In recent years, the study of structural variants (SVs) in plant pangenomes has gained significant attention, revolutionizing our understanding of plant genomic diversity and adaptation. SVs, including large-scale insertions, deletions, duplications, inversions, and translocations, play a critical role in shaping the genomic landscape of plants, influencing everything from individual plant traits to broader evolutionary patterns. Pangenomes, representing the entire genetic makeup of a species, are particularly vital in plants, where genomic diversity is extensive due to varied environmental interactions and artificial selection histories. Analyzing SVs in pangenomes has shed light on how plants adapt to diverse environments. In agricultural contexts, SVs within crop pangenomes are linked to traits like yield, disease resistance, crop production, and environmental resilience, offering new avenues for crop improvement. Moreover, pangenome studies enhance our understanding of plant evolutionary processes, revealing patterns of gene flow, speciation, and the impacts of human cultivation.The core aim of this research topic is to delve into the intricate workings of plant pangenomes and their significance in enhancing plant species' agronomic traits. A deeper understanding of the genetic mechanisms that confer these traits becomes increasingly critical. We now have the capacity to construct comprehensive pangenomes that reflect the rich genetic variation present in plant species, thanks to recent breakthroughs in genomic sequencing. The challenge lies in harnessing this wealth of data to uncover the genomic basis of agronomic traits. This Research Topic will gather contributions that apply cutting-edge genomic and multi-omics analyses to elucidate the complex interactions that govern plant development, resistance, and productivity. By integrating findings from genomics, transcriptomics, epigenomics, and phenomics, we can piece together the vast genetic puzzle that determines plant vitality and performance. Our goal is to compile a body of work that not only presents innovative research techniques but also fosters the development of new bioinformatics strategies to interpret these large and complex datasets. This Research Topic will serve as a nexus for knowledge that can drive our understanding of plant genetics forward and inform the next generation of agricultural innovation.This research topic will welcome papers involved in research on structural variants and pangenomics in plants. The selection of papers for publication will depend on the quality and the rigor of the research. Specific topics include but are not limited to:- Discovery and characterization of SVs in plant pangenomes- Study of the role of SVs in plant adaptation and evolution- Impacts of SVs on crop improvement- Methodological advancements in pangenome and structural variation analysis- Pangenome-wide gene family study and functional analysis of related SVs- Comparative pangenomics across plant species- Integrative approaches combining SV analysis with other omics data
In recent years, the study of structural variants (SVs) in plant pangenomes has gained significant attention, revolutionizing our understanding of plant genomic diversity and adaptation. SVs, including large-scale insertions, deletions, duplications, inversions, and translocations, play a critical role in shaping the genomic landscape of plants, influencing everything from individual plant traits to broader evolutionary patterns. Pangenomes, representing the entire genetic makeup of a species, are particularly vital in plants, where genomic diversity is extensive due to varied environmental interactions and artificial selection histories. Analyzing SVs in pangenomes has shed light on how plants adapt to diverse environments. In agricultural contexts, SVs within crop pangenomes are linked to traits like yield, disease resistance, crop production, and environmental resilience, offering new avenues for crop improvement. Moreover, pangenome studies enhance our understanding of plant evolutionary processes, revealing patterns of gene flow, speciation, and the impacts of human cultivation.The core aim of this research topic is to delve into the intricate workings of plant pangenomes and their significance in enhancing plant species' agronomic traits. A deeper understanding of the genetic mechanisms that confer these traits becomes increasingly critical. We now have the capacity to construct comprehensive pangenomes that reflect the rich genetic variation present in plant species, thanks to recent breakthroughs in genomic sequencing. The challenge lies in harnessing this wealth of data to uncover the genomic basis of agronomic traits. This Research Topic will gather contributions that apply cutting-edge genomic and multi-omics analyses to elucidate the complex interactions that govern plant development, resistance, and productivity. By integrating findings from genomics, transcriptomics, epigenomics, and phenomics, we can piece together the vast genetic puzzle that determines plant vitality and performance. Our goal is to compile a body of work that not only presents innovative research techniques but also fosters the development of new bioinformatics strategies to interpret these large and complex datasets. This Research Topic will serve as a nexus for knowledge that can drive our understanding of plant genetics forward and inform the next generation of agricultural innovation.This research topic will welcome papers involved in research on structural variants and pangenomics in plants. The selection of papers for publication will depend on the quality and the rigor of the research. Specific topics include but are not limited to:- Discovery and characterization of SVs in plant pangenomes- Study of the role of SVs in plant adaptation and evolution- Impacts of SVs on crop improvement- Methodological advancements in pangenome and structural variation analysis- Pangenome-wide gene family study and functional analysis of related SVs- Comparative pangenomics across plant species- Integrative approaches combining SV analysis with other omics data