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1.
Science ; 364(6445): 1095-1098, 2019 06 14.
Article in English | MEDLINE | ID: mdl-31197015

ABSTRACT

Wild almond species accumulate the bitter and toxic cyanogenic diglucoside amygdalin. Almond domestication was enabled by the selection of genotypes harboring sweet kernels. We report the completion of the almond reference genome. Map-based cloning using an F1 population segregating for kernel taste led to the identification of a 46-kilobase gene cluster encoding five basic helix-loop-helix transcription factors, bHLH1 to bHLH5. Functional characterization demonstrated that bHLH2 controls transcription of the P450 monooxygenase-encoding genes PdCYP79D16 and PdCYP71AN24, which are involved in the amygdalin biosynthetic pathway. A nonsynonymous point mutation (Leu to Phe) in the dimerization domain of bHLH2 prevents transcription of the two cytochrome P450 genes, resulting in the sweet kernel trait.


Subject(s)
Amygdalin/genetics , Basic Helix-Loop-Helix Transcription Factors/genetics , Domestication , Gene Expression Regulation, Plant , Plant Proteins/genetics , Prunus dulcis/genetics , Amino Acid Substitution , Amygdalin/biosynthesis , Amygdalin/metabolism , Basic Helix-Loop-Helix Transcription Factors/chemistry , Cytochrome P-450 Enzyme System/genetics , Leucine/genetics , Multigene Family , Phenylalanine/genetics , Point Mutation , Protein Conformation , Protein Multimerization/genetics , Prunus dulcis/metabolism , Taste , Transcription, Genetic
2.
J Exp Bot ; 66(7): 1817-32, 2015 Apr.
Article in English | MEDLINE | ID: mdl-25697789

ABSTRACT

The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator(®) at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf 'greenness' correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants.


Subject(s)
Nitrogen/metabolism , Sorghum/physiology , Water/physiology , Algorithms , Biomass , Chlorophyll/metabolism , Crops, Agricultural , Droughts , Edible Grain/growth & development , Edible Grain/physiology , Models, Theoretical , Phenotype , Plant Leaves/growth & development , Plant Leaves/physiology , Plant Shoots/growth & development , Plant Shoots/physiology , Sorghum/growth & development
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