Abstract
With unprecedented increase in next generation sequencing technologies, there has been a persistent interest on transcript profiles of long non-coding RNAs (lncRNAs) and protein-coding genes forming an interaction network. Apart from protein–protein interaction (PPI), gene network models such as Weighted Gene Co-expression Network Analysis (WGCNA) are used to functionally annotate lncRNAs in identifying their potential disease associations. To address this, studies have led to characterizing transcript structures and understanding expression profiles mediating regulatory roles. In the current exploratory analysis, we show how a lncRNA – cyp2c91 contributes to the transcriptional regulation localized to cytoplasm thereby making refractory environment for transcription. By applying network methods and pathway analyses on genes related to a disease such as obesity and systemic lupus erythematosus, we show that we can gain deeper insight in biological processes such as the perturbances in immune system, and get a better understanding of the systems biology of diseases.
Highlights
The long non-coding RNAs are known to be involved in several biological roles including epigenetic regulation, immune signaling, aberrant methylation of imprinted genes and cell cycle (Li et al, 2015)
With unprecedented increase in generation sequencing (NGS) technologies, there has been a persistent interest on transcript profiles of long non-coding RNAs (lncRNAs) and protein-coding genes forming an interaction network
Consistent with the interaction networks, subcellular localization of the products of the three protein-coding genes revealed that two are nuclear while one, CCR1 was found to be in cytoplasm
Summary
With unprecedented increase in generation sequencing technologies, there has been a persistent interest on transcript profiles of long non-coding RNAs (lncRNAs) and protein-coding genes forming an interaction network. Apart from protein–protein interaction (PPI), gene network models such as Weighted Gene Co-expression Network Analysis (WGCNA) are used to functionally annotate lncRNAs in identifying their potential disease associations. Studies have led to characterizing transcript structures and understanding expression profiles mediating regulatory roles. By applying network methods and pathway analyses on genes related to a disease such as obesity and systemic lupus erythematosus, we show that we can gain deeper insight in biological processes such as the perturbances in immune system, and get a better understanding of the systems biology of diseases
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