ArticleBMC genomics2024
Whole transcriptome analysis to identify non-coding RNA regulators and hub genes in sperm of non-obstructive azoospermia by microarray, single-cell RNA sequencing, weighted gene co-expression network analysis, and mRNA-miRNA-lncRNA interaction analysis.
Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Integrated Bulk and Single-Cell Transcriptomic Analysis Reveals Mitochondrial Transporter Gene Programs in Human Spermatogonial Stem Cells.Stem cell reviews and reports · 2026Article
- Identifying Mouse Undifferentiated To Differentiated Spermatogonia Stem Cells at the Single-Cell Level Using Machine Learning Approaches.Stem cell reviews and reports · 2026Article
- Machine learning, whole-transcriptome and integrative omics analysis reveals key regulatory networks governing human spermatogonial stem cells.Clinical and experimental medicine · 2026Article
- Analysis of microarray and single-cell RNA-seq finds gene co-expression, cell-cell communication, and tumor environment associated with cytoskeleton protein in epithelial-mesenchymal transition in ovarian cancer.Discover oncology · 2026Article
- Article
- Microarray and Single-Cell RNA Sequencing Reveals G-Protein Gene Expression Signatures of Spermatogonia Stem Cell.Stem cell reviews and reports · 2025Article
- Analysis of Microarray and Single-Cell RNA-Seq Finds Gene Co-Expression and Tumor Environment Associated with Extracellular Matrix in Epithelial-Mesenchymal Transition in Prostate Cancer.International journal of molecular sciences · 2025Article
- Transcriptomic Analysis Identifies Oxidative Stress-Related Hub Genes and Key Pathways in Sperm Maturation.Antioxidants (Basel, Switzerland) · 2025Article
- Using machine learning to discover DNA metabolism biomarkers that direct prostate cancer treatment.Scientific reports · 2025Article
- Role of Defense/Immunity Proteins in Non-Obstructive Azoospermia: Insights from Gene Expression and Single-Cell RNA Sequencing Analyses.Reproductive sciences (Thousand Oaks, Calif.) · 2025Article
- Comprehensive analysis of long non-coding RNA and mRNA expression patterns during seminiferous tubules maturation in Guanzhong dairy goats.BMC genomics · 2025Article
- Analysis of microarray and single-cell RNA-seq identifies gene co-expression, cell-cell communication, and tumor environment associated with metabolite interconversion enzyme in prostate cancer.Discover oncology · 2025Article
- Single-cell sequencing in non-obstructive azoospermia: insights from primary and re-analysis studies.Frontiers in endocrinology · 2025Review
- Transcriptomic Analysis and Finding of Potential Key mRNA Expression Profile in Human Cumulus Cells During in Vitro Culture and Different Passages Based on Integrated Bioinformatics Analysis.Reproductive sciences (Thousand Oaks, Calif.) · 2024Article
- Integrating Microarray Data and Single-Cell RNA-Seq Reveals Key Gene Involved in Spermatogonia Stem Cell Aging.International journal of molecular sciences · 2024Article
- A prospective diagnostic model for breast cancer utilizing machine learning to examine the molecular immune infiltrate in HSPB6.Journal of cancer research and clinical oncology · 2024Article
- Exploring the interaction between immune cells in the prostate cancer microenvironment combining weighted correlation gene network analysis and single-cell sequencing: An integrated bioinformatics analysis.Discover oncology · 2024Article
- Advances in the diagnosis and treatment of oligoasthenozoospermia based on epigenetic regulation.Therapeutic advances in urologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundThe issue of male fertility is becoming increasingly common due to genetic differences inherited over generations. Gene expression and evaluation of non-coding RNA (ncRNA), crucial for sperm development, are significant factors. This gene expression can affect sperm motility and, consequently, fertility. Understanding the intricate protein interactions that play essential roles in sperm differentiation and development is vital. This knowledge could lead to more effective treatments and interventions for male infertility. MATERIALS AND
methodsOur research aim to identify new and key genes and ncRNA involved in non-obstructive azoospermia (NOA), improving genetic diagnosis and offering more accurate estimates for successful sperm extraction based on an individual's genotype.
resultsWe analyzed the transcript of three NOA patients who tested negative for genetic sperm issues, employing comprehensive genome-wide analysis of approximately 50,000 transcript sequences using microarray technology. This compared gene expression profiles between NOA sperm and normal sperm. We found significant gene expression differences: 150 genes were up-regulated, and 78 genes were down-regulated, along with 24 ncRNAs up-regulated and 13 ncRNAs down-regulated compared to normal conditions. By cross-referencing our results with a single-cell genomics database, we identified overexpressed biological process terms in differentially expressed genes, such as "protein localization to endosomes" and "xenobiotic transport." Overrepresented molecular function terms in up-regulated genes included "voltage-gated calcium channel activity," "growth hormone-releasing hormone receptor activity," and "sialic acid transmembrane transporter activity." Analysis revealed nine hub genes associated with NOA sperm: RPL34, CYB5B, GOL6A6, LSM1, ARL4A, DHX57, STARD9, HSP90B1, and VPS36.
conclusionsThese genes and their interacting proteins may play a role in the pathophysiology of germ cell abnormalities and infertility.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.