Evidence map›Paper›PMID 41039586›Full record

ArticleAlgorithms for molecular biology : AMB2025

Orthology and near-cographs in the context of phylogenetic networks.

Anna Lindeberg, Guillaume E Scholz, Nicolas Wieseke, Marc Hellmuth

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Article in Algorithms for molecular biology : AMB, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Anna LindebergDepartment of Mathematics, Stockholm University, Albanovägen 28, 10691, Stockholm, Sweden.
Guillaume E ScholzDepartment of Computer Science & Interdisciplinary Center for Bioinformatics, Universität Leipzig, Härtelstraße 16-18, 04107, Leipzig, Germany.
Nicolas WiesekeDepartment of Computer Science, Universität Leipzig, Augustusplatz 10, 04109, Leipzig, Germany.
Marc HellmuthDepartment of Mathematics, Stockholm University, Albanovägen 28, 10691, Stockholm, Sweden. marc.hellmuth@math.su.se.

Funding

Deutsche Forschungsgemeinschaft MI439/14-2
6 · The paper itself

Abstract

Orthologous genes, which arise through speciation, play a key role in comparative genomics and functional inference. In particular, graph-based methods allow for the inference of orthology estimates without prior knowledge of the underlying gene or species trees. This results in orthology graphs, where each vertex represents a gene, and an edge exists between two vertices if the corresponding genes are estimated to be orthologs. Orthology graphs inferred under a tree-like evolutionary model must be cographs. However, real-world data often deviate from this property, either due to noise in the data, errors in inference methods or, simply, because evolution follows a network-like rather than a tree-like process. The latter, in particular, raises the question of whether and how orthology graphs can be derived from or, equivalently, are explained by phylogenetic networks. In this work, we study the constraints imposed on orthology graphs when the underlying evolutionary history follows a phylogenetic network instead of a tree. We show that any orthology graph can be represented by a sufficiently complex level-k network. However, such networks lack biologically meaningful constraints. In contrast, level-1 networks provide a simpler explanation, and we establish characterizations for level-1 explainable orthology graphs, i.e., those derived from level-1 evolutionary histories. To this end, we employ modular decomposition, a classical technique for studying graph structures. Specifically, an arbitrary graph is level-1 explainable if and only if each primitive subgraph is a near-cograph (a graph in which the removal of a single vertex results in a cograph). Additionally, we present a linear-time algorithm to recognize level-1 explainable orthology graphs and to construct a level-1 network that explains them, if such a network exists. Finally, we demonstrate the close relationship of level-1 explainable orthology graphs to the substitution operation, weakly chordal and perfect graphs, as well as graphs with twin-width at most 2.

Indexed as

HomologyLevel-1 networkLinear-time algorithmModular decompositionNear cographPerfect graphTwin-width

Identifiers

PMID41039586
PMCPMC12490074

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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.