Evidence map›Paper›PMID 38051702›Full record

ArticlePLoS biology2023

Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants.

Sourabh Palande, Joshua A M Kaste, Miles D Roberts, Kenia Segura Abá, Carly Claucherty, Jamell Dacon, Rei Doko, Thilani B Jayakody, Hannah R Jeffery, Nathan Kelly and 15 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Sourabh PalandeDepartment of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.
Joshua A M KasteDepartment of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0003-1942-0315
Miles D RobertsDepartment of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.
Kenia Segura AbáDepartment of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.
Carly ClauchertyDepartment of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.
Jamell DaconDepartment of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0002-6917-6835
Rei DokoDepartment of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America.
Thilani B JayakodyDepartment of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.
Hannah R JefferyDepartment of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.
Nathan KellyDepartment of Horticulture, Michigan State University, East Lansing, Michigan, United States of America.
Andriana ManousidakiDepartment of Statistics and Probability, Michigan State University, East Lansing, Michigan, United States of America.
Hannah M ParksDepartment of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0002-9861-8049
Emily M RoggenkampDepartment of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.
Ally M SchumacherDepartment of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.
Jiaxin YangDepartment of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.
Sarah PercivalDepartment of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0003-1024-4618
Jeremy PardoDepartment of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.
Aman Y HusbandsDepartment of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Arjun KrishnanDepartment of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0002-7980-4110
Beronda L MontgomeryDepartment of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America.
Elizabeth MunchDepartment of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.
Addie M ThompsonDepartment of Plant, Soil & Microbial Sciences, Michigan State University, East Lansing, Michigan, United States of America.
Alejandra Rougon-CardosoLaboratory of Agrigenomic Sciences, Universidad Nacional Autónoma de México, ENES-León, León, Mexico.ORCID 0000-0002-5273-5709
Daniel H ChitwoodDepartment of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0003-4875-1447
Robert VanBurenDepartment of Horticulture, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0000-0003-2133-2760

Funding

Plant Biotechnology for Health and SustainabilityT32GM110523 · NIGMS · MICHIGAN STATE UNIVERSITY · PI LAST, ROBERT LOUIS · 2014 to 2023
$2.2M
NIGMS NIH HHS T32 GM110523
6 · The paper itself

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.

Indexed as

MagnoliopsidaGene ExpressionGene Expression Regulation, PlantPlant LeavesPlantsStress, Physiological

Identifiers

PMID38051702
PMCPMC10723737

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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.