/P4–P6 RMSD and 9.6 Å global RMSD; crystal structure (PDB ID 4P8Z, center left); MCM model (center right), 11.2 Å P2.1/P4–P6 RMSD and 8.2 Å global RMSD. In (A–F), MOHCA-seq proximity maps with annotated helix elements (rounded rectangles) and tertiary hits (purple and pink circles) as in Figure 1D are shown at right. Full-size proximity maps, including 5′- and 3′-flanking sequences outside the region of interest, are shown in Figure 3—figure supplement 3. M2 analyses of AdoCbl riboswitch aptamer, class I ligase, and lariat-capping ribozyme are shown in Figure 3—figure supplements 1, 2, 7. Figure 3—figure supplement 4 shows comparisons of models generated by different computational methods for RNA-puzzle 6. Figure 3—figure supplements 5, 6 show comparisons of additional modeling runs for class I ligase and AdoCbl riboswitch aptamer to crystal structures.

Bottom Line: Accelerating discoveries of non-coding RNA (ncRNA) in myriad biological processes pose major challenges to structural and functional analysis.Despite progress in secondary structure modeling, high-throughput methods have generally failed to determine ncRNA tertiary structures, even at the 1-nm resolution that enables visualization of how helices and functional motifs are positioned in three dimensions.This multidimensional chemical mapping (MCM) pipeline resolves unexpected tertiary proximities for cyclic-di-GMP, glycine, and adenosylcobalamin riboswitch aptamers without their ligands and a loose structure for the recently discovered human HoxA9D internal ribosome entry site regulon.

View Article: PubMed Central - PubMed

Affiliation: Department of Biochemistry, Stanford University, Stanford, United States.

ABSTRACT
Accelerating discoveries of non-coding RNA (ncRNA) in myriad biological processes pose major challenges to structural and functional analysis. Despite progress in secondary structure modeling, high-throughput methods have generally failed to determine ncRNA tertiary structures, even at the 1-nm resolution that enables visualization of how helices and functional motifs are positioned in three dimensions. We report that integrating a new method called MOHCA-seq (Multiplexed •OH Cleavage Analysis with paired-end sequencing) with mutate-and-map secondary structure inference guides Rosetta 3D modeling to consistent 1-nm accuracy for intricately folded ncRNAs with lengths up to 188 nucleotides, including a blind RNA-puzzle challenge, the lariat-capping ribozyme. This multidimensional chemical mapping (MCM) pipeline resolves unexpected tertiary proximities for cyclic-di-GMP, glycine, and adenosylcobalamin riboswitch aptamers without their ligands and a loose structure for the recently discovered human HoxA9D internal ribosome entry site regulon. MCM offers a sequencing-based route to uncovering ncRNA 3D structure, applicable to functionally important but potentially heterogeneous states.

No MeSH data available.


Related in: MedlinePlus