Cardiovascular Disease and Long Noncoding RNAs
2017; Lippincott Williams & Wilkins; Volume: 10; Issue: 4 Linguagem: Inglês
10.1161/circgenetics.117.001556
ISSN1942-325X
Autores Tópico(s)Circular RNAs in diseases
ResumoHomeCirculation: Cardiovascular GeneticsVol. 10, No. 4Cardiovascular Disease and Long Noncoding RNAs Free AccessReview ArticlePDF/EPUBAboutView PDFSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessReview ArticlePDF/EPUBCardiovascular Disease and Long Noncoding RNAsTools for Unraveling the Mystery Lnc-ing RNA and Phenotype Elizabeth J. Hennessy, PhD Elizabeth J. HennessyElizabeth J. Hennessy From the Perelman School of Medicine, University of Pennsylvania, Philadelphia. Originally published2 Aug 2017https://doi.org/10.1161/CIRCGENETICS.117.001556Circulation: Cardiovascular Genetics. 2017;10The last decade has ushered in a surge of genetic information with budget-friendly and more efficient sequencing technologies adding to our understanding of human development and disease. The sequencing of the human genome was a remarkable feat, yet using this information to understand human health and disease has proven to be challenging. The mammalian genome is comprised of a complex infrastructure of defined nucleotide sequences and dynamic epigenetic modifications that result in shifts in gene expression patterns and subsequent developmental and phenotypic outcomes. Genome wide association studies (GWAS) have demonstrated the link between alterations in nucleotide sequences created by mutations, such as single nucleotide polymorphisms (SNPs) and disease. However, it remains unclear how SNPs alter gene expression patterns and phenotypes. One hypothesis links SNP containing regions to mutational phenotypes via changes to epigenetic processes that control how genes are regulated, such as DNA methylation and histone acetylation.SNPs are changes in nucleotide sequences that occur in at least 1% of the population. It is estimated that there are 10 to 30 million SNPs in humans that occur every 100 to 300 bases, and this variation is the major source of heterogeneity among people. A nonsynonymous SNP changes the amino acid sequence of a protein-coding gene. Less than 10% of SNPs are nonsynonymous, whereas 90% occur in nonprotein coding regions of the genome.1 SNPs can be found in regions of deoxyribonuclease I (DNase I) hypersensitivity or promoters affecting transcription factor–binding sites and chromatin state. SNPs can create or delete microRNA-binding sites in 3′ untranslated regions (UTRs) affecting microRNA target mRNA expression.2 SNPs can also be found in regions expressing noncoding RNAs, such as long noncoding RNAs (lncRNAs) leading to alterations in their expression patterns. SNPs can affect alternative splicing and the secondary structure of an RNA transcript leading to altered function (Figure 1). It has been estimated that 7% of SNPs that associate with autoimmune diseases are found in lncRNAs located in intergenic regions, signifying the increasing importance of these noncoding regions.3 LncRNAs represent undiscovered disease-associated loci that could be identified through GWAS analysis.Download figureDownload PowerPointFigure 1. The Effect of SNPs on RNA Secondary Structure. SNPs found in long noncoding genes can alter the splicing pattern of a RNA transcript and the subsequent secondary structure leading to effects on the functional interactions of the lncRNA.The National Institutes of Health sponsored ENCODE (Encyclopedia of DNA Elements) project set out to uncover all of the functional elements of the human genome. It revealed that 85% of the human genome is transcribed into several classes of noncoding RNAs, whereas only 3% is translated into protein.4,5 RNA-sequencing (RNA-seq) is currently the most widespread method for detecting the expression of RNA transcripts and for identifying novel noncoding transcripts.6 The importance of noncoding RNA is evident by the fact that as the complexity of an organism increases, the abundance of noncoding RNA sequences found in its genome also grows illustrating the requirement for more sophisticated gene regulation in evolved eukaryotic species.7 LncRNAs are a class of noncoding RNA that is broadly defined as nonprotein coding transcripts >200 nucleotides. They share some features of mRNAs, including polyadenylation and splicing, so they can be difficult to identify and distinguish from neighboring genes.8,9 They exhibit specific and regulated patterns of expression in cells and tissues, and this can help when identifying them and trying to determine their function.10–16 They have no strict sequence conservation restraints like protein-coding genes, so lncRNA sequences are often poorly conserved between species.LncRNAs do not share a common mode of action, but they can be categorized into 4 general methods used to execute their functions, as (1) signals, (2) decoys, (3) guides, or (4) scaffolds where lncRNAs interact with DNA, RNA, and proteins (Figure 2). These interactions can result in cellular epigenetic modifications, such as changes to DNA methylation status,17 modifications to histones, and the remodeling of chromatin, leading to changes in the expression of target genes. Although several thousand lncRNAs have been identified in the genome,9,18,19 the function of only a limited number has, thus, far been described. Functions for lncRNAs have been described in various cellular processes, such as development and disease, including X-chromosome inactivation (Xist/Tsix), cancer metastasis (HOTAIR), nuclear import (Nron), type 2 diabetes mellitus (HI-LNC25 and KCNQ1OT1), and inflammation (LincRNA-COX-2 and LETHE).20–32 Interestingly, 2 lncRNAs have been identified that were once thought to be noncoding for proteins but were re-examined for open reading frames and are now recognized to form micropeptides that play essential roles in muscle function.33,34 It is becoming more apparent that the criteria for identifying lncRNAs and their functional implications are constantly evolving; so at the present time, there is no fixed set of rules.Download figureDownload PowerPointFigure 2. Four General Mechanisms of Action for Long Noncoding RNAs. LncRNAs can act as signaling molecules bringing transcription factors to promoter regions; decoys sequestering away TFs, RNA-binding proteins or miRNAs; guides for chromatin modifying enzymes or scaffolds for bringing together complexes of proteins.Recent studies have indicated that noncoding RNAs play important roles in the regulation of genes involved in the development and progression of cardiovascular disease (CVD) with several being classified as epi-lncRNAs or lncRNAs involved in epigenetic regulation through their interactions with epigenetic modifiers.35 FENDRR (Foxf1 adjacent noncoding developmental regulatory RNA) is an essential regulator of heart development and is required for the proper development of the mouse, and this was shown using 2 different knockout models, 1 disrupting FENDRR transcription through the insertion of transcription termination signals in the first exon and the other inserting a lacZ reporter cassette in place of the FENDRR gene.15,16,36 Both mouse models demonstrated the lethality of FENDRR deficiency but that it occurs at different stages of development: 1 prenatally16 and the other perinatally,36 and the authors attribute this to the differences in targeting strategies. FENDRR modifies the chromatin signature of genes involved in the formation and differentiation of the lateral mesoderm lineage. It interacts with the polycomb repressor complex 2 (PRC2) bringing it to target gene promoters (including its neighbor gene Foxf1) and increasing H3K27me3 (Histone3 lysine27 trimethylation), a repressive mark at these sites suppressing target gene transcription. Like FENDRR, Braveheart is an epi-lncRNA that is also required for cardiovascular lineage commitment by interacting with a component of the PRC2 complex, SUZ12, to control gene regulatory networks, including key transcription factors (MesP1, Gata4, Hand2, Nkx2.5, and Tbx5).37 In Braveheart deficient cells, SUZ12 and the repressive mark H3K27me3 were enriched at the promoters of these transcription factors decreasing their activity and the ability of the cells to differentiate into cardiomyocytes suggesting that Braveheart sequesters away the SUZ12 component of PRC2 from these transcription factor genes. However, it remains unknown whether Braveheart plays a direct role in the epigenetic regulation of these transcription factors. A structural study of Braveheart uncovered a key motif in the lncRNA that interacts with a nucleic acid–binding protein and affects cardiomyocyte differentiation.38 Currently, there is no knockout model for Braveheart function and no human homologue, so translational studies are limited. Chaer (cardiac-hypertrophy-associated epigenetic regulator) is another epi-lncRNA that is heart specific and acts as an epigenetic checkpoint. Like FENDRR and Braveheart, it interacts with the repressor protein PRC2 and prevents it from targeting the promoters of genes involved in cardiac hypertrophy and repressing them via H3K27 trimethylation at the sites.39 Despite displaying required roles in development, cardiac lineage commitment and hypertrophy through epigenetic regulation, the precise mechanisms for these epi-lncRNAs action remains unclear.SENCR (smooth muscle and endothelial cell–enriched migration/differentiation-associated long noncoding RNA) is a lncRNA that was identified in a study aimed at distinguishing the lncRNA profile of vascular cells, including smooth muscle cells and endothelial cells. Its expression affects smooth muscle cell migration. Silencing SENCR led to increased expression of promigratory and contractility genes including myocardin, a key transcriptional switch for smooth muscle cell contractile gene expression, and 2 migratory genes MDK and PTN.40 MALAT1 (Metastasis-associated lung adenocarcinoma transcript 1) is expressed at high levels in endothelial cells. It regulates migration and vascular sprouting, and its expression is increased in response to hypoxia. Silencing of MALAT1 in vitro promotes a migratory endothelial cell phenotype, and pharmacological inhibition of MALAT1 in vivo reduces vascular growth.41 Despite showing a vascular phenotype in vitro and in vivo, the mechanism underlying these changes is unknown. MALAT1 has been shown to interact with a protein in the polycomb complex CBX4 to regulate histone modifications and control cell proliferation and lung metastasis, but this epigenetic function for MALAT1 has not been shown in endothelial cells. In contrast to these studies, 2 different MALAT1 knockout mouse models have demonstrated that this lncRNA is dispensable for functions that could be linked to the in vitro phenotypes, including pressure overload–induced heart failure in mice, mouse pre and postnatal development, and global gene expression.42,43 However, in a MALAT1 conditional knockout mouse model and in mice treated with a MALAT1 antisense inhibitor, there was a decrease in lung tumor metastasis, and the expression of cis-genes was affected. These conflicting findings in the in vivo modulation of MALAT1 illustrate that MALAT1 like other lncRNAs may play redundant roles in the whole organism for some functions but are still relevant when studying distinct cellular processes. The varied observations between cellular and whole organism studies illustrate the complexity of lncRNA research. We do not know enough about their mechanisms to disregard them. Each of the lncRNA studies described demonstrates their cell type specificity and the potential for targeting specific cardiovascular phenotypic processes through the modulation of their expression. It is evident that the identification of lncRNAs and their effect on the cellular epigenetic signature has created new possibilities for researchers to develop novel therapeutics for CVD.SNPs in Noncoding Genes and Their Link to CVDSeveral lncRNAs that contain SNPs implicated in the development and severity of CVD have been identified through GWAS analysis. The lncRNA MIAT (myocardial infarction associated transcript) was identified in a 2000-person case-control association study of a myocardial infarction (MI) susceptibility locus located on chromosome 22.44 A follow-up study confirmed this finding and that altered expression of MIAT resulting from 6 independent SNPs in the MIAT gene at location chromosome 22q12.1 conferred genetic susceptibility to MI.45 One of these SNPs located in exon 5 increased the expression of MIAT and altered its ability to bind to an as yet uncharacterized nuclear protein. MIAT has been implicated in microvascular dysfunction with increased expression in diabetic retinas and in response to high glucose linking it to diabetic pathology.46 Another study showed that MIAT expression was significantly decreased in peripheral blood cells and platelets of patients with acute MI, whereas showing a positive association with lymphocytes and a negative association with neutrophils and platelets.47 MIAT has also been described as a competing endogenous RNA (ceRNA) targeting miR-150-5p and affecting levels of miR-150-5p target mRNA vascular endothelial growth factor (VEGF).46 Lastly, in a study of 414 patients with acute MI, there was an association between levels of several lncRNAs, including MIAT and ANRIL, with inflammatory markers, such as matrix metalloproteinase 9 (MMP9), illustrating their potential role in the regulation of the inflammatory response.48ANRIL (antisense noncoding RNA in the INK4 locus) was identified through GWAS analysis that linked its locus on human chromosome 9p21 to coronary artery disease (CAD) and myocardial infarction susceptibility.22,23,48–50 ANRIL is expressed in endothelial, smooth muscle, and inflammatory cells, and its expression is associated with risk for atherosclerosis, peripheral artery disease, and other vascular diseases.51 A primate specific ALU element–containing motif was identified in ANRIL that acts to regulate genes involved in proliferation, cell adhesion, and apoptosis.50 SNPs in the ANRIL gene result in the alternative splicing of the transcript into many isoforms, including a circular form (circANRIL), and each variant correlates with CAD to a different degree. CircANRIL regulates the maturation of precursor ribosomal RNA and ribosome biogenesis leading to reduced proliferation and protection against atherosclerosis.52 Carriers of the ANRIL risk alleles exhibit increased whole blood RNA expression levels of 2 of the shortest ANRIL variants and decreased expression of the longest variant demonstrating the differential impact of the different isoforms of ANRIL in response to SNPs in the gene. However, despite these correlation studies, the precise biological function of ANRIL remains unknown.Linc-VWF is a lncRNA that is highly expressed in endothelial cells and is induced by lipopolysaccharide. Linc-VWF is located 105 kb from the VWF gene—an endothelial and platelet-derived circulating plasma glycoprotein that plays a central role in hemostasis and thrombosis. A study by Liu et al53 showed that linc-VWF contains an SNP (rs1558324) associated with mean platelet volume—a predictor of cardiovascular disease; however, there is no linkage disequilibrium between the linc-VWF SNP and SNPs in the VWF gene that have been associated with circulating VWF levels. Additional work needs to be done to elucidate the mode of action for linc-VWF after stimulation with LPS, including potential protein-binding partners that could explain the association of the SNP to platelet volume.SNPs have also been identified in the lncRNA H19 conferring either susceptibility or protection from CVD (rs217727 and rs2067051). The expression of H19 is induced during embryogenesis and downregulated after birth except in the heart. It is induced in response to homocysteine and is increased in the aortae of mice with hyperhomocysteinemia—a risk factor for CAD. H19 has been linked to different types of cancers, and this is thought to occur via the interaction between H19 and the microRNA let-7. H19 binds to and sequesters let-7 preventing it from inhibiting the expression of its target genes. Impaired let-7 has also been implicated in CVD, so it is thought that H19 could be a regulator of let-7 expression, and, therefore, CVD.54 The few examples presented here (Summarized in Table 1) describe the potential for lncRNAs to affect cardiovascular phenotypes via SNPs found within their nucleotide sequences. How these noncoding RNA-associated SNPs interact with other factors, such as via their secondary structures, is currently being explored and is proving to be essential to understanding their function.Table 1. List of Cardiovascular-Associated Long Noncoding RNAsLncRNASpeciesCell/Tissue TypeFunctionIn Vivo PhenotypeReferencesFENDRRMouse/HumanEmbryonic stem cells Caudal end of the lateral plate mesoderm of midgestation embryosModifies chromatin signature of genes involved in the formation and differentiation of lateral mesoderm lineageEmbryonic lethal15,16, 35, 36BraveheartMouseEmbryonic stem cellsCardiomyocytesRequired for cardiovascular lineage commitmentNone37,38ChaerMouse/HumanHeartEpicardium, where progenitor cells for endothelial cells and fibroblasts resideRequired in development, cardiac lineage commitment, and hypertrophyRegulates hypertrophy39SENCRHumanSmooth muscle cellsEndothelial cellsAffects smooth muscle cell migrationNone40MALAT1Mouse/HumanEndothelial cellsRegulates migration and vascular sprouting, and its expression is increased in response to hypoxiaPharmacological inhibition in vivo reduces vascular growthIn vivo ko showed it is dispensable for pressure overload–induced heart failureAntisense inhibitor in vivo showed a decrease in lung tumor metastasis, and expression of cis-genes were affected41–43MIATMouse/ HumanPositive association with lymphocytes Negative association with neutrophils and plateletsSNPs in exon 5 increased the expression of MIAT and altered its ability to bind to an as yet uncharacterized nuclear proteinImplicated in microvascular dysfunctionDecreased in peripheral blood cells and platelets of patients with acute MIAssociated with MMP944–48ANRILHumanEndothelial cellsSmooth muscle cellsMacrophagesUnknownAssociated with risk for CAD, MI, atherosclerosis, and peripheral artery disease22, 23, 48–52Linc-VWFHumanEndothelial cellsLPS inducibleSNP associated with mean platelet volume53H19HumanHeartAortaInduced in response to homocysteineIncreased in aorta of mice with hyperhomocysteinemia54CVD has several lncRNAs implicated in its pathology. LncRNAs are listed with the cell or tissue type where it is primarily expressed, known functions and in vivo evidence.The Potential for SNPs to Alter RNA Secondary and Tertiary StructuresThe genes encoding lncRNAs are thought to evolve rapidly, so their sequences are often poorly conserved between species. Because of the rapid evolution of lncRNAs, SNPs are likely to be created. Unlike protein coding genes, lncRNAs do not need to maintain sequence conservation to maintain their functionality because it is thought that the secondary structure of the RNA molecule is important for function, and this can be conserved. One of the first lncRNAs to be described, Xist regulates X-chromosome inactivation, and it has undergone rapid sequence evolution, whereas preserving its function. Despite moderate sequence conservation, Xist displays conserved RNA secondary structure between various species.55 Another lncRNA, MEG3 was used as an example to demonstrate the importance of secondary structure over nucleotide conservation. One hundred and fifty-seven nucleotides from the wild-type MEG3 sequence that formed a stem-loop structure were replaced with a different nucleotide sequence that could also form a similar stem loop forming a hybrid transcript. According to RNAfold, the artificial hybrid RNA molecule displayed a similar secondary folding structure to the wild-type MEG3 and had an equivalent effect on p53 activation demonstrating that for some lncRNAs, it is not the sequence that is important for function but the resulting secondary structure that forms.56Single base-pair changes in the genetic code can alter sequence elements that are essential for correct splicing or translation of an mRNA, as well as change the structure and folding of an mRNA molecule and, therefore, its function (Figure 1).57 Computational and experimental methods can be used to define the secondary structure for a given RNA. Online algorithms include Vienna RNAFold,58 RNAStructure,59 Sfold,60 and RNAMutants.61 These algorithms use thermodynamics to calculate the minimum free energy presented by the RNA structure. Negative values signify that less energy is required for base pairs to interact, so it is more likely to be a valid and stable predicted structure. Stem-loop structures are thought to be the functional elements of the transcript that will interact with DNA, RNA, or proteins; however, current bioinformatics tools are not able to accurately detect the short sequences that may form important stem-loop structures. The database lncRNASNP provides information about SNPs encoded in lncRNA genes, such as the potential effects of SNPs on structure, lncRNA:miRNA-binding relationships, and their possible functions.62 Databases like lncRNASNP are adding details to the mystery between SNPs encoded in lncRNA genes and structure/function relationships. However, it is unknown how in vitro examples of RNA structures compare with their in vivo counterparts. There could be alternatively folded secondary structures depending on the scenario, and more studies are needed to conclusively determine the effect of SNPs on disease pathology.Methods are rapidly being sought to experimentally validate in silico-predicted secondary structures and to identify key motifs in RNA molecules that will help predict interactions between RNA, DNA, and protein.38 Earlier studies have probed genome-wide RNA secondary structures using dimethyl sulfate sequencing (DMS-seq).63 Specific bases in the RNA molecule are methylated with DMS preventing natural hydrogen bonds from forming between modified bases. The resulting altered RNA is then sequenced, and the interruptions in the signal indicate modifications to the structure like single-stranded stem-loops. Advancing from the DMS protocol, selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) can predict RNA secondary structure at single-nucleotide resolution and uses chemical probing agents like N-methylisatoic anhydride (NMIA) or 1-methyl-7-nitroisatoic anhydride (1M7) to target hydroxyl groups and acylate single-stranded or flexible regions of RNA (Figure 3A).64,65 The sites of chemical modification are detected by reverse transcription. The reverse transcriptase enzyme pauses at RNA nucleotides that are modified by 1M7 indicating single strandedness. Nucleotides that are constrained by base-pairing show less product formation than nucleotides that are unpaired. The resulting cDNA library maps ribonucleotides that are single stranded in the context of the folded RNA. Products of this reaction are then fractionated by capillary electrophoresis (CE) generating electropherograms that are converted into nucleotide reactivity tables that are then converted into pseudoenergy constraints by the prediction algorithms like RNAStructure. The 2D RNA structures obtained by combining SHAPE with computational RNA secondary structure prediction programs are more accurate than structures obtained using either method alone.Download figureDownload PowerPointFigure 3. Techniques for Determining the Functions of Long Noncoding RNAs. A) SHAPE uses reagents to detect nucleotides that are constrained by base-pairing, they will show less product formation (see nucleotides in black) when fractionated by capillary electrophoresis than nucleotides that are unpaired. (B) Chromosome capture experiments allow for the identification of interacting loci in the genome, a typical scenario for lncRNAs. DNA is crosslinked, cut into fragments with restriction enzymes and then randomly ligated back together. 3C, 4C, 5C and Hi-C differ only in the methods used to identify interacting loci. (C) Various pull-down techniques can be used to detect interactions between a single target lncRNA or a protein of interest.A key motif in the lncRNA Braveheart that is required for the development of cardiovascular cells was identified using SHAPE.38 This study set out to investigate the molecular mechanism of Braveheart action by determining the secondary structure of in vitro transcribed full-length Braveheart using SHAPE and DMS probing. The Braveheart transcript is organized into a highly modular structure, including an asymmetrical G-rich internal loop (AGIL) at the 5′ end. The authors then used CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats) technology to delete this AGIL motif and observed an inability of embryonic stem cells to differentiate into cardiomyocytes. The AGIL motif interacts with key factors expressed in the heart, such as the zinc-finger protein CNBP/ZNF9, which is known to bind to single-stranded G-rich sequences and repress cardiomyocyte differentiation. Through its AGIL motif, Braveheart antagonizes CNBP to promote differentiation. The authors have yet to identify a human homolog to the mouse Braveheart transcript, but the structure of the mouse Braveheart lncRNA can be used to analyze human lncRNA molecules and identify similar structures/motifs that may have similar functions. Motifs found in RNA transcripts using secondary structure analysis may contain key regions of interaction for SNPs, and they can be used as fingerprints to make a catalog of key motifs.Currently, there are no examples of cardiovascular disease–associated SNPs in lncRNAs that affect the secondary structure of the lncRNA, but an example of a polymorphism associated with celiac disease was found in the lncRNA Lnc13 that affects its secondary structure.66 Lnc13 is downregulated in small intestine biopsies from celiac patients, and LPS downregulates Lnc13 via degradation by the mRNA decapping enzyme Dcp2. In healthy people, Lnc13 acts as a brake to keep a subset of inflammatory genes downregulated through interaction with the nuclear proteins heterogeneous nuclear ribonucleoprotein D (hnRNPD) and histone deacetylase 1 (HDAC1). However, in patients with the disease-associated SNP, Lnc13 binds hnRNPD less efficiently than its wild-type counterpart leading to increased expression of the inflammatory genes. The predicted secondary structures for wild-type and disease-associated Lnc13 were significantly different. In vitro transcribed RNA for wild-type and disease-associated Lnc13 showed dramatically different mobilities on a native agarose gel signifying that the structures for these RNA transcripts indeed differ, and this may play a role in their functional differences.It is becoming evident that in addition to secondary structures, tertiary structures of RNA molecules could be key to understanding their functional consequences. A recent study described both the secondary and tertiary structures for the well-characterized lncRNA Xist and the lncRNA RepA whose sequence is identical to the 5′ region of Xist. RepA is thought to function in the initiation and spreading of X-chromosome inactivation by Xist.67 This study was able to show that 3 dimensional structures were able to form in the absence of protein partners signifying that Xist and RepA do not require the presence of their protein partners to form their structures. The laboratory of Rhiju Das is making advances toward understanding the relationship between secondary and tertiary RNA structures of noncoding RNAs by studying benchmarking RNAs like ribozymes, riboswitches, and ribosomal RNA domains in cells and viruses with high-resolution computational approaches and multidimensional chemical mapping to uncover 3 dimensional structures.68,69 The low abundance of many lncRNAs and the complexity of proteins binding to RNAs can make in vivo interpretation of in vitro signals more complicated. An attempt to examine RNA structures in vivo was made with in vivo click selective 2′ hydroxyl acylation and profiling experiment (icSHAPE-seq) in living cells. It revealed active unfolding of mRNA structures suggesting that RNA structures are contributing to global RNA processing.70 Studying the secondary and tertiary structures of lncRNAs is contributing to a better understanding of how noncoding transcripts and alterations in sequences because of SNPs affect disease progression. These studies will aid in the creation of guidelines for streamlining lncRNA studies and ultimately the development of new therapies targeting disease-causing SNPs.Noncoding RNA Interactions and Their Effect on the Epigenetic Signature of the CellIt is well established that the epigenetic landscape of the cell is responsible for alterations in the accessibility to chromatin by molecules like chromatin-modifying enzymes, transcription factors, and more recently, lncRNAs resulting in changes in gene expression, cellular differentiation, development, and disease pathology. Specific combinations of modifications constitute a unique epigenetic signature, and variations in the genomic sequence caused by SNPs can affect this signature. A prominent role for lncRNAs has recently been established in epigenetic regulation through chromatin remodeling via the targeting of specific loci. Many lncRNAs have been shown to complex with chromatin-modifying enzymes and guide them to specific sites in the genome altering histone acetylation and affecting the methylation status of DNA through interactions with histone lysine methyltransferases.17 Acetylation is generally thought to open up chromatin allowing for proteins to access it, whereas an increase in methylation at a gene's promoter can open or close
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