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Systematic characterization of photoperiodic gene expression patterns reveals diverse seasonal transcriptional systems in Arabidopsis

Photoperiod is an annual cue measured by biological systems to align growth and reproduction with the seasons. In plants, photoperiodic flowering has been intensively studied for over 100 years, but we lack a complete picture of the transcriptional networks and cellular processes that are photoperio...

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Detalles Bibliográficos
Autores principales: Leung, Chun Chung, Tarté, Daniel A., Oliver, Lilijana S., Wang, Qingqing, Gendron, Joshua M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10497145/
https://www.ncbi.nlm.nih.gov/pubmed/37699055
http://dx.doi.org/10.1371/journal.pbio.3002283
Descripción
Sumario:Photoperiod is an annual cue measured by biological systems to align growth and reproduction with the seasons. In plants, photoperiodic flowering has been intensively studied for over 100 years, but we lack a complete picture of the transcriptional networks and cellular processes that are photoperiodic. We performed a transcriptomics experiment on Arabidopsis plants grown in 3 different photoperiods and found that thousands of genes show photoperiodic alteration in gene expression. Gene clustering, daily expression integral calculations, and cis-element analysis then separate photoperiodic genes into co-expression subgroups that display 19 diverse seasonal expression patterns, opening the possibility that many photoperiod measurement systems work in parallel in Arabidopsis. Then, functional enrichment analysis predicts co-expression of important cellular pathways. To test these predictions, we generated a comprehensive catalog of genes in the phenylpropanoid biosynthesis pathway, overlaid gene expression data, and demonstrated that photoperiod intersects with 2 major phenylpropanoid pathways differentially, controlling flavonoids but not lignin. Finally, we describe the development of a new app that visualizes photoperiod transcriptomic data for the wider community.