Integration of multi-omics technologies for crop improvement: Status and prospects - Zhang, Ru; Zhang, Cuiping; Yu, Chengyu; Dong, Jungang; Hu, Jihong (Frontiers in Bioinformatics, 2022)
With the rapid development of next-generation sequencing (NGS), multi-omics techniques have been emerging as effective approaches for crop improvement. Here, we focus mainly on addressing the current status and future perspectives towards omics-related technologies, bioinformatic resources with potential applications in crop breeding. Using large amount of omics-level data from the functional genome, transcriptome, proteome, epigenome, metabolome and microbiome, clarifying the interaction between gene and phenotype formation will become possible. The integration of multi-omics datasets with pan-omics platform and systems biology could predict the complex traits of crops and elucidate the regulatory regulating networks for genetic improvement. Different scales of trait predictions and decision-making models will facilitate the crop breeding more intelligent. Potential challenges that integrate the multi-omics data with studies of gene function and their network to efficiently select desirable agronomic traits are discussed with proposing some cutting edge breeding strategies for crop improvement. Multi-omics-integrated approaches together with other artificial intelligence techniques will contribute to broaden and deepen our knowledge for crop precision breeding, resulting in speed up the breeding process.