Abscisic acid (ABA) is an important phytohormone regulating plant growth, development, and stress responses. It has an essential role in multiple physiological processes of plants, such as stomatal closure, cuticular wax accumulation, leaf senescence, bud dormancy, seed germination, osmotic regulation, and growth inhibition among many others. Abscisic acid controls downstream responses to abiotic and biotic environmental changes through both transcriptional and posttranscriptional mechanisms. During the past 20 years, ABA biosynthesis and many of its signaling pathways have been well characterized. Here we review the dynamics of ABA metabolic pools and signaling that affects many of its physiological functions.

https://onlinelibrary.wiley.com/doi/epdf/10.1111/jipb.12899

Abscisic acid dynamics, signaling, and functions in plants

Reciprocal regulation of the TOR kinase and ABA receptor balances plant growth and stress response

ABA Insensitive 5 (ABI5) is a basic leucine zipper (bZIP) transcription factor that plays a key role in the regulation of seed germination and early seedling growth in the presence of ABA and abiotic stresses. ABI5 functions in the core ABA signaling, which is composed of PYR/PYL/RCAR receptors, PP2C phosphatases and SnRK2 kinases, through the regulation of the expression of genes that contain the ABSCISIC ACID RESPONSE ELEMENT (ABRE) motif within their promoter region. The regulated targets include stress adaptation genes, e.g. LEA proteins. However, the expression and activation of ABI5 is not only dependent on the core ABA signaling. Many transcription factors such as ABI3, ABI4, MYB7 and WRKYs play either a positive or a negative role in the regulation of ABI5 expression. Additionally, the stability and activity of ABI5 are also regulated by other proteins through post-translational modifications such as phosphorylation, ubiquitination, sumoylation and S-nitrosylation. Moreover, ABI5 also acts as an ABA and other phytohormone signaling integrator. Components of auxin, cytokinin, gibberellic acid, jasmonate and brassinosteroid signaling and metabolism pathways were shown to take part in ABI5 regulation and/or to be regulated by ABI5. Monocot orthologues of AtABI5 have been identified. Although their role in the molecular and physiological adaptations during abiotic stress have been elucidated, knowledge about their detailed action still remains elusive. Here, we describe the recent advances in understanding the action of ABI5 in early developmental processes and the adaptation of plants to unfavorable environmental conditions. We also focus on ABI5 relation to other phytohormones in the abiotic stress response of plants.

/pdf/the-role-and-regulation-of-abi5-aba-insensitive-5-in-plant-qru7e0937u.pdf

The Role and Regulation of ABI5 (ABA-Insensitive 5) in Plant Development, Abiotic Stress Responses and Phytohormone Crosstalk

Soybean is a major legume crop originating in temperate regions, and photoperiod responsiveness is a key factor in its latitudinal adaptation. Varieties from temperate regions introduced to lower latitudes mature early and have extremely low grain yields. Introduction of the long-juvenile (LJ) trait extends the vegetative phase and improves yield under short-day conditions, thereby enabling expansion of cultivation in tropical regions. Here we report the cloning and characterization of J, the major classical locus conferring the LJ trait, and identify J as the ortholog of Arabidopsis thaliana EARLY FLOWERING 3 (ELF3). J depends genetically on the legume-specific flowering repressor E1, and J protein physically associates with the E1 promoter to downregulate its transcription, relieving repression of two important FLOWERING LOCUS T (FT) genes and promoting flowering under short days. Our findings identify an important new component in flowering-time control in soybean and provide new insight into soybean adaptation to tropical regions.

Natural variation at the soybean J locus improves adaptation to the tropics and enhances yield

Overall growth and development of a plant is regulated by complex interactions among various hormones, which is critical at different developmental stages. Some of the key aspects of plant growth include seed development, germination and plant survival under unfavorable conditions. Two of the key phytohormones regulating the associated physiological processes are gibberellins (GA) and abscisic acid (ABA). GAs participate in numerous developmental processes, including, seed development and seed germination, seedling growth, root proliferation, determination of leaf size and shape, flower induction and development, pollination and fruit expansion. Despite the association with abiotic stresses, ABA is essential for normal plant growth and development. It plays a critical role in different abiotic stresses by regulating various downstream ABA-dependent stress responses. Plants maintain a balance between GA and ABA levels constantly throughout the developmental processes at different tissues and organs, including under unfavorable environmental or physiological conditions. Here, we will review the literature on how GA and ABA control different stages of plant development, with focus on seed germination and selected abiotic stresses. The possible crosstalk of ABA and GA in specific events of the above processes will also be discussed, with emphasis on downstream stress signaling components, kinases and transcription factors (TFs). The importance of several key ABA and GA signaling intermediates will be illustrated. The knowledge gained from such studies will also help to establish a solid foundation to develop future crop improvement strategies.

/pdf/regulation-of-seed-germination-and-abiotic-stresses-by-3tk0haoipb.pdf

Regulation of Seed Germination and Abiotic Stresses by Gibberellins and Abscisic Acid.

The antagonistic crosstalk between gibberellic acid (GA) and abscisic acid (ABA) plays a pivotal role in the modulation of seed germination. However, the molecular mechanism of such phytohormone interaction remains largely elusive. Here we show that three Arabidopsis NUCLEAR FACTOR-Y C (NF-YC) homologues NF-YC3, NF-YC4 and NF-YC9 redundantly modulate GA- and ABA-mediated seed germination. These NF-YCs interact with the DELLA protein RGL2, a key repressor of GA signalling. The NF-YC–RGL2 module targets ABI5, a gene encoding a core component of ABA signalling, via specific CCAAT elements and collectively regulates a set of GA- and ABA-responsive genes, thus controlling germination. These results suggest that the NF-YC–RGL2–ABI5 module integrates GA and ABA signalling pathways during seed germination. Crosstalk between gibberellic acid (GA) and abscisic acid (ABA) regulates seed germination. Here the authors show that NF-YC transcription factors can interact with the RGL2 DELLA protein to regulate expression of ABI5and therefore modulate ABA- and GA-responsive gene expression.

/pdf/the-nf-yc-rgl2-module-integrates-ga-and-aba-signalling-to-ghsrwizj4x.pdf

The NF-YC-RGL2 module integrates GA and ABA signalling to regulate seed germination in Arabidopsis.

Abstract The quality of milk is largely determined by the protein content. The feasibility of predicting the protein content of milk by hyperspectral image has attracted more attentions from researchers for minor detection cost and high efficiency. In this paper, a prediction modeling method based on improved sparrow search algorithm (SSA) and optimized back propagation (BP) neural network is proposed, in which sine chaotic map is introduced to initialize the population position to improve the optimization performance of SSA. In the experiment, hyperspectral images of each kind of milk were collected by visible/near infrared hyperspectral imaging system to acquire hyperspectral data, then the spectral data were pretreated by Savitzky–Golay smoothing, and the competitive adaptive reweighted sampling combined with successive projections algorithm to select 13 characteristic bands. Subsequently, the spectral data corresponding to the characteristic bands are used as the input of back propagation neural network, optimized by the improved sparrow search algorithm for the initial weight and threshold of BP neural network, to establish three prediction models(BP model, the BP model based on SSA optimization and the BP model based on improved SSA optimization).Experimental results demonstrate that the BP model based on improved SSA optimization has better fitting ability and higher prediction accuracy for milk protein content. This research provides algorithm support and theoretical basis for the rapid nondestructive detection of milk protein content based on BP neural network.

Pengwei Hu

Papers

The NF-YC-RGL2 module integrates GA and ABA signalling to regulate seed germination in Arabidopsis.

Prediction of milk protein content based on improved sparrow search algorithm and optimized back propagation neural network