Genome-wide association study and genomic prediction of root system architecture in a diverse field-grown maize panel

Root system architecture (RSA) plays a pivotal role in nutrient acquisition, water uptake, lodging resistance, and environmental adaptation in maize (Zea mays L.). However, the genetic basis of RSA at the mature stage under field conditions remains poorly characterized, primarily owing to the challenges of high-throughput phenotyping. In this study, RSA-related traits were evaluated in a diverse maize association panel across four field environments using Shovelomics combined with manual measurements. Genome-wide association analysis (GWAS) was performed using the BLINK and 3VmrMLM models, identifying four main-effect loci consistently detected by both methods and three additional loci exhibiting significant QTN-by-environment interactions (QEIs).Notably, SNP AX-90556586 on chromosome 9 was consistently associated with nodal and crown root number across environments. Its candidate gene encodes a leucine-rich repeat receptor-like serine/threonine-protein kinase with similarity to BRI1/SOBIR1-like proteins, implicating hormone-mediated root development. Genomic prediction revealed that marker subsets enriched for significant loci enhanced within-population prediction, whereas genome-wide markers better captured the polygenic architecture required for robust cross-population prediction. These findings provide insights into the genetic architecture and environmental responsiveness of maize RSA and offer genomic resources for improving root traits in breeding programs.