biostudies-arrayexpressMagdalena GomółkaHomo sapienshttps://www.ebi.ac.uk/biostudies/studies/E-MTAB-17125Serum and sperm samples were collected from participants of the PLMS cohort and the CTQ cohort. The PLMS cohort consisted of children of both sexes, whereas the CTQ cohort consisted of adult men. Participants represented individuals with and without exposure to adverse childhood experiences (ACE). Total RNA was isolated and subjected to small RNA sequencing with a focus on microRNAs. Sequencing data were processed and analyzed using standard bioinformatic workflows, including differential expression analysis performed with the DESeq2 package in R. The study aimed to identify miRNA signatures associated with early-life adversity.biostudies-arrayexpressNucleic Acid Extraction - Total RNA was extracted from human serum and sperm samples using QIAzol (Qiagen) or TRIzol (Invitrogen) reagents according to the study protocol. Briefly, 1 ml of QIAzol or TRIzol was added to 200 µl of serum or to the sperm pellet, respectively. RNA extraction was performed by chloroform-based phase separation followed by isopropanol precipitation. RNA concentration was assessed using a NanoDrop spectrophotometer. RNA quality and integrity were evaluated using the Agilent 2100 Bioanalyzer with the RNA 6000 Nano Kit.Library Construction - miRNA libraries were prepared using the QIAseq miRNA Library Kit according to the manufacturer’s instructions. Libraries were generated from 200 ng of total RNA. Briefly, 3′ and 5′ adapters were ligated to miRNAs, followed by reverse transcription, cDNA purification, and PCR amplification. Library quality was evaluated using the Agilent 2100 Bioanalyzer with a High Sensitivity DNA chip. The mean library size was 174 bp.Sequencing - Libraries were quantified using a Quantus fluorometer and the QuantiFluor double-stranded DNA System. Libraries were single-end sequenced with 75 bp reads on the Illumina NovaSeq 6000 platform.Sample Collection - Serum and sperm samples were collected from participants of the PLMS and CTQ cohorts according to the study protocol. Samples were anonymized before sequencing and downstream analysis.OrganizationMINSEQE ScoreAssays and DataMAGE-TAB FilesData Transformation - Secondary analysis was performed in R using the DESeq2 package. UMI count data were combined with sample metadata to construct DESeq2 objects. Low-expressed miRNAs were removed during pre-filtering. Serum and sperm samples were analyzed separately. For serum samples, biological sex was included as a covariate in the differential expression model. Normalized miRNA counts were obtained using DESeq2 normalization procedures.Sequence Alignment - Primary miRNA bioinformatic analysis was performed using the QIAGEN GeneGlobe Data Analysis Center. The workflow included calibration of miRBase entries, trimming of adapters and low-quality bases, identification of unique molecular identifiers (UMIs), alignment to miRBase v21 and piRNABank reference databases, and quantification of unique molecules. Samples with fewer than 200,000 miRNA reads were excluded from downstream analysis.MetabolomicsUnknownTranscriptomicsGenomicsProteomicsIllumina NovaSeq 6000microRNA profiling by high throughput sequencingHomo sapiensMagdalena GomółkafalseSmall RNA sequencing of human serum and sperm samples associated with adverse childhood experiencesSerum and sperm samples were collected from participants of the PLMS cohort and the CTQ cohort. The PLMS cohort consisted of children of both sexes, whereas the CTQ cohort consisted of adult men. Participants represented individuals with and without exposure to adverse childhood experiences (ACE). Total RNA was isolated and subjected to small RNA sequencing with a focus on microRNAs. Sequencing data were processed and analyzed using standard bioinformatic workflows, including differential expression analysis performed with the DESeq2 package in R. The study aimed to identify miRNA signatures associated with early-life adversity.2026-07-01T00:00:00Z2026-07-01T01:04:21.802Z2026-06-08T12:26:14.078ZE-MTAB-17125ERP194554EFO_0002944EFO_0004170EFO_0004917EFO_0005518EFO_0003816EFO_0004184