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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Main Authors: Soudabeh Sabetian, Mohd Shahir Shamsir
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:International Journal of Molecular Sciences
Subjects:
Online Access:http://www.mdpi.com/1422-0067/17/11/1857
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spelling doaj-990dfa392dc6425eaabc1ba393ed86f62020-11-25T02:27:32ZengMDPI AGInternational Journal of Molecular Sciences1422-00672016-11-011711185710.3390/ijms17111857ijms17111857Systematic Analysis of Protein Interaction Network Associated with AzoospermiaSoudabeh Sabetian0Mohd Shahir Shamsir1Department of Biological and Health Sciences, Faculty of Bioscience & Medical Engineering, Universiti Teknologi Malaysia, 81310 Johor, MalaysiaDepartment of Biological and Health Sciences, Faculty of Bioscience & Medical Engineering, Universiti Teknologi Malaysia, 81310 Johor, MalaysiaNon-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, CREBBP and BCAR1, 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.http://www.mdpi.com/1422-0067/17/11/1857azoospermiagene ontologyinfertilityprotein interaction network
collection DOAJ
language English
format Article
sources DOAJ
author Soudabeh Sabetian
Mohd Shahir Shamsir
spellingShingle Soudabeh Sabetian
Mohd Shahir Shamsir
Systematic Analysis of Protein Interaction Network Associated with Azoospermia
International Journal of Molecular Sciences
azoospermia
gene ontology
infertility
protein interaction network
author_facet Soudabeh Sabetian
Mohd Shahir Shamsir
author_sort Soudabeh Sabetian
title Systematic Analysis of Protein Interaction Network Associated with Azoospermia
title_short Systematic Analysis of Protein Interaction Network Associated with Azoospermia
title_full Systematic Analysis of Protein Interaction Network Associated with Azoospermia
title_fullStr Systematic Analysis of Protein Interaction Network Associated with Azoospermia
title_full_unstemmed Systematic Analysis of Protein Interaction Network Associated with Azoospermia
title_sort systematic analysis of protein interaction network associated with azoospermia
publisher MDPI AG
series International Journal of Molecular Sciences
issn 1422-0067
publishDate 2016-11-01
description 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, CREBBP and BCAR1, 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.
topic azoospermia
gene ontology
infertility
protein interaction network
url http://www.mdpi.com/1422-0067/17/11/1857
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