It is difficult for beginners to learn and use amplicon analysis software because there are so many software tools to choose from, and all of them need multiple steps of operation. Herein, we provide a cross‐platform, open‐source, and community‐supported analysis pipeline EasyAmplicon. EasyAmplicon has most of the modules needed for an amplicon analysis, including data quality control, merging of paired‐end reads, dereplication, clustering or denoising, chimera detection, generation of feature tables, taxonomic diversity analysis, compositional analysis, biomarker discovery, and publication‐quality visualization. EasyAmplicon includes more than 30 cross‐platform modules and R packages commonly used in the field. All steps of the pipeline are integrated into RStudio, which reduces learning costs, keeps the flexibility of the analysis process, and facilitates personalized analysis. The pipeline is maintained and updated by the authors and editors of WeChat official account “Meta‐genome.” Our team will regularly release the latest tutorials both in Chinese and English, read the feedback from users, and provide help to them in the WeChat account and GitHub. The pipeline can be deployed on various platforms, and the installation time is less than half an hour. On an ordinary laptop, the whole analysis process for dozens of samples can be completed within 3 h. The pipeline is available at GitHub (https://github.com/YongxinLiu/EasyAmplicon) and Gitee (https://gitee.com/YongxinLiu/EasyAmplicon).

ImageGP is an extensively utilized, open‐access platform for online data visualization and analysis. Over the past 7 years, it has catered to more than 700,000 usages globally, garnering substantial user feedback. The updated version, ImageGP 2 (available at https://www.bic.ac.cn/BIC), introduces a redesigned interface leveraging cutting‐edge web technologies to enhance functionality and user interaction. Key enhancements include the following: (i) Addition of modules for data format transformation, facilitating operations such as matrix merging, subsetting, and transformation between long and wide formats. (ii) Streamlined workflows with features like preparameter selection data validation and grouping of parameters with similar attributes. (iii) Expanded repertoire of visualization functions and analysis tools, including Weighted Gene Co‐Expression Network Analysis, differential gene expression analysis, and FASTA sequence processing. (iv) Personalized user space for uploading large data sets, tracking analysis history, and sharing reproducible analysis data, scripts, and results. (v) Enhanced user support through a simplified error debugging feature accessible with a single click. (vi) Introduction of an R package, ImageGP, enabling local data visualization and analysis. These updates position ImageGP 2 as a versatile tool serving both wet‐lab and dry‐lab researchers with expanded capabilities.

The Microbiome Protocols eBook (MPB) serves as a crucial bridge, filling gaps in microbiome protocols for both wet experiments and data analysis. The first edition, launched in 2020, featured 152 meticulously curated protocols, garnering widespread acclaim. We now extend a sincere invitation to researchers to participate in the upcoming 2nd version of MPB, contributing their valuable protocols to advance microbiome research.

Orobanche cumana Wallr. is a holoparasite weed that extracts water and nutrients from its host the sunflower, thereby causing yield reductions and quality losses. However, the number of O. cumana parasites in the same farmland is distinctly different. The roots of some hosts have been heavily parasitized, while others have not been parasitized. What are the factors contributing to this phenomenon? Is it possible that sunflower interroot microorganisms are playing a regulatory role in this phenomenon? The role of the microbial community in this remains unclear. In this study, we investigated the rhizosphere soil microbiome for sunflowers with different degrees of O. cumana parasitism, that is, healthy, light infection, moderate infection, and severe infection on the sunflower roots. The microbial structures differed significantly according to the degree of parasitism, where Xanthomonadaceae was enriched in severe infections. Metagenomic analyses revealed that amino acid, carbohydrate, energy, and lipid metabolism were increased in the rhizosphere soils of severely infected sunflowers, which were attributed to the proliferation of Lysobacter. Lysobacter antibioticus (HX79) was isolated and its capacity to promote O. cumana seed germination and increase the germ tube length was confirmed by germination and pot experiments. Cyclo(Pro‐Val), an active metabolite of strain HX79, was identified and metabolomic and molecular docking approaches confirmed it was responsible for promoting O. cumana seed germination and growth. And we found that Pseudomonas mandelii HX1 inhibited the growth of O. cumana in the host rhizosphere soil. Our findings clarify the role of rhizosphere microbiota in regulating the parasite O. cumana to possibly facilitate the development of a new weed suppression strategy.

Orobanche cumama wallr. is the sunflower root parasitic weed with special life stage in which seed germination and parasitism take place in the soil. In practice, applying microbial agents and trapping crop rotation are utilized separately, or just one of them is selected to control O. cumana. The development of the sunflower industry is severely constrained on the farmland, where there is high density of O. cumana’s seed banks. In this study, two biological control methods were combined to solve the problem of O. cumana parasitism. The bioassay experiment showed that the high concentration fermentation filtrates of Streptomyces rochei D74 could effectively inhibit the germination and growth of the germ tube of O. cumana seeds. As the concentration was increased to 3.1 mg/mL, O. cumana was almost unable to sprout. A two-year pot experiment revealed that the use of D74 agents and sunflower–maize–sunflower rotation together promoted sunflower growth, as shown by the biomass accumulation, plant height, and denser root systems. The combined method resulted in a significant decrease in the number of O. cumana parasitism, compared to one method alone. Additionally, it affected the bacterial community composition of sunflower rhizosphere, mostly leading to an increase in Streptomyces and Brevibacterium and a decrease in Arthrobacter. This experiment, combined with multiple biological control, means significantly reducing the parasitism of O. cumana, which provides an effective foundation for practical application.

Sunflower broomrape (Orobanche cumana Wallr.) has severely restricted the development of the sunflower industry in China, and more efficient and convenient control methods are urgently needed. In this experiment, we investigated the effects of N, P and silica fertilizers on the parasitism rate of O. cumana, as well as on the yield of sunflower and native microbial communities in the field. Firstly, pot experiments were conducted to select the most effective fertilization method and to determine the physiological and biochemical indexes of sunflowers. Subsequently, field application studies were carried out to determine the physiological indexes, yield, O. cumana parasitism on sunflower, and the effect on the indigenous microbial community. The results demonstrate that compared with the CNP treatment (Control), the number of parasites under the N1P5 treatment significantly decreased by 66.15%. The exogenous application of silica can significantly reduce the number of O. cumana parasites. The treatments with N1P5 (N/P = 1:5) and available SiO₂ content higher than 40 mg/kg (NS2, NS3, SF2 and SF3) significantly increased superoxide dismutase (SOD) activity and decreased malondialdehyde (MDA) content in sunflower leaves. In the field, fertilization significantly decreased the number of O. cumana parasites. The S treatment improved the native microbial community structure and enriched beneficial microorganisms, including Vicinamibacteria and Pyrinomonadaceae. Additionally, applying the S treatment significantly increased sunflower yield by 23.82% and crude protein content by 20.20%. In summary, the application of silicon fertilizer can effectively improve the host microbial community, reduce O. cumana parasitism and improve the yield and quality of sunflower.