Project description:Numerous studies have shown the potential of spermatozoal RNAs to delineate failures of spermatogenic pathways in infertile samples. However, the RNA contribution of normal fertile samples still needs to be established in relation to transcripts consistently present in human spermatozoa. We report here the spermatozoal transcript profiles characteristic of 24 normally fertile individuals. RNA was extracted from the purified sperm cells of ejaculate and hybridized to Illumina Human-8 BeadChip Microarrays
Project description:Normal human spermatogenesis concludes with the formation of large numbers of morphologically well developed spermatozoa. While transcriptionally quiescent these cells carry an RNA payload that reflects the final spermiogenic phase of transcription. We report here the spermatozoal transcript profiles characteristic of normally fertile individuals and infertile males suffering from a consistent and severe teratozoospermia in which under 4% of spermatozoa are morphologically normal. RNA was extracted from the purified sperm cells of ejaculate and hybridized to Affymetrix U133 (v2) Microarrays. Spermatozoal RNAs were prepared from the semen samples of 21 individuals. An asymmetric dual block design was adopted with biological replicates in both blocks. 13 semen samples were assessed from normally fertile males who had fathered at least one child. 8 semen samples were assessed from infertile individuals with a severe and consistent heterogeneous teratozoospermia who showed no other abnormal semen parameters.
Project description:Normal human spermatogenesis concludes with the formation of large numbers of morphologically well developed spermatozoa. While transcriptionally quiescent these cells carry an RNA payload that reflects the final spermiogenic phase of transcription. We report here the spermatozoal transcript profiles characteristic of normally fertile individuals and infertile males suffering from a consistent and severe teratozoospermia in which under 4% of spermatozoa are morphologically normal. RNA was extracted from the purified sperm cells of ejaculate and hybridized to Illumina WG6 Microarrays. Keywords: disease state analysis
Project description:Normal human spermatogenesis concludes with the formation of large numbers of morphologically well developed spermatozoa. While transcriptionally quiescent these cells carry an RNA payload that reflects the final spermiogenic phase of transcription. We report here the spermatozoal transcript profiles characteristic of normally fertile individuals and infertile males suffering from a consistent and severe teratozoospermia in which under 4% of spermatozoa are morphologically normal. RNA was extracted from the purified sperm cells of ejaculate and hybridized to Illumina WG ref8 Microarrays. Keywords: disease state analysis
Project description:Normal human spermatogenesis concludes with the formation of large numbers of morphologically well developed spermatozoa. While transcriptionally quiescent these cells carry an RNA payload that reflects the final spermiogenic phase of transcription. We report here the spermatozoal transcript profiles characteristic of normally fertile individuals and infertile males suffering from a consistent and severe teratozoospermia in which under 4% of spermatozoa are morphologically normal. RNA was extracted from the purified sperm cells of ejaculate and hybridized to Affymetrix U133 (v2) Microarrays. Keywords: disease state analysis
Project description:The objective of the study was to compare the microRNA content in uterine fluid from patients with recurrent implantation failure (RIF) to that of healthy fertile women. It is a descriptive laboratory study including healthy fertile women and patients with RIF, defined as three failed in vitro fertilization cycles with high quality embryos. Study subjects were instructed to monitor their menstrual cycles using a luteinizing hormone test kit. Uterine fluid was collected on day LH+ 7-9 by flushing with saline. Samples were processed for small RNA sequencing and results were analysed using bioinformatics. The main outcome measure was to identify differentially expressed miRNAs between patients with RIF and healthy fertile women.