4.7 Article

Comparative physiological and transcriptomic analysis of pear leaves under distinct training systems

Journal

SCIENTIFIC REPORTS
Volume 10, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-020-75794-z

Keywords

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Funding

  1. National Key R&D Program of China [2018YFD1000200]
  2. China Agriculture Research System [CARS-28-11]
  3. Hubei Agricultural Science and Technology Innovation Fund [2019-620-000-001-22]
  4. Young Scientist Foundation of Hubei Academy of Agricultural Sciences [2017NKYJJ02]
  5. Talent Project of Hubei Academy of Agricultural Sciences [C2018006]

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Canopy architecture is critical in determining the light interception and distribution, and subsequently the photosynthetic efficiency and productivity. However, the physiological responses and molecular mechanisms by which pear canopy architectural traits impact on photosynthesis remain poorly understood. Here, physiological investigations coupled with comparative transcriptomic analyses were performed in pear leaves under distinct training systems. Compared with traditional freestanding system, flat-type trellis system (DP) showed higher net photosynthetic rate (P-N) levels at the most time points throughout the entire monitored period, especially for the interior of the canopy in sunny side. Gene ontology analysis revealed that photosynthesis, carbohydrate derivative catabolic process and fatty acid metabolic process were over-represented in leaves of DP system with open-canopy characteristics. Weighted gene co-expression network analysis uncovered a significant network module positive correlated with P-N value. The hub genes (PpFKF1 and PpPRR5) of the module were enriched in circadian rhythm pathway, suggesting a functional role for circadian clock genes in mediating photosynthetic performance under distinct training systems. These results draw a link between pear photosynthetic response and specific canopy architectural traits, and highlight light harvesting and circadian clock network as potential targets for the input signals from the fluctuating light availability under distinct training systems.

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