Editorial: Multi-omics Strategies to Analyze Complex Agronomic Traits in Plants, Volume II

Guo-Fei Tan^1*Lin Chen²

• ¹Institute of Horticulture, Guizhou Academy of Agricultural Sciences, Guiyang, China
• ²Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China

the transcriptional regulatory landscape of crops. Among these articles, researches focused on the agronomic traits related to plant development, regulatory, and postharvest. The multi-omics strategies, including metabolome, transcriptome, GWAS, BAS-seq and so on. To benefit of the potential readers, the key points of the 7 articles in this research topic were highlighted as follows:Maize is a wide world crop in the world, the photoperiod sensitivity and heterosis is important for maize environmental adaptation and yield. In photoperiod sensitivity, Jiang et al. identify genetics loci and candidate genes for photoperiod sensitivity by integrated GWAS, linkage, and transcriptome analysis. The results showed that a total of 48 quantitative trait loci (QTLs) and 252 quantitative trait nucleotides (QTNs) were detected by linkage population and the inbred association panel, and 13 candidate genes were identified by GWAS, linkage analysis, and transcriptome analysis; MYB163, bif1, burp8, CADR3, and Zm00001d050238 were the candidate genes for photoperiod sensitivity. For maize heterosis under drought stress, Dai et al. using Zhengdan7137 and Zhengdan7153 are two maize hybrid varieties as the materials under well-watering (WW), water-deficit (WD), and re-watering (RW) conditions by RNA-Seq. The results showed that a total of 303 and 252 conservative drought response overdominance genes (DODGs) and underdominance genes (DUDGs) were identified, respectively, and 165 and 267 conservative re-watering response overdominance genes (RODGs) and underdominance genes (RUDGs), respectively. These results provide the important candidate genes for the further molecular mechanism research of photoperiod sensitivity and heterosis und drought stress in maize.Stripe margin pattern and rind color of watermelon peel are the significant traits that affects consumer acceptability. In the peel stripe margin pattern of watermelon, were all increased dramatically and significantly under both moderate and heavy grazing by anatomical analysis. Transcriptome analysis showed that the differentially expressed genes related to different grazing intensities were also engaged in plant cell wall formation and photosynthesis and respiration. This research points out that appropriate grazing density is of great significance for maintaining the normal life growth and development of S. breviflora.Crop breeding entails developing and selecting plant varieties with improved agronomic traits, and the integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. Huo et al. summarized how these omics technologies can be applied to specific agronomic research and breeding improvement, and focus on the transcriptional regulatory/gene regulatory network landscape of crops. This review provide a better understanding of multi omics in improving crop breeding efforts and contribute of global food security.Based on the above articles published in this research topic, the research tactics of complex crop agronomic traits with multi-omics techniques were introduced, which not only requires joint analysis of multiple omics, but also requires analysis of population genetics, morphology, physiology, cells, and other data in order to better conduct comprehensive, accurate, and rapid analysis of complex agronomic traits in plants. With the continuous changes in environmental climate and human needs, the requirements for special agricultural traits of crops in the future are becoming increasingly diverse. We hope that comprehensive analysis of multi-omics can help readers and researchers to study the development needs of omics in the future. We are very grateful for the efforts made by journal editors, peer reviewers, and relevant authors. Without their help, this research topic would not be presented to the readers.We also would like to thank all colleagues who contributed to this research topic. We hope that readers can obtain valuable information from this topic to help them achieve success in the future.