Since its initial release in 2022, ggClusterNet has become a vital tool for microbiome research, enabling microbial co‐occurrence network analysis and visualization in over 300 studies. To address emerging challenges, including multi‐factor experimental designs, multi‐treatment conditions, and multi‐omics data, we present a comprehensive upgrade with four key components: (1) A microbial co‐occurrence network pipeline integrating network computation (Pearson/Spearman/SparCC correlations), visualization, topological characterization of network and node properties, multi‐network comparison with statistical testing, network stability (robustness) analysis, and module identification and analysis; (2) Network mining functions for multi‐factor, multi‐treatment, and spatiotemporal‐scale analysis, including Facet.Network() and module.compare.m.ts(); (3) Transkingdom network construction using microbiota, multi‐omics, and other relevant data, with diverse visualization layouts such as MatCorPlot2() and cor_link3(); and (4) Transkingdom and multi‐omics network analysis, including corBionetwork.st() and visualization algorithms tailored for complex network exploration, including model_maptree2(), model_Gephi.3(), and cir.squ(). The updates in ggClusterNet 2 enable researchers to explore complex network interactions, offering a robust, efficient, user‐friendly, reproducible, and visually versatile tool for microbial co‐occurrence networks and indicator correlation patterns. The ggClusterNet 2R package is open‐source and available on GitHub (https://github.com/taowenmicro/ggClusterNet).

Chromosome-Level Genome Assembly and Annotation of the Fiber Flax (Linum usitatissimum) Genome

The one-time application of slow-release nitrogen fertilizer can not only reduce the labor input, but also reduce the mechanical input cost, and has the characteristics of slow release and reduce volatilization loss. This research is grounded in a localization trial initiated in 2018, which underwent comprehensive analysis utilizing high-throughput sequencing technology to elucidate the mutual feeding mechanism of slow-release nitrogen fertilizer application rate on microbial community structure, network complexity, and maize yield in different root niches (bulk soil, rhizosphere, and endosphere). Soil characteristics, microbial community composition, and collinear network of different ecological niches under slow-release nitrogen fertilizer were analyzed, and the key core species affecting the stability of the microbial network and the factors driving yield were identified. The results showed that nitrogen application increased the diversity of bacteria, and nitrogen application significantly increased the diversity of rhizosphere bacteria and fungi due to rhizosphere effects. Slow-release nitrogen fertilizer increased the complexity of the bacterial network and decreased the complexity of the fungal network, particularly, the network complexity of bacteria and fungi in the rhizosphere was higher than that in the bulk soil and the rhizosphere. The application of slow-release nitrogen fertilizer increased the abundance of Proteobacteria, Bacteroidota, Gemmatimonadota, Actinobacteria, Ascomycota, Basidiomycota and other dominant bacteria. Coordinate soil physical and chemical properties, increase soil enzyme activity and soil nutrients, improve soil microenvironment, regulate microbial community composition, and promote above-ground yield increase, in which nitrogen application, urease, nitrate reductase and nitrate nitrogen are the main driving factors for yield increase. These findings provide a new idea for the mutual feeding mechanism of slow-release nitrogen fertilizer on microbial diversity and yield in different ecological niches. To selection of suitable nitrogen application rate and regional ecological security in the agro-pastoral ecotone.It offers a theoretical framework for establishing optimal nitrogen application rates and ensuring food security in agro-pastoral ecotones.

To investigate the salt tolerance of Populus talassica × Populus euphratica, morphological and physiological parameters were measured on the second day after the 15th, 30th and 45th days of NaCl treatment, revealing significant effects of NaCl on growth. To further elucidate the mechanisms underlying salt tolerance, transcriptomic and metabolomic analysis were conducted under different NaCl treatments. The results of morphological and physiological indexes showed that under low salt treatment, P. talassica × P. euphratica was able to coordinate the growth of aboveground and belowground parts. Under high salt concentration, the growth and water balance of P. talassica × P. euphratica were markedly inhibited. The most significant differences between treatments were observed on the second day after the 45th day of NaCl treatment. Transcriptomic analysis showed that the pathways of gene enrichment in the roots and stems of P. talassica × P. euphratica were different in the salt resistance response. And it involves several core pathways such as plant hormone signal transduction, phenylpropanoid biosynthesis, MAPK signaling pathway-plant, plant- pathogen interaction, carbon metabolism, biosynthesis of amino acids, and several key Transcription factors (TFs) such as AP2/ERF, NAC, WRKY and bZIP. Metabolomic analysis revealed that KEGG pathway enrichment analysis showed unique metabolic pathways were enriched in P. talassica × P. euphratica under both 200 mM and 400 mM NaCl treatments. Additionally, while there were some differences in the metabolic pathways enriched in the roots and stems, both tissues commonly enriched pathways related to the biosynthesis of secondary metabolites, biosynthesis of cofactors, biosynthesis of amino acids, flavonoid biosynthesis, and ABC transporters. Association analysis further indicated that biosynthesis of amino acids and plant hormone signal transduction pathway play key roles in the response of P. talassica × P. euphratica to salt stress. The interactions between the differentially expressed genes (DEGs) and several differentially accumulated metabolites (DAMs), especially the strong association between LOC105124002 and Jasmonoyl-L-Isoleucine (pme2074), were again revealed by the interactions analysis. In this study, we resolved the changes of metabolic pathways in roots and stems of P. talassica × P. euphratica under different NaCl treatments and explored the associations between characteristic DEGs and DAMs, which provided insights into the mechanisms of P. talassica × P. euphratica in response to salt stress.

The yellow nutsedge (Cyperus esculentus L. 1753) is an unconventional oil plant with oil-rich tubers, and a potential alternative for traditional oil crops. Here, we reported the first high-quality and chromosome-level genome assembly of the yellow nutsedge generated by combining PacBio HiFi long reads, Novaseq short reads, and Hi-C data. The final genome size is 225.6 Mb with an N50 of 4.3 Mb. More than 222.9 Mb scaffolds were anchored to 54 pseudochromosomes with a BUSCO score of 96.0%. We identified 76.5 Mb (33.9%) repetitive sequences across the genome. A total of 23,613 protein-coding genes were predicted in this genome, of which 22,847 (96.8%) were functionally annotated. A whole-genome duplication event was found after the divergence of Carex littledalei and Rhynchospora breviuscula, indicating the rich genetic resources of this species for adaptive evolution. Several significantly enriched GO terms were related to invasiveness of the yellow nutsedge, which may explain its plastic adaptability. In addition, several enriched Kyoto Encyclopedia of Genes and Genomes pathways and expanded gene families were closely related with substances in tubers, partially explaining the genomic basis of characteristics of this oil-rich tuber.

Crop straw contains huge amounts of exploitable energy, and efficient biomass degradation measures have attracted worldwide attention. Mining strains with high yields of cellulose-degrading enzymes is of great significance for developing clean energy and industrial production of related enzymes. In this study, we reported a high-quality genome sequence of Bacillus velezensis SSF6 strain using high-throughput sequencing technology (Illumina PE150 and PacBio) and assessed its lignocellulose degradation potential. The results demonstrated that the genome of B. velezensis SSF6 was 3.89 Mb and contained 4,015 genes, of which 2,972, 3,831 and 158 genes were annotated in the COGs (Clusters of Orthologous Groups), KEGG (Kyoto Encyclopedia of Genes and Genomes) and CAZyme (Carbohydrate-Active enZymes) databases, respectively, and contained a large number of genes related to carbohydrate metabolism. Furthermore, B. velezensis SSF6 has a high cellulose degradation capacity, with a filter paper assay (FPA) and an exoglucanase activity of 64.48 ± 0.28 and 78.59 ± 0.42 U/mL, respectively. Comparative genomic analysis depicted that B. velezensis SSF6 was richer in carbohydrate hydrolase gene. In conclusion, the cellulose-degrading ability of B. velezensis SSF6 was revealed by genome sequencing and the determination of cellulase activity, which laid a foundation for further cellulose degradation and bioconversion.