WAWABILITY July 11–12, 2025 Washington DC. Big ideas. Bold Progress. Global Impact. Powered by TDIforAccess.
WAWABILITY July 11–12, 2025 Washington DC. Big ideas. Bold Progress. Global Impact. Powered by TDIforAccess.

A-B.07: Extending AnnoTALE for Improved TALE Annotation and Analysis Across Xanthomonas Genomes

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Many plant-pathogenic Xanthomonas bacteria encode transcription activator-like effectors (TALEs) in their genomes. These virulence factors bind specific DNA sequences in host plants and modulate gene expression. TALE repertoires vary across strains and pathovars and differences in repeat structure affect binding preferences. Interpreting this diversity requires consistent genome-based identification and classification.

AnnoTALE is a software tool for automated TALE gene annotation and comparative analysis that introduced class-based grouping and standardized nomenclature, enabling biologically meaningful comparison of TALE repertoires across strains. Here, we present a modernization and extension of AnnoTALE focused on enhancing scalability and biological interpretability. As a prerequisite, the underlying sequence analysis library (Jstacs) was modularized and AnnoTALE separated into an independent, Maven-based project, strengthening reproducibility and maintainability. The TALE class assignment algorithm was revised and accelerated, yielding more robust and consistent classification across larger genome collections. The data model was redesigned around a relational database, enhancing data organization and access. This enables structured queries across genomes, TALE classes, and strains, improves data integrity and introduces richer, normalized strain and taxonomy metadata, increasing consistency of annotations both internally and with external reference resources.

A hosted web-based database explorer (annotale.informatik.uni-halle.de) supports biological analysis by enabling exploration of TALE class distributions across taxa, comparison of repertoires between strains, and integration of strain metadata such as geographic origin. It allows analysis of genomic context, including TALE positions within assemblies. Users can inspect individual TALE records with sequence features, annotations, and external links, supporting integrated exploratory and comparative analysis.

Co-authors: Jan Grau, Jens Boch, Laura Marti Torres

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