An Efficient Triplex TaqMan Quantitative PCR to Detect a Blackleg-Causing Lineage of Pectobacterium brasiliense in Potato Based on a Pangenome Analysis.

P. brasiliense is an important bacterial pathogen causing blackleg (BL) in potatoes. Nevertheless, P. brasiliense is often detected in seed lots that do not develop any of the typical blackleg symptoms in the potato crop when planted. Field bioassays identified that P. brasiliense strains can be categorized into two distinct classes, some able to cause blackleg symptoms and some unable to do it. A comparative pangenomic approach was performed on 116 P. brasiliense strains, of which 15 were characterized as BL-causing strains and 25 as non-causative. In a genetically homogeneous clade comprising all BL-causing P. brasiliense strains, two genes only present in the BL-causing strains were identified, one encoding a predicted lysozyme inhibitor Lprl (LZI) and one encoding a putative Toll/interleukin-1 receptor (TIR) domain-containing protein. TaqMan assays for the specific detection of BL-causing P. brasiliense were developed and integrated with the previously developed generic P. brasiliense assay into a triplex TaqMan assay. This simultaneous detection makes the scoring more efficient as only a single tube is needed, and it is more robust as BL-causing strains of P. brasiliense should be positive for all three assays. Individual P. brasiliense strains were found to be either positive for all three assays or only for the P. brasiliense assay. In potato samples, the mixed presence of BL-causing and not BL-causing P. brasiliense strains was observed as shown by the difference in Ct value of the TaqMan assays. However, upon extension of the number of strains, it became clear that in recent years additional BL-causing lineages of P. brasiliense were detected for which additional assays must be developed.

PanVA: Pangenomic Variant Analysis.

Genomics researchers increasingly use multiple reference genomes to comprehensively explore genetic variants underlying differences in detectable characteristics between organisms. Pangenomes allow for an efficient data representation of multiple related genomes and their associated metadata. However, current visual analysis approaches for exploring these complex genotype-phenotype relationships are often based on single reference approaches or lack adequate support for interpreting the variants in the genomic context with heterogeneous (meta)data. This design study introduces PanVA, a visual analytics design for pangenomic variant analysis developed with the active participation of genomics researchers. The design uniquely combines tailored visual representations with interactions such as sorting, grouping, and aggregation, allowing users to navigate and explore different perspectives on complex genotype-phenotype relations. Through evaluation in the context of plants and pathogen research, we show that PanVA helps researchers explore variants in genes and generate hypotheses about their role in phenotypic variation.

PanTools v3: functional annotation, classification and phylogenomics.

SUMMARY: The ever-increasing number of sequenced genomes necessitates the development of pangenomic approaches for comparative genomics. Introduced in 2016, PanTools is a platform that allows pangenome construction, homology grouping and pangenomic read mapping. The use of graph database technology makes PanTools versatile, applicable from small viral genomes like SARS-CoV-2 up to large plant or animal genomes like tomato or human. Here, we present our third major update to PanTools that enables the integration of functional annotations and provides both gene-level analyses and phylogenetics. AVAILABILITY AND IMPLEMENTATION: PanTools is implemented in Java 8 and released under the GNU GPLv3 license. Software and documentation are available at https://git.wur.nl/bioinformatics/pantools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Pectobacterium pangenome, with a focus on Pectobacterium brasiliense, shows a robust core and extensive exchange of genes from a shared gene pool.

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.