Trends in Plant Science最新文献

With growing evidence that genomic selection (GS) improves genetic gains in plant breeding, it is timely to review the key factors that improve its efficiency. In this feature review, we focus on the statistical machine learning (ML) methods and software that are democratizing GS methodology. We outline the principles of genomic-enabled prediction and discuss how statistical ML tools enhance GS efficiency with big data. Additionally, we examine various statistical ML tools developed in recent years for predicting traits across continuous, binary, categorical, and count phenotypes. We highlight the unique advantages of deep learning (DL) models used in genomic prediction (GP). Finally, we review software developed to democratize the use of GP models and recent data management tools that support the adoption of GS methodology.

To address the persistent challenge of cell death spread and limitation during effector-triggered immunity (ETI), we propose a 'concentric circle' model. This model outlines a regulatory framework, integrating multiple cells and diverse signaling molecules, including salicylic acid (SA), jasmonic acid (JA), and Ca²⁺. By accounting for the varying concentrations and spatiotemporal distributions of these molecules, our model aims for precision in immune defense and regulated cell death. To validate this model, a pathosystem-triggering ETI without pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) is required. Here, we review potential ETI elicitors, including victorin, thaxtomin A, and second messengers. We anticipate that future discovery of 'pure' ETI-triggering effectors will provide deeper insights into the transcellular regulation of immune response in plants.

Plant cryptochromes (CRYs) are photolyase-like blue-light receptors that contain a flavin adenine dinucleotide (FAD) chromophore. In plants grown in darkness, CRYs are present as monomers. Photoexcited CRYs oligomerize to form homo-tetramers. CRYs physically interact with non-constitutive or constitutive CRY-interacting proteins to form the non-constitutive or constitutive CRY complexes, respectively. The non-constitutive CRY complexes exhibit a different affinity for CRYs in response to light, and act by a light-induced fit (lock-and-key) mechanism. The constitutive CRY complexes have a similar affinity for CRYs regardless of light, and act via a light-induced liquid-liquid phase separation (LLPS) mechanism. These CRY complexes mediate blue-light regulation of transcription, mRNA methylation, mRNA splicing, protein modification, and proteolysis to modulate plant growth and development.

Botrytis cinerea is an important generalist fungal plant pathogen that causes great economic losses. Conventional detection methods to identify B. cinerea infections rely on visual assessments, which are error prone, subjective, labor intensive, hard to quantify, and unsuitable for artificial intelligence (AI) and machine learning (ML) applications. New, often camera-based, techniques provide objective digital data by remote and proximal sensing. We detail the B. cinerea infection process and link this with conventional and novel detection methods. We evaluate the effectiveness of current digital phenotyping methods to detect, quantify, and classify disease symptoms for disease management and breeding for resistance. Finally, we discuss the needs, prospects, and challenges of digital camera-based phenotyping.

Recent research indicates an involvement of microautophagy in the uptake of seed storage proteins (SSPs) into the plant-specific protein storage vacuole (PSV), particularly in cereal grains. However, because microautophagy plays a vital role in cellular homeostasis by degrading and recycling cellular components, we question whether it is a suitable term for a process involved in long-term storage. Additionally, because fission-type microautophagy shares mechanistic similarities with the intraluminal vesicle (ILV) formation of multivesicular bodies (MVBs), we draw parallels between microautophagy and membrane remodeling facilitated by the endosomal sorting complex required for transport (ESCRT). Finally, we propose that the complex structure of cereal endosperm is an optimal tissue to study microautophagy in a plant- and tissue-specific context to decipher its molecular regulation in anabolism and catabolism.

In the past decade, precise genome editing has transitioned from theory to practical application. Yet, plastid genomes have largely remained impervious to these advances. A recent breakthrough by Mok et al. (2024) demonstrated successful plastid genome editing by developing transgene-free atrazine-resistant arabidopsis (Arabidopsis thaliana) plants.

A recent study conducted by Hu et al. has provided novel insights into the perception of strigolactone (SL). These findings offer a comprehensive understanding of activation, termination, and regulation mechanisms involved in SL perception, all of which are crucial for the adaptation of plant architecture to fluctuations in nitrogen availability.

The study by Zhang et al. demonstrated that two kinases (SlCDPK27 and SlCDPK26) regulate the sugar content in tomato fruits with little impact on morphology. They act as sugar breaks by phosphorylating a sucrose synthase, promoting its degradation and unveiling the mechanism by which sugar content can be increased without yield penalty.