DOI: 10.5061/dryad.bp7j7
title: Data from: Genome-wide transcriptional signatures of migratory flight activity in a globally invasive insect pest

description: Migration is a key life history strategy for many animals and requires a
 suite of behavioural, morphological and physiological adaptations which
 together form the ‘migratory syndrome’. Genetic variation has been
 demonstrated for many traits that make up this syndrome, but the
 underlying genes involved remain elusive. Recent studies investigating
 migration-associated genes have focussed on sampling migratory and
 nonmigratory populations from different geographic locations but have
 seldom explored phenotypic variation in a migratory trait. Here, we use a
 novel combination of tethered flight and next-generation sequencing to
 determine transcriptomic differences associated with flight activity in a
 globally invasive moth pest, the cotton bollworm Helicoverpa armigera. By
 developing a state-of-the-art phenotyping platform, we show that
 field-collected H. armigera display continuous variation in flight
 performance with individuals capable of flying up to 40 km during a single
 night. Comparative transcriptomics of flight phenotypes drove a gene
 expression analysis to reveal a suite of expressed candidate genes which
 are clearly related to physiological adaptations required for
 long-distance flight. These include genes important to the mobilization of
 lipids as flight fuel, the development of flight muscle structure and the
 regulation of hormones that influence migratory physiology. We conclude
 that the ability to express this complex set of pathways underlines the
 remarkable flexibility of facultative insect migrants to respond to
 deteriorating conditions in the form of migratory flight and, more
 broadly, the results provide novel insights into the fundamental
 transcriptional changes required for migration in insects and other taxa.
description: Total distance flown by
 individual adult Helicoverpa armigera on the flight
 millsFlight mill data used in
 all figures and REML analyses. This data is used in Fig1B, Fig1C and
 FigS2. Column headings and data are as follows:- ID = the flight mill
 channel (A or B), year flown ('13' represents 2013), date flown
 (e.g. Nov13 = November 13th) and mill flown (e.g. _Ch7 = mill #7). origin
 = origin of the insect population. sex = male (m) or female (f). Total
 distance flown = the total distance (metres) each individual flew on the
 flight mill during the course of a single night as recorded by the
 tethered flight mill.flight_mill_total
 distance.csvRNAseq read count data
 from China Helicoverpa armigeraThe data is a matrix of
 read counts generated from an RNAseq analysis of six samples of H.
 armigera. Each RNA sample was extracted from a pool of three whole
 individual insects. The first column contains the gene identification
 number. All other column headings represent the individual samples. AY =
 insects from Anyang. DF = insects from Dafeng. The data was used to
 determine differential gene expression using the open software packages
 edgeR and DEseq2.china_read_count.matrix.csvRNAseq read count data from Greek Helicoverpa armigeraThe data is a matrix of read counts generated from an RNAseq analysis of six samples of H. armigera from Greece. Each RNA sample was extracted from a pool of three whole individual insects. The first column contains the gene identification number. All other column headings represent the individual samples. GR_S = short-distance flying insects from Northern Greece. GR_L = long-distance flying insects from Northern Greece. The data was used to determine differential gene expression using the open software packages edgeR and DEseq2.greece_read_count.matrix.csvRNA-seq analysis of flight phenotypes of H. armigera - DEseq2 full outputOutput from R package DEseq2 for China and Greece H. armigera RNAseq experiments analysing differential expression between flight phenotypes. Gene ID = gene identification number. baseMean = average of the normalised count values. log2FoldChange = estimated log fold change between sample groups (for China the estimate is measured against AY; for Greece the estimate is measured against GR_S). lfcSE = standard error estimate for logFC. p-value = evidence for an effect of treatment on expression. padj = multiple testing correction for p-value. 'NA' in the p-value or padj column indicates that the gene was excluded from the analysis due to no count data or an extreme outlier.deseq2_full_output.xlsxRNAseq analysis of H. armigera flight phenotypes - edgeR_full_outputOutput from R package edgeR for China and Greece H. armigera RNAseq experiments analysing differential expression between flight phenotypes. Gene ID = gene identification number. logFC = estimated log fold change between sample groups (for China the estimate is measured against AY; for Greece the estimate is measured against GR_S). logCPM = log2 counts per million. p-value = evidence for an effect of treatment on expression. FDR = multiple testing correction for p-value. Note that the number of rows do not equate to the number of total estimated genes (17001). This is because data with less than 5 read counts across all samples are removed from the analysis.edgeR_full_output.xlsxIdentified GO terms for Helicoverpa armigera genesThe file provides a list of GO-terms used in a functional enrichment analysis for genes involved in flight activity in Helicoverpa armigera. The list was generated using BLAST-2-GO. A total of 11316 genes (from a total of 17001) have identified GO-terms.go_terms.txtRaw qPCR data for RNA-seq validationData file consists of two excel sheets. The first sheet labelled 'ct' contains all raw Ct values that informed the qPCR analysis. Column headings are gene IDs for that particular gene. Information on qPCR primers and efficiency can be found in the Supplementary information. 'Treatment' = phenotype tested. 'Biorep' = biological replicate. 'Techrep' = technical replicate. The second sheet ('validation') contains the fold-change comparisons that informed the RNA-seq validation analysis. Validations were performed for each software package - edgeR and DEseq2. Comparisons were made only in instances when the gene was significantly differentially expressed in the RNA-seq.jones_mol_ecol_qpcr_ct.xlsx