Understanding how plants interact with their colonizing microbiota to determine plant phenotypes is a fundamental question in modern plant science. Existing approaches for genome-wide association studies (GWAS) are often focused on the association analysis between host genes and the abundance of individual microbes, failing to characterize the genetic bases of microbial interactions that are thought to be important for microbiota structure, organization, and function. Here, we implement a behavioral model to quantify various patterns of microbe-microbe interactions, i.e., mutualism, antagonism, aggression, and altruism, and map host genes that modulate microbial networks constituted by these interaction types. We reanalyze a root-microbiome data involving 179 accessions of Arabidopsis thaliana and find that the four networks differ structurally in the pattern of bacterial-fungal interactions and microbiome complexity. We identify several fungus and bacterial hubs that play a central role in mediating microbial community assembly surrounding A. thaliana root systems. We detect 1142 significant host genetic variants throughout the plant genome and then implement Bayesian networks (BN) to reconstruct epistatic networks involving all significant SNPs, of which 91 are identified as hub QTLs. Results from gene annotation analysis suggest that most of the hub QTLs detected are in proximity to candidate genes, executing a variety of biological functions in plant growth and development, resilience against pathogens, root development, and abiotic stress resistance. This study provides a new gateway to understand how genetic variation in host plants influences microbial communities and our results could help improve crops by harnessing soil microbes.

Fruit ripening is a crucial stage in quality development, influenced by a diverse array of internal and external factors. Among these factors, epigenetic regulation holds significant importance and has garnered substantial research attention in recent years. Here, this review aims to discuss the breakthrough in epigenetic regulation of tomato (Solanum lycopersicum) fruit ripening, including DNA methylation, N⁶-Methyladenosine mRNA modification, histone demethylation/deacetylation, and non-coding RNA. Through this brief review, we seek to enhance our understanding of the regulatory mechanisms governing tomato fruit ripening, while providing fresh insights for the precise modulation of these mechanisms.

Dysfunctional NF-κB signaling is critically involved in inflammatory bowel disease (IBD). We investigated the mechanism by which RIPK1 and TRADD, two key mediators of NF-κB signaling, in mediating intestinal pathology using TAK1 IEC deficient model. We show that phosphorylation of TRADD by TAK1 modulates RIPK1-dependent apoptosis. TRADD and RIPK1 act cooperatively to mediate cell death regulated by TNF and TLR signaling. We demonstrate the pathological evolution from RIPK1-dependent ileitis to RIPK1- and TRADD-co-dependent colitis in TAK1 IEC deficient condition. Combined RIPK1 inhibition and TRADD knockout completely protect against intestinal pathology and lethality in TAK1 IEC KO mice. Furthermore, we identify distinctive microbiota dysbiosis biomarkers for RIPK1-dependent ileitis and TRADD-dependent colitis. These findings reveal the cooperation between RIPK1 and TRADD in mediating cell death and inflammation in IBD with NF-κB deficiency and suggest the possibility of combined inhibition of RIPK1 kinase and TRADD as a new therapeutic strategy for IBD.

The aroma, taste, and flavour profiles of mango cultivars vary, directly influencing their marketability and consumer acceptance. In this study, we explored the effects of volatile organic compounds (VOCs) on the distinct aromas of two mango cultivars during storage using GC-IMS and HS-SPME-GC-MS combined with OPLS-DA analysis. Our findings revealed that the terpene and aldehyde contents were higher in the ‘Tainong’ mango cultivar, compared to the ‘Hongyu’ mango, while the ester content was lower. The aroma was attributed to the presence of terpinolene, 2-nonenal, delta-carene, and alpha-phellandrene in the early stages of storage, and later—between 5 and 11 days—to ethyl acetate, ethyl butyrate, and ethyl propanoate. Further analysis of characteristic VOCs using OPLS-DA demonstrated and explained the strong grassy aroma of the ‘Tainong’ mango, and the strong fruity and sweet aromas of the ‘Hongyu’ mango. Additionally, esters mainly accumulated during the later periods of storage, especially propyl butyrate, which was produced and accumulated when fruit quality deteriorated in the later storage period. Our study provides a theoretical basis for detecting mango VOCs during storage to determine the appropriate marketing time for the two mango cultivars and enables informed consumer choice.

As an important member of the plant receptor-like kinases, Catharanthus roseus receptor-like kinase 1-like (CrRLK1L) plays vital roles in plant growth and development, as well as biotic and abiotic stress response. Numerous CrRLK1Ls have been identified and analyzed in various plant species, while our knowledge about eggplant (Solanum melongena L.) CrRLK1Ls is still scarce. Utilizing state-of-the-art genomic data, we conducted the first genome-wide identification and analysis of CrRLK1L proteins in eggplant. In this study, 32 CrRLK1L proteins were identified and analyzed in eggplant. A subsequent gene structure and protein domain analysis showed that the identified eggplant CrRLK1Ls possessed typical features of CrRLK1Ls. A subcellular localization prediction demonstrated that these proteins mostly localized on the plasma membrane. A collinearity analysis showed that some eggplant CrRLK1L genes had predicted intraspecies or interspecies evolutionary duplication events. Promoter analysis suggests that eggplant CrRLK1Ls may be involved in plant hormone signaling, host–pathogen interactions, and environmental responses. Based on transcriptomic gene expression analysis, it is indicated that eggplant CrRLK1Ls may be involved in the resistance response of eggplant to Botrytis cinerea. Together, these results will give us a theoretical foundation and guidance for elaborating the biological functions of CrRLK1Ls in eggplant growth, development, and resistance response.

Summary: Long noncoding RNAs (lncRNAs) are critical regulators of numerous biological processes in plants. Nevertheless, their identification is challenging due to the low sequence conservation across various species. Existing computational methods for lncRNA identification often face difficulties in generalizing across diverse plant species, highlighting the need for more robust and versatile identification models. Here, we present PlantLncBoost, a novel computational tool designed to improve the generalization in plant lncRNA identification. By integrating advanced gradient boosting algorithms with comprehensive feature selection, our approach achieves both high accuracy and generalizability. We conducted an extensive analysis of 1662 features and identified three key features – ORF coverage, complex Fourier average, and atomic Fourier amplitude – that effectively distinguish lncRNAs from mRNAs. We assessed the performance of PlantLncBoost using comprehensive datasets from 20 plant species. The model exhibited exceptional performance, with an accuracy of 96.63%, a sensitivity of 98.42%, and a specificity of 94.93%, significantly outperforming existing tools. Further analysis revealed that the features we selected effectively capture the differences between lncRNAs and mRNAs across a variety of plant species. PlantLncBoost represents a significant advancement in plant lncRNA identification. It is freely accessible on GitHub ( https://github.com/xuechantian/PlantLncBoost ) and has been integrated into a comprehensive analysis pipeline, Plant‐LncRNA‐pipeline v.2 ( https://github.com/xuechantian/Plant‐LncRNA‐pipeline‐v2 ).