Panomics is an approach to integrate multiple ‘omics’ datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.

全景组学是一种整合多个“组学”数据集的方法，这些数据集是使用不同个体或自然变异生成的。考虑到其多样化的表型谱，表型组本质上与基于泛组学的科学相关，它进一步与基因组学、转录组学、代谢组学和其他组学技术独立或共同结合。基因组学领域的最新技术进步加速了全景组学的发展，这些技术进步能够检测群体范围的结构变异（SV），从而为重要农艺性状的遗传变异提供前所未有的见解。本综述提供了全景组学驱动的基因发现的最新趋势，涉及与植物发育、胁迫耐受性、专门代谢物的积累以及驯化/非驯化相关的各种性状。此外，这些成功案例在提高作物生产力的更广泛背景下得到了强调。