About this Research Topic
Multi omics studies explore the interactions among multiple living substances during plant growth and development, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics, which collectively affect the final phenotype of plants. While cost-effective high-throughput technologies are providing an increasing amount of data, analysis of single-layer data rarely provides causal links. With the development of high-throughput sequencing technology, omics studies continue to evolve. Using through high-throughput sequencing of various groups and data integration studies, we can comprehensively and systematically understand the constitution of complex agronomic traits, as well as the interrelationship of multiple substances in molecular breeding and other fields. This provides an important technical approach to the study of network biology and systems biology.
Recently, the utilization of large data sets from different omics sources has laid a good foundation for the genetic dissection of complex agronomic traits and has also provided new breeding ideas for plant breeders. These data involve studies at various omics levels ranging from molecular biology to various complex environments, analyzed through data on DNA, RNA, proteins, metabolites, and phenotypes. This suggests that there is great promise for accelerating plant improvement by utilizing different omics datasets. However, with the increasing volume and complexity of omics data from different sources, significant challenges remain on how to analyze these vast sets of omics data rapidly and precisely. Therefore, new insights and analytical methods are needed to use this information for the elucidation of complex agronomic traits as well as plant genetic improvement.
This Research Topic encourages the submission of the latest studies in new methods for multi-omics data, and on using multi omics data to better understand the genetic basis of plant complex traits. The results of this topic can be used to accelerate plant genetic improvement. We welcome submissions that include:
• New methods or tools to integrate omics data from different sources
• Genetic basis for plant complex traits by using the integration of genomics, genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and so on
• New genetic selection (GS) strategies by using multi-omics data
Recently, the utilization of large data sets from different omics sources has laid a good foundation for the genetic dissection of complex agronomic traits and has also provided new breeding ideas for plant breeders. These data involve studies at various omics levels ranging from molecular biology to various complex environments, analyzed through data on DNA, RNA, proteins, metabolites, and phenotypes. This suggests that there is great promise for accelerating plant improvement by utilizing different omics datasets. However, with the increasing volume and complexity of omics data from different sources, significant challenges remain on how to analyze these vast sets of omics data rapidly and precisely. Therefore, new insights and analytical methods are needed to use this information for the elucidation of complex agronomic traits as well as plant genetic improvement.
This Research Topic encourages the submission of the latest studies in new methods for multi-omics data, and on using multi omics data to better understand the genetic basis of plant complex traits. The results of this topic can be used to accelerate plant genetic improvement. We welcome submissions that include:
• New methods or tools to integrate omics data from different sources
• Genetic basis for plant complex traits by using the integration of genomics, genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and so on
• New genetic selection (GS) strategies by using multi-omics data
Keywords: Omics, genetic selection, complex traits, crop improvement
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