Analyzing Immunity in Non-model Insects Using De Novo Transcriptomics

Abstract

With the advent of widely accessible and cost-effective next-generation sequencing technologies, it has become increasingly feasible to study insect immunity on a deep genomic or transcriptomic level. Here we introduce a protocol that is aimed at exploiting transcriptomic data to study immunity in non-model insect organisms. We provide instructions for an entire workflow, starting with successful extraction of insect RNA through to bioinformatic guidelines for the effective analysis of mRNA sequencing data. The RNA extraction procedure is based on TRIzol Reagent and a spin-column clean-up step. The bioinformatic pipeline is intended to help users identify immune genes from de novo transcriptome data and includes guidelines for conducting differential gene expression analyses on transcriptomic data. The immune gene prediction method is based on inferring protein homologs with HMMER and Blastp and takes advantage of the ImmunoDB database, which is a valuable resource for research on insect immune-related genes and gene families. The differential gene expression analysis procedure utilizes the DESeq2 package as implemented in R. We hope this protocol will serve as a useful resource for researchers aiming to study immunity in non-model insect species.