The role of plants within the biological food chain is crucial for addressing the world's major environmental and ecological challenges. The complexities of a plant’s biology require in-depth analysis to predict how natural or manmade threats influence its growth and development. The progress made in systems and synthetic biology provide unprecedented opportunities to revolutionize crop improvement. By leveraging efficient algorithms, data visualization, and computational modeling, we can enhance simulation and communication in the field. Integrative and predictive models reveal the consequences of perturbing plant systems, to monitor genes, proteins, and metabolic pathways, elucidating how plants interact with environmental stimuli. This research topic aims to explore the benefits of applying systems and synthetic biology principles to enhance the development of future crops. Integrating computational models, omics technologies, and genetic engineering enhances our understanding and improves crop traits, resilience, and productivity.
Modern crop productivity is challenged by environmental stresses and unpredictable climatic shifts across the globe, which require the development of advanced traits to enhance crop resilience and productivity. In this context, systems and synthetic biology approaches aim to generate novel biological components, such as enzymes, genetic circuits, and cells, or to redesign existing biological pathways to yield new and improved functions. Synthetic biology enables stacking multiple genes concurrently and expanding genetic modification. It also allows for bottom-up genome assembly from modular genetic parts, which can then be transferred into target cells or organisms. Moreover, it aids in annotating through the proteogenomic approach to identify new gene models which are missed during whole genome sequencing. Altogether, this approach holds promise to advance breeding by introducing genes with known functionalities, generating artificial genetic variations, and engineering metabolic pathways to improve crop efficiency and biomass production. Insights gained from systems biology investigations can direct the construction of diverse libraries of biological components for synthetic biology applications, enabling modification or re-engineering of underlying biological mechanisms.
This research topic will encompass a broad spectrum of topics within the context of systems and synthetic biology applied to crop improvement. Key areas of interest include, but are not limited to, the following:
• Systems biology, and multi-omics approach to investigate crop architecture, physiological processes, nutritional alterations, and responses to external cues.
• QTL mapping, GWAS, prediction modeling, genomic selection, and genomics-assisted breeding (GAB) for further effective crop breeding.
• Genome editing and RNAi technology to tackle critical agronomic challenges.
• Biological databases, tools, and technologies to drive progress in crop engineering.
• Computational modeling, machine learning, and automation to decipher complex biological systems.
We invite submissions of fundamental and application-oriented research, systematic reviews, mini-reviews, method papers, opinions, and perspectives that explore the synergies between systems and synthetic biology, aimed at breeding multi-trait crops and enhancing their resilience to harsh environments.
Keywords:
crop improvement, genetic engineering, machine learning, omics integration, synthetic biology, system biology
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The role of plants within the biological food chain is crucial for addressing the world's major environmental and ecological challenges. The complexities of a plant’s biology require in-depth analysis to predict how natural or manmade threats influence its growth and development. The progress made in systems and synthetic biology provide unprecedented opportunities to revolutionize crop improvement. By leveraging efficient algorithms, data visualization, and computational modeling, we can enhance simulation and communication in the field. Integrative and predictive models reveal the consequences of perturbing plant systems, to monitor genes, proteins, and metabolic pathways, elucidating how plants interact with environmental stimuli. This research topic aims to explore the benefits of applying systems and synthetic biology principles to enhance the development of future crops. Integrating computational models, omics technologies, and genetic engineering enhances our understanding and improves crop traits, resilience, and productivity.
Modern crop productivity is challenged by environmental stresses and unpredictable climatic shifts across the globe, which require the development of advanced traits to enhance crop resilience and productivity. In this context, systems and synthetic biology approaches aim to generate novel biological components, such as enzymes, genetic circuits, and cells, or to redesign existing biological pathways to yield new and improved functions. Synthetic biology enables stacking multiple genes concurrently and expanding genetic modification. It also allows for bottom-up genome assembly from modular genetic parts, which can then be transferred into target cells or organisms. Moreover, it aids in annotating through the proteogenomic approach to identify new gene models which are missed during whole genome sequencing. Altogether, this approach holds promise to advance breeding by introducing genes with known functionalities, generating artificial genetic variations, and engineering metabolic pathways to improve crop efficiency and biomass production. Insights gained from systems biology investigations can direct the construction of diverse libraries of biological components for synthetic biology applications, enabling modification or re-engineering of underlying biological mechanisms.
This research topic will encompass a broad spectrum of topics within the context of systems and synthetic biology applied to crop improvement. Key areas of interest include, but are not limited to, the following:
• Systems biology, and multi-omics approach to investigate crop architecture, physiological processes, nutritional alterations, and responses to external cues.
• QTL mapping, GWAS, prediction modeling, genomic selection, and genomics-assisted breeding (GAB) for further effective crop breeding.
• Genome editing and RNAi technology to tackle critical agronomic challenges.
• Biological databases, tools, and technologies to drive progress in crop engineering.
• Computational modeling, machine learning, and automation to decipher complex biological systems.
We invite submissions of fundamental and application-oriented research, systematic reviews, mini-reviews, method papers, opinions, and perspectives that explore the synergies between systems and synthetic biology, aimed at breeding multi-trait crops and enhancing their resilience to harsh environments.
Keywords:
crop improvement, genetic engineering, machine learning, omics integration, synthetic biology, system biology
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.