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With rapidly developing sequencing technology and lower sequencing costs, over 500 plant genomes have been sequenced since the first release of the Arabidopsis genome in 2000. Meanwhile, more and more omics datasets have been released utilizing techniques such as genome re-sequencing, pan-genomics, ...

With rapidly developing sequencing technology and lower sequencing costs, over 500 plant genomes have been sequenced since the first release of the Arabidopsis genome in 2000. Meanwhile, more and more omics datasets have been released utilizing techniques such as genome re-sequencing, pan-genomics, RNA-seq, metabolomics, proteomics, and so on. The release of all these data provides us with an excellent opportunity and rich data resources to study the evolution of plant genes. In recent years, in addition to the rapid development of bioinformatics, many types of software and tools have also become available. However, in the face of more and more kinds of omics data, we still need more efficient, powerful, and user-friendly tools, software, pipelines, websites, and databases.

Together with the rich omics datasets and advanced bioinformatics tools and methods, we hope to make more progress in plant comparative genomics and functional genomics. Utilizing the different types of omics data will help us to better understand the evolutionary history of plants, provide resources for molecular studies on important agronomic and economical traits, and develop new gene function verification methods.

This Research Topic will cover a broad range of comparative and functional genomic studies. We particularly encourage contributions related to research in horticultural crops (e.g., vegetables, fruits, ornamentals, and medicinal plants). This collection welcomes, but is not limited to, the following subtopics:
• Comparative genomics analyses to better understand genes or species evolution utilizing bioinformatics, including gene family analyses (please note that single species focused gene family analyses will not be accepted) and plant evolutionary analyses (please note that phylogenies based on only one or a few species without comprehensive analysis will not be accepted)
• Functional genomics analyses to better understand plant genes or genome evolution utilizing omics datasets and molecular biology methods (including de novo genome sequencing and pan-genomic analyses, genome re-sequencing and GWAS analyses, RNA-seq and metabolomics analyses, and characterization of novel genes)

Keywords: Plant evolution, genome sequencing, molecular marker development, database construction, gene family


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