Review Volume 14, Issue 19 pp 8110—8136
RNA modifications in aging-associated cardiovascular diseases
- 1 Fangshan Hospital Beijing University of Chinese Medicine, Beijing 102400, China
- 2 Key Laboratory of Chinese Internal Medicine of the Ministry of Education, Dongzhimen Hospital Affiliated with Beijing University of Chinese Medicine, Beijing 100700, China
- 3 Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- 4 College of Basic Medical and Sciences, Heilongjiang University of Chinese Medicine, Harbin 150040, Heilongjiang, China
- 5 Guang’an Men Hospital, Chinese Academy of Chinese Medical Sciences, Beijing 100053, China
- 6 Center for Transplantation Science, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
Received: May 7, 2022 Accepted: September 17, 2022 Published: September 29, 2022
https://doi.org/10.18632/aging.204311How to Cite
Copyright: © 2022 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide that bears an enormous healthcare burden and aging is a major contributing factor to CVDs. Functional gene expression network during aging is regulated by mRNAs transcriptionally and by non-coding RNAs epi-transcriptionally. RNA modifications alter the stability and function of both mRNAs and non-coding RNAs and are involved in differentiation, development, and diseases. Here we review major chemical RNA modifications on mRNAs and non-coding RNAs, including N6-adenosine methylation, N1-adenosine methylation, 5-methylcytidine, pseudouridylation, 2′ -O-ribose-methylation, and N7-methylguanosine, in the aging process with an emphasis on cardiovascular aging. We also summarize the currently available methods to detect RNA modifications and the bioinformatic tools to study RNA modifications. More importantly, we discussed the specific implication of the RNA modifications on mRNAs and non-coding RNAs in the pathogenesis of aging-associated CVDs, including atherosclerosis, hypertension, coronary heart diseases, congestive heart failure, atrial fibrillation, peripheral artery disease, venous insufficiency, and stroke.
Introduction
The incidence of cardiovascular disease (CVD) is increasing rapidly around the world, taking nearly 17.9 million lives every year, and this number will increase to 23.6 million by 2030 [1–3]. This medical burden is expected to increase in developing and developed countries because of the aging population and changing risks factors posed by the environment. During aging, heart and blood vessels gradually exhibit homeostatic imbalances leading to vascular sclerosis and fibrosis, increased left ventricular (LV) wall thickness, decreased tissue fitness, and reduced stress tolerance [4, 5]. These changes contribute to different types of CVDs, including atherosclerosis, hypertension, peripheral artery disease, venous insufficiency, stroke, coronary artery diseases (CAD), atrial fibrillation (AF), congestive heart failure (CHF), and cardiac hypertrophy. Better understanding of the underlying signaling pathways that are involved in these diseases may lead to the development of novel targeted therapies against CVDs. Recent advances in next-generation sequencing, particularly RNA sequencing (RNA-Seq), have enabled the study of new classes of non-coding RNAs (ncRNAs), such as long ncRNA (lncRNA), miRNA, circular RNAs (circRNAs), apart from the traditionally well-known mRNA, rRNA, and tRNAs. Among them, RNA modifications have emerged as one of the key contributors in the pathogenesis of aging-associated CVDs.
More than a hundred RNA modifications have been identified that could alter the chemical and topological properties of the ribonucleotide molecules to perform specific biological functions during their post-transcriptional regulation. Initially, RNA modifications were only studied in tRNA, rRNA, and small nuclear RNAs (snRNA). Eventually, through multiple advanced tools together with subsequent next-generation sequencing [6, 7], even low abundant modifications are now increasingly discovered in most RNAs including mRNA [8], miRNA [9], circRNA [10], lncRNA [11], snRNA, and snoRNA [12]. RNA modifications can directly affect RNA chemistry, including secondary structure, base pairing, and the ability to interact with proteins. Of note, these changes modulate gene expression by regulating RNA processing, localization, translation, and decay [13]. In CVDs, extensive RNA modifications serve as novel mechanisms that underlie the hypertension, CAD, and CHF. In this review, we will summarize the molecular evidence towards the known regulation and interaction of several kinds of RNA modifications in CVDs.
Different RNA species that undergo post-transcriptional modification
RNA is one of the key molecules, that can perform most types of functions in a cell, and dynamic modifications of RNA have been identified in the transcriptome which are largely conserved across species evolutionarily [14]. Therefore, understanding its structure and functional relationship is not only critical for a deeper understanding of basic molecular biology but also has important implications for human health [15]. Most RNA modifications have been primarily identified in mRNAs (Figure 1). In the following sections, we delve deeply into how these different aging-related mRNA modifications impact CVDs. Although there are nearly 170 types of RNA modification, we will only be discussing the topmost frequently observed modifications that influence aging-associated cardiovascular health in this review. In addition to the classical mRNA, the progress of advanced experimental techniques and computational methods have led to the discovery of various ncRNAs species of different lengths and biological roles that undergo RNA modifications as well. We will also briefly discuss those that are critically involved in aging-associated CVDs.
Figure 1. Dynamic RNA modifications. Multiple internal modifications within mRNAs, and specific groups of modifications are highlighted, along with modification deposition, removal, and base pairing of modification pairs for downstream recognition. m6A, N6-adenosine methylation; m5C, 5-methylcytidin; ac4C, N4-acetylcytidine; Ψ, pseudouridine; A-to-I, adenosine-to-inosine; m7G, N7-methylguanosine; m1A, N1-adenosine methylation.
RNAs other than protein coding mRNAs are literally categorized as ncRNAs. For the ease of understanding, ncRNAs are further classified into two categories based on their function. The first class is “infrastructural RNAs” that involve in basic housekeeping functions, such as protein-coding related RNAs including RNAs designated for the protein translation, namely rRNA and tRNA, as well as RNAs responsible for their maturation and even splicing, including snRNAs and snoRNAs [16]. SnRNAs mainly play a role in pre-mRNA processing in the nucleus and snoRNAs have an impressive diversity of functions including rRNA and snRNA modifications [17].
The second class of ncRNAs includes regulatory RNAs that include all other cellular ncRNAs not included as infrastructural RNAs. For instance, short ncRNAs include miRNAs, which can alter gene expression by degrading mRNA molecules after transcription, while the piwi-interacting RNAs (piRNAs) silence retrotransposons in the germ cells [18]. A lesser known, enhancer RNA (eRNA) has been reported to be a ncRNA molecule transcribed from the enhancer regions that is involved in transcription regulation [19]. They are 100-9000 nucleotides long synthesized from regions enriched with H3K4me, RNA Polymerase II and co-activators such as p300. They are believed to be transcription activators and since they have only recently been identified, their mechanism of action is still unclear. Promoter Associated RNA (PAR) are 16-200 nucleotides in length and are usually observed to be expressed around the transcription start site or near the promoter, preferentially near GC rich regions of highly expressed genes. They are usually poorly expressed with short half-lives and are observed to be involved in transcriptional regulation. Another vast and important type of ncRNAs are the lncRNAs. lncRNAs are defined as being over 200 nucleotides in length, some even exhibiting mRNA-like characteristics, such as being 5’-capped, spliced and undergoing polyadenylation. They are transcribed in tissue-specific, disease-specific, and developmental regulatory ways, mediating epigenetic changes by enrolling chromatin remodeling complexes to specific genomic sites along many of their other functions. CircRNAs are usually 4-6 exon long evolutionarily conserved closed continuous RNA loops without any poly A tails, principally acting as miRNA sponges. More recently, they have increasingly been observed to have important physiological roles such as in cancer and CVDs.
Detection of dynamic RNA modifications
While techniques such as chromatography or mass spectrometry could recognize many extensive modifications, more rare RNA modifications require advanced sequencing techniques to identify the nucleosides that have undergone modifications and differentiate these from unmodified ones [20, 21]. Identification involves several challenges. For example, in the process of reverse transcription (RT), the modifications may interfere with the production of reverse transcribed copies of cDNA. Recent studies have revealed that the N1-methyladenosine (m1A) modifications in the template RNA has an influence on the cDNA synthesis and their application in the test of their respective patterns in the machine learning-based high-throughput sequencing data [22]. In this section, we will introduce some of the techniques that are commonly used to identify most RNA modifications [23] (Table 1).
Table 1. Techniques for detecting RNA modifications.
Method | Application | Main pathway of action | Detection sensitivity | Reference | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Mass spectrometry | various modifications | the fragment mode | Low (5 μg) | 24 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
LC-MS | various modifications | complementary DNA oligonucleotides | High (0.5 μg) | 27, 28 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Antibody-based enrichment techniques | m6A and m7G | Antibodies recognizing m6A or m7G modification | High (1 μg) | 31, 32 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Modifications in high throughput sequencing | Ψ and I | RT arrest or misincorporation | High (10 ng-1 μg) | 34 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Bisulfite treatment | m5C | bisulfite based on RNA | High (5 ng - 1 μg) | 37, 38 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MeRIP | 2'-O-Me | the 5ʹ and 3ʹ linker connection protocol | High (1 μg -2 μg) | 39 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SCARLET | m6A and Ψ | RNase H | High (1 μg) | 40, 41 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
RiboMethSeq | 2'-O-Me | RT under low concentration dNTP | High (1 μg) | 43 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
LC-MS, Liquid chromatography-mass spectrometry; RT, reverse transcription; MeRIP, Methylated RNA Immunoprecipitation; RiboMethSeq, ribose methylation sequencing. |
Mass spectrometry
It is the most direct method for the high-throughput and sequence-specific analysis of the transcriptome stems from an adaptive mean widely used in proteomics [24]. The elution fragments are analyzed by mass spectrometry and the modification can be detected from the fragment mode by comparing the calculated quality with that of the unmodified fragment [25]. This approach has been used to RNAs. Although nucleases (RNase T1 and MC1) permit the preparation of fragment libraries, protocols, tools, and databases common in proteomics are largely lacking in the RNA domain.
Modifications in liquid chromatography-mass spectrometry (LC-MS)
In this technique, nuclease protection was achieved by forming double-stranded bodies with complementary DNA oligonucleotides, such that the unhybridized RNA was then degraded by the nucleases and the remaining double-stranded bodies were analyzed by the LC-MS for nucleoside analysis [26, 27]. Other methods that had been used to excise certain fragments from larger RNAs including the site-specific cleavages applied to the RNase H and short DNA oligonucleotides or enzymes [28]. The retention behavior utilized in the LC-MS method reflected a biophysical property that also formed the basis of thin layer chromatography (TLC) that is applied to identify and quantify in the RNA modifications.
Antibody-based enrichment techniques
These are very useful tools known for their very high affinity and the potential to specifically recognize molecular structures [29]. Nucleic acid applications include the analysis of DNA modifications and the generation of specific antibodies against the modified nucleotides in the RNA with a long history [30, 31]. Meanwhile, more antibodies to m6A, m1A, m5C and hm5C are currently available. Because antibody binding provides only the non-covalent complexes with modified RNA, the rigor and enrichment of the washing step is limited. Significant improvement was achieved by an ultraviolet (UV)-induced cross-linking step after the formation of a non-covalent complex between the modified RNA and the antibody [31, 32]. In addition, even single-nucleotide resolution was achieved using this technique by analyzing the unique signal generated due to the covalent cross-linking of a specific antibody to a particular RNA modification that in turn leaves a specific RT signature in the corresponding sequencing spectrum [33].
Modifications in high throughput sequencing
Another dimension of information can be accessed using high-throughput sequencing data after processing RNA templates with reagents that can react specifically with the modifications to alter their RT characteristics in the terms of RT stasis or misincorporation. For example, the inosine specific cyanoethylation (ICE-SEQ) of acrylonitrile produces a strong RT termination that can distinguish true A to I conversion sites from simple sequencing errors [34]. Currently, the well-known reaction specificity of the ψ residue of N-cyclohexyl-N'-(2-morpholine ethyl) carbodiimide methyl-p-toluene sulfonic acid (CMCT) has been applied in multiple independent pseudouridine (PU) mapping in the transcriptomes of yeast and human. [35, 36].
Bisulfite treatment
Recent adaptation for the detection of m5C in bisulfite based on RNA. In the process of this technology, the technology was based on the mature detection of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in the DNA, and the modification of cytosine to m5C or 5hmC can protect these sites from the impacts of bisulfite treatment [37, 38].
MeRIP
In the MeRIP protocol or ribose methylation sequencing (RiboMethSeq) method, the precise definition of the fragment is located in the 5ʹ and 3ʹ linker connection protocol [39]. The ribose 2ʹ-O-methylation in the yeast rRNA was obtained by two published RiboMethSeq methods and compared with data acquired by direct rRNA performed by the mass spectrometry.
SCARLET
The latest and most complex development is the SCARLET variation. In the SCARLET method, the target RNA was first cleaved with RNase H at the desired site and the cleavage was guided by the chimeric oligonucleotides containing DNA and 2ʹ -O-Me-RNA [40, 41]. In several applications, it has been applied to verify the high-throughput data for the m6A and ψ residues in the mRNA and lncRNA.
RiboMethSeq
In some cases, RT primer extension can also be useful as a verification method for high-throughput mapping candidates of the RT arrest signals [42]. One example is the modification after alkaline hydrolysis according to the RiboMethSeq method, which is verified by RT under low concentration dNTP [43]. Invalid cDNA produced at the 2ʹ -o-methylation site can be analyzed directly by the polyacrylamide gel electrophoresis (PAGE) or semi-quantitative PCR or qPCR analysis.
Bioinformatic tools and resources in epitranscriptomics
Several epitranscriptome-wide landscapes of RNA modifications have been performed using high-throughput sequencing and these have led to the development of extensive databases for such modifications. They are important tools in furthering this field and have been discussed as shown below:
Databases for RNA modifications
The following are some common RNA modification databases: MODOMICS-RNA modification pathway database [44], RNA modification database (RNAMDB) [45], MeT-DB-mammalian cell transcriptome methylation database [46], and a database devoted to RNA modification in the normal and disease, such as the RNA Modification Base (RMBase) [47].
MODOMICS
The MODOMICS database is a reference database for RNA modification because it provides the most complete information on the chemical structure of the modified ribosides, reaction abstracts, functional characteristic enzymes involved in the modification, and the biosynthetic pathways of RNA modifications [44].
RNAMDB
As a reference for updating the RNA modification results, the RNAMDB portal provides many useful tools for the mass spectrometry identification of natural or modified RNAs. Beginning with RNA sequences, molecular weight, electrospray series, CID fragment, internal fragment, base loss, and fragment digestion can be calculated [45].
MeT-DB
The MeT-DB is a synthetical database focused on the m6A mammalian methyl transcriptome. It includes approximately 300,000 m6A methylation sites, which have been detected in the samples from humans, mice, and cells under various experimental conditions [46]. Data were analyzed by the methylated RNA immunoprecipitation sequencing (MERIP-SEQ) and detected by the exomePeak and MACS2 algorithms [48, 49].
RMBase
The RMBase is also a comprehensive database. It integrates epigenome sequencing data to explore post-transcriptional modification of RNAs and their relationships with the miRNAs, the disease-associated the RNA-binding proteins (RBPs) and single nucleotide polymorphisms (SNPs) [50]. Meanwhile, RMBase has provided various interfaces and graphical visualizations to facilitate the analysis of a large number of modification sites.
Bioinformatic tools to predict RNA modifications
The computer methods development based on the support vector machines, which can accurately predict post-transcriptional modification sites from sequence information, is very helpful for the scientific community to further understand epigenetic modification [51, 52]. As a good complement to experimental innovations, many computational methods have been put forward in recent years to forecast the RNA modification sites. Some of the currently available online calculation tools for predicting RNA modification sites, are HAMR, PAI, iRNA-AI, RAMPred, iRNA-3typeA, iRNA-PseColl, iRNAm5C-PseDNC, iRNA-Methyl, m6Apred, MethyRNA, SRAMP, RAM-ESVM, PPUS, iRNA-PseU, tRNAMOD [52–67].
Conclusions
Dynamic RNA modification is quite abundant in most RNA species such as mRNA, rRNA, and tRNA and have been proved to be critical in cellular functions. This review attempted to consolidate different aspects of RNA modifications that are crucial in regulating aging-associated CVDs. We first briefly summarized the different types of RNA modifications commonly abundant in cells as well the different ncRNA types. We then enumerated the different methods of identifying the RNA modifications. As sequencing techniques were one of the most superior methods of identifying RNA modifications, we also summarize the different bioinformatic tools and databases that help in their study. We then summarized the role of different modifications in various aging-driven CVDs. These observations have augmented our current understanding of the effect of epigenetics on cardiovascular aging and disease that has tremendously increased during the last few years. Therefore, epigenetic modifications like chromatin remodeling, DNA occupation, and changes in ncRNA expression, which are driven by modifications in RNA bases, contribute to the progression of cardiovascular aging and disease. However, one of the major challenges in the field is the difficulties in detecting these modifications by sequencing methods. Despite improvements in the field, there is still an urgent unmet need in developing advanced tools/techniques to detect and study these RNA modifications, especially with respect to precise profiling of these modifications. Unfortunately, a non-uniform detection of these modifications also poses a disadvantage of not accurately representing the profile of RNA modifications. It is certain that more work needs to be done to understand the reason behind such dynamic modifications and pathogenesis, ultimately moving further towards pattern recognition in aging-driven diseases. There is no doubt that unraveling such crosstalk between RNA modifications and other DNA or RNA modification methods, will further deepen our understanding of these mechanisms and potential therapeutic strategies for CVDs. In the future, further research enhancing the understanding of RNA epigenetic mechanisms, facilitating the development and use of epigenetic modification therapies to improve clinical outcomes for heart disease and other age-related diseases is needed.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Funding
The work was supported by the National Natural Science Foundation of China (Grant NOs: 81725024, 82205088, and 81904307).
Editorial Note
This corresponding author has a verified history of publications using a personal email address for correspondence.
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