36
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Ten simple rules for drawing scientific comics

      editorial

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Institutions around the world are in a constant struggle to improve science communication. From calls for journal papers to be simpler and more accessible to encouraging scientists to take a more active role through community engagement, there is a drive to demystify and improve public understanding of and engagement with science [1–3]. This drive for engagement is crucial to both helping recruit the next generation of scientist and highlighting the impact and role science has in public life. It also has a role in peer-to-peer communication and wider dissemination of ideas throughout the community. Technology has greatly helped expand the range of teaching styles that a lecturer can call on to reach more people in new ways. Social media outlets like Twitter, Facebook, Instagram, and Tumblr have expanded the reach of science communication within and across scientific disciplines and to the lay public [1, 3]. These new communication channels seem to support endless innovations in the development of videos, interactive quizzes, and instant feedback. Yet they are also providing a platform for a renaissance of one of the simplest and most effective methods for communicating ideas—comics. There are few scientists who haven’t heard of Randall Munroe, the artist behind the web comic “xkcd” [4], which features amazing graphic explanations on everything from climate change [5] to data storage [6]. These comics are widely appealing to a diverse audience and are posted on walls in laboratories and pubs alike. The ideas that they explain are complicated, but by simplifying them down to the core messages and by providing simple visual analogies, the comics educate and engage the groups that other media cannot always reach. A comic is generally an illustration that employs metaphor and/or storytelling to clearly communicate an idea to a broad audience. Comics often employ humor, but their narratives can be exclusively informational in nature or can deal with nonhumorous topics. Comics can take multiple forms, from the single panel one-liner, to multiple panels, to graphic novels that span multiple pages. There are a number of science- and academic-oriented comics in circulation, including xkcd, PHD [7], and the authors’ own Errant Science [8] and RedPen/BlackPen [9]. An effective comic can communicate difficult ideas efficiently, illuminate obscure concepts, and create a metaphor that can be much more memorable than a straightforward description of the concept itself. Comics can be used to punctuate presentations or journal publications [10–12] to increase impact. In public health education, comics have long been recognized as an effective tool for reaching lots of different populations for education on subjects like cancer [13], fitness [14], and diabetes [15], to name only a few. A recent trend is for scientists and artists (and scientist-artists) to capture the content of talks at conferences, or indeed entire meetings [16], as graphical notes [17]. A vibrant and growing scientific community on social media makes this a particularly effective method for expanding the intended audience; i.e., particularly engaging comics are “virally” spread within very short time frames. Science comics have also been included in research studies to enhance the story and facilitate understanding by a broader audience [10–12]. Certain journals have a “cartoon” category for submission so that the comic will appear in a citable form in publication [18]. Broadly, all of these avenues represent different ways of promoting work to others. Here, we focus on three key opportunities provided by comics. First, presenting ideas visually is an effective entry point to complex ideas. Second, using metaphor makes information memorable in ways that literal descriptions do not. Third, though not all topics and situations are suited to the use of humor, employing humor can engage nonexperts and experts alike. It both reduces the levels of intimidation associated with presenting scientific results to a wide audience and breaks down the barriers to understanding that often come with new science. Here, we set out several guidelines that we hope will convince more scientists that drawing your own comics is simpler than you think. We start with breaking the biggest deterrent of all. Rule 1: You don’t have to be good at art Comics are not about art. They are about conveying a message in graphic form. Graphs and plots are for accurately conveying data, diagrams are for accurately depicting a system or setup, and comics are there to help people understand an idea. Some of the best cartoonists and comic artists cannot draw much better than wobbly lines forming strange shapes (Figs 1–10). The trick is to find the shapes that best convey the point you are trying to make. For example, you can convey the sense of scale within a system with a single circle and a dot. Use the dot to represent your smallest scale and then draw a proportionally scaled circle to represent the larger scale. This very basic comic conveys a sense of scale better than writing “small” and “twenty times bigger” (Fig 1). As is explored further, it’s not about the smoothness of the lines or the accuracy of the circles, and if you can make a crude shape on paper, you can do what we set out in these rules. Anyone can create a comic, and often the biggest barrier is just getting over the idea that you can’t. With practice, you’ll get better at communicating ideas this way. 10.1371/journal.pcbi.1005845.g001 Fig 1 Sense of relative scale can be conveyed with very simple drawings. While a piece of paper and a pencil are enough to get started drawing, there are also numerous websites that provide comic drawing software free [19] as well as guides on some of the finer details behind producing full comics [20]. Rule 2: Comics should be simple The use of comics should make a complicated idea simpler and easier to understand—not harder! Figure out which of your components or steps can be removed or combined in your comic. Comics are like figures in papers; they are best when each conveys one message. Complicated multithreaded comics can look like a “ridiculogram"—a graph with six axes or a Venn diagram with six categories, one of them shaped like a banana (see Fig 4 from [21]). These are graphical strategies that are fun to look at but cannot be easily interpreted (Fig 2). As with the previous example, the comic works best when conveying a simple message, in that case indicating the scale of the system. 10.1371/journal.pcbi.1005845.g002 Fig 2 Adding information can create a “Vennster” (the intersection of a Venn diagram and monster). Rule 3: Make it right, not perfect Check the science. If your comic has scientific ideas in it, take the time to make sure you have the details right. If it’s mainly just a funny-joke comic, it doesn’t need to be absolutely right. For example, you can add footnotes to comics to point out scientific inaccuracies. But if it’s a comic that is meant to really illustrate a scientific concept for the purpose of education, then it should be as factually correct as you can make it. Including incorrect information in something that is intended to educate is misleading and can lead to misconceptions for those you are trying to reach who may not have a scientific background. In the example of the dot and the circle, no one is going to run a volume analysis on your comic (Fig 3). But they will expect it to be within a by-eye–visible order of magnitude of what you are trying to convey. 10.1371/journal.pcbi.1005845.g003 Fig 3 In general use, only enough information to get the idea across. Rule 4: Characters can improve engagement Create characters with personality that can guide the reader—what your character wears, how tall they are, what they are carrying. If your subjects are inanimate objects, then add personality by including a face. Humans see a face and easily recognize humanity in objects. The famous example is when you hold a pencil, tell everyone that you have named it Steve and then immediately break it [22]. People will tend to feel empathy for the pencil. Simply naming your shapes can be enough to help people engage with the comic and understand and remember the message it conveys. Personification allows the expression of emotions and interactions between players in your comic that let a story be told (see Rule 6). In the dot and circle example, this can be as simple as giving one of the objects hand-like shapes (Fig 4). Or in a more real-world setting, adding something as simple as googly eyes to equipment can produce the same result. 10.1371/journal.pcbi.1005845.g004 Fig 4 Adding faces and names increases engagement. Rule 5: Don’t punch down Comics have a way of going viral (Fig 5), and it’s a good idea to reflect on the possible consequences of everyone in the world reading your comic. (No, not literally everyone in the world.) Don’t punch down: making mean fun of those less powerful or privileged than you is bad form, and you should evaluate with every comic you produce. Maintaining a spirit of fun, self-effacing humor and/or commiseration can often express similar ideas without putting anyone down. Be careful with work-inspired comic ideas. Complaining about your workplace using specific details is simply not a good idea. If you do, try not to make any situation or anyone in the comic identifiable—unless you’ve asked them first or they’re a public figure. It shouldn’t need to be said, but avoid jokes that are sexist, racist, ableist, or most other “ists.” (Marxist jokes may be back on the table.) You should really avoid those in real life as well. If you do get criticized for a comic you’ve posted, take a deep breath, let it out, find a trusted and honest friend or colleague, and ask their opinion. Don’t be afraid to pull the comic. There are rare cases in which any communication, especially those involving social media, has grown to have serious implications for the author [23] and, potentially, the institution they are associated with. 10.1371/journal.pcbi.1005845.g005 Fig 5 Comics have a way of going viral. Rule 6: Tell a story A good comic, like a good scientific manuscript, tells a story. Like a story, a comic has a beginning (the setup), a middle (the conflict), and a resolution (the punchline). A single-panel comic compresses all these into a single illustration, but it may lay out all the elements of the story in the panel (Fig 6). If illustrating a process or mechanism, start with Rule 4 and personify the elements. Then, think about the story your comic is telling—the steps of the process—and how this might be made more memorable by using your characters. What would the enzyme in your comic say if it could talk? You’ve just given the enzyme that ability! All stories have conflict. This can be in the form of an actual villain, a conflict of ideas, an unseen context to the story, or a joke that the reader is likely to understand. It is important that the language you use to help tell this story be simple and legible. Ideally, it should be tested on nonnative speakers. The impact of the comic can be highly reduced if readers don’t understand the dialogue. 10.1371/journal.pcbi.1005845.g006 Fig 6 Interaction between characters is an essential part of storytelling. Rule 7: Draw on what you know and find your own voice As with many other things, the adage “write what you know” applies to comics as well, but don’t feel limited to only what you’re an expert in. Draw from your own experience (paying attention to Rule 5, of course), and if you are comfortable taking on difficult problems or ideas, then go ahead. Personal stories that come from your own experience and emotions can be incredibly powerful [24]. Your comics might be topical, but that’s ok—science is topical. And by bringing something that you care about and understand to a wider audience, you might just communicate outside your subspecialty. Paying attention to concepts you find important, issues that are relevant to you, and interactions you have daily can be a treasure trove of ideas if you pay attention. If you have a comic or an idea for a comic, try bouncing it off a trusted friend or colleague (Fig 7); then, take their feedback and use it to improve your ideas iteratively. It may take time to find what subjects you like to focus on and how you like to represent ideas, and that’s ok. Art, like science, is a continually evolving process, and it is important to find your own voice. 10.1371/journal.pcbi.1005845.g007 Fig 7 Find a trusted friend to bounce ideas off of. Rule 8: Use your imagination Readers expect comics to be imaginative and to depict ideas in new, fresh ways. A great way to communicate complex or esoteric concepts is to use analogies. Analogies allow the reader to make a connection between something that they can relate to and abstract concepts that may be complex and hard to grasp. An added benefit of analogies is that they often allow for simple variations to make a subject humorous. For example, you can equip a car with multiple “accessories” to depict the process of peer review [18] or transform a dot and circle into an acorn and a squash (Fig 8). However, be careful with analogies because they can sometimes lead to incorrect conclusions about a topic. 10.1371/journal.pcbi.1005845.g008 Fig 8 Adding an analogy can transform a comic. Rule 9: Sketch and draft One of the most important aspects of an effective comic is clear communication. Storyboard ideas with quick sketches. Lay out the important bits of the comic: where you want the characters, how you want the panels arranged, and where the text will go. This last point, where the text will go, is actually really important and sometimes difficult to do. Experiment with it if it doesn’t seem right the first time. Choose your words. Just like a joke given by a standup comedienne, the difference between a great joke and a dud can sometimes be the specific way that you deliver it and the words that you use. You usually won’t give a talk at a conference off-the-cuff, so don’t do it here either! Test ideas out on others first. Write down a few ideas if you are having trouble. Sometimes the first thing that pops into your head is the best. Other times, an idea needs coaxing and refinement to really shine (Fig 9). You’ll learn to recognize the difference between the two. 10.1371/journal.pcbi.1005845.g009 Fig 9 Some ideas take time to develop, others are better fresh. Rule 10: Practice, practice, practice and have fun No one becomes great at something instantly. Give yourself time and practice often. Sketch at conferences (see [17]), doodle during down time, and carry a notebook for ideas. Learn from others. Read some comics. There are some great ones out there and new ones popping up all the time. Find some that resonate with you and draw inspiration from them. Remember, if you have an idea, you can start without needing to do any drawing at all [19]. Use social media like Twitter, Facebook, Tumblr, and Instagram to reach your audience. Start an account for your comic and it will start to take on a life of its own! Most of all, have fun (Fig 10). Let’s make that a rule. 10.1371/journal.pcbi.1005845.g010 Fig 10 Relax and have fun—in whatever way you can. If you are still reading, take out a piece of paper and draw a circle. Now give it some eyes and a mouth. Now have it thinking or saying something about science. Did it work? Congratulations! You are now a science comic artist!

          Related collections

          Most cited references12

          • Record: found
          • Abstract: found
          • Article: not found

          Foundations for engineering biology.

          Drew Endy (2005)
          Engineered biological systems have been used to manipulate information, construct materials, process chemicals, produce energy, provide food, and help maintain or enhance human health and our environment. Unfortunately, our ability to quickly and reliably engineer biological systems that behave as expected remains quite limited. Foundational technologies that make routine the engineering of biology are needed. Vibrant, open research communities and strategic leadership are necessary to ensure that the development and application of biological technologies remains overwhelmingly constructive.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Female Behaviour Drives Expression and Evolution of Gustatory Receptors in Butterflies

            Introduction Nearly 50 years ago Ehrlich and Raven proposed that butterflies and their host-plants co-evolve [1]. Based on field observations of egg-laying in adult female butterflies, feeding behavior of caterpillars, and studies of systematics and taxonomy of plants and butterflies themselves, they outlined a scenario in which plant lineages evolved novel defensive compounds which then permitted their radiation into novel ecological space. In turn, insect taxa evolved resistance to those chemical defences, permitting the adaptive radiation of insects to exploit the new plant niche. Ehrlich and Raven's theory of an evolutionary arms-race between insects and plants drew primarily from an examination of butterfly species richness and host-plant specialization. It did not specify the sensory mechanisms or genetic loci mediating these adaptive plant-insect interactions. Insects possess gustatory hairs or contact chemosensilla derived from mechanosensory bristles, scattered along a variety of appendages [2]–[4]. In adult butterflies and moths, gustatory sensilla are found on the labial palps and proboscis (Figure 1), the legs (Figure 2A) [5], the antennae (Figure 2B) [6], [7], and the ovipositor [8], [9]. In adult Heliconius charithonia legs, the 5 tarsomeres of the male foreleg foretarsus are fused and lack chemosensory sensilla, while female foretarsi bear groups of trichoid sensilla (n = 70–90 sensilla/tarsus) associated with pairs of cuticular spines [10]. Each trichoid sensilla contains five receptor neurons. These sensilla are sensitive to compounds that may be broadly classified as phagostimulants (e.g., sugars and amino acids), which promote feeding behavior, or phagodeterrents (secondary plant compounds), which suppress it [11]; in adult females they may also modulate oviposition [12]. 10.1371/journal.pgen.1003620.g001 Figure 1 Scanning electron micrographs of the proboscis of Heliconius butterflies. (A) The labial palps (lp) and proboscis (p) of the H. erato head contain gustatory sensilla. (B) The proximal portion of the H. melpomene proboscis has hair-like sensilla chaetica (sc). (C) The tip portion of the proboscis has specialized ridges for pollen collection along with sensilla styloconica (ss). Reproduced with permission [9]. (D) H. melpomene with a pollen-load. c, clypeus, ce, compound eye; pr, proximal region; mr, mid region; tr, tip region; dgl, dorsal galeal linking structures; sb, blunt-tipped sensilla. 10.1371/journal.pgen.1003620.g002 Figure 2 Sexual dimorphism in H. melpomene chemosensory tissues. Scanning electron micrographs of adult legs showing a sexual dimorphism in gustatory (trichoid) sensilla. Foreleg foretarsi of a male (A) and a female (B). Four pairs of clumped taste sensilla are each found associated with a pair of cuticular spines on each female foot (only three are shown). Arrow indicates a clump of taste sensilla. Antennae of an adult male (C) and a female (D) showing individual gustatory sensilla (arrow). Genes for vision, taste and smell are likely to be crucial genomic loci underlying the spectacular diversity of butterfly-plant interactions. The availability of genomes for two butterfly species, the postman Heliconius melpomene (Nymphalidae) [13] and the monarch (Danaus plexippus) [14], as well as the silkmoth (Bombyx mori) [15], enables us to examine the evolutionary diversification of gustatory (Gr) and olfactory (Or) receptor genes that mediate insect-plant interactions. Each of these species feeds on hosts from different plant families. Silkmoth larvae feed on mulberry (Morus spp., Moraceae) and monarch larvae feed on milkweed (Asclepias spp., Apocynaceae). The larvae of Heliconius feed exclusively on passion flower vines, primarily in the genus Passiflora (Passifloraceae). In addition, adult Heliconius are notable for several derived traits such as augmented UV color vision [16], pollen feeding (Figure 1B) [17], [18], and the ability to sequester substances from their host plants that are toxic to vertebrate predators such as birds [19], [20]. In Drosophila melanogaster, the Gr gene family consists of 60 genes [21]–[24], several of which are alternatively spliced, yielding 68 predicted Gr transcripts [24]. One or more of these Gr proteins including possibly obligatory co-receptors [25]–[27] may be expressed in each gustatory receptor neuron [11]. Originally considered members of the G-protein-coupled receptor (GPCR) family, insect Grs have an inverted orientation in the membrane compared to the GPCR family of vertebrate Grs [28] and are part of the same superfamily as the insect Ors [21]. Signalling pathways for insect Grs may be both G-protein dependent [29], [30], [31] and G-protein independent [32]. For the vast majority of Drosophila Grs the specific compounds to which they are sensitive remain unknown. Nonetheless, several receptors for sugars [33]–[35], CO2 [26], [36], bitter substances [37]–[39] and plant-derived insecticides [25] have been identified in flies. Knowledge of the Gr gene family for insects outside Drosophila is sparse and has primarily relied on the analyses of individual reference genomes. Expression studies are challenging, due to the very low expression of Grs in gustatory tissues [21], [23]. In addition, Grs and Ors typically have large introns, small exons and undergo fast sequence evolution, making their in silico identification using automated gene prediction algorithms from genomic sequences problematic. Thus, the large repertoire of Grs (and Ors) that have been examined in the reference genomes of the pea aphid [40], the honey bee [41], the red flour beetle Tribolium castaneum [42], the mosquitoes Aedes aegypti [43] and Anopheles gambiae [44], and several Drosophila spp. [45], [46] have required extensive manual curation. In Lepidoptera, a large insect group which includes ∼175,000 species, completely described Gr (and Or) gene models from genomes are rare and limited to B. mori [47], D. plexippus [14] and H. melpomene (Grs, this study; Ors, [13]). In other lepidopteran species, only fragmentary Gr data are available: five sequences in Spodoptera littoralis [48], three in Heliothis virescens [49], two in Manduca sexta [50], [51] and one in Papilio xuthus [52]. Adult females of each Heliconius species only lay eggs on a limited number of host plants [53], and therefore need to recognize different species from among the large and diverse Passifloraceae family, which also show a remarkable diversity of chemical defences [54]. The evolutionary arms race between Heliconius butterflies and their hosts led us to hypothesize that Heliconius Grs (and Ors) might be subject to rapid gene duplication and gene loss as well as copy-number variation (CNV). Recent work taking advantage of published Drosophila genomes has shown a relationship between host specialization and/or endemism and an increased rate of gene loss, as well as a positive relationship between genome size and gene duplication [46], [55]. Moreover, Drosophila Grs appear to be evolving under weaker purifying selection than Ors [55]. We previously used the reference genome sequence for H. melpomene to annotate three chemosensory gene families, encoding the chemosensory proteins (CSPs), the odorant-binding proteins (OBPs), and the olfactory receptors (Ors). This demonstrated a surprising diversity in these gene families. In particular there are more CSPs in the butterfly genomes than in any other insect genome sequenced to date [13]. We build on this work below by characterizing the Gr gene family in the reference H. melpomene melpomene genome and in two other lepidopteran species whose genomes have been sequenced, B. mori (Bombycidae) and D. plexippus (Nymphalidae), by performing in silico gene predictions and phylogenetic analysis. We then analyzed whole-genome sequences of twenty-seven individual butterflies, representing eleven species sampled across all major lineages of the Heliconius phylogeny and including sixteen individuals from two species, H. melpomene and its sister-species H. cydno. We also generated RNA-sequencing expression profiles of the proboscis and labial palps, antennae and legs of individual adult male and female butterflies of the sub-species H. melpomene rosina from Costa Rica (∼1 billion 100 bp reads). We used these data to address four major questions: Are different chemosensory modalities less prone to duplication and loss than others (e.g., taste vs. olfaction)? Is there evidence of lineage-specific differentiation of Gr (and Or) repertoires between genera, species and populations? What is the relationship between CNVs and the retention of paralogous genes over long-term evolutionary timescales? Are the life history differences between males and females reflected in the expression of Grs and Ors as well as in the retention of novel sensory genes in the genome? We find higher turnover of the Grs than the Ors over longer evolutionary timescales, and evidence for both gene duplication and loss among a clade of intronless Grs between lepidopteran species and within the genus Heliconius. We also find for H. melpomene and its sister species, H. cydno, evidence of copy-number variation (CNVs) within their Gr and Or repertoires. Lastly, our RNA-sequencing suggests both tissue-specific and sex-specific differences in the diversity of expressed Grs and Ors, with female legs expressing a more diverse suite of Grs than male legs. Our data set revealing the expression of 67 of 73 predicted Gr genes and 67 of 70 predicted Or genes in adult H. melpomene butterflies is the most comprehensive profiling of these chemosensory gene families in Lepidoptera to date, and suggests how female host plant-seeking behaviour shapes the evolution of gustatory receptors in butterflies. Results Annotation of Grs in the reference genome of H. melpomene In total, we manually annotated 86,870 bp of the H. melpomene melpomene reference genome (Table S1). Our 73 Gr gene models, consisted of 1–11 annotated exons, with the majority having three or four exons; six were intronless. We found genomic evidence (but not RNA-seq evidence) of possible alternative splicing of the last two exons of HmGr18, bringing the total number of predicted Grs to 74. Alternative splicing has not been previously described in the silkmoth B. mori [47], but is known to occur in most other insects examined, including D. melanogaster, Anopheles gambiae, Aedes aegypti and T. castaneum [24], [43], [44]. We also identified eleven new putative Grs in the monarch butterfly genome, DpGr48-56, DpGr66 and DpGr68 (Table S1) [14]. All but five of our gene models contained more than 330 encoded amino acids (AAs) while individual gene models ranged from 258–477 AAs. Several Gr genes contained internal stop codons (Table S1). In at least one case, we found RNA-seq evidence of an expressed pseudogene–HmGr61–with two in-frame stop codons. In other cases, the 5′ end of our assembled transcripts was not long enough to verify the internal stop codons in the genome assembly. The Grs are located on 33 distinct scaffolds, with 58 forming clusters of 2–8 genes on 18 scaffolds, distributed across 14 chromosomes. Gene duplication and loss in a clade of putative bitter receptors To study the patterns of gene duplication and loss more broadly across the Lepidoptera, we next examined the phylogenetic relationships of Grs from the three lepidopteran reference genomes [13]–[15]. Across the gene family phylogeny a large number of duplications among the putative ‘bitter’ gustatory receptors of Heliconius or Danaus have occurred, while the putative CO2 and sugar receptors are evolving more conservatively, with only single copies in the H. melpomene reference genome (see below)(black arcs, Figure 3). A majority (∼64%) of Gr genes found in the H. melpomene genome are the result of gene duplication since Heliconius shared a common ancestor with Danaus or Bombyx. This is in contrast to the more conserved pattern of evolution of the Ors (Figure 4) [13] where a majority (37 of 70 or 53%) of genes show a one-to-one orthologous relationship with either a gene in Danaus, in Bombyx or both. 10.1371/journal.pgen.1003620.g003 Figure 3 Phylogeny of the Grs identified in three lepidopteran genomes. A maximum likelihood analysis of amino acid sequences was performed. Bootstrap support is out of 500 replicates. Putative CO2 and fructose receptors show a conserved 1-to-1 orthologous relationship in each of the three lepidopteran genomes, while putative sugar receptors of the monarch butterfly have duplicated twice. By contrast, numerous butterfly- or moth-specific gene duplications are evident among the remaining Grs, which are hypothesized to be bitter receptors. Small red dots indicate single-copy Heliconius Grs classified as conserved genes in the analyses shown in Table 1 and Table 2. Small black arrows indicate female-specific Grs expressed in adult H. melpomene legs. Small red arrows indicate Grs expressed in adult H. melpomene proboscis only. Bar indicates branch lengths in proportion to amino acid substitutions/site. Synephrine and fructose receptors are described in [52] and [32]. Bm = Bombyx mori, Hm = Heliconius melpomene, Dp = Danaus plexippus, Px = Papilio xuthus. 10.1371/journal.pgen.1003620.g004 Figure 4 Phylogeny of the Ors identified in three lepidopteran genomes. A maximum likelihood analysis of amino acid sequences was performed. Bootstrap support is out of 500 replicates. Fewer lineage-specific duplications are evident among the Ors compared to the Grs, with the exception of one large butterfly-specific expansion (orange arc). Small red dots indicate single-copy Heliconius Ors classified as conserved genes in the analyses shown in Table 1 and Table 2. Ors that are enriched in male or female adult B. mori antennae (blue and black arcs) are described in [91]; cis-jasmonate and monoterpene citral receptors are described in [92] and [93]. Phylogenetic tree reconstruction details are given in [13]. Bar indicates branch lengths in proportion to amino acid substitutions/site. Small arrows indicate female-specific Ors expressed in adult H. melpomene legs. Bm = Bombyx mori, Hm = Heliconius melpomene, Dp = Danaus plexippus. Within the genus Heliconius there is a great diversity of host plant preferences for different Passiflora species. To look at the relationship between gene duplication and loss over this shorter timescale, we focussed our efforts on a group of six intronless Grs, HmGr22-26 and Gr53, because it is only feasible to identify single-exon genes with high confidence, given that the Illumina whole-genome sequencing approach leads to poorly assembled genomes (Table S2). These genes are also of interest as some members of this group are very highly expressed. Notably HmGr22 is one of the most widely expressed genes in our adult H. melpomene transcriptomes, which was verified by reverse-transcriptase (RT)-PCR and sequencing of the PCR products (Figure 5A). In this regard HmGr22 resembles another intronless Gr, the silkmoth gene BmGr53, which is expressed in adult male and female antennae and larval antennae, maxilla, labrum, mandible, labium, thoracic leg, proleg and gut [32]. The remaining five intronless Grs have much more limited domains of expression in adult H. melpomene (see below). We searched for these genes in de novo assemblies of whole-genome Illumina sequences from eleven species across the Heliconius phylogeny. We investigate whether, as in Drosophila, a high turnover in putative bitter receptors is observed in species with host plant specializations or in species which are endemic and thus smaller in effective population size [46]. 10.1371/journal.pgen.1003620.g005 Figure 5 HmGr22 expression in adults and intronless Grs from whole-genome sequence data across the Heliconius phylogeny. (A) Reverse-transcriptase PCR (RT-PCR) of adult H. melpomene tissues showing the expression of HmGr22 and elongation factor-1 alpha. Two products are evident from the Gr22 RT-PCR. The bottom RT-PCR product is HmGr22 (arrow) and the top RT-PCR product is 18 s rRNA, which was verified by Sanger sequencing. (B) Neighbor-joining tree showing the phylogenetic relationship between the forty-six intact Grs and four pseudogenes identified in the 13 lepidopteran genomes. Bootstrap support is out of 500 bootstrap replicates. Pseudogene sequences are indicated by a ‘p’ after the gene name. Although patterns of host plant use are complex within the genus, some notable host-plant shifts have occurred, leading to the prediction that gene loss may have occurred along more specialized lineages [46]. For example, H. doris unlike many Heliconius, tends to feed on large woody Passiflora that can support their highly gregarious larvae [53]. It also probably has a smaller effective population size than most other Heliconius species. From the 11 species studied, we identified a total of 44 intact or nearly intact intronless Grs, as well as three intronless pseudogenes (Genbank Accession Nos. KC313949-KC313997)(Table S2 and S3). We also identified one intact intronless Gr each in monarch and silkmoth and one intronless Gr pseudogene in monarch. Phylogenetic analysis indicates that six intact intronless Gr genes were present at the base of the genus Heliconius while the intronless Gr pseudogene in monarch was the result of duplication since Heliconius and monarch shared a common ancestor (Figure 5B, Figure 6). Subsequent to the radiation of the genus Heliconius, there have been a number of gene losses. Whereas all members of the melpomene clade (H. melpomene, H. cydno, H. timareta) retained genomic copies of all six genes, members of the erato clade (H. erato, H. clysonymus and H. telesiphe) and sara-sapho clade (H. sara and H. sapho) have lost their copies of Gr22 and Gr25. In addition, members of the so-called primitive clade (H. wallacei, H. hecuba, and H. doris) have lost Gr23, while H. doris and H. wallacei have apparently lost Gr24 independently (Figure 6). The woody plant specialist, H. doris, has retained the fewest intronless Grs, apparently also having lost its copy of Gr53, a pattern mirrored by Drosophila host plant specialists [46]. We have, however, no direct evidence that the intronless Grs are in fact involved in host plant discrimination so the observed patterns of loss may be better explained by other variables such as effective population size. 10.1371/journal.pgen.1003620.g006 Figure 6 Inferred patterns of intronless Gr gene gain and loss across the genus Heliconius. Estimates of the number of Gr loci (number of pseudogenes is indicated in parentheses) on internal nodes of the lepidopteran phylogeny and gene gain (purple dots), gene loss (orange slashes) and pseudogenisation events (red slashes) on each branch. Heliconius phylogeny is based on Beltran et al. (2007) [90]. Reconciliation of gene trees onto the species tree was performed in Notung using maximum likelihood gene family trees. Primary Passiflora host plant subgenera (green dots) affiliated with each Heliconius species [53]. No clear relationship exists between the number of known Passiflora subgenera used and the number of intronless Grs in a species, which are presumed to be putative bitter receptors, but whose ligands are not yet identified. The woody vine specialist, H. doris, with the smallest effective population size, has the fewest intact intronless Grs. CNVs occur frequently among paralogous gustatory receptor genes We next tested whether the greater level of diversification of Grs as compared to Ors over long evolutionary timescales (compare Figure 3 and Figure 4), is similarly reflected in greater population level variation in Gr and Or duplicate genes. To test this hypothesis, we examined the incidence of CNVs among Grs and Ors that exist as single-copy genes in the reference H. melpomene genome with a one-to-one orthologous relationship with a gene in Danaus, Bombyx or both (conserved)(red dots, Figure 3 and 4), or as genes that are Heliconius-specific where no orthologue exists in either Danaus or Bombyx (non-conserved). We used whole genome resequence data (12 genomes) for three subspecies of H. melpomene (H. melpomene amaryllis, n = 4; H. melpomene aglaope, n = 4; and H. melpomene rosina, n = 4)(Figure 7, inset) and one sub-species of H. cydno (H. cydno chioneus, n = 4)(Table S4). We first mapped genomic resequence reads to the H. melpomene melpomene reference genome, and then searched for regions of abnormal coverage using CNVnator [56]. More than half of Gr loci showed presence of CNVs (37 out of 68 loci). However, there were noticeably fewer CNVs in Gr loci that evolve conservatively over the long-term, such as among the putative CO2 receptors, while there was an excess of CNVs in loci that show patterns of Heliconius-specific duplication (11.1% vs. 54.9%, respectively)(Fisher's Exact Test, two-tailed, P = 0.0004) (Table 1)(Figure 7). Intriguingly, many sugar receptor CNVs are sub-species specific; we observed fixed duplications relative to the reference genome in H. melpomene aglaope (HmGr4, Gr5, Gr6, Gr8, Gr45, Gr52) and H. melpomene amaryllis (Gr4, Gr5, Gr6, Gr7, Gr8, Gr45, Gr52), among genes that are found on different chromosomes (Table S5, Figure 7). Although the majority of CNVs are likely to be evolving neutrally, this raises the possibility of local adaptation within the species range around the detection of sugars. As expected given their long-term stability, Ors also show a lower incidence of CNVs (12 out of 67 loci), with no association between gene duplication and CNV incidence at least in H. melpomene (Table 1, Table S6). In H. cydno, a slight excess of Or CNVs was observed in loci that resulted in paralogous genes over longer evolutionary timescales (Fisher's Exact Test, two-tailed, P = 0.0475)(Table 1)(Figure 8). 10.1371/journal.pgen.1003620.g007 Figure 7 Copy-number variant (CNV) analysis of Grs in the H. melpomene genome. Scaffolds comprising each chromosome are indicated by alternating light and grey stripes. Grs without CNVs are indicated by open boxes and Grs with CNVs are indicated by closed boxes. Grs are classified as conserved if, in the H. melpomene reference genome, they have a one-to-one orthologous relationship with either a gene in Danaus, Bombyx or both (red dots, Figure 3). Grs are classified as non-conserved if they are duplicated in the H. melpomene reference genome or have no orthologue in either Danaus, Bombyx or both. Genes mapped to chromosomes but without precise locations are indicated by question marks. Scaffold arrangement is based on the published linkage map [13]. 10.1371/journal.pgen.1003620.g008 Figure 8 Copy-number variant (CNV) analysis of Ors in the H. melpomene genome. Scaffolds comprising each chromosome are indicated by alternating light and grey stripes. Ors without CNVs are indicated by open boxes and Ors with CNVs are indicated by closed boxes. The classification of Ors as being either conserved or non-conserved follows the same criteria as for the Grs. The eight genes for which the chromosome locality is not known are shown at the bottom. 10.1371/journal.pgen.1003620.t001 Table 1 Relationship between evolutionarily-conserved genes and copy-number variation (CNV). Species Gene family Gene classification Number of genes with P value§ CNV No-CNV H. melpomene Grs † Heliconius-specific 28 23 CO2 receptors+other conserved Grs * 1 8 Sugar receptors 8 0 0.0004 H. cydno Grs † Heliconius-specific 10 41 CO2 receptors + other conserved Grs 0 9 Sugar receptors 0 8 0.247 H. melpomene Ors ‡ Heliconius-specific 7 24 Conserved Ors 5 29 0.527 H. cydno Ors ‡ Heliconius-specific 6 25 Conserved Ors 1 33 0.0475 * Consists of single-copy genes in H. melpomene; in the monarch or Bombyx genomes, homologues are either single-copy or duplicate genes with bootstrap support ≥80%. § Fisher's exact test, two-tailed. † Excludes 3 Grs where read-mapping of the reference genome reads back to the reference assembly indicated areas of poor assembly: Gr37, Gr39 and Gr49. ‡ Excludes 3 Ors where read-mapping of the reference genome reads back to the reference assembly indicated areas of poor assembly: Or20, Or24, Or43, Or50 and Or74. We have not experimentally verified the incidence of copy number variation in any of these genomes, and some of the regions identified as CNVs are likely to be false positives. To investigate the rate of false positives, we analysed resequence data from the reference genome itself and discovered 3 Gr and 3 Or CNVs, suggesting a false positive rate of around 4%. (We therefore excluded these loci from our statistical tests.) However, the fact that broad patterns of observed CNVs are consistent with the evolutionary patterns at deeper levels supports our conclusion that CNV, in the absence of strong purifying selection, is an important driver of gene family diversification. These results also provide a novel line of evidence that the butterfly Grs have a higher rate of evolutionary turnover as compared to Ors. Sexually dimorphic gustatory sensilla in adult legs mirror Gr expression diversity The life histories of adult male and female butterflies are similar with respect to the need to find food and potential mates except that adult females are under strong selection to identify suitable host plants for oviposition. To ascertain host-plant identity, female butterflies drum with their legs on the surface of leaves before laying eggs [10]. This behaviour presumably allows the female to taste oviposition stimulants. Consistent with this behaviour, adult nymphalid butterfly legs are known to contain gustatory sensilla [57], and it has been reported that while nymphalid butterfly females have clusters of gustatory sensilla on their foreleg foretarsi, males lack these entirely [10], [58]. Here we confirm this mostly anecdotal evidence for sexual dimorphism using scanning electron microscopy (SEM). The mid- and hindlegs of both male and female H. melpomene have similar numbers of individual gustatory sensilla along their entire lengths, but there is a striking difference in their abundance and distribution on the foretarsi of the female forelegs. Unlike males, females exhibit cuticular spines associated with gustatory (trichoid) sensillae (n∼80 sensilla/foretarsus for females; n = 0/foretarsus for males) (Figure 2A) [10]. We therefore hypothesized that the repertoire of expressed Gr and Or genes in H. melpomene legs might be more diverse in females as compared to males. Furthermore, if female-specific genes are used for assessment of potential host plants, then fast-evolving insect-host interactions might produce rapid duplication of these genes over evolutionary timescales. Accordingly, we examined the expression profiles of Grs and Ors in adult H. melpomene by RNA-sequencing of libraries prepared from mRNAs expressed in adult antennae, labial palps and proboscis, and legs from one deeply-sequenced male and female each of H. melpomene (6 libraries total)(Table S7 and S8). The number of 100 bp reads per individual library ranged from 17.4 to 25.9 million for paired-end sequencing or 74.8–103.9 million for single-end sequencing (Table S8). To confirm these findings, we subsequently made 12 individual libraries from two more males and two more females (Table S7). As coverage was uneven across these libraries, we analysed them by merging biological replicates by sex and tissue type, and then downsampling so that an equal number of reads was analyzed for each treatment. The number of 100 bp reads analyzed for paired-end sequencing ranged from 19.4 to 49.6 million (Table S8). After downsampling, we examined the expression levels of the widely-expressed elongation factor-1 alpha gene in each of the libraries as a control, and found a comparable level of expression between sexes within each tissue type (Table S8). By careful visual examination of the uniquely-mapped reads to our 143 reference Gr and Or sequences, we found evidence of Gr and Or expression in all three adult tissue-types, with both tissue-specific and sex-specific differences as detailed below (Figure 9, Tables S9, S10, S11, S12, S13, S14). In total, we found evidence for expression of 67 of 73 Grs and 67 of 70 Ors identified in the H. melpomene reference genome. 10.1371/journal.pgen.1003620.g009 Figure 9 Comparison of Gr and Or expression in male and female adult H. melpomene chemosensory tissues. (A) The common set of Grs expressed in each tissue in both males and females. Red box indicates the presence of reads uniquely mapping to the coding region of each Gr gene model. To facilitate the visualization of tissue-specific expression found in both males and females, only Grs where both sexes show expression are indicated. Where only one sex or neither sex shows expression, the box is empty. (B) Grs showing sex-specific expression. To facilitate the visualization of sex-specific Grs, only Grs where one sex shows expression are indicated by a filled box. Grs which are expressed in both sexes or no sex are indicated by an empty box. (C) Venn diagram showing the number of uniquely expressed gustatory receptors in each transcriptome. (D) The common set of Ors expressed in each tissue in both males and females. Blue box indicates the presence of reads uniquely mapping to the coding region of each Or gene model. As above, only Ors where both sexes show expression are indicated. Where only one sex or neither sex show expression, the box is empty. (E) Ors showing sex-specific expression are indicated by a filled box. Ors which are expressed in both sexes or no sex are indicated by an empty box. (F) Venn diagram showing the number of uniquely expressed gustatory receptors in each transcriptome. The proboscis libraries also included both labial palps, the antennal libraries included both antennae, and the leg libraries included all six legs. Strikingly, the sexual dimorphism of gustatory sensilla we observed among the foreleg foretarsi is reflected in Gr gene expression patterns. A total of thirty-two Grs are expressed in both male and female H. melpomene leg transcriptomes including three CO2 receptors, HmGr1-3, four putative sugar receptors HmGr4, Gr6, Gr45 and Gr52 and a fructose receptor, HmGr9 (Figure 9A, Table S9, Supplementary Text). Many Grs showed sex-specific expression, however, with many more Grs in female (n = 46) as compared to male leg transcriptomes (n = 33)(Figure 9B, C). In total 15 of these Grs expressed in female legs, HmGr10, Gr24, Gr26, Gr29, Gr40, Gr41, Gr48, Gr50, Gr51, Gr16, Gr55, Gr57, Gr58, Gr60 and Gr67, are the result of duplications since Heliconius and Danaus shared a common ancestor (Figure 3 small arrows, Figure 9B, Table S9). By contrast, only one of the three male-biased Grs, HmGr19, evolved as a result of recent duplication. There is an excess of Heliconius-specific Grs but not Ors (see below) that are expressed in female legs (Fisher's Exact Test, two-tailed, p = 0.019)(Table 2). Since male H. melpomene do not need to identify host-plants for oviposition, it seems likely that the 17 female-specific Grs in our leg transcriptomes are candidate receptors involved in mediating oviposition (Figure S1). 10.1371/journal.pgen.1003620.t002 Table 2 An overabundance of Grs expressed in female legs are the result of Heliconius-specific duplication. Gene Family Gene duplication Gene Expression Female-specific Both sexes P value† Gr ‡ Heliconius-specific 15 20 0.019 Conserved* 1 13 Or § Heliconius-specific 6 12 0.483 Conserved* 5 19 * Consists of single-copy genes in H. melpomene; in the monarch or Bombyx genomes, homologues are either single-copy or duplicate genes with bootstrap support ≥80%. † Fisher's exact test, two-tailed, d.f. = 1. ‡ Excludes Gr39 because of poor coverage in the reference genome read-mapping. § Excludes Or20 and Or24 because of coverage in the reference genome. Female Gr expression is more diverse in antennae than male Gr expression Besides using their antennae for olfaction, female nymphalid butterflies also taste a host plant by antennal tapping before oviposition. This tapping behaviour presumably allows the host plant chemicals to come into physical contact with gustatory sensilla on the antennae. We therefore examined whether there was any difference in the abundance of gustatory sensilla on the antennae of male and female H. melpomene. Using scanning electron microscopy, we found individual gustatory sensilla scattered along each antennae of both male and female H. melpomene but no obvious sexual dimorphism in their abundance or distribution (Figure 2B). We found 28 Grs expressed in both male and female H. melpomene antennae (Figure 9A, Table S10), including two sugar receptors, HmGr4 and HmGr52, a putative fructose receptor HmGr9 and two CO2 receptors, HmGr1 and Gr3. Besides the sugar and CO2 receptors noted, other conserved genes that are expressed in both male and female antennae include HmGr63, a candidate Gr co-receptor (see Text S1), and HmGr66, a candidate bitter receptor. We also found 11 Grs expressed in female H. melpomene antennae that did not appear to be expressed in male antennae. Two of these, HmGr47 and Gr68, appeared in the top one-third of the most abundant female antennal Grs in terms of number of reads recovered from the individual butterfly transcriptome. In contrast, just four Grs were expressed in male antennae HmGr11, Gr25, Gr31, and Gr69 but not female antennae (Figure 9B, C, Table S10). Six of the female-biased Grs and two of the male-biased Grs (Gr31, Gr69) expressed in antennae are the result of duplication events since Heliconius and Danaus shared a common ancestor. Candidate Heliconius gustatory receptors for nectar- and pollen-feeding By contrast with the leg and antennal tissue, where more Grs are expressed in females compared to males, the labial palps and proboscis (Figure 1) transcriptomes contained the largest number of Grs (n = 35) expressed in both sexes (Figure 9A, C, Table S11). Five of the six candidate sugar receptors in the H. melpomene genome are expressed in both the male and the female transcriptomes along with two of the three conserved CO2 receptors, which may be used to assess floral quality [59] (Figure 3, Table S11). A majority (21 of 35) of Heliconius Grs expressed in both male and female labial palps and proboscis libraries have no existing ortholog in the silkmoth genome, apparently the result of gene loss in B. mori or gene duplication along the lineage leading to Heliconius (Figure 3). This may in part reflect the fact that adult silkmoths have lost the ability to feed. Interestingly, four Grs expressed in both male and female labial palps and proboscis transcriptomes could not be detected in male and female antennae and legs (HmGr12, Gr20, Gr35, and Gr59)(Figure 3, red arrows, Figure 9B). Some of these Grs might play a role in the pollen-feeding behaviour that is specific to Heliconius, and which involves preferences for particular species of flowers in the plant families Rubiaceae, Cucurbitaceae and Verbenaceae (see Discussion). Widespread expression of Ors in H. melpomene antennae, proboscis and labial palps and legs In addition to the Gr gene expression described above, we examined Or expression in the three adult tissues. The expression of Ors in antennal tissue has been widely studied in a variety of insects including Drosophila and some Lepidoptera [50], [60]. As expected, we observed that Or gene expression was high in the antennae. Unexpectedly, Or expression was about as prevalent as Gr expression in the proboscis and labial palps and leg transcriptomes (Figure 9D, E, F). In total across all three tissues profiled, we found evidence for the expression of nearly all predicted Or genes (67 of 70 genes)(Table S12, S13, S14) in the H. melpomene reference genome [13]. Discussion Outside Drosophila, the study of sensory gene family evolution in insects has generally been limited to the comparison of a small number of phylogenetically distant reference genomes. Such studies have commonly involved a comparison of the size of gene families between taxa in order to document lineage-specific expansions (Figure 10), and the comparison of dN/dS ratios to identify branches subject to rapid evolution [61]. Here we have used a similar approach to annotate 73 Grs in the Heliconius melpomene reference genome. However, we have also demonstrated the power of next-generation sequencing to elucidate patterns of evolution and expression of these genes. These data have offered exciting new insights into a set of genes that show both rapid evolution and sex-specific expression patterns, suggesting that female oviposition behaviour drives the evolution of butterfly gustatory receptors. 10.1371/journal.pgen.1003620.g010 Figure 10 Insect chemosensory gene family repertoires. Numbers indicate intact genes and numbers in parentheses indicate pseudogenes. References are given in [13], [55], [94]. OBP = odorant binding protein; CSP = chemosensory protein; OR = olfactory receptor, GR = gustatory receptor. Previous work in other insects indicates that Grs are an important target for gene duplication and loss between species. Most notably, D. sechellia and D. erecta are host specialists, on Morinda citrifolia and Pandanus candelabrum respectively, while D. simulans is a generalist fly exploiting a broad array of rotting fruit [46]. Host specialization in the former species is associated with an acceleration of gene loss and increased rates of amino acid evolution at receptors that remain intact. Here we have used whole-genome Illumina sequencing of single diploid individuals to similarly document patterns of gene gain and loss across Heliconius. This method yields highly fragmented genome assemblies, but such assemblies have proven very informative, most notably for studying the evolution of the clade of single-exon bitter receptor genes. We identified three gene duplication events along the lineage leading to Heliconius, followed by eight independent instances of clade-specific pseudogenizations or losses of different members of the intronless Grs, Gr22-26 and Gr53, within Heliconius and one instance within Danaus plexippus (Figure 5 and Figure 6). In both Heliconius and Drosophila gene gain and loss appear to primarily affect Grs that are presumed to respond to bitter compounds (Figure 3). To verify whether this pattern holds within the genus Heliconius for the remaining gene family members with more complex intron-exon structure will require better genome assemblies for multiple Heliconius species (Table S2). These patterns of rapid gene gain and loss are mirrored by within-population variation in copy number. From 16 resequenced genomes for H. melpomene and its sister species H. cydno, we have shown that CNVs occur more commonly among the Grs than the Ors (Figure 7, 8, Table 1). Within the Grs, the bitter receptors of H. melpomene represent a class of genes that are both highly prone to lineage-specific duplication and commonly subject to population-level copy number variation. These putative bitter receptor genes are also more likely to show female-specific expression, especially in the legs, which suggests a role in insect-host chemical interactions (Table 2, Figure 3, Figure S1). In human genomes, a tendency for CNV-rich areas to display higher dN/dS ratios and yield paralogous genes has been noted [62], along with an enrichment of CNVs in genes involved in immune function and in the senses (specifically in Ors which are unrelated to the insect Ors) [63], [64]. It is also widely known that copy-number variation is an important source of disease-causing mutations in humans [64]. With the exception of insecticide resistance in insects [65], [66], the spectrum of naturally-occurring copy-number variants is only just starting to be explored in Drosophila [67], [68] and non-model systems. Our results demonstrate the great utility of high throughput sequencing to reveal the naturally-occurring spectrum of CNVs that underlie gene family expansions in non-model systems, in traits of ecological relevance. Heliconius butterflies have complex relationships with their Passifloraceae host plants. Some species are host-specialist, feeding on only one or a few Passiflora species, others specialise on particular sub-genera within Passiflora, while others are generalists, albeit within this one host plant family (Figure 6) [53]. The Passifloraceae is extremely chemically diverse, most notably in their diversity of cyanogenic glycosides that protect the plant from herbivores. It seems likely that coevolution of the butterfly chemosensory and detoxification system on the one hand, with the plant biochemical defense on the other, has played an important role in the evolution of this chemical arsenal. In contrast to the research already carried out on the chemistry of the host plants [54], until recently almost nothing was known about the chemosensory system of Heliconius butterflies. All of these insect host-plant interactions are mediated primarily by adult female butterflies, which must correctly identify suitable host plants for oviposition [69], [70], or risk the survival of their offspring. Expression data for Grs in the Lepidoptera have been limited until now–especially for adults–due to their low expression level. The largest previous study identified 14 Grs profiled in larval B. mori [32]. We have found evidence for adult expression for most (∼91%) of the 73 predicted Gr genes. This provides a marked contrast to the handful of gustatory receptors that have been identified from traditional expressed sequence tag (EST) projects in other Lepidoptera. Our methods may provide a greatly improved yield of expressed genes because we now have a set of well-annotated target Gr genes against which RNA-seq data can be mapped, together with a greater diversity of transcripts afforded by deep sequencing. Such methods have also permitted us to find widespread expression of their sister gene family, the Ors, in the adult chemosensory tissues examined (68 of 70 or 97% of predicted genes) (Figure 9). Many of these Gr genes are likely to be involved in the detection of host plant attractants as well as toxic secondary metabolites and thus allow the discrimination of suitable hosts. Most notably, there were a large number of Heliconius-specific Grs with female-biased expression in both legs and antennae (Figure 9). As mentioned previously, these female-biased leg Grs (but not Ors) are also more likely to represent unique duplicates on the Heliconius lineage (Table 2). Female-biased Or expression, as quantified using RNA-seq data, has been reported for Ors expressed in the antennae of the adult mosquito, Anopheles gambiae [71]. Specifically, 22 Ors displayed enhanced expression in mosquito female antennae but not in male antennae. Since adult mosquito females but not males need to find hosts for a blood-meal, and adult butterfly females but not males need to find host plants for egg-laying, this suggests that host-seeking behaviour of female insects may be an important general driver of sensory gene evolution. Indirect evidence for the possible role of some of these Grs in Heliconius host plant detection comes from comparative studies of Grs mediating oviposition behaviour in swallowtail butterflies (Papilionidae). Papilio xuthus PxGr1 a member of the Gr subgroup that contains D. melanogaster Gr43a and HmGr9, has been characterized as a receptor for synephrine, which is an alkaloid found in citrus trees [52]. It is expressed in female P. xuthus tarsi and is necessary for the correct oviposition behavior of swallowtail butterflies [52]. Within the two clades most closely-related to PxGr1, are 9 butterfly-specific Grs: HmGr10, Gr16, Gr55, Gr56 and Gr57, and the newly-described DpGr16, Gr50, Gr52, and Gr54 (Figure 3). Four these Grs, HmGr16, Gr55, Gr56 and Gr57, result from Heliconius-specific gene duplications (i.e., no Danaus or Bombyx homologs). Grs55-57 are also in the top ten most highly expressed Grs in female legs. The identification of these sex-biased leg Grs has provided an important starting point for future ligand specificity studies combining heterologous expression, electrophysiology, RNAi [51], assays of the proboscis-extension reflex, and female oviposition behavior. Lastly, the patterns of Gr gene expression among different tissues and sexes has permitted us to identify a number of Grs that are strong candidates for mediating the remarkable pollen feeding behaviour that is unique to Heliconius, among the butterflies. The Heliconius proboscis contains at least two types of gustatory sensilla, hair-like sensilla chaetica, and sensilla styloconica (Figure 1). Like other butterflies, Heliconius respond to varying amounts of sugars including sucrose present in floral nectar [72]. Unlike other moths and butterflies, Heliconius actively collect pollen with their proboscides, preferentially from Psychotria (Rubiaceae), Psiguria/Gurania (Cucurbitaceae) and Lantana (Verbenaceae) flowers [17], [18], [73]. Once a pollen load is collected (Figure 1D), the butterflies use a combination of mechanical shearing (coiling and uncoiling of the proboscis) and enzymatic activity (using proteases found in saliva) to release amino acids from the pollen [74]. The RNA-seq data we have collected for H. melpomene proboscis and labial palps should provide a useful resource for future studies examining the molecular basis of this unique digestive trait. Pollen feeding in adult Heliconius has an important ecological function. Amino acids obtained from pollen are key resources used in male nuptial gifts and egg allocation [18], [75]–[77]. They also permit Heliconius adults to have exceptionally long lifespans. Pollen feeding behavior is not found outside the genus Heliconius, even in the sister genus Eueides, whose larvae share a preference for Passiflora host-plants with Heliconius. In the present study we have identified four Heliconius-specific Grs that are only expressed in the proboscis (HmGr12, Gr20, Gr35 and Gr59) but not in antennae or legs (Figure 9B), suggesting a role for these genes in pollen-feeding behaviour. Taken together, the whole-genome and whole-transcriptome data suggest that Gr genes in particular are highly evolutionarily labile both on short and long evolutionary timescales, and begin to offer an insight into the likely molecular basis for the rapid coevolution observed between these butterflies and their host plants. Understanding the remarkable diversity underlying this ecological interaction at a molecular level has remained a challenge (but see [32], [52], [78], [79]). Thanks to technological innovations in sequencing, the genetic basis of taste and olfaction involved in host-plant adaptation in Heliconius is beginning to be uncovered. Conclusions We have shown that like the opsin visual receptors [80], the chemosensory superfamily composed of constituent Gr and Or families in Lepidoptera show rapid gene family evolution, with higher rates of copy-number variation and gene duplication among the Grs than the Ors, as well as gene losses in the Grs. In particular, there is a group of putative bitter receptors that show female-specific expression in the legs and that are especially prone to gene duplication, providing new material for sensory diversification in the insect-host plant arms race. We have also shown, for the first time, widespread expression of Ors in non-antennal tissues in a lepidopteran. With the most comprehensive data set on Gr and Or expression in butterflies to date we are one step closer to identifying the sensory and molecular genetic basis of the Heliconius-Passiflora co-evolutionary race that inspired Ehrlich and Raven in 1964. Materials and Methods Genome annotation tBLASTn searches were conducted iteratively against the H. melpomene melpomene genome (version v1.1) and haplotype scaffolds [13] using B. mori [28], [47] and D. plexippus Grs [14] as input sequences. For these in silico gene predictions, intron-exon boundaries were identified by first translating the scaffold nucleotides in MEGA version 5 [81], searching for exons identified in the tBLASTn searches, then back translating to identify splice junctions. Intron sequences were then excised to verify that the remaining exonic sequences formed an in-frame coding sequence. Insect Grs are defined by a conserved C-terminal motif TYhhhhhQF, where ‘h’ is any hydrophobic amino acid [21]. We inspected our predicted protein sequences for this motif or variants thereof, specifically ‘S’, ‘M’ or ‘K’ instead of a ‘T’ or ‘L’, ‘T’ or ‘I’ instead of ‘F’. In the handful of cases where we were unable to find the last short exon that contains this motif, final assignment to the Gr gene family was based on using the predicted amino acid sequence as a search string for either tBLASTn or BLASTp against the nr/nt Genbank database. Gene annotations were submitted to the EnsemblMetazoa database http://metazoa.ensembl.org/Heliconius_melpomene/Info/Index as part of the H. melpomene v. 2 genome release (for GeneIDs see Table S1). Chromosomal assignments were based on published mapping of scaffolds in the H. melpomene melpomene reference genome [13]. Following amino acid alignment using ClustalW, preliminary phylogenetic trees were constructed in MEGA using neighbor-joining and pair-wise deletion to identify orthologous relationships with B. mori and D. plexippus Grs. Reciprocal tBLASTn searches against the B. mori and D. plexippus genomes as well as searches using the protein2genome module in EXONERATE [82] were then performed in order to search for ‘missing’ Grs in those genomes. Final phylogenetic analysis was performed using a maximum-likelihood (ML) algorithm and JTT model on an amino acid alignment that was inspected by eye and manually adjusted. These results were compared to a ML tree made from a Clustal-Omega alignment [83] and were found to be nearly identical. Once the initial H. melpomene Gr gene predictions were obtained, EXONERATE, Perl scripts and manual annotations in Apollo [84] were used to produce gff3 files for submission of the annotated H. melpomene genome scaffolds to EMBL-EBI. RNA-sequencing Butterfly pupae of H. melpomene rosina were obtained from Suministros Entomológicos Costarricenses, S.A., Costa Rica. Adult males and females were sexed and frozen at −80°C. Total RNAs were extracted separately from antennae, proboscis together with labial palps, and all six legs of three males and three females of H. melpomene using Trizol (Life Technologies, Grand Island, NY). A NucleoSpin RNA II kit (Macherey-Nagel, Bethlehem, PA) was used to purify total RNAs. Each total RNA sample was purified through one NucleoSpin RNA II column. Purified total RNA samples were quantified using a Qubit 2.0 Fluorometer (Life Technologies, Grand Island, NY). The quality of the RNA samples was checked using an Agilent Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). 0.3–4.0 µg of purified total RNAs were used to make cDNA libraries. A TruSeq RNA sample prep kit (Illumina, San Diego, CA) was used to prepare 18 individual cDNA libraries. After being normalized according to their concentrations, the enriched individual libraries were pooled and then run on a 2% agarose gel. cDNA products ranging from 280 to 340 bp with an average of 310 bp were cut out and purified using a Geneclean III kit (MP Biomedicals, Solon, OH) to facilitate post-sequencing assembly. After being re-purified using Agencourt AMPure XP magnetic beads (Beckman Coulter Genomics, Danvers, MA), the cDNA pool was quantified using the Qubit 2.0 Fluorometer, and quality control-checked using the Agilent Bioanalyzer 2100. The cDNA pools were then normalized to 10 nM and run as either two paired-end or three single-end 100 bp runs on a HiSeq 2000 (Illumina, San Diego, CA) by the UCI Genomics High-Throughput Facility. RNA-seq assembly and read mapping mRNA sequences were demultiplexed, trimmed and sorted using Python and Perl scripts. A single de novo assembly of the combined libraries was performed using CLC Genomics Workbench 5 to check for missing exons in our gene models. The 73 corrected Gr gene models and 70 Or gene models were then used as an alignment reference to perform unique read mapping of each individual chemosensory transcriptome. To determine if an individual Gr or Or was expressed in a given tissue, each of the 1716 individual Gr and Or mapping alignments was inspected by eye for uniquely mapped reads, and any spuriously-mapped reads (i.e., reads 2× were counted as potential duplications and <0.5× as potential deletions. Whole-genome sequence assembly The GenePool, University of Edinburgh, and the Oxford Genomics Centre, University of Oxford, U.K., produced whole genome 100 bp sequences from H. cydno, H. timareta, H. wallacei, H. doris, H. clysonymus, H. telesiphe, H. erato petiverana, H. sara and H. sapho using the Illumina Pipeline v. 1.5–1.7 with insert sizes ranging from 300 to 400 bp. We deposited sequences for H. sapho and H. sara in the Sequence Read Archive (SRA) under accession number ERP002444. We performed de novo assembly of the short reads using Abyss v. 1.2 [86] implemented in parallel at the School of Life Sciences, University of Cambridge, U.K. Based on previous results [87], recommendations estimated by the software, and comparison of N50 values in preliminary experiments, we chose a k-mer size of 31, a minimum number of pairs required n = 5 and the minimum mean k-mer coverage of a unitig c = 2 (full command: abyss-pe n = 5 k = 31 c = 2 in = ‘for.fastq rev.fastq’). In all assemblies, at least 96% of reads mapped back to the contigs. We created BLAST databases of these whole genome sequence assembly contigs (Table S2) in Geneious Pro v. 5.5.6. The lack of introns in the putative bitter receptor genes Gr22-26 and Gr53 permitted us to easily retrieve them from these BLAST databases. To confirm the identity and improve the quality of the sequences found, we mapped the reads to the assembled exon sequences in CLC Genomics Workbench v. 5.5.1, using the following conservative settings to prevent mis-mapping of paralogous sequences: mismatch, insertion and deletion cost of 3; length fraction and similarity fraction of 0.9. We then inspected all read-mappings by eye. Because the intronless Grs are closely related, we aligned the translated nucleotide sequences in MEGA using the ClustalW algorithm, and also inspected the alignment by eye. For all intronless Gr sequences except for the pseudogenes, sequence length was highly conserved (i.e., there were few indels). To illustrate the high substitution rate of the retrieved pseudogene sequences, we selected the neighbor-joining method for tree reconstruction and performed 500 bootstrap replicates. Inferring gene duplications and losses To infer the number of intronless Gr gene duplications and losses, we used the program Notung v. 2.6 [88], [89], which reconciles gene trees onto the species tree. The gene tree was made by a maximum likelihood analysis of 1074 nucleotide sites, aligned by Clustal-Omega, and 500 bootstrap replications. The species tree was derived from a phylogeny based on independent nuclear and mitochondrial DNA sequences [90]. RT-PCR We verified the presence of HmGr22 in several adult tissues using reverse-transcriptase PCR and primers for HmGr22 (5′-CCATAATTTTGTCATCCT-3′ and 5′-GATTTCGAAATAAGGTCTGT-3′) and EF1alpha (5′-CGTTTCGAGGAAATCAAGAAGG-3′ and 5′-GACATCTTGTAAGGGAAGACGCAG 3′). RNA was extracted from fresh frozen specimens using Trizol and purified using the Nucleospin RNA II kit, which contains a DNAase-treatment step. RNA concentration was diluted to 12.5 µg/ml. Each 25 µl reaction had 2.5 µl 10× BD Advantage 2 PCR buffer, 2.5 µl dNTPs (2 mM), 0.5 µl (100 µM) forward and 0.5 µl reverse primer, 0.5 µl (1∶20 diluted) Stratagene Affinity Script Reverse Transcriptase, 0.5 µl 50× Advantage 2 Polymerase Mix, 17 µl H2O and 1 µl RNA. The PCR reaction consisted of 38 cycles of 95°C for 30 s, 55°C for 30 s, and 68°C for 55 s. The identity of the RT-PCR products was confirmed by Sanger sequencing. Supporting Information Figure S1 “For Bitter or Worse: A Tale of Sexual Dimorphism and Good Taste”, an original cartoon by author and illustrator of science-oriented comics, Jay S. Hosler. (PDF) Click here for additional data file. Table S1 Heliconius melpomene genome gustatory receptor annotations. Gene name, EnsemblMetazoa GeneID, amino acid sequence, nucleotide sequence, number of exons, top BLAST hit. (XLS) Click here for additional data file. Table S2 Whole genome Illumina sequencing de novo assembly statistics. (DOC) Click here for additional data file. Table S3 Intronless gustatory receptor genes retrieved from whole-genome Illumina assemblies. (DOC) Click here for additional data file. Table S4 CNV sample data and whole-genome resequencing statistics. (DOC) Click here for additional data file. Table S5 CNVs in H. melpomene and H. cydno gustatory receptors. (XLS) Click here for additional data file. Table S6 CNVs in H. melpomene and H. cydno olfactory receptors. (XLS) Click here for additional data file. Table S7 List of specimens and localities used in RNA-seq. (DOC) Click here for additional data file. Table S8 Number of 100 bp Illumina reads sequenced per RNA-seq library. (DOC) Click here for additional data file. Table S9 Gustatory receptor mRNAs expressed in adult H. melpomene legs. (DOC) Click here for additional data file. Table S10 Gustatory receptor mRNAs expressed in adult H. melpomene antennae. (DOC) Click here for additional data file. Table S11 Gustatory receptor mRNAs expressed in adult H. melpomene labial palps and proboscis. (DOC) Click here for additional data file. Table S12 Olfactory receptor mRNAs expressed in adult H. melpomene antennae. (DOC) Click here for additional data file. Table S13 Olfactory receptor mRNAs expressed in adult H. melpomene legs. (DOC) Click here for additional data file. Table S14 Olfactory receptor mRNAs expressed in adult H. melpomene proboscis and labial palps. (DOC) Click here for additional data file. Text S1 Identification of H. melpomene homologs of all described insect Gr subfamilies. (DOC) Click here for additional data file.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A super-assembly of Whi3 encodes memory of deceptive encounters by single cells during yeast courtship.

              Cellular behavior is frequently influenced by the cell's history, indicating that single cells may memorize past events. We report that budding yeast permanently escape pheromone-induced cell-cycle arrest when experiencing a deceptive mating attempt, i.e., not reaching their putative partner within reasonable time. This acquired behavior depends on super-assembly and inactivation of the G1/S inhibitor Whi3, which liberates the G1 cyclin Cln3 from translational inhibition. Super-assembly of Whi3 is a slow response to pheromone, driven by polyQ and polyN domains, counteracted by Hsp70, and stable over generations. Unlike prion aggregates, Whi3 super-assemblies are not inherited mitotically but segregate to the mother cell. We propose that such polyQ- and polyN-based elements, termed here mnemons, act as cellular memory devices to encode previous environmental conditions. Copyright © 2013 Elsevier Inc. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                4 January 2018
                January 2018
                : 14
                : 1
                : e1005845
                Affiliations
                [1 ] Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington, United States of America
                [2 ] Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States of America
                [3 ] Engineering Photonics, Cranfield University, Cranfield, Bedfordshire, United Kingdom
                [4 ] Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, New Jersey, United States of America
                [5 ] Institute for Advanced Study, Technische Universität München, Garching, Germany
                Dassault Systemes BIOVIA, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-2961-2572
                http://orcid.org/0000-0001-5280-8309
                Article
                PCOMPBIOL-D-17-01303
                10.1371/journal.pcbi.1005845
                5754043
                29300733
                8a1a553f-675b-4a64-bc98-01e68227a132
                © 2018 McDermott et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 10, Tables: 0, Pages: 10
                Funding
                NSF CAREER Award 1553289; the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Editorial
                Science Policy
                Science and Technology Workforce
                Careers in Research
                Scientists
                People and Places
                Population Groupings
                Professions
                Scientists
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Memory
                Face Recognition
                Biology and Life Sciences
                Neuroscience
                Learning and Memory
                Memory
                Face Recognition
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Perception
                Face Recognition
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Perception
                Face Recognition
                Social Sciences
                Psychology
                Cognitive Psychology
                Perception
                Face Recognition
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Twitter
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Twitter
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Twitter
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Facebook
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Facebook
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Facebook
                Computer and Information Sciences
                Data Visualization
                Infographics
                Graphs
                Biology and Life Sciences
                Psychology
                Personality
                Social Sciences
                Psychology
                Personality

                Quantitative & Systems biology
                Quantitative & Systems biology

                Comments

                Comment on this article