Dysregulated long intergenic non-coding RNA modules contribute to heart failure

Abstract

Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulatory molecules involved in diseases including heart failure. However, little is known about how the lincRNAs work together with protein-coding genes (PCGs) contributing to the pathogenesis of heart failure. In this study, we constructed a comprehensive transcriptome profile of lincRNAs, PCGs and miRNAs using RNA-seq and miRNA-seq data of 16 heart failure patients (HFs) and 8 non-failing individuals (NFs). Through integrating lincRNA and PCG expression profiles, we identified HF-associated lincRNA modules. We identified a heart-specific lincRNA module which was significantly enriched for differentially expressed lincRNAs and PCGs. This module was associated with heart failure rather than with other clinical traits such as sex, age, smoking and diabetes mellitus. Moreover, the module was significantly correlated with certain indicators of left ventricular function like ejection fraction and left ventricular end-diastolic diameter, implying the potential of its components as crucial biomarkers. Apart from enhancer-like function, lincRNAs in this module could act as competing endogenous RNAs (ceRNAs) to regulate genes which were associated with left-ventricular systolic function. Our work provided deep insights into the critical roles of lincRNAs in the pathology of heart failure and suggested that they could be valuable biomarkers and therapeutic targets.

Keywords: ceRNA; contraction; heart failure; heart specificity; lincRNAmodule.

Figure 1. Transcriptome profiles of lincRNAs, mRNAs and miRNAs

A. The workflow of the construction of transcriptome. The basic features of transcriptome about B. the numbers of exons, C. conservation, D. expression levels of known lincRNAs, novel lincRNAs and PCGs. E. MDS plot using the lincRNA expression levels. F. Heatmaps showing hierarchical clustering of differentially expressed genes and miRNAs. G. Functional enrichment results for up-regulated (red bars) and down-regulated PCGs (green bars).

Figure 2. Identification and characterization of HF-associated lincRNA modules

A. The heatmap on the left panel represents absolute Pearson's correlation between 11 modules and clinical traits including heart failure (HF), sex, age, smoking and diabetes mellitus (DM). P-values of correlation test were filled in the cells. The two panels on the right side denote proportions of differentially expressed lincRNAs and PCGs. The numbers denote the amount of lincRNAs or PCGs in the corresponding modules. B. Enrichment results of gene sets obtained from GSEA Molecular Signatures Database (MSigDB) for heart-associated lincRNA modules. Several module-specific functional gene sets are highlighted in red. C. Heatmap representing frequencies of gene sets enriched by heart-associated lincRNA modules. D. heart-associated lincRNA modules together participate in Wnt signaling pathway. Genes in modules are colored cyan with corresponding module IDs attached. Several lincRNAs highly co-expressed with important components of the Wnt signaling pathway are highlighted in red. E. Several important components in the Wnt signaling pathway show significant expression alterations in heart failure.

Figure 3. Heart specificity of M4

A. Connectivity between genes (lincRNAs and PCGs) in M4 is plotted against the module's first principal component. Red and blue dots represent lincRNAs and PCGs, respectively. B. Co-expression network of M4 in which a lincRNA is linked to a PCG if their expression correlation is greater than 0.75. C. Barplot of the ratio of TSLincRNAs and TSPCGs in each heart-associated lincRNA module. D. Heatmap showing hierarchical clustering of JS scores of lincRNAs in M4 and barplot of JS score of each lincRNA in M4. E. The density plot of Spearman correlation between lincRNAs and EF in each heart-associated lincRNA modules. F. Multiple correlation scatter plot of predicted EF and observed EF. G. Multiple correlation scatter plot of predicted LVEDD and observed LVEDD.

Figure 4. Chromatin states of lincRNAs in M4

A. Heatmaps showing hierarchical clustering of modules based on a certain chromatin state in lincRNAs. B. Venn diagram representing the significant overlap between elincRNAs and lincRNAs in M4. C. Pie chart representing the percentage of DElincRNAs, heart-specific lincRNAs in elincRNAs of M4. D. UCSC genome browser views of histone marks H3K4me1, H3K27ac, H3K4me3, H3K9me3 and H3K27me3 around ENSG00000261434. E. The expression levels of lincRNA ENSG00000261434 in NF controls and HF cases. F. The expression levels of LRRC14B and the expression correlation between ENSG00000261434 and LRRC14B. G. The expression levels of AKAP1and the expression correlation between ENSG00000261434 and AKAP1.

Figure 5. The ceRNA network in M4

A. The lincRNA-associated ceRNA network in M4. B. ENSG00000249816-associated ceRNA regulation in M4. Red stars represent the genes and miRNAs have been reported to be associated with heart development or cardiac disease including heart failure. C. Boxplot of the JS score of ENSG00000249816 in 16 tissues. D. Heatmaps showing the expression levels oflincRNAs, mRNAs and miRNAs in the ceRNA network. E. GO terms enriched by PCGs in the ceRNA network.