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:In this study, we tested whether reduction in spermatozoal quality induced by under-nutrition is associated with an increase in germ cell apoptosis and a reduction in spermatogenesis, and whether these effects are regulated by small RNAs. Groups of 8 male sheep were fed for a 10% increase or 10% decrease in body mass over 65 days. Testicular tissue from underfed males had more apoptotic germ cells (TUNEL assay; P < 0.05) and greater (P < 0.05) levels of expression of apoptosis-related genes than well-fed males. We identified 44 miRNAs and 35 piRNAs that were differentially expressed in well-fed and underfed males (FDR < 0.05) and found that they were predominantly related to development of the reproductive system, apoptosis (miRNAs), or sperm production and quality (piRNAs). Furthermore, experimental validation showed that novel-miR-144, a homologue of miR-98, would target three apoptotic genes (TP53, CASP3, FASL). The proportion of miRNAs as a total of small RNAs was greater in well-fed males than in underfed males (P < 0.05) and was positively correlated with the proportion of piRNAs in well-fed males (r = 0.8, P < 0.05) and underfed males (r = 0.8, P < 0.05). We conclude that the reductions in spermatozoal quality induced by under-nutrition are due, at least partly, to increased germ cell apoptosis and to changes in the expression of miRNAs and piRNAs.
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:Paternal exposure to genotoxic compounds is thought to contribute to diseases in their offspring. Therefore, mRNA profiles from sperm in ejaculates of cigarette smokers (N=4) were compared with non-smokers (N=4). Smoking behaviour was verified by assessing cotinine levels in seminal plasma. Gene-expression analysis was subsequently performed using microarray technology (Agilent human 4x44k) to investigate the use of gene-expression profiling as biomarker of gene-environment interactions in human testis
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