TraitCapture: genomic and environment modelling of plant phenomic data

Brown, Thomas S.; Cheng, Riyan; Sirault, Xavier; Rungrat, Tepsuda; Murray, Kevin; Trtílek, Martin; Furbank, Robert T.; Badger, Murray R.; Pogson, Barry J.; Borevitz, Justin O.

doi:10.1016/j.pbi.2014.02.002

Cited by 99 publications

(73 citation statements)

References 44 publications

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“…Leaf area expansion was measured using the TraitCapture imaging and segmentation pipeline (Brown et al, 2014). Images with a resolution of approximately 25 pixels mm 22 were captured with two Canon EOS700D, DSLR digital cameras mounted in the center of each side of the chamber about 1.5 m from the plants.…”

Section: Leaf Area Expansion Measurementsmentioning

confidence: 99%

Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply

et al. 2017

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Plant respiration can theoretically be fueled by and dependent upon an array of central metabolism components; however, which ones are responsible for the quantitative variation found in respiratory rates is unknown. Here, large-scale screens revealed 2-fold variation in nighttime leaf respiration rate (R N ) among mature leaves from an Arabidopsis (Arabidopsis thaliana) natural accession collection grown under common favorable conditions. R N variation was mostly maintained in the absence of genetic variation, which emphasized the low heritability of R N and its plasticity toward relatively small environmental differences within the sampling regime. To pursue metabolic explanations for leaf R N variation, parallel metabolite level profiling and assays of total protein and starch were performed. Within an accession, R N correlated strongly with stored carbon substrates, including starch and dicarboxylic acids, as well as sucrose, major amino acids, shikimate, and salicylic acid. Among different accessions, metabolite-R N correlations were maintained with protein, sucrose, and major amino acids but not stored carbon substrates. A complementary screen of the effect of exogenous metabolites and effectors on leaf R N revealed that (1) R N is stimulated by the uncoupler FCCP and high levels of substrates, demonstrating that both adenylate turnover and substrate supply can limit leaf R N , and (2) inorganic nitrogen did not stimulate R N , consistent with limited nighttime nitrogen assimilation. Simultaneous measurements of R N and protein synthesis revealed that these processes were largely uncorrelated in mature leaves. These results indicate that differences in preceding daytime metabolic activities are the major source of variation in mature leaf R N under favorable controlled conditions. Few plant metabolic fluxes are readily accessible to routine measurement. The major exceptions to this are fluxes involving gas exchange, such as respiration and photosynthesis. Measurements of respiratory gas exchange (i.e. mitochondrial oxygen uptake or CO 2 release in the absence of photorespiration) are useful from a metabolic perspective because they can be interpreted in terms of the underlying carbon fluxes and the generation of ATP by oxidative phosphorylation (Sweetlove et al., 2013). The biochemical reactions of respiration that produce CO 2 and lead to oxygen consumption are well understood (Plaxton and Podestá, 2006;Sweetlove et al., 2010;Millar et al., 2011;Tcherkez et al., 2012). The stoichiometries of the reactions and the connections between them are known, which provides us with a metabolic map of respiration that includes glycolysis, the oxidative pentose phosphate pathway, the citric acid cycle, the mitochondrial electron transport chain (mETC), ATP synthase, and several other surrounding reactions. In plants, carbohydrates are the dominant respiratory substrates, whereas lipids are rarely respired (Plaxton and Podestá, 2006). Carbohydrate oxidation proceeds via organic acids, which serve many purposes in plant...

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Section: Leaf Area Expansion Measurementsmentioning

confidence: 99%

Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply

et al. 2017

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“…When applied to the entirety of field plots under evaluation in breeding programs, high-throughput phenotyping will balance the genotype-to-phenotype datasets and provide the raw material for transformative analysis. The integration of weather data into these high-resolution datasets will enable study of genotype-by-environment interaction in an ecophysiologial modeling framework as never before [44].…”

Section: Current Opinion In Plant Biologymentioning

confidence: 99%

Breeding-assisted genomics

Poland

2015

Current Opinion in Plant Biology

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“…For example, obtaining repeated measurements of some traits such as root architecture is not possible using conventional methods because these methods would necessitate destroying the plants. By contrast, some HTPPs, relying on various imaging techniques, are able to more conveniently monitor the dynamic growth of the traits without damaging the plant [15][16][17][18][19][20]. Therefore, HTPPs can efficiently bring time as an extra dimension to the phenotype data, which may potentially facilitate QTL analysis of developmental and growth-related traits.…”

Section: Trendsmentioning

confidence: 99%

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data

Sillanpää

2015

Trends in Plant Science

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TraitCapture: genomic and environment modelling of plant phenomic data

Cited by 99 publications

References 44 publications

Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply

Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply

Breeding-assisted genomics

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data

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