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Summary Low grain moisture at harvest is crucial for safe production, transport and storage, but the genetic architecture of this trait in maize (Zea mays) remains elusive. Here, we measured the dynamic changes in grain moisture content in an association‐mapping panel of 513 diverse maize inbred lines at five successive stages across five geographical environments. Genome‐wide association study (GWAS) revealed 71 quantitative trait loci (QTLs) that influence grain moisture in maize. Epistatic effects play vital roles in the variability in moisture levels, even outperforming main‐effect QTLs during the early dry‐down stages. Distinct QTL–environment interactions influence the spatio‐temporal variability of maize grain moisture, which is primarily triggered at specific times. By combining genetic population analysis, transcriptomic profiling and gene editing, we identified GRMZM5G805627 and GRMZM2G137211 as candidate genes underlying major QTLs for grain moisture in maize. Our results provide insights into the genetic architecture of dynamic changes in grain moisture, which should facilitate maize breeding.

The emerging and promising biotechnology methodology of CRISPR/Cas9 gene-editing is revolutionizing crop improvement. However, the low-efficiency, time-consuming, and labor-intensive nature of positive or/and negative selections during or after transformation and subsequent identification of mutations are major challenges for its agricultural application, from upstream (high-throughput) mutant screening to downstream commercial production (He and Zhao, 2020). Although visual markers, and in particular fluorescent markers including green fluorescent protein (GFP) and red fluorescent protein (RFP), have been employed for the rapid visualization of transgenic material (Qi et al., 2020), the integration of cost-effective and non-invasive CRISPR-separation gene-editing tools is still in its infancy but remains critical for crop genetics and breeding (Callaway, 2018). Furthermore, special light sources are required to visualize fluorescent signals, which increases the cost and inconvenience of the application of fluorescence markers, especially in field conditions. We have developed a visualization toolbox, ViMeBox (VIsual Maize Editing toolBox), for the selection of positive transformants in maize (Zea mays). In the ViMeBox system, the vector expressing Cas9 includes a gene cassette containing a visible marker expressed from a tissue-specific promoter; Cas9-free kernels that are easy to separate by the visible marker are also undergoing gene editing. ViMeBox offers two advantages: 1) It enables enhanced expression of DsRED2, which makes seeds containing Cas9 visible to the naked eye in natural light, and does not affect genome editing efficiency or plant development. 2) It is effective for different seed tissues, for example, using embryo-specific promoters or promoters preferentially expressed in the embryo or aleurone. Furthermore, ViMeBox has potential applications in diverse additional scenarios.

In maize (Zea mays), kernel weight is an important component of yield that has been selected during domestication. Many genes associated with kernel weight have been identified through mutant analysis. Most are involved in the biogenesis and functional maintenance of organelles or other fundamental cellular activities. However, few quantitative trait loci (QTLs) underlying quantitative variation in kernel weight have been cloned. Here, we characterize a QTL, qKW9, associated with maize kernel weight. This QTL encodes a DYW motif pentatricopeptide repeat protein involved in C-to-U editing of ndhB, a subunit of the chloroplast NADH dehydrogenase-like complex. In a null qkw9 background, C-to-U editing of ndhB was abolished, and photosynthesis was reduced, resulting in less maternal photosynthate available for grain filling. Characterization of qKW9 highlights the importance of optimizing photosynthesis for maize grain yield production.

Maize (Zea mays) is one of the most important crops in the world. However, few agronomically important maize genes have been cloned and used for trait improvement, due to its complex genome and genetic architecture. Here, we integrated multiplexed CRISPR/Cas9-based high-throughput targeted mutagenesis with genetic mapping and genomic approaches to successfully target 743 candidate genes corresponding to traits relevant for agronomy and nutrition. After low-cost barcode-based deep sequencing, 412 edited sequences covering 118 genes were precisely identified from individuals showing clear phenotypic changes. The profiles of the associated gene-editing events were similar to those identified in human cell lines and consequently are predictable using an existing algorithm originally designed for human studies. We observed unexpected but frequent homology-directed repair through endogenous templates that was likely caused by spatial contact between distinct chromosomes. Based on the characterization and interpretation of gene function from several examples, we demonstrate that the integration of forward and reverse genetics via a targeted mutagenesis library promises rapid validation of important agronomic genes for crops with complex genomes. Beyond specific findings, this study also guides further optimization of high-throughput CRISPR experiments in plants.