ArticleNucleic acids research2019
Genome-wide epistasis and co-selection study using mutual information.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Mapping the evolutionary path towards multi-drug resistance in the pandemicMicrobial genomics · 2026Article
- Epistasis and co-adaptation in bacterial genome evolution.Nature reviews. Genetics · 2026Review
- Genome co-adaptation and the evolution of methicillin resistant Staphylococcus aureus.Genome biology · 2026Article
- Within-host bacterial evolution and the emergence of pathogenicity.Nature microbiology · 2025Review
- Article
- Context matters: assessing the impacts of genomic background and ecology on microbial biosynthetic gene cluster evolution.mSystems · 2025Review
- Real-time identification of epistatic interactions in SARS-CoV-2 from large genome collections.Genome biology · 2024Article
- Pangenome-spanning epistasis and coselection analysis via de Bruijn graphs.Genome research · 2024Article
- Estimating between-country migration in pneumococcal populations.G3 (Bethesda, Md.) · 2024Article
- Detecting co-selection through excess linkage disequilibrium in bacterial genomes.NAR genomics and bioinformatics · 2024Article
- The emergence of highly resistant and hypervirulent Klebsiella pneumoniae CC14 clone in a tertiary hospital over 8 years.Genome medicine · 2024Article
- Accurate and fast graph-based pangenome annotation and clustering with ggCaller.Genome research · 2023Article
- Detecting patterns of accessory genome coevolution in Staphylococcus aureus using data from thousands of genomes.BMC bioinformatics · 2023Article
- Identification of potential pathogenic targets and survival strategies ofFrontiers in cellular and infection microbiology · 2023Article
- Beneath the surface: Amino acid variation underlying two decades of dengue virus antigenic dynamics in Bangkok, Thailand.PLoS pathogens · 2022Article
- Horizontal gene transfer and adaptive evolution in bacteria.Nature reviews. Microbiology · 2022Review
- Co-evolutionary Signals Identify Burkholderia pseudomallei Survival Strategies in a Hostile Environment.Molecular biology and evolution · 2022Article
- An Epistatic Network DescribesFrontiers in molecular biosciences · 2022Article
- Evidence for Selection in the Abundant Accessory Gene Content of a Prokaryote Pangenome.Molecular biology and evolution · 2021Article
- Negative frequency-dependent selection and asymmetrical transformation stabilise multi-strain bacterial population structures.The ISME journal · 2021Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which adjusts for the phylogenetic signal in the data without requiring an explicit phylogenetic tree. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Simulations demonstrate the usefulness of our method and give some insight to when this type of analysis is most likely to be successful. Application of the method to large population genomic datasets of two major human pathogens, Streptococcus pneumoniae and Neisseria meningitidis, revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.