DOI: 10.5061/dryad.8sf7m0cmk
title: Annotation and evolutionary analysis of chemosensory gene sequence data in the Colorado potato beetle, Leptinotarsa decemlineata

description: Plants and plant-feeding insects comprise the majority of global species
 diversity, and their coevolutionary dynamics provide an important window
 into the mechanisms that mediate niche evolution. In particular, there is
 considerable interest in understanding the nature of genetic changes that
 allow host-plant shifts to occur and to determine whether functional
 genomic diversity varies predictably in relation to host-plant breadth.
 Insect chemosensory proteins play a central role in mediating insect-plant
 interactions, as they directly influence plant detection and sensory
 stimuli during feeding. This large group of gene families is known to
 evolve rapidly, yet it remains unclear how these genes evolve in response
 to host-shifts and host specialization. Here we investigate whether
 selection at chemosensory genes is linked to host-plant expansion in the
 Colorado potato beetle (CPB), Leptinotarsa decemlineata (Coleoptera:
 Chrysomelidae), and whether rates of selection vary among ten closely
 related Leptinotarsa species. To develop functional hypotheses of
 chemosensory genes involved in the detection of potato host-plants, we
 combine gene expression analysis of the antennae and maxillary-labial
 palps using RNA sequencing with genomic evidence of natural selection. We
 show that expression of chemosensory genes differs among pest populations
 of Leptinotarsa decemlineata and numerous genes are under positive
 selection. We also find that rates of positive selection on olfactory
 receptors are higher in host-plant generalists, whereas rates are higher
 for gustatory receptors and olfactory binding proteins in host-plant
 specialists.
description: <strong>Chemosensory annotations</strong>: Building
 upon prior genes models (Liu et al. 2015, Schoville et al. 2018, Mitchell
 et al. 2019), chemosensory genes were manually edited using the
 tissue-specific RNA sequence data. We focused on identifying new genes and
 resolving known problems in the annotation of OR and GR
 families. <strong>Gene expression
 analysis</strong>: We generated RNA sequencing datasets
 (NCBI: PRJNA716273; 2x125 bp HiSeq2500) to compare gene expression data in
 chemosensory organ tissues (antennae versus palps) of adult <em>L.
 decemlineata</em>. For further population comparison, we also
 obtained RNAseq reads (NCBI SRA Accessions: SRR1948057 and SRR1948059, 2 x
 100 bp, HiSeq2000) generated from the antennae of adult male and female
 <em>L. decemlineata </em>from a site in Xinjiang, China by Liu
 et al. (2015). We additionally obtained published whole-body RNAseq reads
 for a non-pest population from Colorado (n=6) and a pest population from
 Wisconsin (n=9) to examine gene expression variation in comparisons of
 populations.  <strong>Population genomic
 analysis: </strong>We used whole-genome resequencing data (NCBI
 PRJNA580490) to compare nucleotide diversity and signatures of positive
 selection in olfactory genes between pest and non-pest lineages of
 <em>L. decemlineata</em>. We first used SNP genotypes
 identified by Pélissié <em>et al</em>. (2021) as input for
 BEAGLE 4.1 (Browning and Browning 2016) to generate phased, genome-wide
 haplotype sequences (two per individual) and then isolated chemosensory
 loci of the annotated families.
 <strong>Phylogenomic analysis:</strong> Among the ten
 <em>Leptinotarsa</em> species (NCBI PRJNA580490), gene models
 were isolated from <em>de novo </em>genomes of each
 <em>Leptinotarsa</em> species following the procedures
 described therein. In brief, chemosensory orthologs were first identified
 using a multiphase heuristic algorithm implemented by the spALN v2.3.3
 program (Gotoh 2008), which efficiently maps cDNA sequences onto whole
 genomes (options -M4 -O6 -S0 -Q7 -LS were selected). These sequences were
 subsequently aligned to each other, using the CPB reference ortholog
 sequence, via a custom C program CATaNNN v4.0 (Weibel and Cohen 2018) and
 MAFFT v7.450 (Katoh and Standley 2013). We corrected for misalignment and
 quality using Guidance v2.02, at high stringency, with 30 bootstrap
 replicates per alignment (Penn et al. 2010).
description: All files can be opened using text editors.
description: This data directory contains files supporting the project
 "Chemosensory genes in Leptinotarsa decemlineata", by Zachary
 Cohen, Michael S. Crossley, Robert F. Mitchell, Patamarerk Engsontia,
 Yolanda H. Chen, and Sean D. Schoville. Please contact Sean Schoville with
 any questions: sean.schoville@wisc.edu ### Description of data and file
 structure The files below contain genetic sequence data or derived data
 that have no units. #### File: CPB\_chemosensory\_sequences.fasta This
 file contains the nucleotide coding sequences of Colorado potato beetle
 chemosensory genes: each olfactory receptor (OR), ionotropic receptor
 (IR), odorant binding protein (OBP), and gustatory receptor (GR). These
 sequences were derived from a combination of genomic DNA and RNAseq data,
 with manual editing to annotate start/stop positions and splice sites.
 Sequence identifiers have a letter for a gene with alternatively spliced
 transcripts and an underscore with a number if part of a gene model.
 Annotation names are designated with the AnnotName field in the fasta
 header name. #### Files (1 ct): Annotation\_tables.xls This excel file
 contains information on the re\-annotation of chemosensory genes \(ORs and
 GRs\) undertaken in this paper\. Building upon prior genes models \(Liu et
 al\. 2015\, Schoville et al\. 2018\, Mitchell et al\. 2019\)\,
 chemosensory genes were manually edited using the tissue\-specific RNA
 sequence data\. We focused on identifying new genes and resolving known
 problems in the annotation of OR and GR families\. Earlier annotation
 efforts \(for the IRs and OBPs\) are documented in Schoville et al\.
 2018\. A model species for agricultural pest genomics: the genome of the
 Colorado potato beetle\, Leptinotarsa decemlineata \(Coleoptera:
 Chrysomelidae\)\. Scientific Reports 8\(1\): 1931\.
 https://www\.nature\.com/articles/s41598\-018\-20154\-1\. Abbreviations in
 the tables are as follows: The number \(No\.\) and name \(Gene name\)
 assigned to each gene; the newly added suffix \(Suffix\) or previous
 suffix \(Original\) that indicates whether the gene model has the
 following issue: CTE = C\-terminal missing; JOI = exons from two scaffolds
 joined into one gene model; FIX = model completed manually using raw
 reads; PSE = pseudogene; 1\-letter abbreviations for genes with multiple
 suffixes: FJ = FIX \+ JOI\.; de novo transcripts that match chemoreceptor
 genes \(Transcriptome\)\, coding sequence \(mRNA\) and protein sequence
 \(Protein\)\, genomic locations \(columns 'Scaffold'\,
 'Coordinates' \[start\-end position in genome\] and
 'Strand'\)\, number of introns and splicing phases
 \(INtrons\|phases\)\, number of amino acids \(AA\)\. Cells containing
 "not applicable" \(N/A\) have no suffix or note associated with
 them\. #### Files (2 ct): Annotation\_tables\*.csv These csv files are
 identifical to the Annotation\_table.xls above, but in machine-readable
 format for each spreadsheet. Each file contains information on the
 re-annotation of chemosensory genes (ORs or GRs) undertaken in this paper.
 Building upon prior genes models (Liu et al. 2015, Schoville et al. 2018,
 Mitchell et al. 2019), chemosensory genes were manually edited using the
 tissue-specific RNA sequence data. We focused on identifying new genes and
 resolving known problems in the annotation of OR and GR families. Earlier
 annotation efforts (for the IRs and OBPs) are documented in Schoville et
 al. 2018. A model species for agricultural pest genomics: the genome of
 the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera:
 Chrysomelidae). Scientific Reports 8(1): 1931.
 https://www.nature.com/articles/s41598-018-20154-1. Abbreviations in the
 tables are as follows: The number (No.) and name (Gene name) assigned to
 each gene; the newly added suffix (Suffix) or previous suffix (Original)
 that indicates whether the gene model has the following issue: CTE =
 C-terminal missing; JOI = exons from two scaffolds joined into one gene
 model; FIX = model completed manually using raw reads; PSE = pseudogene;
 1\-letter abbreviations for genes with multiple suffixes: FJ = FIX \+
 JOI\.; de novo transcripts that match chemoreceptor genes
 \(Transcriptome\)\, coding sequence \(mRNA\) and protein sequence
 \(Protein\)\, genomic locations \(columns ’Scaffold’\, ’Coordinates’
 \[start\-end position in genome\] and ’Strand’\)\, number of introns and
 splicing phases \(INtrons\|phases\)\, number of amino acids \(AA\)\. Cells
 containing "not applicable" \(N/A\) have no suffix or note
 associated with them\. #### File (1 ct): RNAseq\_read\_counts.xls This
 Excel file contains the read count data (number of reads per gene) for
 tissue and among-population differential expression analyses. We generated
 RNA sequencing datasets (NCBI: PRJNA716273; 2x125 bp HiSeq2500) to compare
 gene expression data in chemosensory organ tissues (antennae versus palps)
 of adult L. decemlineata. For further population comparison, we also
 obtained RNAseq reads (NCBI SRA Accessions: SRR1948057 and SRR1948059, 2 x
 100 bp, HiSeq2000) generated from the antennae of adult male and female L.
 decemlineata from a site in Xinjiang, China by Liu et al. (2015). We
 additionally obtained published whole-body RNAseq reads for a non-pest
 population from Colorado (n=6) and a pest population from Wisconsin (n=9)
 to examine gene expression variation in comparisons of populations. Short
 read data were mapped to the CPB genome v1.1 (NCBI Project: PRJNA171749)
 and read counts per sample per gene were generated by combining our new
 chemoreceptor annotations with the L. decemlineata official gene set
 (OGSv1.1) from Schoville et al. (2018). Counts were obtained using the
 functions makeTxDbFromGFF, transcriptsBy, and summarizeOverlaps available
 in the R packages GenomicAlignments and GenomicFeatures (Lawrence et al.,
 2013). The first worksheet provides results from the tissue specific
 samples, including published data from a population in China. Samples
 represent pooled adult individuals, separated by tissue type and sex. The
 second worksheet provides results from comparisons of adult populations
 using whole body tissues, where each sample represents an indvidual
 beetle. #### Files (4 ct): Leptinotarsa\_\*\_msa.tgz Each tarballed file
 contains a directory of files that represent the multiple sequence
 alignments (multi-fasta format) of chemoreceptor genes used for
 interspecific comparisons in the branch site test in Hyphy. Among the ten
 Leptinotarsa species (NCBI PRJNA580490), gene models were isolated from de
 novo genomes of each Leptinotarsa species following the procedures
 described therein. In brief, chemosensory orthologs were first identified
 using a multiphase heuristic algorithm implemented by the spALN v2.3.3
 program (Gotoh 2008), which efficiently maps cDNA sequences onto whole
 genomes (options -M4 -O6 -S0 -Q7 -LS were selected). These sequences were
 subsequently aligned to each other, using the CPB reference ortholog
 sequence, via a custom C program CATaNNN v4.0 (Weibel and Cohen 2018) and
 MAFFT v7.450 (Katoh and Standley 2013). We corrected for misalignment and
 quality using Guidance v2.02, at high stringency, with 30 bootstrap
 replicates per alignment (Penn et al. 2010). Each file is named by the
 gene name, and in the file each species name occurs at the sequence header
 (e.g. "&gt;Ldecemlineata") followed by the sequence. ####
 Files (4 ct): CPB\_.tar.gz Each tarballed file contains a directory of
 files that represent the multiple sequence alignments (multi-fasta format)
 of chemoreceptor genes used for intraspecific comparisons in the
 Tajima's D and McDonald-Kreitman test. We used whole-genome
 resequencing data (NCBI PRJNA580490) to compare nucleotide diversity and
 signatures of positive selection in olfactory genes between pest and
 non-pest lineages of L. decemlineata. We first used SNP genotypes
 identified by Pélissié et al. (2021) as input for BEAGLE 4.1 (Browning and
 Browning 2016) to generate phased, genome-wide haplotype sequences (two
 per individual) and then isolated chemosensory loci of the annotated
 families. Each file is named by the gene name, and the entries represent
 individual samples of Leptinotarsa decemlineata (e.g.
 "&gt;CPBWGS\_"). See Supplemental File 1 Table S1 for a key
 to the individual ids. #### File (1 ct): Trinity\_denovo.zip This fasta
 file contains the de novo transcriptome nucelotide sequences generated for
 chemosensory gene annotation. RNA sequencing reads (NCBI SRA Accessions:
 SRR1948057 and SRR1948059, 2 x 100 bp, HiSeq2000) from Wisconsin antennae
 and palps tissues were used to generate this assembly. using the software
 Trinity v2.3.2 (Haas et al., 2013). We first trimmed adaptor sequences and
 low-quality bases from Illumina reads using Trimmomatic v0.36 (Bolger et
 al., 2014), and then used default settings to assemble a transcriptome in
 Trinity.