ArticlePLoS biology2023
Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants.
Article in PLoS biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The architecture of resilience: a genome assembly of Myrothamnus flabellifolia sheds light on desiccation tolerance and sex determination.The New phytologist · 2026Article
- The cell as a token: high-dimensional geometry in language models and cell embeddings.Bioinformatics (Oxford, England) · 2025Review
- Gene-environment-brain topology reveals clinical subtypes of depression in UK Biobank.Scientific reports · 2025Article
- Interdisciplinarity through internationality: Results from a US-Mexico graduate course bridging computational and plant science.Plant direct · 2024Article
- Convergent evolution of desiccation tolerance in grasses.Nature plants · 2024Article
- Topological data analysis reveals core heteroblastic and ontogenetic programs embedded in leaves of grapevine (Vitaceae) and maracuyá (Passifloraceae).PLoS computational biology · 2024Article
- Expression-based machine learning models for predicting plant tissue identity.Applications in plant sciencesArticle
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Authors and funding
25 authors.
Funding
Abstract
Since they emerged approximately 125 million years ago, flowering plants have evolved to dominate the terrestrial landscape and survive in the most inhospitable environments on earth. At their core, these adaptations have been shaped by changes in numerous, interconnected pathways and genes that collectively give rise to emergent biological phenomena. Linking gene expression to morphological outcomes remains a grand challenge in biology, and new approaches are needed to begin to address this gap. Here, we implemented topological data analysis (TDA) to summarize the high dimensionality and noisiness of gene expression data using lens functions that delineate plant tissue and stress responses. Using this framework, we created a topological representation of the shape of gene expression across plant evolution, development, and environment for the phylogenetically diverse flowering plants. The TDA-based Mapper graphs form a well-defined gradient of tissues from leaves to seeds, or from healthy to stressed samples, depending on the lens function. This suggests that there are distinct and conserved expression patterns across angiosperms that delineate different tissue types or responses to biotic and abiotic stresses. Genes that correlate with the tissue lens function are enriched in central processes such as photosynthetic, growth and development, housekeeping, or stress responses. Together, our results highlight the power of TDA for analyzing complex biological data and reveal a core expression backbone that defines plant form and function.
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