Identifying mechanisms and pathways involved in gene-environment interplay and phenotypic plasticity is a long-standing challenge. It is highly desirable to establish an integrated framework with an environmental dimension for complex trait dissection and prediction. A critical step is to identify an environmental index that is both biologically relevant and estimable for new environments. With extensive field-observed complex traits, environmental profiles, and genome-wide single nucleotide polymorphisms for three major crops (maize, wheat, and oat), we demonstrated that identifying such an environmental index (i.e., a combination of environmental parameter and growth window) enables genome-wide association studies and genomic selection of complex traits to be conducted with an explicit environmental dimension. Interestingly, genes identified for two reaction-norm parameters (i.e., intercept and slope) derived from flowering time values along the environmental index were less colocalized for a diverse maize panel than for wheat and oat breeding panels, agreeing with the different diversity levels and genetic constitutions of the panels. In addition, we showcased the usefulness of this framework for systematically forecasting the performance of diverse germplasm panels in new environments. This general framework and the companion CERIS-JGRA analytical package should facilitate biologically informed dissection of complex traits, enhanced performance prediction in breeding for future climates, and coordinated efforts to enrich our understanding of mechanisms underlying phenotypic variation.

The frequency of heat stress events is expected to increase, further complicating the challenge of feeding a growing population. A better understanding of the genetic and molecular mechanisms of heat stress tolerance in maize (Zea mays L.) would facilitate the development of heat‐tolerant cultivars. To address this knowledge gap, we evaluated two biparental recombinant inbred line (RIL) populations (B73 × NC350 and B73 × CML103) for leaf and tassel heat tolerance traits. Two foliar traits, leaf firing and leaf blotching, were evaluated at three vegetative growth stages. In B73 × NC350, two tassel traits, tassel blasting and reduction in spikelet size, were scored at flowering. We detected 22 quantitative trait loci (QTL), 15 in B73 × NC350 and seven in B73 × CML103. We previously observed that the development of leaf firing was differentiable between parents, and indeed, the different manifestations of the leaf firing trait were not significantly correlated and QTL did not co‐localize. Leaf firing and leaf blotching traits were correlated at some vegetative growth stages, and most QTL did not co‐localize. Quantitative trait loci number and position for traits measured at multiple vegetative stages were generally consistent. There was a single QTL for tassel blasting on chromosome 5. Heat‐induced plant death segregated in B73 × CML103 and a major QTL was detected on chromosome 3, explaining 26.2% of phenotypic variance. Our study indicates that complex genetic mechanisms underlie the heat stress response in maize.

Tomato (Solanum lycopersicum L.) is the second most-consumed vegetable in the world. The market value and culinary purpose of tomato are often determined by fruit size and shape, which makes the genetic improvement of these traits a priority for tomato breeders. The main objective of the study was to detect quantitative trait loci (QTL) associated with the tomato fruit shape and size. The use of elite breeding materials in the genetic mapping studies will facilitate the detection of genetic loci of direct relevance to breeders. We performed QTL analysis in an intra-specific population of tomato developed from a cross between two elite breeding lines NC 30P × NC-22L-1(2008) consisting of 110 recombinant inbred lines (RIL). The precision software Tomato Analyzer (TA) was used to measure fruit morphology attributes associated with fruit shape and size traits. The RIL population was genotyped with the SolCAP 7720 SNP array. We identified novel QTL controlling elongated fruit shape on chromosome 10, explaining up to 24% of the phenotypic variance. This information will be useful in improving tomato fruit morphology traits.