A continuous increase in the prevalence of heart failure and the lack of adequate therapy highlight poor understanding of the underlying genetic regulatory mechanisms involved in heart failure pathogenesis. Growing evidence has demonstrated a signi cant contribution of non-coding genome regulatory elements towards transcriptomic changes in heart disease. Thus, there is a pressing need for a comprehensive resource of the human cardiac regulatory network in healthy and failing states. We applied cap analysis of gene expression sequencing to directly measure the expression of RNA associated with enhancers and promoters. Based on this data, we constructed the atlas of transcribed cardiac regulatory elements from 21 healthy and 10 failing (ischemic and non-ischemic cardiomyopathy) human hearts. In total, we have sequenced 109 samples from the left and right atria and ventricles, identifying 17,668 promoters and 14,920 enhancers associated with 14,519 genes. Leveraging this atlas, we provide insights into functional and structural regulatory changes between healthy and failing hearts. Healthy atria and ventricles had distinct pathway enrichment and transcription factor binding patterns, signi cantly remodeled by heart failure. Using the advantages of deep sequencing that allow effective analysis of cis-regulatory elements-derived RNA, we found that heart failure is associated with the expression of transcripts derived from alternative promoters and a speci c set of transcribed enhancers. Furthermore, we identi ed a high prevalence of single nucleotide polymorphisms associated with cardiovascular diseases within the regulatory regions highlighting their importance in disease pathogenesis. This open-source atlas will serve the cardiovascular community to improve understanding cardiac regulatory network and facilitate the development of novel therapeutics.

Transcription of the human genome yields mostly long non-coding RNAs (lncRNAs). Systematic functional annotation of lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. Currently, 95% of human lncRNAs have no functional characterization. Using chromatin conformation and Cap Analysis of Gene Expression (CAGE) data in 18 human cell types, we systematically located genomic regions in spatial proximity to lncRNA genes and identified functional clusters of interacting protein-coding genes, lncRNAs and enhancers. Using these clusters we provide a cell type-specific functional annotation for 7,651 out of 14,198 (53.88%) lncRNAs. LncRNAs tend to have specialized roles in the cell type in which it is first expressed, and to incorporate more general functions as its expression is acquired by multiple cell types during evolution. By analyzing RNA-binding protein and RNA-chromatin interaction data in the context of the spatial genomic interaction map, we explored mechanisms by which these lncRNAs can act.

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