New tools for automated high-resolution cryo-EM structure determination in RELION-3.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 30412051.
- Also identified by DOI 10.7554/eLife.42166 and PMC identifier 6250425.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Here, we describe the third major release of RELION. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, <i>de novo</i> model generation and 3D-classification. Per-particle refinement of CTF parameters and correction of estimated beam tilt provides higher resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not been optimal. Ewald sphere curvature correction improves resolution for large particles. We illustrate these developments with publicly available data sets: together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 0.2-0.7 Å compared to previous RELION versions.
Medical subject headings
- Automation, Laboratory
- Cryoelectron Microscopy
- Image Processing, Computer-Assisted