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      Molecular traces of alternative social organization in a termite genome.

      Nature Communications

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          Abstract

          Although eusociality evolved independently within several orders of insects, research into the molecular underpinnings of the transition towards social complexity has been confined primarily to Hymenoptera (for example, ants and bees). Here we sequence the genome and stage-specific transcriptomes of the dampwood termite Zootermopsis nevadensis (Blattodea) and compare them with similar data for eusocial Hymenoptera, to better identify commonalities and differences in achieving this significant transition. We show an expansion of genes related to male fertility, with upregulated gene expression in male reproductive individuals reflecting the profound differences in mating biology relative to the Hymenoptera. For several chemoreceptor families, we show divergent numbers of genes, which may correspond to the more claustral lifestyle of these termites. We also show similarities in the number and expression of genes related to caste determination mechanisms. Finally, patterns of DNA methylation and alternative splicing support a hypothesized epigenetic regulation of caste differentiation.

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          Most cited references 40

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          An olfactory sensory map in the fly brain.

          We have isolated the "complete" repertoire of genes encoding the odorant receptors in Drosophila and employ these genes to provide a molecular description of the organization of the peripheral olfactory system. The repertoire of Drosophila odorant receptors is encoded by 57 genes. Individual sensory neurons are likely to express only a single receptor gene. Neurons expressing a given gene project axons to one or two spatially invariant glomeruli in the antennal lobe. The insect brain therefore retains a two-dimensional map of receptor activation such that the quality of an odor may be encoded by different spatial patterns of activity in the antennal lobe.
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            The Gene vitellogenin Has Multiple Coordinating Effects on Social Organization

            Introduction Vitellogenin has versatile regulatory functions in honeybees, suggesting that this glycolipoprotein may be involved in the control of social life-history traits [1–5]. Vitellogenin is the common yolk precursor protein of oviparous taxa [6]. However, it appears to have evolved pleiotropic functions in the advanced eusocial honeybee that have not as yet been given attention in other species that rely on vitellogenin for oocyte development [1,4]. Honeybee vitellogenin has been hypothesized to work together with juvenile hormone in a double repressor network to coordinate behavior [7]. In this network, vitellogenine suppresses juvenile hormone and inhibits the worker honeybees' age-associated shift from nest tasks to foraging duties [3]. This shift is a complex behavioral transition characterized by decreasing vitellogenin and increasing juvenile hormone titer [8]. It has been proposed also that variation in vitellogenin gene expression early in life is associated with subsequent behavioral specialization that gives rise to a division of labor between nectar and pollen foraging workers [9]. Finally, honeybee vitellogenin can reduce oxidative stress by scavenging free radicals, thereby prolonging lifespan in the facultatively sterile worker castes and the reproductive queen castes [4]. Similar antioxidant function has been suggested for vitellogenin molecules in the nematode Caenorhabditis elegans [10] and in eggs of the eel Anguilla japonica [11], but positive effects of vitellogenin on adult longevity have not been demonstrated in these species. In summary, the proposed pleiotropic effects of honeybee vitellogenin suggest that the vitellogenin gene is a central element in the life-history regulation of this social insect. Here we test these proposed functions by using RNA interference (RNAi) to knock down expression of the honeybee vitellogenin gene. Results The vitellogenin RNAi tool [12] was used in combination with observations of the behavior and lifespan of worker honeybees living in otherwise unmanipulated colonies. RNAi-mediated knockdown of the vitellogenin protein has been confirmed repeatedly in 5–7-d-old worker bees [3,5,12]. In this first RNAi study of honeybee social life history, however, we aimed to monitor workers over several weeks. Therefore, RNAi was validated in cohorts of 10-d-old (n = 31), 15-d-old (n = 27) and 20-d-old (n = 27) bees (Figure 1). Figure 1 The Effect of vitellogenin RNAi on Hemolymph Vitellogenin Concentrations Levels are in micrograms per microliter relative to a β-galactosidase standard. Significant suppression of vitellogenin is apparent in RNAi knockdowns (vgRNAi) compared to injected controls (injGFP; Mann-Whitney U test: Z = 2.84, n = 54, p 0.05). Our finding is supported by the previous results showing that worker bees with reduced vitellogenin activity levels are more susceptible to oxidative stress [4], a physiological state that is an established indicator of aging [18,19]. Figure 4 Effect of vitellogenin Gene Activity on Lifespan Cumulative hazard increases until all bees have died. Injected controls (injGFP) lived longer than knockdowns (vgRNAi; LRT = 4.38, df = 1, p < 0.036, hazard ratio [comparative survival experience calculated over the entire time of the study] = 1.29 d longer, confidence interval = 1.02–1.63 d). Longevity was affected by laboratory handling (LRT = 43.4, df = 1, p < 0.0001, hazard ratio = 1.96 d longer for non-injected reference (noREF) bees compared with injGFP bees, confidence interval = 1.61–2.38 d). Discussion Our results suggest that honeybee vitellogenin has an integrative function in regulating social organization through its pleiotropic effects on division of labor and foraging specialization. Vitellogenin inhibits the onset of foraging (our study) but declines with age in workers [8,20], thereby serving as a pacemaker for age polyethism and lifespan, as first hypothesized by Omholt and Amdam [7,21]. Higher titers early in life [9] prime bees for pollen collection, whereas low titers prime bees for collecting nectar (our study). vitellogenin RNAi established at adult emergence triggers persistent suppression of vitellogenin activity [3,5,12] (Figure 1), and therefore, the knockdown phenotype was expected to initiate foraging early, collect nectar, and live a short life (Figure 5). Figure 5 Vitellogenin Has a Dual Role in Regulation of Social Behavior After the maturation phase, when bees are unable to forage (grey) [37], vitellogenin suppresses the transition from nest tasks to foraging activity when its titer remains above the foraging threshold level [3,7]. Below this threshold, the probability of initiating foraging is increased [5]. Pre-foraging vitellogenin titers above the pollen threshold prime workers for pollen foraging (green), while workers with lower pre-foraging titers (yellow) are primed for nectar foraging [9]. vitellogenin RNAi causes workers to mature with vitellogenin titers that are below both thresholds [3,7,9,12], resulting in the vitellogenin knockdown phenotype documented here: bees that forage precociously and preferentially collect nectar. Life-history pleiotropy demonstrated by the effects of vitellogenin is similar in principle to trait associations that are controlled by the systemic endocrine factors juvenile hormone and ecdysone in the solitary insect Drosophila (reviewed by Flatt et al. [22]). In Drosophila, yolk precursor peptides [23] are downstream components of these hormonal signaling cascades [24], whereas in honeybees, vitellogenin is part of a regulatory feedback loop that enables vitellogenin and juvenile hormone to mutually suppress each other [3,4,7]. As a consequence, vitellogenin and juvenile hormone should be considered joint effectors of division of labor and foraging specialization, at least until methods can be developed to separate their individual effects. This feedback relationship is uncommon in insects [3], suggesting in combination with our findings that evolutionary co-option and remodeling of vitellogenin and juvenile hormone action [1,4–6] have been important steps in honeybee social evolution [3]. Previous studies have identified genes that affect honeybee foraging onset (Amfor [25] and malvolio [26]), and multiple genes with mRNA levels that correlate with foraging behavior [27] or lifespan [28]. Yet our work represents the first successful RNAi approach to decipher gene and protein function in honeybee social behavior. Our data demonstrate for the first time that several key characteristics of a social phenotype can be coordinated by a single reproductive gene. This pleiotropy lends support to studies showing that complex social behavior in insects can evolve from ancestral reproductive traits [9,29–31]. Materials and Methods Validation of vitellogenin knockdown. The non-injected reference (noREF), GFP dsRNA control (injGFP), and vitellogenin knockdown (vgRNAi) phenotypes were obtained as previously described by Amdam et al. [5,12]. In short, primers were designed from the sequence of the A. mellifera vitellogenin cDNA clone AP4a5, and the GFP encoding sequence of the pGFP vector (Clontech, Palo Alto, California, United States). GFP dsRNA does not affect vitellogenin [5], but was used in planned comparisons with vitellogenin dsRNA to control for laboratory handling that affects sensory and physiological correlates of worker foraging behavior [5,13,14]. Primers were fused with T7 promoter sequence (underlined): for clone AP4a5: 5′-TAATACGACTCACTATAGGGCGAACGACTCGACCAACGACTT-3′ and 5′-TAATACGACTCACTATAGGGCGAAACGAAAGGAACGGTCAATTCC-3′; and for pGFP: 5′-TAATACGACTCACTATAGGGCGATTCCATGGCCAACACTTGTCC-3′ and 5′-TAATACGACTCACTATAGGGCGATCAAGAAGGACCATGTGGTC-3′. PCR reactions were performed according to standard procedures using AP4a5 and the pGFP vector as templates. Resulting products excluding the fused T7 promoters were 504 base pairs (bp) (vitellogenin) and 503 bp (GFP derived). Products were purified using the QIAquick PCR purification kit (Qiagen, Valencia, California, United States), and RNA was prepared using the Promega RiboMax T7 system (Promega, Madison, Wisconsin, United States). RNA was extracted by TRIzol LS reagent (GIBCO-BRL, San Diego, California, United States), resuspended in nuclease-free water, heated at 96 °C for 2 min in an Eppendorf Thermomixer (Brinkmann Instruments, Westbury, New York, United States), and left to cool at room temperature for 20 min. The integrity of the dsRNA was tested using 1.5% agarose gels, and the products were diluted with nuclease-free water (Qiagen) to the final concentration of 5 μg/μl. Newly emerged workers were randomly assigned to one of three treatments and marked with paint (Testors Enamel; Testor Corporation, Rockford, Illinois, United States) to indicate treatment identity. The noREF group was set aside. The two remaining groups were injected with vitellogenin-derived or GFP-derived dsRNA (to make up the vgRNAi or injGFP treatment, respectively) between the fifth and sixth tergite using Hamilton syringes with G30 disposable needles (BD, Palo Alto, California, United States). Injection volume was 2 μl. Injections were performed by trained personnel that were blind to treatment identities. Workers were introduced into two colonies kept in commercial hive boxes (n = 50 for each treatment group and in each colony, respectively) and collected after 10, 15, and 20 d during non-foraging hours. Bees were anesthetized on ice, and hemolymph was extracted with Drummond Scientific Company (Broomall, Pennsylvania, United States) micropipettes after puncturing the abdomen between the third and fourth tergite with a sterile G30 needle (BD). Care was taken to avoid contaminating the samples with tissue fragments and foregut content. Hemolymph (1 μl) was dissolved in 10-μl Tris buffer: 20 mM Tris, 150 mM NaCl, 5 mM EDTA (pH 7.5), 1 mM phenylmethylsulfonyl fluoride, 5 mM benzamidin, 0.7 μM pepstatin, 8 μM chymostatin, 10 μM leupeptin, 0.8 μM aprotinin (Sigma-Aldrich, St. Louis, Missouri, United States), before samples were separated by 8% SDS-polyacrylamide gel electrophoresis using standard methods [32]. A β-galactosidase standard (Sigma-Aldrich) was included to allow densitometrically quantification by the method of Lin et al. [33], in which vitellogenin is detected as a single band of 180 kDa [5,33,34]. The densitometrical analysis was performed by the Quantity One imaging software (Bio-Rad, Hercules, California, United States) after staining the gels with Commassie Brilliant Blue (Sigma-Aldrich). Gel-to-gel variation in staining intensity was controlled by background correction and the β-galactosidase standards as we have described previously [5]. Age of foraging onset and lifespan. Newly emerged workers were randomly assigned to one of three treatments. noREF bees were uniquely tagged and set aside. Groups of vgRNAi and injGFP workers were obtained as described above. About equal numbers of bees from each treatment group were introduced into two host colonies (n = 288 noREF, 338 injGFP, and 293 vgRNAi into Colony 1; and n = 288 noREF, 338 injGFP, and 299 vgRNAi into Colony 2). Each colony was set up in an observation hive with about 5,000 unmarked adult bees of diverse ages. Observers were blind to treatment identity. Colonies were surveyed daily for tagged bees during non-foraging hours to establish survivorship (the combs of each colony were scanned twice daily), and for two 40-min periods daily during peak foraging hours to establish foraging activity. Ramps from the outside port leading to the bottom comb were observed for incoming tagged forager bees during these 40-min sessions. A bee's age of foraging onset was the number of days since adult emergence that she was first seen returning from a foraging trip. A bee's day of death was established as the day after the last day she was observed. Substance collected. Set-ups were separate, but identical, to the one described for age of foraging onset and lifespan, except that host colonies were kept in commercial hive boxes. During peak foraging hours, incoming foragers were collected at the hive entrances, brought to the laboratory, and sampled once for type of substance collected. Bees were not returned to the colonies after sampling. At the time of collection, the workers were 10–16 d old (Colony 1) or 7–13 d old (Colony 2). Pollen and/or nectar loads were removed and quantified for each individual worker as described before [35]. In all, n = 80 noREF, 84 injGFP, and 65 vgRNAi bees were taken from Colony 1, and n = 78 noREF, 75 injGFP, and 95 vgRNAi bees were taken from Colony 2. Workers that returned empty (with no measurable nectar or pollen) were not used in our analyses. Data analysis. The dataset on hemolymph vitellogenin levels was not normally distributed, as determined by Bartlett's test of sphericity. Therefore, the non-parametric Kruskal-Wallis test was used (n = 85) to examine the data for effects of treatment (H = 14.32, p = 0.001) and age (H = 0.79, p = 0.68). A Mann-Whitney U test was used to test for colony effects (Z = −3.54, p < 0.001). Vitellogenin titers were higher overall in Colony 2, but the relative expression pattern between treatments was the same in the two colonies (unpublished data). Therefore, the dataset was not split by colony, but used in full to increase the statistical power of the post hoc analysis. A Mann-Whitney U test was used as a post hoc test of the planned comparisons of vitellogenin levels between noREF and injGFP, and between injGFP and vgRNAi. Treatment differences in age of foraging onset and lifespan were analyzed using the Cox proportional hazards regression model with the likelihood ratio chi-square tests (LRT) for bees that foraged at least twice (n = 149 noREF, 69 injGFP, and 48 vgRNAi for Colony 1; and n = 137 noREF, 110 injGFP, and 74 vgRNAi for Colony 2). The proportional hazards assumption was verified by Schoenfeld residuals [36]. Colony effects were controlled for by using the colony as a stratifying variable in the analyses. Effect of treatment was detected in the dataset overall (foraging onset LRT = 95.1, df = 2, p < 0.0001; lifespan LRT = 82.2, df = 2, p < 0.0001). Thus, planned pair-wise comparisons were made between noREF and injGFP, and between injGFP and vgRNAi. The data on foraging loads passed Bartlett's test of sphericity. Two-way analysis of variance (ANOVA) was therefore used to test for effects of treatment on foraging loads while controlling for the colony factor. A significant effect of treatment was detected (ANOVA, F 2,471 p < 0.0001) and planned pair-wise comparisons were made using a two-way ANOVA. Pearson analysis was used to correlate age at foraging onset and lifespan. Statistical software was SPLUS version 6.1 (http://www.insightful.com), Systat 6.0 (http://www.systat.com), and Statistica 6.0 (http://www.statsoft.com). Supporting Information Accession Numbers The GenBank (http://www.ncbi.nlm.nih.gov/Genbank) accession numbers for the genes discussed in this paper are vitellogenin (AJ517411) and the GFP encoding sequence of the pGFP vector (AF324407).
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              Draft genome of the globally widespread and invasive Argentine ant (Linepithema humile).

              Ants are some of the most abundant and familiar animals on Earth, and they play vital roles in most terrestrial ecosystems. Although all ants are eusocial, and display a variety of complex and fascinating behaviors, few genomic resources exist for them. Here, we report the draft genome sequence of a particularly widespread and well-studied species, the invasive Argentine ant (Linepithema humile), which was accomplished using a combination of 454 (Roche) and Illumina sequencing and community-based funding rather than federal grant support. Manual annotation of >1,000 genes from a variety of different gene families and functional classes reveals unique features of the Argentine ant's biology, as well as similarities to Apis mellifera and Nasonia vitripennis. Distinctive features of the Argentine ant genome include remarkable expansions of gustatory (116 genes) and odorant receptors (367 genes), an abundance of cytochrome P450 genes (>110), lineage-specific expansions of yellow/major royal jelly proteins and desaturases, and complete CpG DNA methylation and RNAi toolkits. The Argentine ant genome contains fewer immune genes than Drosophila and Tribolium, which may reflect the prominent role played by behavioral and chemical suppression of pathogens. Analysis of the ratio of observed to expected CpG nucleotides for genes in the reproductive development and apoptosis pathways suggests higher levels of methylation than in the genome overall. The resources provided by this genome sequence will offer an abundance of tools for researchers seeking to illuminate the fascinating biology of this emerging model organism.
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                10.1038/ncomms4636
                24845553

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