Find, Label, Annotate Genomes: FLAG, a fully automated tool for structural and functional gene annotation

Recent advances in long-read sequencing technologies and the efforts of projects aimed at increasing the universe of sequenced reference genomes have led to a growth in the number of whole genomes sequenced for non-model organisms. Still, 81% of the over 36,000 unique publicly available eukaryotic genomes in the NCBI database lack gene structure annotations (1). While there are many open-source tools available for each step in the annotation process, many of these tools are designed for chromosomal assemblies with available transcript data from the same or very closely related organisms. Here we present “Find, Label, Annotate Genomes” (FLAG), a fully automated genome annotation workflow. FLAG (i) works on any computing environment, (ii) runs automatically without initial training data, (iii) generates structural and functional annotations, (iv) performs accurately with fragmented genomes, (v) does not require species-specific extrinsic evidence (transcript sequences) and (vi) includes quality control steps to evaluate annotation completeness. We compared the gene annotations generated by FLAG and publicly available annotations from 12 eukaryotic organisms, including 1 plant, 8 living animals, and 1 extinct animal. In fragmented genomes, FLAG annotations provided an average of 18% increase in complete BUSCO scores and 15x lower error rate for the predicted number of protein-coding genes when compared to published BRAKER2 annotations. With FLAG-Refiner further improved results by decreasing the error rate to 17x lower when compared to published BRAKER2 annotations. In high-quality model organisms, FLAG demonstrates comparable results to those of the NCBI EGAP pipeline, underscoring its robustness and accuracy in gene prediction across diverse taxa and assembly qualities.