Abstract
Long non-coding RNAs (lncRNAs) are an emerging class of RNA species that may play a critical regulatory role in gene expression. However, the association between lncRNAs and atrial fibrillation (AF) is still not fully understood. In this study, we used RNA sequencing data to identify and quantify the both protein coding genes (PCGs) and lncRNAs. The high enrichment of these up-regulated genes in biological functions concerning response to virus and inflammatory response suggested that chronic viral infection may lead to activated inflammatory pathways, thereby alter the electrophysiology, structure, and autonomic remodeling of the atria. In contrast, the downregulated GO terms were related to the response to saccharides. To identify key lncRNAs involved in AF, we predicted lncRNAs regulating expression of the adjacent PCGs, and characterized biological function of the dysregulated lncRNAs. We found that two lncRNAs, ETF1P2, and AP001053.11, could interact with protein-coding genes (PCGs), which were implicated in AF. In conclusion, we identified key PCGs and lncRNAs, which may be implicated in AF, which not only improves our understanding of the roles of lncRNAs in AF, but also provides potentially functional lncRNAs for AF researchers.
Highlights
Atrial fibrillation (AF), one of the most common serious arrhythmia worldwide, whose extreme complications such as heart failure and embolic stroke are often of high risks and associated with increasing morbidity and mortality (Conen et al, 2011)
The analysis of sequencing data with 6 atrial fibrillation (AF) patients and 6 controls allowed us to identify 15,147 genes in total (FPKM > 1 in at least one sample), which consisted of 29 RNA categories, including protein-coding genes (PCGs), pseudogenes, antisense RNAs and etc. (Figure 1A)
Given a threshold of FPKM >1 in at least 25% samples (n = 3), we identified 9,233 PCGs, 2,213 Long non-coding RNAs (lncRNAs), and 961 other ncRNA genes, which were used for downstream analysis (Figure 1B)
Summary
Atrial fibrillation (AF), one of the most common serious arrhythmia worldwide, whose extreme complications such as heart failure and embolic stroke are often of high risks and associated with increasing morbidity and mortality (Conen et al, 2011). Atrial remodeling, both electrical and structural, are important characteristics in AF (Li et al, 2017; Allessie et al, 2002). Increasing left atrial volume has been stated as a risk factor of cardioembolic stroke, and it is critical to interpret the mechanism behind this to improve the stroke prevention strategy. With the development of next-generation sequencing technologies, non-coding
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