Gα_q controls organ size and developmental timing in Drosophila

The G protein alpha subunit, Gαq, transduces extracellular signals from G-protein-coupled receptors (GPCRs) into the cell, playing essential roles in developmental processes such as organ size control, wound healing, and disease. Hyperactivating mutations in the Gαq are associated with Sturge-Weber syndrome and uveal melanoma, and thus, it serves as an important candidate drug target. However, the downstream mechanisms of Gαq signaling remain poorly defined, creating a bottleneck for designing more effective and targeted therapeutics. Here, we used Drosophila melanogaster wing discs to investigate the cellular and transcriptional consequences of Gαq dysregulation in a model epithelial system. We found that overexpression of Gαq in the wing discs reduces adult wing size and induces systemic developmental delay. Additional notable phenotypes include decreased apoptosis and reduced proliferation. Transcriptomic profiling reveals that the JAK/STAT signaling pathway is specifically upregulated in Gαq overexpression, but not in Gαq knockdown. Furthermore, perturbing Gαq impacts the cytoskeleton, confirmed by altered localization of phosphorylated Myosin II. Gαq overexpression in the wing disc upregulates stress-response pathways and triggers secretion of Drosophila insulin-like peptide 8 (Dilp8), a hormone that coordinates growth and developmental timing. Functional experiments confirmed that IP₃ receptor (IP₃R)-dependent calcium signaling mediates this delay and that the delay is rescued by the knockdown of Dilp8. In sum, Gαq acts as a critical regulator of epithelial growth and developmental timing via Ca²⁺-dependent Dilp8 signaling. These findings establish mechanistic links between GPCR signaling, tissue regeneration, and systemic developmental coordination, with broader implications for understanding Gαq-related pathologies in humans.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12964-025-02449-9.

Plain language summary

This study explores how a protein called Gαq helps organs grow to the optimal size and shape during development, using fruit flies as a model. Gαq is part of a signaling system that controls how cells communicate and respond to their environment.

We found that Gαq helps produce waves of calcium activity in developing wing tissue. When we altered Gαq levels during larval development, the adult wings became smaller. This was due to fewer cells dividing and, unexpectedly, fewer cells dying. These effects may relate to how Gαq functions in human diseases like cancer, though more research is needed.

Gαq also slowed overall development. This delay was linked to the release of a signal called Dilp8, which tells the body to slow down growth so tissues can catch up. We showed that blocking Dilp8, or interfering with calcium signaling, could restore normal development speed. This means Gαq plays a role in managing developmental timing through a hormone system that coordinates growth across the body.

Further genetic analysis revealed that Gαq activates several important pathways involved in immunity, growth, and cell structure. It also affects how cells connect physically and multiply, which are crucial for shaping tissues.

In summary, Gαq is a key regulator of growth and timing during development. By influencing both local cell behavior and whole-body signals, it ensures that organs form correctly and in sync with the rest of the organism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12964-025-02449-9.

Background

How organs achieve their final size and shape during development remains an open and fundamental question in developmental biology [1–4]. Organ size control relies on both intrinsic intra-tissue signals and extrinsic hormonal growth regulators [5]. The information from all these levels of communication is received and processed by receptors on the cell surface, such as G-protein coupled receptors (GPCRs), which constitute the largest family of transmembrane receptors, having roughly ~ 800 members in humans [6]. Activation of GPCRs triggers conformational changes that promote the generation of secondary messengers. Through this mechanism, GPCRs convert a diverse range of external stimuli into internal signals, ultimately modulating diverse physiological processes such as growth and proliferation [7].

G proteins are heterotrimeric proteins that are coupled to GPCRs within the cell (Fig. 1). They are ubiquitous in plants, mammals, and insects [8]. They transduce signals from extracellular cues to generate a range of second messengers such as IP₃, DAG, and Ca²⁺, thus providing the framework for a broad range of cellular responses [9]. G-proteins are composed of α, β, and γ subunits that are associated with GPCRs and classified according to the structure and function of their α subunit into four families: Gα_i, Gα_s, Gα_12/13, and Gα_q (referred further as Gαq) [10]. Upon binding of an agonist, the receptor alters its conformation, leading to the exchange of guanosine diphosphate (GDP) with guanosine triphosphate (GTP) [11]. Once GTP-binds Gα, it dissociates from the heterotrimeric complex and activates Phospholipase C β (PLC β) [12]. The Gβγ subunits also play a role in PLCβ activation, as well as in regulating protein kinases and small G-proteins [13]. Subsequently, PLC β, the main effector of Gαq, promotes the hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP₂) into diacylglycerol (DAG) and inositol trisphosphate (IP₃) [14]. DAG further activates protein kinase C (PKC) [15], whereas IP₃ stimulates the release of Ca²⁺ from the endoplasmic reticulum (ER) by binding to its receptor (IP₃R) [13, 14, 16–18]. Following this release, Ca²⁺ binds to a range of proteins to generate diverse cellular responses (Fig. 1).

Fig. 1.

GPCR signaling through the Gαq/PLCβ pathway. Upon agonist binding, the GPCR (G-protein coupled receptors) undergoes a conformational change that facilitates the exchange of guanosine diphosphate (GDP) with guanosine triphosphate (GTP) on the Gα subunit. Activated Gαq dissociates from the Gβγ complex and stimulates Phospholipase C β (PLCβ). Gβγ subunits can also contribute to PLCβ activation. PLCβ hydrolyzes phosphatidylinositol 4,5-bisphosphate (PIP₂) into diacylglycerol (DAG) and inositol trisphosphate (IP₃). DAG activates protein kinase C (PKC), while IP₃ binds its receptor (IP₃R) on the endoplasmic reticulum, triggering Ca²⁺ release. The resulting increase in intracellular Ca²⁺ leads to the activation of downstream effectors that mediate diverse cellular responses. The rise in Ca²⁺ is then recovered by SERCA (sarcoplasmic/endoplasmic reticulum Ca²⁺-ATPase), which sequesters Ca²⁺ back into the ER. Created in BioRender. Zartman, J. (2025)

Gαq regulates a diverse set of biological processes. The wounding of epithelial tissues generates multicellular calcium (Ca²⁺) waves [19], which requires Gαq [20]. Ca²⁺ serves as a key regulator of growth, glucose transport, actin cytoskeleton regulation, cardiac physiology, and development [20–23]. For example, mutant mice lacking both Gαq and Gα₁₁ die during embryonic development, and at least two functional alleles (either of Gαq, Gα11, or one of each) are required for extrauterine life for mice [24]. Genetic depletion studies [22, 25] highlight that Gαq is essential for normal development and can act as a growth regulator. As a second example, Gαq activity is required for insulin-induced glucose transport in adipocytes [23]. Further, the Adipokinetic Receptor (AkhR) functions through the Gαq/Gγ1/Plc21C signaling module to regulate body fat storage in adult Drosophila [21]. Mutations in the gene that encodes Gαq in humans (GNAQ) are associated with upregulated Gαq function and have been shown to induce a port wine birthmark condition and Sturge-Weber syndrome—a congenital neurological and skin disorder. With age, accumulated somatic hotspot mutations in GNAQ can also cause uveal melanoma in the eyes [26–28]. Gαq is coupled to GPCRs of various neurotransmitters such as dopamine and acetylcholine, and hormones such as bradykinin and angiotensin [13], among others. Also, GPCRs regulate metamorphosis in Drosophila by transmitting ecdysone signaling and controlling hormone production through the nuclear hormone pathway [29–33]. Additionally, Gαq regulates gut innate immunity through the modulation of DUOX [34]. Overall, these studies underscore the complexity of the diverse biological functions that Gαq performs across a broad range of biological contexts, and in many cases, the downstream pathways remain to be elucidated.

Previously, we reported that perturbing Gαq expression regulates the size of Drosophila wings [35]. Further, the overexpression of wild-type Gαq is correlated with the occurrence of intercellular Ca²⁺ waves (ICWs) in ex vivo wing disc cultures [35]. Gαq is also required for wound-induced Ca²⁺ waves in the pupal notum [19, 36]. However, the downstream effectors through which Gαq transduces the growth regulatory signals are unknown. This can be primarily attributed to the wide range of second messengers it activates. For example, the downstream pathways through which Gαq-mediated Ca²⁺ signaling regulates organ size and shape remain unknown.

To address this question in a genetically accessible system, we used the Drosophila wing disc to identify the key genes acting downstream of partial loss- and gain-of-function Gαq perturbations, utilizing tissue-specific gene expression driven by the UAS-Gal4 system [37, 38]. Drosophila melanogaster serves as a key model organism due to an expansive genetic toolkit enabling the generation of organ- or cell-specific mutants. Its short lifecycle also makes it well-suited for high-throughput experimentation. Additionally, the imaginal wing disc provides a powerful platform to decode epithelial morphogenesis and signal transduction pathways, including Ca²⁺ signaling [2, 39–42]. The wing disc has been shown to be invaluable for phenotypic screening in early preclinical studies [43–45], and multiple signaling pathways, such as the Bone Morphogenetic Protein BMP (Drosophila Decapentaplegic/Dpp), Wnt (Drosophila Wg), and Hedgehog (Hh), which coordinate the patterning of epithelial cells [46–48]. Altogether, these studies have established different functional roles assumed by Gαq in Drosophila and the utility of the fly system for investigating core components of the calcium signaling toolkit.

Here, we used genetic perturbations, RNA-seq, phenotypic functional analysis, and immunohistochemistry to identify downstream pathways of Gαq. We discovered that Dilp8 is the downstream effector of Gαq signaling that causes developmental delay. This finding suggests that Gαq plays organ-specific roles in communication between peripheral tissues and the brain. Thus, Gαq contributes to the regulation of multiple processes and pathways involved in development, wound healing, and inter-organ communication.

Methods

Fly stocks

Drosophila stocks (Table 1) were grown on standard laboratory cornmeal food, “Fly food B” Bloomington recipe [49]. All crosses were set up at 25 °C, unless otherwise noted.

Table 1.

Fly stocks

Stock genotype	Source	Abbreviation
y[1] w[*]; P{w[+ mW.hs] = GawB}C-765	Bloomington Drosophila Stock Center (BDSC):36523	C765-Gal4 or C765-G4
nubbin-GAL4, UAS-Dcr-2	BDSC:25754	nubbin-Gal4 or nub-Gal4
y w hsflp; apterous-Gal4/CyO; UAS-GFP	Basler lab	ap-G4 or ap-Gal4
w[*]; P{w[+ mC] = UAS-Galphaq.R}2	BDSC:30734	UAS-Gαq or GαqOE (Gαq Over Expression)
P{w[+ mC] = UAS-Galphaq.Q203L}F58a, w[*]/FM7i, P{w[+ mC] = ActGFP}JMR3	BDSC:30743	GαqOE (BL#:30743)
w; UAS-Gαq, C765-Gal4/SM5-TM6B, Tb	Generated in this study	C765 > Gαq
nubbin-GAL4, UAS-GCaMP6f/CyO	Zartman Lab	Nub-Gal4 > GCAMP6f
y[1] v[1]; P{y[+ t7.7] v[+ t1.8] = TRiP.JF01100}attP2	BDSC:31540	RyR RNAi
y[1] v[1]; P{y[+ t7.7] v[+ t1.8] = TRiP.JF01957}attP2	BDSC:25937	IP 3 R RNAi
y[1] v[1]; P{y[+ t7.7] v[+ t1.8] = TRiP.JF02390}attP2	BDSC:36775	GαqRNAi or GαqKD (Gαq Knock Down)
y[1] v[1]; P{y[+ t7.7] v[+ t1.8] = TRiP.HMS06016}attP40	BDSC:80436	Dilp8 RNAi

Immunohistochemistry and imaging of fixed samples

Imaginal wing discs were dissected in Phosphate Buffered Saline (PBS) (#P5368, Millipore-Sigma). Following dissection, discs were fixed in 4% paraformaldehyde (PFA) for 20 min at room temperature, followed by three 10-minute washes in PBT (0.03% Triton X-100 (#T9284, Sigma-Aldrich) in PBS). Next, discs were blocked with 5% Normal Goat Serum (NGS) (#NC9660079; Jackson Immuno Research Laboratories, West Grove, PA) for 30 min, followed by overnight incubation with primary antibodies at 4 °C (Table 2).

Table 2.

Antibodies for immunohistochemistry

Antibody	Catalog number	Company
PH3	9701 S	Cell Signaling
DCP-1	9578 S	Cell Signaling
PMyoII	3671	Cell signaling
Gq/11α	06–709	Millipore corporation
Dilp8	n/a	Gift from Dr. Léopold lab @ Institut Curie, France

Incubation with the primary antibodies was followed by three 15-minute washes with PBT and subsequent incubation with Alexa Fluor-conjugated secondary antibodies (1:500 in 5%NGS) and DAPI (# D9542; Millipore Sigma, 1:1000) for 2–3 h at room temperature in the dark. Next, wing discs were washed with PBT overnight at 4 °C, followed by two 15-minute washes at room temperature. Discs were next mounted in Vectashield (# H-1000, Vector Laboratories) on a 24 × 66 mm coverslip with a tape frame, providing a gap to prevent wing discs from being squished by the 22 × 22 coverslip placed on top. Sides were then sealed with clear nail polish. Images of mounted wing discs were obtained using a Nikon Eclipse Ti confocal microscope with a Yokogawa spinning disk (Tokyo, Japan) and Leica STELLARIS 8 DIVE.

Quantifications of pMyoII antibody staining

Optical reslices that are parallel to the dorsal–ventral (DV) boundary were taken within the dorsal compartment of the wing disc, positioned 10 μm away from the boundary. Immunostained discs labeled with anti-pMyoII were used to extract intensity profiles across the apical, basal, and lateral surfaces. Profiles were obtained in FIJI (ImageJ), background-subtracted, and normalized to background signal to yield signal-to-noise ratios. Measurements were collected from multiple discs, with the DV section length normalized to curve length to allow comparison across samples. Individual profiles were averaged and mean ± standard deviation was plotted to capture variation. Data processing and visualization were performed in Python (3.11.7) with numpy (1.26.4), pandas (2.1.4), and matplotlib (3.8.0).

For quantitative comparison (Fig. 7), apical and basal surface signals were measured from discs expressing Nub-G4 > UAS-RyR^RNAi (control, also used as a control in several of our previous studies due to lack of expression in the wing disc, n = 5) and Nub-G4 > UAS-Gαq (mutant, n = 5). The signal-to-noise ratio was calculated as (F − Fb)/Fb. Profiles were averaged, and mean values are shown as solid lines with shaded regions indicating standard deviation. The x-axis (x AP/l AP) represents position along the apical or basal surface normalized by total length. The domain was divided into three regions, and t-tests were used to compare average expression between control and mutant samples in each region.

Fig. 7.

Gαq induces changes in wing disc Phospho-Myosin II localization. PMyoII antibody staining of nub-Gal4 > UAS-RyR^RNAi (control where RyR is not significantly expressed in wing discs) (i) and nub-Gal4 > UAS-Gαq (ii) wing discs. Cross sections of the wing disc pouch region. Wing discs were dissected from the same physiological age wandering Larvae L3 for each condition. PMyoII – Phospho-Myosin Light Chain 2 (Ser19) antibody. (i) nub-Gal4, UAS-Dicer > UAS-RyR^RNAi (BDSC# 31540), (Control); (ii) nub-Gal4, UAS-Dicer > UAS-Gαq (BDSC# 30743). Sample size n = 5 for each cross. (iii) Average intensity (line) and standard deviation (shadowed area), plotted for PMyoII apical and basal localizations. Y axis: F (Fluorescence), Fb (background Fluorescence). X-axis: Position along the Anterior-Posterior (AP) axis normalized by the length of the AP axis. T-test was performed, and P-values are shown as ****p-value < 0.0001, **p-value < 0.003, ns = not significant

PH3 and DCP1 antibody staining image analysis

The wing imaginal discs images were processed using Image J. Quantification included manually counting PH3 positive cells and measuring pouch dorsal and pouch ventral compartment areas. To measure DCP1 positive cells, we removed the background by setting a threshold of ~ 1%. We quantified each DCP1 positive area using the analyze particle tool and manually measured the pouch dorsal and the pouch ventral compartments. Finally, we calculated the PH3 and DCP1 coefficients, dividing by the area of the respective compartment.

In vivo imaging setup

Third instar wandering larvae were collected and rinsed in deionized water prior to imaging. Larvae were dried and adhered to a coverslip with Scotch tape. The larvae were attached with their spiracles facing the coverslip to align the wing discs toward the microscope. An EVOS FL Auto microscope was used to image the larvae at a magnification of 20x for 20 min. The images were taken every 15 s.

RNA extraction

RNA was isolated using RNeasy Mini Kit (#74104; QIAGEN), using a standard procedure with DNase on column digestion (RNase-free DNase set, #79254, QIAGEN). RNA was eluted in RNase DNase-free water provided by the RNeasy Mini Kit. Samples from multiple days of dissection were stored at −80 °C and pooled such that each biological replica would have around 20–30 wing discs. Three biological replicas were used for each condition. To assess the RNA quantity and quality, we performed QC using Qubit and Agilent Bioanalyzer and pooled samples from multiple days of RNA isolation to achieve at least 50ng or higher of RNA per sample.

RNA-seq experimental design

The Ryanodine Receptor (RyR) is a Ca²⁺ channel in the endoplasmic reticulum (ER) of excitable cells [50]. It functions like IP₃R, allowing Ca²⁺ release from ER into the cytoplasm upon activation. RyR is not expressed in epithelial tissues and wing imaginal disc [51]. The following three groups were included: C765-Gal4 >UAS-RyR^RNAi, which serves as a control with Gal4 expression and RNAi against mRNA not expressed in wing discs; C765-Gal4 >UAS-Gαq^RNAi; and C765-Gal4 >UAS-Gαq. Three biological replicas (b.r.) with ~ 30 wing discs each were collected for RNA-seq.

RNA sequencing (RNA-seq)

RNA-seq libraries were prepared and sequenced across one lane of an Illumina NextSeq v2.5 (Mid Output 150 cycle) flow cell. Each library was prepared using the NEBNext Ultra II Directional RNA Library Prep kit and the NEB mRNA Magnetic Isolation Module. We performed QC and quantitation on the library pool using the Qubit dsDNA Agilent Bioanalyzer DNA. For all libraries Mid Output (150 cycle) sequencing, High Sensitivity Chip, and Kapa Illumina Library Quantification qPCR assays were used. The sequencing form was paired-end 75bp. Base calling was done by Illumina Real Time Analysis (RTA) v2 software.

Processing of RNA-seq data

Raw sequences were trimmed of adapters with Trimmomatic version 0.39 [52] and assessed for quality with FastQC v 0.11.8 [53]. Trimmed sequences were aligned to the Drosophila genome, and Ensembl built Drosophila melanogaster.BDGP6.32.104.gtf, Berkeley Drosophila Genome Project (BDGP, Release 6, Aug. 2014), using Dmel_Release_6.01 version annotations and HISAT2 version 2.1.0 [54]. SAMtools version 1.9 was used to sort the corresponding alignments [55]. Read counts were generated with HTSeq-count version 0.11.2 [56]. Subsequent statistics were completed in R (R Core Team, 2014). Using the Ensembl version of BioMart, Gene names, and GO terms were identified [57].

Analysis of RNA-seq data

Using DESeq2 v1.36.0 [58], we identified differentially expressed genes (DEGs) from the read counts. The genes with significant differential expression were identified based on the following criteria: log2FC >0.6 or log2FC < − 0.6 and FDR < 0.05, (FC: Fold Change, FDR: False Discovery Rate). First, we confirmed Gal4 expression in the libraries. Next, we performed the comparison between the control and the two Gαq perturbations and confirmed Gαq upregulation/downregulation in corresponding datasets. For Gαq overexpression confirmation please see SI for more details, as it required checking raw reads. Next, DEGs were subjected to Gene Ontology (GO) [59] and pathway enrichment analysis based on FlyBase [60] for determining key biological functions and pathways, which are divided into the upregulated group and downregulated group by log2FC >0.6 and log2FC<−0.6, respectively. The results of GO and Pathway Enrichment Analysis of the two groups were separately analyzed by using the clusterProfiler package (v4.2.2) in R [61] and PANGEA [62, 63] where terms with p-values < 0.05 cutoff were significantly enriched.

Quantification of adult wings and statistics

Using ImageJ and MAPPER [64], we measured the total area of the wings. The wing margin was traced by following veins L1 and L5, and the hinge region was excluded from the size analysis. All statistical analyses were performed using Prism Graphpad and Excel. Student t-test was performed to assess the statistical significance between two groups and one-way ANOVA for multiple comparisons. P-value, standard deviation, and sample size (n) are provided in each figure or legend.

Developmental timing assays

Virgins (1–3 days old) where mated with (1–3 day-old) males in a 1:1 ratio (30 males and 30 females). Crosses were mated for 24 h before being transferred to grape agar and yeast paste, changing paste daily for 2–3 days to increase egg productivity. Next, the fertilized eggs were collected for 2 h for each cross on fresh agar plates. After 36 h the 1 st instars were collected and moved to the regular food with a density of 20 larvae per vial per cross. At least two or more biological replicas were achieved per Gαq perturbation. After egg laying (AEL), pupae were manually scored in 2-hour intervals from 7 am to 11 pm for 8 days.

Results

Gαq homeostasis promotes optimal organ size regulation

To identify how Gαq regulates organ size, we used the Gal4-UAS system to either inhibit or overexpress Gαq in the developing wing with the pouch-specific nubbin-Gal4, UAS-Dcr2 driver (nub-G4) (Table 1; Fig. 2E) [37, 65]. The wing disc includes a pouch, hinge, and notum, which develop into the adult wing blade, hinge, and dorsal thorax, respectively (SI Figure S3). First, we performed immunohistochemistry against Gαq to confirm overexpression and inhibition of Gαq. Through an ANOVA comparison, we found a statistically significant difference between the fluorescence intensity of GαqOE vs. the parental control (SI Figure S1). RNAi against Gαq also reduced fluorescence intensity compared to the control (p = 0.03, paired T-test). These results were additionally confirmed by RNA-seq, revealing statistically significant Gαq mRNA levels increased 5–7-fold for GαqOE and decreased 0.5 fold for GαqKD with the C765-Gal4 driver compared to control.

Fig. 2.

Gαq reduces wing size, induces Ca²⁺ waves, and delays larval development.(A-D) Drosophila melanogaster adult wing micrographs from (A) nubbin-Gal4, UAS-Dicer2 (nub-G4) (control), n=11; (B) nub-G4 x white¹¹¹⁸ (control) n=14; (C) nub-G4>UAS-Gαq^RNAi(Gαq knockdown), n=16; (D) nub-G4>UAS-Gαq (Gαq overexpression), n=11. (E) Imaginal wing disc cartoon representing nubbin gene expression pattern in wing disc pouch (green). (F) Box plot of adult wing area (min. to max.). Gαq knockdown was omitted from the ANOVA due to incomplete wing expansion. ANOVA was performed for all the rest of samples and P-values are shown as ****p-value <0.0001, ns=not significant. (G) Time-lapse images from in vivo imaging of wing discs expressing nubbin-Gal4>UAS-GCaMP6f (GCaMP6f), a GFP Ca²⁺ reporter (i), (control); crossed to white (ii) (also control); (iii) driving UAS-Gαq^RNAi and (iv) driving UAS-Gαq. Recording of in vivo activity was limited to 20 min, with 5 min intervals. The kymographs depict 20 min recordings, n=8. (H, I) GαqOE induces developmental delay via IP₃-Receptor. Flies were reared at 25°C, 12 hours light/dark cycle. (H) pupariation dynamics. (I) Box plot shows the average percent pupariation time per each experimental condition: C765-Gal4 x white (control); C765-Gal4>UAS-RyR^RNAi (control); C765-Gal4-UAS-Gαq^RNAi (Gαq knockdown); C765-Gal4>UAS-Gαq (Gαq overexpression), with ANOVA comparisons: ****(p<0.0001), ns=not significant. Sample size n>75 for each condition. AEL – after egg laying

Confirming our previous results, over-expression of Gαq (GαqOE), (nub-G4 > UAS-Gαq), (Fig. 2D) reduced adult wing size (Fig. 2F) compared to both parental nub-G4 (Fig. 2A) and nub-G4 outcrossed to white (nub-G4 x white), (Fig. 2B) controls. GαqOE induced a significant wing area reduction of approximately 30% (Fig. 2F). Since the wing size variation within each control group was 2.8%−3.9%, 30% reduction is considered a strong wing phenotype. Gαq RNAi-mediated knockdown (GαqKD) led to a complete loss of wing expansion (81% penetrance, Fig. 2C). A second Gal4 driver used in this study, C765-Gal4 (C765-G4), expressed in the entire wing disc, also resulted in reduction of wing area with both GαqOE and GαqKD reared at 22.5 °C (Table 1, SI Figure S2). Additionally, GαqKD produced wavy wings and melanization phenotypes at 25 °C, and at 28 °C caused a complete loss of wing and thorax segments and larval lethality with C765-G4 driver (SI Figure S3).

Previously, we reported that Gαq over-expression stimulates tissue-wide calcium waves (ICWs) in the wing disc pouch cells cultured ex vivo, and Gαq knockdown inhibits ICWs [35]. To test the functional activity of GαqOE, we over-expressed Gαq using the nub-Gal4 driver and the Ca²⁺ sensor GCaMP6f simultaneously (nubbin-Gal4 >UAS-GCAMP6f, UAS-Gαq) and performed in vivo imaging. We confirmed that GαqOE induces Ca²⁺ spontaneous and periodic intercellular activity in vivo (Fig. 2G iv, SI Video 1). Thus, we established with the phenotypic analysis (Fig. 2A-D, SI Figures S2, S3), Ca²⁺ reporter assay (Fig. 2G) and antibody staining (Table 2, SI FigureS1) that the Gαq perturbations used in this study are significant. Taken together, these results demonstrate that optimal organ size depends on achieving a balance of Gαq levels and associated Gαq-induced Ca²⁺ signaling.

Perturbation of Gαq expression induces developmental delay

While evaluating Gαq as a growth regulator, we also observed significant developmental delay. Both C765 >Gαq and C765 >Gαq^RNAi larvae pupariated statistically significantly later than control larvae at 25 °C (Fig. 2H and I) and at 22.5 °C (SI Figs. 2 SH, 2SI). This suggests that GαqKD-induced developmental delay occurs due to a lack of intracellular calcium, and GαqOE-induced developmental delay occurs due to an excess of intracellular calcium (Fig. 1). Downstream of Gαq, IP₃ Receptor (IP₃R) activation induces Ca²⁺ release from the endoplasmic reticulum (ER) [50] (Fig. 1). Consistently, inhibition of IP₃R also causes developmental delay (Fig. 2H and I), providing further evidence that the lack of intracellular calcium slows development. To test if the effects triggered by GαqOE are driven by an increase in the cytosolic Ca²⁺ via IP₃R, we inhibited IP₃R while co-expressing GαqOE and rescued the developmental delay (Fig. 2H and I and SI Figs. 2SH, 2SI). Thus, GαqOE-induced developmental delay occurs through IP₃R-related Ca²⁺ signaling. These results reveal that Gαq homeostasis, in concert with Gαq-induced Ca²⁺ signaling, regulates the timing of larval to pupal transition.

Gαq overexpression reduces proliferation and apoptosis during wing development

To examine whether Gαq phenotypic effects on wing size were mediated by decreased cell proliferation, or induced cell death, we perturbed Gαq transcription using the apterous-Gal4,UAS-GFP (ap-G4) driver. The ap-G4 driver is specific to the wing disc dorsal compartment, allowing for the comparisons of GFP-marked dorsal with the non-GFP ventral compartment as an internal control (Fig. 3K).

Fig. 3.

Gαq dysregulation reduces proliferation, apoptosis, and wing disc pouch area. (A-C, F-H) Third instar imaginal wing discs from (A, F): apterous-Gal4,UAS-GFP x white (control); (B, G): apterous-Gal4,UAS-GFP > UAS-Gαq^RNAi (Gαq knockdown) and (C, H): apterous-Gal4,UAS-GFP > UAS-Gαq (Gαq overexpression), showing apterous-Gal4,UAS-GFP driver expression pattern (GFP) localized in dorsal compartment and immuno-labeled of Phospho-Histone H3 (Ser10) antibody (shown as pH3) (A-C), and Cleaved Drosophila Dcp-1 (Asp215) antibody (shown as DCP1) (F-H). (D) Box plot showing PH3 positive cells per compartment in dorsal and ventral compartments, all genetic perturbations do not show statistically significant difference in PH3 signal between compartments (ns = non-significant). (E) Box plot showing PH3 signal in total wing pouch area. ANOVA of entire pouch comparison, **p = 0.0015. ns = non-significant. However, T-test comparison of ap > Gαq^RNAi and control is statistically significant p = 0.03. (I) Box plot showing DCP1 positive area per compartment and condition. T-test comparison was performed between dorsal and ventral compartments for each condition (D, I). (J) Box plot showing DCP1 signal in total wing pouch area. ANOVA of entire pouch comparison, ***(p-value = 0.0008). Sample sizes (n) for PH3 staining: ap x white n = 5, ap > Gαq^RNAi n = 12, ap > Gαq n = 8. Sample sizes for DCP1 staining: ap x white n = 9, ap > Gαq^RNAi n = 6, ap > Gαq n = 12. (K) Cartoon representation of ap-Gal4 driver expression pattern in the wing disc. D Distal, V Ventral, A Anterior, P Posterior, the dashed line represents a wing disc pouch area. (L) GαqOE and GαqKD both reduce total wing disc pouch area. ANOVA was performed to compare pouch areas of each genetic perturbation. *(p-value = 0.03) Sample sizes (n) as follows: ap x white n = 14; ap > Gαq^RNAi n = 18; ap > Gαq n = 20

First, we assessed proliferation in the wing disc using antibody staining with Phospho-Histone H3 (PH3) [66] (Table 2; Fig. 3A-E). Neither GαqOE nor GαqKD induced statistically significant changes in PH3 levels between dorsal (perturbed) and ventral (control) compartments for each cross (Fig. 3D). Therefore, proliferation changes did not occur compartment-specifically. However, we found a statistically significant global reduction in proliferation in GαqOE, which can explain smaller wing size phenotype for GαqOE (Fig. 3E). A comparison of GαqKD with the control showed a statistically significant result by T-test comparison (p = 0.03). Together, this indicates that dysregulation of Gαq impacts organ size.

Next, we tested whether perturbing Gαq levels also impacts apoptosis by measuring for spatial distribution of the effector caspase, Death caspase-1 (Dcp-1), a marker for programmed cell death [67], that acts downstream of initiator caspase Dronc (Fig. 3F-H). As caspases play an essential role in apoptosis [68], we quantified the area of Dcp-1 expressing cells in both ap >Gαq and ap >Gαq^RNAi, where the ventral compartment (non-GFP) of the wing disc pouch served as an internal control. Neither GαqOE nor GαqKD induced statistically significant changes in Dcp-1 levels between dorsal (perturbed) and ventral (control) compartments for each cross (Fig. 3I). Therefore, apoptosis changes did not occur compartment-specifically. However, we found that increasing the levels of Gαq caused a statistically significant reduction of the Dcp-1-induced apoptotic cells in the total wing disc pouch area (Fig. 3J). Further, RNA-seq analysis revealed that many cell-death-related genes are downregulated (Fig. 4A). Additionally, we identified that Gαq perturbations driven by the ap-Gal4 driver produced smaller wing discs, supported by the total wing disc pouch area measurements (Fig. 3L). This suggests that perturbing Gαq during development, even with compartment-specific expression, results in overall smaller organs. In summary, GαqOE causes a statistically significant tissue-level reduction in both proliferation and apoptosis, and a reduction in the entire wing pouch area despite using the ap-Gal4dorsal-specific driver. This indicates that perturbing the expression levels of Gαqlocally in the wing disc causes a pause in growth and development at an organismal level and suggests signaling mechanisms that work at the global scale.

Fig. 4.

Gαq transcriptionally downregulates cell death, nuclear hormone receptor, ecdysone effector, and insulin pathway genes. (A-D) Heatmaps of Log2 Fold Change (Log2FC) Differentially Expressed Genes (DEGs) of (A) Cell death related genes, (B) Nuclear hormone receptors, (C) Insulin pathway genes, note upregulation of Dilp8, and (D) ecdysone response genes

RNA-seq and KEGG enrichment analysis revealed cellular stress and signaling disruption in the Gαq-perturbed wing discs

We next sought to explain the paradoxical signaling seen with inhibition and overexpression of Gαq, where upregulation of a gene causes similar phenotypes as downregulation, including smaller wing size (Fig. 2A-D and F, SI Figure S2 A-D and G) and developmental delay (Fig. 2H and I). To do so, we performed an RNA-seq analysis to evaluate gene expression levels. We sequenced three mRNA libraries (3 biological replicas) per cross of 15–30 wing discs for each bio replica, of the following genetic crosses: C765-Gal4 > UAS-RyR^RNAi; (control); C765-Gal4 > UAS-Gαq^RNAi; C765-Gal4 > UAS-Gαq. We pooled the results of each bio replica per condition for the bioinformatic analysis, provided detailed in Supplementary Information (SI RNA-seq gene counts section). We performed Principal component analysis (PCA) and plotted the results for each library and observed a well-defined clustering for each bio-replica within its group, confirming the sequencing results (SI Figure S4). The C765-Gal4 driver was employed since it is expressed in the entire wing disc and therefore would drive the expression of Gαq across the whole wing to increase the amount of tissue reflecting perturbations in Gαq levels. The wing discs consist predominantly of epithelial tissue but also have several other cell types. By perturbing the expression of Gαq across the entire wing, we obtained a general readout of its expression, not limited to a single cell type, intending to understand how Gαq-related calcium signaling and a lack of it affect development.

We next evaluated our results with a KEGG enrichment analysis (SI Table S10, Table S11). Of note, the KEGG enrichment analysis of DEGs for GαqKD indicated downregulation (25%) of Hippo signaling, which is an evolutionarily conserved signaling pathway that controls organ size [69]. Hippo normally promotes apoptosis and suppresses cell division, therefore downregulation of Hippo can produce uncontrolled growth [70]. Also, interactions between the ECM and cell receptors were downregulated, with Integrins being the primary transmembrane molecules mediating this process. Disruption in Integrin-ECM interactions can lead to abnormalities in cellular activities such as adhesion, migration, differentiation, proliferation, and apoptosis. This could explain the wavy adult wing phenotype for C765-G4 >UAS-Gαq^RNAi (SI Figure S3A). The KEGG enrichment analysis of DEGs for GαqOE indicated downregulation of lysosomes, which can lead to the accumulation of misfolded proteins and organelles (mitochondria), increased oxidative stress and inflammation, cellular dysfunction, and cell death (SI Table S11). It also notably showed downregulation of apoptosis, which can lead to an imbalance in cellular homeostasis and can contribute to various diseases such as cancer, autoimmune disorders, and neurodegenerative conditions. It was also enriched for the upregulation of TCA cycle components (Krebs cycle), protein and nucleic acid synthesis, detoxification mechanisms, cytokine production, and the Longevity-regulating pathway. These upregulated pathways likely compensate for the repercussions of downregulated pathways in a developing wing for GαqOE. To summarize, KEGG showed that perturbing Gαq levels leads to metabolic stress, disrupted cellular signaling and membrane structure.

Gαq conveys a transcriptional signal for repair locally and suppresses morphogenesis through ecdysone signaling via Dilp8 globally

We next evaluated GO enrichment associations (SI Figures S6-S17). Genes upregulated when overexpressing Gαq were significantly enriched with many terms for mitosis and DNA replication (SI Figure S7), as well as categories of actomyosin structure organization and protein refolding (SI Figures S6, S8), among others, which are indications of cell stress and regenerative growth. Additionally, the upregulation of serine proteases (a cluster of gene family Jon, SI Figure S15, SI Table S8), downregulation of serine protease inhibitors (Serpins) (Fig. 5C, SI Table S4), and upregulation of Heat shock proteins (Hsp70) (Fig. 5D, SI Table S5) indicate that Gαq regulates stress and wound healing responses. Finally, we discovered that the signaling peptide Drosophila insulin-like peptide 8 (Dilp8, a.k.a. ilp8) [71] is upregulated when perturbing Gαq expression (Fig. 4C, Fig. 5A, SI TableS1).

Fig. 5.

Gαq perturbations transcriptionally upregulate JAK/STAT and Toll signaling pathways. (A-D) Heatmaps of Log2 Fold Change (Log2FC) Differentially Expressed Genes (DEGs) of (A) JAK/STAT signaling pathway components, (B) Toll/NF-kB signaling pathway, (C) Serine Protease Inhibitors, (D) Heat Shock Protein 70 family. Comparisons of C765-Gal4 > UAS-Gαq (Gαq overexpression) and C765-Gal4 > UAS-Gαq^RNAi (Gαq knockdown), were performed versus the C765-Gal4 > UAS-RyR^RNAi control

For the Gαq overexpression condition, GO enrichment terms for downregulated genes include larval or pupal development, neuron projection, tube morphogenesis, cell morphogenesis, molting cycle, biological adhesion, aminoglycan metabolic process, among others (SI Figures S10, S11). Transcripts of genes downstream of ecdysone signaling, including blimp1, HR3 and HR4, eip75B (ecdysone induced protein 75B) and eig71Ee (ecdysone induced gene 71Ee), are downregulated (Fig. 4), and enriched with negative regulation of metabolic process and cellular response to ecdysone categories (SI Figures S11, S12). These results prompted us to investigate the question: How does Gαq dysregulation lead to developmental delay (Fig. 2H) if Gαq perturbations are genetically induced with a wing disc specific Gal4 driver (C765-Gal4)? We hypothesized that the upregulation of Dilp8 signaling facilitates the developmental delay (Fig. 4C) since it mediates periphery signals to the brain following wounding [71]. To summarize, signaling mediated by upregulation of Gαq in the wing disc tissue triggers transcriptional downregulation of development, and upregulation of stress-response genes, with notable upregulation of Dilp8 expression.

Perturbing Gαq results in transcriptional dysregulation of JAK/STAT, Toll/NF-kappaB and Insulin signaling pathways

Next, we used PANGEA’s PathON to reveal how perturbations to Gαq expression impacts major signaling pathways. We found that Gαq perturbations cause transcriptional changes in genes that are associated with Toll/NF-kappaB, JAK/STAT, Insulin, EGFR/FGFR/PVR, and Notch signaling pathways, as seen in circular plots with the DEG members of each enriched pathway (SI Figure S5).

Transcriptional upregulation of the JAK/STAT signaling pathway by overexpression of Gαq

Upd1 and upd3, the activators of the JAK/STAT signaling pathway, were only transcriptionally upregulated when Gαq is overexpressed but not under the knockdown condition (Fig. 5A, SI Table S1). Notably, the transcription factor Ken, which inhibits the JAK/STAT pathway, is upregulated in both C765 >Gαq and C765 >Gαq^RNAi (Fig. 5A, SI Table S2). Therefore, JAK/STAT was only upregulated in the overexpression condition. Both upregulating and downregulating perturbations of Gαq increased the expression of chinmo (chronologically incorrect morphogenesis) [72], but prominently more so in GαqOE (Figs. 4C and 5A). Interestingly, GPCR Methuselah-like 8 (Mthl8) was significantly upregulated (log₂FC = 11.5) with overexpression of Gαq, but not knockdown (Fig. 5A, SI Table S2). As a counterexample, Shawl, a rectified potassium channel, is highly expressed (log₂FC = 9.6) in exclusively the GαqKD (SI Table S2). Overall, our bioinformatic analysis identified that exclusively overexpression of Gαq promoted transcriptional upregulation of JAK/STAT pathway, and knockdown of Gαq likely downregulates the JAK/STAT pathway via upregulation of ken.

Other significantly perturbed signaling pathways for both GαqOE and GαqKD include Toll, Insulin, Notch, EGFR, Wnt, and Imd. (Figures 4 and 5, SI Table S3, SI Figure S5). The Toll signaling pathway is an immune response cascade that includes inhibited proteases when in its inactive state [73], and is involved in development [74]. Several initiators [75] (Ea - usually activated by embryonic patterning, Psh - typically activated by yeast and bacteria), ligands (spz4 and spz5), the Toll-9 receptor, and its target Dif were transcriptionally upregulated in both GαqKD and GαqOE conditions (Fig. 5B, SI Table S3), with stronger induction in GαqOE. Notably, Peptidoglycan recognition protein SC2 (PGRP-SC2) – typically activated by Gram + bacteria, was transcriptionally upregulated exclusively for GαqKD. Additionally, Gαq perturbations stimulated stress response genes such as Heat shock proteins Hsp70 (Fig. 5D, SI Table S5), and downregulated several Serine Protease Inhibitors (SerPIns, Serpins) (Fig. 5C), which prevent inhibition of serine proteases (SI Table S4). Particularly, Serpin 43Aa and Serpin 77Ba are known to be involved in Toll signaling pathway inhibition [76]. This Serpin downregulation indicates the likelihood of the activation of the Toll signaling pathway, especially for the GaqOE condition. Therefore, our data shows that Toll signaling pathway, normally triggered by various virulence factors, is also upregulated by perturbed Gαq.

Gαq overexpression induces developmental delay through Dilp8

Dilp8 (Drosophila insulin-like peptide 8) is an insulin-like peptide which regulates growth timing and, thus, the larval-to-pupal transition [71, 77]. As noted from RNA-seq results, Dilp8 expression levels were significantly higher when Gαq was upregulated. To functionally confirm this, we performed antibody staining for Dilp8 in the background of GαqOE (Table 2, Fig. 6). Compared to the control, the GαqOE condition induced a higher Dilp8 signal seen as bright yellow specs throughout the tissue (Fig. 6A and A’ versus 6B and 6B’). Further, we confirmed that the developmental delay is conveyed by Dilp8, by performing a Gαq-originated delay rescue experiment by knocking down Dilp8 in the background of GαqOE and measuring the larval-to-pupal transition time for both control and Gαq perturbations (Fig. 6C and D). In conclusion, we established that Gαq overexpression induces developmental delay through Dilp8.

Fig. 6.

Wing discs overexpressing Gαq upregulate Dilp8, mediating Gαq - induced developmental delay.(A-A’, B-B’) Dilp8 antibody staining in imaginal wing discs in C765-Gal4 x White (control), and C765-Gal4 >UAS-Gαq (GαqOE). (A, B) Frontal views; (A’, B’) corresponding cross-sections. Sample size: n > 5 per genotype. (C) Pupariation dynamics under standard conditions (25°C, 12 h light/dark cycle). (D) Quantification of pupariation delay by one-way ANOVA, (****P < 0.0001). Sample sizes: (Control: n = 75); (GαqOE, Dilp8KD: n = 48); (GαqOE: n = 157)

Gαq signaling affects cytoskeleton organization in the developing wing disc

Transcriptionally, GαqOE reduced biological adhesion (SI Figure S10), and upregulated actomyosin structure organization, regulation of cytokinesis, and protein refolding (SI Figure S8). Cell adhesion is crucial in morphogenesis and when disrupted, results in metastatic cancer [78]. Furthermore, RNA-seq analysis determined that several Troponin C proteins are strongly upregulated for GαqOE and GαqKD compared to control (SI Table S7). Troponin C directly binds Ca²⁺ and acts downstream of Gαq to regulate the cell cytoskeleton [79]. Also, Myosin proteins were upregulated for the GαqOE and GαqKD conditions compared to the control (SI Table S9). For functional confirmation of actomyosin distribution in the developing tissue due to perturbed Gαq we used immunohistochemistry assay against Phospho-Myosin II (PMyoII) antibodies. The PMyoII antibody against myosin phosphorylated at specific Serin 19 residue, provides a measure of actomyosin contractility [80] in non-muscle and muscle cells. Previously, we showed that cells at the center of the wing disc pouch are normally stiffer than the cells of the wing disc pouch periphery, and actomyosin accumulates along the Distal-Ventral (D-V) axis [81]. To find the relative PMyoII localization in wing discs, we used antibody staining (Table 2) for nub >GαqOE and control (Fig. 7). Through qualitative analysis, we observed an upregulation in PMyoII signal strength and its uneven distribution upon overexpression of Gαq (Fig. 7i, ii, iii). PMyoII localization increased basally and accumulated unevenly topically in the wing disc pouch as compared to the control (Fig. 7, i and ii), suggesting that actomyosin contractility is increased basally and is uneven throughout the pouch. This was confirmed by statistical analysis (Fig. 7 iii). In summary, Gαq-promoted signaling influences pMyoII localization in the developing wing disc, indicating abnormally stiffer areas. Collectively, these results functionally confirm that Gαq regulates key components of the cytoskeleton.

Discussion

Gαq homeostasis plays a key role in optimal organ size

In characterizing the broader calcium signaling network and its influence on organ growth, we found unexpectedly that both overexpression of Gαq and knockdown of Gαq led to smaller wing sizes (Fig. 2, SI Figure S2). Gene Ontology (GO) enrichment analysis of differentially expressed genes (DEGs) in the GαqOE condition, identified upregulation of pathways related to DNA replication (SI Figure S6) and the mitotic cell cycle (SI Figure S7) specifically among upregulated genes with log₂FC > 0.6. This suggests that the tissue was transcriptionally primed for proliferation, potentially in response to stress. However, proliferation assays revealed a statistically significant non-compartment specific global reduction in cell proliferation under GαqOE and GαqKD conditions (Fig. 3A-E). These results indicate that despite transcriptional cues favoring proliferation, actual cell-division and tissue growth were impaired, contributing to the reduced organ size.

In line with this, several growth-promoting pathways—including epidermal growth factor receptor (EGFR) pathway—were transcriptionally downregulated in the RNA-seq data (SI Figure S5), likely contributing to suppressed growth. Additionally, some of the pro-apoptotic genes, such as Dronc (Death regulator Nedd2-like caspase) and hid (head involution defective) were downregulated (Fig. 4A, SI Table S6), while rpr (reaper) [82], was upregulated in both Gαq perturbations. Damm, (Death associated molecule related to Mch2 caspase), was also upregulated in GαqOE, suggesting that apoptosis was not fully activated and may have been disrupted. Such dysregulation could lead to incomplete apoptotic signaling, elevate cellular stress and contribute to various diseases such as cancer, autoimmune disorders, and neurodegenerative conditions. Additionally, CG3819 and CG6839—two genes predicted to be involved in apoptotic DNA fragmentation in mitochondria are strongly upregulated (Fig. 4A), indicating mitochondria involvement and possibly mitophagy.

To distinguish normal Dcp-1 expression from active apoptosis, we performed an apoptosis assay and used the Cleaved Drosophila Dcp-1 (Asp215) antibody that recognizes only the activated Dcp-1. Indeed, Dcp-1 antibody staining confirmed a significant reduction in apoptosis in GαqOE, again on the global scale, with a similar but not significant trend observed in GαqKD (Fig. 3F-J). Consistently, stress-related transcriptional signatures of HSP70 family (Fig. 5, SI Table S5) and Serine proteases (Table S8) as well as metabolic processes upregulation, protein refolding (SI Figure S8) and downregulation of biological adhesion (SI Figure S10), which can be important in cancer progression, were detected in our RNA-seq dataset. Given that constitutively active Gαq signaling underlies uveal melanoma, our study suggests a potential mechanism by which Gαq contributes to tumorigenesis: by impairing apoptosis and promoting cellular stress, Gαq dysregulation creates an enabling environment for oncogenic transformation.

Gαq overexpression induces developmental delay through Dilp8

The distal-compartment specific Gαq perturbations with ap-Gal4 driver decreased both ventral and distal compartment areas (Fig. 3L), as well as proliferation and apoptosis were both reduced globally (Fig. 3A-J). This indicates that Gαq perturbations during development cause effects that are not compartment-specific but instead globally affect the entire organ and suggest a signaling mechanism from the organ to the brain. Transcriptionally, Dilp8 was upregulated in both perturbations (Fig. 4C, SI Table), but prominently more so in GαqOE. Dilp8 governs the larval-to-pupal transition and developmental timing by regulating ecdysone signaling [71]. We confirmed with Dilp8 antibody staining that GαqOE produces significantly higher levels of Dilp8 than the control, and the GαqOE-induced developmental delay (Fig. 2H) was rescued via Dilp8 knockdown (Fig. 6). Therefore, we established that the wing disc communicates Gαq signaling dysregulated homeostasis to the brain via Dilp8. This organism-wide developmental pause aims to provide the wing disc time to recover and complete its development [71]. From the literature, the release of Dilp8 is triggered by the activation of JAK/STAT signaling, which leads to ecdysone inhibition, thereby slowing growth [83]. Our pathway analysis suggests that GαqOE in the wing disc triggers an immune and stress response in part via the activation of the JAK/STAT pathway (SI Figure S5, SI Table S1). Katsuyama et al. found that JAK/STAT signaling is activated in the wing disc at a wound site and induces regenerative cell proliferation that leads to the expression of Dilp8 [83]. They found that JAK/STAT is required for Dilp8 production and also confirmed findings from Colombani et al. [71] that Dilp8 can signal from the periphery using LGR3 receptors in the ring gland to the brain and can delay the onset of pupariation. Several studies demonstrated that uncontrolled constitutively active JAK/STAT can create cancer-like growth and melanotic tumors [84]. Therefore, our findings suggest that through Gαq-related Ca²⁺ signaling, JAK/STAT signaling is activated and stimulates, among other effectors, Dilp8 production that circulates from the periphery to the brain. Next, Dilp8 inhibits ecdysone synthesis in the brain, ultimately slowing down molting cycle and development (Figs. 5A and 6, SI Figures S11 and S12).

In GαqKD, a decrease in Ca²⁺ activity caused by Gαq downregulation also inhibits growth. Ca²⁺ is an important secondary messenger that regulates multiple cellular responses, including growth and apoptosis [9, 85, 86]. We propose that the downregulation of Gαq affects growth by reducing Ca²⁺ release from the ER via IP₃R, which in turn causes abnormal changes in gene expression and membrane potential. In the future, we plan to continue functionally validating the genes and pathways identified in this study to gain a deeper understanding of the Ca²⁺ signaling in the developing Drosophila wing.

Limitations of this study

For RNA-seq analysis, efforts were made to meticulously dissect wing discs and remove tracheal attachments, however, trace amounts of tracheal mRNA may have been present in the dataset due to the attachment of tracheal tissue to the wing disc. While this potential contamination is expected to be minimal, it should be considered when interpreting gene expression data, particularly for genes known to be expressed in tracheal tissues.

Most drivers that were utilized for wing-specific expression do, to a degree, also have some expression patterns in the brain (our unpublished data) (apterous-Gal4, nubbin-Gal4, C765-Gal4). Therefore, studies using these drivers have limited scope due to the influences of brain expression. Confirming this, we observed that RyR knockdown in the wing disc caused a larger wing size (SI Fig. 2B, G), even though RyR is not expressed in the wing disc (our unpublished data and Modencode project). C765-Gal4 driver is expressed in neurons, and so is RyR, potentially explaining wing size alterations. Therefore, there could be some gene transcripts in our control that were influenced by brain hormonal signaling.

Finally, the C765-Gal4 driver used for RNA-seq crosses was advantageous in providing a larger yield of RNA. However, it drives expression not only in future wing blade cells (corresponding to the wing disc pouch region) but also in the hinge (muscle attachment of the wing to the thorax) and notum (future dorsal thorax). As a result, the RNA-seq data reflects not just epithelial tissue development, but also, to a lesser extent, muscle tissue and thorax development. Additionally, unlike other drivers, the C765-Gal4 line does not include extra Dicer expression to enhance RNAi efficiency. RNAi is also known to be temperature-dependent. Although all crosses were reared at 25 °C unless otherwise noted, RNA-seq data and immunostaining suggest that Gαq^RNAi produced a relatively weak effect under these conditions (SI Figure S1). Raising the temperature to 27–28 °C yields lethality and severe phenotypes (SI Figure S3).

Conclusions

In this study, we demonstrate that Gαq homeostasis is required for organs to achieve their optimal size and shape. We confirmed that Gαq generates periodic multicellular Ca²⁺ transients and waves in in vivo developing Drosophila wing discs (Fig. 2 G iv) and that Gαq genetic perturbations result in the expected alteration of Gαq expression (SI FigureS1). We found that the small wing size phenotype (Fig. 2) is due to reduced proliferation through anti-PH3 assay (Fig. 3 A-E). We also found that apoptosis is downregulated due to GαqOE (Fig. 2 F-J) through the specific activated Dcp-1 staining, which was confirmed with RNA-seq data. This also indicated a potential cancer connection, which warrants further investigation.

Through the assessment of Gαq-induced developmental delay and its rescue via IP₃R knockdown, we show that Gαq-related Ca²⁺ signaling slows down morphogenesis. RNA-seq revealed that perturbing Gαq causes release of signaling peptide Dilp8 (Figs. 4 C and 5 A), which was also confirmed using Dilp8 antibody staining (Fig. 6). The release of Dilp8 along with the downregulation of ecdysone-related genes highlighted a systemic developmental regulation via ecdysone, and stress response mechanisms that occur when Gαq levels are disrupted. Furthermore, we rescued the Gαq-induced developmental delay via Dilp8 knockdown, revealing that the delay is due to the Dilp8 upregulation (Fig. 6). Therefore, Gαq developmental delay is due to ecdysone signaling delay via Dilp8. Also, Gαq downregulates biological adhesion, changing actomyosin structural organization and regulation of cytokinesis (SI Figures S8 and S10, SI Table S9), which was validated through immunohistochemistry assay (Fig. 7).

Using RNA-seq we also found that Gαq is a key upstream signal that (1) upregulates the JAK/STAT pathway via the transcription of the pathway’s ligands (Fig. 5, SI Table S1), (2) upregulates Toll signaling pathway (Fig. 5, SI Table S3), (3) upregulates Troponin C (SI Table S7), a Ca²⁺ binding protein. However, these findings require future functional confirmation.

Cumulatively, these findings confirm that Gαq homeostasis is critical for proper developmental timing and organ size, acting through Dilp8-mediated systemic signaling.

Authors’ contributions

MFU performed experiments, analyzed data, and wrote the paper. DKS, VVK, MMF also performed experiments, analyzed data, and were involved in writing in the past. DG, NK performed experiments and were involved in writing at a later stage. J. Li performed the RNA-seq bioinformatic analysis, and J. Liu performed GO and transcriptomic analysis. JJZ conceived the study, analyzed data, wrote the paper, and supervised the study. All authors reviewed the manuscript.

Data availability

Bioinformatics analysis of DEGs is provided within the supplementary information file. The bulk DEG expression analysis data obtained from our RNA-seq study as well as the RNA sequencing raw data and the wing image data obtained during the current study is available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable

Competing interests

The authors declare no competing interests.