G-quadruplexes (G4s) are nucleic acid secondary structures with important regulatory functions. Single-nucleotide variants (SNVs), one of the most common forms of genetic variation, can potentially impact the formation of G4 structures if they occur within G4 regions. However, there is currently a lack of software tools specifically designed to assess such effects. Here, we present an R/Bioconductor package named G4SNVHunter, which enables rapid detection of variants that may disrupt G4 structures. This tool, based on the core principles of the G4Hunter algorithm, can provide precise quantitative assessment of the propensity for G4 formation within genomic sequences. Specialized experimental methods can then be designed based on the results provided by G4SNVHunter to further verify the specific functions of the affected G4 structures, facilitating deeper insights into the biological impacts of genetic variants from the perspective of G4 structures. To showcase the functionality of the G4SNVHunter package, we analyzed the Neandertal and Denisovan archaic introgressed variants detected by the Sprime software, and identified approximately 5,800 variants located within G4 regions, among which around 230 may impair G4 structure formation propensity. The source code for the G4SNVHunter package has been publicly released under the MIT license at https://github.com/rongxinzh/G4SNVHunter and https://bioconductor.org/packages/devel/bioc/html/G4SNVHunter.html.

MOTIVATION: G-quadruplexes (G4) are important regulatory non-B DNA structures with therapeutic potential. A tool for rational design of mutations leading to decreased propensity for G4 formation should be useful in studying G4 functions. Although tools exist for G4 prediction, no easily accessible tool for the rational design of G4 mutations has been available. RESULTS: We developed a web-based tool termed G4Killer that is based on the G4Hunter algorithm. This new tool is a platform-independent and user-friendly application to design mutations crippling G4 propensity in a parsimonious way (i.e., keeping the primary sequence as close as possible to the original one). The tool is integrated into our DNA analyzer server and allows for generating mutated DNA sequences having the desired lowered G4Hunter score with minimal mutation steps. AVAILABILITY AND IMPLEMENTATION: The G4Killer web tool can be accessed at: http://bioinformatics.ibp.cz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Expanding research highlights the importance of guanine quadruplex structures. Therefore, easy-accessible tools for quadruplex analyses in DNA and RNA molecules are important for the scientific community. RESULTS: We developed a web version of the G4Hunter application. This new web-based server is a platform-independent and user-friendly application for quadruplex analyses. It allows retrieval of gene/nucleotide sequence entries from NCBI databases and provides complete characterization of localization and quadruplex propensity of quadruplex-forming sequences. The G4Hunter web application includes an interactive graphical data representation with many useful options including visualization, sorting, data storage and export. AVAILABILITY AND IMPLEMENTATION: G4Hunter web application can be accessed at: http://bioinformatics.ibp.cz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: G-quadruplexes are stable four-stranded guanine-rich structures that can form in DNA and RNA. They are an important component of human telomeres and play a role in the regulation of transcription and translation. The biological significance of a G-quadruplex is crucially linked with its thermodynamic stability. Hence the prediction of G-quadruplex stability is of vital interest. RESULTS: In this article, we present a novel Bayesian prediction framework based on Gaussian process regression to determine the thermodynamic stability of previously unmeasured G-quadruplexes from the sequence information alone. We benchmark our approach on a large G-quadruplex dataset and compare our method to alternative approaches. Furthermore, we propose an active learning procedure which can be used to iteratively acquire data in an optimal fashion. Lastly, we demonstrate the usefulness of our procedure on a genome-wide study of quadruplexes in the human genome. AVAILABILITY: A data table with the training sequences is available as supplementary material. Source code is available online at http://www.inference.phy.cam.ac.uk/os252/projects/quadruplexes. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.