About this Research Topic
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 provides 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, monitoring genes, proteins, and metabolic pathways, and elucidating how plants interact with environmental stimuli. Despite these advancements, there remain significant gaps in our understanding of how to fully harness these technologies to develop crops that can withstand environmental stresses and unpredictable climatic shifts.
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. The goal is to generate novel biological components, such as enzymes, genetic circuits, and cells, or to redesign existing biological pathways to yield new and improved functions. This includes stacking multiple genes concurrently, bottom-up genome assembly, and annotating new gene models through proteogenomic approaches.
To gather further insights into the application of systems and synthetic biology in crop improvement, we welcome articles addressing, but not limited to, the following themes:
• Systems biology and multi-omics approaches 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 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.
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. The goal is to generate novel biological components, such as enzymes, genetic circuits, and cells, or to redesign existing biological pathways to yield new and improved functions. This includes stacking multiple genes concurrently, bottom-up genome assembly, and annotating new gene models through proteogenomic approaches.
To gather further insights into the application of systems and synthetic biology in crop improvement, we welcome articles addressing, but not limited to, the following themes:
• Systems biology and multi-omics approaches 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 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.
