TY - GEN A1 - He, S. A1 - Johnston, P. R. A1 - McMahon, Dino Peter ED - Sandrelli, F. ED - Tettamanti, G. T1 - Analyzing Immunity in Non-model insects Using De Novo Transcriptomics N2 - 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 successfiil 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 HMMERand Blastp and talces Advantage ofthe 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 imple� mented in R. We hope this protocol will serve as a usefi.il resource for researchers aiming to study immunity in non-model insect species. KW - RNA extraction KW - mRNA-seq KW - ImmunoDB KW - Immune gene prediction KW - Differential gene expression analysis KW - De novo assembly PY - 2020 U6 - https://doi.org/10.1007/978-1-0716-0259-1_2 VL - 2020 SP - 35 EP - 49 PB - Springer Science+Business Media CY - Luxemburg AN - OPUS4-53888 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -