BACKGROUND:Citrus canker is a significant bacterial disease caused by Xanthomonas citri subsp. citri (Xcc) that severely impedes the healthy development of the citrus industry. Especially when citrus fruit is infected by Xcc, it will reduce or even lost its commercial value. However, due to the prolonged fruiting cycle and intricate structure, much less research progress had been made in canker disease on fruit than on leaf. In fact, limited understanding has been achieved on canker development and the response to Xcc infection in fruit.RESULTS:Herein, the progression of canker disease on sweet orange fruit was tracked in the field. Results indicated that typical lesions initially appear on the sepal, style residue, nectary disk, epicarp, and peduncle of young fruits after petal fall. The susceptibility of fruits to Xcc infection diminished as the fruit developed, with no new lesions forming at the ripening stage. The establishment of an efficient method for inoculating Xcc on fruit as well as the artificial inoculation throughout the fruit's developmental cycle clarified this infection pattern. Additionally, microscopic observations during the infection process revealed that Xcc invasion caused structural changes on the surface and cross-section of the fruit.CONCLUSIONS:An efficient system for inoculation on citrus fruit with Xcc was established, by which it can serve for the evaluation of citrus germplasm for canker disease resistance and systematic research on the interactions between Xcc and citrus fruits.

Dear Editor, Advances in high-throughput omics technologies,along with methodologies for integrating multi-omics datasets,have sub-stantially enhanced the efficiency of identifying candidate genes in breeding(Gusev et al.,2018;Gupta et al.,2019).However,this process is often complex and laborious.To address this challenge,databases that integrate extensive data and enable convenient and efficient functional genomics studies are being developed(Ma et al.,2021;Yang et al.,2023).Brassica juncea(B.juncea),commonly known as mustard,is an economically significant agricultural species with diverse uses as a vegetable,resilient oilseed crop,and source of distinctively flavored condiments(Yang et al.,2018).This diversity of applications has spurred the accumulation of substantial multi-omics data in funda-mental research on mustard,but there has not been a specialized platform to fully harness these data for the genetic improvement of mustard.To address this gap,we have developed BjuIR(Brassica juncea Information Resource,available at ),which integrates the most comprehensive mustard omics datasets to date from over 2000 accessions,including genomic,variomic,transcriptomic,phenomic,and metabolomic data.BjuIR provides sophisticated analyses for these mustard multi-omics datasets with user-friendly interfaces,enabling rapid querying of"variant/gene expression-phenotype"associations for rapid identification of candidate genes and greatly benefiting functional genomics research.

Members of the Metal Tolerance Protein (MTP) family are critical in mediating the transport and tolerance of divalent metal cations. Despite their significance, little is known about the MTP genes in mustard (Brassica juncea), particularly in relation to how they react to HM stress. In our study, we identified MTP gene sets in Brassica rapa (17 genes), Brassica nigra (18 genes), and B. juncea (33 genes) using the HMMER tool (Cation_efflux; PF01545) and BLAST analysis. Then, for the 33 BjMTPs, we carried out a detailed bioinformatics analysis covering the physicochemical properties, phylogenetic relationships, conserved motifs, protein structures, collinearity, spatiotemporal RNA-seq expression, GO enrichment, and expression profiling under six HM stresses (Mn2+, Fe2+, Zn2+, Cd2+, Sb3+, and Pb2+). According to the findings of physicochemical characteristics and phylogenetic tree, the allopolyploid B. juncea’s MTP genes were inherited from its progenitors, B. rapa and B. nigra, with minimal gene loss during polyploidization. The BjMTP gene family exhibited conserved motifs, promoter elements, and expression patterns that aligned with seven evolutionary branches (G1, G4-G9, and G12). Further, by co-expression analysis, the core and gene-specific expression modules of BjMTPs under six HM stresses were found. The HM treatments exhibited consistently upregulated of BjA04.MTP4, BjA09.MTP10, and BjB01.MTP5 genes, indicating their critical roles in enhancing HM tolerance in B. juncea. These discoveries may contribute to a genetic improvement in B. juncea's HM tolerance, which would facilitate the remediation of HM-contaminated areas.

Since the official release of the stand-alone bioinformatics toolkit TBtools in 2020, its superior functionality in data analysis has been demonstrated by its widespread adoption by many thousands of users and references in more than 5000 academic articles. Now, TBtools is a commonly used tool in biological laboratories. Over the past 3 years, thanks to invaluable feedback and suggestions from numerous users, we have optimized and expanded the functionality of the toolkit, leading to the development of an upgraded version—TBtools-II. In this upgrade, we have incorporated over 100 new features, such as those for comparative genomics analysis, phylogenetic analysis, and data visualization. Meanwhile, to better meet the increasing needs of personalized data analysis, we have launched the plugin mode, which enables users to develop their own plugins and manage their selection, installation, and removal according to individual needs. To date, the plugin store has amassed over 50 plugins, with more than half of them being independently developed and contributed by TBtools users. These plugins offer a range of data analysis options including co-expression network analysis, single-cell data analysis, and bulked segregant analysis sequencing data analysis. Overall, TBtools is now transforming from a stand-alone software to a comprehensive bioinformatics platform of a vibrant and cooperative community in which users are also developers and contributors. By promoting the theme "one for all, all for one", we believe that TBtools-II will greatly benefit more biological researchers in this big-data era.

The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.

Summary: Rapid development of high-throughput sequencing (HTS) techniques has led biology into the “big-data” era. Data analysis using various bioinformatics softwares or pipelines relying on programming and command-line environment is challenging and time-consuming for most wet-lab biologists. Bioinformatics tools with a user-friendly interface are preferred. Here, we present TBtools (a Toolkit for Biologists integrating various biological data handling tools), a stand-alone software with a user-friendly interface. It has powerful data handling engines for both bulk sequence processing and interactive data visualization. It includes a large collection of functions, which may facilitate much simple, routine but elaborate work on biological data, such as bulk sequence extraction, gene set enrichment analysis, Venn diagram preparation, heatmap illustration, comparative sequence visualization, etc. Availability and implementation: TBtools is a platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases. Contact