Highlighting adaptive potential to increase sustainability of maize crop through landscape genomics

Modern agriculture's greatest challenge lies in climate change, as the\r\nlatter has significant impacts on agricultural systems through global\r\nwarming, altered rainfall patterns, and increased frequency and intensity\r\nof extreme events. Maize, as a globally significant crop, is projected to\r\nbe highly susceptible to climate change across Europe. To establish a more\r\neffective cropping system and develop resilient genotypes, existing market\r\nhybrids are inadequate due to their limited genetic diversity. In contrast,\r\nmaize landraces - adapted to diverse agroecological conditions - can offer\r\ninvaluable indigenous germplasm as a promising foundation for future\r\ngenetic enhancements.\r\nThe present research aims to achieve two objectives: a comprehensive study\r\nand genotyping of 28 Italian landraces, and the identification of genetic\r\nmarkers likely to be associated with environmental variables. Selected\r\nlandraces from Lombardia, Emilia Romagna, Trentino-Alto Adige, Veneto,\r\nToscana, Valle d’Aosta and Friuli Venezia Giulia were analysed using the\r\nGBS technique. Subsequent population studies were conducted based on the\r\nsequencing data, revealing 12 ancestral populations in the admixture\r\nanalysis. Together with prominent and well-defined populations, including\r\nNostrano Val Tidone, Châtillon and Entrebin, there are completely admixed\r\ngroups comprising varieties from Trentino, Emilia Romagna, and Toscana,\r\nmaking it challenging to identify a singular reference population. The high\r\ndegree of genetic fragmentation is reflected in the phylogenetic tree,\r\nwhich does not follow regional patterns but clearly distinguishes\r\nindividual varieties. Notably, the Ottofile Mantovano variety stands out as\r\nthe most distinct from all others, aligning with its unique field\r\nphenotype. In the PCA analysis as well, individual populations exhibit\r\nclear differentiation, although specific varietal groups are not\r\ndiscernible. Subsequently, a comprehensive analysis was conducted to\r\ninvestigate local adaptation in relation to the environment, using climatic\r\nvariables spanning a 30-year period (1970-2000). Preliminary findings have\r\nrevealed the identification of SNPs that exhibit strong correlations with\r\nenvironmental factors, indicating the presence of valuable traits for\r\npotential genetic improvement.\r\nIn conclusion, the analyses are consistent and indicate the presence of\r\nsignificant intra-population variability in the germplasm under study.\r\nAdditionally, this collection comprises unique populations derived from\r\nancestral lineages that have not interbred with others. The presence of\r\nadmixed materials aligns with historical cultivation practices prior to\r\nhybridization, where farmers would migrate and cultivate diverse maize\r\nvarieties under territorial continuity, thus facilitating easier crosspollination\r\nbetween distinct materials.\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 n° ECS00000036.