| Literature DB >> 25879484 |
Marco D'Aurora1,2, Alberto Ferlin3, Marta Di Nicola4, Andrea Garolla5, Luca De Toni6, Sara Franchi7,8, Giandomenico Palka9, Carlo Foresta10, Liborio Stuppia11,12, Valentina Gatta13,14.
Abstract
BACKGROUND: Klinefelter Syndrome (KS) is the most common abnormality of sex chromosomes (47,XXY) and represents the first genetic cause of male infertility. Mechanisms leading to KS testis degeneration are still not completely defined but considered to be mainly the result of germ cells loss. In order to unravel the molecular basis of global testis dysfunction in KS patients, we performed a transcriptome analysis on testis biopsies obtained from 6 azoospermic non-mosaic KS patients and 3 control subjects.Entities:
Mesh:
Year: 2015 PMID: 25879484 PMCID: PMC4362638 DOI: 10.1186/s12864-015-1356-0
Source DB: PubMed Journal: BMC Genomics ISSN: 1471-2164 Impact factor: 3.969
Figure 1Unsupervised hierarchical clustering analysis results. The cluster analysis shows the presence of two different clusters composed respectively by 247 down-regulated genes (Cluster A) and 656 up-regulated transcripts (Cluster B). Each row represents a differentially expressed genes. In green the genes down-regulated, in red the genes up-regulated for each replicate. In grey and black are represented respectively the genes not modulated or with missing data for the given replicate. Each column represents an experimental condition, labelled as the specific KS patient vs. control. The columns labelled with the same name stand for the two performed replicate as dye-swap.
Figure 2IPA-inferred biological functions associated to Cluster A and B gene datasets. A) Bar charts indicate IPA-inferred key biological functions modulated by down-regulated genes in Cluster A. C) Bar charts indicate IPA-inferred key biological functions modulated by up-regulated genes in Cluster B. The –log (p-value), is calculated by IPA based on the number of genes involved in the function and their reported role. B, D) Down and up-regulated transcripts in Cluster A and B classified for molecule type.
Figure 3IPA-inferred top networks associated to Cluster A and B gene datasets. A) Top gene network generated by IPA for Cluster A down-regulated gene dataset. The network is centered around the key node gene BRCA1, involved in testis cell death. B) Top gene network generated by IPA for Cluster B up-regulated gene dataset. The central node of this network is SMAD3, involved in SCs functionality. Grey genes represent the deregulated genes associated to each Cluster while white genes represent those transcripts not modulated in KS testis vs. control testis.
Figure 4IPA-inferred Sertoli cell – Sertoli cell junction signalling pathway. The figure shows the significant deregulation of the Sertoli cell pathway generated by the analysis of both up- and down-regulated transcript datasets, mainly involved in Blood-Testis-Barrier maintenance. In grey are labelled the genes deregulated in KS testis vs. control testis.