Structure-function relation of cytokinins determines their differential efficiency in mediating tobacco resistance against Pseudomonas syringae.

The classic plant growth-promoting phytohormone cytokinin has been identified and established as a mediator of pathogen resistance in different plant species. However, the resistance effect of structurally different cytokinins appears to vary and may regulate diverse mechanisms to establish resistance. Hence, we comparatively analysed the impact of six different adenine- and phenylurea-type cytokinins on the well-established pathosystem Nicotiana tabacum-Pseudomonas syringae.

Soil pH, developmental stages and geographical origin differently influence the root metabolomic diversity and root-related microbial diversity of from native habitats.

Improved understanding of the complex interaction between plant metabolism, environmental conditions and the plant-associated microbiome requires an interdisciplinary approach: Our hypothesis in our multiomics study posited that several environmental and biotic factors have modulating effects on the microbiome and metabolome of the roots of wild plants. Furthermore, we postulated reciprocal interactions between the root metabolome and microbiome. We investigated the metabolic content, the genetic variability, and the prokaryotic microbiome in the root systems of wild plants at rosette and flowering stages across six distinct locations.

Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding.

Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in high-throughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods.

Holomics - a user-friendly R shiny application for multi-omics data integration and analysis.

An organism's observable traits, or phenotype, result from intricate interactions among genes, proteins, metabolites and the environment. External factors, such as associated microorganisms, along with biotic and abiotic stressors, can significantly impact this complex biological system, influencing processes like growth, development and productivity. A comprehensive analysis of the entire biological system and its interactions is thus crucial to identify key components that support adaptation to stressors and to discover biomarkers applicable in breeding programs or disease diagnostics.