The study used host-mediated artificial selection to iteratively enrich rice-associated microbiomes that improve growth and drought tolerance, starting from diverse soil microbial communities. Over multiple generations, selected microbiomes converged, and amplicon sequencing along with metagenome-assembled genomes identified specific bacterial taxa and functional pathways (e.g., glycerol-3-phosphate and iron transport) linked to enhanced drought performance. The results demonstrate the effectiveness of plant phenotype-driven microbiome engineering for crop improvement.

The study employed computational approaches to characterize the SUMOylation (ULP) machinery in Asian rice (Oryza sativa), analyzing phylogenetic relationships, transcriptional patterns, and protein structures across the reference genome, a population panel, and wild relatives. Findings reveal an expansion of ULP genes in cultivated rice, suggesting selection pressure during breeding and implicating specific ULPs in biotic and abiotic stress responses, providing resources for rice improvement.