Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Whole Transcriptome analysis to identify non-coding RNA regulators and hub genes in Sperm of non-obstructive azoospermia by microarray

ABSTRACT: Our study utilizes whole transcriptome analysis via microarray technology to uncover non-coding RNA regulators and hub genes within sperm samples afflicted by non-obstructive azoospermia. This comprehensive approach offers insight into the intricate molecular landscape underlying this condition, shedding light on potential regulatory mechanisms and key genetic players implicated in its pathogenesis.

ORGANISM(S): Homo sapiens

PROVIDER: GSE268452 | GEO | 2024/05/31

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Whole Exome Sequencing of two non-obstructive azoospermia patients

Project description:We collected blood samples of two non-obstructive azoospermia patients, and performed whole exome sequencing to explore the causal mutations for male infertility.

2021-06-22 | E-MTAB-9287 | biostudies-arrayexpress

Comparative proteomics analysis of FFPE testicular tissue from men with obstructive and non-obstructive azoospermia

Project description:The project aimed to compare testicular proteomes from patients with obstructive and non-obstructive azoospermia in order to identify molecular signatures involved in spermatogenesis as well to identify candidate biomarkers for discriminating between different types of azoospermia. The samples used in this study were formalin fixed paraffin embedded (FFPE) testicular tissues obtained by biopsy from men with clinical diagnosis of azoospermia. Samples were grouped according to the histopathological report in 3 groups: 1) Spermatogenesis (obstructive azoospermia), 2) Hypospermatogenesis and 3) Sertoli cell only syndrome (SCO). Patients were aged 31–46 years with no differences among groups regarding age (Median age (Hypospermatogenesis) =35; Median age (SCO) =34 and Median age (Spermatogenesis) =39). Each group had 9 samples or 27 samples in total were used for the comparative proteomics analysis by label-free data-independent LC-MS/MS.

2022-07-31 | PXD032722 | Pride

In situ transcriptomic analysis of spermatocytes in non-obstructive azoospermia reveals senescence-like states in arrested spermatocytes

Project description:To investigate in situ transcriptome of spermatocytes in non-obstructive azoospermia , we microdissected spermatocytes in formalin-fixed paraffin-embedded testicular biopsy tissue from two types of non-obstructive azoospermia and obstructive azoospermia as a control, and then constructed cDNA libraries based on Smart-3SEQ method.

2023-08-02 | GSE238078 | GEO

Whole Exome Sequencing of two non-obstructive azoospermia patients

Project description:Whole Exome Sequencing of two non-obstructive azoospermia patients

| PRJEB39182 | ENA

Altered mRNA profile in testis of patients with“secondary idiopathic non-obstructive azoospermia”

Project description:Background: Non-obstructive azoospermia (NOA) is the most severe form of male infertility. Currently known causative factors, including congenital and several acquired causes can only account for approximately 30% of NOA cases. Causes for most patients with NOA remains unclear, which were known as idiopathic NOA (iNOA). However, whether iNOA is congenital defects or acquired abnormalities is a confusing problem due to the delayed diagnosis of this frustrating situation until childbearing age. Materials and Methods: In this study, several patients who were diagnosed as iNOA at this stage, but with a history of natural conceptions with female before were enrolled and defined as “secondary idiopathic NOA”. As little was known about these cases, we performed the mRNA expression profiling by Next-generation sequencing (NGS) in this three patients and other three patients with obstructive azoospermia (OA) as controls. Results: A series of mRNAs were found to be altered in testicular tissues between “secondary idiopathic NOA” and controls, including 6028 downregulated and 3402 upregulated mRNAs. GO analysis and KEGG analysis revealed a range of GO and KEGG terms, such as cellular process involved in reproduction, protein digestion and absorption, etc. Conclusion: Overall, this study introduces a novel classification called “secondary idiopathic NOA” in iNOA. We provide a global view of the altered mRNAs involved in spermatogenetic failure in these cases.

2022-06-01 | GSE190752 | GEO

Potential biomarkers of non-obstructive azoospermia identified in microarray gene expression analysis

Project description:We analyzed gene expression profiles of human testicular biopsies in men with idiopathic nonobstructive azoospermia. Using new generation oligonucleotide microarray platform GeneChipM-BM-. Human Gene 1.0 ST, we identified genes which could be potential biomarkers of azoospermia and molecular indicators that could determine a particular stage of impaired spermatogenesis. Thus, we shed light on genes which were had so far been weakly characterized and which were had never related to infertility before. These studies also included the comparative analysis of the hierarchical clustering of gene expression profile with histopathological data provided for azoospermic patients. We analyzed 31 testicular biopsy samples with Affymetrix Human Gene 1.0 ST microarrays. 27 of them were obtained from patients with various types of NOA and 4 with normal spermatogenesis.

2013-09-16 | E-GEOD-45885 | biostudies-arrayexpress

Potential biomarkers of non-obstructive azoospermia identified in microarray gene expression analysis

Project description:We analyzed gene expression profiles of human testicular biopsies in men with idiopathic nonobstructive azoospermia. Using new generation oligonucleotide microarray platform GeneChip® Human Gene 1.0 ST, we identified genes which could be potential biomarkers of azoospermia and molecular indicators that could determine a particular stage of impaired spermatogenesis. Thus, we shed light on genes which were had so far been weakly characterized and which were had never related to infertility before. These studies also included the comparative analysis of the hierarchical clustering of gene expression profile with histopathological data provided for azoospermic patients.

2013-09-16 | GSE45885 | GEO

Altered mRNA profile in testis of patients with“secondary idiopathic non-obstructive azoospermia”

Project description:Altered mRNA profile in testis of patients with“secondary idiopathic non-obstructive azoospermia”

| PRJNA788390 | ENA

RNA-seq based transcriptome profiles of the human testis tissues across multiple conditions, with an intention to mainly study non-obstructive azoospermia

Project description:To study alternatively spliced isoforms expressed differently in the testis of donors with Non-Obstructive Azoospermia (NOA), testicular biopsies were collected from donors with NOA condition (as identified by cytological examination) and Obstructive Azoospermia (OA), and Varicocele (VA) conditions. The biopsy samples were stored in RNA-later solution (Ambion, cat # AM7024), according to the manufacturer's guidelines. RNA was extracted using the RiboPure kit (Ambion cat # AM1924). Two normal commercial testicular RNA (Clontech cat. no.: 636533, Asian: lot no: 1105041; Caucasian: lot. no.: LOT1105214A) samples were also used. The RNA quality was checked with formaldehyde agarose gel electrophoresis as well as a micro-volume spectrophotometer. For NGS, testicular RNA from 8 NOA, 2 OA and 2 Varicocele donors were used. Paired-end library preparation was carried out using Illumina TruSeq RNA Library Prep Kit v2, and sequencing was done using the Illumina HiSeq 2000. After quality checks, seqtk (https://github.com/lh3/seqtk) was used for trimming low-quality reads. Alignments, identification of transcripts and the chimeric/transplice molecules, and their quantification were performed by Kallisto software. Sample segregation according to the corresponding donor condition was confirmed via clustering RNA-seq data from the samples.

2023-03-10 | GSE216907 | GEO

Loss-of-function mutations TDRD7 lead to a rare novel syndrome combining congenital cataract and non-obstructive azoospermia in humans

Project description:Purpose: Comorbid familial non-obstructive azoospermia (NOA) and congenital cataract (CC) has not been reported previously, and no single human gene has been associated with both diseases in humans. Our purpose is to uncover novel human mutations and genes causing familial NOA and CC. Methods: We performed whole-exome sequencing for two brothers with both NOA and CC from a consanguineous family.The proband was also carried out SNP array analysis. Mutation screening of TDRD7 was performed in another similar consanguineous family and 176 patients with azoospermia or CC alone and 520 healthy controls. Histological analysis was performed for the biopsied testicle sample in one patient, and knockout mice were constructed to verify the phenotype of the mutation in TDRD7. Results: Two novel loss-of-function mutations (c.324_325insA (T110Nfs*30) and (c.688-689insA (p.Y230X), respectively) of TDRD7 were found in the affected patients from the two unrelated consanguineous families. Histological analysis demonstrated a lack of mature sperm in the male patient’s seminiferous tubules. The mutations were not detected in patients with CC or NOA alone. Mice with Tdrd7 gene disrupted at a similar position precisely replicated the human syndrome. Conclusions: We identified TDRD7 causing CC as a new pathogenic gene for male azoospermia in human, with an autosomal recessive mode of inheritance.

2017-06-15 | GSE100019 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data