scholarly journals Genome-Wide Network Analysis Reveals the Global Properties of IFN-β Immediate Transcriptional Effects in Humans

2007 ◽  
Vol 178 (8) ◽  
pp. 5076-5085 ◽  
Author(s):  
Guy Haskin Fernald ◽  
Simon Knott ◽  
Andrew Pachner ◽  
Stacy J. Caillier ◽  
Kavitha Narayan ◽  
...  
Keyword(s):  
Network Analysis ◽  
Global Properties ◽  
Genome Wide

scholarly journals Evaluation of the Common Molecular Basis in Alzheimer’s and Parkinson’s Diseases

2019 ◽  
Vol 20 (15) ◽  
pp. 3730 ◽  
Author(s):  
Pratip Rana ◽  
Edian F. Franco ◽  
Yug Rao ◽  
Khajamoinuddin Syed ◽  
Debmalya Barh ◽  
...  
Keyword(s):  
Network Analysis ◽  
Literature Mining ◽  
Extensive Literature ◽  
Genome Wide ◽  
Parkinson’S Diseases ◽  
Epigenetic Regulator ◽  
Major Genome ◽  
The Common ◽  
Exact Relationship ◽  
Subsequent Literature

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (HLA-DRB5) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD.

scholarly journals Genome-wide identification and co-expression network analysis of nuclear factor-Y in barley revealed potential functions in salt stress

2019 ◽  
Vol 25 (2) ◽  
pp. 485-495 ◽  
Author(s):  
Bahman Panahi ◽  
Seyyed Abolghasem Mohammadi ◽  
Kamil Ruzicka ◽  
Hossein Abbasi Holaso ◽  
Mohammad Zare Mehrjerdi
Keyword(s):  
Salt Stress ◽  
Network Analysis ◽  
Potential Functions ◽  
Nuclear Factor ◽  
Nuclear Factor Y ◽  
Genome Wide

scholarly journals Systems-Level Analysis of Genome-Wide Association Data

2013 ◽  
Vol 3 (1) ◽  
pp. 119-129 ◽  
Author(s):  
Charles R Farber
Keyword(s):  
Network Analysis ◽  
Genome Wide Association ◽  
Coexpression Network ◽  
Genome Wide Association Studies ◽  
Gene Coexpression Network ◽  
Mineral Density ◽  
Gene Coexpression ◽  
Genome Wide ◽  
Nominal Evidence ◽  
Level Analysis

Abstract Genome-wide association studies (GWAS) have emerged as the method of choice for identifying common variants affecting complex disease. In a GWAS, particular attention is placed, for obvious reasons, on single-nucleotide polymorphisms (SNPs) that exceed stringent genome-wide significance thresholds. However, it is expected that many SNPs with only nominal evidence of association (e.g., P < 0.05) truly influence disease. Efforts to extract additional biological information from entire GWAS datasets have primarily focused on pathway-enrichment analyses. However, these methods suffer from a number of limitations and typically fail to lead to testable hypotheses. To evaluate alternative approaches, we performed a systems-level analysis of GWAS data using weighted gene coexpression network analysis. A weighted gene coexpression network was generated for 1918 genes harboring SNPs that displayed nominal evidence of association (P ≤ 0.05) from a GWAS of bone mineral density (BMD) using microarray data on circulating monocytes isolated from individuals with extremely low or high BMD. Thirteen distinct gene modules were identified, each comprising coexpressed and highly interconnected GWAS genes. Through the characterization of module content and topology, we illustrate how network analysis can be used to discover disease-associated subnetworks and characterize novel interactions for genes with a known role in the regulation of BMD. In addition, we provide evidence that network metrics can be used as a prioritizing tool when selecting genes and SNPs for replication studies. Our results highlight the advantages of using systems-level strategies to add value to and inform GWAS.

scholarly journals Genome-wide analysis of alternative splicing events inHordeum vulgare: Highlighting retention of intron-based splicing and its possible function through network analysis

FEBS Letters ◽  
2015 ◽  
Vol 589 (23) ◽  
pp. 3564-3575 ◽  
Author(s):  
Bahman Panahi ◽  
Seyed Abolghasem Mohammadi ◽  
Reyhaneh Ebrahimi Khaksefidi ◽  
Jalil Fallah Mehrabadi ◽  
Esmaeil Ebrahimie
Keyword(s):  
Alternative Splicing ◽  
Network Analysis ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Alternative Splicing Events

scholarly journals Genome-wide analysis of lncRNAs and mRNAs expression during the differentiation of abdominal preadipocytes in chicken

2016 ◽  
Author(s):  
Tao Zhang ◽  
Xiangqian Zhang ◽  
Kunpeng Han ◽  
Genxi Zhang ◽  
Jinyu Wang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Rna Sequencing ◽  
Early Stage ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Valuable Resource ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
And Function ◽  
Jinghai Yellow Chicken

AbstractlncRNAs regulate metabolic tissue development and function, including adipogenesis. However, little is known about the function and profile of lncRNAs in preadipocytes differentiation of chicken. Here, we identified lncRNAs in preadipocytes of different differentiation stages by RNA-sequencing using Jinghai Yellow chicken. A total of 1,300,074,528 clean reads and 27,023 lncRNAs were obtained from twenty samples. 3095 genes (1,336 lncRNAs and 1,759 mRNAs) were differentially expressed among different stages, of which the number of DEGs decreased with the differentiation, demonstrating that the early stage might be most important for chicken preadipocytes differentiation. Furthermore, 3,095 DEGs were clustered into 8 clusters with their expression patterns by K-means clustering. We identified six stage-specific modules related to A0, A2 and A6 stages using weighted co-expression network analysis. Many well-known/novel pathways associated with preadipocytes differentiation were found. We also identified highly connected genes in each module and visualized them by cytoscape. Many well-known genes related to preadipocytes differentiation were found such as IGFBP2 and JUN. Yet, the majority of high connected genes were unknown in chicken preadipocytes. This study provides a valuable resource for chicken lncRNA study and contributes to batter understanding the biology of preadipocytes differentiation in chicken.

scholarly journals Architecture of the cerebral cortical association connectome underlying cognition

2015 ◽  
Vol 112 (16) ◽  
pp. E2093-E2101 ◽  
Author(s):  
Mihail Bota ◽  
Olaf Sporns ◽  
Larry W. Swanson
Keyword(s):  
Network Analysis ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Axonal Connections ◽  
Architectural Features ◽  
Genome Wide ◽  
Starting Point ◽  
Temporal Pole ◽  
Voluntary Behavior ◽  
Cortical Regions

Cognition presumably emerges from neural activity in the network of association connections between cortical regions that is modulated by inputs from sensory and state systems and directs voluntary behavior by outputs to the motor system. To reveal global architectural features of the cortical association connectome, network analysis was performed on >16,000 reports of histologically defined axonal connections between cortical regions in rat. The network analysis reveals an organization into four asymmetrically interconnected modules involving the entire cortex in a topographic and topologic core–shell arrangement. There is also a topographically continuous U-shaped band of cortical areas that are highly connected with each other as well as with the rest of the cortex extending through all four modules, with the temporal pole of this band (entorhinal area) having the most cortical association connections of all. These results provide a starting point for compiling a mammalian nervous system connectome that could ultimately reveal novel correlations between genome-wide association studies and connectome-wide association studies, leading to new insights into the cellular architecture supporting cognition.

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