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Data from: Correction of preferred-orientation induced distortion in cryo-electron microscopy maps

Cite this dataset

Cao, Weili; Zhu, Dongjie; Zhang, Xinzheng (2024). Data from: Correction of preferred-orientation induced distortion in cryo-electron microscopy maps [Dataset]. Dryad. https://doi.org/10.5061/dryad.73n5tb354

Abstract

Reconstruction maps of cryo-electron microscopy (cryo-EM) exhibit distortion when the cryo-EM dataset is incomplete, usually caused by unevenly distributed orientations. Prior efforts had been attempted to address this preferred orientation problem using tilt-collection strategy, modifications to grids or to air-water-interfaces. However, these approaches often require time-consuming experiments and the effect was always protein dependent. Here, we developed a procedure containing removing mis-aligned particles and an iterative reconstruction method based on signal-to-noise ratio of Fourier component to correct such distortion by recovering missing data using a purely computational algorithm. This procedure called Signal-to-Noise Ratio Iterative Reconstruction Method (SIRM) was applied on incomplete datasets of various proteins to fix distortion in cryo-EM maps and to a more isotropic resolution. In addition, SIRM provides a better reference map for further reconstruction refinements, resulting in an improved alignment, which ultimately improves map quality and benefits model building.

README: SIRM: Open Source Data


We have submitted the original chart files (.csv) and density maps (.mrc) related to the images in the article "Correction of preferred-orientation induced distortion in cryo-electron microscopy maps"

Descriptions

SIRM_Fig1_csv.rar

  • Fig1A.csv: The CSV file corresponding to the histogram of Euler angle deviations in particle sets with different degrees of missing wedge under conventional refinement.
  • Fig1B.csv: The CSV file corresponding to the histogram of Euler angle deviations in particle sets with different degrees of missing wedge After Cross-Validation process.

SIRM_Fig3_MRC_map.rar

  • groundTruth.mrc: The ground-truth density map of Apo-ferritin without missing cone, corresponding to Fig.3A.
  • loss70_sameParticleNum.mrc: The MC-35 density map of Apo-ferritin, corresponding to Fig.3D.
  • loss70_sameParticleNum_SIRM.mrc: The MC-35 density map of Apo-ferritin after SIRM processing, corresponding to Fig.3G.
  • loss80_sameParticleNum.mrc: The MC-40 density map of Apo-ferritin, corresponding to Fig.3E.
  • loss80_sameParticleNum_SIRM.mrc: The MC-40 density map of Apo-ferritin after SIRM processing, corresponding to Fig.3H.
  • loss90_sameParticleNum.mrc: The MC-45 density map of Apo-ferritin, corresponding to Fig.3F.
  • loss90_sameParticleNum_SIRM.mrc: The MC-45 density map of Apo-ferritin after SIRM processing, corresponding to Fig.3I.

SIRM_Fig4_MRC_map.rar

  • groundTruth.mrc: The ground-truth density map of EMPIAR-10097 HA-trimer without missing cone, corresponding to Fig.4A.
  • loss70_sameParticleNum_bf50.mrc: The MC-35 density map of EMPIAR-10097 HA-trimer, corresponding to Fig.4D.
  • loss70_SIRM_hist10_bf50.mrc: The MC-35 density map of EMPIAR-10097 HA-trimer after SIRM processing, corresponding to Fig.4G.
  • loss80_sameParticleNum_bf50.mrc: The MC-35 density map of EMPIAR-10097 HA-trimer, corresponding to Fig.4E.
  • loss80_SIRM_hist10_bf50.mrc: The MC-35 density map of EMPIAR-10097 HA-trimer after SIRM processing, corresponding to Fig.4H.
  • loss90_sameParticleNum_bf50.mrc: The MC-35 density map of EMPIAR-10097 HA-trimer, corresponding to Fig.4F.
  • loss90_SIRM_hist10_bf50.mrc: The MC-35 density map of EMPIAR-10097 HA-trimer after SIRM processing, corresponding to Fig.4I.

SIRM_Fig6&&FigS8&&FigS9__csv&MRC.rar

  • Fig6A.csv: The CSV file corresponding to the Fig.6A, The histogram compares the Euler angle errors between conventional refinement and SIRM refinement, as well as between cross-validation and mask-picking.
  • Fig6B.csv: The CSV file corresponding to the Fig.6B. Note that this CSV file contains several columns, which represent multiple directional FSCs.
  • FigS8A.csv: The CSV file corresponding to the FigS.8A. This histogram shows the directional-FSC of ribosomes after SIRM processing.
  • FigS8B.csv: The CSV file corresponding to the FigS.8A. This histogram shows the directional-FSC of ribosomes without SIRM processing.
  • FigS8E.csv: The CSV file corresponding to the Fig.S8E. Note that this CSV file contains several columns, which represent multiple directional FSCs.
  • ribosome_MC50.mrc: The MC-45 density map of ribosome with alignment-error, corresponding to Fig.6C.
  • ribosome_SIRM.mrc: The MC-45 density map of ribosome with alignment-error after SIRM processing, corresponding to Fig.6D.

SIRM_Fig7&&FigS12_csv.rar

  • FigS12C.csv FigS12D.csv FigS12E.csv FigS12F.csv: The CSV file corresponding to FigS12C FigS12D FigS12E FigS12F.

SIRM_FigS5_csv.rar

  • FigS5A.csv FigS5C.csv FigS5E.csv FigS5G.csv FigS5I.csv FigS5K.csv: The 3D-FSC CSV file corresponding to FigS5A FigS5C FigS5E FigS5G FigS5I FigS5K. Note that this CSV file contains several columns, which represent multiple directional FSCs
  • FigS5B.csv FigS5D.csv FigS5F.csv FigS5H.csv FigS5J.csv FigS5L.csv: The D-FSC CSV file corresponding to FigS5A FigS5C FigS5E FigS5G FigS5I FigS5K.

SIRM_FigS6_csv.rar

  • FigS6A.csv FigS6C.csv FigS6E.csv FigS6G.csv FigS6I.csv FigS6K.csv: The 3D-FSC CSV file corresponding to FigS6A FigS6C FigS6E FigS6G FigS6I FigS6K. Note that this CSV file contains several columns, which represent multiple directional FSCs
  • FigS6B.csv FigS6D.csv FigS6F.csv FigS6H.csv FigS6J.csv FigS6L.csv: The D-FSC CSV file corresponding to FigS6A FigS6C FigS6E FigS6G FigS6I FigS6K.

SIRM_FigS10&&FigS11_csv.rar

  • FigS11A.csv FigS11B.csv FigS11C.csv FigS11D.csv: The CSV file corresponding to FigS11A FigS11B FigS11C FigS11D. They demonstrated the results before and after the density SIRM-restoration of HA-trimer with an MC-40 missing wedge (with alignment errors).
  • FigS11G.csv FigS11H.csv FigS11I.csv FigS11J.csv: The CSV file corresponding to FigS11A FigS11B FigS11C FigS11D. They demonstrated the results before and after the density SIRM-restoration of PS-I complex with an MC-40 missing wedge (with alignment errors).
  • FigS11E.csv FigS11F.csv: The CSV file corresponding to FigS11E FigS11F. They demonstrated the recovery capability of our method for Euler angle errors.

SIRM_FigS13_csv.rar

  • FigS13A.csv FigS13B.csv FigS13C.csv FigS13D.csv FigS13E.csv FigS13F.csv: The 3D-FSC CSV file corresponding to FigS13A FigS13B FigS13C FigS13D FigS13E FigS13F. They demonstrated that the recovery effectiveness of SIRM decreases as the signal-to-noise ratio (number of particles) decrease.

Key Information Sources

SIRM\3D-FSC&Directional-FSC

SIRM\Figures

  • The figures are sourced from UCSF Chimera and ChimeraX

SIRM\Softwares

Code/Software

SIRM\Softwares

Funding

National Natural Science Foundation of China