Epigenetic Regulator CoREST Controls Social Behavior in Ants

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Epigenetic Regulator CoREST Controls Social Behavior in Ants Graphical Abstract

Authors Karl M. Glastad, Riley J. Graham, Linyang Ju, Julian Roessler, Cristina M. Brady, Shelley L. Berger

Correspondence [email protected]

In Brief Glastad et al. find that epigenetic regulation is pivotal in mediating programming and reprogramming of worker ant behavior. The conserved neuronal co-repressor CoREST, working with histone deacetylation, is vital in establishing foraging behavior via binding to and repressing genes that degrade JH, a behaviorally mportant hormone promoting foraging.

Highlights d

Reprogrammed worker ant behavior mirrors natural programming via an epigenetic switch

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Neuronal co-repressor CoREST mediates this behavioral programming and reprogramming

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CoREST controls genes that then govern levels of foragingpromoting JH

Glastad et al., 2020, Molecular Cell 77, 1–14 January 16, 2020 ª 2019 Elsevier Inc. https://doi.org/10.1016/j.molcel.2019.10.012

Please cite this article in press as: Glastad et al., Epigenetic Regulator CoREST Controls Social Behavior in Ants, Molecular Cell (2019), https://doi.org/ 10.1016/j.molcel.2019.10.012

Molecular Cell

Article Epigenetic Regulator CoREST Controls Social Behavior in Ants Karl M. Glastad,1,4 Riley J. Graham,1,3,4 Linyang Ju,1,3 Julian Roessler,1 Cristina M. Brady,1 and Shelley L. Berger1,2,3,5,* 1Epigenetics

Institute, Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, PA 19104, USA of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA 3Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA 4These authors contributed equally 5Lead Contact *Correspondence: [email protected] https://doi.org/10.1016/j.molcel.2019.10.012 2Department

SUMMARY

Ants acquire distinct morphological and behavioral phenotypes arising from a common genome, underscoring the importance of epigenetic regulation. In Camponotus floridanus, ‘‘Major’’ workers defend the colony, but can be epigenetically reprogrammed to forage for food analogously to ‘‘Minor’’ workers. Here, we utilize reprogramming to investigate natural behavioral specification. Reprogramming of Majors upregulates Minor-biased genes and downregulates Major-biased genes, engaging molecular pathways fundamental to foraging behavior. We discover the neuronal corepressor for element-1-silencing transcription factor (CoREST) is upregulated upon reprogramming and required for the epigenetic switch to foraging. Genome-wide profiling during reprogramming reveals CoREST represses expression of enzymes that degrade juvenile hormone (JH), a hormone elevated upon reprogramming. High CoREST, low JH-degrader expression, and high JH levels are mirrored in natural Minors, revealing parallel mechanisms of natural and reprogrammed foraging. These results unveil chromatin regulation via CoREST as central to programming of ant social behavior, with potential far-reaching implications for behavioral epigenetics. INTRODUCTION Eusocial insects are among the most successful taxa on earth (Ho¨lldobler and Wilson, 1990) as a result of their ability to segregate tasks between different, often morphologically or behaviorally distinct individuals within a colony. Because of this extreme phenotypic and behavioral plasticity, ants have emerged as models for interrogating complex social behavior and for investigating epigenetic mechanisms that program the expression of a shared genome into disparate individual phenotypes (Smith et al., 2008; Yan et al., 2014). An important example of this division of labor involves differentiation of individuals into sterile

(worker) and reproductive (queen) physiological castes (Ho¨lldobler and Wilson, 1990). Another striking manifestation in many eusocial insect species, is the allocation of distinct colony roles among worker groups (Ho¨lldobler and Wilson, 1990; Robinson, 1992; Tschinkel, 2006; Wilson, 1976). Epigenetic alteration correlates with differential morphology and behavior among ant castes, involving distinct patterns of chromatin modifications including histone post-translational modifications (hPTMs) and possibly DNA methylation (Bonasio, 2014; Bonasio et al., 2012; Glastad et al., 2016; Kucharski et al., 2008; Simola et al., 2013, 2016; Wojciechowski et al., 2018; see also Libbrecht et al., 2016). hPTMs are a diverse set of epigenetic signals that typically occur on histone protein N-terminal amino acid tails and alter transcription through several mechanisms. hPTMs can alter the accessibility of underlying DNA to transcriptional regulators by weakening (for histone acetylation) or tightening (for deacetylation) association between histones and DNA (Zhou et al., 2011). In addition, hPTMs can serve as binding surfaces for effector proteins (Badeaux and Shi, 2013). Another emerging mediator of caste division of labor in multiple eusocial insects are the traditionally metamorphosis-associated hormones juvenile hormone (JH) and ecdysone (20E). These small-molecule hormones play important roles in both the developmental (Nijhout and Wheeler, 1996)) and behavioral division of labor (Barchuk et al., 2002; Fahrbach, 1997; Libbrecht et al., 2013; Robinson et al., 1991; Robinson and Vargo, 1997; Sommer et al., 1993). JH, in particular, is associated with both reproductive castes (Robinson et al., 1991) and distinct behavioral states between workers in honeybees and ants (Fahrbach, 1997; Robinson and Vargo, 1997). In honeybees and ants, increased JH is associated with age-associated transition to foraging in workers (Dolezal et al., 2012), and thus serves a key role in organizing colony behavioral division of labor. The Florida carpenter ant, Camponotus floridanus, has two distinct worker castes: Major and Minor workers. These worker castes display diverse morphologies and behaviors, with smaller Minor workers performing foraging and nursing of brood, whereas larger Major workers defend the nest as soldiers and very rarely forage (Simola et al., 2016). Strikingly, in C. floridanus, Major workers can be reprogrammed to forage, using chromatin-based manipulation via genetic and pharmacological tools (Simola et al., 2016). Prominent unanswered questions Molecular Cell 77, 1–14, January 16, 2020 ª 2019 Elsevier Inc. 1

Please cite this article in press as: Glastad et al., Epigenetic Regulator CoREST Controls Social Behavior in Ants, Molecular Cell (2019), https://doi.org/ 10.1016/j.molcel.2019.10.012

include: what are the intrinsic epigenetic mechanism(s) that underlie programming of caste-specific behaviors, and do the same molecular pathways engage in the experimentally induced epigenetic reprogramming? In this study, we discover that innate chromatin regulation via the corepressor for element-1-silencing transcription factor (CoREST) mediates the natural programming of foraging behavior in Minor workers. Moreover, reprogramming of Major workers to forage commissions this same CoREST epigenetic pathway. While CoREST has long been linked to neural development and neuronal sub-type specification (Abrajano et al., 2009, 2010; Dallman et al., 2004; Qureshi et al., 2010), a direct role in regulation of behavior has not been documented. Our findings reveal that transient epigenetic plasticity is linked to a long-lasting behavioral phenotype, and a chromatin-based epigenetic mechanism governs complex social behavior. RESULTS

Figure 1. Time Course Histone Deacetylase Inhibitor (HDACi) Injections Reveals a ‘‘Window’’ of Behavioral Reprogramming (A) Setup for HDACi brain injection behavioral assays. Major and Minor workers were paint marked upon eclosion and returned to the nest, followed by injection of Majors with 1 mL of HDACi (TSA) or vehicle control (DMSO) at 0, 5, and 10 days post-eclosion. Groups of 10 injected Majors and 10 agematched uninjected Minors were placed in miniature nest area (N) connected by 1 foot of tubing to an external foraging arena (FA) and their foraging activity was imaged for 10 days. (B) Major foraging data for days 0, 5, and 10 for DMSO (blue; n R 3, each time point) and TSA-injected (red; n = 5, each time point) ants. Bars represent average ± SEM. p values determined via Mann-Whitney U test. (C) The same as for (B), but with Minor workers included and broken into individual days of measurement. For day 5-injected ants, all post-injection days are significant via Mann-Whitney U test; for day 0-injected ants, day 9 and day 10 are significant. Bars represent average ± SEM.

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A Peak of Major Worker Reprogramming Occurs at Day 5 Post-eclosion To discover mechanisms underlying caste-specific behavior, we reasoned that central pathways could be identified by the overlap between pathways utilized in natural foraging Minor workers and in Major workers reprogrammed to forage. Previously, we found that injection of the histone deacetylase inhibitor trichostatin A (TSA) induces foraging in newly eclosed C. floridanus Major workers (Simola et al., 2016). To identify mechanisms that promote foraging in Major workers, we first established the peak time for reprogramming after eclosion (defined as emergence of the adult animal from the pupal case). To assess this, Major workers were injected with TSA compared to vehicle control at 0, 5, and 10 days (d0, d5, d10) post-eclosion, and foraging activity was assayed over 10 days following injection (Figure 1A; STAR Methods). Both d0 and d5 Majors exhibited significantly increased foraging (Figure 1B); elevated foraging began 1 day after injection and continued to accumulate for 10 days (Figure 1C). Notably, Major workers injected on d5 with TSA exhibited the strongest induction of foraging, reaching levels of foraging observed in natural Minor workers; this effect was completely absent in TSA-injected d10 Major workers (Figures 1B and 1C). It is remarkable that this ‘‘window’’ of susceptibility to epigenetic reprogramming is so narrowly defined. Transcriptomic Signatures of Natural Caste Identity and during Window of Behavioral Plasticity To discern key genetic pathways of programming, we performed several comparative transcriptomic analyses: (1) ‘‘age-DEGs’’ to find salient changes in early life common to both castes for insight into early brain plasticity; (2) ‘‘caste-DEGs’’ comparing natural Minor workers to natural Major workers to find key differences that underlie profound behavior differences; and (3) ‘‘reprogramming-DEGs’’ focusing on the d5 peak of induced foraging in TSA-injected Majors, to uncover pathways that become activated in reprogrammed Majors and overlap with natural Minor workers but are suppressed in natural Major workers.

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RNA sequencing (RNA-seq) was carried out on individual whole brains of untreated Minors and Majors of d0, d5, and d10 (n R 6 for each caste and age; Figures S1A and S1B), to determine how gene expression naturally varies overall in both castes at the time points relevant to the d5 peak of Major worker reprogramming. We analyzed Gene Ontology (GO) functional terms enriched among differentially expressed genes (DEGs) comparing peak d5 to d0 and d10, to obtain age-DEGs (Figures 2A, 2B, S1C, and S1D; Table S1). While many terms were significantly associated with these age-DEGs, two categories may be principally linked to the dramatic difference in susceptibility to behavioral reprogramming. In the first category, were many terms related to neuronal and synaptic function, such as ‘‘synapse assembly,’’ ‘‘regulation of synaptic vesicle exocytosis,’’ ‘‘memory,’’ and ‘‘synaptic growth at neuromuscular junction’’ (Table S1). Importantly, many significant terms associated with neuronal functions were associated with genes most highly expressed at d5 (Figures 2B, 2C, and S1C; Table S3); these terms were even more strongly enriched when focusing on genes highest in Majors (Figures 2A and 2C), discussed in detail below. Second, many terms were associated with epigenetic regulation such as ‘‘chromatin remodeling,’’ ‘‘histone H3 acetylation,’’ ‘‘chromatin-mediated maintenance of transcription,’’ and ‘‘positive regulation of gene expression, epigenetic’’ (Figure 2A, green; Table S1). Indeed, we found that many epigenetic regulators were differentially expressed between either d0 and d5 or d5 and d10 (Figures 2B, 2D, and S1D), and many of these genes showed highest or lowest expression at d5. Thus, two pivotal factors gleaned from age-DEGs transcriptomics that may govern brain plasticity just after eclosion—at the peak of Major worker reprogramming at d5—are dynamic changes in the epigenome and changes in neuronal remodeling and function, which appear greatly reduced at d10 (Figures 2C and 2D). Next, we assessed genes differentially expressed between castes (caste-DEGs) at each time point, to uncover potential pathways that might promote natural foraging in Minor workers. There was a stepwise reduction in overall number of caste-DEGs as age increased from d0 to d10, with over 2,500 genes differentially expressed at d0 (1,304 Major-biased, 1,289 Minor-biased at false discovery rate [FDR] <0.1) (Figure 2E, left), 245 genes at d5 (52 Major-biased, 192 Minor-biased at FDR <0.1) (Figure 2E center), and only 2 genes at d10 (1 Major-biased, 1 Minorbiased) (Figure 2E, right; Table S2). This starkly diminishing difference between transcriptomes of Major and Minor brains over this time frame may reflect an early period of distinct neuronal development at d0 and d5, with neuronal architecture

becoming entrenched by d10, and is consistent with the strong enrichment of neuronal functional terms seen at d5 (Figure 2A; Table S1). The remarkable lack of significant differences in gene expression between castes in the brain at d10 may underlie the profound reduction in reprogramming efficiency seen at d10 compared to d5. Closer examination of caste-DEGs revealed numerous genes differentially regulated at d0 and d5 that are associated with caste-specific differences in other social insects (Mackert et al., 2008). Prominent examples include regulation of and signaling to JH and ecdysone; the balance between these hormones is associated with reproductive caste and behavioral states in social insects (Barchuk et al., 2002; Fahrbach, 1997; Robinson et al., 1991; Robinson and Vargo, 1997), similar to peptide and small-molecule hormones regulating behavior in mammals (Pryce, 1996; Takahashi, 1990). Relevant genes repressed in Majors were JHamt (JH acid O-methyltransferase) and Ari1 (negative regulator of ecdysone signaling) (Figure 2E; Table S3). In contrast, genes highly activated in Majors were those encoding JHe and JHeh, two enzymes that degrade JH (Figure 2E; Table S3). These results suggest that early developmental canalization of Major- and Minor-specific behaviors may be regulated by the balance between JH and ecdysone signaling, a finding supported in other social hymenoptera (Fahrbach, 1997; Mackert et al., 2008; Robinson et al., 1991; Robinson and Vargo, 1997; Sommer et al., 1993). Indeed, further analyses and functional manipulation below, underscore that JH/ecdysone signaling may be key hormonal pathways regulating caste specificity. Injection of TSA in Major Workers Upregulates Natural Minor-Specific Genes Given our hypothesis that the balance in JH/ecdysone signaling may be central to Major/Minor behavioral specification, we next evaluated gene expression in the reprogrammed Major worker ant brain. RNA-seq was performed on Major worker brains collected after TSA or control injections, thus comparing maximum reprogramming (d5 injection) to minimum reprogramming (d10), to define reprogramming-DEGs. Due to the short half-life of TSA (Sanderson et al., 2004), individual brains were collected 1 and 3 h after injection to investigate immediate and longer-lasting gene expression variations that might be key to reprogramming. Within 1 h of TSA injection into d5 Major workers, 729 genes were differentially expressed, with 63% upregulated (456 up, 273 down) (Figure 3A, left; Table S2). Upregulated genes include many fundamental housekeeping and cell-cycle-related

Figure 2. RNA-Seq Changes between Major and Minor at Days 0, 5, and 10 (A) Top 10 GO terms enriched among DEGs between d5 Majors and other time points are enriched for neural (blue) and epigenetic (green) functions. p values from Fisher’s exact test as implemented by topGO (elim method). (B) Volcano plot illustrating DEGs between d5 and other time points (d0 and d10) are enriched for terms related to neuronal (blue) and chromatin modifying (green) functional terms. (C) RNA-seq expression heatmaps of genes showing significantly higher expression at d5 with functional assignments of ‘‘Neurogenesis,’’ ‘‘Synapse organization,’’ ‘‘Dendrite development’’ and ‘‘Memory.’’ (D) RNA-seq expression heatmaps of epigenetic regulators (annotated with the gene ontology functional term ‘‘covalent chromatin modification’’) showing significantly (adjusted p value < 0.01) lower (top) or higher (bottom) expression at day 5 in C. floridanus worker brains. (E) Volcano plots illustrating decrease in transcriptome divergence between day 0, day 5, and day 10 untreated Major versus Minor workers (n R 6; red points: adjusted p value < 0.05, green points: genes of interest with adjusted p value < 0.05).

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Figure 3. Transcriptome and Epigenome of HDACi Reveals Rapid Response to Global Hyperacetylation (A) Volcano plots illustrating genes induced and repressed by TSA at 1 h (left) and 3 h (right). Genes significantly differentially expressed (adjusted p value < 0.05) between untreated Major and Minor workers are shown as orange and blue points (respectively). (B) Bar plot showing odds ratios from hypergeometric test of DEG overlap between HDACi datasets and caste-biased genes illustrating high level of overlap between caste biased DEGs and HDACi DEGs at day 5 3 h (top right) but little overlap for the same comparison at day 10 (bottom right). (C) Heatmap of RNA-seq expression for all caste DEGs that overlap with 3 h TSA DEGs, separated into those showing upregulation with TSA + untreated Minor bias (left), downregulation with TSA + untreated Major bias (top right), or those not showing such consistency (bottom right). (D) Metaplots of H3K27ac enrichment at 1 h and 3 h TSA upregulated genes illustrating global trend of hyperacetylation at TSA upregulated DEGs. (E) Global correlations between RNA-seq log2 expression ratios and promoter H3K27ac log enrichment ratios for genes showing even marginal degrees of differential expression with TSA (adjusted p value < 0.15). Given values are R2 as well as Spearman’s rank correlation coefficients. (F) Average ratios of TSA:DMSO of normalized proportion of sequencing reads mapping to exogenous genome for H3K27ac samples (see STAR Methods) illustrating overabundance of H3K27ac at 1 h TSA-treated samples relative to other samples. Bars represent average ± 95% confidence intervals.

genes, encoding mismatch repair proteins (e.g., Msh6, lds/ TTF2, TP53BP1, MRE11) and cell-cycle control proteins (e.g., CDC45L, borealin, CCNE1, CCNA1). Functional terms for upregulated genes were associated with histone deacetylation,

‘‘DNA replication,’’ ‘‘cell cycle’’ and other similar terms (Table S4), while downregulated genes showed enrichment of organism-relevant or behavioral functional terms such as ‘‘copulation’’ and ‘‘learning or memory’’ (Table S4). By 3 h after

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TSA-injection, fewer genes were differentially expressed, with less bias toward upregulation (275 genes: 150 up, 125 down) (Figure 3A, right). Of genes differentially expressed within 1 h of TSA injection, less than 10% (69/729) were also differentially expressed at 3 h post-injection, suggesting that, by 3 h, transcriptional differences are distinct from those at 1 h. Genes upregulated at 3 h related to histone deacetylation, DNA replication, and DNA repair, whereas genes downregulated were enriched for terms potentially more relevant to caste behavior, such as ‘‘regulation of TOR signaling,’’ steroid and isoprenoid metabolic processes, and gravitaxis (Table S4). Taken together, these results suggest that in the brains of Major workers TSA-injected at d5, at 1 h after injection, cells are rapidly reacting to and compensating for high levels of acetylation, while by 3 h after injection, this response has lessened and the downstream sequela relating to behavior are underway. Samples injected at d10 showed an opposite pattern of DEGs at 1 and 3 h, with more changes detected after 3 h following TSA injection than after 1 h (1 h: 220 DEGs, 3 h: 623 DEGs) (Figure S2B; Table S2); the reasons for this opposite pattern are unclear. To identify key genes potentially driving foraging behavior, we compared naturally occurring caste-DEGs between untreated Major and Minor workers (Figure 2E), with reprogrammingDEGs in Major workers injected with TSA to reprogram their behavior (Figure 3A). Reprogramming-DEGs (d5 TSA-injected assayed at 3 h) significantly overlapped with caste-DEGs at both d5 and d10, but far more significantly with d5 casteDEGs (d5 chi-square p value = 3.9e
14, d10 chi-square p value = 3.8e
03) (Figures 3B and S2A). Strikingly, d5 reprogramming-DEGs (3 h) exhibiting increased expression were largely Minor-specific, whereas d5 reprogramming-DEGs (3 h) exhibiting decreased expression were largely Major-specific (Figures 3B, 3C, S2A, and S2E). This finding suggests that key gene expression differences driving reprogramming behavior recapitulate the normal regulation in Minors and Majors, and further, occur quickly (by 3 h) after TSA injection. Moreover, these reprogramming-DEGs are long-lasting in their behavior impacts, given their high concordance with caste-DEGs. Deeper analysis of the specific genes represented in the d5 reprogramming-DEGs highlighted a high level of consistency between these reprogramming-DEGs and untreated casteDEGs: of the genes showing differential expression in d0 untreated caste-DEGs (92 genes), 80% of these (74 DEGs) showed reprogramming-upregulation + Minor-bias (48 DEGs) or reprogramming-downregulation + Major-bias (26 DEGs) (Figure 3C). This consistency between reprogramming-DEGs and untreated caste-DEGs was also maintained in DEGs across untreated time points as determined by a combined linear model approach (see STAR Methods; 28 genes showing reprogrammingupregulation + Minor-bias and 21 genes showing reprogramming-downregulation + Major-bias) (Figures S2A and S2E– S2G). Reprogramming-upregulation + Minor-biased genes included tramtrack (ttk) (see below for additional findings), king tubby, neuroligin, and neprilysin-1, and were enriched for functional terms such as ‘‘presynapse organization,’’ and ‘‘TOR signaling’’ (Table S4)—the former term being related to hormonal response, the latter being linked to caste in the honeybee (Patel et al., 2007). Reprogramming-downregulation + Major-biased

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genes included the JH-degrading genes JHeh and JHe discussed above, as well as the Hedgehog-signaling-associated gene shifted (shf), and were additionally enriched for functional terms including ‘‘sesquiterpenoid metabolic process,’’ and ‘‘neuron recognition’’ (Table S4). Taken together, the transcriptomics show reprogramming at d5 of both activated key caste-DEGs naturally higher in Minor workers and repressed key caste-DEGs naturally higher in Major workers—a pattern that was not present at d10 injected ants (Figures S2A, S2E, and S2F). Thus, TSA injection leads to behavioral reprogramming of Majors both by inducing a Minor-like programs and repressing Major-like programs of gene expression in the brain. CoREST Mediates Foraging Behavior in Reprogrammed Majors We interrogated brain chromatin alterations during reprogramming to determine whether TSA injection leads to increased histone acetylation at upregulated genes. We focused on histone H3 lysine-27 acetylation (H3K27ac) given its key role in transcriptional activation (Long et al., 2016) and association of H3K27ac with caste DEGs (Simola et al., 2013). Samples corresponding to the RNA-seq time points, at 1 h and 3 h post-TSA injection for d5 and d10 injections, were analyzed by chromatin immunoprecipitation sequencing (ChIP-seq) (Brind’Amour et al., 2015) in single ant brains. At both 1 and 3 h post-TSA injection, upregulated genes exhibit higher acetylation consistent with increased expression (Figures 3D, 3E, S3A, and S3B). At 1 h post-TSA injection at d5, there was extensive differential acetylation across the genome (Figure 3F), with 5,700 regions showing higher or lower acetylation and a general trend of hyperacetylation (3,439/5,700 hyperacetylated) (Figures S3A and S3B; Table S5). Notably, by 3 h post-TSA injection at d5, there was marked reduction in differential acetylation (only 455 regions, 284/455 hyperacetylated) (Table S5); this may result from compensatory upregulation of HDACs themselves (see below). A similar trend occurred in d10-injected Majors with increased differential acetylation 1 h following TSA injection (4,886/7,110 DBRs hyperacetylated) and greatly reduced hyperacetylation at 3 h following TSA injection (388 DBRs 3 h) (Figure 3F; Table S5). The findings from d10 TSA injections suggest that the lack of reprogramming at d10 (compared to robust reprogramming at d5) is not due to a poor global acetylation response to TSA injection, but instead is likely a change in how targeted genes respond to TSA injection due to other superimposed regulation. Overall, there is well-correlated increased acetylation at genes that exhibit increased expression at 1 h and 3 h post-TSA injection (Figure 3E). Among the top reprogramming-DEGs, we observed strong upregulation of genes related to transcriptional repression and chromatin deactivation, including the histone deacetylase Rpd3/HDAC1 and the transcriptional/chromatin co-repressor CoREST (Figures 3A and 4A), which were both among the top 20 TSA-induced genes at 1 h following TSA injection. We noted that CoREST and HDAC1 genes both showed increased H3K27ac over their promoters at 1 h following TSA injection, correlating with increased RNA levels (Figure 4B). These

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Figure 4. CoREST Binding Reveals Response to HDACi (A) CoREST and HDAC1 are significantly upregulated with TSA in reprogramming RNA-seq data (n R 4, each condition). Adjusted p values were determined by DESeq2. (B) Genome browser tracks showing significant hyper-acetylation at promoters of CoREST (left) and HDAC1 (right). Tracks represent fold enrichment of ChIP versus Input control. (C) Genes upregulated 1 h following TSA show higher enrichment of CoREST signal in or near promoters at both time points, while genes repressed 3 h following TSA show higher CoREST signal at or near promoters at 1 h. p values from a Mann-Whitney U test. (D) Regions with higher CoREST binding 1 h after TSA show lower H3K27ac by 3 h, while those showing higher CoREST binding 3 h after TSA show generally higher H3K27ac with TSA. (E) Top 5 motifs associated with all CoREST peaks also show significant enrichment in peaks showing higher CoREST binding with TSA (left plots: CentriMo motif probability distributions for top five CoREST-enriched motifs). E values and motif best hits were determined by MEME-ChIP.

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findings suggest that chromatin and transcriptional repressors are upregulated following TSA injection, as cells may attempt to dampen hyperacetylation associated with HDAC inhibition (Figures 3D–3F), as observed in other systems (Halsall et al., 2015; Hull et al., 2016). This might explain the global increase of H3K27ac at 1 h following TSA injection, but decrease at 3 h, discussed above (Figure 3F; Table S5). Importantly, CoREST is a scaffold/binding partner for HDAC1 in a variety of histone deacetylating/demethylating corepressor complexes (Dallman et al., 2004); TSA injection may alter CoREST targeting or specificity due to its upregulation via hyperacetylation. Given the role of CoREST in neural differentiation in Drosophila melanogaster and other organisms (Abrajano et al., 2010; Dallman et al., 2004; Lakowski et al., 2006), and TSA induction of CoREST transcription (Figures 4A and 4B), we assessed the function of CoREST during reprogramming. We performed ChIP-seq from brains using a custom CoREST antibody (see Figure S4A for validation) at 1 h and 3 h following TSA or control injections of 5d Major workers, as well as in DMSO-injected Minors. TSA injection impacted binding of CoREST to many genes (Figures S4B–S4E; Table S5) including multiple genes upregulated 1 h after TSA injection (Figure 4C, left panels, upper and lower, S4B, and S4C). Notably, genes downregulated 3 h following TSA injection featured higher promoter CoREST signal at 1 h after TSA injection (Figures 4C, right panels, and S4C). These results indicate that CoREST binding increases in response to elevated acetylation after TSA injection (1 h and 3 h), and then CoREST binding represses target genes (3 h) that are not repressed in untreated samples. A transcription factor that recruits the corepressor CoREST to target loci in insects is the functional homolog of the repressor REST, called tramtrack (ttk) (Dallman et al., 2004). Tramtrack was moderately upregulated in reprogrammed Major workers at 3 h following TSA injection and showed moderate bias to Minor workers in caste-DEGs (Figure 3A, right; see below for additional findings about ttk). DNA sequence motifs enriched within CoREST peaks included binding sites for ttk defined from D. melanogaster (Figure 4E), as well as motifs for other transcriptional repressors tailless (tll), BEAF-32, and Enhancer of split [E(spl)] (Figure 4E; Table S6). These findings indicate that during reprogramming in Major workers, the key repressor genes CoREST and HDAC1 are

strongly upregulated, leading to repressed chromatin of normal Major-biased genes. As described above and below, CoREST/ HDAC1 may commission in reprogrammed Major workers the normal pathways that appear to specify Minor worker caste foraging behavior.

CoREST Mediates Reprogramming through Alteration of JH-Degrading Enzymes Because differential regulation of CoREST appeared to be a key factor mediating reprogramming, we investigated how an epigenetic switch—the induction of CoREST—translated into a behavioral switch in foraging. We reexamined caste-DEGs from untreated Minor and Major workers representing natural caste differential expression, focusing on genes involved in JH and ecdysone signaling (see above, Figure 2E). Multiple lines of evidence indicated that Major workers exhibit decreased JH signaling and higher ecdysone signaling. Major workers showed markedly higher gene expression of JHeh and JHe (Figure 5A, top row), two enzymes that degrade JH (Campbell et al., 1998; Cusson et al., 2013). Major workers also showed increased gene expression of prothoracicotropic hormone (PTTH), which regulates ecdysone production (Ishizaki and Suzuki, 1994), as well as higher ecdysone-inducible gene L2 (ImL2), which is induced by ecdysone (Garbe et al., 1993) (Figure 5A, top row). In contrast, several genes in the biosynthetic pathway for JH were more highly expressed in Minor workers (at d0 and exhibited a conserved trend toward higher expression at d5), mevalonate kinase (Figure 5A, bottom row), as well as genes with high similarity to methyl farnesoate epoxidase and JHacid O-methyltransferase (Jhamt). While the methyl farnesoate epoxidase- and Jhamt-like genes were not the reciprocal best hits to the D. melanogaster copies of these genes, they exhibited high homology (blast e-value <1e
80) to the core copies of these genes in D. melanogaster and other insects and thus may represent functional duplications. The Ari-1 gene, which dampens ecdysone signaling in D. melanogaster (Gradilla et al., 2011), was also more highly expressed in Minor workers (Figure 5A, bottom row left). These data indicate that JH and ecdysone signaling play a crucial role in programming the natural behavior between Major and Minor workers. Given this evidence for a role of JH and ecdysone in programming behavior and precedence for JH being linked to behavioral

Figure 5. CoREST Regulates JH-Degrading Pathway (A) JH-degrading and ecdysone-related genes are naturally significantly higher in Major workers (top row), while multiple members of the JH synthesis pathway are higher in Minor workers (bottom row; n R 6, each condition). Adjusted p values were determined by DESeq2. (B) TSA represses JH-degrading genes 3h after administration at d5 but not d10 in RNA-seq data (n R 4, each condition). Adjusted p values were determined by DESeq2. (C) JH shows higher levels in Minor worker heads versus Major workers at both d0 and d5 and increases from d0 to d5 in Minors by LC/MS. Treatment with TSA increases d5 Major JH levels to levels equivalent to those in Minor workers. Bars represent average ± SEM, and p values represent results of a Student’s t test. n R 5 for all samples. (D and E) Both (D) JHeh and (E) JHe show increased CoREST binding with TSA, matching binding levels seen in Minor workers. Tracks represent fold-enrichment of ChIP versus input control. (F) CoREST differences between Major and Minor workers show significant negative correlation (Spearman’s rank correlation) with RNA-seq ratio between untreated Major and Minor workers, lending support to the view that CoREST represses genes in a caste-specific manner in untreated workers. (G) Real-time qPCR of pupal and d0 adult brains. CoREST and ttk show Minor-biased differential expression in late pupal brain with a consistent (but nonsignificant) trend in d0 adult brain, while JHe and JBeh show Major-biased expression in d0 adult brain via real-time qPCR (n = 5, each condition). Bars represent average ± SEM and p values represent results of a Student’s t test.

Molecular Cell 77, 1–14, January 16, 2020 9

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polyethism in other social insects, we then investigated a role of CoREST and hormones in reprogramming behavior of Majors. Indeed, in the Major reprogramming-DEGs, there was striking reversal of JH-related gene expression: JH-degrading enzymes JHe and JHeh, normally elevated in Major workers (Figure 5A upper), were now markedly downregulated 3 h post-TSA injection (Figures 3A, right, and 5B). We confirmed that the changes in the expression of these genes related to changes in JH levels via liquid chromatography-mass spectrometry (LC/MS), finding that at both d0 and d5 JH is significantly higher in Minor workers than Major workers and significantly increases in Minor workers between d0 and d5 (Figure 5C). More importantly, treatment of Major workers with TSA leads to a significant increase in JH levels, reaching levels seen in Minor workers at the same time point (Figure 5C). JHe and JHeh also showed increased CoREST binding by ChIP-seq in TSA-treated Majors (Figures 5D and 5E); these CoREST binding levels approached CoREST binding levels detected in Minors, where the JHe and JHeh genes are naturally more lowly expressed (Figures 5A, upper, 5D, and 5E). Further, we observed a significant negative correlation between d5 Minor-Major expression bias and differential CoREST enrichment. That is, genes showing Major-bias in CoREST binding show higher expression in Minor RNA-seq (rho =
0.403, p value = 0.0083; Figure 5F), consistent with a role for CoREST in specifically repressing Minor genes in Major ants. Genes differentially CoREST-bound between Majors and Minors were enriched for terms related to development, differentiation, and neuronal function (Table S7), supporting a role for CoREST in mediating natural caste behavioral programming. While CoREST did not show significantly increased expression in Minors after eclosion (see Figure 2E), importantly, CoREST and ttk (the REST functional homolog that recruits CoREST to repressed genes) were both more highly expressed in Minor late pupal brains compared to Major (Figure 5G), consistent with a crucial role of CoREST at an early stage of Minor caste specification. This caste-specific contrast in expression is further underscored in that both CoREST and ttk are more highly expressed in Minors at the developmental time point preceding the observed increase in JHe and JHeh expression in Majors (Figure 5G). These results support the hypothesis that CoREST specifies the Minor worker caste and that TSA-reprogramming taps into this program in Major workers, within a restricted window of susceptibility, by inducing high level expression of CoREST. CoREST then binds to key genes naturally repressed in Minor workers, resulting in a Minor worker-like program of gene expression that drives the foraging behavior of the reprogrammed Majors. CoREST Knockdown Inhibits Reprogramming These findings indicated that CoREST may be central to caste behavioral specification, both in natural programming and in reprogramming. To assess the causative role of CoREST in mediating behavioral specification, we determined whether knockdown of CoREST by double-stranded RNA (dsRNA) injection into animal brains can inhibit reprogramming. CoREST RNAi (compared to control RNAi) was injected into the head capsule of Major ants at d4, and then TSA (or DMSO control) was injected 24 h later at d5, the peak time of reprogramming (scheme in Fig-

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ure 6A; validation of CoREST RNAi in Figures S5A and S5B). Strikingly, the reprogramming effects of TSA treatment were markedly blocked by CoREST RNAi (Figure 6B). To determine whether the block was due to effects on the predicted gene targets, real-time qPCR quantification showed that JHe and JHeh gene repression that occurred with TSA treatment was abrogated with coinjection of CoREST RNAi (Figure 6C). In addition, JHe and JHeh genes were not repressed in d10 workers injected with TSA (Figure 6C), consistent with the lack of reprogramming in d10 TSA-treated Major workers (Figure 1B); thus, at d10, inhibition of CoREST had no effect (Figure 6C). These results further support the hypothesis that CoREST represses key genes in a Minor caste-specific manner, and TSA treatment induces increased levels of CoREST that mediates Major worker behavioral reprogramming. We extended these data via genome-wide analysis, by performing RNA-seq on Majors co-injected with TSA and CoREST RNAi (compared to controls). Genes selectively upregulated by RNAi depletion of CoREST overlapped significantly with genes showing hyperacetylation by TSA injection in d5 Majors (Figure S5C). These findings suggest that CoREST is actively engaged after TSA injection to prevent or dampen the upregulation of these genes as discussed above. In addition, DEGs upon CoREST RNAi and TSA exhibited a significant overlap with natural caste-DEGs of Major and Minor workers (p = 6.08E
09; Figure S5D), and, similar to JHe and JHeh (Figures 5A and 6D), showed a consistent pattern of Major-biased expression in the natural caste-DEGs at d0 and d5, but not at d10 (Figure 6E). Remarkably, of the 52 caste-DEGs that showed differential expression with CoREST RNAi + TSA (relative to GFP RNAi + TSA; CoREST-sensitive genes), 46 of these (88%) showed Major-biased expression (repression in Minor workers) between untreated castes. Overall, these findings demonstrate that CoREST is a critical target of TSA-mediated Major worker reprogramming to Minorlike foraging. Given the strong correlations in gene expression between caste-DEGs and reprogramming-DEGs, the findings further indicate that CoREST may be a pivotal driver of natural Minor caste-specific behavioral specification. DISCUSSION Social insects of different worker castes display markedly distinct behavioral repertoires (Chapuisat and Keller, 2002; Ho¨lldobler and Wilson, 1990; Passera et al., 1996), in spite of a shared genome; thus, caste behavioral identity is mainly dictated by epigenetic programming mechanisms. Despite this, chromatin-based epigenetic mechanisms directly mediating behavioral caste have been largely unknown. Here, we identify an epigenetic pathway potentially central to caste-specific behavior in the ant C. floridanus. Our approach was to identify molecular pathways that both distinguish Minor workers, which forage for food, from Major workers, which provide nest defense, and in parallel identify molecular pathways that are altered upon reprogramming of Major workers to forage. This combination of approaches provided powerful insight into the epigenetic underpinning of caste specification that would otherwise be challenging to unveil.

Please cite this article in press as: Glastad et al., Epigenetic Regulator CoREST Controls Social Behavior in Ants, Molecular Cell (2019), https://doi.org/ 10.1016/j.molcel.2019.10.012

Figure 6. CoREST KD Abrogates JHe/ and JHeh Repression and Behavioral Reprogramming (A) Schematic of injection regime for HDACi following KD of CoREST. (B) Results of foraging assay comparing CoREST KD and control for DMSO- and TSA-treated samples, illustrating that CoREST KD largely abrogates TSA Major reprogramming (n = 4, each condition). (C) Repression of JH-degrading genes by TSA is abrogated with KD of CoREST at day 5 but not day 10 via real-time qPCR (n = 5, each condition). Bars in (B) and (C) represent average ± SEM and p values represent results of Student’s t test. (D) Separate RNA-seq samples illustrating effects of KD on key genes (n = 4, each condition). Adjusted p values as determined by DESeq2. (E) Log2 ratios between untreated Major and Minor brains for 0, 5, and 10 days for genes showing significant differential expression with CoREST KD, illustrating that CoREST regulates genes naturally biased to Major workers (repressed in Minor workers). p values from a Mann-Whitney U test.

Our results implicate the chromatin corepressor CoREST in a crucial role in the epigenetic switch between Minor and Major worker caste behavioral identity. Upon TSA administration, CoREST, along with HDAC1, is strongly upregulated and is targeted to regions of TSA-induced hyper-acetylation (Figure 4D), presumably as a compensatory mechanism responding to global increases in H3K27ac. CoREST is a highly conserved, important regulator of neurogenesis and differentiation in flies

and mammals, controlling a variety of neural signaling pathways such as Notch, Wnt, and SHH signaling (Abrajano et al., 2010; Meier et al., 2012). Despite its central importance in neural differentiation, studies have not directly linked CoREST to behavioral plasticity. Leveraging our reprogramming model, we show that CoREST is central to mediating TSA-induced foraging in Major workers, through repression of key regulators of JH(Figures 5B–5D). Further, this mechanism observed during

Molecular Cell 77, 1–14, January 16, 2020 11

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Figure 7. Model of CoREST-Mediated Regulation of Behavioral Division of Labor in C. floridanus (A and B) (A) Minor workers naturally have elevated JH due to repression of JHe and JHeh by CoREST, resulting in foraging, while (B) Majors have lower JH titers due to absence of CoREST binding and active JHe and JHeh, resulting in suppression of foraging. (C) Application of TSA results in CoREST upregulation, leading to binding and repression of JHe and JHeh, producing elevated levels of JH and subsequent foraging.

reprogramming is reflective of a natural mechanism differentiating Major and Minor workers. Indeed, (1) CoREST binds to JH-degrading genes JHe and JHeh in Minor workers, where these genes are considerably more lowly expressed (Figure 5); (2) CoREST shows a negative correlation with natural Major-Minor gene expression differences (Figure 5E); and (3) CoREST is more highly expressed in Minor worker pupal brains (Figure 5F). Crucially, depletion of CoREST by RNAi blocks Major worker reprogramming (Figure 6B); simultaneously, in the blocked reprogramming, depletion of CoREST leads to upregulation of many genes typically biased to Majors in untreated ants (Figures 6E and S5D). These findings further support a role for CoREST in repression of Major-biased genes in Minor workers to program natural foraging—and this same pathway is utilized in the TSA reprogramming regime (Figure 7). While CoREST was not differentially expressed in untreated worker caste DEGs, real-time qPCR of earlier time points revealed Minor-biased expression of CoREST in late pupal brains, along with ttk, the functional homolog of REST in insects (Dallman et al., 2004) (Figure 5F). Notably, this Minor-biased expression of CoREST directly precedes the most potent natural repression of JHe and JHeh in Minors (at d0) (Figures 5A and 5F). We conclude that in natural caste differentiation, CoREST likely acts during late pupal development to poise workers for adult behavioral differentiation, in particular by modulating downstream levels of the hormone JH. This was confirmed via LC/MS measurement of JH, revealing that untreated Minors have higher JH levels than Majors at both d0 and d5 (with an increase at d5), and, likewise, that TSA-injection increases JH in Majors to levels comparable to that seen in Minors (Figure 5C). JH has been linked to both reproductive caste (Barchuk et al., 2002; Robinson et al., 1991), as well as distinct behavioral states between workers in honeybees and ants (Fahrbach, 1997; Robinson and Vargo, 1997). Indeed, increased JH is correlated with age-associated transition to foraging in workers of at least

12 Molecular Cell 77, 1–14, January 16, 2020

one ant species (Dolezal et al., 2012), as well as in honeybees (Robinson and Vargo, 1997). Thus, detailed analysis of our reprogramming regime has uncovered a novel chromatin-based epigenetic mechanism that also appears to regulate natural behavioral plasticity. This occurs through modulation of an important hormone during a key developmental epoch. Our study also demonstrates the crucial importance of timing during early life in eusocial insects for determination of behavioral caste—an observation consistent with what is seen in diverse taxa across the animal kingdom (Kundakovic and Champagne, 2015; Kundakovic et al., 2013). One open question is the precise relationship between JH signaling and CoREST binding. Our data indicate that CoREST directly represses JH-degrading enzymes in the brain, however, given that endocrine systems frequently employ multiple feedback mechanisms and complex interactions, and given that the developmental decision between Major and Minor worker is made in the larval stage of development, it thus remains unclear whether the CoREST-represses-JH axis is downstream of another hormonal signal set up earlier in development. Future studies will be needed to fully elucidate the connection between CoREST and JH signaling and to determine whether the CoREST epigenetic pathway is sufficient for behavioral caste determination in C. floridanus and how widespread this mechanism is shared across eusocial hymenoptera and beyond. STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: d d d d

KEY RESOURCES TABLE LEAD CONTACT AND MATERIALS AVAILABILITY EXPERIMENTAL MODEL AND SUBJECT DETAILS METHODS DETAILS B Caste and Age Identification B Foraging Assay B RNA Isolation and Preparation B Native ChIP B X-ChIP B Custom Antibodies

Please cite this article in press as: Glastad et al., Epigenetic Regulator CoREST Controls Social Behavior in Ants, Molecular Cell (2019), https://doi.org/ 10.1016/j.molcel.2019.10.012

B

LC/MS Quantification of JHIII RNAi Injections B PEI: RNA Complexing B CoREST dsiRNA Sequences QUANTIFICATION AND STATISTICAL ANALYSIS B RNA-seq Analysis B ChIP-seq Analysis B Statistical Testing DATA AND CODE AVAILABILITY B

d

d

Bonasio, R., Li, Q., Lian, J., Mutti, N.S., Jin, L., Zhao, H., Zhang, P., Wen, P., Xiang, H., Ding, Y., et al. (2012). Genome-wide and caste-specific DNA methylomes of the ants Camponotus floridanus and Harpegnathos saltator. Curr. Biol. 22, 1755–1764. Brind’Amour, J., Liu, S., Hudson, M., Chen, C., Karimi, M.M., and Lorincz, M.C. (2015). An ultra-low-input native ChIP-seq protocol for genome-wide profiling of rare cell populations. Nat. Commun. 6, 6033. Campbell, P.M., Oakeshott, J.G., and Healy, M.J. (1998). Purification and kinetic characterisation of juvenile hormone esterase from Drosophila melanogaster. Insect Biochem. Mol. Biol. 28, 501–515.

SUPPLEMENTAL INFORMATION

Chapuisat, M., and Keller, L. (2002). Division of labour influences the rate of ageing in weaver ant workers. Proc. Biol. Sci. 269, 909–913.

Supplemental Information can be found online at https://doi.org/10.1016/j. molcel.2019.10.012.

Conesa, A., Go¨tz, S., Garcı´a-Go´mez, J.M., Terol, J., Talo´n, M., and Robles, M. (2005). Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21, 3674–3676.

ACKNOWLEDGMENTS We greatly thank Dr. Chris Petucci and the Penn Metabolomics Core for providing measurements of JH3 in ants. We thank Roberto Bonasio, Janko Gospocic, Brendan Hunt, and members of the Berger lab for helpful comments during manuscript preparation. This work was supported by NIH (training grant F32GM120933 to K.M.G.) and NIA (R01 5R01AG055570 to S.L.B.). AUTHOR CONTRIBUTIONS K.M.G., R.J.G., and S.L.B. designed the experiments. K.M.G., R.J.G., J.R., and L.J. collected the data. K.M.G. analyzed the data. K.M.G. and S.L.B. wrote the manuscript with input from all coauthors. DECLARATION OF INTERESTS

Cusson, M., Sen, S.E., and Shinoda, T. (2013). Juvenile Hormone Biosynthetic Enzymes as Targets for Insecticide Discovery. In Advanced Technologies for Managing Insect Pests, I. Ishaaya, S.R. Palli, and A.R. Horowitz, eds. (Springer Netherlands), pp. 31–55. Dallman, J.E., Allopenna, J., Bassett, A., Travers, A., and Mandel, G. (2004). A conserved role but different partners for the transcriptional corepressor CoREST in fly and mammalian nervous system formation. J. Neurosci. 24, 7186–7193. Dobin, A., Davis, C.A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., and Gingeras, T.R. (2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21. Dolezal, A.G., Brent, C.S., Ho¨lldobler, B., and Amdam, G.V. (2012). Worker division of labor and endocrine physiology are associated in the harvester ant, Pogonomyrmex californicus. J. Exp. Biol. 215, 454–460.

The authors declare no competing interests.

Fahrbach, S.E. (1997). Regulation of age polyethism in bees and wasps by juvenile hormone. In Advances in the Study of Behavior, P. Slater, C. Snowdon, J. Rosenblatt, and M. Milinski, eds. (Academic Press), pp. 285–316.

Received: June 27, 2019 Revised: September 13, 2019 Accepted: October 11, 2019 Published: November 12, 2019

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14 Molecular Cell 77, 1–14, January 16, 2020

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STAR+METHODS KEY RESOURCES TABLE

REAGENT or RESOURCE

SOURCE

IDENTIFIER

Rabbit anti-H3K27ac

Active Motif

Active Motif Cat# 39134, RRID: AB_2722569

Rabbit anti-CoRest (C. floridanus)

This paper

S.L. Berger - University of Pennsylvania, Cat# Berger_CF_CoRest_001, RRID:AB_2811209

Minor C. floridanus workers (d0, d5, d10)

Lab-reared from field collected colonies

N/A

Major C. floridanus workers (d0, d5, d10, TSA-treated, DMSO-treated, RNAi-injected+TSA/DMSO treated)

Lab-reared from field collected colonies

N/A

Antibodies

Biological Samples

Chemicals, Peptides, and Recombinant Proteins Trizol Reagent

Invitrogen

Cat #15596026

in vivo JET-PEI

Polypus

Cat #201-10G

Trichostatin A

Sigma-Aldrich

Cat #T1952

Agencourt AMPure XP

Beckman Coulter

Cat #A63880

Juvenile Hormone III-d3

Toronto Research Chemicals

Cat #E589402

Critical Commercial Assays NEBNext Ultra II Directional RNA Library Prep

NEB

Cat #E7706

NEBNext Ultra II DNA Library Prep

NEB

Cat #E7645

SYBR green master Mix

Roche

Cat #04 707 516 001

High capacity cDNA reverse transcription kit

Applied Biosystems

Cat #4368814

TURBO DNase (2 U/mL)

Invitrogen

Cat #AM2239

Dynabeads Protein A

Invitrogen

Cat #10002D

SRA

BioProject: PRJNA530332

Florida Keys, USA

N/A

IDT

N/A

IDT

N/A

GeneWiz

N/A

GeneWiz

N/A

Deposited Data Raw sequencing data Experimental Models: Organisms/Strains Camponotus floridanus Oligonucleotides CoRest_dsiRNA1 Sense: 50 rCrCrUrGrArUrGrArArUrGrGrArCrArGrU rUrGrArArGrATA 30 Antisense: 50 rUrArUrCrUrUrCrArArCrUrGrUrCrCr ArUrUrCrArUrCrArGrGrArA 30 CoRest_dsiRNA1259 Sense: 50 rCrUrGrGrGrUrCrUrGrGrArCrArArGrCrU rArCrUrArArATA 30 Antisense: 50 rUrArUrUrUrArGrUrArGrCrUrUrGrUrC rCrArGrArCrCrCrArGrUrG 30 CFLO_JHe Forward: GTGAATCCAGTAACAACACAAC Reverse: TTCGGCCATTCTACACCAG CFLO_JHeh Forward: TCGGTGCTTTTATTCCTCAAC Reverse: TCCAAAATATATGCTGCCAGTC (Continued on next page)

Molecular Cell 77, 1–14.e1–e6, January 16, 2020 e1

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Continued REAGENT or RESOURCE

SOURCE

IDENTIFIER

CFLO_ttk

GeneWiz

N/A

IDT

N/A

IDT

N/A

Trimmomatic

Bolger et al., 2014

N/A

Bowtie2 v2.2.6

Langmead and Salzberg, 2012

N/A

STAR

Dobin et al., 2013

N/A

Diffbind

Stark and Brown, 2011

N/A

DESeq2

Love et al., 2014

N/A

MACS2 version 2.1

Zhang et al., 2008

N/A

MEME

Bailey et al., 2006

N/A

GeneOverlap

Shen and Sinai, 2013

N/A

OrderedList

Yang et al., 2008

N/A

Blast2GO

Conesa et al., 2005

N/A

topGO

Alexa and Rahnenfuhrer, 2010

N/A

Forward: TTGTTGGCCATCCCGATAAG Reverse: TAAGCGCAGAACCGAGTAATG CFLO_CoRest_cs1 Forward: ATCGCATTCGGCAAATGTTAC Reverse: CGTCAATTTACGTGCTTGTCTATC CFLO_CoRest_cs2 Forward: CCTGTTAATGAACGTCGATTGG Reverse: TCCTAATGCCTGTTCTCCATTAT Software and Algorithms

LEAD CONTACT AND MATERIALS AVAILABILITY Further information and requests for resources should be directed to the Lead Contact, Shelley L. Berger (bergers@pennmedicine. upenn.edu). EXPERIMENTAL MODEL AND SUBJECT DETAILS Mature, queen-right colonies of C. floridanus were used in this study, collected as foundresses from the Florida Keys, USA, in 2007, 2011, and 2015. Colonies were maintained in a sealed environmental growth chamber at constant temperature (25 C) and humidity (50%) under a 12:12 light:dark cycle. Colonies were fed twice weekly with excess supplies of water, 20% sugar water (sucrose cane sugar), and Bhatkar-Whitcomb diet (Bhatkar and Whitcomb, 1970). METHODS DETAILS Caste and Age Identification Worker caste was determined as in Simola et al. (2016). Age was determined by marking gasters of callow workers % 1 day of age with enamel paint (Testors). One-day-old ants were identified by their location among brood in the nest, their general behavior, and their light cuticle coloration (compared to a reference panel of ants aged from pupation through 30 days). Foraging Assay Foraging assay was conducted as previously described using the Piggyback foraging assay (Simola et al., 2016). Briefly, cohorts of 10 age-matched Major workers were sampled from a single queen-right colony and immobilized on ice for 5 minutes. Immobilized ants were placed under a dissecting microscope, and a steel needle was used to make a small opening in the exoskeleton between the eyes along the sagittal plane. A borosilicate glass needle containing injection material was then placed superficially below the exoskeleton, and 1ml of either 50uM TSA or control was injected under low pressure using a microinjector (Eppendorf Femtojet). After injection, Majors were placed briefly in isolation to recover (> 1hr) before being combined with 10 untreated Minor worker nestmates in a piggyback nest box connected to a foraging arena containing 1mL of 20% sugar water, the sole source of food for the duration of the experiment. After injection, colonies were assigned a non-descriptive label and the arena was photographed every 6 min for

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10 days. Photographs were analyzed using a blinded scoring scheme as described in Simola et al. (2016). To avoid pseudoreplication, each treatment and age of injection assay each replicate was taken from a distinct colony background, across 7 distinct colonies (Table S8). For each age, at least two colony backgrounds were sampled for both DMSO and TSA injections, ensuring that at least some replicates of each age point and treatment were from the same colony background. RNA Isolation and Preparation For each sample type, at least two distinct colony backgrounds were used, in order to subsequently control for inter-colony variation. Individual ants were immobilized on ice for 5 minutes before brains were dissected, rinsed twice in chilled sterile Hank’s balanced salt solution media (HBSS), transferred to 1.5 mL microcentrifuge tubes containing 15 mL of chilled HBSS, and immediately snap-frozen in liquid nitrogen. Total RNA was purified from individual brains by trizol extraction, followed by DNase treatment using TURBO DNase (Invitrogen). DNase-treated RNA was subsequently purified using RNase-free Agencourt AMPure XP beads (Beckman Coulter; 2:1 volume of beads:sample). For RNA-seq, polyadenylated RNA was purified from total RNA using the NEBNext Poly(A) mRNA Magnetic Isolation Module (NEB E7490) with on-bead fragmentation as described (Zhong et al., 2011). cDNA libraries were prepared the same day using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB E7760). PCR cycle number was determined empirically using qPCR side reactions performed on 10% of the purified adaptor-ligated cDNA, but fell within 9-11 cycles for all samples, and all samples within a batch were amplified using the same number of PCR cycles. For RT-qPCR, cDNA was produced from total RNA using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Abundance of specific mRNA transcripts was estimated using Power SYBR Green PCR Master Mix (Life Technologies) on a Real Time qPCR machine (Applied Biosystems 7900HT). Relative transcript abundance was estimated using the DDCt method. Briefly, this method involved the use of the housekeeping gene, RPL32, as an internal normalization control for each sample. Following normalization to this gene, the differences in Ct values between normalized Ct amounts (DCt) were taken to obtain DDCt values, which were converted into fold-change values by the function 2^-DDCt = F.C. (Livak and Schmittgen, 2001). Native ChIP For each sample type, at least two distinct colony backgrounds were used, in order to subsequently control for inter-colony variation. For hPTMs, chromatin was isolated from single ant brains using native chromatin immunoprecipitation as in Brind’Amour et al. (2015) with the following modifications: single brains were homogenized by passing through a 31G diabetes syringe in 50uL of homogenization buffer (60mM KCl; 15mM NaCl; 50mM HEPES, pH 7.5; 0.1% Triton X-100) followed by centrifugation for 10 minutes at 500 g. Pellets were resuspended in 20uL EZ nuclei isolation lysis buffer (Sigma, NUC-101), and incubated on ice for 15 minutes. Samples were MNase digested for 10 minutes using 16U MNase (NEB M0247). Digestion was halted by the addition of 10mM EDTA, 0.1% Triton X-100, and 0.1% Na-Deoxycholate (final concentrations). For each set of C. floridanus ChIP experiments one Harpegnathos saltator brain was treated equivalently, and 2.5uL (5%–10%) of digested H. saltator brain lysate was added to each tube of digested C. floridanus lysate (ChIP-RX) (Orlando et al., 2014). To this, 200uL of immunoprecipitation buffer (20mM Tris-HCl pH 8.0; 2mM EDTA; 150mM NaCl; 0.1% Triton X-100) was added, followed by 1h rotation at 4C. 10% volume was then saved as input digestion control (25uL). Lysate was then pre-cleared using washed protein A beads in 100uL of immunoprecipitation buffer for 2h at 4C with rotation. Antibody was conjugated to protein A beads by adding 0.25 uL H3K27ac antibody (Active Motif 39133) to 20uL protein A beads per sample and rotated at 4C for > 2 hours. Optimal antibody concentration was determined using ChIP qPCR using two antibodies (abcam ab4729 and Active Motif 39133) at 3 concentrations and selecting the antibody and concentration with the highest fold enrichment of positive/negative regions while still providing sufficient material for the preparation of complex libraries. Lysate was added to pre-washed, antibody-conjugated protein A beads and incubated overnight (> 12h) at 4C with rotation in 0.5mL low-adhesion tubes. The following day, beads were washed as described (Orlando et al., 2014), and resuspended in 75uL elution buffer (10mM EDTA; 50mM Tris-HCl pH 8.0; 1% SDS) and incubated at 65C for 45 minutes with shaking (1100 RPM). Elution was repeated for a total elution volume of 150uL. DNA was purified via phenol:chloroform:isoamyl alcohol (25:24:1) followed by ethanol precipitation. Pelleted DNA was resuspended in 25uL TE, and subsequently re-purified using 2x Ampure XP beads. Libraries for sequencing were prepared using the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB E7645), as described by the manufacturer. For PCR amplification optimal number of PCR cycles was determined using a qPCR side-reaction using 10% of adaptor-ligated, size-selected DNA. 12 cycles of PCR were used for H3K27ac libraries and 8 cycles were used for Input controls. X-ChIP For CoREST X-ChIP experiments, 2 C. floridanus brains were resuspended in 300uL of homogenization buffer (60mM KCl; 15mM NaCl; 50mM HEPES, pH 7.5; 0.1% Triton X-100) with 1% Formaldehyde and incubated for 10 minutes at room temperature with rotation. After 5 minutes brains were homogenized by passing through a 31G diabetes syringe, followed by continued rotation for the remaining 5 minutes. Formaldehyde was quenched using 250mM glycine (final), and brains were again passed several times through the same 31G diabetes syringe. Homogenate was pelleted by centrifugation for 10 minutes at 500 g, followed by washing in homogenization buffer, and re-pelleting. Homogenate was then resuspended in 1mL lysis buffer (50mM HEPES-KOH, pH 7.5;

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140mM NaCl; 1mM EDTA; 0.5% Triton X-100; 0.1% Na-deoxycholate; 0.5% N-lauroylsarcosine), and sonicated with a Covaris S220 sonicator for 12 minutes (Power: 140, Duty Factor: 5.0, Cycles/burst: 200). Lysate was equalized according to DNA content (qubit flourometer), and 50uL was saved as input sonication control. Washed Ab-conjugated protein A dynabeads (5ug Ab per IP) were added to lysates and incubated overnight at 4C with rotation. The following day, Ab-bead complexes were washed 2x in low salt wash buffer (0.1% Na-deoxycholate; 0.1% SDS; 1% Triton X-100; 10mM Tris-HCl pH 8.0; 1mM EDTA; 140mM NaCl), 2x in high salt wash buffer (0.1% Na-deoxycholate; 0.1% SDS; 1% Triton X-100; 10mM Tris-HCl pH 8.0; 1mM EDTA; 360mM NaCl), 2x in LiCl wash buffer (0.5% Na-deoxycholate; 0.5% NP40; 10mM Tris-HCl pH 8.0; 1mM EDTA; 250mM LiCl), and 1x in TE, followed by 2x elution into 75uL elution buffer (50mM Tris-HCl pH 8.0; 10mM EDTA; 1% SDS) at 65C for 45 minutes with shaking (1100 RPM). DNA was purified via phenol:chloroform:isoamyl alcohol (25:24:1) followed by ethanol precipitation. Pelleted DNA was resuspended in 25uL TE, and subsequently re-purified using 2x Ampure XP beads. Libraries for sequencing were prepared using the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB E7645), as described by the manufacturer. For PCR amplification optimal number of PCR cycles was determined using a qPCR side-reaction using 10% of adaptor-ligated, size-selected DNA. 12 cycles of PCR were used for CoREST libraries and 8 cycles were used for Input controls. Custom Antibodies Briefly, a GST-tagged antigen was produced corresponding to the full length of CoREST and provided for rabbit injection by Cocalico biologics. A MBP-tagged version of the same antigen was then used for affinity purification of polyclonal antibodies from resulting antisera. Two rabbits were used and the best-performing purified Ab (validated via ChIP western blot) was used for all experiments. LC/MS Quantification of JHIII Individual ant head samples were pooled (n = 10 heads/sample for Major workers and n = 20-25 heads/sample for Minor workers). Each pooled sample was homogenized in 500 mL of 50:50 methanol/isooctane (Westerlund and Hoffmann, 2004) in a 2 mL tube with ceramic beads for 2 minutes at 7200 rpm using a Precellys homogenizer at 4 C with a Cryolys cooling system (Bertin Technologies). The resulting homogenates were spiked with 10 mL of internal standard (JH3-d3), vortexed, and centrifuged at 14,000 rpm at 10 C for 10 minutes. The supernatants were transferred to a 96-well, 3 kDa cut-off filter plate and centrifuged into a 1 mL 96-well collection plate at 2000 rpm for 45 minutes at 4 C. The clean solvent extracts in the collection plate were dried down at 45 C under nitrogen. The samples were reconstituted in 100 mL of 50:50 acetonitrile/water, vortexed, and injected onto the LC/MS for analysis. A JH3 standard (Sigma-Aldrich) and JH3-d3 internal standard (Toronto Research Chemicals) were dissolved in acetonitrile at 1 mg/mL, and used to create a standard curve through serial dilution, followed by extraction using the same method as for biological samples. JH3 extracts from ant heads were separated and quantitated on an Agilent 1290 HPLC/6490B triple quadrupole mass spectrometer. A 5 minute linear gradient from 95% A (0.1% formic acid in water)/5% B (acetonitrile with 0.1% formic acid) to 5% A/95% B at 0.4 mL/min on a Waters Acquity BEH C18 column (2.1 3 50 mm, 1.7 mm) at 30 C was used to chromatograph JH3. The column was equilibrated back to gradient starting conditions at 8.75 min. JH3 was ionized by electrospray ionization in positive ion mode with an ESI voltage of 3500 V, nozzle voltage of 500 V, gas flow of 14 L/min, nebulizer pressure of 45 psi, gas temperature of 250 C, sheath gas temperature of 235 C, and sheath gas flow of 12 L/min. The mass spectrometer was run in multiple reaction monitoring mode by monitoring the transitions for JH3 (m/z 267.2 to 235.2) and JH3-d3 (m/z 270.2 to 235.2) at collision energies of 4 V and a dwell time of 50 ms. Confirmatory MRM transitions for JH3 were monitored at m/z 267.2 to 147.1, m/z 267.2 to 189.1, and m/z 267.2 to 217.1. The JH3 signals in ant extracts were quantitated using linear calibration curves of standards with R2 = 0.99 or greater with a 1/x2 weighting. All data given in Table S9. RNAi Injections We tested individual dsiRNA complexes (IDT) targeting CoREST and determined that efficient KD was achieved 24h after injection (Figure S5C). Therefore, to test for the effects of CoREST KD on TSA administration in day 5 Majors, we injected cohorts of agematched Majors with either CoREST or GFP-targeting dsiRNAs at day 4, applied treatment-specific markings, and returned them to their maternal nests overnight. The following day, injected ants were recovered from their nests and injected with either TSA or DMSO as previously described. Prior to injection, CoREST and GFP-targeting dsiRNA’s were complexed with Polyethelenimine (in vivo JET-PEI, Polyplus) transfection reagent to improve delivery of dsiRNA to the cytoplasm. PEI: RNA Complexing 10 mL of 20uM stock dsiRNA was mixed with 10uL 10% glucose to yield a 5% glucose+dsiRNA solution . In a separate tube, 1.6 ml of in vivo-jetPEI (N/P ratio = 6) was mixed with 10uL 10% glucose and 8.4uL sterile water. The 20uL in vivo jetPEI and 20uL dsiRNA were combined in a new tube and incubated for 15 minutes at room temperature prior to injection. DsiRNA:PEI complexes were made fresh for each batch of injections and never stored. 1uL of dsiRNA:PEI solution was injected per ant, and ants were then paint-marked and returned to the nest.

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CoREST dsiRNA Sequences CoREST dsiRNA1 Sense: 50 rCrCrUrGrArUrGrArArUrGrGrArCrArGrUrUrGrArArGrATA 30 Antisense: 50 rUrArUrCrUrUrCrArArCrUrGrUrCrCrArUrUrCrArUrCrArGrGrArA 30 CoREST Dsi1259 Sense: 50 rCrUrGrGrGrUrCrUrGrGrArCrArArGrCrUrArCrUrArArATA 30 Antisense: 50 rUrArUrUrUrArGrUrArGrCrUrUrGrUrCrCrArGrArCrCrCrArGrUrG 30 QUANTIFICATION AND STATISTICAL ANALYSIS RNA-seq Analysis Reads were demultiplexed using bcl2fastq2 (Illumina) with the options ‘‘–mask-short-adapter-reads 20–minimum-trimmedread-length 20–no-lane-splitting–barcode-mismatches 0.’’ Reads were trimmed using TRIMMOMATIC (Bolger et al., 2014) with the options ‘‘ILLUMINACLIP:[adapter.fa]:2:30:10 LEADING:5 TRAILING:5 SLIDINGWINDOW:4:15 MINLEN:18,’’ and aligned to the C. floridanus v7.5 assembly (Shields et al., 2018) using STAR (Dobin et al., 2013). STAR alignments were performed in two passes, with the first using the options ‘‘–outFilterType BySJout–outFilterMultimapNmax 20–alignSJoverhangMin 7–alignSJDBoverhangMin 1–outFilterMismatchNmax 999–outFilterMismatchNoverLmax 0.07–alignIntronMin 20–alignIntronMax 100000–alignMatesGapMax 250000,’’ and the second using the options ‘‘–outFilterType BySJout–outFilterMultimapNmax 20–alignSJoverhangMin 7–alignSJDBoverhangMin 1–outFilterMismatchNmax 999–outFilterMismatchNoverLmax 0.04–alignIntronMin 20–alignIntronMax 100000–alignMatesGapMax 250000–sjdbFileChrStartEnd [SJ_files]’’ where ‘‘[SJ_files]’’ corresponds to the splice junctions produced from all first pass runs. Differential gene expression tests were performed with DESeq2 (Love et al., 2014). For all pairwise comparisons (untreated caste comparisons per day, TSA versus Control comparisons for each time point), the Wald negative binomial test (test = ’’Wald’’) was used for determining DEGs, using colony background as a blocking factor. For the overall untreated caste comparison (combined model approach) a likelihood ratio test was used (test = ’’LRT’’) comparing the full model: colony+day+caste+caste*day to the reduced model: colony+day. Unless otherwise stated, an adjusted p value cutoff of 0.1 was used in differentiating differentially expressed from non-differing genes in order to maximize the sensitivity of our RNA-seq results. For RNA-seq libraries at least 10M mapped reads were sequenced for each replicate, with a mean of 21M reads per library, and no sample type possessed less than 4 replicates. ChIP-seq Analysis For ChIP-seq libraries, modEncode standards were followed, with at least 2 replicates performed for each assay (3x for CoREST X-ChIP-seq), and at least 10M mapped reads required for each library (15M for Input control libraries). Reads were demultiplexed using bcl2fastq2 (Illumina) with the options ‘‘–mask-short-adapter-reads 20–minimum-trimmed-read-length 20–no-lane-splitting– barcode-mismatches 0.’’ Reads were trimmed using TRIMMOMATIC (Bolger et al., 2014) with the options ‘‘ILLUMINACLIP: [adapter.fa]:2:30:10 LEADING:5 TRAILING:5 SLIDINGWINDOW:4:15 MINLEN:18,’’ and aligned to the C. floridanus v7.5 assembly (Shields et al., 2018) using bowtie2 (v2.2.6) (Langmead and Salzberg, 2012) with the option ‘‘–sensitive-local.’’ ChIP enrichment peaks were called using macs2 (v2.1.1.20160309) (Zhang et al., 2008). Differential ChIP peaks were called using DiffBind (Stark and Brown, 2011) on the replicated ChIP samples. For hPTM samples, DiffBind was used with the option bScaleControl = TRUE for dba.count(), bSubControl = TRUE and bFullLibrarySize = TRUE for dba.analyze(). For DiffBind tests condition was used as the test category and colony background was used as a blocking factor. For ChIP-seq libraries IDR analysis was performed to ensure consistency between replicates, and that no set of replicates exhibited excessive or insufficient reproducible binding within a sample type or assay. For ChIP-RX scaling factor estimates (Native ChIP) reads were aligned to a composite genome composed of both C. floridanus (v7.5) and H. saltator (v8.5). For a given sample, the scaling factor was estimated as the proportion of exogenous-mapping reads in IP) adjusted by the proportion of exogenous-mapping reads in Input. For our analyses we chose not to incorporate the scaling factor, due to the fact that 1h TSA-treated samples showed extreme increases in H3K27ac (Figure 3F) that resulted in the majority of H3K27ac peaks being hyper-acetylated with TSA. While this is likely the case, application of a global scaling factor of such magnitude is a coarse approach that is difficult to incorporate in an informed way during differential testing, and we found that the majority of results were quite similar with and without the scaling factor (albiet with different mean fold changes between TSA and control for 1h samples; Figure S3).Assignment of gene orthology and functional terms Genes (NCBI Camponotus floridanus Annotation Release 102; assembly (Shields et al., 2018)) were assigned orthology using the reciprocal best hit method (Moreno-Hagelsieb and Latimer, 2008) to both D. melanogaster (r6.16) and H. sapiens (GRCh38) protein coding genes. Gene ontology function was assigned to genes using the blast2go tool (Conesa et al., 2005) using the nr database, as well as interpro domain predictions. Gene Ontology enrichment tests were performed with the R package topGO (Alexa and Rahnenfuhrer, 2010), utilizing the fishers elim method.

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Statistical Testing For gene overlap calculations (such as in Figures S2A and S2B) the GeneOverlap (Shen and Sinai, 2013) R package was used. For continues value gene overlaps (such as in Figure S2G) the R package OrderedList was used (Yang et al., 2008). De novo motif discovery, enrichment calculation, and association with differentially bound regions was performed with the MEME software suite (Bailey et al., 2006). All other statistical tests given in figures and tables were performed in R unless otherwise stated. DATA AND CODE AVAILABILITY All sequencing data related to this project has been deposited in the NCBI Sequencing Read Archive, accession: BioProject:PRJNA530332.

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