ArticlePLoS computational biology2020
Scalable phylogenetic profiling using MinHash uncovers likely eukaryotic sexual reproduction genes.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- ProteomeLM: A proteome-scale language model enables accurate and rapid prediction of protein-protein interactions and gene essentiality across taxa.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Hash functions in nucleotide sequence analysis.Genome research · 2026Review
- Profylo: A Python Package for Phylogenetic Profile Comparison and Analysis.Journal of molecular evolution · 2025Article
- CORGIAS: identifying correlated gene pairs by considering evolutionary history in a large-scale prokaryotic genome dataset.NAR genomics and bioinformatics · 2025Article
- Reconstructing Evolutionary Histories with Hierarchical Orthologous Groups.Journal of molecular evolution · 2025Review
- Correlated Gene Copy Number Changes in a Seminal Fluid Protein Network inbioRxiv : the preprint server for biology · 2025Article
- Predicting Protein Function in the AI and Big Data Era.Biochemistry · 2025Review
- EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals.Nature communications · 2025Article
- The Community Coevolution Model with Application to the Study of Evolutionary Relationships between Genes Based on Phylogenetic Profiles.Systematic biology · 2023Article
- Phylogenetic profiling in eukaryotes comes of age.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Identification of hidden associations among eukaryotic genes through statistical analysis of coevolutionary transitions.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Defining hierarchical protein interaction networks from spectral analysis of bacterial proteomes.eLife · 2022Article
- Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences.PLoS computational biology · 2022Article
- Inverse Potts model improves accuracy of phylogenetic profiling.Bioinformatics (Oxford, England) · 2022Article
- Article
- Ten Years of Collaborative Progress in the Quest for Orthologs.Molecular biology and evolution · 2021Article
- Public good exploitation in natural bacterioplankton communities.Science advances · 2021Article
- Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes.Briefings in bioinformatics · 2021Article
- OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more.Nucleic acids research · 2021Article
- Mirage: estimation of ancestral gene-copy numbers by considering different evolutionary patterns among gene families.Bioinformatics advances · 2021Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Phylogenetic profiling is a computational method to predict genes involved in the same biological process by identifying protein families which tend to be jointly lost or retained across the tree of life. Phylogenetic profiling has customarily been more widely used with prokaryotes than eukaryotes, because the method is thought to require many diverse genomes. There are now many eukaryotic genomes available, but these are considerably larger, and typical phylogenetic profiling methods require at least quadratic time as a function of the number of genes. We introduce a fast, scalable phylogenetic profiling approach entitled HogProf, which leverages hierarchical orthologous groups for the construction of large profiles and locality-sensitive hashing for efficient retrieval of similar profiles. We show that the approach outperforms Enhanced Phylogenetic Tree, a phylogeny-based method, and use the tool to reconstruct networks and query for interactors of the kinetochore complex as well as conserved proteins involved in sexual reproduction: Hap2, Spo11 and Gex1. HogProf enables large-scale phylogenetic profiling across the three domains of life, and will be useful to predict biological pathways among the hundreds of thousands of eukaryotic species that will become available in the coming few years. HogProf is available at https://github.com/DessimozLab/HogProf.
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