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Genome-wide association (GWA) studies can identify quantitative trait loci (QTL) putatively underlying traits of interest, and nested association mapping (NAM) can further assess allelic series. Near-isogenic lines (NILs) can be used to characterize, dissect and validate QTL, but the development of NILs is costly. Previous studies have utilized limited numbers of NILs and introgression donors. We characterized a panel of 1270 maize NILs derived from crosses between 18 diverse inbred lines and the recurrent inbred parent B73, referred to as the nested NILs (nNILs). The nNILs were phenotyped for flowering time, height and resistance to three foliar diseases, and genotyped with genotyping-by-sequencing. Across traits, broad-sense heritability (0.4-0.8) was relatively high. The 896 genotyped nNILs contain 2638 introgressions, which span the entire genome with substantial overlap within and among allele donors. GWA with the whole panel identified 29 QTL for height and disease resistance with allelic variation across donors. To date, this is the largest and most diverse publicly available panel of maize NILs to be phenotypically and genotypically characterized. The nNILs are a valuable resource for the maize community, providing an extensive collection of introgressions from the founders of the maize NAM population in a B73 background combined with data on six agronomically important traits and from genotyping-by-sequencing. We demonstrate that the nNILs can be used for QTL mapping and allelic testing. The majority of nNILs had four or fewer introgressions, and could readily be used for future fine mapping studies. ; NSF PGRP grantNational Science Foundation (NSF)NSF - Office of the Director (OD) [1127076] ; This work was partially funded by NSF PGRP grant #1127076. The authors thank Greg Marshall, Judith Kolkman and Molly Towne for technical and logistic support. The authors also thank Denise Costich and the CIMMYT Germplasm Bank for originally providing the nNIL seed. The authors also acknowledge the staff at the Central Crops Research Station in Clayton, NC for field trial management, the Cornell University Computational Biology Service Unit for providing computational resources, and Detlef Weigel and Hernan Burbano at the Max Planck Institute for Developmental Biology for desk space. ; Public domain authored by a U.S. government employee

This open access book is the result of an expert panel convened by the Cornell Atkinson Center for Sustainability and Nature Sustainability. The panel tackled the seventeen UN Sustainable Development Goals (SDGs) for 2030 head-on, with respect to the global systems that produce and distribute food. The panel's rigorous synthesis and analysis of existing research leads compellingly to multiple actionable recommendations that, if adopted, would simultaneously lead to healthy and nutritious diets, equitable and inclusive value chains, resilience to shocks and stressors, and climate and environmental sustainability.