Fecha/hora: 09/06/2024 07:47:01

Biblioteca(s): 	INIA Las Brujas.	
Fecha corriente: 	26/02/2020	
Fecha de la última actualización: 	26/02/2020	
Autoria: 	QUERO, G.; BONNECARRERE, V.; SIMONDI, S.; SANTOS, J.; FERNÁNDEZ, S.; GUTIÉRREZ, L.; GARAYCOCHEA, S.; BORSANI, O.	
Afiliación: 	GASTÓN QUERO CORRALLO, Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SEBASTIÁN SIMONDI, Área de Matemática, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo (FCEN-UNCuyo), Mendoza, Argentina; JORGE SANTOS, Área de Física, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo (FCEN-UNCuyo), Mendoza, Argentina; SEBASTIÁN FERNÁNDEZ, Facultad de Ingeniería, Instituto de Ingeniería Eléctrica, Universidad de La República, Montevideo, Uruguay; LUCÍA GUTIÉRREZ, Department of Agronomy, University of Wisconsin-Madison, Madison, WI, USA; Departamento de Biometría, Estadística y Cómputos, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay; SILVIA RAQUEL GARAYCOCHEA SOLSONA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OMAR BORSANI, Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay.	
Título: 	Genetic architecture of photosynthesis energy partitioning as revealed by a genome-wide association approach.	
Año de publicación: 	2020	
Fuente/Imprenta: 	Photosynthesis Research, 2020. Doi: https://doi.org/10.1007/s11120-020-00721-2	
DOI: 	10.1007/s11120-020-00721-2	
Idioma: 	Inglés	
Notas: 	Article 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.	
Contenido: 	ABSTRACT.
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 (&#916;&#955;) 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.	
Palabras-Clave: 	Actinic light; Candidate genes; GWAS; Quantum yields.	
Categoría del tema: 	F30 Genética vegetal y fitomejoramiento	
Registro original: 	INIA Las Brujas (LB)	
Ejemplares: 	LB - (102186-1) - PXI - AP - DD - PP/Photosynth. Res./2020 -  -  - DIS