| Maize is a globally important crop mainly used as food,feed and industrial raw material,which plays an important role in economic development.In recent years,global warming and growing population have led to increased water scarcity and drought,which have become the main natural disasters to reduce maize yield,causing huge economic losses every year.Therefore,in-depth dissection of the genetic and molecular mechanism of maize drought resistance,identification of new droughtresistance genes and breeding new maize varieties with improved drought resistance are urgent needs to promote the sustainable development of agricultural economy and ensure food security.Drought resistance is a complex quantitative trait that involves many internal or external dynamic responses,but what these responses are and the genetic basis that regulates these responses remains unknown.Accurate identification of phenotypes is essential for maize drought resistance studies.However,there is a "phenotyping bottleneck" in the current measurements to evaluate maize drought phenotype,since the traditional phenotyping of drought tolerance is usually lowthroughput,time-consuming,labor-intensive,low-accuracy and destructive,which seriously hinders the identification of drought resistant phenotypes and the mining of drought resistance resources in maize.In recent years,the rapid development of phenomics technology characterized by intelligence,high-throughput and dynamic non-destructive measurement makes it possible to detect phenotypes in multi-temporal and multi-scale,which can realize the dynamic and accurate identification of phenotypes in the whole growth period of crops,providing a new opportunity to decipher the genetic basis of crop drought resistance and mining crop drought resistance resources.In this study,we used a high-throughput multiple optical phenotyping platform combined with visible light imaging(RGB),hyperspectral imaging(HSI),and X-ray computed tomography(CT)systems to noninvasively phenotype 368 maize genotypes with or without drought stress over a course of 98 days,and finally collected about 14 Tb multiple optical images.Through high-throughput image digital phenotypic extraction and multiple screening methods,10080 image-based traits(i-traits)in response to drought stress were obtained.We found that these i-traits can be used to characterize complex drought resistance quantitative traits.They have abundant variation and high heritability,which are effective evaluation indexes for maize drought resistance,and can be used as indicators to dynamically monitor maize drought response.Using i-traits combined with natural variation in the association mapping population for genome-wide association analysis(GWAS),we identified 4322 significantly associated loci which mapped to 1529 QTLs and 2318 candidate genes,and constructed a regulatory network based on candidate genes and i-traits.QTL colocation analysis revealed that 71.4%(1092/1529)QTLs were co-located with droughtresistant QTLs reported in previous studies.Meanwhile,28 previously identified drought-resistant genes were detected in candidate genes,and 34 hotspot genes associated with multiple i-traits were identified.Subsequently,e QTL analysis of these candidate genes using transcriptome data found that 54.2%(1257/2318)of the candidate genes were regulated by e QTL,and local regulation was more important.In addition,we screened and validated two new genes,Zmc PGM2 and Zm FAB1 A.Zmc PGM2 is associated with the sugar metabolism signaling pathway,and this gene regulates the maize drought resistance by influencing soluble sugar content.Zm FAB1 A is involved in the inositol phosphate metabolism pathway and affects the maize drought resistance.Using transgenic and mutant materials,we demonstrated that Zmc PGM2 and Zm FAB1 A are involved in regulating i-traits and drought resistance in maize.Finally,we found that the drought resistance of maize could be well predicted by using candidate genes and 15 screened i-traits,and they could be used as biomarkers with potential applications in maize drought resistance breeding improvement.In conclusion,we obtained a wealth of drought stress response i-traits through a high-throughput multiple optical phenotyping platform,identified a large number of candidate genes and QTLs by combining with GWAS,and constructed an association network of genes and phenotypes,revealing the dynamic response mechanism of maize under drought stress,and providing new gene resources and a large amount of "genetic treasure" for maize drought-resistant genetic improvement and breeding.Meanwhile,this study also proposed a new idea and method for drought resistance gene mining in maize,which provides a successful example for dissecting the genetic basis of other complex traits in crops. |
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