Circ Cardiovasc Genet. 2016 Oct;9(5):395-407.

Decoding the Long Noncoding RNA During Cardiac Maturation: A Roadmap for Functional Discovery

Touma M1,2, Kang X1, Zhao Y1, Cass AA3, Gao F4, Biniwale R5, Coppola G4, Xiao X3, Reemtsen B5, Wang Y2,7


Author’s Affiliation

1) The Children’s Discovery and Innovation Institute (CDI), Department of Pediatrics, University of California, Los Angeles, CA.

2) Cardiovascular Research Laboratory, University of California, Los Angeles, CA

3) Bioinformatics interdepartmental program, University of California, Los Angeles, CA

4) Department of Neurology, University of California, Los Angeles, CA

5) Department of Cardiothoracic Surgery, University of California, Los Angeles, CA.

6) Department of Anesthesiology, University of California, Los Angeles, CA

7) Department of Anesthesiology, Physiology and Medicine, University of California, Los Angeles, CA.



Marlin Touma, MD, PhD

David Geffen School of Medicine, University of California, Los Angeles

10833 Le Conte Ave, B2-375, MDCC, Los Angeles, CA 90095. USA.

Tel: 310-206-6197 / Fax: 310-267-0154 / E-mail 



Background – Cardiac maturation during perinatal transition of heart is critical for functional adaptation to hemodynamic load and nutrient environment. Perturbation in this process has major implications in congenital heart defects. Transcriptome programming during perinatal stages is an important information but incomplete in current literature, particularly, the expression profiles of the long noncoding RNAs (lncRNAs) are not fully elucidated.

Methods and Results – From comprehensive analysis of transcriptomes derived from neonatal mouse heart left and right ventricles, a total of 45 167 unique transcripts were identified, including 21 916 known and 2033 novel lncRNAs. Among these lncRNAs, 196 exhibited significant dynamic regulation along maturation process. By implementing parallel weighted gene co-expression network analysis of mRNA and lncRNA data sets, several lncRNA modules coordinately expressed in a developmental manner similar to protein coding genes, while few lncRNAs revealed chamber-specific patterns. Out of 2262 lncRNAs located within 50 kb of protein coding genes, 5% significantly correlate with the expression of their neighboring genes. The impact of Ppp1r1b-lncRNA on the corresponding partner gene Tcap was validated in cultured myoblasts. This concordant regulation was also conserved in human infantile hearts. Furthermore, the Ppp1r1b-lncRNA/Tcap expression ratio was identified as a molecular signature that differentiated congenital heart defect phenotypes.

Conclusions—The study provides the first high-resolution landscape on neonatal cardiac lncRNAs and reveals their potential interaction with mRNA transcriptome during cardiac maturation. Ppp1r1b-lncRNA was identified as a regulator of Tcap expression, with dynamic interaction in postnatal cardiac development and congenital heart defects.

© 2016 American Heart Association, Inc.

KEYWORDS: congenital cardiac defect; gene regulation; lncRNA; neonatal heart maturation; neonatal mouse cardiomyocyte; transcriptome

PMID: 27591185

PMCID: PMC5085833 Available on 2017-10-01]

DOI: 10.1161/CIRCGENETICS.115.001363



Revealed as a mysterious layer between the genome and the proteome, the long noncoding RNAs have revolutionized the traditional view of central dogma of biology, shedding the lights to the dark matter of the genome, and leading to exciting opportunities for further understanding of developmental biology and human diseases.

Congenital heart defects (CHDs) affect approximately 1% of live births and are a major source of childhood morbidity and mortality. Residing in the non-coding regions of the genome, the lncRNAs are increasingly recognized as important players in cardiac development and pathogenic mechanisms of CHDs [1-4].  Our finding provides one of the first comprehensive landscape of lncRNA profile in developing hearts. The results support putative regulatory role of lncRNAs in transcriptome programming during a critical window of neonatal heart chamber maturation that may impact postnatal heart development and pathology [5]. The article provides transcriptome analysis pipeline and opens new avenue to explore disease modifiers, diagnostic biomarkers and therapeutic targets with potential implications in the newborn infants with a CHD. The entire dataset is disseminated through a new online resource (Neonatal Heart Maturation SuperSeries GSE85728 (http://www.ncbi. for research community.

It is becoming clear that the lncRNAs expression can be highly context and time dependent [6,7].  However, the lncRNAs expression pattern during perinatal transition window has not been previously defined. In this paper we attempted to fills this gap of knowledge by implementing the current advancement of genome wide transcriptome characterization using deep RNA-sequencing and advanced bioinformatics analysis tools. We provide the first delineation of transcriptome landscape in neonatal heart left and right ventricles during 3 stages of fetal to neonatal transition at high level of resolution.  The paper highlights the dynamic nature of lncRNAs expression in neonatal heart in parallel to protein coding genes.  Hence, the lncRNAs are subject to large-scale temporal variation in even a narrow, tightly regulated window of fetal to neonatal development, suggesting a potential regulatory impact in fine-tuning overall cellular transcriptome patterns in a highly sensitive manner.

Not only do lncRNAs exhibit dynamic regulation, but also the tissue specificity of the lncRNAs species has surpassed that of protein coding transcripts [7,8]. During perinatal transition, the left and right ventricle undergo significant changes in morphology and work load, to our surprise, our study revealed few lncRNAs exhibiting chamber specific pattern. These observations may suggest that lncRNA transcription is more intimately linked with premodial tissue and plastic cell phenotypes. Indeed, the tissue and cell specificity of lncRNAs has been shown most elegantly during cardiac progenitor differentiation and early cardiogenesis [3,9].

Much of the pioneering work in transcriptome characterizing during heart development was focused on differential expression studies of the lncRNAs and mRNA separately [7,8]. In this paper we furthered our analysis by performing unsupervised weighted gene network co- expression analysis (WGCNA) along the 3 time points. Our systemic approach reveled several lncRNA and mRNA co-expression modules coordinately and temporally shared in both ventricles, including a total of 33 lncRNAs (11 known and 22 novel) that were significantly concordant with their corresponding mRNA modules in a developmental stage-specific fashion reflecting the rapid adaptation of cardiovascular system to rapid changes in circulation and adaptation to postnatal environment.

It is one of the most challenging issue for lncRNA biology is to depict the biological function with very limited prior information and structural-function insights [10]. We attempted to overcome these difficulties by utilizing a systematic, step-wise, algorithm [Figure 1]. After constructing lncRNA/mRNA modules we examined lncRNAs association and correlation with neighboring gene expression. In total, we reported 114 lncRNAs, including 12 novel lncRNAs, showed significantly correlated expression pattern with a neighboring mRNA. Then, we validated the expression and preservation of the regulatory relationship of the top 4 pairs in human congenital heart defects samples and performed targeted functional screening studies. Finally, we demonstrated that the Ppp1r1b-lncRNA can potently modulate its neighboring partner gene Tcap, and the expression ratio of Ppp1r1b-lncRNA/Tcap segregates different types of CHDs.

In conclusion, the findings of our paper hinted at a higher order regulatory architecture for controlling gene expression at the transcript level, and that the lncRNA was able to play a key role as a regulator. These insights would advance our current understanding of the gene regulatory network and potential mechanisms of perinatal heart development and CHDs.



Figure 1. Schematic representation of workflow pipeline for predicting functional lncRNAs and prioritization for functional screening and validation in human.



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