About this Research Topic
High-throughput technologies are those that allow the generation of large-scale data related to omic analysis (such as genomics, transcriptomics, proteomics, phenomics, and metabolomics). Currently, the development and use of these technologies has gone hand-in-hand with the development of bioinformatics tools, which have allowed the integration of omics-based data to understand crucial knowledge about the molecular systems that underlie the various functions of the plants.
In recent years, there has been a huge development in the field of high-throughput biology, which is attributed to an era of tech startups. Genomics studies in plants, for instance, have benefited from advances in high-throughput technologies, such as high-throughput genotyping, which have allowed us to investigate the regulation and function of thousands of genes and genomic regions involved in a novel adaptation. In fact, with current high-throughput technologies, it is possible to recover substantial portions of the plant diversity, which is a key input for genetic improvement programs, food security and conservation programs. The integration of multilevel biological data, involving investigations at the molecular level (in genomics, transcriptomics, proteomics, and metabolomics, among others), have allowed more comprehensive studies, which broadens the opportunities to clarify key molecular aspects involved in the physiological responses to abiotic stresses.
This Research Topic aims to explore new insights into plant stress and tolerance to environmental constraints through the integration of advanced high-throughput technologies including multi-omics, bioinformatics, systems biology, and artificial intelligence. In this Research Topic, we are seeking reviews and original research articles on studies on plant’s response to environmental pressures based on advanced high-throughput technology approaches.
Keywords: Abiotic stress resilience, Plant stress physiology, High-throughput metagenomic technologies, Genome sequencing, Genome editing, High-throughput phenotyping, Data integration, Multilevel biological data, Bioinformatics resources, Multi-omics
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