Systematic Analysis of Protein Interaction Network Associated with Azoospermia

Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated w...

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Bibliographic Details
Published in:International journal of molecular sciences 2016-11, Vol.17 (11), p.1857-1857
Main Authors: Sabetian, Soudabeh, Shamsir, Mohd Shahir
Format: Article
Language:English
Subjects:
Algorithms
azoospermia
Azoospermia - genetics
Azoospermia - metabolism
CREB-Binding Protein - genetics
CREB-Binding Protein - metabolism
Crk-Associated Substrate Protein - genetics
Crk-Associated Substrate Protein - metabolism
Databases, Genetic
Gene Expression Regulation
Gene Ontology
Gene Regulatory Networks
Genes
Humans
Infertility
Male
Models, Genetic
Ontology
Protein Interaction Mapping - methods
Protein Interaction Maps - genetics
protein interaction network
Proteins
Receptors, Androgen - genetics
Receptors, Androgen - metabolism
RNA-Binding Proteins - genetics
RNA-Binding Proteins - metabolism
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Summary:Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated with azoospermia and to map their relationship, we present the first protein-protein interaction network related to azoospermia and analyze the complex effects of the related genes systematically. Using Online Mendelian Inheritance in Man, the Human Protein Reference Database and Cytoscape, we created a novel network consisting of 209 protein nodes and 737 interactions. Mathematical analysis identified three proteins, ar, dazap2, and esr1, as hub nodes and a bottleneck protein within the network. We also identified new candidate genes, and , which may play a role in azoospermia. The gene ontology analysis suggests a genetic link between azoospermia and liver disease. The KEGG analysis also showed 45 statistically important pathways with 31 proteins associated with colorectal, pancreatic, chronic myeloid leukemia and prostate cancer. Two new genes and associated diseases are promising for further experimental validation.
ISSN:1422-0067
1661-6596
1422-0067
DOI:10.3390/ijms17111857