학술논문
Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants.
Document Type
Academic Journal
Author
Palande S; Department of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.; Kaste JAM; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.; Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.; Roberts MD; Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.; Segura Abá K; Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.; Claucherty C; Department of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.; Dacon J; Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America.; Doko R; Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America.; Jayakody TB; Department of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.; Jeffery HR; Department of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.; Kelly N; Department of Horticulture, Michigan State University, East Lansing, Michigan, United States of America.; Manousidaki A; Department of Statistics and Probability, Michigan State University, East Lansing, Michigan, United States of America.; Parks HM; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.; Roggenkamp EM; Department of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.; Schumacher AM; Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.; Yang J; Department of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.; Percival S; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.; Pardo J; Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.; Husbands AY; Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.; Krishnan A; Department of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.; Montgomery BL; Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.; Department of Microbiology & Molecular Genetics, Michigan State University, East Lansing, Michigan, United States of America.; MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing, Michigan, United States of America.; Munch E; Department of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.; Department of Mathematics, Michigan State University, East Lansing, Michigan, United States of America.; Thompson AM; Department of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.; Plant Resilience Institute, Michigan State University, East Lansing, Michigan, United States of America.; Rougon-Cardoso A; Laboratory of Agrigenomic Sciences, Universidad Nacional Autónoma de México, ENES-León, León, Mexico.; Laboratorio Nacional Plantecc, ENES-León, León, Mexico.; Chitwood DH; Department of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.; Department of Horticulture, Michigan State University, East Lansing, Michigan, United States of America.; VanBuren R; Department of Horticulture, Michigan State University, East Lansing, Michigan, United States of America.; Plant Resilience Institute, Michigan State University, East Lansing, Michigan, United States of America.
Source
Publisher: Public Library of Science Country of Publication: United States NLM ID: 101183755 Publication Model: eCollection Cited Medium: Internet ISSN: 1545-7885 (Electronic) Linking ISSN: 15449173 NLM ISO Abbreviation: PLoS Biol Subsets: MEDLINE
Subject
Language
English
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.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2023 Palande et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2023 Palande et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)