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Studying genetic variation underlying phenotypes is an important topic in genomics. In plant genomic research, for example, scientists analyze the variation between cultivars and wild types to develop crops with improved resistance to diseases. This analysis is commonly based on comparison to a single reference genome. Because the number of genomes is growing rapidly and to avoid bias towards a single reference genome, the field is shifting towards the use of pangenomes, i.e., abstract representations of multiple genomes in a species or population. While pangenomes allow for a more complete picture of the genetic variation, their large size and complex data structure hinder analysis. To deal with this, genome scientists need visual analytics tools that support interactive and exploratory analysis of pangenomes to identify relevant information for variant analysis. A major challenge is to handle multiple references together with providing the adequate context of heterogeneous (meta)data, such as annotations, evolutionary relationships, and phenotypes. To address this challenge, we developed PanVA, a visual analytics design for variant analysis in pangenomes. PanVA supports a novel strategy for pangenomic variant analysis that was designed with the active participation of genomics researchers. PanVA uniquely allows researchers to get a complete picture of the variation within genes in a large set of genomes, and identify associations with phenotypes. The design combines tailored visual representations with interactions such as sorting, grouping and aggregation, allowing the user to navigate and explore different perspectives. The realization of the PanVA design is possible through PanTools. Through user evaluation in the context of plants and pathogen research, we demonstrate that PanVA helps researchers explore regions of interest and generate hypotheses about genetic variants and their role in phenotypic variation.

Background Bacterial plant pathogens of the Pectobacterium genus are responsible for a wide spectrum of diseases in plants, including important crops such as potato, tomato, lettuce, and banana. Investigation of the genetic diversity underlying virulence and host specificity can be performed at genome level by using a comprehensive comparative approach called pangenomics. A pangenomic approach, using newly developed functionalities in PanTools, was applied to analyze the complex phylogeny of the Pectobacterium genus. We specifically used the pangenome to investigate genetic differences between virulent and avirulent strains of P. brasiliense, a potato blackleg causing species dominantly present in Western Europe. Results Here we generated a multilevel pangenome for Pectobacterium, comprising 197 strains across 19 species, including type strains, with a focus on P. brasiliense. The extensive phylogenetic analysis of the Pectobacterium genus showed robust distinct clades, with most detail provided by 452,388 parsimony-informative single-nucleotide polymorphisms identified in single-copy orthologs. The average Pectobacterium genome consists of 47% core genes, 1% unique genes, and 52% accessory genes. Using the pangenome, we zoomed in on differences between virulent and avirulent P. brasiliense strains and identified 86 genes associated to virulent strains. We found that the organization of genes is highly structured and linked with gene conservation, function, and transcriptional orientation. Conclusion The pangenome analysis demonstrates that evolution in Pectobacteria is a highly dynamic process, including gene acquisitions partly in clusters, genome rearrangements, and loss of genes. Pectobacterium species are typically not characterized by a set of species-specific genes, but instead present themselves using new gene combinations from the shared gene pool. A multilevel pangenomic approach, fusing DNA, protein, biological function, taxonomic group, and phenotypes, facilitates studies in a flexible taxonomic context.

Desiccation tolerance is common in seeds and various other organisms, but only a few angiosperm species possess vegetative desiccation tolerance. These 'resurrection species' may serve as ideal models for the ultimate design of crops with enhanced drought tolerance. To understand the molecular and genetic mechanisms enabling vegetative desiccation tolerance, we produced a high-quality whole-genome sequence for the resurrection plant Xerophyta viscosa and assessed transcriptome changes during its dehydration. Data revealed induction of transcripts typically associated with desiccation tolerance in seeds and involvement of orthologues of ABI3 and ABI5, both key regulators of seed maturation. Dehydration resulted in both increased, but predominantly reduced, transcript abundance of genomic 'clusters of desiccation-associated genes' (CoDAGs), reflecting the cessation of growth that allows for the expression of desiccation tolerance. Vegetative desiccation tolerance in X. viscosa was found to be uncoupled from drought-induced senescence. We provide strong support for the hypothesis that vegetative desiccation tolerance arose by redirection of genetic information from desiccation-tolerant seeds.