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  • Title:  Additive Effects of Multiple Global Change Drivers on Terrestrial Nitrogen Cycling Worldwide
  • Authors: 
  • Corresponding Author:  Bangjing Ding, Di Xu, Shuo Wang, Wenzhi Liu*, Quanfa Zhang
  • Pubyear:  2025
  • Title of Journal:  Global Change Biology
  • Paper Code: 
  • Volume:  31
  • Number: 
  • Page: 
  • Others: 
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    Abstract:

  • Heteranthery, the occurrence of functionally and structurally distinct stamens within a flower, represents a striking example of convergent evolution among diverse animal-pollinated lineages. Although the ecological basis of this somatic polymorphism is understood, the developmental and molecular mechanisms are largely unknown. To address this knowledge gap, we selected Monochoria elata (Pontederiaceae) as our study system due to its typical heterantherous floral structure. We constructed a chromosome-level genome assembly of M. elata, conducted transcriptomic analyses and target phytohormone metabolome analysis to explore gene networks and hormones associated with heteranthery. We focused on three key stamen characteristics-colour, spatial patterning, and filament elongation-selected for their significant roles in stamen differentiation and their relevance to the functional diversity observed in heterantherous species. Our analyses suggest that gene networks involving MelLEAFY3, MADS-box, and TCP genes regulate stamen identity, with anthocyanin influencing colour, and lignin contributing to filament elongation. Additionally, variation in jasmonic acid and abscisic acid concentration between feeding and pollinating anthers appears to contribute to their morphological divergence. Our findings highlight gene networks and hormones associated with intra-floral stamen differentiation and indicate that whole genome duplications have likely facilitated the evolution of heteranthery during divergence from other Pontederiaceae without heteranthery. Copyright (c) 2025, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Limited and Science Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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