Triticeae Genomics and Genetics, 2025, Vol.16, No.3, 138-147 http://cropscipublisher.com/index.php/tgg 145 7.3 Prospects of multi-omics integration (transcriptome, metabolome, epigenome) At present, if the genetic improvement of wheat is to make further progress, the integration of multiple omics is probably an inevitable trend. It is difficult to comprehensively explain the complex processes of grain development and quality formation with a single data source. Looking at transcriptomics, metabolomics and epigenomics together not only expands our understanding of regulatory mechanisms, but also helps to discover truly useful biomarkers. In the past, due to cost or technical limitations, omics analysis was mostly confined to a small scale. But now, with the emergence of efficient and economical expression profile analysis methods, research on large groups is no longer out of reach. Meanwhile, spatial transcriptomics and single-molecule techniques are constantly enriching our understanding of gene annotation, and new regulatory elements are thus constantly being discovered (Dong et al., 2015; Wang et al., 2021). If integrated properly, multi-omics can enable breeders to identify more reliable targets, understand how genes and the environment interact, and ultimately breed wheat varieties that are both high-yielding and of high quality, as well as resilient to stress (Liu et al., 2024). 8 Conclusion and Outlook To understand exactly what happens to wheat grains during the grain-filling period, the spatiotemporal transcriptome undoubtedly plays a significant role. This type of research not only sketches out a "timetable" and "spatial map" of gene expression, but also goes further by breaking down the grains by different cell types to identify hundreds of representative marker genes. Regulatory factors like TaABI3-B1 have been confirmed to be directly linked to the size of embryos and grains. And some co-expression modules and conserved motifs have gradually woven a net for regulating yield and quality. These data themselves are of great value. They not only bring us closer to the core of the developmental mechanism but also provide many targets for breeding. But then again, the matter is far from being "concluded". At present, spatial transcriptome technology is still at the "coarse granularity" level. It is considered good if it can be classified into tissue or cell types, but there is still a considerable distance to go to achieve true single-cell resolution. Moreover, although omics integration sounds wonderful, it is actually quite troublesome to implement. Protein, metabolism, and phenotype data are inherently high-dimensional. If they are to be pieced together, it is basically impossible to rely solely on traditional analytical methods. There is another overlooked issue: the data coverage related to the late grouting stage and environmental stress is still scarce, and many conclusions are thus biased. In addition, the lack of unified analytical standards and reference maps makes it difficult to compare different experiments and limits their application to actual breeding. Where should the next work go? At least several directions are very clear. One is to further enhance the precision of spatial expression - single-cell and even subcellular levels are all worth exploring. Another aspect is that the time dimension cannot be overlooked. Grouting must be managed from start to finish, in both favorable and adverse circumstances. Omics integration is not merely a concept. In the future, it is indeed necessary to analyze the transcriptome, proteome, metabolome, epigenome, etc. within the same network. Fortunately, technology is also advancing. For instance, more efficient sequencing methods, more accurate spatial barcode technology, and some new computing tools all make it possible to construct complex and high-resolution maps. Once these resources are established, it is only a matter of time before the key regulatory factors are identified, and precision breeding will truly have a "handle" - not only to produce more and of better quality, but also to better withstand the uncertainties of the future. Acknowledgments I would like to express my gratitude to the reviewers for their valuable feedback, which helped improve the manuscript. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Araya-Flores J., Guzmán C., Matus I., Parada R., Jarpa G., De Camargo A., Shahidi F., and Schwember A., 2020, New findings in amino acid profile and gene expression in contrasting durum wheat gluten strength genotypes during grain filling, Journal of Agricultural and Food Chemistry, 68(20): 5521-5528. https://doi.org/10.1021/acs.jafc.9b07842
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