Quantitative genetics of photosynthetic trait variation in maize
Waqar AliiD, Marcin GrzybowskiiD, J. Vladimir Torres‐RodrígueziD, Fangyi LiiD, Nikee ShresthaiD, Ramesh Kanna MathivananiD, Gabriel de BernardeauxiD, Khang HoangiD, Ravi V. MuraliD, Rebecca RostoniD, James C. SchnableiD, Seema SahayiD
Abstract
Natural genetic variation in photosynthesis-related traits can aid both in identifying genes involved in regulating photosynthetic processes and developing crops with improved productivity and photosynthetic efficiency. However, rapidly fluctuating environmental parameters create challenges for measuring photosynthetic parameters in large populations under field conditions. We measured chlorophyll fluorescence and absorbance-based photosynthetic traits in a maize diversity panel in the field using an experimental design that allowed us to estimate and control multiple confounding factors. Controlling the impact of day of measurement and light intensity as well as patterns of two-dimensional spatial variation in the field substantially increased heritability with the heritability of 7 out of 14 traits measured exceeding 0.4. We were able to identify high confidence GWAS signals associated with variation in four spatially corrected traits (the quantum yield of photosystem II, non-photochemical quenching, redox state of QA, and relative chlorophyll content). Insertion alleles for Arabidopsis orthologs of three candidate genes exhibited phenotypes consistent with our GWAS results. Collectively these results illustrate the potential of applying best practices from quantitative genetics research to address outstanding questions in plant physiology and understand the mechanisms underlying natural variation in photosynthesis. Highlights[bullet] Controlling spatial and environmental confounding factors increased heritability of photosynthetic traits. [bullet]GWAS identified high confidence signals associated with variation in relative chlorophyll, {Phi}PSII, {Phi}NPQ, and qL. [bullet]Insertion alleles of the Arabidopsis orthologs of maize candidate genes exhibited photosynthesis related phenotypes consistent with the GWAS results.
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