Plant Molecular Biology最新文献

Legumes are essential for agriculture and food security. Biotic and abiotic stresses pose significant challenges to legume production, lowering productivity levels. Most legumes must be genetically improved by introducing alleles that give pest and disease resistance, abiotic stress adaptability, and high yield potential. The quickest way to develop high-yielding elite legume varieties with long-lasting resistance is to tap into potential resistance alleles present in landraces and wild relatives and exploit them in legume resistance breeding programs using next-generation molecular breeding methods. Most of the reviews focus on the advancements made by genome editing technologies in generating climate-tolerant legumes for breeding. This review discusses the challenges of genome-based editing tools and how the integration of other popular breeding methodologies, such as QTLs and GWAS, as well as computational techniques, can aid in the development of climate-tolerant legume crops. This review highlights genomics-based methodologies and recent advances that make it easier to assess genetic diversity and uncover adaptive genes in legumes. Computational approaches, such as machine learning, are important in mining the breeding-related genes identified by CRISPR and other genomic tools, as well as detecting the key elements and factors that regulate the expression of these genes, which addresses the challenge of developing climate-resilient legume crops.

Plant growth and development are highly regulated processes and are majorly controlled by various environmental factors, whose extreme exposures lead to chronic stress conditions promoting reactive oxygen species (ROS) and carbonyl species (RCS) production. ROS and RCS extensively damage cellular biomolecules and organelles, affecting a plant's development. Emerging reports highlight that the multi-stress responding DJ-1 superfamily proteins are critical in attenuating cytotoxic effects associated with abiotic stress. The current report, validated in yeast and plant models, shows that AtDJ-1C and AtDJ-1E are robust antioxidants that scavenge ROS and improve survival under oxidative stress. Although they lack conventional glyoxalases and do not attenuate the glycation of proteins, AtDJ-1C and AtDJ-1E preserve the GSH pool and regulate redox homeostasis. Moreover, gene expression profiling indicates that levels of AtDJ-1C and AtDJ-1E are rapidly established to counter heat and oxidative stress conditions. Notably, the knockdown of AtDJ-1 C and AtDJ-1E promotes detrimental alterations such as reduced chlorophyll retention, impaired root morphogenesis, and induced sensitivity to heat stress due to ROS elevation. Contrastingly, overexpression of AtDJ-1C and AtDJ-1E improved plant height and rosette formation under physiological conditions. In conclusion, our study unravels the pivotal functions of Arabidopsis thaliana DJ-1C and DJ-1E in governing plant health and survival under heat and oxidative stress conditions.

Teratosphaeria leaf blight disease caused by Teratosphaeria destructans poses a serious threat to Eucalyptus plantations worldwide. The pathogen infects leaves via stomatal penetration from 24 to 72 h after inoculation. Symptoms are visible after two weeks and pathogen sporulation commonly occurs four weeks after inoculation of a susceptible host. We studied the responses of a susceptible Eucalyptus clone during the entire disease cycle to identify susceptibility factors. RNA from healthy and infected leaves was isolated at 3, 14 and 28 days post inoculation. Differential expression and gene enrichment analysis showed that members of the transcription factor family TGA and MYB, involved in the salicylic acid and abscisic acid pathways, and genes involved in these hormone signaling pathways, were up-regulated. Overall, plant defense response pathways were enriched only at the late stage of infection (28 dpi). In contrast, both gene expression and chemical analysis revealed that the synthesis of the major flavonoids in Eucalyptus leaves was enhanced during pathogen infection, while the synthesis of terpenoids and flavan-3-ols declined. The flavonols, rutin and quercetin enhanced spore germination in-vitro while, the terpenoid eucalyptol and the flavan-3-ol catechin inhibited germination. This study provides insights into the molecular and chemical responses at different stages of infection of a susceptible host by T. destructans, thereby improving the current understanding of the pathosystem.

The recognition of translational initiation sites (TISs) offers complementary insights into identifying genes encoding novel proteins or small peptides. Conventional computational methods primarily identify Ribo-seq-supported TISs and lack the capacity of systematic and global identification of TIS, especially for non-AUG sites in plants. Additionally, these methods are often unsuitable for evaluating the importance of mRNA sequence features for TIS determination. In this study, we present TISCalling, a robust framework that combines machine learning (ML) models and statistical analysis to identify and rank novel TISs across eukaryotes. TISCalling generalized and ranks important features common to multiple plant and mammalian species while identifying kingdom-specific features such as mRNA secondary structures and "G"-nucleotide contents. Furthermore, TISCalling achieved high predictive power for identifying novel viral TISs. Importantly, TISCalling provides prediction scores for putative TIS along plant transcripts, enabling prioritization of those of interest for further validation. We offer TISCalling as a command-line-based package [ https://github.com/yenmr/TISCalling ], capable of generating prediction models and identifying key sequence features. Additionally, we provide web tools [ https://predict.southerngenomics.org/TISCalling/ ] for visualizing pre-computed potential TISs, making it accessible to users without programming experience. The TISCalling framework offers a sequence-aware and interpretable approach for decoding genome sequences and exploring functional proteins in plants and viruses.

A storage polysaccharide in the red alga Cyanidioschyzon merolae is semi-amylopectin, a glucan with properties intermediate between noncrystalline glycogen and semicrystalline amylopectin. The debranching enzyme isoamylase plays a crucial role in determining the semicrystalline nature of glucans. In amylopectin-storing organisms, isoamylases consist of the isozymes ISA1, ISA2, and ISA3, with the former two primarily responsible for semicrystallinity. While the semicrystallinity of C. merolae semi-amylopectin is weaker than that of amylopectin, it retains a semicrystalline structure. Based on a previous analysis of isoamylase-deficient strains of C. merolae, the isoform CMI294C is the main contributor to glucan synthesis. Although the biochemical properties of isoamylases involved in amylopectin synthesis have been characterized, those of isoamylases involved in semi-amylopectin synthesis remain largely unknown. Here, we performed a detailed biochemical analysis of CMI294C to gain insights of isoamylases in semi-amylopectin synthesis. Similar to isoamylases in amylopectin-synthesizing organisms, CMI294C hydrolyzes amylopectin more efficiently than glycogen. However, unlike typical isoamylases, CMI294C is uniquely more active against pullulan than against glycogen; and it is strongly inhibited by Zn²⁺. Our results indicate that CMI294C can be potentially used for industrial maltose production due to its enzymatic properties. Overall, our findings provide molecular insights into the isoamylase in glucan structure modulation and enhance our understanding of glucan metabolism in C. merolae.

Paclitaxel is an important natural anticancer drug. Its biosynthesis is very complex and 18 enzymes likely involved have been characterized. However, the regulatory mechanism of these enzyme genes still remains to be elucidated. Here we identified a novel transcription factor in the MYC family of Taxus chinensis TcJAMYC5 function in paclitaxel biosynthesis. TcJAMYC5 was highly expressed in the roots and regulated by MeJA. Transient overexpression of TcJAMYC5 in T. chinensis cambial meristematic cells resulted in a significant increase in paclitaxel and bacctin III content and upregulated expression of nearly all of paclitaxel biosynthesis related genes except T13αOH. Suppression of TcJAMYC5 expression in cambial meristematic cells resulted in a significant decrease in paclitaxel content. TcJAMYC5 could bind to promoters of paclitaxel biosynthesis pathway enzyme genes TASY, DBTNBT and T5αH for directly activating their expression. Taken together, we conclude that TcJAMYC5 is an activator that improves the accumulation of paclitaxel in T. chinensis through a MeJA-medicated signaling pathway.

Global climate change, particularly the increasing frequency and intensity of heat stress, poses a significant threat to crop productivity. Chickpea (Cicer arietinum L.) employs various physiological, biochemical, and molecular mechanisms to cope with elevated temperatures, including maintaining leaf chlorophyll content to preserve the functional integrity of photosystem II (PSII) and enhancing canopy temperature depression to reduce overheating. These traits are crucial for sustaining photosynthetic efficiency, plant health, and yield stability under heat stress. Recent advances in multi-omics approaches-including genomics, transcriptomics, proteomics, and metabolomics-have enhanced our understanding of the genetic basis of heat stress tolerance in chickpea. These tools have facilitated the identification of key genes and molecular pathways involved in heat stress responses. Functional characterization of these genes has provided insights into their roles within the complex metabolic and signaling networks that underpin heat resilience. This review explores integrating conventional and modern breeding technologies with high-throughput phenotyping (HTP) platforms to accelerate genetic gains in chickpea under heat stress. HTP tools enable rapid, precise screening of heat-resilient traits, facilitating early selection of superior genotypes. We also highlight recent genomic advancements, including genome-wide association studies, whole-genome resequencing, and pangenome assemblies, which have uncovered novel structural variants, candidate genes, and haplotypes associated with heat tolerance. Leveraging these resources in conjunction with functional analyses offers new opportunities for breeding climate-resilient chickpea cultivars capable of delivering stable yields and quality under adverse conditions. These developments are crucial for safeguarding chickpea productivity and ensuring global food and nutrition security amid climate change.

Hippophae tibetana is an enigmatic least explored Seabuckthorn species, with exceptional adaptability to sub-zero temperatures in Trans-Himalayan region. This study integrates physiological and transcriptional profiling to understand its unique cold stress resilience. The physiological assessment including chlorophyll content, relative water content, and electrolyte leakage were least affected during the early response (ER) of cold stress as compared to prolonged (PR) and freeze response (FR), which was effectively restored during the recovery phase (RR). Genome-guided de novo assembly yielded 25,176 high-quality unigenes (N50: 2195 bp; BUSCO: 92.9%), with 75.9% functionally annotated using NCBI-nr, Araport11, SwissProt, COG, KEGG, and Pfam databases. Clustering of differentially expressed unigenes revealed ER (4467 DEGs) and RR (4478) grouped distinctly from PR (14,150) and FR (14,528), underscoring significantly heightened transcriptional reprogramming during PR/FR compared to ER/RR. Furthermore, the integration of transcriptional interactome network with GO and KEGG enrichment highlighted ICE1-CBF regulatory network with significant upregulation of Inducer of CBF Expression (ICE1), Cold receptive protein kinase (CRPK1), anti-freeze proteins (AFPs), and pathways like jasmonic acid signaling, carbohydrate metabolism, and membrane stabilization as key to cold tolerance during PR and FR phases. The current study advances our understanding of cold stress resilience in H. tibetana, elucidating its adaptive mechanisms in extreme Trans-Himalayan environments. The comprehensive genomic resources and key candidates identified here may provide a foundation for discovering cold tolerance-associated genome-wide variations in priority crops and plantation species.

Early detection of drought stress is critical for taking timely measures for reducing crop loss before the drought impact becomes irreversible. The subtle phenotypical and physiological changes in response to drought stress are captured by non-invasive imaging techniques and these imaging data serve as valuable resource for machine learning methods to identify drought stress. While convolutional neural networks are in wide use, vision transformers (ViTs) present a promising alternative in capturing long-range dependencies and intricate spatial relationships, thereby enhancing the detection of subtle indicators of drought stress. We propose an explainable deep learning pipeline that leverages the power of ViTs for drought stress detection in potato crops using aerial imagery. We applied two distinct approaches: a synergistic combination of ViT and support vector machine (SVM), where ViT extracts intricate spatial features from aerial images, and SVM classifies the crops as stressed or healthy and an end-to-end approach using a dedicated classification layer within ViT to directly detect drought stress. Our key findings explain the ViT model's decision-making process by visualizing attention maps. These maps highlight the specific spatial features within the aerial images that the ViT model focuses as the drought stress signature. Our findings demonstrate that the proposed methods not only achieve high accuracy in drought stress identification but also shedding light on the diverse subtle plant features associated with drought stress. This offers a robust and interpretable solution for drought stress monitoring for farmers to undertake informed decisions for improved crop management.