TOA: A software package for automated functional annotation in non-model plant species

The increase of sequencing capacity provided by high-throughput platforms has made it possible to routinely obtain large sets of genomic and transcriptomic sequences from model and non-model organisms. Subsequent genomic analysis and gene discovery in next-generation sequencing experiments are, however, bottlenecked by functional annotation. One common way to perform functional annotation of sets of sequences obtained from next-generation sequencing experiments, is by searching for homologous sequences and accessing the related functional information deposited in genomic databases. Functional annotation is especially challenging for non-model organisms, like many plant species. In such cases, existing free and commercial general-purpose applications may not offer complete and accurate results. We present TOA (Taxonomy-oriented annotation), a Python-based user-friendly open source application designed to establish functional annotation pipelines geared towards non-model plant species that can run in Linux/Mac computers, HPCs and cloud servers. TOA performs homology searches against proteins stored in the PLAZA databases, NCBI RefSeq Plant, Nucleotide Database and Non-Redundant Protein Sequence Database, and outputs functional information from several ontology systems: Gene Ontology, InterPro, EC, KEGG, Mapman and MetaCyc. The software performance was validated by comparing the runtimes, total number of annotated sequences and accuracy of the functional information obtained for several plant benchmark data sets with TOA and other functional annotation solutions. TOA outperformed the other software in terms of number of annotated sequences and accuracy of the annotation and constitutes a good alternative to improve functional annotation in plants. TOA is especially recommended for gymnosperms or for low quality sequence data sets of non-model plants.

Automated summary

TOA is a user-friendly open source application designed for functional annotation in non-model plant species, outperforming other software in terms of number of annotated sequences and accuracy of the annotation.