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Cloning of wheat keto-acyl thiolase 2B reveals a role of jasmonic acid in grain weight determination.

ABSTRACT: Grain weight (GW) is one of the component traits of wheat yield. Existing reports have shown that multiple phytohormones are involved in the regulation of GW in different crops. However, the potential role of jasmonic acid (JA) remains unclear. Here, we report that triticale grain weight 1 (tgw1) mutant, with marked reductions in both GW and JA content, is caused by a premature stop mutation in keto-acyl thiolase 2B (KAT-2B) involved in β-oxidation during JA synthesis. KAT-2B overexpression increases GW in wild type and boosts yield. Additionally, KAT-2B compliments the grain defect in tgw1 and rescues the lethal phenotype of the Arabidopsis kat2 mutant in a sucrose-free medium. Despite the suppression of JA synthesis in tgw1 mutant, ABA synthesis is upregulated, which is accompanied by enhanced expression of SAG3 and reduction of chlorophyll content in leaves. Together, these results demonstrate a role of the JA synthetic gene KAT-2B in controlling GW and its potential application value for wheat improvement.

SUBMITTER: Chen Y

PROVIDER: S-EPMC7722888 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Cloning of wheat keto-acyl thiolase 2B reveals a role of jasmonic acid in grain weight determination.

Chen Yun Y Yan Yan Y Wu Tian-Tian TT Zhang Guo-Liang GL Yin Huanran H Chen Wei W Wang Shuangshuang S Chang Fang F Gou Jin-Ying JY

Nature communications 20201208 1

Grain weight (GW) is one of the component traits of wheat yield. Existing reports have shown that multiple phytohormones are involved in the regulation of GW in different crops. However, the potential role of jasmonic acid (JA) remains unclear. Here, we report that triticale grain weight 1 (tgw1) mutant, with marked reductions in both GW and JA content, is caused by a premature stop mutation in keto-acyl thiolase 2B (KAT-2B) involved in β-oxidation during JA synthesis. KAT-2B overexpression incr ...[more]

PMID: 33293512

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Project description:Mitochondrial fatty-acid beta-oxidation (mFAO) plays a central role in mammalian energy metabolism. Multiple severe diseases are associated with defects in this pathway. Its kinetic structure is characterized by a complex wiring of which the functional implications have hardly been explored. Repetitive cycles of reversible reactions, each cycle shortening the fatty acid by two carbon atoms, evoke competition between intermediates of different chain lengths for a common set of 'promiscuous' enzymes (enzymes with activity towards multiple substrates). In our validated kinetic model of the pathway, substrate overload causes a steep and detrimental flux decline. Here, we unravel the underlying mechanism and the role of enzyme promiscuity in it. Comparison of alternative model versions elucidated the role of promiscuity of individual enzymes. Promiscuity of the last enzyme of the pathway, medium-chain ketoacyl-CoA thiolase (MCKAT), was both necessary and sufficient to elicit the flux decline. Subsequently, Metabolic Control Analysis revealed that MCKAT had insufficient capacity to cope with high substrate influx. Next, we quantified the internal metabolic regulation, revealing a vicious cycle around MCKAT. Upon substrate overload, MCKAT's ketoacyl-CoA substrates started to accumulate. The unfavourable equilibrium constant of the preceding enzyme, medium/short-chain hydroxyacyl-CoA dehydrogenase, worked as an amplifier, leading to accumulation of upstream CoA esters, including acyl-CoA esters. These acyl-CoA esters are at the same time products of MCKAT and inhibited its already low activity further. Finally, the accumulation of CoA esters led to a sequestration of free CoA. CoA being a cofactor for MCKAT, its sequestration limited the MCKAT activity even further, thus completing the vicious cycle. Since CoA is also a substrate for distant enzymes, it efficiently communicated the 'traffic jam' at MCKAT to the entire pathway. This novel mechanism provides a basis to explore the role of mFAO in disease and elucidate similar principles in other pathways of lipid metabolism.

Project description:BackgroundMean grain weight (MGW) is among the most frequently measured parameters in wheat breeding and physiology. Although in the recent decades, various wheat grain analyses (e.g. counting, and determining the size, color, or shape features) have been facilitated, thanks to the automated image processing systems, MGW estimations have been limited to using few number of image-derived indices; i.e. mainly the linear or power models developed based on the projected area (Area). Following a preliminary observation which indicated the potential of grain width in improving the predictions, the present study was conducted to explore more efficient indices for increasing the precision of image-based MGW estimations. For this purpose, an image archive of the grains was processed, which were harvested from a 2-year field experiment carried out with 3 replicates under two irrigation conditions and included 15 cultivar mixture treatments (so the archive was consisted of 180 images including more than 72,000 grains).ResultsIt was observed that among the more than 30 evaluated indices of grain size and shape, indicators of grain width (i.e. Minor & MinFeret) along with 8 other empirical indices had a higher correlation with MGW, compared with Area. The most precise MGW predictions were obtained using the Area × Circularity, Perimeter × Circularity, and Area/Perimeter indices. Furthermore, it was found that (i) grain width and the Area/Perimeter ratio were the common factors in the structure of the superior predictive indices; and (ii) the superior indices had the highest correlation with grain width, rather than with their mathematical components. Moreover, comparative efficiency of the superior indices almost remained stable across the 4 environmental conditions. Eventually, using the selected indices, ten simple linear models were developed and validated for MGW prediction, which indicated a relatively higher precision than the current Area-based models. The considerable effect of enhancing image resolution on the precision of the models has been also evidenced.ConclusionsIt is expected that the findings of the present study, along with the simple predictive linear models developed and validated using new image-derived indices, could improve the precision of the image-based MGW estimations, and consequently facilitate wheat breeding and physiological assessments.

Dataset Information

Cloning of wheat keto-acyl thiolase 2B reveals a role of jasmonic acid in grain weight determination.

Publications

Cloning of wheat keto-acyl thiolase 2B reveals a role of jasmonic acid in grain weight determination.

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