Comprehensive androgen-dependent transcriptome analysis in human genital tissue

Comprehensive androgen-dependent transcriptome analysis in human genital tissue | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comprehensive androgen-dependent transcriptome analysis in human genital tissue Radhika Sivaprasad, Kristian Händler, Almuth Caliebe, Malte Spielmann, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7083899/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Nov, 2025 Read the published version in BMC Genomics → Version 1 posted 11 You are reading this latest preprint version Abstract Background Androgen signalling through the androgen receptor (AR) is crucial for male genital development. Disruptions in this pathway are associated with androgen insensitivity syndrome (AIS), which is typically caused by mutations in the AR gene, although the underlying genetic mechanisms remain unknown in many cases. To better understand androgen-dependent transcriptional changes in human genital tissue, we performed transcriptomic profiling of foreskin- and scrotum-derived human genital skin fibroblasts (GSFs) treated with dihydrotestosterone. Results Differential gene expression analysis revealed 409 and 260 reproducibly up-regulated genes in foreskin- and scrotum-derived GSFs, respectively. GSFs from individuals with complete androgen insensitivity syndrome, carrying inactivating mutations in the AR gene, showed no reproducible androgen response. Androgen response element motif scanning confirmed direct AR binding in key up-regulated genes, including AOX1 , APOD , FKBP5 , and FAM107A . Gene ontology analysis revealed enrichment in pathways related to neuronal, muscle, cardiovascular, and sex development. Conclusion Identifying new AR target genes broadens the current understanding of androgen signalling and aids in better understanding the aetiology of AIS, and other androgen-related conditions. Androgen Receptor Androgen Insensitivity Syndrome Transcriptional Regulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Androgens play an essential role in the development and functional maintenance of male reproductive tissues. Their physiological effects are mediated through the androgen receptor (AR), a 110-kDa protein belonging to the nuclear receptor family of ligand-activated transcription factors [ 1 ]. Upon binding of testosterone (T) or the more potent androgen dihydrotestosterone (DHT), cytoplasmic AR translocates into the nucleus and binds to androgen-responsive DNA elements (AREs), thereby regulating the transcription of androgen-dependent genes. Changes in this pathway are associated with androgen insensitivity syndrome (AIS) [ 2 , 3 ]. AIS is an X-linked recessive condition and a common cause of 46,XY differences of sex development (DSD). The phenotype varies from female external genitalia in the complete form (CAIS) to male external genitalia with infertility and/or gynecomastia in the mild form (MAIS). Partial androgen insensitivity syndrome (PAIS) exhibits a broad spectrum of undervirilized male external genitalia ranging from isolated micropenis to severe hypospadias [ 2 ]. AIS is classically caused by disruptive mutations in the AR gene and the vast majority of CAIS individuals carry hemizygous mutations in the AR . However, an AR mutation can be found in less than 40% of individuals diagnosed with PAIS, suggesting that factors outside the AR may contribute to a similar phenotype [ 4 ]. Measuring DHT-induced expression of the endogenous AR-target gene apolipoprotein D ( APOD ) in genital skin fibroblasts (GSFs) from individuals with the suspected diagnosis AIS but no mutation in the AR gene revealed a group of GSFs with reduced AR activity, termed AIS type II [ 5 ]. Recently, the first genetic cause of AIS type II was described, identifying the formin DAAM2 as a cofactor of the AR, necessary for its transcriptional activity [ 6 ]. Another possible cause of AIS type II could be changes in transcriptional targets of the AR. Microarray-based studies aimed at identifying DHT-induced AR target genes in GSFs, revealed very few significantly up-regulated genes[ 7 , 8 ] one of which, APOD , has been validated in a large cohort [ 5 ]. Using optimized endogenous AR-activity assay conditions, we performed mRNA sequencing on untreated and DHT-treated GSFs derived from six foreskin biopsies and six scrotum biopsies of male controls. We also included GSFs from four CAIS individuals, who lack AR activity, serving as ideal controls to identify gene expression changes mediated by the AR. We show a comprehensive analysis of androgen-dependent transcriptional changes in human genital tissue, identify AR-target genes that are either tissue-specific or common to both tissues and discuss how these transcriptional changes can affect androgen-induced pathways. Results Tissue-specific and hormone-responsive gene expression patterns in GSFs To identify AR target genes in GSFs, we treated 12 male control cells (six from foreskin and six from scrotum) for 48 h and 72 h with either DHT or vehicle (EtOH). As an AR -negative control, we included GSFs from four individuals with CAIS carrying loss-of-function mutations in the AR (Supplementary file 1: Fig. S1 and Table S1 ). All samples were processed for mRNA sequencing and subsequent data analysis. Principal component analysis (PCA) of male control samples (Fig. 1 A) revealed a primary separation by tissue type (scrotum vs. foreskin), accounting for 50.8% of the variation, and, to a lesser extent, by treatment (DHT vs. EtOH), contributing 6.72% of variation. In CAIS samples (Fig. 1 B), separation was observed by tissue type (Labia Majora vs. Labia Minora), representing 59.9% of the variation. To gain a more detailed picture of gene expression variation, we visualized gene expression differences in a heatmap. As shown in Fig. 1 C, consistent with the PCA results, the most prominent separation in gene expression in male control samples was based on the tissue type. Within each tissue type, additional differences emerged based on treatment, with some regions showing higher expression in DHT-treated samples compared to EtOH-treated, and vice versa . Furthermore, the duration of treatment (48 h and 72 h) contributed to subtle shifts in expression patterns. In CAIS samples, gene expression was primarily separated by tissue type, with minor changes observed in expression patterns over time (Supplementary file 1: Fig. S2 ). Comparative gene expression analysis To investigate the biological basis of the observed clustering, differential gene expression analysis was performed by including all genes with a log2FC above or below zero (padj ≤ 0.05). Foreskin derived samples (GSF-F) displayed the most robust response, with 576 genes up-regulated and 565 down-regulated at 48 h, increasing slightly at 72 h to 602 up-regulated and 576 down-regulated genes. Scrotum-derived samples (GSF-S) also showed substantial changes, with 387 genes up-regulated and 400 down-regulated at 48 h, and this number increased at 72 h to 399 up-regulated and 495 down-regulated genes. In total, this resulted in 1141 and 787 differentially expressed genes (DEGs) at 48 h, and 1178 and 894 genes at 72 h, in GSF-F and GSF-S, respectively (Table 1 ). The majority of changes were small, with a median log2FC of 0.27 for GSF-F and 0.21 for GSF-S for up-regulated genes and a median log2FC of -0.23 for GSF-F and GSF-S for down-regulated genes (Fig. 2 ). In CAIS, three differentially expressed genes were identified in labia minora derived samples and five in labia majora derived samples at 72 h, while none were identified at 48 h (Table 1 ). The transcripts did not overlap with any differentially expressed genes in the male control cohort. The observation that nearly no androgen-dependent gene expression changes were observed in CAIS samples indicates that the transcriptional changes observed in male control samples were indeed AR-dependent. Table 1 Summary of DEGs in DHT- versus EtOH-treated GSFs across tissue types and time points Sample Condition (DHT vs EtOH) No. of. up-regulated genes No. of. down-regulated genes Total GSF-F_48 h 576 565 1141 GSF-F_72 h 602 576 1178 GSF-S_48 h 387 400 787 GSF-S_72 h 399 495 894 GSF-L.Min_48 h 0 0 0 GSF- L.Min _72 h 1 2 3 GSF-L.Maj_48 h 0 0 0 GSF- L.Maj _72 h 2 3 5 In GSF-F 409 genes (53.2%) were commonly up-regulated and 356 genes (45.4%) were commonly down-regulated at both 48 h and 72 h of treatment (Fig. 3 A, B and Supplementary file 1: Fig. S3 A, C). In GSF-S 260 genes (49.4%) were commonly up-regulated and 272 genes (43.7%) were commonly down-regulated (Fig. 3 A, B and Supplementary file 1: Fig. S3 B, D) at both time points. A total of 186 (19.6%) of genes were up-regulated at both timepoints in both tissues, while 147 genes (13.7%) were down-regulated (Fig. 3 A, B). For a more stringent analysis, only genes with a log2FC ≥ 0.5 or log2FC ≤ -0.5 and padj ≤ 0.05 were considered. This approach reduces false positives as well as indirect effects, allowing a focus on the most robustly regulated transcripts. In GSF-F, 56 genes (58.3%) were commonly up-regulated and 15 genes (44.1%) were commonly down-regulated (Fig. 3 C, D and Supplementary file 1: Fig. S4 A, C). In GSF-S, 37 genes (52.9%) were commonly up-regulated and 11 genes (39.3%) commonly down-regulated (Fig. 3 C, D and Supplementary file 1: Fig. S4 B, D). Across all conditions, 23 genes (18.4%) were commonly up-regulated and 3 genes (5.9%) were commonly down-regulated (Fig. 3 C, D). No DEGs with a log2FC ≥ 0.5 or log2FC ≤ -0.5 and padj ≤ 0.05 were observed in CAIS derived samples. The list of DEGs is provided in Supplementary file 2. Several genes showed a strong and consistent regulation in all conditions. Among the most, significantly up-regulated genes were AOX1 , FAM107A , CERS6 and APOD which appeared in multiple comparisons (Fig. 4 A-D). Other recurrently up-regulated genes included FAM105A , MYOCD and FKBP5 . Conversely, PRELP , and L1CAM appeared repeatedly among the down-regulated genes across various conditions and tissues (Fig. 4 A-D). We validated the DHT-induced changes in gene expression for six up-regulated genes ( STEAP4 , MYOCD , FAM105A , FAM107A , HSD11B1 , FKBP5 ) by quantitative PCR (qPCR) (Supplementary file 1: Fig. S5 and Supplementary file 3). AR-chromatin binding and binding motif scan within DEG regions In order to verify if the commonly up- and down-regulated genes are directly targeted by the AR, we screened publicly available AR chromatin immunoprecipitation sequencing (ChIPseq) data [ 9 , 10 ] for DHT-dependent AR-binding in the prostate cancer cell lines LnCaP and VCaP. Although these cells derive from a different tissue, we expected to see some overlap in AR-dependent transcription using the most robust AR target genes found in our analysis (those commonly up- or down-regulated at both time points in both tissues with a minimum log2FC ≥ 0.5 or ≤ -0.5). In the 23 up-regulated genes, 12 (52%) showed AR chromatin binding according to the ChIPseq data. No down-regulated gene showed AR chromatin binding. The majority of binding sites were intragenic with a few sites upstream the transcriptional start site (Table 2 ). We validated the binding site by scanning sites for the canonical AR binding site motif (AGAACANNNTGTTCT). At all sites high scoring motifs were found (p < 0.001). The complete list of genes and their associated AR binding sites is provided in Supplementary file 1: Table S2 . Table 2 AR Binding near DEGs in GSF-F/S with canonical AREs. TSS = transcriptional start site. Up-regulated genes (GSF-F and GSF-S at 48h and 72h) AR ChIPseq peak in LnCaP (distance to TSS in bp) AR ChIPseq peak in VCaP (distance to TSS in bp) Canonical AR binding site motif: AGAACANNNTGTTCT p-value/ q-value AOX1 + 80015 + 80015 AGAACAATCTGTTAG 4.01e-05 / 0.0104 APOD -485 -485 GGAACATGGAGTTCC 8.62e-05 / 0.0464 CCDC68 + 1927 + 1927 AGAACACAGTGTCCT 8.35e-07 / 0.000231 CD82 -932 -932 AGCACTGGTTGTTCT 9.95e-06 / 0.0232 CERS6 + 71232 + 71232 AGAACACTCTGTGCT 8.35e-07 / 0.001 ERCC6 + 34037 + 34037 AGAGCATGCTGTTTT 2.69e-05 / 0.0248 FAM105A + 7808 + 7808 AGGACACCGTGTGCT 4.49e-06 / 0.00344 FAM107A + 205 + 205 GGAACATCATGTCCA 0.000142 / 0.046 FKBP5 + 1682 + 1682 GGAACACGAGGTTCT 9.95e-06 / 0.00476 IMPA2 -4365, -4931 -4365, -4931 AGAAAAAGCTGATTT, TGGCCAGGCTGGTCT 0.000376 / 0.0899, 0.000524 / 0.089 KIF26B + 24860 + 24860 AGAACATCCTGTCCA 9.95e-06/ 0.00813 MYOCD + 15790 + 15790 AGAACAGTGTGTACC 9.95e-06 / 0.00889 Functional categorization and pathway enrichment of DEGs Gene Ontology Analysis (GOA) of all up-regulated genes (FDR < 0.05) revealed enrichment in several processes related to neurodevelopment, such as ganglion morphogenesis, across both foreskin and scrotum derived samples. Additionally, GO processes such as hemidesmosome assembly, lateral sprouting involved in mammary gland duct morphogenesis, regulation of prostatic bud formation and regulation of basement membrane organization were shared between the two groups (Fig. 5 A, B). In contrast, distinct sets of GO terms were enriched in each tissue. In GSF-F (Fig. 5 A), processes such as regulation of presynaptic membrane organization and gonadotrophin-releasing hormone neuronal migration to the hypothalamus were enriched. Meanwhile, GSF-S (Fig. 5 B) exhibited enrichment for processes such as relaxation of vascular associated smooth muscle and regulation of systemic arterial blood pressure. We also performed GOA on up-regulated genes with a log2FC of ≥ 0.5. In GSF-F biological processes related to bone tissue development or remodelling were significantly enriched (Fig. 6 A). Whereas, in GSF-S, signalling and cell communication were a prominent theme (Fig. 6 B). The list of all GO Biological Process terms is provided in Supplementary file 4. Discussion Androgens are essential for male genital differentiation, as demonstrated by individuals with androgen insensitivity syndrome, who often exhibit reduced or absent genital virilization at birth due to reduced or absent AR activity. While androgen-activated gene transcription drives key physiological changes during male embryonic development, these gene programs have not yet been fully understood in humans. In mice, androgen-dependent gene expression during male genital development has been studied by comparing male and female cell populations in the external genitalia during the critical sex differentiation window in the mouse embryo [ 11 ]. Given that for ethical reasons such experiments are not possible in humans, GSFs, deriving from an androgen sensitive tissue, represent a valuable research material. Although being terminally differentiated they still might reflect some of the developmental processes occurring during the critical time window where androgens act to induce male sex differentiation. Large-scale AR-dependent gene expression programs in GSF from male controls and CAIS individuals revealed distinct transcriptional profiles, suggesting androgen-dependent programming in these cells [ 12 ]. Two further studies used GSFs to identify androgen induced target genes through microarray analysis with the identification of APOD as a bona fide AR target. We here used mRNA sequencing to identify additional DHT-induced genes in both foreskin and scrotum derived GSFs and compared them to GSFs derived from CAIS individuals. Our study revealed a tissue specific response to DHT treatment, with foreskin derived GSFs showing a higher number of differentially expressed genes compared to scrotum derived GSFs. The majority of androgen-induced changes are, although being significant, subtle and might be secondary changes. Considering only changes with log2FC ≥ 0.5 or ≤ -0.5 foreskin derived fibroblasts showed 56 consistently up-regulated and 15 down-regulated genes, while in scrotal skin derived fibroblasts the numbers of DEGs were 37 and 11, respectively. Across all conditions, 23 genes were commonly up-regulated and 3 genes were commonly down-regulated, making them very robust AR-targets. No reproducible DHT-dependent transcriptional changes were observed in samples from CAIS individuals supporting the notion that the transcriptional changes identified in male control samples are indeed AR-dependent. Among the 23 commonly androgen-induced genes, several have previously been linked to androgen signalling. APOD is androgen-responsive in GSF, though its role in male genital development remains unclear [ 7 ]. FKBP5 is part of the HSP90 chaperone complex, a complex that keeps un-ligated AR in the cytoplasm [ 13 ]. Depletion of either FKBP5 or FKBP4 in prostate cancer cells reduces AR dimer formation, chromatin binding, and phosphorylation, suggesting defective AR signalling [ 14 ]. The AR, in turn, directly regulates the FKBP5 gene via a distal enhancer element indicating a regulatory feedback mechanism [ 15 ]. Monoamine oxidase A ( MAOA ) plays a significant role in prostate cancer progression and AR signalling. MAOA and AR form a positive feedback loop, with androgens inducing MAOA expression through AR binding to the MAOA gene, while MAOA enhances AR transcriptional activity [ 16 ]. RGCC and FAM107A were previously found to be DHT-regulated in foreskin derived fibroblasts [ 8 ] as well as neural stem cells [ 17 ]. Gene ontology analysis gives a broader picture about androgen induced biological pathways. In both tissue types GO terms related to sex differentiation are present, in GFS-F also the term “response to steroid hormone”, although these terms are not under the most enriched ones. Under the twenty most enriched terms in both GSF-F and GSF-S is “regulation of prostatic bud formation”. Prostatic buds originate from the urogenital sinus epithelium in the developing foetus. Androgens play a critical role in promoting prostatic bud development, including their elongation and branching [ 18 ]. In foreskin derived GSF, the most enriched GO terms converge on coordinated cellular processes for the development, organization, and regulation of complex tissues, especially regarding the nervous system, followed by the cardiovascular / vascular system. Of particular interest is the GO term “gonadotrophin-releasing hormone neuronal migration to the hypothalamus”, as gonadotrophin-releasing hormone from the hypothalamus activates gonadal steroid hormone synthesis and is negatively regulated through androgen signalling [ 19 ]. GO-terms derived from the more stringent analysis of genes up-regulated ≥ 0.5 log2FC relate to the formation and regulation of organs and tissues, particularly the skeletal (e.g., ossification and bone mineralization), followed by muscle, renal and nervous systems. Further enriched terms relate to cell signalling and cell motility. In scrotum derived GSF, the most enriched GO terms share common themes centred on the development, structural organization, and functional regulation particularly within the nervous, cardiovascular, and muscular systems overlapping partly with androgen induced biological processes found in GSF-F. In summary, although being terminally differentiated, androgen treated GSFs reveal transcriptional programs involved in development and differentiation. Interestingly, these programs include neuronal, renal, muscle and cardiovascular development, where the AR has been shown to be involved [ 20 – 24 ] Several AR-target genes identified here are also involved in prostate cancer progression. This study therefore helps towards a better understanding of androgen-dependent processes in genital as well as non-genital tissues. Conclusion Our study provides a comprehensive analysis of DHT-induced gene expression changes in genital skin fibroblasts derived from foreskin and scrotum. The identification of new AR target genes expands the current understanding of androgen signalling, providing a broader perspective on AR-mediated gene regulation during development. This helps to better understand the aetiology of AIS, especially AIS type II, as well as other androgen-related conditions. Materials and Methods Patient material Male control scrotum-derived genital fibroblasts (GSF-S) were obtained from fertile adult patients with typical external genitalia virilization who underwent vasectomy (n = 2) and from patients under the age of 18 who underwent orchidopexy due to maldescended testes (n = 4) but with typical external genitalia, i.e., no hypospadias. In addition, we used male control foreskin fibroblasts (GSF-F) from patients who underwent circumcision for cultural reasons or phimosis (n = 6) [ 5 ]. We also included GSFs from Labia majora (GSF-L.Maj) (n = 2) and Labia minora (GSF-L.Min) (n = 2) samples of CAIS individuals carrying loss-of-function mutations in the AR . The GSFs used and a visualisation of CAIS mutations can be seen in Supplementary file 1: Table S1 and Fig. S1 . Cell culture and hormone induction GSFs were cultured in phenol red free Dulbecco's modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (FBS, MaxSpec), 100 units/ml penicillin/streptomycin, 2 mM L-glutamine and 20 mM HEPES buffer (all purchased from Life Technologies) and incubated at 37°C in a 5% CO2 incubator. For hormone induction, cells were seeded in four 10 cm dishes: two dishes with a concentration of 2.8x10 5 cells for a 72 h hormone treatment and two dishes with a concentration of 3.5x10 5 cells for a 48 h hormone treatment. After 24 h, cells were washed three times with PBS (Life Technologies), and medium containing 0.1% charcoal-treated FBS was added to the cells. DHT (Sigma-Aldrich), dissolved in ethanol (EtOH) was added to two dishes at a final concentration of 10 nM, while the control dishes were treated with the same volume of ethanol. Cells were incubated for 48 h and 72 h at 37°C with 5% CO2, after which they were lysed in RNA-extraction buffer (RLT; Qiagen). Hence, each GSF line underwent four different experimental conditions: EtOH and DHT treatments at two time points (48 h and 72 h). RNA Extraction Total RNA was extracted using the RNeasy Mini Kit (Qiagen), including on-column DNase digestion (RNAse-Free DNase Set, Qiagen) to eliminate residual DNA, following the manufacturer’s protocol. RNA quantity and quality were measured with a Nanodrop Spectrophotometer and an Agilent 2100 Bioanalyzer using the RNA 6000 Nano Chip Kit (Agilent), respectively. Library Preparation and RNA Sequencing All RNA samples processed for mRNA sequencing had an RNA Integrity Number (RIN) score ≥ 8, as determined by the Agilent 2100 Bioanalyzer, indicating high-quality and intact RNA suitable for transcriptome analysis. Total RNA (1µg) was converted into sequencing libraries using the Illumina Stranded mRNA Prep Ligation kit (Illumina, Cat. No. 20040532). Sample-specific barcoding was achieved utilizing Illumina Unique Dual (UD) Set A index adapters, employing distinct dual indexes (I7-10 and I5-10) (Illumina, Cat. No. 20091655). The quality of the amplified cDNA was validated with the Bioanalyzer 2100 using the High Sensitivity DNA kit (Agilent), and the concentration was measured using the Qubit DNA HS Assay. High-quality DNA libraries were pooled equimolarly and a 650pM pool was sequenced using paired-end 200 bp reads on the NextSeq 2000 system (Illumina) with NextSeq 2000 P3 Reagents (200 cycles; Illumina, Cat. No. 20040560). Sequencing data conversion and demultiplexing were performed using bcl2fastq2 v2.20 (Illumina). Gene-level count matrices were generated from the FASTQ files using the community-driven nf-core/rnaseq pipeline v3.12.0 [ 25 ]. The pipeline included adapter trimming (TrimGalore v0.6.7), contamination removal (SortMeRNA v4.3.4 and BBMap-BBSplit v39.01), alignment (STAR 2.7.10a) to hg38, transcript-level quantification (Salmon v1.10.1), and comprehensive quality control (FastQC v0.11.9, RESeQC v3.0.1, dupRadar v1.28.0, and MultiQC v1.14). Transcript-level counts were converted to gene-level counts using tximeta-tximport v1.12.0. As the samples were processed in two separate sequencing runs (one for male control and one for CAIS samples), batch correction was applied to account for run-specific effects. The datasets were combined and processed together using Salmon (which includes STAR aligner support), ensuring consistent quantification across both batches. Differential Gene Expression Analysis Transcriptomic analysis was performed using Shiny-Seq [ 26 ], an RNA-sequencing analysis pipeline based on DESeq2. The analysis utilised a count matrix (summarising gene expression levels across samples) and a metadata table (describing sample attributes) as input data to compare gene expression levels between different experimental conditions. The dataset was normalized using the DESeq2 package with a filtering cut-off of 10 raw reads. For hierarchical clustering samples were classified based on a combination of tissue type, treatment type and incubation time for male control and CAIS. The composite condition “Tissue_Treatment_Time” was chosen for normalization to account for variation across these factors. To address batch effects, Surrogate Variable Analysis (SVA) [ 27 ] was applied, estimating ‘10’ surrogate variables for male control samples and ‘2’ for CAIS samples. For tissue-specific gene expression analysis, ‘5’ surrogate variables were estimated for scrotum/foreskin derived samples, and ‘1’ for Labia major/minora-derived samples. Differentially expressed genes in each tissue were identified by comparing DHT-treated versus ethanol-treated cells at 48 h and 72 h time points. Genes with log2 fold change (log2FC) > 0 were considered up-regulated, and those with log2FC < 0 were considered down-regulated, with a significance threshold of adjusted p-value (padj) ≤ 0.05. For a more stringent analysis, we selected DEGs with log2FC ≥ 0.5 or log2FC ≤ -0.5 and a padj ≤ 0.05. The list of DEGs is provided in Supplementary file 2. The distribution of DEGs was visualised using the MaGIC Volcano Plot Tool [ 28 ], which plots the magnitude of change (log2FC) against statistical significance (-log10 padj). Venn diagrams were created using Venny 2.1.0 [ 29 ]. Quantitative Real-Time PCR (qRT-PCR) Total RNA (500ng) was reverse transcribed using QuantiTect Reverse Transcription Kit (Qiagen). qRT-PCR was carried out using the QuantiTect SYBR Green master mix (Qiagen) with gene-specific primers, tested in duplicate for each sample. For the validation of the RNA-Seq results, six up-regulated genes ( MYOCD , FKBP5 , HSD11B1 , FAM105A , FAM107A , STEAP4 ) were selected for analysis. qRT-PCR was performed on samples from four male control individuals (GSF-F, n = 2; GSF-S, n = 2) and two CAIS individuals (L.Maj, n = 1; L.Min, n = 1), with both DHT- and EtOH-treated samples collected at 72 h. The housekeeping gene succinate dehydrogenase complex, subunit A ( SDHA ), was used to normalise the gene expression data. The relative expression of mRNA was calculated by the 2^−ΔΔCt method with normalization to SDHA . Primers for MYOCD , FKBP5 , and HSD11B1 were obtained from Qiagen and used according to the manufacturer’s instructions, while primers for FAM105A , FAM107A and STEAP4 were designed using Primer3 (Supplementary file 1: Table S3 ). ARE motif scanning Chromatin-immunoprecipitation-sequencing (ChIP-seq) data from GEO sources: GSM3148986 and GSM3148988 for ethanol and androgen treated LNCaP cells [ 9 ] and GSM1410768 and GSM1410785 for ethanol and androgen treated VCaP cells [ 10 ] were visualized using the Cistrome data browser and checked for androgen-induced AR-binding. The binding area was then screened for the canonical AR binding site motif (AGAACANNNTGTTCT) using the Find Individual Motif Occurrences (FIMO) software from MEME suite 5.5.7. Gene Ontology Analysis Gene Ontology enrichment analysis was performed using PANTHER [ 30 ] with significantly up- and down-regulated DEGs, as well as those with log2FC ≥ 0.5 or ≤ -0.5, applying a false discovery rate (FDR) threshold of 0.05. The resulting data was visualized using R Studio (R version 4.4.0 (2024-04-24 ucrt)) [ 31 ] to generate bar plots. Biological processes were sorted by fold enrichment from highest to lowest, and the top 20 terms were included in the plot. For genes with log2FC ≥ 0.5 or ≤ -0.5, the top 10 enriched pathways were plotted. The list of significantly enriched GO biological process terms is provided in Supplementary file 4. Declarations Ethics approval and consent to participate This study followed the Declaration of Helsinki. The study was approved by the Ethical Committee of the Medical Faculty of Kiel University (AZ: D415/11; Supplementary file 5). Written informed consent to participate was obtained from all of the participants in the study. We obtained written consent from the parents on behalf of the children/minors enrolled in this study. Consent for publication Not applicable Availability of data and materials Sequence data that support the findings of this study have been deposited to the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE300211). Competing interests none Funding The study has been funded by the German Research Foundation HO 6028/3-1 and SFB 1665/1 M02 to NH. Authors’ contributions NH designed the study. RS performed the experiments. RS, KH and NH analyzed the data. RS and NH drafted the manuscript. All authors reviewed and approved the final manuscript. Acknowledgements We would like to extend our sincere thanks to Mrs. Saranya Balachandran, Varun Sreenivas and Nathalie Kruse for their technical support. References Brinkmann AO, Klaasen P, Kuiper GGJM, van der Korput JAGM, Bolt J, de Boer W, et al. Structure and function of the androgen receptor. Urol Res. 1989;17(2):87–93. Mongan NP, Tadokoro-Cuccaro R, Bunch T, Hughes IA. Androgen insensitivity syndrome. Best Pract Res Clin Endocrinol Metab. 2015;29(4):569–80. Hornig NC, Holterhus PM. Molecular basis of androgen insensitivity syndromes. Mol Cell Endocrinol. 2021;523:111146. Ahmed SF, Bashamboo A, Lucas-Herald A, McElreavey K. 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FKBP51 Promotes Assembly of the Hsp90 Chaperone Complex and Regulates Androgen Receptor Signaling in Prostate Cancer Cells. Mol Cell Biol. 2010;30(5):1243–53. Maeda K, Habara M, Kawaguchi M, Matsumoto H, Hanaki S, Masaki T, et al. FKBP51 and FKBP52 regulate androgen receptor dimerization and proliferation in prostate cancer cells. Mol Oncol. 2022;16(4):940–56. Magee JA, Chang L, wei, Stormo GD, Milbrandt J, Direct. Androgen Receptor-Mediated Regulation of the FKBP5 Gene via a Distal Enhancer Element. Endocrinology. 2006;147(1):590–8. https://doi.org/10.1210/en.2005-1001 . Wei J, Yin L, Li J, Wang J, Pu T, Duan P, et al. Bidirectional cross-talk between MAOA and AR promotes hormone-dependent and castration-resistant prostate cancer. Cancer Res. 2021;81(16):4275–89. Quartier A, Chatrousse L, Redin C, Keime C, Haumesser N, Maglott-Roth A, et al. Genes and Pathways Regulated by Androgens in Human Neural Cells, Potential Candidates for the Male Excess in Autism Spectrum Disorder. 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Direct androgen receptor control of sexually dimorphic gene expression in the mammalian kidney. Dev Cell. 2023;58(21):2338–e23585. Patel H, Ewels P, Manning J, Garcia MU, Peltzer A, Hammarén R et al. nf-core/rnaseq: nf-core/rnaseq v3.18.0 – Lithium Lynx. Zenodo; 2024. https://doi.org/10.5281/zenodo.14537300 Sundararajan Z, Knoll R, Hombach P, Becker M, Schultze JL, Ulas T. Shiny-Seq: advanced guided transcriptome analysis. BMC Res Notes. 2019;12(1):432. Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012;28(6):882–3. Lemenze A. MaGIC-Analytics/magic-volcanoes: V1 release. Zenodo; 2024. https://doi.org/10.5281/zenodo.10845739 Oliveros JC. Venny: An interactive tool for comparing lists with Venn diagrams. CNB-CSIC: BioinfoGP; 2007. Mi H, Muruganujan A, Casagrande JT, Thomas PD. Large-scale gene function analysis with the PANTHER classification system. 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Supplementary Files supplementaryfile1.docx supplementaryfile2.xlsx supplementaryfile3.xlsx supplementaryfile4.xlsx supplementaryfile5.pdf Supplementaryinformation.docx Cite Share Download PDF Status: Published Journal Publication published 17 Nov, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 25 Aug, 2025 Reviews received at journal 13 Aug, 2025 Reviewers agreed at journal 04 Aug, 2025 Reviewers agreed at journal 01 Aug, 2025 Reviews received at journal 31 Jul, 2025 Reviewers agreed at journal 30 Jul, 2025 Reviewers invited by journal 16 Jul, 2025 Editor assigned by journal 16 Jul, 2025 Editor invited by journal 16 Jul, 2025 Submission checks completed at journal 15 Jul, 2025 First submitted to journal 15 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7083899","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486943325,"identity":"72cd5902-3ea9-41ca-9e54-ad95e9022378","order_by":0,"name":"Radhika Sivaprasad","email":"","orcid":"","institution":"University of Lübeck, University of Kiel, Lübeck and Kiel","correspondingAuthor":false,"prefix":"","firstName":"Radhika","middleName":"","lastName":"Sivaprasad","suffix":""},{"id":486943326,"identity":"46704213-bfeb-46e1-855e-8b95f5e21d5c","order_by":1,"name":"Kristian Händler","email":"","orcid":"","institution":"University of Lübeck, University of Kiel, Lübeck and Kiel","correspondingAuthor":false,"prefix":"","firstName":"Kristian","middleName":"","lastName":"Händler","suffix":""},{"id":486943327,"identity":"c536448c-230c-4f40-ad6e-918847da44eb","order_by":2,"name":"Almuth Caliebe","email":"","orcid":"","institution":"University of Lübeck, University of Kiel, Lübeck and Kiel","correspondingAuthor":false,"prefix":"","firstName":"Almuth","middleName":"","lastName":"Caliebe","suffix":""},{"id":486943333,"identity":"5fc5190f-d8d7-4423-9b44-6b869334254e","order_by":3,"name":"Malte Spielmann","email":"","orcid":"","institution":"University of Lübeck, University of Kiel, Lübeck and Kiel","correspondingAuthor":false,"prefix":"","firstName":"Malte","middleName":"","lastName":"Spielmann","suffix":""},{"id":486943338,"identity":"f6ed4e2c-076e-46de-9db4-4367709e4ed2","order_by":4,"name":"Paul-Martin Holterhus","email":"","orcid":"","institution":"University Hospital of Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Paul-Martin","middleName":"","lastName":"Holterhus","suffix":""},{"id":486943340,"identity":"40596358-b01a-4e31-9743-6d6500c2004d","order_by":5,"name":"Nadine C. Hornig","email":"data:image/png;base64,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","orcid":"","institution":"University of Lübeck, University of Kiel, Lübeck and Kiel","correspondingAuthor":true,"prefix":"","firstName":"Nadine","middleName":"C.","lastName":"Hornig","suffix":""}],"badges":[],"createdAt":"2025-07-09 12:38:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7083899/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7083899/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-025-12212-6","type":"published","date":"2025-11-17T15:59:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87360777,"identity":"6eb3b6c2-2fe3-4b1f-9701-344cd99f0aad","added_by":"auto","created_at":"2025-07-23 05:49:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":947684,"visible":true,"origin":"","legend":"\u003cp\u003eExpression profile of DEGs.\u003cstrong\u003e A) \u003c/strong\u003ePrincipal Component Analysis (PCA) of batch-corrected male control samples, showing segregation based on tissue type and treatment. \u003cstrong\u003eB)\u003c/strong\u003e PCA of batch-corrected CAIS samples, showing segregation based on tissue type. In both PCA plots, each dot represents a single individual (n = 6), color-coded by treatment (EtOH or DHT) and time point (48 h or 72 h). \u003cstrong\u003eC)\u003c/strong\u003e Heatmap displaying the expression profiles of the top 1,000 most variable genes across all conditions in male control samples. Each column represents an individual sample, grouped by tissue type (foreskin or scrotum), treatment (DHT or EtOH), and time point (48 h or 72 h), as indicated by the color-coded bar above. Each row corresponds to a gene. The colour scale reflects gene expression levels, with red representing high expression and blue indicating low expression. Hierarchical clustering is shown for both genes and samples to visualize expression similarities and condition-specific patterns.\u003c/p\u003e","description":"","filename":"SivaprasadetalFigures1.png","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/fc39e57209deb8b4ea91ed66.png"},{"id":87360778,"identity":"03da0a63-f9b1-46d9-828a-d12fb34838c3","added_by":"auto","created_at":"2025-07-23 05:49:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61284,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of DEGs in male control samples based on Log2FC and padj ≤ 0.05. Medians and Quartiles are shown as dotted lines.\u003c/p\u003e","description":"","filename":"SivaprasadetalFigures2.png","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/b39a6ab34e4d7238da935776.png"},{"id":87362800,"identity":"364733b6-91fb-49e2-9008-2d9e4fd743ee","added_by":"auto","created_at":"2025-07-23 05:57:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1342515,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram illustrating the individual numbers, percentages and overlaps of \u003cstrong\u003eA)\u003c/strong\u003e up-regulated and \u003cstrong\u003eB)\u003c/strong\u003edown-regulated genes without any threshold, padj ≤ 0.05; \u003cstrong\u003eC)\u003c/strong\u003e up-regulated and \u003cstrong\u003eD)\u003c/strong\u003e down-regulated genes with a threshold log2FC ≥ 0.5 or log2FC ≤ -0.5 and padj ≤ 0.05 in foreskin and scrotum derived GSFs following 48 and 72 hours of DHT treatment.\u003c/p\u003e","description":"","filename":"SivaprasadetalFigures3.png","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/b57f5b663f9fb440287da1d2.png"},{"id":87360779,"identity":"a4b3ed93-9bdb-4bcf-8b22-89183776a12b","added_by":"auto","created_at":"2025-07-23 05:49:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":587673,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plots displaying the distribution of DEGs in \u003cstrong\u003eA)\u003c/strong\u003e GSF-F_48 h, \u003cstrong\u003eB)\u003c/strong\u003eGSF-F_72 h, \u003cstrong\u003eC)\u003c/strong\u003e GSF-S_48 h, and \u003cstrong\u003eD) \u003c/strong\u003eGSF-S_72 h, comparing DHT to EtOH treatment. In all plots, red dots represent significant DEGs that meet both the log2FC ≥ 0.5 or log2FC ≤ -0.5 and padj ≤ 0.05 thresholds. Blue dots represent genes that meet only the significance threshold but not the log2FC threshold. Dotted lines indicate the log2FC threshold of ±0.5.\u003c/p\u003e","description":"","filename":"SivaprasadetalFigures4.png","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/77ee8a9fec1721ab01348536.png"},{"id":87363392,"identity":"44fcc95d-1af4-4281-b729-eb4acc81480a","added_by":"auto","created_at":"2025-07-23 06:05:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":776184,"visible":true,"origin":"","legend":"\u003cp\u003eBar plot depicting top enriched Gene Ontology biological process terms based on fold enrichment for up-regulated DEGs in \u003cstrong\u003eA)\u003c/strong\u003e GSF-F and \u003cstrong\u003eB)\u003c/strong\u003e GSF-S. Bar lengths indicate fold enrichment, and colour gradients represent FDR values, with darker red indicating higher statistical significance and blue indicating lower statistical significance.\u003c/p\u003e","description":"","filename":"SivaprasadetalFigures5.png","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/e8f8636f62105d36c781dcee.png"},{"id":87360795,"identity":"c97371dd-1c31-4e3c-9278-31d5cf447dae","added_by":"auto","created_at":"2025-07-23 05:49:27","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":516000,"visible":true,"origin":"","legend":"\u003cp\u003eBar plot depicting the top enriched Gene Ontology biological process terms based on fold enrichment for up-regulated DEGs with the log2FC ≥ 0.5 in \u003cstrong\u003eA)\u003c/strong\u003e GSF-F and \u003cstrong\u003eB)\u003c/strong\u003e GSF-S. Bar lengths indicate fold enrichment, and colour gradients represent FDR values, with darker red indicating higher statistical significance and blue indicating lower statistical significance.\u003c/p\u003e","description":"","filename":"SivaprasadetalFigures6.png","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/6ccfd76c3b96ba4e4ade4e4f.png"},{"id":96650973,"identity":"3e984841-8e06-497b-9553-8070c6b256d4","added_by":"auto","created_at":"2025-11-24 16:13:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5881771,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/ff8c5395-7a39-4d97-a192-45b5c4e6c636.pdf"},{"id":87363388,"identity":"355fe02f-c7d0-4cae-91a7-761bb025e8a4","added_by":"auto","created_at":"2025-07-23 06:05:27","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1219441,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/92f83ca85c463985da5079ec.docx"},{"id":87360783,"identity":"78158e93-2a44-4003-9603-ce74c6136baf","added_by":"auto","created_at":"2025-07-23 05:49:27","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1256618,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/9533263336149e7f9cec1252.xlsx"},{"id":87362799,"identity":"efd56f35-da18-4ac8-9147-baccc2b13719","added_by":"auto","created_at":"2025-07-23 05:57:27","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15787,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/3ece458e3370915c540a9bcd.xlsx"},{"id":87360788,"identity":"daa1a99c-328d-4813-82d1-759ce50f32f6","added_by":"auto","created_at":"2025-07-23 05:49:27","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":145803,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/809e98a6b0c82e8e4b5c7107.xlsx"},{"id":87360790,"identity":"05454920-460f-4cac-9ecd-56306a79e443","added_by":"auto","created_at":"2025-07-23 05:49:27","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":205759,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/4c63fe967c51656d200df30b.pdf"},{"id":87362804,"identity":"c743d355-8cc1-43d4-a7db-3e83a7bc7efa","added_by":"auto","created_at":"2025-07-23 05:57:27","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":12414,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7083899/v1/1f2db4033be2e3d530819d74.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive androgen-dependent transcriptome analysis in human genital tissue","fulltext":[{"header":"Background","content":"\u003cp\u003eAndrogens play an essential role in the development and functional maintenance of male reproductive tissues. Their physiological effects are mediated through the androgen receptor (AR), a 110-kDa protein belonging to the nuclear receptor family of ligand-activated transcription factors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Upon binding of testosterone (T) or the more potent androgen dihydrotestosterone (DHT), cytoplasmic AR translocates into the nucleus and binds to androgen-responsive DNA elements (AREs), thereby regulating the transcription of androgen-dependent genes. Changes in this pathway are associated with androgen insensitivity syndrome (AIS) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAIS is an X-linked recessive condition and a common cause of 46,XY differences of sex development (DSD). The phenotype varies from female external genitalia in the complete form (CAIS) to male external genitalia with infertility and/or gynecomastia in the mild form (MAIS). Partial androgen insensitivity syndrome (PAIS) exhibits a broad spectrum of undervirilized male external genitalia ranging from isolated micropenis to severe hypospadias [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAIS is classically caused by disruptive mutations in the \u003cem\u003eAR\u003c/em\u003e gene and the vast majority of CAIS individuals carry hemizygous mutations in the \u003cem\u003eAR\u003c/em\u003e. However, an \u003cem\u003eAR\u003c/em\u003e mutation can be found in less than 40% of individuals diagnosed with PAIS, suggesting that factors outside the \u003cem\u003eAR\u003c/em\u003e may contribute to a similar phenotype [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Measuring DHT-induced expression of the endogenous AR-target gene apolipoprotein D (\u003cem\u003eAPOD\u003c/em\u003e) in genital skin fibroblasts (GSFs) from individuals with the suspected diagnosis AIS but no mutation in the \u003cem\u003eAR\u003c/em\u003e gene revealed a group of GSFs with reduced AR activity, termed AIS type II [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Recently, the first genetic cause of AIS type II was described, identifying the formin DAAM2 as a cofactor of the AR, necessary for its transcriptional activity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Another possible cause of AIS type II could be changes in transcriptional targets of the AR. Microarray-based studies aimed at identifying DHT-induced AR target genes in GSFs, revealed very few significantly up-regulated genes[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] one of which, \u003cem\u003eAPOD\u003c/em\u003e, has been validated in a large cohort [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Using optimized endogenous AR-activity assay conditions, we performed mRNA sequencing on untreated and DHT-treated GSFs derived from six foreskin biopsies and six scrotum biopsies of male controls. We also included GSFs from four CAIS individuals, who lack AR activity, serving as ideal controls to identify gene expression changes mediated by the AR. We show a comprehensive analysis of androgen-dependent transcriptional changes in human genital tissue, identify AR-target genes that are either tissue-specific or common to both tissues and discuss how these transcriptional changes can affect androgen-induced pathways.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eTissue-specific and hormone-responsive gene expression patterns in GSFs\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify AR target genes in GSFs, we treated 12 male control cells (six from foreskin and six from scrotum) for 48 h and 72 h with either DHT or vehicle (EtOH). As an \u003cem\u003eAR\u003c/em\u003e-negative control, we included GSFs from four individuals with CAIS carrying loss-of-function mutations in the \u003cem\u003eAR\u003c/em\u003e (Supplementary file 1: Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All samples were processed for mRNA sequencing and subsequent data analysis.\u003c/p\u003e\u003cp\u003ePrincipal component analysis (PCA) of male control samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) revealed a primary separation by tissue type (scrotum vs. foreskin), accounting for 50.8% of the variation, and, to a lesser extent, by treatment (DHT vs. EtOH), contributing 6.72% of variation. In CAIS samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), separation was observed by tissue type (Labia Majora vs. Labia Minora), representing 59.9% of the variation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo gain a more detailed picture of gene expression variation, we visualized gene expression differences in a heatmap. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, consistent with the PCA results, the most prominent separation in gene expression in male control samples was based on the tissue type. Within each tissue type, additional differences emerged based on treatment, with some regions showing higher expression in DHT-treated samples compared to EtOH-treated, and \u003cem\u003evice versa\u003c/em\u003e. Furthermore, the duration of treatment (48 h and 72 h) contributed to subtle shifts in expression patterns. In CAIS samples, gene expression was primarily separated by tissue type, with minor changes observed in expression patterns over time (Supplementary file 1: Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparative gene expression analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate the biological basis of the observed clustering, differential gene expression analysis was performed by including all genes with a log2FC above or below zero (padj\u0026thinsp;\u0026le;\u0026thinsp;0.05). Foreskin derived samples (GSF-F) displayed the most robust response, with 576 genes up-regulated and 565 down-regulated at 48 h, increasing slightly at 72 h to 602 up-regulated and 576 down-regulated genes. Scrotum-derived samples (GSF-S) also showed substantial changes, with 387 genes up-regulated and 400 down-regulated at 48 h, and this number increased at 72 h to 399 up-regulated and 495 down-regulated genes. In total, this resulted in 1141 and 787 differentially expressed genes (DEGs) at 48 h, and 1178 and 894 genes at 72 h, in GSF-F and GSF-S, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The majority of changes were small, with a median log2FC of 0.27 for GSF-F and 0.21 for GSF-S for up-regulated genes and a median log2FC of -0.23 for GSF-F and GSF-S for down-regulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn CAIS, three differentially expressed genes were identified in labia minora derived samples and five in labia majora derived samples at 72 h, while none were identified at 48 h (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The transcripts did not overlap with any differentially expressed genes in the male control cohort. The observation that nearly no androgen-dependent gene expression changes were observed in CAIS samples indicates that the transcriptional changes observed in male control samples were indeed AR-dependent.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of DEGs in DHT- versus EtOH-treated GSFs across tissue types and time points\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample Condition (DHT vs EtOH)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo. of. up-regulated genes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo. of. down-regulated genes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF-F_48 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e565\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1141\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF-F_72 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e602\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF-S_48 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e787\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF-S_72 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e894\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF-L.Min_48 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF- L.Min _72 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF-L.Maj_48 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGSF- L.Maj _72 h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn GSF-F 409 genes (53.2%) were commonly up-regulated and 356 genes (45.4%) were commonly down-regulated at both 48 h and 72 h of treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B and Supplementary file 1: Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA, C). In GSF-S 260 genes (49.4%) were commonly up-regulated and 272 genes (43.7%) were commonly down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B and Supplementary file 1: Fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eB, D) at both time points. A total of 186 (19.6%) of genes were up-regulated at both timepoints in both tissues, while 147 genes (13.7%) were down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor a more stringent analysis, only genes with a log2FC\u0026thinsp;\u0026ge;\u0026thinsp;0.5 or log2FC \u0026le; -0.5 and padj\u0026thinsp;\u0026le;\u0026thinsp;0.05 were considered. This approach reduces false positives as well as indirect effects, allowing a focus on the most robustly regulated transcripts. In GSF-F, 56 genes (58.3%) were commonly up-regulated and 15 genes (44.1%) were commonly down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, D and Supplementary file 1: Fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003eA, C). In GSF-S, 37 genes (52.9%) were commonly up-regulated and 11 genes (39.3%) commonly down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, D and Supplementary file 1: Fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003eB, D). Across all conditions, 23 genes (18.4%) were commonly up-regulated and 3 genes (5.9%) were commonly down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, D). No DEGs with a log2FC\u0026thinsp;\u0026ge;\u0026thinsp;0.5 or log2FC \u0026le; -0.5 and padj\u0026thinsp;\u0026le;\u0026thinsp;0.05 were observed in CAIS derived samples. The list of DEGs is provided in Supplementary file 2.\u003c/p\u003e\u003cp\u003eSeveral genes showed a strong and consistent regulation in all conditions. Among the most, significantly up-regulated genes were \u003cem\u003eAOX1\u003c/em\u003e, \u003cem\u003eFAM107A\u003c/em\u003e, \u003cem\u003eCERS6\u003c/em\u003e and \u003cem\u003eAPOD\u003c/em\u003e which appeared in multiple comparisons (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-D). Other recurrently up-regulated genes included \u003cem\u003eFAM105A\u003c/em\u003e, \u003cem\u003eMYOCD\u003c/em\u003e and \u003cem\u003eFKBP5\u003c/em\u003e. Conversely, \u003cem\u003ePRELP\u003c/em\u003e, and \u003cem\u003eL1CAM\u003c/em\u003e appeared repeatedly among the down-regulated genes across various conditions and tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-D). We validated the DHT-induced changes in gene expression for six up-regulated genes (\u003cem\u003eSTEAP4\u003c/em\u003e, \u003cem\u003eMYOCD\u003c/em\u003e, \u003cem\u003eFAM105A\u003c/em\u003e, \u003cem\u003eFAM107A\u003c/em\u003e, \u003cem\u003eHSD11B1\u003c/em\u003e, \u003cem\u003eFKBP5\u003c/em\u003e) by quantitative PCR (qPCR) (Supplementary file 1: Fig. \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e and Supplementary file 3).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAR-chromatin binding and binding motif scan within DEG regions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to verify if the commonly up- and down-regulated genes are directly targeted by the AR, we screened publicly available AR chromatin immunoprecipitation sequencing (ChIPseq) data [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] for DHT-dependent AR-binding in the prostate cancer cell lines LnCaP and VCaP. Although these cells derive from a different tissue, we expected to see some overlap in AR-dependent transcription using the most robust AR target genes found in our analysis (those commonly up- or down-regulated at both time points in both tissues with a minimum log2FC\u0026thinsp;\u0026ge;\u0026thinsp;0.5 or \u0026le; -0.5). In the 23 up-regulated genes, 12 (52%) showed AR chromatin binding according to the ChIPseq data. No down-regulated gene showed AR chromatin binding. The majority of binding sites were intragenic with a few sites upstream the transcriptional start site (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We validated the binding site by scanning sites for the canonical AR binding site motif (AGAACANNNTGTTCT). At all sites high scoring motifs were found (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The complete list of genes and their associated AR binding sites is provided in Supplementary file 1: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAR Binding near DEGs in GSF-F/S with canonical AREs. TSS\u0026thinsp;=\u0026thinsp;transcriptional start site.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUp-regulated genes (GSF-F and GSF-S at 48h and 72h)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAR ChIPseq peak in LnCaP (distance to TSS in bp)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAR ChIPseq peak in VCaP (distance to TSS in bp)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCanonical AR binding site motif: AGAACANNNTGTTCT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value/ q-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAOX1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;80015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;80015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGAACAATCTGTTAG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.01e-05 / 0.0104\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAPOD\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-485\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGGAACATGGAGTTCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.62e-05 / 0.0464\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCCDC68\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;1927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;1927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGAACACAGTGTCCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.35e-07 / 0.000231\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCD82\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGCACTGGTTGTTCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.95e-06 / 0.0232\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCERS6\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;71232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;71232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGAACACTCTGTGCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.35e-07 / 0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eERCC6\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;34037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;34037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGAGCATGCTGTTTT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.69e-05 / 0.0248\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFAM105A\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;7808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;7808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGGACACCGTGTGCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.49e-06 / 0.00344\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFAM107A\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGGAACATCATGTCCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.000142 / 0.046\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFKBP5\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;1682\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;1682\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGGAACACGAGGTTCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.95e-06 / 0.00476\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIMPA2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-4365,\u003c/p\u003e \u003cp\u003e-4931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-4365,\u003c/p\u003e \u003cp\u003e-4931\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGAAAAAGCTGATTT,\u003c/p\u003e\u003cp\u003eTGGCCAGGCTGGTCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.000376 / 0.0899, 0.000524 / 0.089\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eKIF26B\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;24860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;24860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGAACATCCTGTCCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.95e-06/ 0.00813\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMYOCD\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026thinsp;15790\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e+\u0026thinsp;15790\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGAACAGTGTGTACC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.95e-06 / 0.00889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunctional categorization and pathway enrichment of DEGs\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGene Ontology Analysis (GOA) of all up-regulated genes (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) revealed enrichment in several processes related to neurodevelopment, such as ganglion morphogenesis, across both foreskin and scrotum derived samples. Additionally, GO processes such as hemidesmosome assembly, lateral sprouting involved in mammary gland duct morphogenesis, regulation of prostatic bud formation and regulation of basement membrane organization were shared between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B). In contrast, distinct sets of GO terms were enriched in each tissue. In GSF-F (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), processes such as regulation of presynaptic membrane organization and gonadotrophin-releasing hormone neuronal migration to the hypothalamus were enriched. Meanwhile, GSF-S (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) exhibited enrichment for processes such as relaxation of vascular associated smooth muscle and regulation of systemic arterial blood pressure.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe also performed GOA on up-regulated genes with a log2FC of \u0026ge;\u0026thinsp;0.5. In GSF-F biological processes related to bone tissue development or remodelling were significantly enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Whereas, in GSF-S, signalling and cell communication were a prominent theme (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The list of all GO Biological Process terms is provided in Supplementary file 4.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAndrogens are essential for male genital differentiation, as demonstrated by individuals with androgen insensitivity syndrome, who often exhibit reduced or absent genital virilization at birth due to reduced or absent AR activity. While androgen-activated gene transcription drives key physiological changes during male embryonic development, these gene programs have not yet been fully understood in humans. In mice, androgen-dependent gene expression during male genital development has been studied by comparing male and female cell populations in the external genitalia during the critical sex differentiation window in the mouse embryo [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Given that for ethical reasons such experiments are not possible in humans, GSFs, deriving from an androgen sensitive tissue, represent a valuable research material. Although being terminally differentiated they still might reflect some of the developmental processes occurring during the critical time window where androgens act to induce male sex differentiation. Large-scale AR-dependent gene expression programs in GSF from male controls and CAIS individuals revealed distinct transcriptional profiles, suggesting androgen-dependent programming in these cells [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Two further studies used GSFs to identify androgen induced target genes through microarray analysis with the identification of \u003cem\u003eAPOD\u003c/em\u003e as a bona fide AR target. We here used mRNA sequencing to identify additional DHT-induced genes in both foreskin and scrotum derived GSFs and compared them to GSFs derived from CAIS individuals.\u003c/p\u003e\u003cp\u003eOur study revealed a tissue specific response to DHT treatment, with foreskin derived GSFs showing a higher number of differentially expressed genes compared to scrotum derived GSFs. The majority of androgen-induced changes are, although being significant, subtle and might be secondary changes. Considering only changes with log2FC\u0026thinsp;\u0026ge;\u0026thinsp;0.5 or \u0026le; -0.5 foreskin derived fibroblasts showed 56 consistently up-regulated and 15 down-regulated genes, while in scrotal skin derived fibroblasts the numbers of DEGs were 37 and 11, respectively. Across all conditions, 23 genes were commonly up-regulated and 3 genes were commonly down-regulated, making them very robust AR-targets. No reproducible DHT-dependent transcriptional changes were observed in samples from CAIS individuals supporting the notion that the transcriptional changes identified in male control samples are indeed AR-dependent.\u003c/p\u003e\u003cp\u003eAmong the 23 commonly androgen-induced genes, several have previously been linked to androgen signalling. \u003cem\u003eAPOD\u003c/em\u003e is androgen-responsive in GSF, though its role in male genital development remains unclear [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. \u003cem\u003eFKBP5\u003c/em\u003e is part of the HSP90 chaperone complex, a complex that keeps un-ligated AR in the cytoplasm [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Depletion of either \u003cem\u003eFKBP5\u003c/em\u003e or \u003cem\u003eFKBP4\u003c/em\u003e in prostate cancer cells reduces AR dimer formation, chromatin binding, and phosphorylation, suggesting defective AR signalling [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The AR, in turn, directly regulates the \u003cem\u003eFKBP5\u003c/em\u003e gene via a distal enhancer element indicating a regulatory feedback mechanism [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Monoamine oxidase A (\u003cem\u003eMAOA\u003c/em\u003e) plays a significant role in prostate cancer progression and AR signalling. \u003cem\u003eMAOA\u003c/em\u003e and AR form a positive feedback loop, with androgens inducing \u003cem\u003eMAOA\u003c/em\u003e expression through AR binding to the \u003cem\u003eMAOA\u003c/em\u003e gene, while \u003cem\u003eMAOA\u003c/em\u003e enhances AR transcriptional activity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. \u003cem\u003eRGCC\u003c/em\u003e and \u003cem\u003eFAM107A\u003c/em\u003e were previously found to be DHT-regulated in foreskin derived fibroblasts [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] as well as neural stem cells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGene ontology analysis gives a broader picture about androgen induced biological pathways. In both tissue types GO terms related to sex differentiation are present, in GFS-F also the term \u0026ldquo;response to steroid hormone\u0026rdquo;, although these terms are not under the most enriched ones. Under the twenty most enriched terms in both GSF-F and GSF-S is \u0026ldquo;regulation of prostatic bud formation\u0026rdquo;. Prostatic buds originate from the urogenital sinus epithelium in the developing foetus. Androgens play a critical role in promoting prostatic bud development, including their elongation and branching [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn foreskin derived GSF, the most enriched GO terms converge on coordinated cellular processes for the development, organization, and regulation of complex tissues, especially regarding the nervous system, followed by the cardiovascular / vascular system. Of particular interest is the GO term \u0026ldquo;gonadotrophin-releasing hormone neuronal migration to the hypothalamus\u0026rdquo;, as gonadotrophin-releasing hormone from the hypothalamus activates gonadal steroid hormone synthesis and is negatively regulated through androgen signalling [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. GO-terms derived from the more stringent analysis of genes up-regulated\u0026thinsp;\u0026ge;\u0026thinsp;0.5 log2FC relate to the formation and regulation of organs and tissues, particularly the skeletal (e.g., ossification and bone mineralization), followed by muscle, renal and nervous systems. Further enriched terms relate to cell signalling and cell motility. In scrotum derived GSF, the most enriched GO terms share common themes centred on the development, structural organization, and functional regulation particularly within the nervous, cardiovascular, and muscular systems overlapping partly with androgen induced biological processes found in GSF-F.\u003c/p\u003e\u003cp\u003eIn summary, although being terminally differentiated, androgen treated GSFs reveal transcriptional programs involved in development and differentiation. Interestingly, these programs include neuronal, renal, muscle and cardiovascular development, where the AR has been shown to be involved [\u003cspan additionalcitationids=\"CR21 CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Several AR-target genes identified here are also involved in prostate cancer progression. This study therefore helps towards a better understanding of androgen-dependent processes in genital as well as non-genital tissues.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study provides a comprehensive analysis of DHT-induced gene expression changes in genital skin fibroblasts derived from foreskin and scrotum. The identification of new AR target genes expands the current understanding of androgen signalling, providing a broader perspective on AR-mediated gene regulation during development. This helps to better understand the aetiology of AIS, especially AIS type II, as well as other androgen-related conditions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003ePatient material\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMale control scrotum-derived genital fibroblasts (GSF-S) were obtained from fertile adult patients with typical external genitalia virilization who underwent vasectomy (n\u0026thinsp;=\u0026thinsp;2) and from patients under the age of 18 who underwent orchidopexy due to maldescended testes (n\u0026thinsp;=\u0026thinsp;4) but with typical external genitalia, i.e., no hypospadias. In addition, we used male control foreskin fibroblasts (GSF-F) from patients who underwent circumcision for cultural reasons or phimosis (n\u0026thinsp;=\u0026thinsp;6) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. We also included GSFs from Labia majora (GSF-L.Maj) (n\u0026thinsp;=\u0026thinsp;2) and Labia minora (GSF-L.Min) (n\u0026thinsp;=\u0026thinsp;2) samples of CAIS individuals carrying loss-of-function mutations in the \u003cem\u003eAR\u003c/em\u003e. The GSFs used and a visualisation of CAIS mutations can be seen in Supplementary file 1: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell culture and hormone induction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGSFs were cultured in phenol red free Dulbecco's modified Eagle\u0026rsquo;s medium (DMEM) supplemented with 10% fetal bovine serum (FBS, MaxSpec), 100 units/ml penicillin/streptomycin, 2 mM L-glutamine and 20 mM HEPES buffer (all purchased from Life Technologies) and incubated at 37\u0026deg;C in a 5% CO2 incubator. For hormone induction, cells were seeded in four 10 cm dishes: two dishes with a concentration of 2.8x10\u003csup\u003e5\u003c/sup\u003e cells for a 72 h hormone treatment and two dishes with a concentration of 3.5x10\u003csup\u003e5\u003c/sup\u003e cells for a 48 h hormone treatment. After 24 h, cells were washed three times with PBS (Life Technologies), and medium containing 0.1% charcoal-treated FBS was added to the cells. DHT (Sigma-Aldrich), dissolved in ethanol (EtOH) was added to two dishes at a final concentration of 10 nM, while the control dishes were treated with the same volume of ethanol. Cells were incubated for 48 h and 72 h at 37\u0026deg;C with 5% CO2, after which they were lysed in RNA-extraction buffer (RLT; Qiagen). Hence, each GSF line underwent four different experimental conditions: EtOH and DHT treatments at two time points (48 h and 72 h).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA Extraction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA was extracted using the RNeasy Mini Kit (Qiagen), including on-column DNase digestion (RNAse-Free DNase Set, Qiagen) to eliminate residual DNA, following the manufacturer\u0026rsquo;s protocol. RNA quantity and quality were measured with a Nanodrop Spectrophotometer and an Agilent 2100 Bioanalyzer using the RNA 6000 Nano Chip Kit (Agilent), respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLibrary Preparation and RNA Sequencing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll RNA samples processed for mRNA sequencing had an RNA Integrity Number (RIN) score\u0026thinsp;\u0026ge;\u0026thinsp;8, as determined by the Agilent 2100 Bioanalyzer, indicating high-quality and intact RNA suitable for transcriptome analysis. Total RNA (1\u0026micro;g) was converted into sequencing libraries using the Illumina Stranded mRNA Prep Ligation kit (Illumina, Cat. No. 20040532). Sample-specific barcoding was achieved utilizing Illumina Unique Dual (UD) Set A index adapters, employing distinct dual indexes (I7-10 and I5-10) (Illumina, Cat. No. 20091655). The quality of the amplified cDNA was validated with the Bioanalyzer 2100 using the High Sensitivity DNA kit (Agilent), and the concentration was measured using the Qubit DNA HS Assay. High-quality DNA libraries were pooled equimolarly and a 650pM pool was sequenced using paired-end 200 bp reads on the NextSeq 2000 system (Illumina) with NextSeq 2000 P3 Reagents (200 cycles; Illumina, Cat. No. 20040560). Sequencing data conversion and demultiplexing were performed using bcl2fastq2 v2.20 (Illumina). Gene-level count matrices were generated from the FASTQ files using the community-driven nf-core/rnaseq pipeline v3.12.0 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The pipeline included adapter trimming (TrimGalore v0.6.7), contamination removal (SortMeRNA v4.3.4 and BBMap-BBSplit v39.01), alignment (STAR 2.7.10a) to hg38, transcript-level quantification (Salmon v1.10.1), and comprehensive quality control (FastQC v0.11.9, RESeQC v3.0.1, dupRadar v1.28.0, and MultiQC v1.14). Transcript-level counts were converted to gene-level counts using tximeta-tximport v1.12.0. As the samples were processed in two separate sequencing runs (one for male control and one for CAIS samples), batch correction was applied to account for run-specific effects. The datasets were combined and processed together using Salmon (which includes STAR aligner support), ensuring consistent quantification across both batches.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDifferential Gene Expression Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTranscriptomic analysis was performed using Shiny-Seq [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], an RNA-sequencing analysis pipeline based on DESeq2. The analysis utilised a count matrix (summarising gene expression levels across samples) and a metadata table (describing sample attributes) as input data to compare gene expression levels between different experimental conditions. The dataset was normalized using the DESeq2 package with a filtering cut-off of 10 raw reads. For hierarchical clustering samples were classified based on a combination of tissue type, treatment type and incubation time for male control and CAIS. The composite condition \u0026ldquo;Tissue_Treatment_Time\u0026rdquo; was chosen for normalization to account for variation across these factors. To address batch effects, Surrogate Variable Analysis (SVA) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] was applied, estimating \u0026lsquo;10\u0026rsquo; surrogate variables for male control samples and \u0026lsquo;2\u0026rsquo; for CAIS samples. For tissue-specific gene expression analysis, \u0026lsquo;5\u0026rsquo; surrogate variables were estimated for scrotum/foreskin derived samples, and \u0026lsquo;1\u0026rsquo; for Labia major/minora-derived samples.\u003c/p\u003e\u003cp\u003eDifferentially expressed genes in each tissue were identified by comparing DHT-treated versus ethanol-treated cells at 48 h and 72 h time points. Genes with log2 fold change (log2FC)\u0026thinsp;\u0026gt;\u0026thinsp;0 were considered up-regulated, and those with log2FC\u0026thinsp;\u0026lt;\u0026thinsp;0 were considered down-regulated, with a significance threshold of adjusted p-value (padj)\u0026thinsp;\u0026le;\u0026thinsp;0.05. For a more stringent analysis, we selected DEGs with log2FC\u0026thinsp;\u0026ge;\u0026thinsp;0.5 or log2FC \u0026le; -0.5 and a padj\u0026thinsp;\u0026le;\u0026thinsp;0.05. The list of DEGs is provided in Supplementary file 2. The distribution of DEGs was visualised using the MaGIC Volcano Plot Tool [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], which plots the magnitude of change (log2FC) against statistical significance (-log10 padj). Venn diagrams were created using Venny 2.1.0 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eQuantitative Real-Time PCR (qRT-PCR)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA (500ng) was reverse transcribed using QuantiTect Reverse Transcription Kit (Qiagen). qRT-PCR was carried out using the QuantiTect SYBR Green master mix (Qiagen) with gene-specific primers, tested in duplicate for each sample. For the validation of the RNA-Seq results, six up-regulated genes (\u003cem\u003eMYOCD\u003c/em\u003e, \u003cem\u003eFKBP5\u003c/em\u003e, \u003cem\u003eHSD11B1\u003c/em\u003e, \u003cem\u003eFAM105A\u003c/em\u003e, \u003cem\u003eFAM107A\u003c/em\u003e, \u003cem\u003eSTEAP4\u003c/em\u003e) were selected for analysis. qRT-PCR was performed on samples from four male control individuals (GSF-F, n\u0026thinsp;=\u0026thinsp;2; GSF-S, n\u0026thinsp;=\u0026thinsp;2) and two CAIS individuals (L.Maj, n\u0026thinsp;=\u0026thinsp;1; L.Min, n\u0026thinsp;=\u0026thinsp;1), with both DHT- and EtOH-treated samples collected at 72 h. The housekeeping gene succinate dehydrogenase complex, subunit A (\u003cem\u003eSDHA\u003c/em\u003e), was used to normalise the gene expression data. The relative expression of mRNA was calculated by the 2^\u0026minus;ΔΔCt method with normalization to \u003cem\u003eSDHA\u003c/em\u003e. Primers for \u003cem\u003eMYOCD\u003c/em\u003e, \u003cem\u003eFKBP5\u003c/em\u003e, and \u003cem\u003eHSD11B1\u003c/em\u003e were obtained from Qiagen and used according to the manufacturer\u0026rsquo;s instructions, while primers for \u003cem\u003eFAM105A\u003c/em\u003e, \u003cem\u003eFAM107A\u003c/em\u003e and \u003cem\u003eSTEAP4\u003c/em\u003e were designed using Primer3 (Supplementary file 1: Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eARE motif scanning\u003c/b\u003e\u003c/p\u003e\u003cp\u003eChromatin-immunoprecipitation-sequencing (ChIP-seq) data from GEO sources: GSM3148986 and GSM3148988 for ethanol and androgen treated LNCaP cells [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and GSM1410768 and GSM1410785 for ethanol and androgen treated VCaP cells [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] were visualized using the Cistrome data browser and checked for androgen-induced AR-binding. The binding area was then screened for the canonical AR binding site motif (AGAACANNNTGTTCT) using the Find Individual Motif Occurrences (FIMO) software from MEME suite 5.5.7.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGene Ontology Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGene Ontology enrichment analysis was performed using PANTHER [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] with significantly up- and down-regulated DEGs, as well as those with log2FC\u0026thinsp;\u0026ge;\u0026thinsp;0.5 or \u0026le; -0.5, applying a false discovery rate (FDR) threshold of 0.05. The resulting data was visualized using R Studio (R version 4.4.0 (2024-04-24 ucrt)) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] to generate bar plots. Biological processes were sorted by fold enrichment from highest to lowest, and the top 20 terms were included in the plot. For genes with log2FC\u0026thinsp;\u0026ge;\u0026thinsp;0.5 or \u0026le; -0.5, the top 10 enriched pathways were plotted. The list of significantly enriched GO biological process terms is provided in Supplementary file 4.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study followed the Declaration of Helsinki. The study was approved by the Ethical Committee of the Medical Faculty of Kiel University (AZ: D415/11; Supplementary file 5). Written informed consent to participate was obtained from all of the participants in the study. We obtained written consent from the parents on behalf of the children/minors enrolled in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSequence data that support the findings of this study have been deposited to the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE300211).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been funded by the German Research Foundation HO 6028/3-1 and SFB 1665/1 M02 to NH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNH designed the study. RS performed the experiments. RS, KH and NH analyzed the data. RS and NH drafted the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our sincere thanks to Mrs. Saranya Balachandran, Varun Sreenivas and Nathalie Kruse for their technical support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBrinkmann AO, Klaasen P, Kuiper GGJM, van der Korput JAGM, Bolt J, de Boer W, et al. Structure and function of the androgen receptor. Urol Res. 1989;17(2):87\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMongan NP, Tadokoro-Cuccaro R, Bunch T, Hughes IA. Androgen insensitivity syndrome. Best Pract Res Clin Endocrinol Metab. 2015;29(4):569\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHornig NC, Holterhus PM. 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Vienna, Austria; 2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Androgen Receptor, Androgen Insensitivity Syndrome, Transcriptional Regulation","lastPublishedDoi":"10.21203/rs.3.rs-7083899/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7083899/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAndrogen signalling through the androgen receptor (AR) is crucial for male genital development. Disruptions in this pathway are associated with androgen insensitivity syndrome (AIS), which is typically caused by mutations in the AR gene, although the underlying genetic mechanisms remain unknown in many cases. To better understand androgen-dependent transcriptional changes in human genital tissue, we performed transcriptomic profiling of foreskin- and scrotum-derived human genital skin fibroblasts (GSFs) treated with dihydrotestosterone.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eDifferential gene expression analysis revealed 409 and 260 reproducibly up-regulated genes in foreskin- and scrotum-derived GSFs, respectively. GSFs from individuals with complete androgen insensitivity syndrome, carrying inactivating mutations in the \u003cem\u003eAR\u003c/em\u003e gene, showed no reproducible androgen response. Androgen response element motif scanning confirmed direct AR binding in key up-regulated genes, including \u003cem\u003eAOX1\u003c/em\u003e, \u003cem\u003eAPOD\u003c/em\u003e, \u003cem\u003eFKBP5\u003c/em\u003e, and \u003cem\u003eFAM107A\u003c/em\u003e. Gene ontology analysis revealed enrichment in pathways related to neuronal, muscle, cardiovascular, and sex development.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eIdentifying new AR target genes broadens the current understanding of androgen signalling and aids in better understanding the aetiology of AIS, and other androgen-related conditions.\u003c/p\u003e","manuscriptTitle":"Comprehensive androgen-dependent transcriptome analysis in human genital tissue","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 05:49:22","doi":"10.21203/rs.3.rs-7083899/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-25T07:16:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-14T02:57:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"43009147645204418022604401414725991768","date":"2025-08-04T14:09:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219275758019316791681631775567712348295","date":"2025-08-01T23:09:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-31T21:07:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"181544233493684871866794033827314840440","date":"2025-07-30T12:28:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T08:08:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-16T07:42:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-16T04:59:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-15T15:52:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-07-15T14:47:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d6868846-c0e9-45b7-a84c-268d38410341","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:10:22+00:00","versionOfRecord":{"articleIdentity":"rs-7083899","link":"https://doi.org/10.1186/s12864-025-12212-6","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2025-11-17 15:59:08","publishedOnDateReadable":"November 17th, 2025"},"versionCreatedAt":"2025-07-23 05:49:22","video":"","vorDoi":"10.1186/s12864-025-12212-6","vorDoiUrl":"https://doi.org/10.1186/s12864-025-12212-6","workflowStages":[]},"version":"v1","identity":"rs-7083899","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7083899","identity":"rs-7083899","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}