A2TEA: Identifying trait-specific evolutionary adaptations [version 2; peer review: 2 approved]

• Published in: F1000Research
• Main Authors: Florian Boecker, Heiko Schoof, Tyll Stöcker, Carolin Uebermuth-Feldhaus
• Format: Article
• Language: English
• Published: F1000 Research Ltd 2023-04-01
• Subjects: plants; crops; adaptation; evolution; stress; workflow; eng
• Online Access: https://f1000research.com/articles/11-1137/v2

Background: Plants differ in their ability to cope with external stresses (e.g., drought tolerance). Genome duplications are an important mechanism to enable plant adaptation. This leads to characteristic footprints in the genome, such as protein family expansion. We explore genetic diversity and uncover evolutionary adaptation to stresses by exploiting genome comparisons between stress tolerant and sensitive species and RNA-Seq data sets from stress experiments. Expanded gene families that are stress-responsive based on differential expression analysis could hint at species or clade-specific adaptation, making these gene families exciting candidates for follow-up tolerance studies and crop improvement. Software: Integration of such cross-species omics data is a challenging task, requiring various steps of transformation and filtering. Ultimately, visualization is crucial for quality control and interpretation. To address this, we developed A2TEA: Automated Assessment of Trait-specific Evolutionary Adaptations, a Snakemake workflow for detecting adaptation footprints in silico. It functions as a one-stop processing pipeline, integrating protein family, phylogeny, expression, and protein function analyses. The pipeline is accompanied by an R Shiny web application that allows exploring, highlighting, and exporting the results interactively. This allows the user to formulate hypotheses regarding the genomic adaptations of one or a subset of the investigated species to a given stress. Conclusions: While our research focus is on crops, the pipeline is entirely independent of the underlying species and can be used with any set of species. We demonstrate pipeline efficiency on real-world datasets and discuss the implementation and limits of our analysis workflow as well as planned extensions to its current state. The A2TEA workflow and web application are publicly available at: https://github.com/tgstoecker/A2TEA.Workflow and https://github.com/tgstoecker/A2TEA.WebApp, respectively.