TOAST

TOAST provides ortholog-based phylogenomic alignment generation using BUSCO and integrates plant spaceflight omics datasets for gene-centric comparative analysis.

Key Features:

• Ortholog Identification: Utilizes Benchmarking Universal Single-Copy Orthologs (BUSCO) to identify orthologous sequences from transcriptomes.
• Alignment Automation: Automates search, query, and multiple sequence alignment generation to produce locus-specific and concatenated alignments.
• Missing Data Analysis: Exports outputs that quantify patterns of missing data and permit reassembly of alignments based on user-defined criteria.
• Assembly of Sequences: Assembles public and novel transcriptome-derived sequences against target databases of candidate orthologs.
• Customization: Implemented as an open-source R package that can be adapted and integrated into informatic pipelines.
• Data Integration: Implements a relational database using Qlik to integrate omics datasets from NASA's GeneLab and other repositories with associated metadata.
• Gene-centric Comparative Analysis: Aggregates and compares gene-level data across multiple spaceflight experiments.
• Gene Network Exploration: Supports filtering by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to explore genetic networks.
• Analytical Tool Connectivity: Connects integrated datasets to external web-based analytical tools for downstream investigation.

Scientific Applications:

• Phylogenomic dataset assembly: Streamlines identification and alignment of orthologous sequences from transcriptomes for comparative phylogenetic studies.
• Comparative multispecies analysis: Produces locus-specific and concatenated alignments to support phylogenomic inference across diverse species.
• Missing data impact assessment: Enables quantification and testing of how missing data affect phylogenomic results.
• Plant spaceflight omics integration: Integrates and harmonizes omics datasets and metadata from NASA's GeneLab and other repositories to study plant responses to spaceflight.
• Detection of conserved spaceflight responses: Validates and identifies gene expression patterns such as oxidative stress modulation and altered mitochondrial function across plant spaceflight experiments.
• Pathway and network analysis in stress responses: Facilitates exploration of functional pathways and genetic networks underlying plant responses to spaceflight and related stresses.

Methodology:

Uses BUSCO for ortholog searches in transcriptomes; an R package automates search, query, and multiple sequence alignment generation producing locus-specific and concatenated alignments and exports outputs for missing-data quantification and reassembly; a Qlik-based relational database integrates omics datasets and metadata from NASA's GeneLab and other repositories and enables filtering by Gene Ontology and KEGG pathways for network exploration.