Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for QTL mapping in maize

Xie, Jiayang; Mayfield‐Jones, Dustin; Erice, Gorka; Choi, Myeon-Song; Leakey, Andrew D. B.

doi:10.1101/2020.10.09.333880

Cited by 11 publications

(24 citation statements)

References 98 publications

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“…But, the trait relationships reported here also highlight the complex mix of intrinsic and environmental factors that affect WUE in a field-grown crop (Leakey et al,2019). For example, detecting an association between SD and g s may be complicated by a strong tradeoff between SD and stomatal size (Xie et al, 2021). In maize, the width and length of stomatal complexes were significantly correlated with leaf gas exchange traits (Xie et al, 2021).…”

Section: Rapid Phenotypingmentioning

confidence: 74%

“…For example, detecting an association between SD and g s may be complicated by a strong tradeoff between SD and stomatal size (Xie et al, 2021). In maize, the width and length of stomatal complexes were significantly correlated with leaf gas exchange traits (Xie et al, 2021). And, in rice, stomatal length has been observed to positively correlate with g s across rice accessions, where SD did not (Ohsumi et al, 2007).…”

Section: Rapid Phenotypingmentioning

confidence: 99%

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Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions

et al. 2021

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Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modelling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 (ci/ca) was genetically correlated with SD, SLA, gs and biomass production. Plasticity in SD and SLA were interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with non-synonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

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Section: Rapid Phenotypingmentioning

confidence: 74%

Section: Rapid Phenotypingmentioning

confidence: 99%

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions

et al. 2021

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“…Loss of function mutants of EP3 have smaller stomata, which appeared to drive reductions in g s and A (Yu et al, 2015). Given the substantial evidence for links between gas exchange, stomatal complex size and stomatal density (Lawson and Blatt 2014; Xie et al, 2020), there is potential for variations in the sequence and expression of these genes to drive variation in the g s thermal traits measured in this study. A number of other genes identified by the integrated GWAS/TWAS have been implicated in the development of epidermal cells in general (Supplementary Table S7).…”

Section: Discussionmentioning

confidence: 98%

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

Pignon

Fernandes

Valluru

et al. 2021

Preprint

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Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential to maintenance of water-use efficiency (WUE). However, little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. High-throughput thermal imaging was used to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum accessions. Results from thermal imaging significantly correlated with photosynthetic gas-exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study (GWAS/TWAS) identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with greatest confidence, 77 were orthologs of Arabidopsis genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.

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“…New machine learning-enabled phenotyping methods for measuring stomatal size (e.g. Xie et al , 2020 , Preprint) will aid this effort, because manual estimation of stomatal size currently takes ~30 times longer than manually measuring stomatal density, making it infeasible to assess in many experiments.…”

Section: Discussionmentioning

confidence: 99%

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

Prakash

Banan

Paul

et al. 2021

Journal of Experimental Botany

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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.

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Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for QTL mapping in maize

Cited by 11 publications

References 98 publications

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions

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

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

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