Correlation and co-localization of QTL for stomatal density, canopy temperature, and productivity with and without drought stress inSetaria

Abstract

Mechanistic modeling indicates that stomatal conductance could be reduced to improve water use efficiency (WUE) in C4 crops. Genetic variation in stomatal density and canopy temperature was evaluated in the model C4 genus, Setaria. Recombinant inbred lines (RILs) derived from a Setaria italica×Setaria viridis cross were grown with ample or limiting water supply under field conditions in Illinois. An optical profilometer was used to rapidly assess stomatal patterning, and canopy temperature was measured using infrared imaging. Stomatal density and canopy temperature were positively correlated but both were negatively correlated with total above-ground biomass. These trait relationships suggest a likely interaction between stomatal density and the other drivers of water use such as stomatal size and aperture. Multiple quantitative trait loci (QTL) were identified for stomatal density and canopy temperature, including co-located QTL on chromosomes 5 and 9. The direction of the additive effect of these QTL on chromosome 5 and 9 was in accordance with the positive phenotypic relationship between these two traits. This, along with prior experiments, suggests a common genetic architecture between stomatal patterning and WUE in controlled environments with canopy transpiration and productivity in the field, while highlighting the potential of Setaria as a model to understand the physiology and genetics of WUE in C4 species.

Quantitative trait loci mapping reveals important genomic regions controlling root architecture and shoot biomass under nitrogen, phosphorus, and potassium stress in rapeseed (Brassica napus L.)

“…This finding supports the pyramiding of QTLs for several different traits acting same time in a specific cultivar ( Dormatey et al, 2020 ; Mei et al, 2020 ). The co-localization of QTLs for many traits can be attributed to the pleiotropic effect of a single gene or a network of interrelated genes, each of which affects one trait ( Amoah et al, 2020 ; Ibrahim et al, 2021 ; Prakash et al, 2021 ). The co-localization of 18 QTL clusters in this study suggested that this genomic region could help with breeding NPK efficiency-related root and biomass traits.…”

Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes

“…In general, effective screening of stomatal dynamics is most practical in controlled environment settings due to greater control of environmental conditions and also how plants are pre-conditioned before data collection. But, thermal cameras mounted on aircraft, gantries, and cable-systems, or used from boom lifts, have enabled reliable field-scale measurements of plant temperature ( Deery et al, 2016 , 2019 ; Sagan et al, 2019 ), including for identification of QTL that overlaps with stomatal density QTL ( Prakash et al, 2021 ), but in these settings, the changes in leaf temperature caused by dynamic stomatal changes coincide with the transient effects of wind, leaf shading, and leaf angle. So, evaluating dynamic stomatal responses to varying PPFD in the field remains a daunting prospect.…”

The Global Assessment of Oilseed Brassica Crop Species Yield, Yield Stability and the Underlying Genetics

“…A wide range of sensors is available for monitoring specific plant traits under field or controlled conditions such as RGB, multispectral and hyperspectral cameras, infrared thermal or LiDAR sensors. Infrared thermography images of the plant canopy contribute to determining crop water stress [ 69 ] and assist in identifying QTL associated with stomatal density and canopy temperature in Setaria [ 70 ] , accessed on 4 September 2022. Multispectral and hyperspectral cameras have been widely employed to obtain quantitative measurements of the canopy reflectance throughout plant development, supporting the identification of potassium deficiency and green peach aphid susceptibility [ 71 ], classification of fungal infection severity in B. napus seeds [ 72 ] and seed pod maturity [ 73 ].…”