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Genome regulation by long noncoding RNAs in neonatal heart maturation and congenital heart defects

Fetal to neonatal transition of heart is an elaborate process, during which neonatal cardiomyocytes undergo functional maturation and terminal exit from the cell cycle. This tightly regulated process may become rapidly disrupted in the context of congenital heart defects (CHDs). CHDs affect 1% of live births and are a major source of childhood morbidity and mortality. Residing in the non-coding regions of the genome, the long noncoding RNAs (lncRNAs) are increasingly recognized as important regulators of cardiac development and putative key contributors to CHDs. However, lacking sequence conservation and appropriate annotation, elucidating lncRNAs functions has been notoriously challenging. While the roles of most predicted lncRNAs in heart development and CHDs await functional resolution, the biological impacts of regulatory lncRNAs and their mechanisms of action are likely to be diverse, thus requiring focused efforts in these contexts. These limitations can now be circumvented by the combination of advanced, genome-wide, sequencing platforms and powerful functional and molecular tools. In this review article, we discuss principle considerations for regulatory lncRNA discovery. Although we primarily focus on neonatal heart maturation and CHDs, the proposed algorithm should facilitate mechanistic exploration of functional lncRNAs in various disease models. These insights could ultimately lead to novel diagnostics and therapeutic approaches targeting lncRNAs in neonatal heart pathologies and CHDs.


Introduction
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 by shedding lights to the dark matter of the genome and leading to exciting opportunities for further understanding of developmental biology and human diseases as putative disease modifiers, diagnostic biomarkers, and therapeutic targets.
The finding that most of the genome in complex organisms is transcribed has significantly shifted our understanding of genomic and cellular biology. Parallel to current advancement of genomewide transcriptome characterization, by implementing deep RNAsequencing and advanced bioinformatics analysis tools [1][2][3][4], the recent discoveries of the regulatory lncRNAs, which exert diverse functions and can potentially be implicated in development and disease have led to growing interest in deciphering their functional roles in mammalian biology and human disease [1][2][3][4][5][6]. In particular, there is an increasing interest in investigating their roles in heart development and disease [7][8][9][10][11]. Several reports have identified thousands of lncRNAs enriched in heart, dynamically transcribed during cardiac development and differentially regulated in cardiovascular diseases [9][10][11][12]. For example, Bvht (Braveheart) was found to regulate the core cardiac transcription network during cardiogenesis, acting in trans by interacting with SUZ12, a core component of the polycomb repressive complex 2(PRC2) [8], and MIAT (myocardial infarction-associated transcript) was

Abstract
Fetal to neonatal transition of heart is an elaborate process, during which neonatal cardiomyocytes undergo functional maturation and terminal exit from the cell cycle. This tightly regulated process may become rapidly disrupted in the context of congenital heart defects (CHDs). CHDs affect 1% of live births and are a major source of childhood morbidity and mortality. Residing in the non-coding regions of the genome, the long noncoding RNAs (lncRNAs) are increasingly recognized as important regulators of cardiac development and putative key contributors to CHDs. However, lacking sequence conservation and appropriate annotation, elucidating lncRNAs functions has been notoriously challenging. While the roles of most predicted lncRNAs in heart development and CHDs await functional resolution, the biological impacts of regulatory lncRNAs and their mechanisms of action are likely to be diverse, thus requiring focused efforts in these contexts. These limitations can now be circumvented by the combination of advanced, genome-wide, sequencing platforms and powerful functional and molecular tools. In this review article, we discuss principle considerations for regulatory lncRNA discovery. Although we primarily focus on neonatal heart maturation and CHDs, the proposed algorithm should facilitate mechanistic exploration of functional lncRNAs in various disease models. These insights could ultimately lead to novel diagnostics and therapeutic approaches targeting lncRNAs in neonatal heart pathologies and CHDs.
identified by genome-wide association studies GWAS as a risk factor for myocardial infarction [12]. Nevertheless, the precise mechanistic details on how lncRNAs expression may affect heart development or induce heart pathology remain limited to few reports and we are only at the beginning to understand the putative implications of these emerging genomic regulators in CHDs. Developmental and functional maturation of neonatal heart is determined by its gene expression network, which is regulated by genetic and epigenetic mechanisms, including lncRNAs [1][2][3][4]. The proved links between lncRNAs and heart development [8][9][10] indicate that lncRNAs comprise core transcriptional regulatory circuits with key transcription factors. Furthermore, lncRNAs can potentially mediate pathological response to hemodynamic and environmental stress factors in the context of CHDs. Therefore, establishing lncRNAs function can yield novel biomarkers and targets for therapy. Elucidating the functional roles of these emerging regulators is a crucial step toward important translational implications in neonatal heart maturation in the context of CHDs.

General Characteristics of LncRNA
First discovered in the early 1990s, lncRNAs are arbitrarily defined as the RNA species of >200 nucleotides in length, lacking a significant open reading frame (ORF), and much less conserved than the proteincoding genes [9][10][11]. As a transcriptional class, the lncRNAs are grouped according to their genomic location and orientation as compared to the closest coding gene [13] (Figure 1). Intergenic lncRNAs are located in between two coding genes, not overlapping therefore with any coding sequences. A subclass of intergenic lncRNA is enhancer-associated lncRNAs, many of which are bidirectional, lacking a poly A tail, and expressed at low copy number. In contrast, intragenic lncRNAs overlap with coding sequences. In this case, lncRNAs can be transcribed from the sense or the antisense strand. A subclass of intragenic overlapping antisense lncRNAs is the natural antisense transcripts (NATs), which complement and regulate their opposite coding genes expression. Intronic lncRNAs represent a class of lncRNAs that are encoded within introns of protein-coding genes. Finally, bidirectional lncRNAs are transcribed at the close vicinity of a protein-coding gene on the opposite strand [5,6,[17][18][19][20].
LncRNAs are pervasively transcribed throughout the genome displaying remarkable similarities to classical messenger RNAs (mRNAs) in that they are transcribed by RNA Polymerase II (RNAPII), 5' capped, and polyA tailed, and are generally, alternatively spliced [18][19][20][21][22]. Compared to mRNAs, most lncRNAs are expressed at relatively lower levels, associating with chromatin modifying complexes or splicing machinery. Although some IncRNAs are expressed at levels comparable to mRNAs, those appear to function as structural scaffolds for nuclear domains. Finally, IncRNAs may exhibit specific subcellular localization (cytoplasmic vs nucleus), suggesting roles in regulating specialized cellular functions in these compartments [23].

Functional Diversity of LncRNAs
Featuring temporal regulation, and tissue and cell specificity, as well as functional diversity [24][25][26], the lncRNAs have increasingly expanded the functional complexity of transcriptome. It is increasingly evident that lncRNAs play important roles in regulating gene expression at different levels, including epigenetic modification, transcription regulation, and post-transcriptional processing [24]. While the natural antisense transcripts (NATs) are most likely to repress expression of their complementary counterpart [17,20], which in most cases lies directly in the opposite strand at the same genomic locus, the other classes, however, have diverse functions derived from their ability to fold into complex secondary and tertiary structures. Furthermore, lncRNAs can partially hybridize with DNA leading to the formation of scaffold structures for RNA processing, histone modification, protein binding, and to a minimal extent, protein coding. Moreover, lncRNAs can interact with proteins, modifying their activities, dictating their localizations, and executing their functions via acting as decoys, scaffolds or guides. Taken together, unlike microRNAs, which uniformly carry out repressive functions, lncRNAs are thought to exert diverse regulatory potential acting in cis or in trans to induce or suppress the expression of their target genes by employing a wide range of molecular mechanisms [23][24][25][26].
One important theme of regulatory lncRNAs, which is supported by several experimental evidences, is that lncRNAs transcription can have profound consequences on nearby gene expression by using direct or indirect mechanisms. Transcription of a given lncRNA across the promoter region of a protein-coding gene can directly interfere with transcription factor binding to the promoter and thus prevent the expression of the neighboring gene. Such transcriptional interference mechanism has been shown to regulate key developmental decisions. One example is regulating homeotic HOX genes expression pattern and localization [27]. Even if not directly interfering with nearby promoter transcription, lncRNAs can induce histone modifications that repress transcription initiation of overlapping protein-coding genes. For example, HOTAIR (HOX Antisense Intergenic RNA) recruits the polycomb chromatin remodeling complex PRC2 inducing heterochromatin formation in specific genomic loci leading to transcriptional repression [28]. Furthermore, several lncRNAs, including the protypical lncRNA Xist (X inactive-specific transcript), have been implicated in gene silencing or activation by guiding chromatin-modifying enzymes and associated lncRNAs to their target genes [28][29]. Alternatively, lncRNA transcription can arise in a stepwise manner from multiple sites upstream of a promoter, causing a chromatin-opening cascade, which proceed progressively toward the mRNA transcription start site acting in trans [30]. Moreover, lncRNAs can function by regulating transcription through interacting with RNAbinding proteins [31], such as Polycomb and Trithorax group members acting as a coactivator of TFs [32]. They can also serve as precursors or as a sponge for small interfering RNAs (siRNAs) titrating their activity [33], or regulating gene expression at the post-transcriptional editing, including the splicing level [7].

Genomic Discovery of Regulatory LncRNAs in Neonatal Heart Maturation and CHDs
Lacking sequence conservation, identification and functional characterization of lncRNAs have been challenging. However, with the combination of advanced sequencing and analytic platforms and powerful functional screening tools, these limitations can now be circumvented, leading to increased understanding of the regulatory lncRNAs roles in cardiac development and disease. Elegant studies have implicated lncRNAs in the regulation of chromatin and the control of the pluripotency network [34,35]. Other recent reports have identified Braveheart, Fender and Myheart [8,10,36,37] as critical players during heart development and disease. More recently three new players were reported in early cardiovascular development of vertebrate heart [9]. However, limited reports have focused on elucidating lncRNAs roles in neonatal heart maturation, particularly in the context of CHDs.
Aiming to improve our understanding of this important layer of genome regulation in neonatal heart maturation and their potential implication in CHDs, we and others have implemented deep RNAsequencing and comprehensive bioinformatics analysis to explore the lncRNAs world in neonatal heart [1][2][3][4]. Neonatal lncRNAs profiling reported in our study [1] complemented two reports where deep RNA sequencing was implemented in postnatal hearts at specific time points, Intergenic lncRNA, transcribed intergenically from one or both strands (Bidirectional). Intronic lncRNA, transcribed entirely from introns of protein-coding genes. Sense lncRNA, transcribed from the sense strand of protein-coding genes, overlapping with protein-coding sequence. Antisense lncRNA, transcribed from the antisense strand of protein-coding genes, overlapping with protein-coding sequence focusing on data from P2 and P13 hearts and from P1 and P21 hearts, respectively. Moreover, our analysis focused on lncRNA profile and correlation to mRNA in neonatal heart left and right ventricles during the critical window of perinatal circulatory transition (before and after ductal closure), which was not included in these two data sets. We also employed systems genetics tools and different methods from these two studies. Our findings provide the first delineation of transcriptome landscape in neonatal left and right ventricular chambers during three stages of fetal to neonatal transition at high level of resolution. This is the first time the neonatal heart coding genes and lncRNAs expression have been systematically analyzed in spatial-temporal manner, providing supportive evidence of the putative regulatory roles of lncRNAs in transcriptome programming, all of which may help identify functional lncRNAs of potential translational values in neonatal heart maturation in the context of CHDs.
Our genome-wide analysis pipeline highlights the dynamic nature of lncRNAs expression in neonatal heart in parallel to protein-coding genes. Hence, we learned that 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 tight dynamic regulation, but also the tissue specificity of the lncRNAs species has surpassed that of protein-coding transcripts [3,10]. During perinatal transition, the left and right ventricle undergo significant changes in morphology and workload. To our surprise, our study revealed few lncRNAs exhibiting chamber-specific pattern. From these observations we speculate 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 clearly and elegantly during cardiac progenitor differentiation and early cardiogenesis [38].
The entire dataset is disseminated through a new online resource (Neonatal Heart Maturation SuperSeries GSE85728 (http://www. ncbi. nlm.nih.gov/geo/query/acc.cgi?acc=GSE85728) for research community. In the following we summarize the lessons learned and highlighted insights that may serve to move forward regulatory lncRNAs discovery in this context.

Analysis Pipeline for LncRNA Discovery
A workflow summarizing our lncRNA discovery pipeline is shown in Figure 2. The first step in the analysis process is to assemble transcripts from the RNA-seq derived sequence reads.
In our work, since we focus on identification of lncRNAs in mouse for which the genome sequences are well annotated, we have used a classical approach of first mapping RNA-Seq reads to the genome and then performing transcriptome reconstruction using the Cufflinks algorithm [20]. An alternative strategy is to perform De Novo transcript assembly directly from the sequence reads without the need of a reference genome [11]. The latter strategy is necessary when no reference genome is available. We started from three or more samples of ribosomal RNA depleted, polyA enriched mRNA to construct strand specific cDNA libraries and sequence to a depth of approximately 300 million 100x100 nt paired end reads. A minimum of three biological replicates per condition is necessary to enable any meaningful downstream statistical comparisons in a highly controlled experiment. Following transcript assembly from mapped sequence reads, the next step is to merge or align the results of the raw transcript prediction with known transcripts from a reference database of annotated transcripts such as Ensembl database [1]. This is performed using Cuff merge, which is part of the Cufflinks package.
Having identified the previously annotated transcripts, separating the transcripts into known and novel is now possible, including both protein-coding and noncoding transcripts at this stage. Following this step novel lncRNAs can be identified by filtering out those transcripts that contain an ORF exceeding 100 bp (likely protein-coding transcript, or contain a single exon (likely technical artifacts), as well as those transcripts that are below 200nt in length (as per accepted standards to define a lncRNA), and then use Gene ID to score novel transcripts for their coding potential. In our experience, using read depths of over 300 million paired-end stranded reads, we were recently able to identify more than 2800 novel lncRNAs in neonatal heart during perinatal transition stages [1]. Finally, whether a given RNA transcript exerts protein-coding potential is fundamental to the definition of lncRNA and remains challenging task. Several methods have been implemented recently to ascertain the lack of coding potentials of novel transcripts, including invitro expression and translation, codon substitution frequency analysis and ribosomal profiling among several others [39][40][41][42].

Regulatory LncRNAs in Neonatal Heart Maturation and CHDs: Functional Prediction, Challenges, and Limitation
Navigating the most difficult issue in lncRNA biology that is to depict the biological function of a putative regulatory lncRNA with poor structural conservation and very limited prior information of biochemical properties is a challenging task [17]. To overcome these difficulties, putative candidates can be prioritized for functional characterization based on a number of criteria including: a. cytoplasmic vs. nuclear expression. b. tissue-and cell type-specific expression. c. correlated expression with physiological indices. d. association with specific chromatin states. e. correlated co-expression with coding genes of functional relevance (a guilt-by-association approach). f. dynamic regulation in response to developmental or environmental stimuli. g. the existence of a human ortholog.
As previously stated, a useful clue for defining the range of interactions for a given lncRNA is determining its subcellular localization. Nuclear lncRNAs may influence transcriptional outputs through multiple mechanisms, including epigenetic modifications, interactions with transcription factors, and affecting mRNA processing or export. On the contrary, predominantly cytoplasmic lncRNAs may function through different mechanisms, including influencing the stability of an mRNA, affecting translation initiation, acting as competing endogenous RNAs, or influencing post-translational modification [23].
In our work, we utilized a systematic, stepwise, algorithm [ Figure  2]. As mentioned above, many lncRNAs can remodel their local chromatin environment to regulate the expression of nearby coding genes in cis in response to developmental and environmental ques. Much of the pioneering work in transcriptome characterization during heart development was focused on differential expression studies of the lncRNAs and mRNA separately [3,4]. In our work, we furthered our analysis by performing parallel, unsupervised weighted gene co-expression network analysis (WGCNA) [43,44] along the 3 time points on the protein-coding and long noncoding transcript (a guiltby-association approach). Hence, our integrative, systems-based, approach revealed several lncRNA and mRNA co-expression modules that are stage-specific and coordinately shared in both ventricles. These modules included 33 members (11 known and 22 novel) of abundantly expressed lncRNAs, which exhibited concordant regulation with their corresponding mRNA modules in a stage-specific fashion reflecting the rapid adaptation of cardiovascular system to sharp changes in circulation and postnatal environment.
After constructing lncRNA/mRNA modules, we examined lncRNAs correlation with neighboring gene expression. In total, we reported 114 lncRNAs, including 12 novel lncRNAs that showed significantly correlated expression pattern with a neighboring mRNA.
Next, we identified their potential orthologues in human. Then, we validated the expression of candidate lncRNA/mRNA pairs by quantitative RT-PCR in neonatal mouse heart and human CHDs samples to examine expression levels and tissue specificity. Finally, we verified that the regulatory relationship of the top four correlated lncRNA/mRNA pairs (Ucp2-lncRNA, n420212, FUS-lncRNA, and Ppp1r1b-lncRNA and their partner mRNAs, UCP3, KCNB1, TRIM72, and TCAP, respectively) is preserved in human CHDs samples. Furthermore, the expression ratio of Ppp1r1b-lncRNA/Tcap segregated CHDs based on their structural phenotypes [1].
To better understand the physiological roles of regulatory lncRNAs in neonatal heart development, we employed antisense oligos (GapmeR) to achieve targeted Ppp1r1b-lncRNA silencing in C2C12 cells, a muscle myoblast cell line. Our findings demonstrated that the Ppp1r1b-lncRNA modulates its neighboring partner gene Tcap (titin cap), which is important for sarcomeric integrity and function, and other muscle regulatory factors, leading to promoting myogenic differentiation process.

Conclusions and Future Directions
Our findings hinted at a higher order regulatory architecture for controlling gene expression at the genome-wide and the transcriptspecific levels, in which the lncRNAs were demonstrated to have potential regulatory roles in neonatal heart maturation and CHDs. These insights provide essential foundations that would advance our current understanding of the gene regulatory network and pave the way to investigate the underlying mechanisms. Having demonstrated tightly conserved regulation in human CHDs, we believe that some of these lncRNAs play important intrinsic regulatory function. Further experimental studies to characterize their diverse mechanisms may provide a physiological basis for future investigations in pathological maturation and CHDs. At the mechanistic and technical levels, in addition to using RNA interference and modified antisense oligonucleotide approaches, new approaches for targeting lncRNAS are needed to overcome several challenges. For example, large fraction of newly discovered lncRNAs in heart act as regulators of the epigenome and nuclear architecture in cis at their site of production. In particular, the regulatory function of lncRNAs derived from active enhancers act primarily at their endogenous site of production. Therefore, modulation of the nascent transcript is critical. Furthermore, identifying chromatin marks and histone modifications at gene promoters and further dissecting the molecular mechanisms requires employing sophisticated molecular genetics tools, such as chromatin isolation by RNA purification (ChIRP) [45] and capture hybridization analysis of RNA targets (CHART) [46]. Moreover, genome-editing technologies can serve to modify cardiovascular lncRNA expression in vivo. The lncRNA field will certainly benefit from new techniques to generate targeted mutations in the genome, such as Cas9/CRISPR systems. Finally, hiPSCs (human induced pluripotent stem cells) can provide powerful platforms for future studies designed to establish the mechanisms of human cardiac lncRNA and their potential regulators in development and disease, and then to explore their potential applications as putative disease modifiers, diagnostic biomarkers, and therapeutic targets in pathological maturation of neonatal heart and CHDs.

Data sharing Statement
We refer interested researchers to gene expression data sets deposited within the Gene Expression Omnibus repository (www.ncbi.nlm.nih.gov/geo) under Neonatal Heart Maturation SuperSeries GSE85728 (http://www.ncbi. nlm.nih.gov/geo/query/acc. cgi?acc=GSE85728). All unique materials, resources and reagents are available on request by qualified researchers for their own use.