Systematic Functional Annotation Workflow for Insects

Simple Summary The functions of all genes encoded in the genome should be studied for genome editing. Genome editing technology can speed up insect research for the functional analysis of genes. Our knowledge about the functional information of genes is still incomplete currently, while the genome sequencing of an organism can be completed. The functional information has been annotated based solely on the information that has been obtained from the results of previous biological research. However, this information will be important in determining the target genes for genome editing. In particular, it is very important that this information is in machine-readable form because computer programs mainly parse this information for the understanding of biological systems. In this paper, we describe a workflow-based method for annotating gene functions in insects that makes use of transcribed sequence information as well as reference genome and protein sequence databases. Using the developed workflow, we annotated the functional information of the Japanese stick insect and silkworm, including gene expression as well as sequence analysis. The functional annotation information obtained by the workflow will greatly expand the possibilities of entomological research using genome editing. Next-generation sequencing has revolutionized entomological study, rendering it possible to analyze the genomes and transcriptomes of non-model insects. However, use of this technology is often limited to obtaining the nucleotide sequences of target or related genes, with many of the acquired sequences remaining unused because other available sequences are not sufficiently annotated. To address this issue, we have developed a functional annotation workflow for transcriptome-sequenced insects to determine transcript descriptions, which represents a significant improvement over the previous method (functional annotation pipeline for insects). The developed workflow attempts to annotate not only the protein sequences obtained from transcriptome analysis but also the ncRNA sequences obtained simultaneously. In addition, the workflow integrates the expression-level information obtained from transcriptome sequencing for application as functional annotation information. Using the workflow, functional annotation was performed on the sequences obtained from transcriptome sequencing of the stick insect (Entoria okinawaensis) and silkworm (Bombyx mori), yielding richer functional annotation information than that obtained in our previous study. The improved workflow allows the more comprehensive exploitation of transcriptome data and is applicable to other insects because the workflow has been openly developed on GitHub.