LANDSCAPE GENOMICS AND BIG DATA ANALYSIS TO ENHANCE ADAPTABILITY AND SUSTAINABILITY IN MAIZE CULTIVATION

Modern agriculture's greatest challenge is climate change, significantly\r\nimpacting agricultural systems through altered temperature and\r\nprecipitation patterns, and increased frequency and intensity of extreme\r\nevents. Maize, a crucial crop for food security worldwide, is known to be\r\nhighly susceptible to these changes. Landraces represent germplasm of\r\nelection where breeding may source favourable alleles for adaptation. This\r\nresearch aims to identify genetic markers that explain environmental\r\nvariability to support the development of resilient maize genotypes.\r\nSelected landraces from Northern-Central Italy were genotyped using a\r\ndouble digest restriction-site associated DNA (ddRAD-seq) approach,\r\nfollowed by quality filtering for Phred Score, minor allele frequency and\r\nSNP missingness. The sequencing yielded 1,437,328 variants, and the dataset\r\nafter filtering was reduced to 6,002 variants. Finally, an LD-pruned subset\r\nof 2,018 markers was created to represent the collection's diversity.\r\nPartial redundancy analysis was employed to investigate the relation\r\nexisting between climate and genetic variation of the studied materials.\r\nThe analysis used the LD-pruned SNPs as response variables and a set of noncollinear\r\nbioclimatic indicators as dependent variables while controlling\r\nfor genetic structure and geographical origin. Outliers were identified\r\nwith a Bonferroni correction at a 5% nominal p-value threshold. Partial\r\nredundancy analysis revealed that climate, geography, and genetic structure\r\ntogether explained 30% of the genetic variance in our maize landraces.\r\nClimate accounted for 45% of this variation, genetic structure for 31%, and\r\ngeographic coordinates for 11%. Three significantly associated SNPs were\r\nidentified: two of these are localized in two distinct genes,\r\nZm00001eb068470 and Zm00001eb418760, respectively, not yet characterized.\r\nPerforming analysis of chromosome-specific linkage disequilibrium decay, we\r\nestimated windows based on half-decay distance. In the 67 Kb LD-window of\r\nZm00001eb068470, located on chromosome 2, we found Zm00001eb068520, a gene\r\nencoding the APETALA2 protein. AP2/ERFs are crucial transcription factors\r\nin maize, regulating hormone and stress responses, playing, moreover,\r\nsignificant roles in ethylene signalling pathways that affect ear length,\r\nflower number, fertility, and grain yield. They are therefore vital traits\r\nfor maize's adaptation to environmental stresses like flooding and heat,\r\nmaking them essential targets for breeding programs to improve stress\r\ntolerance and ensure stable, high yields under climate change.\r\nThis work is part of the project NODES, which has received funding from the\r\nMUR–M4C2 1.5 of PNRR with grant agreement no. ECS00000036.