Salinity is one of the most important abiotic stress factors affecting wheat production. Salt in the soil is a major environmental stressor that can affect the bacterial community in the rhizosphere of wheat. The bacteria in the plant’s rhizosphere promote growth and stress tolerance, which vary by variety and location. Nevertheless, the soil harbors some of the most diverse microbial communities, while the rhizosphere selectively recruits according to the needs of plants in a complex harmonic regulation. The microbial composition and diversity under normal and saline conditions were assessed by comparing the rhizosphere of wheat with soil using 16S rRNA gene amplicon sequencing, highlighting the number of operational taxonomic units (OTUs). Taxonomic analyzes showed that the bacterial community was predominantly and characteristically composed of the phyla Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Verrucomicrobia, and Fibrobacteres, representing the usual microbial profile for the rhizosphere of wheat. Idiomarinaceae, Rheinheimera, Halomonas, and Pseudomonas (a strain of Proteobacteria), together with Gracilibacillus (a strain of Firmicutes Bacilli), were recognized as microbial signatures for the rhizosphere microbiome under saline conditions. This was observed even with unchanged soil type and genotype. These patterns occurred despite the same soil type and genotype, with salinity being the only variable. The collective action of these bacterial phyla in the rhizosphere not only improves nutrient availability but also induces systemic resistance in the plants. This synergistic effect improves plant resistance to salt stress and supports the development of salt-tolerant wheat varieties. These microbial signatures could improve our understanding of plant–microbe interactions and support the development of microbiome-based solutions for salt stress.

Water buffalo (Bubalus bubalis) is an important source of meat and milk in countries with relatively warm weather. Compared to the cattle genome, a little has been done to reveal its genome structure and genomic traits. This is due to the complications stemming from the large genome size, the complexity of the genome, and the high repetitive content. In this paper, we introduce a high-quality draft assembly of the Egyptian water buffalo genome. The Egyptian breed is used as a dual purpose animal (milk/meat). It is distinguished by its adaptability to the local environment, quality of feed changes, as well as its high resistance to diseases. The genome assembly of the Egyptian water buffalo has been achieved using a reference-based assembly workflow. Our workflow significantly reduced the computational complexity of the assembly process, and improved the assembly quality by integrating different public resources. We also compared our assembly to the currently available draft assemblies of water buffalo breeds. A total of 21,128 genes were identified in the produced assembly. A list of milk virgin-related genes; milk pregnancy-related genes; milk lactation-related genes; milk involution-related genes; and milk mastitis-related genes were identified in the assembly. Our results will significantly contribute to a better understanding of the genetics of the Egyptian water buffalo which will eventually support the ongoing breeding efforts and facilitate the future discovery of genes responsible for complex processes of dairy, meat production and disease resistance among other significant traits.

ISHS IV International Symposium on Seed, Transplant and Stand Establishment of Horticultural Crops; Translating Seed and Seedling Physiology into Technology SUGAR BEET GERMINATION: PHENOTYPIC SELECTION AND MOLECULAR PROFILING TO IDENTIFY GENES INVOLVED IN ABIOTIC STRESS RESPONSE

Rhizosphere microbiome engineering is a promising approach that can enhance crop resilience and input use efficiency by redirecting plant–microbe–soil interactions toward predictable functions. Here, we review the mechanistic bases underlying rhizosphere assembly and stability, including root exudate-mediated selection, priority effects, keystone taxa, and metabolite-driven signaling, and connect these principles to proposed design rules for microbial inoculants. We present a generalizable Design–Build–Test–Learn (DBTL) framework for engineering synthetic microbial consortia, covering trait-to-module mapping (nutrient acquisition, phytohormone modulation, ACC deaminase activity, stress-protective metabolites, and biocontrol), compatibility screening, minimal yet robust community architectures, and iterative optimization driven by multi-omics and high-throughput phenotyping. Translation to field settings is framed as an engineering challenge defined by formulation and administration limitations, including carrier type, seed coating and encapsulation methods, shelf life, strain invasiveness, and permanence of colonization amid environmental diversity. We also summarize how integrative measurement pipelines (amplicon and shotgun sequencing, transcriptomics, metabolomics, and network or causal analyses) can advance microbiome studies from correlation to actionability. We describe how precision agriculture (sensors, remote sensing, and variable-rate inputs) and AI/ML (split-sample comparisons, transfer learning, and active learning) approaches can accelerate strain discovery, mixture optimization, and adaptive experimentation, driven by the need for stringent controls, metadata-rich reporting, and cross-site comparability. Use cases focus on stress conditions (drought, salinity, thermal extremes, and biotic stress) to demonstrate how microbial functions translate to agronomic outcomes and to highlight critical bottlenecks for reproducible, scalable microbiome products.

The future bio-economy of dairy industry relies on the identification of an affordable approach for increasing milk production and its constituents. Egyptian buffalo (Bubalus bubalis) contributes by about 50% of total milk production in Egypt, therefore it is considered as an essential dairy animal. This study aimed to differentiate between high and low milk producer buffaloes (Bubalus bubalis) using microsatellite and SCoT markers. The results of the six microsatellite primers showed bands of 350, 377, 496, 247, 262 and 280 bp, where three of which were digested by restriction enzyme. SCoT results of bulked samples showed unique bands that were sequenced and aligned to Bubalus bubalis (taxid: 89462) sequences. Alignment results showed similarity to the following encoding genes, Class V myosin, Ubiquitin-conjugating enzyme E2 D4 and acyl-phosphatase 2 (ACYP2), which play a crucial role in organelle trafficking and many pathways, that may affect milk production traits. These results showed that SCoT marker was better than microsatellite in clarifying the difference between high and low milk producing traits in Egyptian buffalo (Bubalus bubalis).