Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta

Summary: Foldit Standalone is an interactive graphical interface to the Rosetta molecular modeling package. In contrast to most command-line or batch interactions with Rosetta, Foldit Standalone is designed to allow easy, real-time, direct manipulation of protein structures, while also giving access to the extensive power of Rosetta computations. Derived from the user interface of the scientific discovery game Foldit (itself based on Rosetta), Foldit Standalone has added more advanced features and removed the competitive game elements. Foldit Standalone was built from the ground up with a custom rendering and event engine, configurable visualizations and interactions driven by Rosetta. Foldit Standalone contains, among other features: electron density and contact map visualizations, multiple sequence alignment tools for template-based modeling, rigid body transformation controls, RosettaScripts support and an embedded Lua interpreter

TILLING to detect induced mutations in soybean

<p>Abstract</p> <p>Background</p> <p>Soybean (<it>Glycine max </it>L. Merr.) is an important nitrogen-fixing crop that provides much of the world's protein and oil. However, the available tools for investigation of soybean gene function are limited. Nevertheless, chemical mutagenesis can be applied to soybean followed by screening for mutations in a target of interest using a strategy known as Targeting Induced Local Lesions IN Genomes (TILLING). We have applied TILLING to four mutagenized soybean populations, three of which were treated with ethyl methanesulfonate (EMS) and one with N-nitroso-N-methylurea (NMU).</p> <p>Results</p> <p>We screened seven targets in each population and discovered a total of 116 induced mutations. The NMU-treated population and one EMS mutagenized population had similar mutation density (~1/140 kb), while another EMS population had a mutation density of ~1/250 kb. The remaining population had a mutation density of ~1/550 kb. Because of soybean's polyploid history, PCR amplification of multiple targets could impede mutation discovery. Indeed, one set of primers tested in this study amplified more than a single target and produced low quality data. To address this problem, we removed an extraneous target by pretreating genomic DNA with a restriction enzyme. Digestion of the template eliminated amplification of the extraneous target and allowed the identification of four additional mutant alleles compared to untreated template.</p> <p>Conclusion</p> <p>The development of four independent populations with considerable mutation density, together with an additional method for screening closely related targets, indicates that soybean is a suitable organism for high-throughput mutation discovery even with its extensively duplicated genome.</p

Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta

SummaryFoldit Standalone is an interactive graphical interface to the Rosetta molecular modeling package. In contrast to most command-line or batch interactions with Rosetta, Foldit Standalone is designed to allow easy, real-time, direct manipulation of protein structures, while also giving access to the extensive power of Rosetta computations. Derived from the user interface of the scientific discovery game Foldit (itself based on Rosetta), Foldit Standalone has added more advanced features and removed the competitive game elements. Foldit Standalone was built from the ground up with a custom rendering and event engine, configurable visualizations and interactions driven by Rosetta. Foldit Standalone contains, among other features: electron density and contact map visualizations, multiple sequence alignment tools for template-based modeling, rigid body transformation controls, RosettaScripts support and an embedded Lua interpreter.Availability and implementationFoldit Standalone is available for download at https://fold.it/standalone , under the Rosetta license, which is free for academic and non-profit users. It is implemented in cross-platform C ++ and binary executables are available for Windows, macOS and [email protected]

TILLING to detect induced mutations in soybean.

BackgroundSoybean (Glycine max L. Merr.) is an important nitrogen-fixing crop that provides much of the world's protein and oil. However, the available tools for investigation of soybean gene function are limited. Nevertheless, chemical mutagenesis can be applied to soybean followed by screening for mutations in a target of interest using a strategy known as Targeting Induced Local Lesions IN Genomes (TILLING). We have applied TILLING to four mutagenized soybean populations, three of which were treated with ethyl methanesulfonate (EMS) and one with N-nitroso-N-methylurea (NMU).ResultsWe screened seven targets in each population and discovered a total of 116 induced mutations. The NMU-treated population and one EMS mutagenized population had similar mutation density (approximately 1/140 kb), while another EMS population had a mutation density of approximately 1/250 kb. The remaining population had a mutation density of approximately 1/550 kb. Because of soybean's polyploid history, PCR amplification of multiple targets could impede mutation discovery. Indeed, one set of primers tested in this study amplified more than a single target and produced low quality data. To address this problem, we removed an extraneous target by pretreating genomic DNA with a restriction enzyme. Digestion of the template eliminated amplification of the extraneous target and allowed the identification of four additional mutant alleles compared to untreated template.ConclusionThe development of four independent populations with considerable mutation density, together with an additional method for screening closely related targets, indicates that soybean is a suitable organism for high-throughput mutation discovery even with its extensively duplicated genome