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Molecular Characterization of the Aphis gossypii Olfactory Receptor Gene Families

  • Depan Cao ,

    Contributed equally to this work with: Depan Cao, Yang Liu

    Affiliations Laboratory of Pesticide, College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, China, State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China

  • Yang Liu ,

    Contributed equally to this work with: Depan Cao, Yang Liu

    Affiliation State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China

  • William B. Walker,

    Affiliation Swedish University of Agricultural Sciences, Department of Plant Protection Biology, Chemical Ecology Research Group, Alnarp, Sweden

  • Jianhong Li ,

    jianhl@mail.hzau.edu.cn (JL); grwang@ippcaas.cn (GW)

    Affiliation Laboratory of Pesticide, College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, China

  • Guirong Wang

    jianhl@mail.hzau.edu.cn (JL); grwang@ippcaas.cn (GW)

    Affiliation State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China

Abstract

The cotton aphid, Aphis gossypii Glover, is a polyphagous pest that inflicts great damage to cotton yields worldwide. Antennal olfaction, which is extremely important for insect survival, mediates key behaviors such as host preference, mate choice, and oviposition site selection. In insects, odor detection is mediated by odorant receptors (ORs) and ionotropic receptors (IRs), which ensure the specificity of the olfactory sensory neuron responses. In this study, our aim is to identify chemosensory receptors in the cotton aphid genome, as a means to uncover olfactory encoding of the polyphagous feeding habits as well as to aid the discovery of new targets for behavioral interference. We identified a total of 45 candidate ORs and 14 IRs in the cotton aphid genome. Among the candidate AgoORs, 9 are apparent pseudogenes, while 19 can be clustered with ORs from the pea aphid, forming 16 AgoOR/ApOR orthologous subgroups. Among the candidate IRs, we identified homologs of the two highly conserved co-receptors IR8a and IR25a; no AgoIR retain the complete glutamic acid binding domain, suggesting that putative AgoIRs bind different ligands. Our results provide the necessary information for functional characterization of the chemosensory receptors of A. gossypii, with potential for new or refined applications of semiochemicals-based control of this pest insect.

Introduction

Chemical senses are critical for most animals, due to the fact that most key behaviors, such as foraging, mating and predator-avoidance, are strongly dependant upon chemical sensing. The importance is most significantly realized in insects by their iconic protuberant antenna, which is the primary olfactory organ. The chemosensory structure, sensilla, can be found across the whole body of the insect. Most sensilla are distributed on the surface of olfactory organs, such as antennae, mouth parts, legs, wings and ovipositor [1]. Olfactory receptor neurons (ORNs) are the terminal interfaces of the chemical sensing systems, which are hosetd in the root of sensilla and project their dendrites into the cavity of sensilla. The chemosensory receptors (CR), which are located within the cell membrane of the ORN dendrite, confer the specificity of the OSN olfactory responses.

The insect chemoreceptor superfamily was first identified in the Drosophila melanogaster genome and consists of the odorant receptor (OR) family and the gustatory receptor (GR) family. Genes from these families are expressed at low levels in the antennae, maxillary palps, and other tissues [2]. These seven-transmembrane-domain (7TM) proteins [3][6] were thought to be ligand-gated ion channels, which are evolutionarily distant from the vertebrate G-protein–coupled receptors (GPCRs) chemosensory receptor family [7][13]. In 2009, a different class of ligand-gated ion channel, the ionotropic receptor (IR), was identified as an additional repertoire of chemoreceptors of ORs and GRs [14]. The IRs belong to a variant subfamily of ionotropic glutamate receptors (iGluRs), which is best known for their role in allowing neurons to communicate with each other in the brain. Evidence of highly divergent iGluRs, expressing in olfactory organs, with chemosensory sensillla subcellular localization combined with mis-expression experiments has provided direct genetic evidence for the role of IRs in odor sensing [15].

In D. melanogaster, 62 olfactory receptors (OR) and 68 gustatory receptors (GR) were detected, with alternative splice variants also identified. Comparison to the 79 ORs and 76 GRs from Anopheles gambiae revealed that GRs of the heteromeric carbon dioxide receptors and several sugar receptors are conserved [16][18] but ORs of different species are highly divergent, and that few simple orthologous relationships remained. One exception is the DmOR83b and its ortholog in A. gambiae AgOR7, which function as a heterodimerization partner for all of the other ORs and is broadly conserved [19], [20]. This species-specific expansion trend of ORs is confirmed by genome sequencing of other insects. Within the genomes of Bombyx mori, Apis mellifera, Aedes aegypti, and Nasonia vitripennis, 41, 170, 131 and 301 ORs were respectively identified [21][24]. All of these works demonstrate that the OR family undergoes rapid evolution in a species-specific manner, with the exception of the DmOR83b orthologs, now referred to as Orco, to reflect their funciton as the OR co-receptor. Recent transcriptome works on Lepidoptera sexual pheromone receptors, however, provide an example of inter-species OR homologs. As that Lepidopterans use long chain polyunsaturated fat acid analogues for their sexual pheromone communication, the Lepidopterans’ pheromone receptor genes are conserved enough that they can be grouped together as a subfamily of ORs in inter-species phylogenetic analyses [25]. Aphids are model organisms in both evolutionary and applied biology. For evolutionary biologists, the extended group of more than 4,000 species and specialization to their host plants make aphids the perfect model to study evolution and coevolution between plants and herbivorous insects [26], [27]. For example, genetic differences have been reported between Acyrthosiphon pisum host plant races with reproductive isolation occurring as by-product of host adaptation [28], [29]. For applied biology, aphids represent one of the major pests in agriculture, with the characteristics of rapid breeding, causing great economic losses and serious insecticide dependence for population control.

The cotton aphid, Aphis gossypii Glover, is a polyphagous pest that damages cotton through direct feeding on the underside of leaves or on the growing tips of shoots. Feeding is carried out through the sucking of juices from the plant, causing leaf curling and distortion, which greatly hinders efficient photosynthesis, and induces foliage chlorotic and premature death. Unlike the monophagous Pea aphid (Acyrthosiphon pisum), the cotton aphid has a very wide host range of over 700 species world-wide, including watermelons, cucumbers, pumpkin, pepper, eggplant, okra and hibiscus [30]. As the genome of the cotton aphid had been sequenced and is under continuous refinement, we report our chemosensory receptor gene analysis of 45 ORs and 13 IRs, and the expression profiles of these families.

Materials and Methods

Identification of cotton aphid ORs and IRs by bioinformatics

The 3rd assembly version of A. gossypii genome was queried using previously described OR sequences from A.pisum [31], An. Gambiae [32], D. melanogaster [4], [33], [34] and other known ORs and IRs from GenBank by tblastn, in order to obtain possible OR and IR exons. Genomic scaffold sequences of exons found in tblastn were used to construct putative OR and IR sequences manually using Sequencher v4.5 (Gene Codes, Inc., Ann Arbor, MI) and refined using SplicePredictor (http://deepc2.psi.iastate.edu/cgi-bin/sp.cgi/). All A. gossypii ORs identified in this manner were in turn used in successive tblastn searches to identify other candidate sequences, which were annotated as above. Cotton aphid OR genes were named as “AgoOR” with a number which is confirmed by similarity with Pea aphid ORs. Due to high divergence and/or discontinuity among scaffolds, not all detected OR/IR genes could be entirely annotated: In these cases, deduced amino acid sequences shorter than 150 amino acids were discarded as probable gene fragments, while for sufficiently long partial sequences a suffix N, C or M after the gene–protein name was used to indicate that the 5′ terminus (N) or 3′ terminus (C) or the internal exon (M) is missing. When frameshifts or stop codons were identified in the gene sequence, we defined these genes as putative pseudogenes (suffix P). As highly similar gene models were found in our annotations, pairwise alignment was used to detect single nucleotide differences and non-frameshift gaps. If one sequence had only non-frameshift gaps and located on a separate small contig, they were considered to be likely allelic variants and excluded from the final list. If some sequences were located in long tandem arrays in one contig, they were considered to be paralogs and were kept, ignoring their similarities to other sequences. For highly divergent sequence detection, artificial gene models were used as queries in PSI-blastp searches against the A. gossypii unigenes database and genome annotation database. Sequences detected in PSI-blastp were mapped to the genome to confirm and extend the artificial annotation. The final annotations of artificial gene models were supported to be OR/IR by matches to other insect CRs using blastp against the NCBI non-redundant protein database (nr). AgoORs were confirmed by their trans-member structures using TMHMM [6].

Intron/exon analysis

The predicted structure of each AgoOR gene was reconstructed and recorded as described above. The structure of each Pea Aphid odorant receptors were obtained by mapping ApOR sequences to the Pea aphid genome assembly version 2 (http://www.aphidbase.com/aphidbase/downloads) with GMAP [35]. The splice sites of AgoORs and ApORs nucleotide sequences were transformed into deduced amino acid coordinates with ORF phase indicated. Deduced amino acid sequences of AgoORs were aligned with ApORs using ClustalW [36]. Then the splice positions of AgoORs and ApORs were transformed into amino acid coordinates and mapped to the aligned peptide sequences. Only the most parsimonious intron locations were considered to be conserved. All other were considered idiosyncratic.

Phylogenetic analysis

Deduced amino acid sequences of AgoORs were aligned with ApORs by ClustalW using default settings. Corrected distances were obtained using the maximum likelihood method in MEGA5.10 [37] with the Jones-Taylor-Thornton amino acid substitution model (JTT model) and otherwise default settings. Node support was assessed using a bootstrap procedure based on 1000 replicates. The AgoIR phylogenetic analysis was performed as above, while the reference dataset contained 12, 18, and 66 IR sequences from S. littoralis, B. mori, D. melanogaster, respectively and 10 iGluRs sequences from D. melanogaster [25].

Quantitative real-time PCR (qRT-PCR) analysis

Cotton aphids from a laboratory colony, which has been raised on cotton seedling for over ten years, were used in our qRT-PCR analysis. Different parts and organs of cotton aphid were collected. The forepart of the aphid head was collected by clipping beneath the ommateum using a precise scissors. This part containing antenna, proboscis and part of the aphid head, was marked as “head”. The aphid “leg” sample was collected by directly tweezing from the very root of the legs. The aphid “body” sample contains the thorax and abdomen without legs.

Total RNA of different samples was extracted separately using TRIZOL, and 2 µg total RNA of each sample was reverse-transcribed by the One-Step gDNA Removal and cDNA Synthesis kit (TRANSGEN, China) using Ploy-T primer. qRT-PCR was performed on ABI Prism 7500 real-time PCR system (Applied Biosystems, Foster City, CA, USA) using the GoTaq qPCR Master Mix (Promega), according to the manufacturers’ instructions. The first-strand cDNA (2 µl) and the no-template control (NTC, 2 µl) were used as templates for three technical replication assays in each 20 µl reaction mixture under the following conditions: denaturation at 95°C for 60 s, followed by 40 cycles of 95°C for 15 s and 60°C for 60 s. After amplification, melting curves were constructed of the temperature range 60–95°C and data analysis was performed on SDS software with the ABI 7500 system. The results were standardized to the expression level of cotton aphid GAPDH gene. The 2−ΔΔCt method [38] was used to analyze the relative differences in the transcript levels.

Results

The odorant receptor family

We identified a total of 45 candidate AgoOR genes in the genome of A. gossypii. Of these, 22 genes encode putative, complete functional proteins, 14 are incompletely annotated genes, and 9 are apparent pseudogenes (Table 1). As is well-known, a reliable homology based gene prediction is heavily dependent on the maturity of the genome assembly. That means the inevitable refinement of genome assembly will ultimately result in changes in the known complexity of the AgoOR gene family. But according to the current available assembly version 3, these represent the complete OR repertoire in the A. gossypii genome. During our gene prediction procedure, more than 100 sites in the genome displayed potential homology with queried OR sequences. However, half of these sites were located on small scaffolds with length less than 10K nt, which produced incomplete ORFs or short coding fragments. Most of these fragments were filtered as redundant sequences because of their high similarity with other AgoORs. The sequences of putative AgoORs are attached in Supplementary Material S1.

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Table 1. Summary of putative odorant receptor genes of A. gossypii.

https://doi.org/10.1371/journal.pone.0101187.t001

Due to the high divergence of insect ORs as well as genome complexites, full-length annotation of AgoORs is difficult. In our study, 7 gene models are incompletely annotated as a result of failure to detect 5′ and 3′ ends. AgoOR18, 22 and 40 are short gene models consisting of only one or two recognizable exons and encode peptides less than 200aa; AgoOR11 and 34 are relatively long gene models, located on big scaffolds and near other AgoORs, but their N and C terminal ends remain undetected. Large introns, assembly errors and sequencing gaps may also result in incomplete gene models. AgoOR5, 9, 17, 19, 28, 32 and 33 are marked incomplete as there are unknown nucleotides (Ns) in their exons or are apparently matched to the terminal ends of known insect OR but the internal sequence remains unidentified. These gene models also failed in the TMHMM test, as intact OR genes should have a hallmark of seven-transmembrane-domains (Table 1).

Pseudogenes are another reason for incomplete sequences. Notably, we identified 9 potential pseudo-ORs out of 45 odorant receptors, which is reflective of a high rate of pseudoenization. All pseudogenes are the result of frameshifts caused by indels in their open-reading frames. Pseudogenes are rare occurrences in model insects like D. melanogaster and An. gambiae genomes [39]. In pea aphid genome there are also 10 pseudo-ORs detected, but the total number of ApORs is 73, nearly twice that of the OR family of cotton aphid. This phenomenon is likely to be caused by sequencing errors or misassemblies in the cotton aphid genome.

Amino acid identity percentage between genes represents the similarity of two genes. We collected the identity data of AgoORs versus ApORs. As a result, the average identity percentage of all 45 AgoORs versus ApORs is 54.76%; the average identity of intact genes is 64.08%. 26 AgoORs have identities higher than 50%. By phylogenetic analysis of the proteins encoded by the 45 AgoORs along with the 73 ApORs, we identified 16 AgoOR/ApOR orthologous subgroups, which contain 19 AgoOR in total. Orthologous subgroup with the highest identity, 95.0%, is the AgoOrco/ApOR1 subgroup, representing the highly conserved Orco genes including the Drosophila Orco (OR83b) gene, Ae. aegypti and An. gambiae Orco (OR7) genes and B. mori Orco (OR2) gene. These two genes are clear orthologs as prior research in Drosophila have proven that Orco are essential for olfactory signal transduction [8], [19]. Other than the Orco family, orthologous subgroups with identities higher that 80% include the AgoOR2/ApOR2, AgoOR43/ApOR43 and AgoOR4/ApOR4 subgroups with 84.3%, 80.6%, and 80.1% identites respectively. Another eight AgoOR sequences (AgoOR 10, 20, 23, 37, 38, 39, 41 and 42) have closely related ApOR homologues, with identities greater than 70%.

Apart from the conserved ORs mentioned above, there are still several species-specific OR expansions found in AgoORs (Fig. 1). A total of five species-specific clades were found in the phylogenetic tree. The largest AgoOR clade contains AgoOR7, 8, 14, 16, 28, 34 and 36. Among them, AgoOR7, 8, 28 and 34 were located tandemly on Scarfold_S000485. Another four sequences in a tandem array, AgoOR25, 26, 29 and 30, which are located on Scarfold_S000381, formed another AgoOR-specific clade. Furthermore, these sequences in species-specific clades are relatively divergent, as none of them have identity higher than 50% to their most-similar ApORs.

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Figure 1. Phylogenetic relationships of the cotton aphid AgoORs with relative pea aphid ApORs.

This corrected distance tree was rooted by declaring the Orco gene orthologs (ApOR1–AgoOrco clade) as outgroup, based on the basal location of the Orco within the OR family. Support for major branches is shown above them as percent of 1,000 uncorrected distance bootstrap replications. Suffixes after gene names are: P–pseudogene, N–N-terminal exon(s) or region missing, C–C-terminal exon(s) or region missing, M–internal exon(s) or region missing. Species abbreviations are Ap – Acyrthosiphon pisum and Ago – Aphis gossypii.

https://doi.org/10.1371/journal.pone.0101187.g001

In addition, we identified 6 intron positions to be conserved among our AgoOR sequences, for reason that more than 8 AgoORs have introns at these positions. As shown in Fig. 2, the intron position of AgoORs and ApORs are mapped relative to a scale of the average receptor size in amino acids. 5 amino acid positions were detected as conserved intron positions in both AgoORs and ApORs. The most conserved intron sites are pos.299, pos.246 and pos.355, for which 45, 44, 43 ApORs and 31, 22, 21 AgoORs have introns at these sites, respectively. Other conserved positions, pos.267 and 269, were found in both AgoORs and ApORs of no less than 15 genes. By conjectures from early research, the quantity of OR genes in one species arise through gene duplication, since OR genes are always paired in tandem arrays in the genome and some ancient intron positions are retained in the gene clade [21]. Our intron position analysis conformed to this theory, as well as the tandem AgoORs in one scaffold.

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Figure 2. Intron analysis of A. gossypii and A. pisum OR genes.

The intron positions of A. gossypii and A. pisum OR genes are shown relative to a scale of the average receptor size in amino acids. The x-axis indicates the exon-exon junction positions relative to the amino acid scale of 400aa. The y-axis indicates the number of ORs harbouring each exon-exon junction positions.

https://doi.org/10.1371/journal.pone.0101187.g002

The ionotropic receptors family

The IRs in the cotton aphid genome were represented according to their similarity with known insect IRs. Bioinformatic analysis led to the identification of 13 candidates IRs, in which 11 sequences contain full-length ORFs, the remaining 2 sequences are marked as incomplete because of missing exons. Among these 13 candidate AgoIRs, 2 were named as AgoIR8a and AgoIR25a respectively, for their highly identity to the putative co-operator DmelIR8a and DmelIR25a (Table 2). 6 of the rest 11 sequences were named as “AgoIR” attached with a number inherited from their Dmel/Bmor/Slit IR homologs, as they scored high similarities to their homologs and credible bootstrap values in the phylogenetic test. The remaining five putative IR sequences presented neither enough similarity with previously characterized IRs, nor reliable bootstrap evidence in phylogenetic analysis. These 5 sequences were named as AgoIR2, 3, 4, 5 and 6. The sequences of putative AgoIRs are attached in Supplementary Material S2.

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Table 2. Summary of putative ionotropic receptor genes of A. gossypii.

https://doi.org/10.1371/journal.pone.0101187.t002

According to the characterization of DmelIRs, the insect IRs contain conserved regions with three transmembrane domains (M1, M2 and M3), a bipartite ligand-binding domain with two lobes (S1 and S2) and one ion channel pore (P) [14]. The most conserved region between IRs and iGluRs spans the ion channel pore (Fig. 3c), suggesting that IRs retain ion-conducting properties. We tested AgoIR sequences in TMHMM, which predicted that the candidate AgoIRs contain transmembrane domains ranging from 0 to 5, and only 3 candidate sequence, AgoIR6, 8, 25 show the typical three transmembrane domains (Table 2). But the protein secondary structure analysis by SMART showed that all AgoIRs except AgoIR21a, 5 and 6 have S1, S2 and PORE domains found. This phenomenon suggests that computational predictions could be inaccurate or that the gene models we annotated are probably incomplete.

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Figure 3. Conserved amino acid positions analysis of Drosophila iGluRs and A. gossypii IRs.

(A) Amino acid alignments of part of the S1 ligand binding domains. (B) Amino acid alignments of part of the S2 ligand binding domains. (C) Amino acid alignments of part of the pore loop (P) and M2 transmembrane segment of the ion channel domain. The positions of key ligand binding residues in iGluRs are marked with asterisks at the top.

https://doi.org/10.1371/journal.pone.0101187.g003

Among the conserved domains of iGluRs, the ligand-binding domains containing S1, S2 lobes are considerably more variable. But for the iGluRs family, some conserved amino acid positions were identified to be directly in contact with glutamate or artificial agonists [40][42]. Alignment of small regions of the S1 and S2 lobes of AgoIRs revealed that the arginine (R) residue that binds the glutamate α-carboxyl group in the S1 lobe was conserved in eight putative AgoIRs (Fig. 3a); the threonine (T) residue that binds the glutamate γ-carboxyl group in the first half of S2 lob was not retained in any of the 13 AgoIRs (Fig. 3b); a S2 lob end located aspartate (D) or glutamate (E) that interacts with the α-amino group of the glutamate ligand was retained in 6 AgoIRs (Fig. 3b). Thus, no AgoIRs retain the complete set of iGluRs characteristic residues, suggesting that putative AgoIRs bind different ligands.

To further distinguish putative IRs from iGluRs, AgoIRs were aligned with IR orthologues from D. melanogaster, B. mori, S. littoralis and some DmeliGluRs for phylogenetic analysis. The result revealed a clear segregation between DmeliGluRs and insect IRs (Fig. 4). The most conserved IR8a and IR25a clades, which contain AgoIR8a and AgoIR25a, were confidently clustered together with bootstrap support of more than 80%. Furthermore, amongst the entire IR gene family, the IR8a and 25a families contained the closest relatives to the iGluRs family, for the reason that they clustered into the big clade of DmeliGluRs and DmelNmdars. Other putative AgoIR sequences we identified did not cluster with iGluRs and grouped with other IRs.

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Figure 4. Unrooted tree of putative AgoIRs.

Ago: Aphis gossypii; Dmel: Drosophila melanogaster; Bmor: Bombyx mori; Slit: Spodoptera littoralis. Bootstrap support values presented as percentages were based on 1000 replicates. Accession numbers of sequences used in the analysis were listed in our previous paper (Liu et al., 2012).

https://doi.org/10.1371/journal.pone.0101187.g004

Validation by expression profile

To validate our annotation, we studied the expression of AgoORs and AgoIRs using qRT-PCR. Of all the 45 putative ORs, 38 sequences have expression detected. As shown in Fig. 5, all these putative ORs were mainly expressed in the sample “head”, which contains main olfaction organs like antenna and proboscis. The co-receptor gene AgoOrco showed a significant higher expression than most of the other ORs. This olfaction-organ enriched expression style is consistent with the typical olfaction-gene’s character, proving that the accuracy of our prediction is acceptable. Furthermore, there were 5 AgoORs showed a significant higher expression than others, even higher than the co-receptor AgoOrco. This phenomenon implied that these high-expression ORs may act important roles in the cotton aphid’s chemosensation. For the AgoIR dataset, all 13 putative AgoIRs were detected with a trend of olfaction-organ enrichment (Fig. 6). Like the Orco gene, IR8a and IR25a genes were thought to act as co-receptors because of their co-expression with other IRs. Our expression profile was consistent with this hypothesis by showing a significant higher expression of AgoIR8a and AgoIR25a genes. The primers used in our qRT-PCR analysis can be found in Supplementary Material S3.

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Figure 5. Expression profiles of putative AgoORs.

The expression was standardized to the expression level of cotton aphid GAPDH gene using 2−ΔΔCt method.

https://doi.org/10.1371/journal.pone.0101187.g005

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Figure 6. Expression profiles of putative AgoIRs.

The expression was standardized to the expression level of cotton aphid GAPDH gene using 2−ΔΔCt method.

https://doi.org/10.1371/journal.pone.0101187.g006

Discussion

Previous research on insect ORs revealed that odorant receptor genes are highly divergent among different species because OR genes undergo stringent Darwinian selection in the process of species formation. Comparing other insects such as D. melanogaster and B. mori, OR genes of cotton aphid indeed display a high degree of divergence. But in comparing AgoORs with ORs from a closely related species, Acyrthosiphon pisum, the result reveals a not-so-divergent relationship. The average identity of AgoOR-ApOR pairs is more than 50%, which is significantly greater than another relative species pair, Ae. aegypti and An. Gambiae, as the majority of AaORs share less than 20% identity at the amino acid level with OR peptides from An. Gambiae [21]. This phenomenon may probably due to the different relative distances between the two aphids and the two mosquitos, but whether other specific characteristics of aphids, such as parthenogernesis or ecological niche, were involved in the evolution procedure of aphid OR genes is not known and requires further research.

Compared to the large expansion clades of ApORs, the AgoOR clades are fewer and less diverse. One obvious reason is that the quantity of AgoORs is far less than the ApORs. Our phylogenetic tree shows that most of the AgoORs are clustered together with ApORs and the AgoOR specific expansion is rather small. From the common viewpoint that life is a system of maximum energy savings, less genes associated with odorants suggests lower sensitivity to different odorant stimulation. This phenomenon can be easily reconciled with the polyphagous nature of the cotton aphid–fewer odorant receptors make it difficult for the cotton aphid to differentiate between different plants. While for the oligophagous pea aphid, the large family of 73 ORs may likely make pea aphid sensitive to the specific odorants of its few host plants.

But what is the relationship between the feeding habit and OR quantity? Does the sensitive olfactory system make the pea aphid focus on few plants, or has the longtime process of species formation forced the pea aphid to evolve a complex OR family, while this Darwinian selection is relaxed on cotton aphid? We tried to preform selective pressure analysis by PAML using these predicted sequences, and we obtained some interesting results (data not shown). We focused on clades with different components in the phylogenetic trees, including ApOR-specific clades, ApOR-AgoOR-mix clades and AgoOR-specific clades. For the ApOR-specific clades, similar results were obtained as Samdja et al [31]–some sequences of the ApOR-specific expansion might have evolved under positive selection by one-radio model versus free-radio model. For the AgoOR-ApOR-mixed clade, there were still sequences with ω>1 found but the P-Value (after Bonferroni Correction) test stands on the edge of rejection. For the AgoOR-specific clade, no sequence was detected with ω>1. Although performing molecular evolution tests on sequences not obtained from strict molecular cloning procedure is unpersuasive, this attempt gave us some ideas about the differences between the species formation of pea aphid and cotton aphid. As the division of Marcosiphini and Aphidini was thought to happen about 62 million years ago [43], there is reason enough for us to think about whether the olfactory systems of pea aphid and cotton aphid have undergone entirely different types of selection subsequent to parting ways in evolution.

Beyond that, there is still one nonnegligible phenomenon–the pseudogene rate of AgoORs is much higher than that in ApORs. Sequencing error and mis-assembly could be one reason, and the evaluation requires further research, including cloning and sequencing, transcriptome sequencing of olfactory organs and genome-resequencing. But before these confirmations are done, we should think about the possibility that the pea aphid and cotton aphid have different mechanisms in gene formation, especially in the OR family. As is widely agreed, adapting to different hosts is a key factor to the division of aphids. The gossypii group of Aphidini was formed in the later stage of Oligocene [43] and expanded to over 40 species until now. Conversely, the Acyrthosiphon of Marcosiphini seems being relatively slow in the step of speciation, as only about 10 Acyrthosiphon species were found. However, the current-available taxonomy databases may not represent all aphid species from these families.

The Ionotropic Receptor family, which was recently proposed to detect environmental volatile chemicals in olfactory cilia, is a variant iGluR subfamily. Animal iGluRs have been best characterized for their essential roles in synaptic transmission as receptors for the excitatory neurotransmitter glutamate [44], [45]. Three subfamilies with distinct molecular and pharmacological properties were identified in both vertebrates and invertebrates, which are named following their main agonist: a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), kainate and N-methyl-D-aspartate (NMDA). IRs share a considerable degree of commonalities with the typical iGluRs: firstly, they are all located to specialized distal membrane domains of neuronal dendrites (cilia and post-synaptic membranes, respectively); secondly, response to binding of extracellular ligands (volatile component and neurotransmitter); thirdly, the multimer form of functional complexes (IR8a/25a co-express with other cell-type specific IRs and the heteromeric assembly of iGluR subunits). It is easy to conjecture that the IR arose from an iGluR with a change in expression localization from an interneuron to a sensilla neuron [15].

Compared to insect ORs, the IR family is relatively conserved. As the Orco is the only homolog gene that discovered extensively among insect species, many D. melanogaster antennal IRs are conserved in insects, both in sequence and expression pattern, let alone the highly conserved IR8a and IR25a. There is also evidence in evolution that a Paleoptera insect Rhithrogena semicolorata bears coeloconic sensilla that contains IR-expressing neurons, but no trichoid or basiconic sensilla found [46]. In conclusion, it is conceivable that the IR family is a more ancient chemosensory receptor family than the OR/GR gene family. And considering that there are fewer IR genes, but IRs show relatively higher conservation than ORs, it is reasonable to think that IRs may probably function to detect molecules being physiologically and behaviorally important to many insect species, and ORs may be primarily dedicated to detection of species-specific odor cues. In our study, orthologues for all 14 putative IRs were found in other species, indicating that the AgoIRs may function similarly to Dmel antennal IRs, where there is relatively clarity concerning ligands. By far, the known IR ligands include carboxylic acids, ammonia, etc. [47]. Similar compounds have been recorded in GC-EAG analysis or bioassays that can elicit electrophysiological or behavioral response in the aphid [48][54]. In all, our 14 putative AgoIRs were the first report of IRs in the whole family of aphids. This extensively conserved chemosensory receptor family could be a source for new targets of broad-spectrum insect repellents.

Conclusion

We believe that our approach has thoroughly identified the OR and IR families in the current version of the A. gossypii genome. This enables further investigation of chemosensation in the cotton aphid, in particular explaining the difference in feeding habits between polyphagous and monophagous aphids. The discovery of ORs and IRs will also assist in the explanation of some classic behaviors like the inter-species alarm behavior and the self-regulation of aphid population, as well as in the discovery of novel volatile compounds, which would give new options for aphid population control by disorientation, mass trapping, or breeding trap crops.

Supporting Information

Supplementary Material S3.

Primer sequences used in the quantitative real-time PCR analysis.

https://doi.org/10.1371/journal.pone.0101187.s003

(XLSX)

Acknowledgments

We thank Dr. Yongping Huang for providing cotton aphid genome sequence.

Author Contributions

Conceived and designed the experiments: DC YL JL GW. Performed the experiments: DC YL GW. Analyzed the data: DC YL WW JL GW. Contributed reagents/materials/analysis tools: DC YL WW GW. Contributed to the writing of the manuscript: DC JL GW.

References

  1. 1. van der Goes van Naters W, Carlson JR (2006) Insects as chemosensors of humans and crops. Nature 444: 302–307.
  2. 2. Rutzler M, Zwiebel LJ (2005) Molecular biology of insect olfaction: recent progress and conceptual models. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 191: 777–790.
  3. 3. Clyne PJ, Warr CG, Carlson JR (2000) Candidate taste receptors in Drosophila. Science 287: 1830–1834.
  4. 4. Clyne PJ, Warr CG, Freeman MR, Lessing D, Kim J, et al. (1999) A novel family of divergent seven-transmembrane proteins: candidate odorant receptors in Drosophila. Neuron 22: 327–338.
  5. 5. Gao Q, Chess A (1999) Identification of candidate Drosophila olfactory receptors from genomic DNA sequence. Genomics 60: 31–39.
  6. 6. Krogh A, Larsson B, von Heijne G, Sonnhammer EL (2001) Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol 305: 567–580.
  7. 7. Bargmann CI (2006) Comparative chemosensation from receptors to ecology. Nature 444: 295–301.
  8. 8. Benton R, Sachse S, Michnick SW, Vosshall LB (2006) Atypical membrane topology and heteromeric function of Drosophila odorant receptors in vivo. PLoS Biol 4: e20.
  9. 9. Lundin C, Kall L, Kreher SA, Kapp K, Sonnhammer EL, et al. (2007) Membrane topology of the Drosophila OR83b odorant receptor. FEBS Lett 581: 5601–5604.
  10. 10. Smart R, Kiely A, Beale M, Vargas E, Carraher C, et al. (2008) Drosophila odorant receptors are novel seven transmembrane domain proteins that can signal independently of heterotrimeric G proteins. Insect Biochem Mol Biol 38: 770–780.
  11. 11. Wistrand M, Kall L, Sonnhammer EL (2006) A general model of G protein-coupled receptor sequences and its application to detect remote homologs. Protein Sci 15: 509–521.
  12. 12. Sato K, Pellegrino M, Nakagawa T, Nakagawa T, Vosshall LB, et al. (2008) Insect olfactory receptors are heteromeric ligand-gated ion channels. Nature 452: 1002–1006.
  13. 13. Wicher D, Schafer R, Bauernfeind R, Stensmyr MC, Heller R, et al. (2008) Drosophila odorant receptors are both ligand-gated and cyclic-nucleotide-activated cation channels. Nature 452: 1007–1011.
  14. 14. Benton R, Vannice KS, Gomez-Diaz C, Vosshall LB (2009) Variant ionotropic glutamate receptors as chemosensory receptors in Drosophila. Cell 136: 149–162.
  15. 15. Croset V, Rytz R, Cummins SF, Budd A, Brawand D, et al. (2010) Ancient protostome origin of chemosensory ionotropic glutamate receptors and the evolution of insect taste and olfaction. PLoS Genet 6: e1001064.
  16. 16. Dahanukar A, Lei YT, Kwon JY, Carlson JR (2007) Two Gr genes underlie sugar reception in Drosophila. Neuron 56: 503–516.
  17. 17. Kent LB, Walden KK, Robertson HM (2008) The Gr family of candidate gustatory and olfactory receptors in the yellow-fever mosquito Aedes aegypti. Chem Senses 33: 79–93.
  18. 18. Kwon JY, Dahanukar A, Weiss LA, Carlson JR (2007) The molecular basis of CO2 reception in Drosophila. Proc Natl Acad Sci U S A 104: 3574–3578.
  19. 19. Jones WD, Nguyen TA, Kloss B, Lee KJ, Vosshall LB (2005) Functional conservation of an insect odorant receptor gene across 250 million years of evolution. Curr Biol 15: R119–121.
  20. 20. Krieger J, Klink O, Mohl C, Raming K, Breer H (2003) A candidate olfactory receptor subtype highly conserved across different insect orders. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 189: 519–526.
  21. 21. Bohbot J, Pitts RJ, Kwon HW, Rutzler M, Robertson HM, et al. (2007) Molecular characterization of the Aedes aegypti odorant receptor gene family. Insect Mol Biol 16: 525–537.
  22. 22. Robertson HM, Gadau J, Wanner KW (2010) The insect chemoreceptor superfamily of the parasitoid jewel wasp Nasonia vitripennis. Insect Mol Biol 19 Suppl 1121–136.
  23. 23. Robertson HM, Wanner KW (2006) The chemoreceptor superfamily in the honey bee, Apis mellifera: expansion of the odorant, but not gustatory, receptor family. Genome Res 16: 1395–1403.
  24. 24. Wanner KW, Anderson AR, Trowell SC, Theilmann DA, Robertson HM, et al. (2007) Female-biased expression of odourant receptor genes in the adult antennae of the silkworm, Bombyx mori. Insect Mol Biol 16: 107–119.
  25. 25. Liu Y, Gu S, Zhang Y, Guo Y, Wang G (2012) Candidate olfaction genes identified within the Helicoverpa armigera Antennal Transcriptome. PLoS One 7: e48260.
  26. 26. Berlocher SH, Feder JL (2002) Sympatric speciation in phytophagous insects: moving beyond controversy? Annu Rev Entomol 47: 773–815.
  27. 27. Via S, West J (2008) The genetic mosaic suggests a new role for hitchhiking in ecological speciation. Mol Ecol 17: 4334–4345.
  28. 28. Ferrari J, Via S, Godfray HCJ (2008) Population differentiation and genetic variation in performance on eight hosts in the pea aphid complex. Evolution 62: 2508–2524.
  29. 29. Via S, Hawthorne DJ (2002) The genetic architecture of ecological specialization: correlated gene effects on host use and habitat choice in pea aphids. The American Naturalist 159: S76–S88.
  30. 30. Schirmer S, Sengonca C, Blaeser P (2008) Influence of abiotic factors on some biological and ecological characteristics of the aphid parasitoid Aphelinus asychis (Hymenoptera: Aphelinidae) parasitizing Aphis gossypii (Sternorrhyncha: Aphididae). European Journal of Entomology 105: 121.
  31. 31. Smadja C, Shi P, Butlin RK, Robertson HM (2009) Large gene family expansions and adaptive evolution for odorant and gustatory receptors in the pea aphid, Acyrthosiphon pisum. Mol Biol Evol 26: 2073–2086.
  32. 32. Hill CA, Fox AN, Pitts RJ, Kent LB, Tan PL, et al. (2002) G protein-coupled receptors in Anopheles gambiae. Science 298: 176–178.
  33. 33. Vosshall LB, Amrein H, Morozov PS, Rzhetsky A, Axel R (1999) A spatial map of olfactory receptor expression in the Drosophila antenna. Cell 96: 725–736.
  34. 34. Zwiebel LJ, Takken W (2004) Olfactory regulation of mosquito-host interactions. Insect Biochem Mol Biol 34: 645–652.
  35. 35. Wu TD, Watanabe CK (2005) GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 21: 1859–1875.
  36. 36. Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22: 4673–4680.
  37. 37. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, et al. (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28: 2731–2739.
  38. 38. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25: 402–408.
  39. 39. Krzywinski J, Wilkerson RC, Besansky NJ (2001) Toward understanding Anophelinae (Diptera, Culicidae) phylogeny: insights from nuclear single-copy genes and the weight of evidence. Syst Biol 50: 540–556.
  40. 40. Armstrong N, Sun Y, Chen GQ, Gouaux E (1998) Structure of a glutamate-receptor ligand-binding core in complex with kainate. Nature 395: 913–917.
  41. 41. Jin R, Banke TG, Mayer ML, Traynelis SF, Gouaux E (2003) Structural basis for partial agonist action at ionotropic glutamate receptors. Nat Neurosci 6: 803–810.
  42. 42. Mayer ML, Ghosal A, Dolman NP, Jane DE (2006) Crystal structures of the kainate receptor GluR5 ligand binding core dimer with novel GluR5-selective antagonists. J Neurosci 26: 2852–2861.
  43. 43. Kim H, Lee S, Jang Y (2011) Macroevolutionary patterns in the Aphidini aphids (Hemiptera: Aphididae): diversification, host association, and biogeographic origins. PLoS One 6: e24749.
  44. 44. Gereau IV RW, Swanson GT (2008) The glutamate receptors: Springer.
  45. 45. Madden DR (2002) The structure and function of glutamate receptor ion channels. Nat Rev Neurosci 3: 91–101.
  46. 46. Rebora M, Piersanti S, Gaino E (2009) The antennal sensilla of adult mayflies: Rhithrogena semicolorata as a case study. Micron 40: 571–576.
  47. 47. Yao CA, Ignell R, Carlson JR (2005) Chemosensory coding by neurons in the coeloconic sensilla of the Drosophila antenna. J Neurosci 25: 8359–8367.
  48. 48. Birkett MA, Campbell CA, Chamberlain K, Guerrieri E, Hick AJ, et al. (2000) New roles for cis-jasmone as an insect semiochemical and in plant defense. Proc Natl Acad Sci U S A 97: 9329–9334.
  49. 49. Bruce TJ, Wadhams LJ, Woodcock CM (2005) Insect host location: a volatile situation. Trends Plant Sci 10: 269–274.
  50. 50. Hegde M, Oliveira JN, da Costa JG, Bleicher E, Santana AE, et al. (2011) Identification of semiochemicals released by cotton, Gossypium hirsutum, upon infestation by the cotton aphid, Aphis gossypii. J Chem Ecol 37: 741–750.
  51. 51. Koczor S, Szentkiralyi F, Birkett MA, Pickett JA, Voigt E, et al. (2010) Attraction of Chrysoperla carnea complex and Chrysopa spp. lacewings (Neuroptera: Chrysopidae) to aphid sex pheromone components and a synthetic blend of floral compounds in Hungary. Pest Manag Sci 66: 1374–1379.
  52. 52. Quiroz A, Niemeyer H (1998) Olfactometer-assessed responses of aphid Rhopalosiphum padi to wheat and oat volatiles. Journal of chemical ecology 24: 113–124.
  53. 53. Webster B, Bruce T, Dufour S, Birkemeyer C, Birkett M, et al. (2008) Identification of volatile compounds used in host location by the black bean aphid, Aphis fabae. J Chem Ecol 34: 1153–1161.
  54. 54. Zhu J, Park KC (2005) Methyl salicylate, a soybean aphid-induced plant volatile attractive to the predator Coccinella septempunctata. J Chem Ecol 31: 1733–1746.