02911naa a2200277 a 450000100080000000500110000800800410001902400360006010000140009624501370011026000090024750003610025652017410061765300180235865300200237665300090239665300190240570000210242470000160244570000150246170000190247670000190249570000200251470000160253477300830255010608382020-02-26       2020    bl uuuu     u00u1 u    #d7 a10.1007/s11120-020-00721-22DOI1 aQUERO, G.  aGenetic architecture of photosynthesis energy partitioning as revealed by a genome-wide association approach.h[electronic resource]  c2020  aArticle history: Received: 11 October 2019 / Accepted: 10 February 2020 / Published: 18 February 2020. Corresponding author: Gastón Quero (gastonquero@fagro.edu.uy)  Electronic supplementary material: The online version of this article (https://doi.org/10.1007/s1112 0-020-00721 -2) contains supplementary material, which is available to authorized users.  aABSTRACT. The photosynthesis process is determined by the intensity level and spectral quality of the light; therefore, leaves need to adapt to a changing environment. The incident energy absorbed can exceed the sink capability of the photosystems, and, in this context, photoinhibition may occur in both photosystem II (PSII) and photosystem I (PSI). Quantum yield parameters analyses reveal how the energy is managed. These parameters are genotype-dependent, and this genotypic variability is a good opportunity to apply mapping association strategies to identify genomic regions associated with photosynthesis energy partitioning. An experimental and mathematical approach is proposed for the determination of an index which estimates the energy per photon flux for each spectral bandwidth (Δλ) of the light incident (QI index). Based on the QI, the spectral quality of the plant growth, environmental lighting, and the actinic light of PAM were quantitatively very similar which allowed an accurate phenotyping strategy of a rice population. A total of 143 genomic single regions associated with at least one trait of chlorophyll fluorescence were identified. Moreover, chromosome 5 gathers most of these regions indicating the importance of this chromosome in the genetic regulation of the photochemistry process. Through a GWAS strategy, 32 genes of rice genome associated with the main parameters of the photochemistry process of photosynthesis in rice were identified. Association between light-harvesting complexes and the potential quantum yield of PSII, as well as the relationship between coding regions for PSI-linked proteins in energy distribution during the photochemical process of photosynthesis is analyzed.  aActinic light  aCandidate genes  aGWAS  aQuantum yields1 aBONNECARRERE, V.1 aSIMONDI, S.1 aSANTOS, J.1 aFERNÁNDEZ, S.1 aGUTIÉRREZ, L.1 aGARAYCOCHEA, S.1 aBORSANI, O.  tPhotosynthesis Research, 2020. Doi: https://doi.org/10.1007/s11120-020-00721-2