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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

MOHCA-seq data analysis.(A) Raw counts for a single P4–P6 MOHCA-seq data set. Following paired-end sequencing, the MAPseeker software is used to align the reads to the sequence of the RNA that was probed. (B) Closure-based •OH COrrelation Analysis (COHCOA) after 40 iterations on P4–P6 data set. (C) Final analyzed P4–P6 proximity map. A filter is applied to remove points with signal-to-noise ratio < 1, a 2D smoothing algorithm aids visualization of the strongest features, and the data are scaled using the mean of the data. A full description of the analysis is given in the ‘Materials and methods’.DOI:http://dx.doi.org/10.7554/eLife.07600.004
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fig1s1: MOHCA-seq data analysis.(A) Raw counts for a single P4–P6 MOHCA-seq data set. Following paired-end sequencing, the MAPseeker software is used to align the reads to the sequence of the RNA that was probed. (B) Closure-based •OH COrrelation Analysis (COHCOA) after 40 iterations on P4–P6 data set. (C) Final analyzed P4–P6 proximity map. A filter is applied to remove points with signal-to-noise ratio < 1, a 2D smoothing algorithm aids visualization of the strongest features, and the data are scaled using the mean of the data. A full description of the analysis is given in the ‘Materials and methods’.DOI:http://dx.doi.org/10.7554/eLife.07600.004

Mentions: (A) Schematic of mutate-and-map (M2) workflow, showing transcription of comprehensive point mutant library and chemical mapping of library with reverse transcription readout (Kladwang et al., 2011a). (B) Schematic of Multiplexed •OH (hydroxyl radical) Cleavage Analysis (MOHCA)-seq workflow, showing random incorporation of radical sources, fragmentation, adapter ligations, and analysis by sequencing. (C) M2 data set for P4–P6 domain of Tetrahymena group I ribozyme. (D) MOHCA-seq data set (proximity map) for P4–P6. In (C) and (D), rounded rectangles indicate helix elements with colors matching helices in (E–F), purple circles indicate hits corresponding to < 30 Å pairwise distance in the crystal structure, and pink circles indicate hits corresponding to > 30 Å pairwise distance in the crystal structure. In (D), magenta arrows indicate MOHCA-seq hits due to diffusion across the major (top arrow) or minor (bottom arrow) grooves from radical sources located in P5b. (E–F) Representation of MOHCA-seq tertiary proximities on M2-guided secondary structure (E) and on final single Rosetta model (F). Purple lines indicate MOHCA-seq hits corresponding to < 30 Å pairwise distance in the crystal structure. Figure 1—figure supplement 1 shows stages of MOHCA-seq data analysis in the MAPseeker software package (accessible through the RNA Mapping Database server at http://rmdb.stanford.edu/tools/). Figure 1—figure supplement 2 shows the pseudo-energy potential used for pairwise MOHCA-seq constraints in Rosetta modeling and plots of MOHCA-seq signal vs pairwise distance.


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)

MOHCA-seq data analysis.(A) Raw counts for a single P4–P6 MOHCA-seq data set. Following paired-end sequencing, the MAPseeker software is used to align the reads to the sequence of the RNA that was probed. (B) Closure-based •OH COrrelation Analysis (COHCOA) after 40 iterations on P4–P6 data set. (C) Final analyzed P4–P6 proximity map. A filter is applied to remove points with signal-to-noise ratio < 1, a 2D smoothing algorithm aids visualization of the strongest features, and the data are scaled using the mean of the data. A full description of the analysis is given in the ‘Materials and methods’.DOI:http://dx.doi.org/10.7554/eLife.07600.004
© Copyright Policy
Related In: Results  -  Collection

License
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getmorefigures.php?uid=PMC4495719&req=5

fig1s1: MOHCA-seq data analysis.(A) Raw counts for a single P4–P6 MOHCA-seq data set. Following paired-end sequencing, the MAPseeker software is used to align the reads to the sequence of the RNA that was probed. (B) Closure-based •OH COrrelation Analysis (COHCOA) after 40 iterations on P4–P6 data set. (C) Final analyzed P4–P6 proximity map. A filter is applied to remove points with signal-to-noise ratio < 1, a 2D smoothing algorithm aids visualization of the strongest features, and the data are scaled using the mean of the data. A full description of the analysis is given in the ‘Materials and methods’.DOI:http://dx.doi.org/10.7554/eLife.07600.004
Mentions: (A) Schematic of mutate-and-map (M2) workflow, showing transcription of comprehensive point mutant library and chemical mapping of library with reverse transcription readout (Kladwang et al., 2011a). (B) Schematic of Multiplexed •OH (hydroxyl radical) Cleavage Analysis (MOHCA)-seq workflow, showing random incorporation of radical sources, fragmentation, adapter ligations, and analysis by sequencing. (C) M2 data set for P4–P6 domain of Tetrahymena group I ribozyme. (D) MOHCA-seq data set (proximity map) for P4–P6. In (C) and (D), rounded rectangles indicate helix elements with colors matching helices in (E–F), purple circles indicate hits corresponding to < 30 Å pairwise distance in the crystal structure, and pink circles indicate hits corresponding to > 30 Å pairwise distance in the crystal structure. In (D), magenta arrows indicate MOHCA-seq hits due to diffusion across the major (top arrow) or minor (bottom arrow) grooves from radical sources located in P5b. (E–F) Representation of MOHCA-seq tertiary proximities on M2-guided secondary structure (E) and on final single Rosetta model (F). Purple lines indicate MOHCA-seq hits corresponding to < 30 Å pairwise distance in the crystal structure. Figure 1—figure supplement 1 shows stages of MOHCA-seq data analysis in the MAPseeker software package (accessible through the RNA Mapping Database server at http://rmdb.stanford.edu/tools/). Figure 1—figure supplement 2 shows the pseudo-energy potential used for pairwise MOHCA-seq constraints in Rosetta modeling and plots of MOHCA-seq signal vs pairwise distance.

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