Early-life macronutrient exposure alters pubertal timing through hypothalamic microRNA networks

Abstract

Pubertal timing is modulated by early-life nutrition through epigenetic mechanisms that remain incompletely understood. This study investigated how macronutrient-specific diets influence hypothalamic microRNA (miRNA) expression and pubertal onset in female Wistar rats. Animals were exposed to High-Fat (HFD), High-Carbohydrate (HCD), High-Protein (HPD), and Cafeteria diets (CafD) from postnatal day 21–42 followed with comprehensive analysis of phenotypic markers, hormone levels, ovarian histology, in-silico structural modelling and hypothalamic microRNA (miRNA) transcriptomics. Energy-dense diets (HFD, HCD) significantly advanced vaginal opening by 4–5 days compared to controls and increased body weight, serum Luteinizing Hormone (LH), Follicle Stimulating Hormone (FSH), and Estradiol levels compared to control. Small RNA sequencing revealed extensive miRNA reprogramming, with over 490 differentially expressed miRNAs in each dietary group. Key findings included upregulation of miR-30b (targeting Mkrn3, a pubertal inhibitor), downregulation of miR-199 (targeting Kiss1, a pubertal activator), and altered expression of let-7 family miRNAs affecting developmental timing genes. Quantitative PCR validation confirmed inverse relationships between regulatory miRNAs and their target mRNAs involved in HPG axis control. In-silico structural modelling supported the thermodynamic stability of predicted miRNA-mRNA interactions. Functional enrichment analysis revealed convergence on GnRH signalling, MAPK pathways, and neuroendocrine regulation. These findings suggest that early nutritional environments may influence hypothalamic miRNA networks, potentially contributing to long-term neuroendocrine modulation.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-24488-5.

Introduction

Puberty marks the transition to reproductive maturity and is governed by the hypothalamic-pituitary-gonadal (HPG) axis, initiated by increased pulsatile secretion of gonadotropin-releasing hormone (GnRH) from the hypothalamus^1,2. While genetic factors contribute substantially to the timing of pubertal onset, early-life nutritional status has emerged as a powerful modulator^3–5, influencing both the trajectory and magnitude of HPG axis activation^6,7. Nutritional cues, such as leptin, are integrated in the hypothalamus where they modulate kisspeptin neurons upstream of GnRH release^8,9. Both overnutrition and undernutrition can perturb this neuroendocrine circuitry, resulting in shifts in pubertal timing¹⁰. However, the molecular pathways linking dietary inputs to hypothalamic gene regulation remain incompletely understood, especially during the prepubertal period¹¹. Among the emerging candidates mediating these effects are microRNAs (miRNAs) which are short, non-coding RNAs that fine-tune gene expression by binding to complementary sequences in the 3′ untranslated regions (3′UTRs) of target mRNAs, leading to translational repression or mRNA degradation^12,13. Several miRNAs have been shown to regulate genes involved in pubertal control, including Kiss1, Mkrn3, Gnrh1, and Lin28¹³. For example, miR-30b suppresses the puberty-inhibitor Mkrn3, while let-7 modulates Lin28¹⁶, a conserved regulator of developmental timing¹⁷. These findings suggest that miRNAs may serve as epigenetic switches that integrate nutritional cues and orchestrate HPG axis activation.

In this study, we examined how four macronutrient-rich dietary regimens high-fat (HFD), high-carbohydrate (HCD), high-protein (HPD), and cafeteria diet (CafD) affect pubertal programming in weaned female Wistar rats through modulation of hypothalamic miRNAs. By integrating small RNA transcriptomics with qPCR validation of key neuroendocrine genes (Kiss1, Gnrh1, Mkrn3, Zeb1, Tbx21, Cebpb, Mapk14), serum hormone profiling (LH, FSH, estradiol), and ovarian histology, we sought to construct a comprehensive mechanistic framework linking diet-induced miRNA shifts to phenotypic markers of pubertal onset. We further employed in-silico target prediction, functional enrichment, and miRNA–mRNA docking analysis to elucidate the regulatory roles of differentially expressed miRNAs. We hypothesized that distinct macronutrient exposures would differentially reprogram hypothalamic miRNA expression, influencing pubertal timing through neuroendocrine pathways. Additionally, the miR-30b/MKRN3 pathway has already been identified as a critical regulator of pubertal timing in both animal and human studies^18,19. Building upon this established foundation, our study extends these findings by investigating how macronutrient-specific dietary exposures can modulate this pathway, thereby linking nutritional environments with miRNA-regulated neuroendocrine mechanisms of puberty.

Materials and methods

Animal maintenance

Female Wistar rats (PND 18, 24 ± 0.9 g) were procured from Sync Bio Research Pvt. Ltd. and housed under controlled environmental conditions (22 ± 1 °C, 50–60% humidity, 12:12 h light–dark cycle) with ad libitum access to food and water. All experimental procedures involving animals were reviewed and approved by the Institutional Animal Ethics Committee (IAEC) of the Maharaja Sayajirao University of Baroda, under approval number MSU-Z/IAEC08/13-2024 and complied with ARRIVE guidelines²⁰.

Animals (n = 20 per group) were randomly assigned to one of five dietary regimens from PND 21 to 42: standard chow (control), HFD, HCD, HPD, and CafD, a palatable, energy-dense mixture of snack foods (cookies, chips, sweetened milk) mimicking Western diets. Detailed macronutrient compositions are provided in Supplementary Tables 1–5²¹. Daily caloric intake per rat was calculated based on diet-specific consumption and energy density²⁵. Body weights were recorded every 7 days and pubertal onset was assessed via daily monitoring of vaginal opening (VO) from PND 25 onward, with VO age recorded and compared across groups, animals were euthanized on PND 42 via intraperitoneal administration of sodium pentobarbital (200 mg/kg) in accordance with the AVMA Guidelines for the Euthanasia of Animals (2020).

Blood samples were collected via retro-orbital puncture on PND 28, 35, and 42²⁶. Serum was separated (n = 6) and immediately processed for measuring the levels of follicle-stimulating hormone (FSH) (EA0015Ra, Bioassay Technology Laboratory, Jiaxing, Zhejiang, China), luteinizing hormone (LH) (EA0013Ra, Bioassay Technology Laboratory, Jiaxing, Zhejiang, China), and estradiol (E-OSEL-R0001, Elabscience, Texas, USA) were measured using commercially available ELISA kits, following manufacturer protocols; The sensitivity of kits for LH (0.31mIU/ml), Estradiol (1.17pg/ml) and FSH (0.022mIU/ml) as mentioned on the manufacturer’s datasheet. All samples were run in triplicate. For downstream molecular analyses, six animals per group were randomly selected for RNA sequencing and qPCR validation, this allocation was performed at random to minimize potential bias.

RNA isolation and small RNA library preparation

Total RNA was extracted from frozen hypothalamic tissue (40 mg) using the Direct-Zol™ RNA MiniPrep Kit (R2050, Zymo Research, USA) according to the manufacturer’s protocol. Dissections were guided by stereotaxic landmarks to isolate the medio basal hypothalamus enriched for the ARC, with tissues pooled within groups to ensure adequate RNA yield (n = 6). RNA quantity and purity were assessed using a NanoDrop 2000 spectrophotometer (ND-2000, Thermo Fisher Scientific, USA), and integrity was confirmed using the Agilent 4200 TapeStation (G2991BA, Agilent technologies, USA) with high sensitivity RNA ScreenTape. Only samples with RNA Integrity Numbers (RIN) > 6 were selected for library preparation.

Small RNA libraries were constructed using 1 µg of high-quality RNA per sample and the NEBNext^® Multiplex Small RNA Library Prep Kit for Illumina (E7300L, New England Biolabs, USA). The protocol involved sequential ligation of 3′ and 5′ adapters, reverse transcription, and PCR amplification with indexed primers for multiplexing. Adapter-ligated products (120–190 bp) were size-selected using AMPure XP beads (A63880, Beckman Coulter, USA). Library quality was validated via TapeStation analysis to confirm fragment size distribution and absence of adapter dimers. Quantification was performed using the Qubit Fluorometer (Q33238, Thermo Fisher Scientific, USA), and libraries were pooled equimolarly. Sequencing was conducted on the Illumina NextSeq500 platform using single-end 1 × 75 bp reads, targeting ~ 10 million reads per sample.

Small RNA sequencing data processing and bioinformatics analysis

Raw reads from the Illumina NextSeq500 platform were trimmed using Cutadapt²⁷ and Trimmomatic to remove adapters, poly(A) tails, low-quality bases (Phred < 20), and ambiguous nucleotides. Reads of 18–30 nucleotide was retained and aligned to the Rattus norvegicus genome (mRatBN7.2, Ensembl) using Bowtie v1.3.1 (https://bowtie-bio.sourceforge.net/index.shtml). Non-miRNA reads (e.g., tRNA, snoRNA, snRNA, piRNA) were filtered using Rfam and Repbase. miRNAs were annotated and quantified using miRDeep2. Known and novel miRNAs were identified based on miRBase alignment and miRDeep2 score (≥ 4) with significant randfold p-values. Expression values were normalized as reads per million (RPM). Differential expression was analysed using DEGseq (Likelihood Ratio Test), with p < 0.05 as the threshold for significance, and Benjamini–Hochberg false discovery rate (FDR) correction was applied to control for multiple testing across all miRNAs. Heatmaps and volcano plots were generated in Rstudio (version: 2025.05.1 + 513).

Target prediction was performed using miRanda with strict 5′ seed matching and energy cutoff of − 25 kcal/mol. Gene Ontology (GO)²⁸ and Kyoto Encyclopedia of Genes and Genomes (KEGG)^29,30 enrichment of predicted targets was conducted using ClusterProfiler³¹, focusing on pathways related to hypothalamic signalling and pubertal regulation. Raw data are available in the NCBI SRA (PRJNA1240077) under BioSample accessions SAMN47502131–SAMN47502135. The schematic diagram for this pipeline is detailed in supplementary Fig. 1.

Quantitative gene expression study

To validate small RNA-seq findings, RT-qPCR was performed on hypothalamic RNA using the miScript II RT Kit (218160, Qiagen, Germany) and SYBR Green PCR Kit (A25741, Applied Biosystems) with miRNA-specific stem-loop primers. Reactions were run on a QuantStudio Real-Time PCR System (4369074, Applied Biosystems), and U6 snRNA was used as an internal control. The thermal cycling conditions were as follows: initial denaturation at 95 °C for 10 min, followed by 40 amplification cycles of 95 °C for 15 s and 60 °C for 60 s. Relative expression of selected miRNAs (miR-30b, miR-29a, miR-375, miR-137, miR-199a, miR-155) was calculated using the 2^−ΔΔCt method³².

For mRNA quantification, cDNA was synthesized using the High-Capacity cDNA Reverse Transcription Kit (4374967, Thermo Fisher Scientific, USA), followed by qPCR with PowerUp SYBR Green Master Mix using the Step One PCR (4369074, Applied Biosystems, USA). RT-qPCR was performed using the following thermal cycling conditions: an optional UDG activation step at 50 °C for 2 min, initial denaturation at 95 °C for 2 min, followed by 40 amplification cycles of denaturation at 95 °C for 15 s, annealing at 57–60 °C for 15 s, and extension at 72 °C for 1 min. Target genes included Mkrn3, Kiss1, Gnrh, Tbx21, Zeb1, Cebpb, Mapk14 (p38), Sirt1, Ampk and mTOR normalized to GAPDH. All reactions were run in technical triplicates with no-template controls to ensure specificity. List of primers are detailed in supplementary Tables 6–7.

Histology

Ovarian tissue (n = 6) Sections (5 μm thick) were harvested and deparaffinized in xylene and rehydrated through a graded ethanol series. Sections were stained with haematoxylin for 5 min, differentiated in 1% acid alcohol, and blued in ammonia water. Subsequently, sections were counterstained with eosin for 2 min, dehydrated in ascending ethanol concentrations, cleared in xylene, and mounted with DPX. This standard H&E staining technique was employed to assess the general histoarchitecture of the ovarian tissue³³. For follicle counting, every 5th section was considered for quantitative analysis. Follicles were staged according to established morphological criteria^34–36. To avoid repeated counting of the same follicle across adjacent sections, only follicles with a visible oocyte nucleolus were included³⁷. Follicles were reported as absolute counts per ovary (mean ± SEM). The observer was blinded to group allocation during analysis.

miRNA–mRNA interaction modelling

The thermodynamic stability of miRNA–mRNA interactions was assessed using RNAfold (http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi), which predicts secondary structures and minimum free energy (MFE) values³⁸. Mature miRNAs and 3′UTR target sequences were sourced from miRBase and Ensembl. More negative MFE values indicated greater duplex stability, supporting the likelihood of post-transcriptional regulation.

miRNA–mRNA docking

To evaluate interactions between selected miRNAs and their mRNA targets, docking simulations were performed using the HADDOCK 2.4 web server (https://wenmr.science.uu.nl/haddock2.4).Input sequences of mature miRNAs and corresponding mRNA 3′UTRs were retrieved from public databases. Docking involved energy minimization and refinement, and complexes were scored using HADDOCK score, Z-score, and RMSD. Top-ranked interactions, characterized by low HADDOCK scores and favourable Z-scores, were visualized using BIOVIA Discovery Studio (https://www.3ds.com/products/biovia/discovery-studio).

Statistical analysis

Normality of data distribution was assessed using the Shapiro-Wilk test. Group comparisons for variables such as body weight, age at vaginal opening, and gene expression (RT-qPCR) were performed using one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparisons test. For serum hormone levels (LH, FSH, and estradiol), a two-way ANOVA was conducted to evaluate the effects of both dietary group and time point (PND 28, 35, and 42), followed by Bonferroni’s post hoc test. All statistical analyses were conducted using GraphPad Prism version 9.0 (GraphPad Software, USA), and data are presented as mean ± standard error of the mean (SEM). A p-value < 0.05 was considered statistically significant.

Results

Macronutrient-rich diets differentially modulate body weight gain and advance pubertal timing

Early exposure to different macronutrient compositions during the prepubertal period (PND 21–42) significantly affected growth and reproductive maturation. Energy-dense diets produced the most pronounced effects on body weight. By PND 35, HFD and HCD groups showed significantly higher weights (62.3 ± 1.8 g and 61.7 ± 1.5 g, *p < 0.05) compared to control (55.2 ± 1.3 g). At PND 42, final weights were HFD (89.4 ± 2.1 g, *p < 0.05), HCD (87.8 ± 1.9 g, *p < 0.05), CafD (83.2 ± 2.0 g, *p < 0.05), HPD (81.5 ± 1.8 g), and control (78.6 ± 1.7 g) described in Fig. 1a.

Fig. 1.

Diet-specific effects on growth, pubertal timing, and reproductive hormone profiles female rats. (a) Body weight progression from postnatal day (PND) 21 to 42 across dietary groups. High-fat diet (HFD) and high-carbohydrate diet (HCD) groups showed significantly higher body weights compared to control (*p < 0.05). Dashed vertical lines indicate mean vaginal opening (VO) timing for each group. The sexual maturation timeline below shows age at VO (PND) with statistical significance indicated by asterisks (***p < 0.001 vs. control). (b-d) Serum hormone concentrations measured at PND 28, 35, and 42. (b) Estradiol levels (pg/mL) showed progressive increases across all groups, with HFD, HCD (**p < 0.01) and CafD (*p < 0.05) exhibiting significantly elevated concentrations by PND 42. (c) Follicle-stimulating hormone (FSH, mIU/L) significantly increased in HFD and HCD (**p < 0.01) and (d) luteinizing hormone (LH, mIU/L) levels demonstrated significant increase in HFD, HCD (**p < 0.01) and CafD (*p < 0.05) compared to control, till PND 42. Data are presented as mean ± SEM (n = 6 per group). Statistical significance was determined by one-way ANOVA followed by Tukey’s post hoc test for VO timing and two-way ANOVA with Bonferroni’s post hoc test for hormone analyses. *p < 0.05, **p < 0.01 vs. control group.

Vaginal opening (VO) timing revealed diet-dependent acceleration of reproductive maturation. Controls reached VO at 35.4 ± 0.24 PND whereas energy-rich diets dramatically advanced maturation: HFD group at 30.4 ± 0.22 PND (***p < 0.001), HCD at 31.6 ± 0.18 PND (***p < 0.001), and CafD at 32.2 ± 0.20 PND. HPD showed minimal impact (34.6 ± 0.26 PND) also shown in supplementary Fig. 2.

Serum hormone profiling at PND 28, 35, and 42 revealed progressive HPG axis activation, with energy-dense diets producing the strongest responses. Estradiol levels increased across all groups but differed in magnitude. At PND 28, baseline levels were similar (15.2–17.8 pg/mL), nevertheless at PND 42, HFD and HCD groups showed dramatically elevated levels (82.7 ± 3.4 and 79.3 ± 3.1 pg/mL, **p < 0.01) along with HPD and CafD also showed significant elevation (61.16 ± 0.91 and 61.86 ± 0.85 pg/mL) as compared to control (45.2 ± 2.7 pg/mL) as shown in Fig. 1 (b). FSH concentrations followed similar patterns, at PND 42, HFD and HCD groups exhibited ~ 2.5-fold higher concentrations (3.1 ± 0.2 and 2.9 ± 0.2 mIU/L, **p < 0.01) than control (1.8 ± 0.1 mIU/L), CafD and HPD showed no significant change as shown in Fig. 1 (c). LH demonstrated the most significant changes, at PND 42, HFD animals showed markedly elevated concentrations (4.2 ± 0.3 mIU/L, **p < 0.01), followed by HCD (3.8 ± 0.3 mIU/L, **p < 0.01), both representing > 2-fold increase compared to control (1.9 ± 0.2 mIU/L). The CafD group showed a significant increase (*p < 0.05) compared to control, while the HPD group exhibited a non-significant elevation (Fig. 1d).

Distinct macronutrient diets induce unique hypothalamic miRNA profiles

To investigate the impact of macronutrient-specific dietary interventions on hypothalamic miRNA expression during the pubertal transition, small RNA sequencing was performed on hypothalamic tissue from juvenile female rats exposed to HFD, HCD, HPD, and CafD, and compared with age-matched controls. The raw reads alignment, filtering of non-miRNA small RNA, length base selection of mature miRNA are detailed in supplementary Tables 8–10. A total of 490 miRNAs were differentially expressed across all dietary groups when compared to controls. Among these, the HFD group exhibited the greatest number of DE miRNAs (n = 478), including 231 upregulated and 101 downregulated. CafD showed 473 DE miRNAs (208 upregulated, 98 downregulated), followed by HPD (477 DE miRNAs; 172 upregulated, 98 downregulated), and HCD (466 DE miRNAs; 208 upregulated, 94 downregulated) as shown in (Fig. 2a-b). Notably, all groups showed a higher number of upregulated than downregulated miRNAs, indicating a broad diet-induced activation of miRNA-mediated regulatory processes. Volcano plots (Fig. 2c-f) were generated to visualize the magnitude and significance of miRNA expression changes. A filtered, high-confidence subset of DE miRNAs was used for visualization, each meeting stricter fold change and adjusted p-value thresholds than those used for statistical testing.

Fig. 2.

Diet-specific differential expression of hypothalamic microRNAs in female rats. (a) Comparative analysis showing the number of upregulated (UP, light blue) and downregulated (DOWN, dark blue) miRNAs in each dietary group compared to control. Numbers above bars indicate total upregulated miRNAs per group. (b) Venn diagram illustrating the overlap of differentially expressed miRNAs across dietary interventions, with 460 miRNAs commonly altered across all groups and diet-specific signatures shown in non-overlapping regions. (c-f) Volcano plots depicting the magnitude and statistical significance of miRNA expression changes for each dietary group versus control: (c) High-protein diet (HPD), (d) Cafeteria diet (CafD), (e) High-fat diet (HFD), and (f) High-carbohydrate diet (HCD). Red dots represent significantly upregulated miRNAs, green dots represent significantly downregulated miRNAs, and black dots represent non-significantly changed miRNAs. The x-axis shows log₂ fold change and y-axis shows -log₁₀(p-value). Horizontal dashed lines indicate p < 0.05 significance threshold, and vertical dashed lines indicate fold change thresholds. HFD showed the most extensive miRNA reprogramming with 478 differentially expressed miRNAs, followed by HPD (477), CafD (473), and HCD (466).

Among the differentially expressed (DE) miRNAs, 23 candidates were shortlisted for detailed investigation based on prior literature linking them to HPG axis regulation, pubertal onset, and neuroendocrine function, as well as target prediction using the miRanda algorithm. This panel included members of the let-7 family (let-7a-5p, let-7a-2-3p, let-7b-3p), miR-30b, miR-375, miR-29a, miR-29b, miR-132, miR-212, miR-9a, miR-7a, and others (Fig. 3a).

Fig. 3.

Diet-specific differential expression of hypothalamic miRNAs in juvenile female rats. (a) Venn diagram showing the overlap between total differentially expressed (DE) miRNAs (n = 490) and puberty-related DE miRNAs (n = 23) identified across all dietary groups. (b-e) Heatmaps displaying the expression patterns of 23 puberty-associated miRNAs in each dietary group compared to control: (b) high-protein diet (HPD), (c) cafeteria diet (CafD), (d) high-fat diet (HFD), and (e) high-carbohydrate diet (HCD). Each heatmap shows hierarchical clustering of samples with normalized expression values represented by color intensity. Individual miRNA names are listed on the right side of each heatmap, with samples clustered by dietary treatment group.

The let-7 family miRNAs were particularly prominent across diets. Let-7a-5p, let-7a-2-3p, and let-7b-3p were upregulated in response to HFD, CafD, and HCD. These miRNAs target genes such as Hmga2 and C-Myc, implicated in cellular growth and developmental timing. Although Hmga2 has not been directly linked to puberty, its regulation by let-7 is well-established and may contribute to hypothalamic maturation. miR-30b, was significantly upregulated in the HFD and CafD groups, potentially facilitating earlier activation of GnRH signalling. Similarly, miR-132-3p and miR-212-3p, both involved in synaptic plasticity and hormonal feedback, were downregulated across all diets except HPD. miR-375, targeting transcriptional regulators such as Tle4 and Sp1, also showed reduced expression under HFD and CafD conditions.

Other diet-responsive miRNAs included miR-29a-3p and miR-29b-3p, which were consistently upregulated across HFD, HCD, and CafD, and are predicted to target Tbx21, a gene involved in neuroimmune and hormonal signalling. miR-9a-5p, predicted to regulate Foxl1 and Lin28, was notably upregulated in HFD and CafD groups, while miR-7a, a neuroendocrine regulatory miRNA expressed in POMC and LepR neurons, was enriched in CafD-fed animals.

To visualize the expression patterns of these 23 puberty-associated miRNAs, heatmaps were generated using normalized expression values. Hierarchical clustering clearly segregated samples by dietary group, revealing both convergent and divergent regulatory patterns (Fig. 3b-e). In the HPD group, several miRNAs (miR-29c-3p, miR-29b-3p, let-7c-5p, miR-9a-5p) were downregulated, while others (miR-375-3p, miR-30b-5p, miR-132-3p, let-7a-1-3p, miR-505-3p) were upregulated. CafD showed the reverse trend: miR-29 family and let-7 miRNAs were upregulated, whereas miR-30b-5p, miR-375, miR-132, and miR-212 were suppressed. HFD induced a robust shift with upregulation of miR-29a/b/c, let-7a, miR-9a, and downregulation of miR-30b, miR-132, miR-375, and miR-200c. HCD showed both overlapping and unique responses, with upregulation of miR-29 family members and let-7, and downregulation of miR-132, miR-212, and miR-429.

Expression of puberty-related genes reflects miRNA-mediated regulatory shifts

To investigate the molecular mechanisms through which early-life dietary composition influences pubertal timing, we analysed the expression of key hypothalamic miRNAs and their predicted or validated mRNA targets. A focused panel of miRNAs known to regulate the HPG axis was examined across all dietary groups. These included miR-30b, let-7a, miR-137, miR-29, miR-199, miR-375, and miR-155, selected based on prior literature and target prediction algorithms (Fig. 4a-p).

Fig. 4.

Diet-specific modulation of hypothalamic miRNAs and their target genes.

RT-qPCR validation of selected miRNAs and their predicted target genes in hypothalamic tissue from rats fed different macronutrient-rich diets from PND 21–42. (a-p) Expression levels of puberty-associated miRNAs: miR-30b, miR-199, miR-29, miR-137, miR-155, and miR-375. (g-m) Expression levels of the target genes involved in HPG axis regulation: Mkrn3, p38 (Mapk14), Tbx21, Kiss1, Gnrh, Cebpb, and Zeb1 along with mTOR, AMPK, Sirt1. Data are presented as the mean ± SEM (n = 6 per group). Gene expression was normalized to that of GAPDH, and miRNA expression was normalized to that of U6 snRNA. Statistical significance was determined by one-way ANOVA followed by Tukey’s multiple comparison test. *p < 0.05, **p < 0.01 vs. control group. Dietary groups: Control (standard chow), high-protein diet (HPD), cafeteria diet (CafD), high-fat diet (HFD), high-carbohydrate diet (HCD).

Quantitative RT-PCR revealed that miR-30b, was significantly upregulated in both HFD (2.146 ± 0.118; *p < 0.05) and HCD (2.085 ± 0.129; *p < 0.05), consistent with a concurrent downregulation of Mkrn3 expression in these groups (HFD: 0.457 ± 0.015; **p < 0.01, HCD: 0.619 ± 0.048; *p < 0.05). Similarly, miR-155, predicted to target Cebpb and Gnrh1, was significantly elevated in HFD (3.259 ± 0.198; *p < 0.05) and HCD (2.764 ± 0.307; *p < 0.05), aligning with reduced Cebpb expression and increased Gnrh1 transcript levels (both HFD and HCD: 2.491 ± 0.1; **p < 0.01). miR-199, a putative repressor of Kiss1, was downregulated in HFD (0.401 ± 0.028; **p < 0.01), while Kiss1 expression was strongly upregulated in the same group (4.127 ± 0.114; **p < 0.01), and moderately in HCD (3.735 ± 0.158; *p < 0.05), further supporting a de-repression mechanism. miR-137, showed significant upregulation in HFD (2.833 ± 0.132; *p < 0.05) and HCD (2.714 ± 0.120; *p < 0.05). Notably, the let-7 family, including let-7a, was broadly upregulated across dietary groups, with implications for suppression of Hmga2 and acceleration of neuronal differentiation, although Hmga2 expression was not directly assessed in this study. miR-29, targeting Tbx21, was significantly downregulated in HFD (0.309 ± 0.061; *p < 0.05) and HCD (0.319 ± 0.058; *p < 0.05), while Tbx21 showed corresponding upregulation (HFD: 2.581 ± 0.222; **p < 0.01; HCD: 2.188 ± 0.127). A similar inverse relationship was observed for miR-375 and its target Sp1, both of which were downregulated in HFD and HCD, supporting the notion that additional diet-responsive transcriptional regulators are modulated via post-transcriptional repression.

Additional targets such as Zeb1, implicated in neuroendocrine differentiation, were downregulated in HFD and HCD (HFD: 0.430 ± 0.095, **p < 0.01; HCD: 0.547 ± 0.064, *p < 0.05), corresponding with the upregulation of its predicted regulatory miRNAs (miR-200 and miR-9a). Likewise, Mapk14, a kinase linked to cellular stress and metabolic signalling, showed progressive upregulation across diets (HFD: 3.289 ± 0.130; **p < 0.01), though a direct regulatory miRNA was not identified. A marked reduction of Sirt1 transcript levels in both HFD and HCD groups, (HFD: 0.50 ± 0.04, **p < 0.01; HCD: 0.55 ± 0.05, *p < 0.05). Ampk, a key energy sensor kinase, was also significantly downregulated in both HFD and HCD (HFD: 0.55 ± 0.05, **p < 0.01; HCD: 0.60 ± 0.05, *p < 0.05) relative to controls. In contrast, mTOR expression exhibited robust upregulation under both HFD and HCD conditions (HFD: 1.80 ± 0.12, *p < 0.05; HCD: 1.75 ± 0.11, *p < 0.05), far exceeding baseline levels.

Ovarian weights were significantly higher in all dietary groups (CaFD, HFD, HCD) compared with control (Supplementary Table 11). Follicle staging revealed a reduction in primordial and primary follicles in dietary groups, accompanied by a relative increase in secondary and antral follicles. The number of Graafian follicles and Corpora lutea was also greater in the HFD and HCD groups compared with control, consistent with advanced folliculogenesis and ovulatory activity. Atretic follicles were modestly elevated across dietary groups. Representative H&E sections are provided in Supplementary Fig. 3.

Functional enrichment of miRNA targets reveals puberty-relevant pathways

To explore the biological relevance of diet-induced changes in hypothalamic miRNA expression, functional enrichment analyses were performed on predicted mRNA targets using GO and KEGG pathway mapping. These analyses revealed that differentially expressed miRNAs across all dietary groups converge on key signalling pathways associated with pubertal timing, neuroendocrine activation, and synaptic plasticity.

GO enrichment analysis

GO biological process enrichment indicated strong representation of terms associated with neuronal communication, hormonal regulation, and epigenetic modulation. In the HFD and CafD groups, target genes were significantly enriched in processes such as “neuropeptide signalling pathway,” “glutamatergic synaptic transmission,” and “regulation of hormone secretion.” These functions align with known molecular mechanisms underlying activation of the HPG axis during puberty.

In contrast, HPD-specific targets were enriched in “TRKB receptor binding,” “MAP kinase phosphatase activity,” and “fat cell differentiation,” suggesting involvement of neurotrophin signalling and energy sensing pathways. The HCD group exhibited enrichment in pathways related to epigenetic remodelling and cellular morphogenesis, including “histone acetylation,” “morphogenesis of epithelium,” and “BMP signalling regulation.”

Across all diet groups, shared GO terms included “positive regulation of glucocorticoid receptor signalling” and “long-term synaptic plasticity,” indicating that the miRNA-mediated response to dietary input is broadly conserved and involves modulation of both stress pathways and neuronal adaptability, detailed in Fig. 5 (a-d).

Fig. 5.

Gene Ontology (GO) enrichment analysis of predicted miRNA targets across different dietary groups.

Bubble plots showing GO term enrichment for predicted targets of differentially expressed miRNAs in hypothalamic tissue from female rats fed distinct macronutrient-rich diets from PND 21–42. (a) High-protein diet (HPD), (b) Cafeteria diet (CafD), (c) High-fat diet (HFD), and (d) High-carbohydrate diet (HCD). The x-axis represents the negative log10 of adjusted p-values, indicating statistical significance of enrichment. The y-axis lists enriched GO terms related to biological processes, cellular components, and molecular functions. Bubble size corresponds to gene count (number of genes associated with each GO term), and colour represents GO terms class.

KEGG pathway analysis

KEGG enrichment further supported the role of miRNA target networks in pubertal regulation. Canonical signalling cascades enriched in all dietary groups included the gonadotropin-releasing hormone (GnRH) signalling pathway, mitogen-activated protein kinase (MAPK) signalling, phosphoinositide 3-kinase (PI3K)-Akt signalling, estrogen signalling, as well as oxytocin, prolactin, insulin resistance, and AMPK pathways. In the HFD and HCD groups, where the most extensive miRNA shifts were observed, enrichment extended to nutrient-sensing and metabolic pathways such as “fatty acid metabolism” and “adipocytokine signalling.” The HCD group also uniquely enriched pathways related to chromatin modification, including histone deacetylation and phospholipid signalling, reflecting potential epigenetic modulation of the hypothalamic environment.

Additionally, reproductive pathways such as “progesterone-mediated oocyte maturation” and “oocyte meiosis” were significantly enriched, indicating peripheral integration of central miRNA signals. Upstream neuronal regulators, including “cAMP signalling” and “calcium signalling,” were also prominent, suggesting miRNA involvement in neuroendocrine activation cascades, described in Fig. 6 (a-d).

Fig. 6.

KEGG pathway enrichment analysis of miRNA target genes across different dietary interventions in hypothalamic tissue. KEGG pathway enrichment analysis showing the top significantly enriched pathways (p < 0.05) for predicted target genes of differentially expressed miRNAs in juvenile female rats exposed to distinct macronutrient-rich diets from PND 21–42. (a) High-protein diet (HPD), (b) Cafeteria diet (CafD), (c) High-fat diet (HFD), and (d) High-carbohydrate diet (HCD). Bar length represents the number of target genes (counts) enriched in each pathway, while color intensity indicates statistical significance (-log₁₀(p-value)). Key reproductive and neuroendocrine pathways consistently enriched across energy-dense diets (HFD, HCD and CafD) included GnRH signalling, MAPK signalling, insulin resistance, estrogen signalling, and oxytocin signalling pathways. HPD showed distinct enrichment patterns with an emphasis on neurotrophin signalling and metabolic pathways. The analysis demonstrated diet-specific modulation of hypothalamic miRNA networks that converge on pathways critical for HPG axis regulation and pubertal timing.

In-silico validation and prediction analysis

The interaction between miR-30b and the 3′ untranslated region (UTR) of Mkrn3 yielded a predicted MFE of − 9.4 kcal/mol, indicating moderate thermodynamic stability of the duplex. HADDOCK docking simulations further supported this interaction, with a docking score of − 35.3 and a Z-score of − 2.2, suggesting a highly favourable and specific miRNA–mRNA complex. A similarly robust interaction was observed between let-7a-2-3p and its predicted target Hmga2, a gene implicated in developmental timing and neuronal differentiation. The duplex exhibited a highly negative MFE of − 23.1 kcal/mol, along with a HADDOCK docking Z-score of − 2.1, confirming a strong interaction potential.

The miR-137–Kiss1 interaction also demonstrated substantial duplex stability, with an MFE of − 30.0 kcal/mol and a HADDOCK Z-score of − 2.1. Although miR-137 expression was upregulated in the HFD group, its concurrent increase with Kiss1 mRNA suggests that other regulatory mechanisms may override its suppressive role under dietary stress. Similarly, miR-199a-3p was predicted to interact with Kiss1 (MFE = − 28.5 kcal/mol, Z = − 1.6), and its downregulation in HFD corresponded with a marked rise in Kiss1 transcript levels, reinforcing its potential functional impact. Additional structurally stable interactions were observed for miR-155 and Cebpb (MFE = − 7.45 kcal/mol, Z = − 1.9), as well as miR-29c-3p and Tbx21 (MFE = − 21.6 kcal/mol, Z = − 1.5), both of which demonstrated inverse expression relationships consistent with direct post-transcriptional repression in-vivo (shown in Fig. 7 (a-q) and supplementary Fig. 4–8), the scores are detailed in Table 1.

Fig. 7.

Structural modelling of miRNA-mRNA interactions reveals thermodynamically stable complexes involved in pubertal regulation. Three-dimensional ribbon structures show HADDOCK 2.4-predicted docking complexes between diet-responsive hypothalamic miRNAs and their target mRNA 3’ untranslated regions (UTRs). Each panel displays the optimal docked conformation for key miRNA-target pairs identified through differential expression analysis. miRNA sequences are represented in darker ribbons, while target mRNA 3’UTR sequences are shown in lighter ribbons. Red dotted circles highlight the predicted binding interfaces and seed region complementarity. Nucleotide positions are labelled in green text. The structural models demonstrate favourable binding energetics and geometric complementarity for functionally validated interactions.

Table 1.

Summarizes the thermodynamic and structural parameters of miRNA–mRNA interactions relevant to pubertal onset, predicted using RNAfold and modelled via HADDOCK 2.4 Docking simulations. For each miRNA–target pair, the Z-score (a measure of statistical significance of Docking), HADDOCK score (indicative of binding affinity; more negative values suggest stronger interactions) shown as mean ± SD, and RMSD (root-mean-square deviation, reflecting conformational stability and consistency among docked structures), shown as mean ± SD are provided.

miRNA	Target	Z-Score	HADDOCK Score ± SD	RMSD ± SD
rno-mir-7a-2-3p	Glg1	-1.4	51.4 ± 5.2	5.8 ± 0.6
rno-mir-7a-2-3p	Bmp	-2.1	-32.7 ± 4.2	2.3 ± 1.3
rno-mir-30b-5p	Mkrn3	-2.2	-35.3 ± 3.8	2.7 ± 1.9
rno-mir-155-5p	Cebpb	-1.9	-36.4 ± 2.3	2.6 ± 1.6
rno-mir-155-5p	Gnrh	-1.0	-20.9 ± 1.9	12.8 ± 0.2
rno-mir-137-5p	Kiss1	-2.1	-30.0 ± 3.7	2.1 ± 1.2
rno-mir-199a-3p	Mapk	-2.0	-20.8 ± 6.2	15.0 ± 0.7
rno-mir-199a-3p	Kiss1	-1.6	-28.5 ± 3.4	3.4 ± 2.0
rno-let-7a-2-3p	Hmga2	-2.1	-23.1 ± 1.6	12.3 ± 0.9
rno-mir-29c-3p	Tbx21	-1.5	-21.6 ± 5.1	5.7 ± 3.7
rno-mir-200a-5p	Zeb1	-1.5	-25.9 ± 8.7	3.3 ± 1.9
rno-mir-200b-3p	Zeb1	-1.6	-21.9 ± 3.4	2.4 ± 1.9
rno-mir-200c-3p	Zeb1	-1.3	-17.1 ± 6.1	11.3 ± 0.5
rno-mir-9a-5p	Foxl	-1.5	-27.3 ± 5.7	10.3 ± 0.4
rno-mir-429	Zeb1	-1.7	-29.0 ± 12.7	3.2 ± 2.3
rno-mir-375-3p	Sp1	-1.3	-18.7 ± 2.0	13.9 ± 0.4
rno-mir-505-3p	Srsf1	-1.6	-21.1 ± 2.4	12.2 ± 0.3

Discussion

Pubertal development is a complex, finely orchestrated neuroendocrine process sensitive to early-life nutritional cues³⁹. This study aimed to elucidate how distinct macronutrient-rich diets influence pubertal timing through hypothalamic miRNA regulation in female rats. By integrating small RNA transcriptomics, gene expression profiling, in-silico miRNA–mRNA interaction analysis, and physiological outcomes such as vaginal opening and ovarian maturation, we reveal a coordinated, diet-specific modulation of the hypothalamic molecular landscape. These findings advance our understanding of the epigenetic mechanisms by which nutritional environments modulate the HPG axis, ultimately affecting the onset of puberty.

Early exposure to macronutrients significantly modulated body growth and timing of reproduction, with energy-dense diets, especially HFD and HCD, resulting in higher body weight as well as considerably earlier vaginal opening. These findings are consistent with the idea that early onset of puberty is not simply a consequence of overall energy intake, but rather more specifically of diet composition, where surplus amounts of fat and carbohydrate serve as strong metabolic signals to activate HPG axis^6,40. The CafD group, even with intermediate body growth, also demonstrated premature vaginal opening, inferring that palatability as well as energy density can also impact pubertal timing via neuroendocrine sensitization. Contrasting with these outcomes, HPD animals had the smallest body-weight gain coupled with only a moderate advancement in vaginal opening age, suggesting high protein feeding does not send the identical permissive signal for pubertal progression⁴¹. These phenotypic patterns were complemented by differential hormonal responses. HFD and HCD groups had markedly higher levels of LH, FSH, and estradiol on PND 42, implying strong central and peripheral activation of the reproductive axis. CafD animals had a similar but blunted course. HPD-fed animals, on the other hand, had only modest elevations in hormone levels, consistent with protein-rich diets being less capable of activating neuroendocrine maturity. The unexpected outcomes observed in the cafeteria diet group may be attributable to the relatively short duration of the experimental intervention. Our results support the hypothesis that macronutrient composition, particularly fat and carbohydrate enrichment, may differentially influence pubertal timing via alterations in hypothalamic miRNA expression.

Small RNA sequencing revealed that among the dietary groups, HFD, HCD and CafD induced the most extensive modulation, with over 490 miRNAs differentially expressed in each case, reflecting the transcriptional plasticity of the hypothalamus in response to metabolic stimuli. HPD-induced changes were less pronounced, with fewer high-magnitude shifts in miRNA expression, suggesting a subtler regulatory impact. Notably, a consistent trend was observed across all experimental diets as seen in the volcano plots, upregulated miRNAs outnumbered downregulated ones, suggesting that nutritional environments may act as potent epigenetic modulators during developmental windows, with miRNAs serving as key molecular intermediaries.

Among the most prominent findings was the consistent upregulation of miR-30b in the HFD and HCD groups, while HPD and CafD were mildly upregulated. This miRNA has been experimentally validated to target Mkrn3, a gene that encodes an upstream repressor of pubertal onset through suppression of Gnrh1 release¹⁸. Concordantly, we observed a robust downregulation of Mkrn3 mRNA in these same dietary groups, the observed inverse relationship between miR-30b and Mkrn3 expression suggests a potential mechanism through which nutritional signals may modulate pubertal timing^13,19. Interestingly, miR-137, a well-established repressor of pubertal function that binds to the 3’-UTR regions of Kiss1, was upregulated⁴². This elevation diverges from the expected increase in Kiss1 mRNA expression suggesting possible compensatory mechanisms that may attempt to override the repression. One such possibility is through the buffering capacity of RNA-binding proteins that may sequester the miRNA function and still permit translation of the target mRNA⁴³. It should be noted that not all miRNA–target pairs exhibited strict inverse expression relationships. This is consistent with previous reports showing that miRNAs often act as fine-tuners rather than simple repressors, and their effects may depend on compensatory feedback, developmental stage, or cell-type context^44–46. Thus, the concurrent upregulation of miR-137 and Kiss1 in our study may reflect such context-dependent modulation rather than direct linear repression. Moreover, miR-29 family targets Tbx21 that directly activates Gnrh1 transcription or via the activation of Dlx1, which in-turn upregulates Gnrh1^47,48. Therefore, the downregulated expression of miR-29 and the release of transcriptional repression of Tbx21 leading to its increased expression, further support the effect HFD and HCD group has on miRNA expression. In parallel, miR-375, a miRNA implicated in neuronal differentiation and transcriptional regulation, was significantly suppressed in energy-dense diet groups⁴⁹. Its target gene, Sp1, is involved in hormonal gene regulation, and while not directly measured in this study, suppression of miR-375 likely contributes to the derepression of its downstream pathways^49,50. A similar inverse trend was observed for miR-199, which was downregulated in HFD animals and is predicted to target Kiss1⁵¹. In this context, reduced miR-199 expression likely facilitated the robust upregulation of Kiss1, further supporting HPG axis activation. Zeb1, a transcriptional repressor, was significantly downregulated in the HFD and HCD groups, aligning with increased expression of miRNAs that relieve transcriptional inhibition and promote cellular differentiation. Mapk14, which encodes the stress-activated p38 MAP kinase, showed a progressive increase across energy-dense diets, consistent with its role in cellular signalling during hypothalamic remodelling. Studies have also explored other miRNAs that are indirectly involved in pubertal function in rodents, including miR-505-3p that halts the transcription of its target srsf1 gene further increasing the potential for revealing multi-tiered regulatory pathways⁵². The observed downregulation of Sirt1 and AMPK alongside upregulation of mTOR in HFD and HCD groups is consistent with earlier findings that obesogenic diets suppress cellular energy-sensing pathways while enhancing anabolic signalling^53–55. Reduced Sirt1–AMPK activity and concomitant activation of mTOR have been linked to impaired metabolic flexibility and accelerated hypothalamic aging, thereby predisposing to obesity and neuroendocrine dysregulation. These central molecular and hormonal changes were accompanied by marked alterations in ovarian histology. Specifically, animals exposed to HFD and HCD displayed a greater number of tertiary follicles and corpora lutea, consistent with advanced follicular development and ovulation. These findings align with elevated LH, FSH, and estradiol levels, indicating both central and peripheral activation of the reproductive axis⁵⁶. The histological evidence supports the notion that hypothalamic miRNA changes may contribute not only to upstream GnRH activation but also to downstream ovarian maturation, completing the cascade of pubertal progression⁵⁷. Goto et al.⁵⁸ recently demonstrated that dietary cues rapidly influence pubertal onset via an AgRP- kisspeptin circuit, providing a neural substrate for metabolic regulation of reproduction. In parallel, our prior work in the same model showed that dietary composition alters hypothalamic Kiss1, Kiss1r, Lepr, Pomc, and Mkrn3 expression, with protein-level validation⁵⁶. The present study extends this framework by demonstrating that hypothalamic miRNA–mRNA networks are also diet-sensitive. How this layer of post-transcriptional regulation integrates with AgRP–kisspeptin circuitry remains an important avenue for future study.

The in-silico modelling offered key mechanistic information supplementary to expression data, with structural evidence supporting the miRNA–mRNA interactions predicted to mediate nutritional programming towards puberty. Consistent agreement between high thermodynamic stability (negative MFE values) and positive docking parameters (HADDOCK scores and Z-scores) highlights the bio-likelihood of these regulatory processes. The miR-30b–Mkrn3 interaction showed favourable docking energy and thermodynamic stability, supporting its plausibility as a direct post-transcriptional regulatory interaction. In parallel, predicted interactions between Kiss1 and miR-137, as well as between Gnrh1 and miR-155, imply that the transcriptional alterations are supported by direct pairing at a molecular level, rather than by secondary modifications. While not all expression patterns displayed perfectly inverse correlations, co-upregulation between miR-137 and Kiss1 being one example, the docked data indicate potential complexity in such a regulatory interaction, including cooperative or context-dependent behavior. Additionally, let-7a’s strong docking with Hmga2, as well as miR-29 with Tbx21, further establishes evidence for diet-sensitive, miRNA-regulated control over hypothalamic developmental timing as well as neuroendocrine competence. These structural analyses support the plausibility of the predicted miRNA–mRNA interactions and suggest their potential involvement in diet-induced changes to hypothalamic gene regulation and plasticity, although functional validation in vivo remains necessary to confirm these roles.

Functional enrichment of HPG axis miRNA targets demonstrated key biological pathways between early nutrition and pubertal regulation. Gene Ontology enrichment highlighted processes integral to hypothalamic function, including neuropeptide signalling, synaptic transmission, as well as hormonal regulation- most evident in HFD and CafD groups. These pathways directly contribute to GnRH neuron activation, supporting the implication of miRNA modulated mechanisms in HPG axis development. Interestingly, enrichment specific to HCD in chromatin remodelling, as well as in morphogenesis, points towards an epigenetic level of hypothalamic plasticity elicited by carbohydrate-dense diets. HPD, on the other hand, was enriched in signalling for neurotrophin-related pathways and fat cell differentiation, suggesting a divergent, perhaps growth-oriented response with minimal pubertal involvement. Commonly overrepresented GO terms between all diets like glucocorticoid receptor signalling, as well as long-term synaptic plasticity suggest conserved endocrine adaptation to metabolic stimuli. KEGG pathway analysis supported these observations with consistent enrichment across groups for GnRH, MAPK, PI3K-Akt, and estrogen signalling pathways, key regulators of reproductive axis initiation. Interestingly, HFD and HCD also enriched metabolic as well as nutrient-sensing pathways (adipocytokine signalling), highlighting the convergence of energy homeostasis with reproductive development. Supplemental enrichment in pathways of oocyte maturation and cAMP/calcium signalling implies that nutritional modulation of hypothalamic miRNAs has its impact on central as well as peripheral targets involved in reproduction, uniting the epigenetic platform connecting nutrition with pubertal initiation.

This study integrates dietary interventions with miRNA sequencing, mRNA expression analysis, hormonal profiling, ovarian histology, and structural modelling to explore how early-life nutrition may influence pubertal timing. The inclusion of diverse macronutrient-specific diets and in-silico prediction of miRNA–mRNA interactions provide a multidimensional view of potential regulatory mechanisms, while highlighting the need for functional validation. This study is limited by its observational design and lack of functional validation of miRNA–mRNA interactions in vivo. The relatively rapid effects observed following dietary exposure are best interpreted as acute modulation of established hypothalamic pathways rather than stable de novo epigenetic reprogramming. Moreover, the short duration of the intervention further supports that these findings reflect transient nutritional influences on puberty-related pathways. Use of a grain-based chow diet, which, despite its common use in rodent research, contains variable phytoestrogen and fibre levels; future studies employing purified, open-formula diets will be necessary to isolate macronutrient-specific effects. Finally, as the in-silico predictions presented here are hypothesis-generating, functional validation through approaches such as 3′UTR luciferase reporter assays will be essential to confirm the biological relevance of the identified miRNA–mRNA interactions. While structural modelling and qPCR provide supportive evidence, further studies using gene knockdown or overexpression models are needed to confirm causal roles. Additionally, findings in rats may not fully extrapolate to human pubertal biology.

Conclusion

Early-life dietary composition appears to influence pubertal timing by modulating hypothalamic miRNA networks, underscoring the importance of nutritional quality during critical developmental windows. High-fat and high-carbohydrate diets accelerated puberty, as reflected by earlier vaginal opening, increased gonadotropin and estradiol levels, and advanced ovarian maturation. These phenotypic changes were paralleled by significant alterations in the expression of miRNAs such as miR-30b, let-7a, miR-137, miR-29, miR-199, and miR-155, many of which showed inverse relationships with target genes (Mkrn3, Hmga2, Kiss1, Tbx21, Gnrh, and Cebpb). Structural modelling further supported the functional relevance of these miRNA–mRNA interactions. Collectively, the findings position hypothalamic miRNAs as central mediators of diet-induced neuroendocrine maturation and suggest that early nutritional environments may modulate reproductive development via hypothalamic miRNA networks.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Harsh Shah: Methodology, Formal Analysis, Investigation, Visualization, Data curation, Writing – Original Draft. Sripriya Bulusu and Nehareeka Dan: Methodology, Formal Analysis, Data curation. Hetvi Shah: In-silico analysis. Ankita Salunke: Methodology and Investigation AV Ramachandran: Writing–Review & Editing, Supervision. Parth Pandya: Conceptualization, Methodology, Writing – Review & Editing, Supervision.

Funding

This research received no external funding and was conducted using the authors’ personal resources and institutional support.

Data availability

The datasets generated during and/or analysed during the current study are available in the NCBI BioSample repository: SAMN47502131 (https://www.ncbi.nlm.nih.gov/biosample/47502131),SAMN47502132 (https://www.ncbi.nlm.nih.gov/biosample/47502132),SAMN47502133 (https://www.ncbi.nlm.nih.gov/biosample/47502133),SAMN47502134 (https://www.ncbi.nlm.nih.gov/biosample/47502134),SAMN47502135 ( https://www.ncbi.nlm.nih.gov/biosample/47502135 ).

Declarations

Competing interests

The authors declare no competing interests.

Ethics declarations

All experimental procedures with animals followed the ethical standards of the Institutional Animal Ethics Committee (IAEC) of the Maharaja Sayajirao University of Baroda, under protocol number MSU-Z/IAEC08/13-2024. Procedures complied with ARRIVE guidelines and institutional and national regulations for laboratory animal care.

Declaration of generative AI

The authors used Grammarly to assist with grammar and language checks during the preparation of this work, and after reviewing and editing the content, take full responsibility for the final version of the manuscript.