scholarly journals Gene network analysis to determine the effect of hypoxia-associated genes on brain damages and tumorigenesis using an avian model

Author(s):  
Hamed Kharrati-Koopaee ◽  
Esmaeil Ebrahimie ◽  
Mohammad Dadpasand ◽  
Ali Niazi ◽  
Rugang Tian ◽  
...  

Abstract Background Hypoxia refers to the condition of low oxygen pressure in the atmosphere and characterization of response to hypoxia as a biological complex puzzle, is challenging. Previously, we carried out a comparative genomic study by whole genome resequencing of highland and lowland Iranian native chickens to identify genomic variants associated with hypoxia conditions. Based on our previous findings, we used chicken as a model and the identified hypoxia-associated genes were converted to human’s orthologs genes to construct the informative gene network. The main goal of this study was to visualize the features of diseases due to hypoxia-associated genes by gene network analysis. Results It was found that hypoxia-associated genes contained several gene networks of disorders such as Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and cancers. We found that biological pathways are involved in mitochondrion dysfunctions including peroxynitrous acid production denoted in brain injuries. Lewy body and neuromelanin were reported as key symptoms in Parkinson disease. Furthermore, calmodulin, and amyloid precursor protein were detected as leader proteins in Alzheimer’s diseases. Dexamethasone was reported as the candidate toxic drug under the hypoxia condition that implicates diabetes, osteoporosis, and neurotoxicity. Our results suggested DNA damages caused by the high doses of UV radiation in high-altitude conditions, were associated with breast cancer, ovarian cancer, and colorectal cancer. Conclusions Our results showed that hypoxia-associated genes were enriched in several gene networks of disorders including Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and different types of cancers. Furthermore, we suggested, UV radiation and low oxygen conditions in high-altitude regions may be responsible for the variety of human diseases.

2015 ◽  
Vol 113 (03) ◽  
pp. 521-531 ◽  
Author(s):  
Riccardo Bellazzi ◽  
Felix Engel ◽  
Fulvia Ferrazzi

SummaryNetworks offer a flexible framework to represent and analyse the complex interactions between components of cellular systems. In particular gene networks inferred from expression data can support the identification of novel hypotheses on regulatory processes. In this review we focus on the use of gene network analysis in the study of heart development. Understanding heart development will promote the elucidation of the aetiology of congenital heart disease and thus possibly improve diagnostics. Moreover, it will help to establish cardiac therapies. For example, understanding cardiac differentiation during development will help to guide stem cell differentiation required for cardiac tissue engineering or to enhance endogenous repair mechanisms. We introduce different methodological frameworks to infer networks from expression data such as Boolean and Bayesian networks. Then we present currently available temporal expression data in heart development and discuss the use of network-based approaches in published studies. Collectively, our literature-based analysis indicates that gene network analysis constitutes a promising opportunity to infer therapy-relevant regulatory processes in heart development. However, the use of network-based approaches has so far been limited by the small amount of samples in available datasets. Thus, we propose to acquire high-resolution temporal expression data to improve the mathematical descriptions of regulatory processes obtained with gene network inference methodologies. Especially probabilistic methods that accommodate the intrinsic variability of biological systems have the potential to contribute to a deeper understanding of heart development.


2016 ◽  
Vol 94 (suppl_4) ◽  
pp. 76-77
Author(s):  
R. Xiang ◽  
J. McNally ◽  
S. J. Rowe ◽  
A. Jonker ◽  
C. Pinares-Patino ◽  
...  

2020 ◽  
Vol 11 ◽  
Author(s):  
Huihui Wang ◽  
Yongqing Wu ◽  
Ruiling Fang ◽  
Jian Sa ◽  
Zhi Li ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document