EDITORIAL article
Front. Plant Sci.
Sec. Plant Systematics and Evolution
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1623554
This article is part of the Research TopicEvolution of Crop Genomes and Epigenomes Volume IIView all 6 articles
Editorial: Evolution of Crop Genomes and Epigenomes
Provisionally accepted- 1Southwest University, Chongqing, China
- 2Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
- 3Corporación Colombiana de Investigación Agropecuaria, Las Palmas, Rionegro, Gambia
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sequencing, machine learning, and bioinformatics (Cortés & López-Hernández, 2021) have accelerated crop genome research (Corté s et al., 2023), revealing how domestication reshaped genomes/epigenomes (Purugganan, 2022).A deeper understanding of these evolutionary constrains and changes is crucial for developing superior and sustainable crop varieties with enhanced yield, nutritional value, and stress resilience. This Research Topic explores crop genome/epigenome evolution through multi-omics analyses, compiling discoveries across gene families, pathways, and diverse species. This topic comprises five original research articles focusing on the above research areas, viewed 6,301 times by the time of this Editorial. These works enable readers to (i) quantify the scale of divergence and conservation of genomes and epigenomes during crop evolution, (ii) reconstruct the evolutionary history of target gene families and pathways, (iii) expand the paradigm of molecular evolution to acknowledge variable gene expression, gene regulatory and metabolomic profiles into what nowadays can be recognized as multi-omic evolution, (iv) identify patters and causal relationships between genome size, genome duplication/polyploidy, and the occurrence of key evolutionary innovations, and ultimately (v) interpret the metabolomic/phenotypic consequences of genome/epigenome evolution. All insights leverage large-scale multi-omics data with biotech/agricultural applications. analyses revealed significant structural variations and phylogenetic relationships. For instance, the authors found that the mitogenomes exhibited complex, graph-based structures with multiple junctions. They identified a total of 51 unique genes in the mitogenomes, including 32 protein-coding genes (PCGs), 16 tRNA genes, and 3 rRNA genes. Authors also traced the sequences transferred from the chloroplast to the mitogenome, with M. sinensis showing the highest transfer length and proportion. Based on the phylogenetic analysis of 13 conserved mitochondrial PCGs, the authors concluded that N. porphyrocoma was the closest relative to Saccharum. They also unveiled the extensive genomic rearrangements among the mitogenomes, and highlighted the dynamic nature of mitochondrial genome evolution, including gene duplication and loss, with the ATP synthase and cytochrome c synthesis genes being the most conserved likely due to puryfing selection. The significance of this study lies in its contribution to comparative genomic studies and the enrichment of genomic resources relevant to sugarcane breeding. The identification of structural variations and phylogenetic insights directly address the need for more comparative studies and mechanistic understanding of organelle evolution.Ultimately, this study enriches the mitochondrial genomic resources for Saccharinae and provides new insights into the evolution of mitogenomes at the family and genus levels. The findings highlighted in this Research Topic lay the foundation for innovative research in the nascent field of multi-omic evolution. Among the several key areas that warrant further exploration, expanding the species scope is perhaps the most imperative.The studies presented here focus on a select group of crop species, yet future research should expand the species spectrum to encompass a broader representation of crops, particularly those with unique evolutionary histories (e.g., Corté s et al., 2018), orphan research (Hu et al., 2025), or paramount importance for the food security (e.g., López-Herná ndez et al., 2023), nutrition (Wu et al., 2020;Wu et al., 2024), sustainability (Benitez-Alfonso et al., 2023) and self-sufficiency (Scherer et al., 2020;Varshney et al., 2021b) targets. This will enlighten more generalizable patterns of crop genome and epigenome evolution.Second, but not less important, a more prominent integration of epigenetic regulation is desirable. Epigenetic modifications play a crucial role in shaping gene expression (Chinnusamy and Zhu, 2009) and phenotypic plasticity (Kristensen et al., 2020;Fox et al., 2019), yet are often disregarded by studies focusing on the latter paradigms (Bossdorf et al., 2008). Oncoming research should aim integrating epigenomic data (e.g., DNA methylation, histone modifications) with genomic and transcriptomic data to build a more comprehensive understanding of the evolutionary constrains shaping crop genomes and epigenomes, and their phenotypic consequences.On a third note, interpreting evolution across the multi-omics continuum requires more advanced modeling techniques. The development of sophisticated computational models capable of predicting the multi-dimensional downstream consequences of genomic and epigenomic variations on crop traits and metabolomes is crucial. These models should be capable to simultaneously integrate multiple data types and incorporate information on gene regulatory networks and their environmental interactions. The current machine learning boom (Varshney, 2021) promises assisting in these matters (Libbrecht and Noble, 2015;Schrider and Kern, 2018).While substantial progress has been made in recognizing major trends and causes during crop genome evolution, as illustrated by this Research Topic, critical knowledge gaps remain. A more comprehensive understanding requires the integration of diverse data types genomic, transcriptomic, epigenomic, and metabolomicto build a holistic picture of evolutionary changes at intricate omic levels (Barrera-Redondo et al., 2020). Meanwhile, further comparative studies across closely related species are essential to disentangle common evolutionary trajectories (Wolf and Ellegren, 2017) from unique adaptations driven by specific environmental pressures or selective breeding (Feng et al., 2024).Despite recent efforts in these last two fronts, the mechanistic comprehension of coupled genomic and epigenomic changes, and their downstream consequences, are still in its infancy. Therefore, identifying the key genes and regulatory pathways involved, as well as their environmental context (Corté s et al., 2022;Lasky et al., 2023), is crucial for a complete understating of these evolutionary processes. Equally important, translating fundamental mechanistic knowledge into practical applications for crop improvement is critical, especially due to a limited adoption of innovation by farmers (Kholova et al., 2024). This will require strategies that harness multi-omic evolutionary novelty to speed breeding programs aiming at the design of crops with superior resilience to biotic and abiotic stresses (Varshney et al., 2021a;Corté s, 2024), without disregarding their market value and the farmers' preferences (Peláez et al., 2022).Visualizing these novel trends in the field of multi-omic evolution will in turn impact other transgressive technologies, such as gene editing. Target genes and regulatory elements identified as part of these studies can be manipulated by unprecedented genome editing tools such as CRISPR/Cas9 (Doudna and Charpentier, 2014). For instance, this approach is now allowing precise editions to test gene functionality in crop backgrounds, and eventually leverage them for fast-forward improvement (Dort et al., 2020), while
Keywords: multi-omics, Genomics, Epigenomics, Epitranscriptomics, Transcriptomics, Metabolomics, gene evolution, pathway evolution
Received: 06 May 2025; Accepted: 27 May 2025.
Copyright: © 2025 Du, Liang and Cortés. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Hai Du, Southwest University, Chongqing, China
Zhe Liang, Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
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