Project description:Although piwi-interacting RNAs (piRNAs) play pivotal roles in spermatogenesis, little is known about piRNAs in the seminal plasma of infertile males. In this study, we systematically investigated the profiles of seminal plasma piRNAs in infertile males to identify piRNAs that are altered during infertility and evaluate their diagnostic value. Seminal plasma samples were obtained from 211 infertile patients (asthenozoospermia and azoospermia) and 91 fertile controls. High-throughput sequencing technology was employed to screen piRNA profiles in seminal plasma samples pooled from healthy controls and infertile patients. The results identified 61 markedly altered piRNAs in the infertile patient groups compared with the control group. Next, a quantitative RT-PCR assay was conducted in the training and validation sets to measure and confirm the concentrations of altered piRNAs. The results identified a panel of 5 piRNAs that were significantly decreased in the seminal plasma of infertile patients compared with healthy controls. The areas under the ROC curves for these piRNAs ranged from 0.796 to 0.996, suggesting that the diagnostic potential of these 5 piRNAs to distinguish asthenozoospermic and azoospermic individuals from healthy controls was high. In summary, this study identifies a panel of piRNAs that can accurately distinguish fertile from infertile males. This finding may provide pathophysiological clues that are involved in the development of infertility. Fresh samples were collected and stored at -80â??.Total RNA of seminal plasma were extracted and solexa sequencing was performed.
Project description:The human seminal plasma is a potential source of biomarkers for male reproductive disorders. A tissue-profiling analysis of the main organs participating in the secretion of this body fluid was conducted to identify tissue-specific genes along the male reproductive tract. Total RNA from non pathological Human seminal vesicles were extracted and hybridized on Affymetrix microarrays. Expression signals in seminal vesicles (present dataset), prostates (GEO; GSE7307), epidydimises (GEO; GSE7808) and testicular samples (Arrayexpress; E-TABM-130) were compared to identify genes that are detected in one of these organs only.
Project description:Although piwi-interacting RNAs (piRNAs) play pivotal roles in spermatogenesis, little is known about piRNAs in the seminal plasma of infertile males. In this study, we systematically investigated the profiles of seminal plasma piRNAs in infertile males to identify piRNAs that are altered during infertility and evaluate their diagnostic value. Seminal plasma samples were obtained from 211 infertile patients (asthenozoospermia and azoospermia) and 91 fertile controls. High-throughput sequencing technology was employed to screen piRNA profiles in seminal plasma samples pooled from healthy controls and infertile patients. The results identified 61 markedly altered piRNAs in the infertile patient groups compared with the control group. Next, a quantitative RT-PCR assay was conducted in the training and validation sets to measure and confirm the concentrations of altered piRNAs. The results identified a panel of 5 piRNAs that were significantly decreased in the seminal plasma of infertile patients compared with healthy controls. The areas under the ROC curves for these piRNAs ranged from 0.796 to 0.996, suggesting that the diagnostic potential of these 5 piRNAs to distinguish asthenozoospermic and azoospermic individuals from healthy controls was high. In summary, this study identifies a panel of piRNAs that can accurately distinguish fertile from infertile males. This finding may provide pathophysiological clues that are involved in the development of infertility.
Project description:This dataset contains small RNA sequencing data and mRNA capture sequencing data from 20 different human biofluids (amniotic fluid, aqueous humor, ascites, bile, bronchial lavage fluid, breast milk, cerebrospinal fluid, colostrum, gastric fluid, pancreatic cyst fluid, plasma, saliva, seminal fluid, serum, sputum, stool, synovial fluid, sweat, tear fluid and urine). In total, 180 samples were sequenced. Files are provided in fastQ format. Samples were sequenced on a NextSeq 500.
Project description:In this study we examined the influence of seminal plasma on gene expression in human Ect1 ectocervical epithelial cells, and the extent to which recombinant TGFβ3 elicits comparable changes. Ect1 cells were incubated with recombinant human TGFβ3 (5 ng/ml), 10% pooled human seminal plasma (v/v), or medium alone for 10h. RNA was reverse transcribed into cDNA and hybridized to Affymetrix GeneChip® Human Genome U133 plus 2.0 microarrays (Affymetrix, Santa Clara, CA). Exposure of Ect1 cells to seminal plasma resulted in differential expression of a total of 3955 probe sets, identified using high stringency criteria with MAS 5.0 analysis. These corresponded to 1338 genes up-regulated and 1343 genes down-regulated by seminal plasma. TGFβ3 treatment of Ect1 cells resulted in differential expression of 884 probe sets, corresponding to 346 up-regulated genes and 229 down-regulated genes. The genes differentially regulated by seminal plasma included several genes associated with cytokine–cytokine receptor interaction, TGFβ signalling, JAK/STAT signalling or VEGF signalling pathways, as specified by the KEGG database. Of 47 genes in these families, 17 (36.1%) were similarly regulated by both seminal plasma and TGFβ3. These data, together with additional experiments showing all three TGFβ isoforms can regulate inflammatory cytokine expression in Ect1 cells, identify TGFβ isoforms as key agents in seminal plasma that signal induction of pro-inflammatory cytokine synthesis in cervical cells.
Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..
Project description:We hypothesized that seminal plasma, the acellular seminal fluid component, influences the endometrium stimulating the immune system and facilitating the implantation. We designed a randomized, double-blinded, placebo-controlled trial, and we used microarray analysis to evaluate differences in the endometrial transcriptomic profile after vaginal seminal plasma application. Differential gene pathways analysis showed an upregulation of pathways associated with the immune response, cell viability, proliferation and cellular movement, implantation, embryo development, oocyte maturation and angiogenesis. We compared our results with similar studies in pigs, mice and in vitro human endometrial cells and found similar and found comparable results. Our data show that seminal plasma has a positive effect on the endometrium during the implantation window.
Project description:Transcriptional profiling of adult mouse liver tissue comparing offspring derived from sperm and seminal plasma of normal protein diet fed males (controls, NN), sperm and seminal plasma from males fed a low protein diet fed males (LL), sperm from normal protein fed males and seminal plasma from low protein fed males (NL) or sperm from low protein diet fed males and seminal plasma from normal protein diet males (NL). The first letter denotes the diet of the sperm donor and the second letter the diet of the seminal plasma donor. Three-condition experiment: NN vs. LL, NN vs. NL, NN vs. LN. Adult offspring liver tissue. Biological replicates: 7 control (NN), 9 LL, 7 NL and 7 LN. One replicate per array chip.
Project description:Previously, we published a dataset of human blood plasma and serum samples of 10 healthy males and 10 healthy females, fractionated on a set of sorbents (cation exchange Toyopearl CM-650M, CM Bio-Gel A, SP Sephadex C-25 and anion exchange QAE Sephadex A-25) and analyzed by LC-MS/MS individually and pooled in equal amounts (Supplementary Table S1, Sheet 1) [33]. The mass spectrometry peptidomics data was deposited to the ProteomeXchange Consortium via the PRIDE partner repository (dataset identifiers PXD008141 and 10.6019/PXD008141). Direct download link: http://www.ebi.ac.uk/pride/archive/projects/PXD008141. We analyzed this dataset again within this work. The detailed information about the dataset of blood plasma/serum samples of 20 healthy donors fractionated on a set of sorbents is available in the original paper [33], including the clinical parameters of the donors, sample collection, plasma/serum fractionation, peptide extraction and LC-MS/MS analysis. 33. Arapidi, G. et al. Peptidomics dataset: Blood plasma and serum samples of healthy donors fractionated on a set of chromatography sorbents. Data Brief 18, 1204–1211 (2018).
Project description:In this study we examined the influence of seminal plasma on gene expression in human Ect1 ectocervical epithelial cells, and the extent to which recombinant TGFβ3 elicits comparable changes. Ect1 cells were incubated with recombinant human TGFβ3 (5 ng/ml), 10% pooled human seminal plasma (v/v), or medium alone for 10h. RNA was reverse transcribed into cDNA and hybridized to Affymetrix GeneChip® Human Genome U133 plus 2.0 microarrays (Affymetrix, Santa Clara, CA). Exposure of Ect1 cells to seminal plasma resulted in differential expression of a total of 3955 probe sets, identified using high stringency criteria with MAS 5.0 analysis. These corresponded to 1338 genes up-regulated and 1343 genes down-regulated by seminal plasma. TGFβ3 treatment of Ect1 cells resulted in differential expression of 884 probe sets, corresponding to 346 up-regulated genes and 229 down-regulated genes. The genes differentially regulated by seminal plasma included several genes associated with cytokine–cytokine receptor interaction, TGFβ signalling, JAK/STAT signalling or VEGF signalling pathways, as specified by the KEGG database. Of 47 genes in these families, 17 (36.1%) were similarly regulated by both seminal plasma and TGFβ3. These data, together with additional experiments showing all three TGFβ isoforms can regulate inflammatory cytokine expression in Ect1 cells, identify TGFβ isoforms as key agents in seminal plasma that signal induction of pro-inflammatory cytokine synthesis in cervical cells. RNA from each of four biological replicates, each comprising pooled material from separate sets of 4 replicate wells, was analysed for each treatment. Total RNA was reverse transcribed into cDNA and sent to the Australian Genome Research Facility (AGRF; Melbourne, Australia) for single-cycle labeling and hybridization to 12 Affymetrix GeneChip® Human Genome U133 plus 2.0 microarrays (Affymetrix, Santa Clara, CA).