Abstract

Long noncoding RNAs (lncRNAs) are transcripts that do not code for proteins, but nevertheless exert regulatory effects on various biochemical pathways, in part via interactions with proteins, DNA, and other RNAs. LncRNAs are thought to regulate transcription and other biological processes by acting, for example, as guides that target proteins to chromatin, scaffolds that facilitate protein–protein interactions and complex formation, and orchestrators of phase-separated compartments. The study of lncRNAs has reached an exciting time, as recent advances in experimental and computational methods allow for genome-wide interrogation of biochemical and biological mechanisms of these enigmatic transcripts. A better appreciation for the biochemical versatility of lncRNAs has allowed us to begin closing gaps in our knowledge of how they act in diverse cellular and organismal contexts, including development and disease.

Introduction

DNA, RNA, and proteins play critical roles in living cells, but RNA is uniquely able to both carry genetic information in the form of nucleotide sequence and also perform biochemical functions due to its ability to fold into complex tertiary structures. The long-held view that biochemical pathways are the domain of proteins has been reconsidered in recent years, as more roles have been attributed to once-thought non-functional RNA molecules that are not translated into proteins [1]. This paradigm shift was in part spurred by advances in large-scale analyses of gene expression, first provided by tiling oligonucleotide microarrays followed by even more powerful next-generation sequencing technologies, which revealed active transcription in ever-growing swaths of noncoding regions of the genome [26]. Only a very small portion of this widespread noncoding transcription could be assigned to conserved RNAs with well-known functions, such as ribosomal RNAs, transfer RNAs, small nuclear and nucleolar RNAs, and microRNAs. Most of the remaining noncoding transcripts were grouped in a category comprising RNAs longer than 200 nucleotides, puzzlingly lacking an obvious function, that were originally termed simply ‘large’ or ‘long’ noncoding RNAs (lncRNAs) [79].

Thousands of lncRNAs have been annotated in animals, including various mammals [6,912], zebrafish [13], and insects [1416]. Although plant and yeast genomes also contain lncRNAs, this review focuses on studies in humans, mice, and fruit flies, with only passing mentions of lncRNAs from plants and fungi, which have been reviewed elsewhere [1719].

Some lncRNAs had previously been identified by conventional methods. Arguably, the first molecule in this category was found in 1990, when the imprinted H19 transcript was noted to lack a long open reading frame and association with the translational machinery, suggesting that the RNA itself was functional, not an encoded protein product [20,21]. Similarly, the lncRNA XIST, which is critical for X chromosome inactivation [22,23], was discovered in 1991 and reported to lack coding potential [24,25]. However, the functional classification of most lncRNAs has been hindered thus far by low expression levels, a lack of sequence conservation, and incomplete annotation in many organisms. In recent years, improved biochemical, genetic, and computational methods have given researchers more tools to study lncRNAs and their regulatory roles, to dissect their biochemical mechanisms of action, and to understand their contributions to cancer [26,27] and other diseases [28,29].

Many reviews have been written on various aspects of lncRNA biology [3039]. In this one, we focus on relatively recent new insights into the function of nuclear lncRNAs in animals, with a particular focus on mechanistic studies and newly developed biochemical methods.

Biochemical mechanisms of lncRNA function

The pioneering papers reporting the existence of lncRNAs on a broad scale, as well as the results of the first perturbation studies, suggested that this broad category of transcripts might share a common biological function in gene regulation [9,4042], as do known classes of small noncoding RNAs, such as microRNAs, and piwi-associated RNAs [43]. However, it has become clear that the only thing that all lncRNAs have in common is their lack of coding potential. Many different subtypes of lncRNAs exist, such as promoter-associated, enhancer-derived, antisense, and intervening [30], each likely carrying out diverse functions in different molecular contexts. Even broader diversity exists among the intervening lncRNA subtype (lincRNAs), which might possess a variety of biochemical and cellular functions and will likely require individual characterization. Nonetheless, several central themes are emerging for the molecular roles that lncRNAs might be playing in the cell. In this review, we mainly elaborate on lncRNAs that have been proposed to regulate chromatin structure and transcription; however, roles for lncRNAs in a diverse set of crucial processes such as alternative splicing [4446], translation [47], and genome stability [48,49] have been identified, and more, surely, remain to be discovered. Below we review new evidence in support of two previously proposed [50] biochemical mechanisms of lncRNA function, chromatin recruitment and protein complex scaffolding, as well as their emerging role as potential orchestrators of nuclear organization and phase separation. We emphasize that these mechanisms of action need not be mutually exclusive, as the same lncRNA might have different biochemical functions (Figure 1).

Biochemical functions of lncRNAs.

Figure 1.
Biochemical functions of lncRNAs.

(A) Some lncRNAs form DNA–RNA triplexes (top), providing a potential mechanism for specific targeting of proteins to chromatin. LncRNAs discussed in the text are highlighted along with their associated proteins and target genes. LncRNAs could also recognize target regions on chromatin via Watson–Crick interactions with the DNA, forming R-loops (middle). TERRA forms an R-loop at its own locus at the telomeric region of chromosomes, activating the DNA damage response. Some lncRNAs are thought to guide chromatin-modifying complexes and transcription factors to target genes (bottom). (B) Many lncRNAs act as scaffolds to facilitate interactions between proteins, as in the NORAD–TOP1–RBMX complex that promotes genome stability and the rOX2–MSL–MLE complex involved in dosage compensation in Drosophila. Some lncRNAs have multiple biochemical functions, as with the scaffolding lncRNA GUARDIN, which also promotes genome stability through sequestering miR-23a. (C) Some lncRNAs may affect gene expression by regulating genome. HIDALGO, THYMOD, and HOTTIP regulate looping interactions at their own loci, while EVF2 and FIRRE are organizers of genome architecture on a larger scale. Some of these lncRNAs are aided by architectural proteins, such as CTCF and cohesin. (D) MALAT1 and NEAT1 lncRNAs are important for assembly of two phase-separated bodies in the nucleus, speckles, and paraspeckles, respectively. Speckles contain proteins involved in transcription and splicing; MALAT1 regulates the localization and the distribution of these proteins. NEAT1 acts as a scaffold to bring together members of the RNA production and processing machinery in paraspeckles.

Figure 1.
Biochemical functions of lncRNAs.

(A) Some lncRNAs form DNA–RNA triplexes (top), providing a potential mechanism for specific targeting of proteins to chromatin. LncRNAs discussed in the text are highlighted along with their associated proteins and target genes. LncRNAs could also recognize target regions on chromatin via Watson–Crick interactions with the DNA, forming R-loops (middle). TERRA forms an R-loop at its own locus at the telomeric region of chromosomes, activating the DNA damage response. Some lncRNAs are thought to guide chromatin-modifying complexes and transcription factors to target genes (bottom). (B) Many lncRNAs act as scaffolds to facilitate interactions between proteins, as in the NORAD–TOP1–RBMX complex that promotes genome stability and the rOX2–MSL–MLE complex involved in dosage compensation in Drosophila. Some lncRNAs have multiple biochemical functions, as with the scaffolding lncRNA GUARDIN, which also promotes genome stability through sequestering miR-23a. (C) Some lncRNAs may affect gene expression by regulating genome. HIDALGO, THYMOD, and HOTTIP regulate looping interactions at their own loci, while EVF2 and FIRRE are organizers of genome architecture on a larger scale. Some of these lncRNAs are aided by architectural proteins, such as CTCF and cohesin. (D) MALAT1 and NEAT1 lncRNAs are important for assembly of two phase-separated bodies in the nucleus, speckles, and paraspeckles, respectively. Speckles contain proteins involved in transcription and splicing; MALAT1 regulates the localization and the distribution of these proteins. NEAT1 acts as a scaffold to bring together members of the RNA production and processing machinery in paraspeckles.

Chromatin guides

Among the first molecular function assigned to lncRNAs was acting as a guide to recruit protein complexes, in particular, those that participate in gene regulation, to their target sites on chromatin [50,51] (Figure 1A). Various models have been proposed for how lncRNAs localize to specific sites on chromatin to facilitate protein recruitment, either proximal to their transcribed locus or at distal loci. LncRNA-mediated targeting of proteins to chromatin is composed of two distinct processes: the interaction of a lncRNA with the DNA sequence on one side and with protein effectors on the other.

Finding targets on DNA

LncRNAs can target specific sequences on chromatin either via direct association with DNA or indirectly as part of a protein–RNA complex. As previously hypothesized [52,53], sequence-driven recognition of genomic target sites by lncRNAs could occur either at intact double-stranded DNA (triplex mode) or by displacing a DNA strand (R-loop mode). DNA–RNA triplexes (Figure 1A) are structures formed by the sequence-specific interaction of an RNA strand with the major groove of a double-stranded DNA helix [54,55]. These structures are stabilized by non-canonical Hoogsteen hydrogen bonding between an RNA base and the canonical Watson–Crick base pair of DNA. Triplexes can be either parallel or antiparallel, based on the orientation of the RNA strand relative to the target DNA strand [54]. One example of a lncRNA binding to chromatin via a triplex interaction occurs at the human DHFR locus, where an upstream ncRNA forms a DNA–RNA triplex at the promoter, preventing transcription by disrupting the pre-initiation complex [56]. Another example is found at the rDNA locus in mouse, from which ribosomal RNAs are transcribed. Here, lncRNAs from the sense (pRNA) and antisense (PAPAS) strand form triplexes locally at the promoter and recruit the DNA methyltransferase DNMT3B and the chromatin remodeling complex NuRD, respectively [57,58], with the result of repressing rDNA transcription. Additional lncRNAs reported to form triplexes at distal loci include the developmental regulator FENDRR, the imprinted lncRNA MEG3, and the irradiation-responsive PARTICLE [5962], all of which were also reported to recruit the Polycomb repressive complex PRC2 (but see below for a discussion on the complexity of PRC2–RNA interactions). Despite these intriguing examples, clear rules have yet to emerge that would allow prediction of lncRNAs binding to genomic targets at distal loci based on the formation of DNA–RNA triplexes.

An alternative means by which lncRNAs could be recruited to chromatin is by forming DNA–RNA hybrid structures called R-loops (Figure 1A), whereby a complementary RNA directly pairs to DNA by displacing one of its strands [63]. This process normally occurs co-transcriptionally, when a nascent transcript binds to its template DNA. A well-characterized example is the TERRA family of lncRNAs in Saccharomyces cerevisiae, which regulate telomere length and cell senescence via R-loop formation [64]. Other studies in yeast have reported that lncRNA-mediated R-loops can occur post-transcriptionally at distal loci, but whether this is the case in higher organisms remains unknown [65,66]. Emerging new technologies to map R-loops with high resolution and sensitivity in mammalian cells [6770] might help answer this important question.

Some lncRNAs utilize spatial proximity to localize to specific chromatin sites. For example, local chromatin topology directs the spreading of XIST on the X chromosome and insertion of an Xist transgene at a different genomic locus changes its early localization pattern [71]. Whether this proximity model can be extended to other lncRNAs is not known.

Chromatin proteins that bind to lncRNAs

Typically, lncRNAs are more dynamically expressed during development and maintain more tissue specificity than protein-coding genes [10,11]. Together with their ability to guide proteins to chromatin, this makes lncRNAs prime candidates for factors that contribute target specificity to epigenetic regulators, which often lack DNA-binding domains, during development and in different cell types. A role for lncRNAs in recruiting the epigenetic silencer PRC2 to chromatin has been hypothesized for many years, though questions remain about the specificity of lncRNA binding and mechanisms of recruitment [39,72,73]. One of the first lncRNAs classified as functional was HOTAIR, which was shown to silence HOXD10 by facilitating the recruitment of the epigenetic silencing complex PRC2 through direct interactions [51]. Although following studies cast some doubt on the biochemical details of the initial model [74] and have not come to an agreement on the phenotypic consequences of the genetic deletion of Hotair in mice [7578], the pioneering work on HOTAIR spurred a search for other lncRNA–protein interactions that might underpin the recruitment of transcriptional regulators to chromatin, which in many cases pointed back to PRC2 and its affinity for various lncRNAs.

In fact, several subunits of PRC2, as well as PRC1 (another well-studied Polycomb repressive complex [79]), have been reported to bind to RNA in mammals, including EZH2, JARID2, SUZ12, CBX7, and SCML2 [8087]. Similarly, the plant lncRNAs COLDAIR, and COLDWRAP, which are involved in seasonal regulation of flowering in Arabidopsis thaliana, were observed to interact with PRC2 [88,89]. In animals, members of the trithorax group of proteins, which counter Polycomb-mediated epigenetic silencing [90] can also bind to lncRNAs. HOTTIP is a lncRNA transcribed from the Hoxa locus that binds to WDR5, a subunit of the H3K4 methyltransferase MLL complex [91,92]. Other examples of lncRNAs that guide deposition of epigenetic histone marks are AIR, which binds to the G9a H3K9 methyltransferase [93], and PAUPAR, which affects levels of the repressive H3K9me3 mark at target promoters by interacting with KAP1/TRIM28 [94,95].

In addition to regulating the deposition of histone modifications, lncRNAs can affect another key epigenetic modification, DNA methylation, via the recruitment of DNA methyltransferases (DNMTs). In addition to the pRNA from the rDNA locus mentioned above [57], the lncRNAs ecCEBPA and DALI repress methylation at neighboring genes by interacting with and inhibiting DNMT1 [96,97]. Furthermore, many lncRNAs involved in imprinting regulate DNA methylation at their associated protein-coding genes and might do so by directly or indirectly recruiting DNMTs [98].

In addition to guiding chromatin-modifying complexes to their targets, lncRNAs can participate in the recruitment of transcription factors, although these proteins also have a built-in ability to recognize DNA motifs embedded in the genomic sequence. The intronic lncRNA PANCT1 was originally identified in a screen for positive regulators of the pluripotency factor Pou5f1/Oct4 [99]. PANCT1 binds to the protein product that originates from its own locus, TOBF1, and increases its occupancy at target genes on chromatin. Interestingly, promoters for these genes are enriched for the Oct–Sox sequence motif, which is also embedded in the lncRNA itself. Rescue of TOBF1 binding can be achieved with overexpression of wild-type PANCT1, but not a mutant with a scrambled Oct–Sox motif [100], demonstrating that the lncRNA can function at distal loci and suggesting that PANCT1 recognizes target sequences on DNA directly, perhaps by forming an R-loop (see above). The lncRNA RMST is another effector of cell fate choice that facilitates binding of SOX2 to the promoters of neurogenic transcription factors via direct association [101]. Finally, some lncRNAs prevent the recruitment of transcription factors to chromatin, as in the example of the lncRNA PANDA, which inhibits chromatin binding of the transcription factor NF-YA [102].

RNA binding is a property shared by many chromatin-modifying complexes and chromatin-associated proteins [40,41,103,104], suggesting that the list of protein–RNA interactions with an epigenetic role is destined to grow. However, years of research on RNA-mediated regulation of chromatin function have taught us that isolated reports of lncRNA–protein interactions correlated with transcriptional effects might not be sufficient to draw strong conclusions on the biochemical and biological function of a lncRNA. Fortunately, emerging technologies will provide us with the ability to detect and manipulate lncRNA–protein interactions with ever increasing resolution and accuracy (see below) and will enable scientists in the field to perform rigorous rescue and tethering experiments using mutant proteins defective in RNA binding as controls. These experiments will allow us to confirm or refute proposed models for the function of lncRNAs within chromatin-associated complexes.

Scaffolds for complexes

A diverse collection of lncRNAs scaffold interactions between proteins and protein complexes (Figure 1B), affecting epigenetic regulation of gene expression, genome stability, nuclear organization, and microRNA biogenesis.

Drosophila achieves dosage compensation of the sex chromosome by doubling the transcriptional output from the single male X chromosome. This function is carried out by the dosage compensation complex (DCC), which is formed by the histone acetyltransferase Males-absent on first (MOF), four different Male sex lethal proteins (MSL1–4), and the RNA helicase Maleless (MLE) [105]. In addition to these protein components, spreading of DCC to the entire X chromosome requires the presence of at least one of two lncRNAs, roX1 and roX2 [106,107]. Protein–RNA cross-linking revealed that two stem loops on roX2 act as a switch for the binding of MSL2: when MLE is bound to roX2, one of the stem-loops is unwound, allowing for the formation of the other stem-loop and promoting binding of MSL2 [108]. The presence of RNA is required to stabilize the association of MLE with the other DCC proteins [109], suggesting the possibility that roX2 (and perhaps roX1) provides a scaffolding function within this essential complex.

Another epigenetic regulator, PRC2, whose complex relationship with RNA was briefly discussed above, has also been shown to interact with scaffolding lncRNAs. HOTAIR was shown to mediate interactions between PRC2 and the histone demethylase LSD1 [110], whereas the imprinted lncRNA MEG3 was shown to facilitate interactions of the core PRC2 subunit EZH2 with the accessory subunit JARID2 [83].

The lncRNA NORAD was first shown to interact with PUMILIO proteins and proposed to sequester them to promote the stability and translation of PUMILIO mRNAs targets [111]. RAP-MS (described later) and biochemical studies revealed that NORAD is required for the assembly of a novel complex, termed NARC1, which includes RBMX, TOP1, ALYREF, and the PRPF19–CDC5L complex, all of which had previously known roles in suppressing genomic instability [49]. The formation of this complex requires NORAD, which directly binds to RBMX. NORAD depletion causes replication-fork velocity reduction and cell-cycle defects, phenotypes similar to those observed upon deletion of TOP1 or RBMX, two proteins in the NORAD-dependent complex, thus indicating a role in genome stability for the NORAD transcript. The segregation defects observed upon Norad knockout were rescued by the reintroduction of the full-length transcript, confirming its ability to act at the RNA level.

Other scaffolding lncRNAs include NEAT1, which organizes paraspeckles, nuclear subdomains involved in splicing regulation [112] (see below) and regulates the interaction between paraspeckle proteins and the Microprocessor complex, thus enhancing pri-microRNA processing [113], and the lncRNA GUARDIN, which promotes heterodimerization between BRCA1 and BARD1. This interaction stabilizes BRCA1 by preventing its polyubiquitination [114]. GUARDIN can also sequester miR-23a, stabilizing the shelterin complex member TRF2 [114], demonstrating the ability of a single lncRNA to act via multiple non-exclusive biochemical mechanisms.

Overall, experimental evidence is growing for a pervasive scaffolding function of lncRNAs, which was previously postulated [50,115]. In addition to the candidate-based studies reviewed above, a recent proteome-wide analysis revealed that ∼20% of cellular protein complexes are sensitive to RNase A treatment [116], suggesting that RNA is a component of many mature complexes or at a minimum participates in their assembly. What portion of these scaffolding RNAs are lncRNAs remains to be determined.

Architects of the genome

Another increasingly appreciated function of lncRNAs is the regulation of chromosome conformation [32] (Figure 1C). XIST-mediated repression is associated with a general reshaping of the X chromosome in space [117,118] and with its relocalization to the nuclear lamina, possibly via a direct interaction of the lncRNA with the lamin B receptor (LBR) [119121]. Regulating enhancer–promoter contacts also provides a mechanism for controlling gene expression locally. HOTTIP was implicated as a factor in chromatin looping at the Hoxa locus [91], and two ‘activatory’ lncRNAs, ncRNA-a3 and ncRNA-a7, facilitate the formation of chromatin loops between their own locus and target genes, dependent on their interaction with the Mediator complex [122].

A class of lncRNAs that may contribute to nuclear architecture is chromatin-enriched lncRNAs, or cheRNAs [123,124]. Many cheRNAs overlap enhancers but have several properties that distinguish them from canonical enhancer-associated RNAs [125], including polyadenylation, H3K4me3-marked promoters, and a specific strand bias. HIDALGO is a cheRNA derived from read-through transcription of the hemoglobin gene Hgb1 and is required for the interaction between Hgb1 and its enhancer during K562 differentiation. Silencing of Hidalgo using CRISPR interference (CRISPRi) attenuated the contacts between Hgb1 and its two interacting partners, which include the Hidalgo promoter, and reduced Hgb1 expression. Antisense oligonucleotide-mediated depletion of HIDALGO recapitulated this effect, demonstrating a role for the RNA.

The phenomenon of lncRNAs activating genes near the site of their transcription is widespread [126], perhaps suggesting that the facilitation of looping either by the act of transcription or by the lncRNA is responsible for local regulation of gene expression. Indeed, lncRNAs that act locally are enriched at the boundaries of topological associated domains (TADs) [127,128], suggesting a role for lncRNAs in regulating local genome architecture.

One way lncRNAs might shape chromatin conformation is by interacting with known architectural proteins, such as cohesin and CTCF [129,130]. The lncRNA THYMOD activates expression of the T-cell specific gene Bcl11b by facilitating a promoter-enhancer loop [131]. THYMOD is transcribed from a downstream control region of Bcl11b and is required for interaction between Bcl11b and its enhancer. Attenuation of ThymoD transcription led to reduced CTCF and cohesin occupancy at the Bcl11b control region, abolishing the interaction and reducing Bcl11b expression. Another example is EVF2, transcribed from an ultraconserved super-enhancer, which maintains the gene expression program in mouse interneurons [132]. EVF2 localizes with cohesin subunits at targets genes, regulating their interactions with the super-enhancer from which it is transcribed.

The FIRRE lncRNA has been proposed to function as an organizer of interchromosomal interactions as well as a facilitator of correct nuclear localization of the inactive X chromosome. FIRRE localizes to the X chromosome from which it is transcribed, but also to distal autosomes, bringing these regions into nuclear proximity with each other [133]. FIRRE binds both cohesin and CTCF on the inactive X, contributing to its anchoring to the nucleolus [134]. Knockdown of FIRRE caused deregulation of both X-linked and autosomal genes, perhaps due to the loss of H3K27me3 on the inactive X chromosome. Interestingly, although CTCF occupancy and long-range interactions on the X chromosome are disrupted by Firre knockout, the overall structure of TADs is unchanged [135].

The RNA-binding activity of CTCF was initially characterized in the context of its interaction with the antisense lncRNA WRAP53 [136], and it was mapped to an RNA-binding region that was recently shown to be required for a large fraction of CTCF-dependent loops, suggesting the possibility that many more lncRNAs might control genome organization by interacting via CTCF [137,138].

Organizers of phase separation

Phase separation allows for functional compartmentalization in the cell, resulting in droplets where key factors are concentrated, thereby facilitating biochemical processes. Proteins with intrinsically disordered or low complexity domains interact to form ‘hubs,’ which are ensembles of phase-separated molecules with hydrogel-like properties [139]. The assembly of phase-separated stress granules is facilitated by the presence of RNA [140]. Many proteins with disordered regions interact with RNA [104,141,142], suggesting that the diversity of lncRNA sequences, expression patterns, and protein-binding properties might contribute to specifying compositionally and functionally distinct phase-separated compartments.

Paraspeckles and speckles are two such compartments that concentrate proteins in the nucleus in phase-separated domains [143,144] (Figure 1D). The lncRNA MALAT1 (also known as NEAT2) has long been known to associate with nuclear speckles [145], which contain components of the transcription and splicing machinery [146]. MALAT1 regulates the localization and the distribution of splicing factors in speckles, thereby affecting the alternative splicing of pre-mRNAs. Its acute depletion by knockdown is lethal in transformed HeLa cells [147], but a constitutive deletion by genetic knockout is surprisingly compatible with mouse development [148], and therefore key questions remain about its function in vivo. In contrast, NEAT1 is known to be required for the formation of paraspeckles [143], which are almost completely abolished upon its knockdown [149]. Paraspeckles contain members of the DBHS protein family, which play a part in various aspects of RNA production and processing [150]. Both MALAT1 and NEAT1 were reported to localize to chromatin at active sites of transcription [151] and it is tempting to speculate that these lncRNAs might facilitate phase transition processes, which are increasingly appreciated to play a role in transcriptional regulation [152].

The functional domains of NEAT1 have recently been explored in great depth using systematic deletions of different regions of the transcript [112]. NEAT1 has two isoforms; the longer isoform is stabilized by a triple helix and is required for paraspeckle formation. The middle domain of NEAT1 contains long repetitive sequences and is necessary and sufficient (along with the terminal 5′-end and the stabilizing triple helix) for the formation of ordered paraspeckles. Treatment with the known disruptor of phase-separated structures 1,6-hexanediol dissolved intact paraspeckles and abolished the co-localization of NEAT1 with the essential paraspeckle protein NONO. In addition, cells expressing a deletion mutant of NEAT1 that lacks protein-binding domains do not form normal paraspeckles. Tethering paraspeckle proteins to NEAT1 rescues normal paraspeckle formation; however, the NOPS dimer formation domain of NONO is required to successfully rescue the phenotype. These observations suggest that NEAT1 recruits NONO, which then initiates formation of paraspeckles protein complexes, using NEAT1 as a scaffold.

Finally, it has been recently hypothesized that XIST might silence the X chromosomes by forming phase-separated ‘silence granules’, due to its interactions with disordered proteins, including FUS and hnRNPA2 [22,153]. Although experimental evidence is required to support this suggestion, it provides an interesting new perspective on the biochemistry of XIST-mediated silencing.

‘The company you keep’ — techniques to study the lncRNA interactome

The common theme in the biochemical processes discussed above is that the molecular functions of lncRNAs emerge from their interactions with other proteins and DNA. Techniques to study protein–protein and DNA–protein interactions in both candidate-based and unbiased fashions have been available for decades and have more recently been coupled with high-throughput approaches in genomics and proteomics. Although similar approaches for lncRNA discovery have been lagging behind, the last few years have seen great advances in techniques to map protein–RNA and DNA–RNA interactions. The definitions for the many acronyms of methods mentioned in the following sections are collected in Table 1 along with the relevant citations.

Table 1
Biochemical methods to identify lncRNA interactions
Method Full name Use Citation 
DNA–RNA 
CHAR-seq Chromatin-Associated RNA sequencing genome-wide DNA–RNA contacts [166
CHART Capture Hybridization Analysis of RNA Targets candidate RNA localization on chromatin [159
ChIRP Chromatin Isolation by RNA Purification candidate RNA localization on chromatin [160
dChIRP domain-specific Chromatin Isolation by RNA Purification candidate RNA localization on chromatin [162
GRID-seq Global RNA Interactions with DNA by deep sequencing genome-wide DNA–RNA contacts [167
MARGI Mapping RNA-genome Interactions genome-wide DNA–RNA contacts [169
RAP RNA Antisense Purification candidate RNA localization on chromatin [71
RNA-DamID RNA-DNA adenine methylase identification candidate RNA localization on chromatin [164
SPRITE Split Pool Recognition of Interactions by Tag Extension genome-wide DNA–RNA contacts [168
protein–RNA 
IPL invivoProximity Labeling proximity labeling for protein–RNA [184
CARIC click Chemistry-assisted RNA Interactome Capture proteome-scale identification of all RBPs [195
CLIP ultraviolet Crosslinking and Immunoprecipitation discovery of RNA interactors of a candidate protein [176
eCLIP enhanced CLIP discovery of RNA interactors of a candidate protein [179
GoldCLIP Gel-omitted ligation-dependent CLIP discovery of RNA interactors of a candidate protein [180
HITS-CLIP High-Throughput Sequencing of RNA isolated by CLIP discovery of RNA interactors of a candidate protein [175
iCLIP individual nucleotide resolution CLIP discovery of RNA interactors of a candidate protein [178
iDRIP identification of Direct RNA Interacting Proteins discovery of protein interactors of a candidate RNA [121
RaPID RNA-protein Interaction Detection discovery of protein interactors of a candidate RNA [189
RBDmap RNA-binding Domain Mapping on a proteome scale proteome-scale identification of polyA-bound RBPs and domains [141
RBR-ID Proteomic Identification of RNA-binding Regions proteome scale identification of RBPs and domains [104
RICK newly transcribed RNA Interactome capture with Click chemistry proteome scale identification of nascent RNA-associated RBPs [194
RIP-seq RNA Immunoprecipitation and sequencing discovery of RNA interactors of a candidate protein [173
uvCLAP Ultraviolet Crosslinking and Affinity Purification discovery of RNA interactors of a candidate protein [181
XRNAX protein-crosslinked RNA extraction proteome scale identification of RBPs and domains [196
RNA–RNA 
CLASH Crosslinking Ligation and Sequencing of Hybrids candidate protein-associated RNA-RNA interactions [200
COMRADES Crosslinking of Matched RNAsand Deep Sequencing identification of RNA duplex interactions of candidate RNAs [203
LIGR-seq LIGation of interacting RNA and high-throughput sequencing trasncriptome-wide identification of RNA duplexes [202
PARIS Psoralen Analysis of RNA Interactions and Structures transcriptome-wide identification of RNA duplexes [201
RAP-RNA RAP for RNA-RNA interactions of a target RNA intermolecular RNA interactions of candidate RNA [199
Method Full name Use Citation 
DNA–RNA 
CHAR-seq Chromatin-Associated RNA sequencing genome-wide DNA–RNA contacts [166
CHART Capture Hybridization Analysis of RNA Targets candidate RNA localization on chromatin [159
ChIRP Chromatin Isolation by RNA Purification candidate RNA localization on chromatin [160
dChIRP domain-specific Chromatin Isolation by RNA Purification candidate RNA localization on chromatin [162
GRID-seq Global RNA Interactions with DNA by deep sequencing genome-wide DNA–RNA contacts [167
MARGI Mapping RNA-genome Interactions genome-wide DNA–RNA contacts [169
RAP RNA Antisense Purification candidate RNA localization on chromatin [71
RNA-DamID RNA-DNA adenine methylase identification candidate RNA localization on chromatin [164
SPRITE Split Pool Recognition of Interactions by Tag Extension genome-wide DNA–RNA contacts [168
protein–RNA 
IPL invivoProximity Labeling proximity labeling for protein–RNA [184
CARIC click Chemistry-assisted RNA Interactome Capture proteome-scale identification of all RBPs [195
CLIP ultraviolet Crosslinking and Immunoprecipitation discovery of RNA interactors of a candidate protein [176
eCLIP enhanced CLIP discovery of RNA interactors of a candidate protein [179
GoldCLIP Gel-omitted ligation-dependent CLIP discovery of RNA interactors of a candidate protein [180
HITS-CLIP High-Throughput Sequencing of RNA isolated by CLIP discovery of RNA interactors of a candidate protein [175
iCLIP individual nucleotide resolution CLIP discovery of RNA interactors of a candidate protein [178
iDRIP identification of Direct RNA Interacting Proteins discovery of protein interactors of a candidate RNA [121
RaPID RNA-protein Interaction Detection discovery of protein interactors of a candidate RNA [189
RBDmap RNA-binding Domain Mapping on a proteome scale proteome-scale identification of polyA-bound RBPs and domains [141
RBR-ID Proteomic Identification of RNA-binding Regions proteome scale identification of RBPs and domains [104
RICK newly transcribed RNA Interactome capture with Click chemistry proteome scale identification of nascent RNA-associated RBPs [194
RIP-seq RNA Immunoprecipitation and sequencing discovery of RNA interactors of a candidate protein [173
uvCLAP Ultraviolet Crosslinking and Affinity Purification discovery of RNA interactors of a candidate protein [181
XRNAX protein-crosslinked RNA extraction proteome scale identification of RBPs and domains [196
RNA–RNA 
CLASH Crosslinking Ligation and Sequencing of Hybrids candidate protein-associated RNA-RNA interactions [200
COMRADES Crosslinking of Matched RNAsand Deep Sequencing identification of RNA duplex interactions of candidate RNAs [203
LIGR-seq LIGation of interacting RNA and high-throughput sequencing trasncriptome-wide identification of RNA duplexes [202
PARIS Psoralen Analysis of RNA Interactions and Structures transcriptome-wide identification of RNA duplexes [201
RAP-RNA RAP for RNA-RNA interactions of a target RNA intermolecular RNA interactions of candidate RNA [199

Mapping lncRNAs on chromatin

The biochemical functions of lncRNAs go hand in hand with their subcellular localization. While some lncRNAs are exported to the cytoplasm, many remain in the nucleus, where they can interact with DNA and protein complexes. LncRNAs are generally enriched in the nucleus compared with protein-coding RNAs [6,154], and recent efforts fusing typically cytoplasmic transcripts to different regions of known nuclear lncRNAs have identified sequence motifs responsible for their nuclear retention [155,156]. These motifs demonstrated higher conservation than other lncRNA regions, suggestive of functionality [156]. One such motif found was an Alu-derived sequence, called SIRLOIN for SINE-derived nuclear RNA localization [155]. The nuclear retention of SIRLOIN-containing RNAs was mediated by the RNA-binding protein HNRNPK.

The longstanding hypothesis that lncRNAs participate in gene regulation [30,157,158] is supported by the observation that many of them are enriched in the chromatin fraction [123,124]. Mapping lncRNAs along the genome is thus critical for understanding this suspected function. Various methods have been developed toward this end, including CHART, ChIRP, and RAP [71,159,160]. These methods identify genome-wide lncRNA binding sites by chemical cross-linking followed by the capture of target RNAs using antisense biotinylated probes (Figure 2A). DNA that co-purifies with the lncRNA of choice is sequenced and regions of enrichment are identified, similar to existing strategies to localize protein on chromatin, such as chromatin immunoprecipitation. While conceptually similar, these methods differ in probe design, cross-linking strategies, and DNA elution conditions. RAP uses long 120 nt probes that tile the entire RNA sequence, whereas CHART and ChIRP opt for shorter 20–25 nt probes. ChIRP employs glutaraldehyde cross-linking to fix DNA–RNA contacts, which can potentially capture interactions over long distance, in contrast with usage of formaldehyde in CHART, which cross-links across shorter distances. RAP uses both formaldehyde and disuccinimidyl glutarate to capture both shorter- and longer-range contacts [161]. dChIRP is a further refinement of the ChIRP method, which probes individual lncRNA domains, providing a higher resolution map of interactions [162].

Methods for mapping the lncRNA interactome.

Figure 2.
Methods for mapping the lncRNA interactome.

(A) Outline of methods to study lncRNA localization on chromatin. RAP, ChIRP, and CHART (left) use chemical cross-linking and biotinylated probes to capture a candidate lncRNA cross-linked to chromatin and identify its genomic targets by sequencing the associated DNA. In RNA-DamID (middle) cells express a lncRNA of interest fused to MS2 stem-loop sequences and an Escherichia coli adenine methyltransferase (Dam) fused to the MCP. This results in methylation at lncRNA-bound genomic sites in vivo. Methylated DNA is then isolated with a methylation-sensitive restriction enzyme and sequenced. MARGI, GRID-seq, and CHAR-seq (right) use a biotinylated oligonucleotide bridge to ligate RNA to DNA in close proximity, followed by affinity purification of ligated complexes, library preparation, and sequencing. (B) Schematic of methods used to identify RNA interactors of a given RBP. GoldCLIP and uvCLAP use affinity handles to purify cross-linked protein–RNA complexes, followed by adaptor ligation and direct elution of bound RNAs for sequencing. eCLIP, iCLIP, and irCLIP use protein-specific antibodies, SDS–PAGE, membrane transfer, and membrane excision to isolate RNAs for sequencing. (C) Outline of methods to identify lncRNA–protein interactions. Left: methods to detect protein interactors of a candidate lncRNA. RAP-MS, ChIRP-MS, and CHART-MS chemically cross-link RNA to proteins, use biotinylated probes to capture target lncRNA–protein complexes, and digest with RNase to release bound proteins for MS; RaPID targets the BirA* biotin ligase to a stem-loop-modified RNA to biotinylate protein interactors in live cells. Right: methods to identify new RBPs that bind to RNA in cells. RBDmap (left) and RBR-ID (right) use UV to cross-link RNA to protein in live cells in the presence or absence of 4SU. RBDmap lyses cells and employs two rounds of oligo(dT) capture to enrich for polyadenylated transcripts (left). RBR-ID isolates cell nuclei to identify all nuclear RNA-binding proteins. Both methods include RNAse digestion and protease digestion steps to generate short cross-linked peptides that can be analyzed by MS (bottom).

Figure 2.
Methods for mapping the lncRNA interactome.

(A) Outline of methods to study lncRNA localization on chromatin. RAP, ChIRP, and CHART (left) use chemical cross-linking and biotinylated probes to capture a candidate lncRNA cross-linked to chromatin and identify its genomic targets by sequencing the associated DNA. In RNA-DamID (middle) cells express a lncRNA of interest fused to MS2 stem-loop sequences and an Escherichia coli adenine methyltransferase (Dam) fused to the MCP. This results in methylation at lncRNA-bound genomic sites in vivo. Methylated DNA is then isolated with a methylation-sensitive restriction enzyme and sequenced. MARGI, GRID-seq, and CHAR-seq (right) use a biotinylated oligonucleotide bridge to ligate RNA to DNA in close proximity, followed by affinity purification of ligated complexes, library preparation, and sequencing. (B) Schematic of methods used to identify RNA interactors of a given RBP. GoldCLIP and uvCLAP use affinity handles to purify cross-linked protein–RNA complexes, followed by adaptor ligation and direct elution of bound RNAs for sequencing. eCLIP, iCLIP, and irCLIP use protein-specific antibodies, SDS–PAGE, membrane transfer, and membrane excision to isolate RNAs for sequencing. (C) Outline of methods to identify lncRNA–protein interactions. Left: methods to detect protein interactors of a candidate lncRNA. RAP-MS, ChIRP-MS, and CHART-MS chemically cross-link RNA to proteins, use biotinylated probes to capture target lncRNA–protein complexes, and digest with RNase to release bound proteins for MS; RaPID targets the BirA* biotin ligase to a stem-loop-modified RNA to biotinylate protein interactors in live cells. Right: methods to identify new RBPs that bind to RNA in cells. RBDmap (left) and RBR-ID (right) use UV to cross-link RNA to protein in live cells in the presence or absence of 4SU. RBDmap lyses cells and employs two rounds of oligo(dT) capture to enrich for polyadenylated transcripts (left). RBR-ID isolates cell nuclei to identify all nuclear RNA-binding proteins. Both methods include RNAse digestion and protease digestion steps to generate short cross-linked peptides that can be analyzed by MS (bottom).

These methods have yielded robust results in select contexts, for example, in the characterization of early spreading of XIST on the X chromosome [71,163] and the identification of chromatin binding sites for MALAT1 and NEAT1 [151], but they suffer from high levels of background signal and contamination from cross-linked interactions [161] and alternative strategies might be required in cases where the biological material is limiting or the lncRNA of interest is expressed at low levels.

More recently, RNA-DamID was developed to map lncRNA-occupied sites in vivo [164]. This method is based on the principle of targeted DamID, in which the bacterial adenine methylase Dam is expressed in cells as a fusion to a protein of interest, and methylates adenines in the vicinity of its genomic targets [165]. In RNA-DamID, a lncRNA of interest fused to MS2 stem loops and the Dam enzyme fused to MS2 coat protein (MCP) are coexpressed in live cells. The stem-loop–MCP interaction recruits Dam to the lncRNA, and, therefore, to its binding sites on chromatin, which are methylated and subsequently identified by selective digestion with a methylation-sensitive restriction enzyme followed by sequencing (Figure 2A). RNA-DamID was applied to map tissue-specific binding of roX RNAs in Drosophila embryos with increased accuracy and sensitivity compared with previous methods, by identifying fewer false-positive peaks of roX binding and reducing the amount of required input material 100-fold [164]. The drawback of this method is the demand for genetic manipulation of cells and tagging the lncRNA of interest with MS2 stem-loops, preventing its use in certain cases, such as patient-derived samples.

The techniques above are designed to map the localization of only a single lncRNA. It has now become possible to map the distribution of all chromatin-associated RNAs in an unbiased manner with the development of MARGI, CHAR-seq, GRID-seq, and more recently SPRITE [166169]. MARGI, CHAR-seq, and GRID-seq use chemical cross-linking followed by a biotinylated oligonucleotide bridge to ligate DNA and RNA in close proximity, forming a DNA–RNA chimera that is captured and sequenced after reverse transcription (RT) (Figure 2A). SPRITE does not use proximity ligation but instead employs a split-and-pool strategy to sequentially label interacting DNA and RNA with barcoded tags, which are identified after sequencing by matching reads that contain the same combination of barcodes [168]. These methods have thus far uncovered local and long-distance DNA–RNA contacts in both human and Drosophila and could shed light on the potential roles of lncRNAs in orchestrating three-dimensional genome architecture, but, as with any unbiased approach, suffer from the limitations of being skewed toward detecting the most abundant species.

Defining protein–RNA interactions

Identifying the proteins that interact with a given lncRNA is critical for understanding its function. Protein–RNA interactions can be interrogated in vivo and in vitro by various binding assays, including RNA immunoprecipitation (RIP) with or without cross-linking, electro-mobility shift assays (EMSA), filter-binding assays, and fluorescence anisotropy measurements. These, however, can only test candidate interactions where both the protein and the RNA are known. Several unbiased methods have been developed to discover new protein–RNA interactions and we divide them into those that identify all RNAs bound to a protein of choice (‘RNA discovery’, Figure 2B) or choose a lncRNA and identify all proteins that bind to it (‘protein discovery’, Figure 2C).

RNA discovery

Historically, RNA discovery methods were developed first. Immunoprecipitation in RNA-preserving conditions was coupled initially to custom-designed microarrays interrogating large sets of RNAs simultaneously [9,41,170172] and then with unbiased deep sequencing (RIP-seq, [173]). However, native RIP-based methods, lacking stringent washing steps, are known to suffer from exceedingly high noise levels [174], especially when combined with PCR-mediated amplification and sensitive deep sequencing. More recent alternatives are all based on variants of CLIP and its high-throughput version, HITS-CLIP (also known as CLIP-seq), which were originally developed to study factors regulating alternative splicing in the brain [175,176]. CLIP entails UV-mediated cross-linking of RNA to its interacting proteins in vivo followed by immunoprecipitation of a protein of interest, separation on an SDS–PAGE gel and transfer to nitrocellulose membrane. Once the presence of cross-linked protein–RNA complexes on the membrane is confirmed at a position compatible with the expected molecular mass of the protein of interest, they can be excised and the eluted RNA can be processed for deep sequencing (Figure 2B).

Because of the covalent nature of protein–RNA cross-linking, some of the biochemical steps in CLIP are performed in extremely stringent conditions (i.e. SDS denaturation during SDS–PAGE) but the initial forms of this method were still troubled by high levels of noise and poor yields [177]. Some of these issues were addressed in subsequent improvements. iCLIP introduced a circular ligation step after RT during library preparation, which allowed recovery of the truncated cDNAs resulting from early termination of RT at the cross-link site, increasing yields and providing single-base resolution information regarding the position of the presumptive protein–RNA interaction [178]. eCLIP further refined the iCLIP protocol and included a strategy to sequence size-matched input material in parallel [179], which is in our opinion a necessary step to calculate enrichment of true RNA interactors.

Other variants of CLIP have been developed to address the issue of low yields at the biochemical level, by replacing the highly inefficient and time-consuming membrane transfer and elution steps with in-solution purification strategies. GoldCLIP and uvCLAP are both based on epitope tags that allow for purifications in extremely stringent conditions [180,181]. The GoldCLIP method involves fusion of the protein of interest to the bacterial HaloTag, which covalently attaches to chloroalkane-conjugated beads during purifications, whereas uvCLAP introduced an affinity tag that allows for in vivo biotinylation of the protein of choice followed by streptavidin-mediated purification of the cross-linked complexes under denaturing conditions. uvCLAP was utilized to study the nuclear RNA helicase DHXF9, revealing that it binds to RNAs containing inverted Alu repeats, proving the method's practical advantages [182]. However, both GoldCLIP and uvCLAP rely on molecular engineering of the protein of interest to introduce the affinity tag and therefore might not be suitable to investigate protein–RNA interactions in all contexts.

Finally, proximity labeling approaches [183] are now becoming available for RNA discovery. These are experimental strategies conceptually different from those described above, which all rely on some type of affinity purification of a protein–RNA complex. Instead, proximity labeling converts the physical proximity of potential RNA interactors to a protein of choice in vivo into a chemical labeling that can then be used to recover and identify the RNAs. The first of these approaches was in vivo proximity labeling (IPL), which utilized photoactivatable biotin to tag RNAs in the proximity of a protein of choice [184]. More recently, proximity labeling techniques developed to study protein–protein interactions have also been adapted for RNA discovery. APEX, which uses an engineered ascorbate peroxidase 2 to biotinylate targets [185] has now been used to biotinylate proximal RNAs in vivo [186,187]. It is important to note that, like all proximity labeling strategies, these methods reveal proximity in vivo and not physical interaction and therefore caution should be used in inferring biochemical relationships between the protein of choice and the newly identified RNAs without additional validation steps.

Protein discovery

The first techniques for protein discovery (i.e. to identify proteins bound to a lncRNA) have been adaptations of the hybridization capture methods CHART, ChIRP, and RAP described above, whereby a protein elution step was added after the purification of cross-linked protein–RNA complexes followed by mass spectrometry (MS) for protein identification. Several methods based on these principles have been developed to date, including CHART-MS, ChIRP-MS, RAP-MS, and iDRIP [120,121,151,190] (Figure 2C). ChIRP-MS, RAP-MS, and iDRIP were used to identify interactors of the XIST lncRNA in mouse embryonic stem cells, including the transcriptional repressor SPEN, which was functionally validated. RAP-MS was also applied to study the role of the lncRNA SAMMSON in promoting melanoma cell survival by stabilizing mitochondrial protein p32 [26], and the orchestration of a protein–RNA complex essential for genome stability by the lncRNA NORAD [49].

Proximity-based methods are also available for protein discovery. For example, RaPID is an adaptation of BioID that uses the bacterial biotin ligase mutant BirA* to biotinylate the protein interactors of a given RNA motif in live cells [189] (Figure 2C). The RNA of interest is fused to bacteriophage BoxB stem loops and coexpressed with BirA* fused to the BoxB-binding λN peptide. The BirA*–λN fusion binds strongly to the BoxB stem loops and biotinylates proteins associated with the target RNA motif in vivo, which are purified and analyzed by MS.

Identification of new RNA-binding proteins and domains

In addition to candidate-based studies of proteins known to bind lncRNAs, several methods have been developed to identify new RNA-binding proteins in an empirical manner and, more recently, map their RNA-binding domains. Pioneered by the Hentze group, these approaches initially relied on protein–RNA cross-linking followed by affinity purification of polyadenylated transcripts and identification of cross-linked proteins by MS [142,191193]. A refinement of this method, termed RBDmap, allowed for the simultaneous identification of RNA-binding proteins and the mapping of the interaction site at peptide resolution [141]. We developed RBR-ID, a similar method, but based on a slightly different principle, which allowed us to identify a larger scope of RNA-binding proteins, including those that bind non-polyadenylated transcripts, and to map their RNA-binding regions in vivo [104]. Several other methods have been developed along these same lines, including CARIC and RICK, which combine metabolic labeling of RNAs and biotin conjugation for purification of cross-linked RNA and protein [194,195], and XRNAX, which captures cross-linked RNA–protein complexes in the insoluble TRIZOL interphase during purification for downstream sequencing or MS [196].

Collectively, these methods have led to the realization that in addition to the several hundred ‘canonical’ RNA-binding proteins, characterized by possessing one or more well-characterized RNA-binding domains (e.g. RRM, KH, dsRBD; [197]), hundreds — perhaps thousands — more form protein–RNA interactions in vivo, whose functional significance remains unexplored. We propose that in many cases these interactions might be taking place with lncRNAs and that characterizing them will greatly contribute to our understanding of lncRNA function. Furthermore, ‘targeted’ versions of RBR-ID and RBDmap have been developed that can map protein–RNA interactions at high resolution within a complex of choice (e.g. PRC2 [198]). These studies will be instrumental to design ‘separation-of-function’ mutants to address the biochemical and biological roles of RNA interactions within these complexes and validate the proposed biological functions of lncRNAs (see above).

RNA–RNA interactions

While small noncoding RNAs — including micro RNAs, piwi-associated RNAs, and small nucleolar RNAs — are known to function largely via RNA–RNA base pairing [43], whether lncRNAs also participate in functional interactions with other RNAs is much less clear.

RAP-RNA was one of the first methods developed to identify the RNA interactors of specific lncRNAs. In RAP-RNA, cellular RNA is chemically cross-linked with one of three cross-linking agents to enrich for direct, both direct and indirect, or only indirect RNA interactions [199]. This is followed by the capture of a target lncRNA using antisense biotinylated probes. While RAP-RNA revealed that the abundant MALAT1 lncRNA interacts with pre-mRNAs at active chromatin loci, it recovered virtually no direct RNA interactors, suggesting that MALAT1 does not base pair with its mRNA targets.

CLASH is another method that has enabled the high-throughput sequencing of direct RNA–RNA interactions [200]. CLASH requires the expression of a tagged ‘bait’ protein in cells, followed by UV cross-linking of RNAs to protein. The tagged protein is pulled down with its cross-linked RNAs, which are ligated to form chimeric molecules that are subsequently sequenced. CLASH has been applied to identify global miRNA interactions in human cells, revealing widespread non-canonical binding of microRNAs to mRNAs and ncRNAs. CLASH may hold promise for identifying lncRNA–RNA interactions but is limited by the requirement of a universal protein bait. Two additional methods — PARIS and LIGR-seq — allowed for the mapping of RNA duplexes in living cells through a combination of psoralen cross-linking and proximity ligation followed by sequencing [201,202]. The resulting data can be used to infer RNA secondary structure as well as functional interactions. COMRADES, a similar method, uses tandem affinity purification to isolate RNA duplexes and was developed alongside a new computational pipeline to predict and cluster RNA structures [203]. Because these methods identify global RNA interactions, it may be challenging to leverage them to study lowly expressed lncRNAs.

Aiding biochemistry: genetic and computational tools to study lncRNAs

Although the many new methods discussed above have the potential to reveal a large number of new biochemical interactions of lncRNAs, often choosing which lncRNA to study is the most difficult question, and biochemistry alone might not provide the answer. The number of annotated lncRNAs in the human genome is in the order of nearly ten thousand [6], and in many cases, the lncRNA itself has no discernible RNA-mediated function [204]. How, then, can the needle of a new functional lncRNA be found in the haystack of thousands of potentially non-functional annotations? New genetic and computational tools might provide the answer.

Genome-wide forward genetic screens

Forward genetic screens in mammalian cells have become feasible due to the power and versatility of CRISPR-based tools, which allow for both loss- and gain-of-function screening strategies in a pooled format [205] (Figure 3A) allowing the direct interrogation of thousands of lncRNAs in a relatively manageable experiment.

Functional characterization of lncRNAs.

Figure 3.
Functional characterization of lncRNAs.

(A) CRISPR screens have been used to identify functional lncRNAs. A guide RNA library is created against a set of lncRNA genes and transfected into cells, with the goal of targeting one gene in each cell. Different proteins can be targeted to the locus of interest, including Cas9 (knockout screens), a combination of NLS–dCas9–VP64 and MS2–p65–HSF1 (synergistic activation mediator, ‘SAM’; CRISPR activation screens), or dCas9–KRAB repressor (CRISPR interference screens). Following selection of successfully transfected cells, cells are allowed to proliferate, with the possible addition of a treatment such as a drug. After a period of growth, the composition of guide RNAs in the final pool of cells is compared with that in the starting population. Enriched or depleted guides indicate a phenotype for the targeted gene, depending on the direction of enrichment and the type of screen. (B) Some lncRNAs exhibit synteny without conservation. In these cases, two lncRNAs that occupy the same genomic position in different species do not have significant sequence similarity, suggesting that these lncRNAs might act locally to regulate transcription of neighboring orthologous protein-coding (pc) genes. (C) LncRNAs can be grouped functionally by their k-mer profile. In this example, activating lncRNA 1 and 2 have similar k-mer profiles, while repressing lncRNA 3 and 4 have similar k-mer profiles.

Figure 3.
Functional characterization of lncRNAs.

(A) CRISPR screens have been used to identify functional lncRNAs. A guide RNA library is created against a set of lncRNA genes and transfected into cells, with the goal of targeting one gene in each cell. Different proteins can be targeted to the locus of interest, including Cas9 (knockout screens), a combination of NLS–dCas9–VP64 and MS2–p65–HSF1 (synergistic activation mediator, ‘SAM’; CRISPR activation screens), or dCas9–KRAB repressor (CRISPR interference screens). Following selection of successfully transfected cells, cells are allowed to proliferate, with the possible addition of a treatment such as a drug. After a period of growth, the composition of guide RNAs in the final pool of cells is compared with that in the starting population. Enriched or depleted guides indicate a phenotype for the targeted gene, depending on the direction of enrichment and the type of screen. (B) Some lncRNAs exhibit synteny without conservation. In these cases, two lncRNAs that occupy the same genomic position in different species do not have significant sequence similarity, suggesting that these lncRNAs might act locally to regulate transcription of neighboring orthologous protein-coding (pc) genes. (C) LncRNAs can be grouped functionally by their k-mer profile. In this example, activating lncRNA 1 and 2 have similar k-mer profiles, while repressing lncRNA 3 and 4 have similar k-mer profiles.

The first lncRNA loss-of-function screen utilized CRISPRi [206] to identify lncRNAs required for survival in various cell lines [207]. Consistent with the marked cell type specificity of these noncoding transcripts, 89% of lncRNAs with a growth phenotype were specific to one cell type, compared with 55% of protein-coding mRNAs, and no single lncRNA was required for survival in all cell types. Critical pathways such as translation, DNA replication, and post-transcriptional regulation were perturbed by lncRNA repression. Functional lncRNAs identified by this screen have a set of distinct characteristics: expression level, distance from an enhancer, and number of exons were predictive of a growth phenotype following their repression. A gain-of-function screen identified lncRNAs that conferred resistance to BRAF inhibitors in melanoma cells [126]. One hit from this screen was the lncRNA EMICERI, which is responsible for the activation of the nearby protein-coding gene Mob3b, part of the vemurafenib resistance-associated Hippo signaling pathway. Most lncRNA hits that mediated BRAF resistance acted by affecting the expression of nearby genes, adding to the number of examples of lncRNAs that regulate targets locally.

Genetic screens have also been used to identify lncRNAs with positive or negative effects on growth in HuH7.5 liver cancer cells [208], lncRNAs that affect a specific pathway [209], and antisense lncRNAs that regulate cell viability following Ara-C chemotherapy in acute myeloid leukemia (AML) [210]. The AML screen found one coding/noncoding pair, GAS6/GAS6-AS2, that also had correlated expression in a large database of cancer cells treated with Ara-C. Overexpression of the lncRNA GAS6-AS2 caused the up-regulation of its cognate protein-coding gene GAS6 locally but also induced expression of the GAS6 receptor gene, AXL, distally, suggesting that this lncRNA might act via multiple biochemical mechanisms.

Computational approaches to infer lncRNA function

Classic tools used to infer the functional importance of protein sequence, namely its evolutionary conservation, are less powerful in the context of lncRNAs, which are not under pressure to maintain a coding frame. However, rather than maintaining primary sequence through evolution, lncRNAs may conserve their function through positional homology, k-mer content, or secondary structure.

Many lncRNAs have synteny without sequence conservation, perhaps indicating a regulatory role that does not depend on sequence. For these genes, sequence conservation exists in protein-coding genes and genomic sequences flanking the lncRNA locus, but not in the lncRNA itself (Figure 3B) [211].

Also suggested is a conservation of short sequence motifs, or k-mers, as the frequency of certain k-mers may affect the ability of a protein to bind to the transcript [212]. The k-mer profiles of lncRNAs from different functional groups, such as those that repress or activate transcription locally, tend to cluster together (Figure 3C). The localization and binding ability of proteins can be predicted from k-mer profiles. The dynamics of lncRNA biogenesis can also be used to infer functional classes of lncRNAs. Measuring transcription, splicing, degradation, localization, and translation dynamics of protein-coding and noncoding RNAs recovered known characteristics of lncRNAs, including slower splicing, synthesis, and processing rates, paired with higher degradation rates [213]. The function of lncRNAs was assigned by grouping them with protein-coding genes of known function that had similar characteristics. This produced protein-coding/lncRNA groups with a wide range of metabolic properties and distinct likely functions.

Another common strategy for identifying lncRNAs and their function is correlating their expression with that of protein-coding genes. Increasing amounts of sequencing data from various tissues and conditions allow for the detection of highly variable genes and the identification of frequently co-expressed genes. The function of a lncRNA can be inferred from the identity of protein-coding genes that have a similar transcriptional profile [10]. In non-model organisms, where sophisticated genetic tools are not always readily available, the approach of using large sequencing datasets to identify correlated lncRNAs and protein-coding genes could be used to identify potentially functional lncRNAs and prioritize them for follow-up experiments.

Finally, comparative genomics and evolutionary analyses of lncRNA sequence conservation have provided information on potential lncRNA function. Co-expression networks of lncRNAs and protein-coding genes that are expressed in multiple organisms helped identify lncRNAs involved in spermatogenesis, synaptic transmission, and muscle functions in the heart [10]. Although lncRNAs evolve more rapidly than protein-coding genes, lncRNA promoters contain more transcription factor binding sites than random intergenic regions do and are particularly enriched for motifs recognized by homeobox transcription factors. The age of a lncRNA affects the likelihood of its active regulation, as the Polycomb protein SUZ12 and the pluripotency transcription factor OCT4 associate more with older, more conserved lncRNAs [10].

Concluding remarks/future outlook

We have witnessed an acceleration in the development of new technologies and strategies to discover and characterize functional lncRNAs, several of which are reviewed above. Looking ahead, continued improvements to biochemical and genomic technologies will allow for the functional interrogation of lncRNAs in specific tissues and cell types, as well as the identification of novel lncRNAs with important biological roles.

Given their very specific and restricted expression patterns, we believe that great insight into lncRNA function will be offered by single-cell analyses [31]. Indeed, it has already been shown that at least in the case of some lncRNAs their presumptive lower expression level in bulk samples was a consequence of the smaller population of cells in heterogeneous mixtures that expressed them. A collection of 81 single-cell transcriptomes revealed that lncRNAs are activated during reprograming and suppress lineage-specific genes on a single-cell level [214]. Another study of 226 cells from radial sections of the mouse neocortex identified cell type-specific lncRNAs [214]. Single-cell sequencing has revealed different lncRNA profiles among fibroblast cell types [215] and between neurons and glia in Drosophila [216]. Although these studies are informative, higher-throughput studies may provide more information about the specificity and regulatory potential of lncRNAs in the context of a whole tissue or organism.

Evolutionary studies of lncRNAs have been aided by new annotations of lncRNAs in a variety of model and non-model organisms, facilitated by new and improved genome assemblies. For example, new lncRNA annotations in Xenopus tropicalis and the analysis of their expression patterns suggested functional roles in tissue identity during development [217]. Annotations of lncRNAs have become available in multiple social insect species [15,16], where alternative developmental trajectories give rise to individuals with identical genomes but vastly different morphological, physiological, and behavioral phenotypes. We analyzed lncRNA expression in Harpegnathos saltator, an ant that maintains reproductive plasticity in workers during a unique caste transition [218]. Major transcriptional changes occur in the brain during this event, including differential regulation of lncRNAs [16,219]. As CRISPR-mediated editing of the germline has been achieved in Harpegnathos ants [220], these newly discovered caste-specific transcripts are prime targets for the functional investigation of lncRNAs potentially involved in brain function and behavior.

Another emerging frontier in lncRNA research is the analysis of their post-transcriptional chemical modification [221]. Pioneering studies on XIST showed that its modification with m6A is required for the silencing of several X-linked genes [222]. DCI, a protein required for XIST-mediated transcriptional silencing, binds preferentially at m6A residues. As folding of lncRNAs is thought to be key to their function, it will be of great interest to determine if chemical modifications that affect their three-dimensional structure contribute to their biological and biochemical versatility.

Given the many known and suspected roles of lncRNAs in various cellular processes, it should not come as a surprise that dysregulation of lncRNAs can lead to disease or aberrant phenotypes. LncRNAs are increasingly being considered as therapeutic targets [223,224]. As mentioned above, genetic screens have detected many lncRNAs involved in cancer progression [126,209,210]. Additionally, organisms that transmit or cause disease can affect how the immune system recognizes threats through regulation of lncRNAs in their own transcriptome or in host cells. The genomes of mosquitoes and of the malaria parasites harbor lncRNAs [225228], and the parasite Toxoplasma gondii affects the lncRNA profile of its host [229]. The annotation of lncRNAs in more organisms will lead to a better understanding of their function and will provide new avenues to study lncRNA-related diseases and their treatment.

Abbreviations

     
  • AML

    acute myeloid leukemia

  •  
  • CRISPRi

    CRISPR interference

  •  
  • DCC

    dosage compensation complex

  •  
  • DNMTs

    DNA methyltransferases

  •  
  • EMSA

    electro-mobility shift assays

  •  
  • IPL

    in vivo proximity labeling

  •  
  • LBR

    lamin B receptor

  •  
  • lincRNAs

    intervening lncRNA subtype

  •  
  • lncRNAs

    long noncoding RNAs

  •  
  • MCP

    MS2 coat protein

  •  
  • MLE

    maleless

  •  
  • MOF

    males-absent on first

  •  
  • MS

    mass spectrometry

  •  
  • RIP

    RNA immunoprecipitation

  •  
  • RT

    reverse transcription

  •  
  • TADs

    topologically associated domains

Funding

R.B. acknowledges support from the NIH [DP2MH107055, R01GM127408], the Searle Scholars Program (15-SSP-102), the March of Dimes Foundation [1-FY-15-344], a Linda Pechenik Montague Investigator Award, and the Charles E. Kaufman Foundation [KA2016-85223]. E.J.S. was supported in part by an NIH training grant [T32HG000046]. A.P. was supported in part by an NIH training grant [T32 HD083185].

Acknowledgements

The authors thank M. Owens and R. Warneford-Thomson for critical reading of the manuscript.

Competing Interests

The Authors declare that there are no competing interests associated with the manuscript.

References

References
1
Cech
,
T.R.
and
Steitz
,
J.A.
(
2014
)
The noncoding RNA revolution-trashing old rules to forge new ones
.
Cell
157
,
77
94
2
ENCODE Project Consortium
(
2012
)
An integrated encyclopedia of DNA elements in the human genome
.
Nature
489
,
57
74
3
Kapranov
,
P.
,
Cawley
,
S.E.
,
Drenkow
,
J.
,
Bekiranov
,
S.
,
Strausberg
,
R.L.
,
Fodor
,
S.P.
et al.  (
2002
)
Large-scale transcriptional activity in chromosomes 21 and 22
.
Science
296
,
916
919
4
Okazaki
,
Y.
,
Furuno
,
M.
,
Kasukawa
,
T.
,
Adachi
,
J.
,
Bono
,
H.
,
Kondo
,
S.
et al.  (
2002
)
Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs
.
Nature
420
,
563
573
5
Bertone
,
P.
,
Stolc
,
V.
,
Royce
,
T.E.
,
Rozowsky
,
J.S.
,
Urban
,
A.E.
,
Zhu
,
X.
et al.  (
2004
)
Global identification of human transcribed sequences with genome tiling arrays
.
Science
306
,
2242
2246
6
Derrien
,
T.
,
Johnson
,
R.
,
Bussotti
,
G.
,
Tanzer
,
A.
,
Djebali
,
S.
,
Tilgner
,
H.
et al.  (
2012
)
The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression
.
Genome Res.
22
,
1775
1789
7
Mattick
,
J.S.
(
2005
)
The functional genomics of noncoding RNA
.
Science
309
,
1527
1528
8
Kapranov
,
P.
,
Cheng
,
J.
,
Dike
,
S.
,
Nix
,
D.A.
,
Duttagupta
,
R.
,
Willingham
,
A.T.
et al.  (
2007
)
RNA maps reveal new RNA classes and a possible function for pervasive transcription
.
Science
316
,
1484
1488
9
Guttman
,
M.
,
Amit
,
I.
,
Garber
,
M.
,
French
,
C.
,
Lin
,
M.F.
,
Feldser
,
D.
et al.  (
2009
)
Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals
.
Nature
458
,
223
227
10
Necsulea
,
A.
,
Soumillon
,
M.
,
Warnefors
,
M.
,
Liechti
,
A.
,
Daish
,
T.
,
Zeller
,
U.
et al.  (
2014
)
The evolution of lncRNA repertoires and expression patterns in tetrapods
.
Nature
505
,
635
640
11
Cabili
,
M.N.
,
Trapnell
,
C.
,
Goff
,
L.
,
Koziol
,
M.
,
Tazon-Vega
,
B.
,
Regev
,
A.
et al.  (
2011
)
Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses
.
Genes Dev.
25
,
1915
1927
12
Pervouchine
,
D.D.
,
Djebali
,
S.
,
Breschi
,
A.
,
Davis
,
C.A.
,
Barja
,
P.P.
,
Dobin
,
A.
et al.  (
2015
)
Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression
.
Nat. Commun.
6
,
5903
13
Pauli
,
A.
,
Valen
,
E.
,
Lin
,
M.F.
,
Garber
,
M.
,
Vastenhouw
,
N.L.
,
Levin
,
J.Z.
et al.  (
2012
)
Systematic identification of long noncoding RNAs expressed during zebrafish embryogenesis
.
Genome Res.
22
,
577
591
14
Young
,
R.S.
,
Marques
,
A.C.
,
Tibbit
,
C.
,
Haerty
,
W.
,
Bassett
,
A.R.
,
Liu
,
J.L.
et al.  (
2012
)
Identification and properties of 1,119 candidate lincRNA loci in the Drosophila melanogaster genome
.
Genome Biol. Evol.
4
,
427
442
15
Jayakodi
,
M.
,
Jung
,
J.W.
,
Park
,
D.
,
Ahn
,
Y.J.
,
Lee
,
S.C.
,
Shin
,
S.Y.
et al.  (
2015
)
Genome-wide characterization of long intergenic non-coding RNAs (lincRNAs) provides new insight into viral diseases in honey bees Apis cerana and Apis mellifera
.
BMC Genomics
16
,
680
16
Shields
,
E.J.
,
Sheng
,
L.
,
Weiner
,
A.K.
,
Garcia
,
B.A.
and
Bonasio
,
R.
(
2018
)
High-quality genome assemblies reveal long non-coding RNAs expressed in ant brains
.
Cell Rep.
23
,
3078
3090
17
Ariel
,
F.
,
Romero-Barrios
,
N.
,
Jégu
,
T.
,
Benhamed
,
M.
and
Crespi
,
M.
(
2015
)
Battles and hijacks: noncoding transcription in plants
.
Trends Plant Sci.
20
,
362
371
18
Chekanova
,
J.A.
(
2015
)
Long non-coding RNAs and their functions in plants
.
Curr. Opin. Plant Biol.
27
,
207
216
19
Yamashita
,
A.
,
Shichino
,
Y.
and
Yamamoto
,
M.
(
2016
)
The long non-coding RNA world in yeasts
.
Biochim. Biophys. Acta Gene Regul. Mech.
1859
,
147
154
20
Bartolomei
,
M.S.
,
Zemel
,
S.
and
Tilghman
,
S.M.
(
1991
)
Parental imprinting of the mouse H19 gene
.
Nature
351
,
153
155
21
Brannan
,
C.I.
,
Dees
,
E.C.
,
Ingram
,
R.S.
and
Tilghman
,
S.M.
(
1990
)
The product of the H19 gene may function as an RNA
.
Mol. Cell. Biol.
10
,
28
36
22
Galupa
,
R.
and
Heard
,
E.
(
2018
)
X-chromosome inactivation: a crossroads between chromosome architecture and gene regulation
.
Annu. Rev. Genet.
52
,
535
566
23
Sahakyan
,
A.
,
Yang
,
Y.
and
Plath
,
K.
(
2018
)
The role of Xist in X-chromosome dosage compensation
.
Trends Cell Biol.
28
,
999
1013
24
Brown
,
C.J.
,
Ballabio
,
A.
,
Rupert
,
J.L.
,
Lafreniere
,
R.G.
,
Grompe
,
M.
,
Tonlorenzi
,
R.
et al.  (
1991
)
A gene from the region of the human X inactivation centre is expressed exclusively from the inactive X chromosome
.
Nature
349
,
38
44
25
Brockdorff
,
N.
,
Ashworth
,
A.
,
Kay
,
G.F.
,
McCabe
,
V.M.
,
Norris
,
D.P.
,
Cooper
,
P.J.
et al.  (
1992
)
The product of the mouse Xist gene is a 15 kb inactive X-specific transcript containing no conserved ORF and located in the nucleus
.
Cell
71
,
515
526
26
Leucci
,
E.
,
Vendramin
,
R.
,
Spinazzi
,
M.
,
Laurette
,
P.
,
Fiers
,
M.
,
Wouters
,
J.
et al.  (
2016
)
Melanoma addiction to the long non-coding RNA SAMMSON
.
Nature
531
,
518
522
27
Hua
,
J.T.
,
Ahmed
,
M.
,
Guo
,
H.
,
Zhang
,
Y.
,
Chen
,
S.
,
Soares
,
F.
et al.  (
2018
)
Risk SNP-mediated promoter-enhancer switching drives prostate cancer through lncRNA PCAT19
.
Cell
174
,
564
575 e518
28
Castellanos-Rubio
,
A.
,
Fernandez-Jimenez
,
N.
,
Kratchmarov
,
R.
,
Luo
,
X.
,
Bhagat
,
G.
,
Green
,
P.H.
et al.  (
2016
)
A long noncoding RNA associated with susceptibility to celiac disease
.
Science
352
,
91
95
29
Lo Sardo
,
V.
,
Chubukov
,
P.
,
Ferguson
,
W.
,
Kumar
,
A.
,
Teng
,
E.L.
,
Duran
,
M.
et al.  (
2018
)
Unveiling the role of the most impactful cardiovascular risk locus through haplotype editing
.
Cell
175
,
1796
1810 e1720
30
Bonasio
,
R.
and
Shiekhattar
,
R.
(
2014
)
Regulation of transcription by long noncoding RNAs
.
Annu. Rev. Genet.
48
,
433
455
31
Deveson
,
I.W.
,
Hardwick
,
S.A.
,
Mercer
,
T.R.
and
Mattick
,
J.S.
(
2017
)
The dimensions, dynamics, and relevance of the mammalian noncoding transcriptome
.
Trends Genet.
33
,
464
478
32
Engreitz
,
J.M.
,
Ollikainen
,
N.
and
Guttman
,
M.
(
2016
)
Long non-coding RNAs: spatial amplifiers that control nuclear structure and gene expression
.
Nat. Rev. Mol. Cell Biol.
17
,
756
770
33
Kopp
,
F.
and
Mendell
,
J.T.
(
2018
)
Functional classification and experimental dissection of long noncoding RNAs
.
Cell
172
,
393
407
34
Rutenberg-Schoenberg
,
M.
,
Sexton
,
A.N.
and
Simon
,
M.D.
(
2016
)
The properties of long noncoding RNAs that regulate chromatin
.
Annu. Rev. Genomics Hum. Genet.
17
,
69
94
35
Ulitsky
,
I.
(
2016
)
Evolution to the rescue: using comparative genomics to understand long non-coding RNAs
.
Nat. Rev. Genet.
17
,
601
614
36
Quinn
,
J.J.
and
Chang
,
H.Y.
(
2016
)
Unique features of long non-coding RNA biogenesis and function
.
Nat. Rev. Genet.
17
,
47
62
37
Goff
,
L.A.
and
Rinn
,
J.L.
(
2015
)
Linking RNA biology to lncRNAs
.
Genome Res.
25
,
1456
1465
38
Yang
,
L.
,
Froberg
,
J.E.
and
Lee
,
J.T.
(
2014
)
Long noncoding RNAs: fresh perspectives into the RNA world
.
Trends Biochem. Sci.
39
,
35
43
39
Long
,
Y.
,
Wang
,
X.
,
Youmans
,
D.T.
and
Cech
,
T.R.
(
2017
)
How do lncRNAs regulate transcription?
Sci. Adv.
3
,
eaao2110
40
Guttman
,
M.
,
Donaghey
,
J.
,
Carey
,
B.W.
,
Garber
,
M.
,
Grenier
,
J.K.
,
Munson
,
G.
et al.  (
2011
)
lincRNAs act in the circuitry controlling pluripotency and differentiation
.
Nature
477
,
295
300
41
Khalil
,
A.M.
,
Guttman
,
M.
,
Huarte
,
M.
,
Garber
,
M.
,
Raj
,
A.
,
Rivea Morales
,
D.
et al.  (
2009
)
Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression
.
Proc. Natl Acad. Sci. U.S.A.
106
,
11667
11672
42
Lee
,
J.T.
(
2012
)
Epigenetic regulation by long noncoding RNAs
.
Science
338
,
1435
1439
43
Holoch
,
D.
and
Moazed
,
D.
(
2015
)
RNA-mediated epigenetic regulation of gene expression
.
Nat. Rev. Genet.
16
,
71
84
44
Romero-Barrios
,
N.
,
Legascue
,
M.F.
,
Benhamed
,
M.
,
Ariel
,
F.
and
Crespi
,
M.
(
2018
)
Splicing regulation by long noncoding RNAs
.
Nucleic Acids Res.
46
,
2169
2184
45
Mercer
,
T.R.
,
Dinger
,
M.E.
and
Mattick
,
J.S.
(
2009
)
Long non-coding RNAs: insights into functions
.
Nat. Rev. Genet.
10
,
155
159
46
Barry
,
G.
,
Briggs
,
J.A.
,
Vanichkina
,
D.P.
,
Poth
,
E.M.
,
Beveridge
,
N.J.
,
Ratnu
,
V.S.
et al.  (
2014
)
The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing
.
Mol. Psychiatry
19
,
486
494
47
Yoon
,
J.H.
,
Abdelmohsen
,
K.
and
Gorospe
,
M.
(
2013
)
Posttranscriptional gene regulation by long noncoding RNA
.
J. Mol. Biol.
425
,
3723
3730
48
Schmitt
,
A.M.
,
Garcia
,
J.T.
,
Hung
,
T.
,
Flynn
,
R.A.
,
Shen
,
Y.
,
Qu
,
K.
et al.  (
2016
)
An inducible long noncoding RNA amplifies DNA damage signaling
.
Nat. Genet.
48
,
1370
1376
49
Munschauer
,
M.
,
Nguyen
,
C.T.
,
Sirokman
,
K.
,
Hartigan
,
C.R.
,
Hogstrom
,
L.
,
Engreitz
,
J.M.
et al.  (
2018
)
The NORAD lncRNA assembles a topoisomerase complex critical for genome stability
.
Nature
561
,
132
136
50
Wang
,
K.C.
and
Chang
,
H.Y.
(
2011
)
Molecular mechanisms of long noncoding RNAs
.
Mol. Cell
43
,
904
914
51
Rinn
,
J.L.
,
Kertesz
,
M.
,
Wang
,
J.K.
,
Squazzo
,
S.L.
,
Xu
,
X.
,
Brugmann
,
S.A.
et al.  (
2007
)
Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs
.
Cell
129
,
1311
1323
52
Bonasio
,
R.
,
Tu
,
S.
and
Reinberg
,
D.
(
2010
)
Molecular signals of epigenetic states
.
Science
330
,
612
616
53
Hung
,
T.
and
Chang
,
H.Y.
(
2010
)
Long noncoding RNA in genome regulation: prospects and mechanisms
.
RNA Biol.
7
,
582
585
54
Li
,
Y.
,
Syed
,
J.
and
Sugiyama
,
H.
(
2016
)
RNA-DNA triplex formation by long noncoding RNAs
.
Cell Chem. Biol.
23
,
1325
1333
55
Roberts
,
R.W.
and
Crothers
,
D.M.
(
1992
)
Stability and properties of double and triple helices: dramatic effects of RNA or DNA backbone composition
.
Science
258
,
1463
1466
56
Martianov
,
I.
,
Ramadass
,
A.
,
Serra Barros
,
A.
,
Chow
,
N.
and
Akoulitchev
,
A.
(
2007
)
Repression of the human dihydrofolate reductase gene by a non-coding interfering transcript
.
Nature
445
,
666
670
57
Schmitz
,
K.M.
,
Mayer
,
C.
,
Postepska
,
A.
and
Grummt
,
I.
(
2010
)
Interaction of noncoding RNA with the rDNA promoter mediates recruitment of DNMT3b and silencing of rRNA genes
.
Genes Dev.
24
,
2264
2269
58
Zhao
,
Z.
,
Sentürk
,
N.
,
Song
,
C.
and
Grummt
,
I.
(
2018
)
lncRNA PAPAS tethered to the rDNA enhancer recruits hypophosphorylated CHD4/NuRD to repress rRNA synthesis at elevated temperatures
.
Genes Dev.
32
,
836
848
59
Grote
,
P.
and
Herrmann
,
B.G.
(
2013
)
The long non-coding RNA Fendrr links epigenetic control mechanisms to gene regulatory networks in mammalian embryogenesis
.
RNA Biol.
10
,
1579
1585
60
Grote
,
P.
,
Wittler
,
L.
,
Hendrix
,
D.
,
Koch
,
F.
,
Währisch
,
S.
,
Beisaw
,
A.
et al.  (
2013
)
The tissue-specific lncRNA Fendrr is an essential regulator of heart and body wall development in the mouse
.
Dev. Cell
24
,
206
214
61
Mondal
,
T.
,
Subhash
,
S.
,
Vaid
,
R.
,
Enroth
,
S.
,
Uday
,
S.
,
Reinius
,
B.
et al.  (
2015
)
MEG3 long noncoding RNA regulates the TGF-beta pathway genes through formation of RNA-DNA triplex structures
.
Nat. Commun.
6
,
7743
62
O'Leary
,
V.B.
,
Ovsepian
,
S.V.
,
Carrascosa
,
L.G.
,
Buske
,
F.A.
,
Radulovic
,
V.
,
Niyazi
,
M.
et al.  (
2015
)
PARTICLE, a triplex-forming long ncRNA, regulates locus-specific methylation in response to low-dose irradiation
.
Cell Rep.
11
,
474
485
63
Santos-Pereira
,
J.M.
and
Aguilera
,
A.
(
2015
)
R loops: new modulators of genome dynamics and function
.
Nat. Rev. Genet.
16
,
583
597
64
Balk
,
B.
,
Maicher
,
A.
,
Dees
,
M.
,
Klermund
,
J.
,
Luke-Glaser
,
S.
,
Bender
,
K.
et al.  (
2013
)
Telomeric RNA-DNA hybrids affect telomere-length dynamics and senescence
.
Nat. Struct. Mol. Biol.
20
,
1199
1205
65
Wahba
,
L.
,
Gore
,
S.K.
and
Koshland
,
D.
(
2013
)
The homologous recombination machinery modulates the formation of RNA-DNA hybrids and associated chromosome instability
.
eLife
2
,
e00505
66
Cloutier
,
S.C.
,
Wang
,
S.
,
Ma
,
W.K.
,
Al Husini
,
N.
,
Dhoondia
,
Z.
,
Ansari
,
A.
et al.  (
2016
)
Regulated formation of lncRNA-DNA hybrids enables faster transcriptional induction and environmental adaptation
.
Mol. Cell
61
,
393
404
67
Yan
,
Q.
,
Shields
,
E.J.
,
Bonasio
,
R.
and
Sarma
,
K.
(
2018
)
Mapping native R-loops genome-wide using a targeted nuclease approach
.
bioRxiv
,
457226
68
Dumelie
,
J.G.
and
Jaffrey
,
S.R.
(
2017
)
Defining the location of promoter-associated R-loops at near-nucleotide resolution using bisDRIP-seq
.
eLife
6
,
e28306
69
Sanz
,
L.A.
,
Hartono
,
S.R.
,
Lim
,
Y.W.
,
Steyaert
,
S.
,
Rajpurkar
,
A.
,
Ginno
,
P.A.
et al.  (
2016
)
Prevalent, dynamic, and conserved R-loop structures associate with specific epigenomic signatures in mammals
.
Mol. Cell
63
,
167
178
70
Chen
,
L.
,
Chen
,
J.Y.
,
Zhang
,
X.
,
Gu
,
Y.
,
Xiao
,
R.
,
Shao
,
C.
et al.  (
2017
)
R-ChIP using inactive RNase H reveals dynamic coupling of R-loops with transcriptional pausing at gene promoters
.
Mol. Cell
68
,
745
757 e745
71
Engreitz
,
J.M.
,
Pandya-Jones
,
A.
,
McDonel
,
P.
,
Shishkin
,
A.
,
Sirokman
,
K.
,
Surka
,
C.
et al.  (
2013
)
The Xist lncRNA exploits three-dimensional genome architecture to spread across the X chromosome
.
Science
341
,
1237973
72
Brockdorff
,
N.
(
2013
)
Noncoding RNA and Polycomb recruitment
.
RNA
19
,
429
442
73
Ringrose
,
L.
(
2017
)
Noncoding RNAs in polycomb and trithorax regulation: a quantitative perspective
.
Annu. Rev. Genet.
51
,
385
411
74
Portoso
,
M.
,
Ragazzini
,
R.
,
Brenčič
,
Z.
,
Moiani
,
A.
,
Michaud
,
A.
,
Vassilev
,
I.
et al.  (
2017
)
PRC2 is dispensable for HOTAIR-mediated transcriptional repression
.
EMBO J.
36
,
981
994
75
Amândio
,
A.R.
,
Necsulea
,
A.
,
Joye
,
E.
,
Mascrez
,
B.
and
Duboule
,
D.
(
2016
)
Hotair is dispensible for mouse development
.
PLoS Genet.
12
,
e1006232
76
Li
,
L.
,
Liu
,
B.
,
Wapinski
,
O.L.
,
Tsai
,
M.C.
,
Qu
,
K.
,
Zhang
,
J.
et al.  (
2013
)
Targeted disruption of Hotair leads to homeotic transformation and gene derepression
.
Cell Rep.
5
,
3
12
77
Li
,
L.
,
Helms
,
J.A.
and
Chang
,
H.Y.
(
2016
)
Comment on ‘hotair is dispensable for mouse development’
.
PLoS Genet.
12
,
e1006406
78
Selleri
,
L.
,
Bartolomei
,
M.S.
,
Bickmore
,
W.A.
,
He
,
L.
,
Stubbs
,
L.
,
Reik
,
W.
et al.  (
2016
)
A hox-embedded long noncoding RNA: is it all hot air?
PLoS Genet.
12
,
e1006485
79
Simon
,
J.A.
and
Kingston
,
R.E.
(
2009
)
Mechanisms of polycomb gene silencing: knowns and unknowns
.
Nat. Rev. Mol. Cell Biol.
10
,
697
708
80
Rosenberg
,
M.
,
Blum
,
R.
,
Kesner
,
B.
,
Maier
,
V.K.
,
Szanto
,
A.
and
Lee
,
J.T.
(
2017
)
Denaturing CLIP, dCLIP, pipeline identifies discrete RNA footprints on chromatin-associated proteins and reveals that CBX7 targets 3′ UTRs to regulate mRNA expression
.
Cell Syst.
5
,
368
385 e315
81
Beltran
,
M.
,
Yates
,
C.M.
,
Skalska
,
L.
,
Dawson
,
M.
,
Reis
,
F.P.
,
Viiri
,
K.
et al.  (
2016
)
The interaction of PRC2 with RNA or chromatin is mutually antagonistic
.
Genome Res.
26
,
896
907
82
Bonasio
,
R.
,
Lecona
,
E.
,
Narendra
,
V.
,
Voigt
,
P.
,
Parisi
,
F.
,
Kluger
,
Y.
et al.  (
2014
)
Interactions with RNA direct the Polycomb group protein SCML2 to chromatin where it represses target genes
.
eLife
3
,
e02637
83
Kaneko
,
S.
,
Bonasio
,
R.
,
Saldaña-Meyer
,
R.
,
Yoshida
,
T.
,
Son
,
J.
,
Nishino
,
K.
et al.  (
2014
)
Interactions between JARID2 and noncoding RNAs regulate PRC2 recruitment to chromatin
.
Mol. Cell
53
,
290
300
84
Kaneko
,
S.
,
Son
,
J.
,
Shen
,
S.S.
,
Reinberg
,
D.
and
Bonasio
,
R.
(
2013
)
PRC2 binds active promoters and contacts nascent RNAs in embryonic stem cells
.
Nat. Struct. Mol. Biol.
20
,
1258
1264
85
Davidovich
,
C.
,
Zheng
,
L.
,
Goodrich
,
K.J.
and
Cech
,
T.R.
(
2013
)
Promiscuous RNA binding by Polycomb repressive complex 2
.
Nat. Struct. Mol. Biol.
20
,
1250
1257
86
Cifuentes-Rojas
,
C.
,
Hernandez
,
A.J.
,
Sarma
,
K.
and
Lee
,
J.T.
(
2014
)
Regulatory interactions between RNA and polycomb repressive complex 2
.
Mol. Cell
55
,
171
185
87
Zhao
,
J.
,
Sun
,
B.K.
,
Erwin
,
J.A.
,
Song
,
J.J.
and
Lee
,
J.T.
(
2008
)
Polycomb proteins targeted by a short repeat RNA to the mouse X chromosome
.
Science
322
,
750
756
88
Heo
,
J.B.
and
Sung
,
S.
(
2011
)
Vernalization-mediated epigenetic silencing by a long intronic noncoding RNA
.
Science
331
,
76
79
89
Kim
,
D.H.
and
Sung
,
S.
(
2017
)
Vernalization-triggered intragenic chromatin loop formation by long noncoding RNAs
.
Dev. Cell
40
,
302
312 e304
90
Schuettengruber
,
B.
,
Bourbon
,
H.M.
,
Di Croce
,
L.
and
Cavalli
,
G.
(
2017
)
Genome regulation by polycomb and trithorax: 70 years and counting
.
Cell
171
,
34
57
91
Wang
,
K.C.
,
Yang
,
Y.W.
,
Liu
,
B.
,
Sanyal
,
A.
,
Corces-Zimmerman
,
R.
,
Chen
,
Y.
et al.  (
2011
)
A long noncoding RNA maintains active chromatin to coordinate homeotic gene expression
.
Nature
472
,
120
124
92
Yang
,
Y.W.
,
Flynn
,
R.A.
,
Chen
,
Y.
,
Qu
,
K.
,
Wan
,
B.
,
Wang
,
K.C.
et al.  (
2014
)
Essential role of lncRNA binding for WDR5 maintenance of active chromatin and embryonic stem cell pluripotency
.
eLife
3
,
e02046
93
Nagano
,
T.
,
Mitchell
,
J.A.
,
Sanz
,
L.A.
,
Pauler
,
F.M.
,
Ferguson-Smith
,
A.C.
,
Feil
,
R.
et al.  (
2008
)
The air noncoding RNA epigenetically silences transcription by targeting G9a to chromatin
.
Science
322
,
1717
1720
94
Pavlaki
,
I.
,
Alammari
,
F.
,
Sun
,
B.
,
Clark
,
N.
,
Sirey
,
T.
,
Lee
,
S.
et al.  (
2018
)
The long non-coding RNA Paupar promotes KAP1-dependent chromatin changes and regulates olfactory bulb neurogenesis
.
EMBO J.
37
,
e98219
95
Vance
,
K.W.
,
Sansom
,
S.N.
,
Lee
,
S.
,
Chalei
,
V.
,
Kong
,
L.
,
Cooper
,
S.E.
et al.  (
2014
)
The long non-coding RNA Paupar regulates the expression of both local and distal genes
.
EMBO J.
33
,
296
311
96
Di Ruscio
,
A.
,
Ebralidze
,
A.K.
,
Benoukraf
,
T.
,
Amabile
,
G.
,
Goff
,
L.A.
,
Terragni
,
J.
et al.  (
2013
)
DNMT1-interacting RNAs block gene-specific DNA methylation
.
Nature
503
,
371
376
97
Chalei
,
V.
,
Sansom
,
S.N.
,
Kong
,
L.
,
Lee
,
S.
,
Montiel
,
J.F.
,
Vance
,
K.W.
et al.  (
2014
)
The long non-coding RNA Dali is an epigenetic regulator of neural differentiation
.
eLife
3
,
e04530
98
Lee
,
J.T.
and
Bartolomei
,
M.S.
(
2013
)
X-inactivation, imprinting, and long noncoding RNAs in health and disease
.
Cell
152
,
1308
1323
99
Chakraborty
,
D.
,
Kappei
,
D.
,
Theis
,
M.
,
Nitzsche
,
A.
,
Ding
,
L.
,
Paszkowski-Rogacz
,
M.
et al.  (
2012
)
Combined RNAi and localization for functionally dissecting long noncoding RNAs
.
Nat. Methods
9
,
360
362
100
Chakraborty
,
D.
,
Paszkowski-Rogacz
,
M.
,
Berger
,
N.
,
Ding
,
L.
,
Mircetic
,
J.
,
Fu
,
J.
et al.  (
2017
)
lncRNA Panct1 maintains mouse embryonic stem cell identity by regulating TOBF1 recruitment to Oct-Sox sequences in early G1
.
Cell Rep.
21
,
3012
3021
101
Ng
,
S.Y.
,
Bogu
,
G.K.
,
Soh
,
B.S.
and
Stanton
,
L.W.
(
2013
)
The long noncoding RNA RMST interacts with SOX2 to regulate neurogenesis
.
Mol. Cell
51
,
349
359
102
Hung
,
T.
,
Wang
,
Y.
,
Lin
,
M.F.
,
Koegel
,
A.K.
,
Kotake
,
Y.
,
Grant
,
G.D.
et al.  (
2011
)
Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters
.
Nat. Genet.
43
,
621
629
103
G. Hendrickson
,
D.
,
Kelley
,
D.R.
,
Tenen
,
D.
,
Bernstein
,
B.
and
Rinn
,
J.L.
(
2016
)
Widespread RNA binding by chromatin-associated proteins
.
Genome Biol.
17
,
28
104
He
,
C.
,
Sidoli
,
S.
,
Warneford-Thomson
,
R.
,
Tatomer
,
D.C.
,
Wilusz
,
J.E.
,
Garcia
,
B.A.
et al.  (
2016
)
High-resolution mapping of RNA-binding regions in the nuclear proteome of embryonic stem cells
.
Mol. Cell
64
,
416
430
105
Samata
,
M.
and
Akhtar
,
A.
(
2018
)
Dosage compensation of the X chromosome: a complex epigenetic assignment involving chromatin regulators and long noncoding RNAs
.
Annu. Rev. Biochem.
87
,
323
350
106
Franke
,
A.
and
Baker
,
B.S.
(
1999
)
The rox1 and rox2 RNAs are essential components of the compensasome, which mediates dosage compensation in Drosophila
.
Mol. Cell
4
,
117
122
107
Figueiredo
,
M.L.
,
Kim
,
M.
,
Philip
,
P.
,
Allgardsson
,
A.
,
Stenberg
,
P.
and
Larsson
,
J.
(
2014
)
Non-coding roX RNAs prevent the binding of the MSL-complex to heterochromatic regions
.
PLoS Genet.
10
,
e1004865
108
Ilik
,
I.A.
,
Maticzka
,
D.
,
Georgiev
,
P.
,
Gutierrez
,
N.M.
,
Backofen
,
R.
and
Akhtar
,
A.
(
2017
)
A mutually exclusive stem-loop arrangement in roX2 RNA is essential for X-chromosome regulation in Drosophila
.
Genes Dev.
31
,
1973
1987
109
Ilik
,
I.A.
,
Quinn
,
J.J.
,
Georgiev
,
P.
,
Tavares-Cadete
,
F.
,
Maticzka
,
D.
,
Toscano
,
S.
et al.  (
2013
)
Tandem stem-loops in roX RNAs act together to mediate X chromosome dosage compensation in Drosophila
.
Mol. Cell
51
,
156
173
110
Tsai
,
M.C.
,
Manor
,
O.
,
Wan
,
Y.
,
Mosammaparast
,
N.
,
Wang
,
J.K.
,
Lan
,
F.
et al.  (
2010
)
Long noncoding RNA as modular scaffold of histone modification complexes
.
Science
329
,
689
693
111
Lee
,
S.
,
Kopp
,
F.
,
Chang
,
T.C.
,
Sataluri
,
A.
,
Chen
,
B.
,
Sivakumar
,
S.
et al.  (
2016
)
Noncoding RNA NORAD regulates genomic stability by sequestering PUMILIO proteins
.
Cell
164
,
69
80
112
Yamazaki
,
T.
,
Souquere
,
S.
,
Chujo
,
T.
,
Kobelke
,
S.
,
Chong
,
Y.S.
,
Fox
,
A.H.
et al.  (
2018
)
Functional domains of NEAT1 architectural lncRNA induce paraspeckle assembly through phase separation
.
Mol. Cell
70
,
1038
1053 e1037
113
Jiang
,
L.
,
Shao
,
C.
,
Wu
,
Q.J.
,
Chen
,
G.
,
Zhou
,
J.
,
Yang
,
B.
et al.  (
2017
)
NEAT1 scaffolds RNA-binding proteins and the microprocessor to globally enhance pri-miRNA processing
.
Nat. Struct. Mol. Biol.
24
,
816
824
114
Hu
,
W.L.
,
Jin
,
L.
,
Xu
,
A.
,
Wang
,
Y.F.
,
Thorne
,
R.F.
,
Zhang
,
X.D.
et al.  (
2018
)
GUARDIN is a p53-responsive long non-coding RNA that is essential for genomic stability
.
Nat. Cell Biol.
20
,
492
502
115
Spitale
,
R.C.
,
Tsai
,
M.C.
and
Chang
,
H.Y.
(
2011
)
RNA templating the epigenome: long noncoding RNAs as molecular scaffolds
.
Epigenetics
6
,
539
543
116
Mallam
,
A.L.
,
Sae-Lee
,
W.
,
Schaub
,
J.M.
,
Tu
,
F.
,
Battenhouse
,
A.
,
Jang
,
Y.J.
et al.  (
2018
)
Systematic discovery of endogenous human ribonucleoprotein complexes
.
bioRxiv
,
480061
117
Giorgetti
,
L.
,
Lajoie
,
B.R.
,
Carter
,
A.C.
,
Attia
,
M.
,
Zhan
,
Y.
,
Xu
,
J.
et al.  (
2016
)
Structural organization of the inactive X chromosome in the mouse
.
Nature
535
,
575
579
118
Splinter
,
E.
,
de Wit
,
E.
,
Nora
,
E.P.
,
Klous
,
P.
,
van de Werken
,
H.J.
,
Zhu
,
Y.
et al.  (
2011
)
The inactive X chromosome adopts a unique three-dimensional conformation that is dependent on Xist RNA
.
Genes Dev.
25
,
1371
1383
119
Chen
,
C.K.
,
Blanco
,
M.
,
Jackson
,
C.
,
Aznauryan
,
E.
,
Ollikainen
,
N.
,
Surka
,
C.
et al.  (
2016
)
Xist recruits the X chromosome to the nuclear lamina to enable chromosome-wide silencing
.
Science
354
,
468
472
120
McHugh
,
C.A.
,
Chen
,
C.K.
,
Chow
,
A.
,
Surka
,
C.F.
,
Tran
,
C.
,
McDonel
,
P.
et al.  (
2015
)
The Xist lncRNA interacts directly with SHARP to silence transcription through HDAC3
.
Nature
521
,
232
236
121
Minajigi
,
A.
,
Froberg
,
J.E.
,
Wei
,
C.
,
Sunwoo
,
H.
,
Kesner
,
B.
,
Colognori
,
D.
et al.  (
2015
)
Chromosomes. A comprehensive Xist interactome reveals cohesin repulsion and an RNA-directed chromosome conformation
.
Science
349
.
122
Lai
,
F.
,
Orom
,
U.A.
,
Cesaroni
,
M.
,
Beringer
,
M.
,
Taatjes
,
D.J.
,
Blobel
,
G.A.
et al.  (
2013
)
Activating RNAs associate with Mediator to enhance chromatin architecture and transcription
.
Nature
494
,
497
501
123
Werner
,
M.S.
and
Ruthenburg
,
A.J.
(
2015
)
Nuclear fractionation reveals thousands of chromatin-tethered noncoding RNAs adjacent to active genes
.
Cell Rep.
12
,
1089
1098
124
Werner
,
M.S.
,
Sullivan
,
M.A.
,
Shah
,
R.N.
,
Nadadur
,
R.D.
,
Grzybowski
,
A.T.
,
Galat
,
V.
et al.  (
2017
)
Chromatin-enriched lncRNAs can act as cell-type specific activators of proximal gene transcription
.
Nat. Struct. Mol. Biol.
24
,
596
603
125
Kim
,
T.K.
and
Shiekhattar
,
R.
(
2015
)
Architectural and functional commonalities between enhancers and promoters
.
Cell
162
,
948
959
126
Joung
,
J.
,
Engreitz
,
J.M.
,
Konermann
,
S.
,
Abudayyeh
,
O.O.
,
Verdine
,
V.K.
,
Aguet
,
F.
et al.  (
2017
)
Genome-scale activation screen identifies a lncRNA locus regulating a gene neighbourhood
.
Nature
548
,
343
346
127
Amaral
,
P.P.
,
Leonardi
,
T.
,
Han
,
N.
,
Viré
,
E.
,
Gascoigne
,
D.K.
,
Arias-Carrasco
,
R.
et al.  (
2018
)
Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci
.
Genome Biol.
19
,
32
128
Tan
,
J.Y.
,
Smith
,
A.A.T.
,
Ferreira da Silva
,
M.
,
Matthey-Doret
,
C.
,
Rueedi
,
R.
,
Sönmez
,
R.
et al.  (
2017
)
cis-acting complex-trait-associated lincRNA expression correlates with modulation of chromosomal architecture
.
Cell Rep.
18
,
2280
2288
129
Kagey
,
M.H.
,
Newman
,
J.J.
,
Bilodeau
,
S.
,
Zhan
,
Y.
,
Orlando
,
D.A.
,
van Berkum
,
N.L.
et al.  (
2010
)
Mediator and cohesin connect gene expression and chromatin architecture
.
Nature
467
,
430
435
130
Phillips
,
J.E.
and
Corces
,
V.G.
(
2009
)
CTCF: master weaver of the genome
.
Cell
137
,
1194
1211
131
Isoda
,
T.
,
Moore
,
A.J.
,
He
,
Z.
,
Chandra
,
V.
,
Aida
,
M.
,
Denholtz
,
M.
et al.  (
2017
)
Non-coding transcription instructs chromatin folding and compartmentalization to dictate enhancer-promoter communication and T cell fate
.
Cell
171
,
103
119 e118
132
Cajigas
,
I.
,
Chakraborty
,
A.
,
Swyter
,
K.R.
,
Luo
,
H.
,
Bastidas
,
M.
,
Nigro
,
M.
et al.  (
2018
)
The Evf2 ultraconserved enhancer lncRNA functionally and spatially organizes megabase distant genes in the developing forebrain
.
Mol. Cell
71
,
956
972 e959
133
Hacisuleyman
,
E.
,
Goff
,
L.A.
,
Trapnell
,
C.
,
Williams
,
A.
,
Henao-Mejia
,
J.
,
Sun
,
L.
et al.  (
2014
)
Topological organization of multichromosomal regions by the long intergenic noncoding RNA Firre
.
Nat. Struct. Mol. Biol.
21
,
198
206
134
Yang
,
F.
,
Deng
,
X.
,
Ma
,
W.
,
Berletch
,
J.B.
,
Rabaia
,
N.
,
Wei
,
G.
et al.  (
2015
)
The lncRNA Firre anchors the inactive X chromosome to the nucleolus by binding CTCF and maintains H3K27me3 methylation
.
Genome Biol.
16
,
52
135
Barutcu
,
A.R.
,
Maass
,
P.G.
,
Lewandowski
,
J.P.
,
Weiner
,
C.L.
and
Rinn
,
J.L.
(
2018
)
A TAD boundary is preserved upon deletion of the CTCF-rich Firre locus
.
Nat. Commun.
9
,
1444
136
Saldana-Meyer
,
R.
,
Gonzalez-Buendia
,
E.
,
Guerrero
,
G.
,
Narendra
,
V.
,
Bonasio
,
R.
,
Recillas-Targa
,
F.
et al.  (
2014
)
CTCF regulates the human p53 gene through direct interaction with its natural antisense transcript, Wrap53
.
Genes Dev.
28
,
723
734
137
Hansen
,
A.S.
,
Hsieh
,
T.-H.S.
,
Cattoglio
,
C.
,
Pustova
,
I.
,
Darzacq
,
X.
and
Tjian
,
R.
(
2018
)
An RNA-binding region regulates CTCF clustering and chromatin looping
.
bioRxiv
,
495432
138
Saldana-Meyer
,
R.
,
Rodriguez-Hernaez
,
J.
,
Nishana
,
M.
,
Jacome-Lopez
,
K.
,
Nora
,
E.P.
,
Bruneau
,
B.G.
et al.  (
2019
)
RNA interactions with CTCF are essential for its proper function
.
bioRxiv
,
530014
139
Shin
,
Y.
and
Brangwynne
,
C.P.
(
2017
)
Liquid phase condensation in cell physiology and disease
.
Science
357
,
eaaf4382
140
Molliex
,
A.
,
Temirov
,
J.
,
Lee
,
J.
,
Coughlin
,
M.
,
Kanagaraj
,
A.P.
,
Kim
,
H.J.
et al.  (
2015
)
Phase separation by low complexity domains promotes stress granule assembly and drives pathological fibrillization
.
Cell
163
,
123
133
141
Castello
,
A.
,
Fischer
,
B.
,
Frese
,
C.K.
,
Horos
,
R.
,
Alleaume
,
A.M.
,
Foehr
,
S.
et al.  (
2016
)
Comprehensive identification of RNA-binding domains in human cells
.
Mol. Cell
63
,
696
710
142
Castello
,
A.
,
Fischer
,
B.
,
Eichelbaum
,
K.
,
Horos
,
R.
,
Beckmann
,
B.M.
,
Strein
,
C.
et al.  (
2012
)
Insights into RNA biology from an atlas of mammalian mRNA-binding proteins
.
Cell
149
,
1393
1406
143
Fox
,
A.H.
,
Nakagawa
,
S.
,
Hirose
,
T.
and
Bond
,
C.S.
(
2018
)
Paraspeckles: where long noncoding RNA meets phase separation
.
Trends Biochem. Sci.
43
,
124
135
144
Uversky
,
V.N.
(
2017
)
Intrinsically disordered proteins in overcrowded milieu: membrane-less organelles, phase separation, and intrinsic disorder
.
Curr. Opin. Struct. Biol.
44
,
18
30
145
Hutchinson
,
J.N.
,
Ensminger
,
A.W.
,
Clemson
,
C.M.
,
Lynch
,
C.R.
,
Lawrence
,
J.B.
and
Chess
,
A.
(
2007
)
A screen for nuclear transcripts identifies two linked noncoding RNAs associated with SC35 splicing domains
.
BMC Genomics
8
,
39
146
Galganski
,
L.
,
Urbanek
,
M.O.
and
Krzyzosiak
,
W.J.
(
2017
)
Nuclear speckles: molecular organization, biological function and role in disease
.
Nucleic Acids Res.
45
,
10350
10368
147
Tripathi
,
V.
,
Ellis
,
J.D.
,
Shen
,
Z.
,
Song
,
D.Y.
,
Pan
,
Q.
,
Watt
,
A.T.
et al.  (
2010
)
The nuclear-retained noncoding RNA MALAT1 regulates alternative splicing by modulating SR splicing factor phosphorylation
.
Mol. Cell
39
,
925
938
148
Zhang
,
B.
,
Arun
,
G.
,
Mao
,
Y.S.
,
Lazar
,
Z.
,
Hung
,
G.
,
Bhattacharjee
,
G.
et al.  (
2012
)
The lncRNA Malat1 is dispensable for mouse development but its transcription plays a cis-regulatory role in the adult
.
Cell Rep.
2
,
111
123
149
Clemson
,
C.M.
,
Hutchinson
,
J.N.
,
Sara
,
S.A.
,
Ensminger
,
A.W.
,
Fox
,
A.H.
,
Chess
,
A.
et al.  (
2009
)
An architectural role for a nuclear noncoding RNA: NEAT1 RNA is essential for the structure of paraspeckles
.
Mol. Cell
33
,
717
726
150
Fox
,
A.H.
and
Lamond
,
A.I.
(
2010
)
Paraspeckles
.
Cold Spring Harb. Perspect. Biol.
2
,
a000687
151
West
,
J.A.
,
Davis
,
C.P.
,
Sunwoo
,
H.
,
Simon
,
M.D.
,
Sadreyev
,
R.I.
,
Wang
,
P.I.
et al.  (
2014
)
The long noncoding RNAs NEAT1 and MALAT1 bind active chromatin sites
.
Mol. Cell
55
,
791
802
152
Hnisz
,
D.
,
Shrinivas
,
K.
,
Young
,
R.A.
,
Chakraborty
,
A.K.
and
Sharp
,
P.A.
(
2017
)
A phase separation model for transcriptional control
.
Cell
169
,
13
23
153
Cerase
,
A.
,
Armaos
,
A.
,
Cid-Samper
,
F.
,
Avner
,
P.
and
Tartaglia
,
G.G.
(
2018
)
Xist lncRNA forms silencing granules that induce heterochromatin formation and repressive complexes recruitment by phase separation
.
bioRxiv
,
351015
154
Cabili
,
M.N.
,
Dunagin
,
M.C.
,
McClanahan
,
P.D.
,
Biaesch
,
A.
,
Padovan-Merhar
,
O.
,
Regev
,
A.
et al.  (
2015
)
Localization and abundance analysis of human lncRNAs at single-cell and single-molecule resolution
.
Genome Biol.
16
,
20
155
Lubelsky
,
Y.
and
Ulitsky
,
I.
(
2018
)
Sequences enriched in Alu repeats drive nuclear localization of long RNAs in human cells
.
Nature
555
,
107
111
156
Shukla
,
C.J.
,
McCorkindale
,
A.L.
,
Gerhardinger
,
C.
,
Korthauer
,
K.D.
,
Cabili
,
M.N.
,
Shechner
,
D.M.
et al.  (
2018
)
High-throughput identification of RNA nuclear enrichment sequences
.
EMBO J.
37
,
e98452
157
Mattick
,
J.S.
(
2003
)
Challenging the dogma: the hidden layer of non-protein-coding RNAs in complex organisms
.
Bioessays
25
,
930
939
158
Rinn
,
J.L.
and
Chang
,
H.Y.
(
2012
)
Genome regulation by long noncoding RNAs
.
Annu. Rev. Biochem.
81
,
145
166
159
Simon
,
M.D.
,
Wang
,
C.I.
,
Kharchenko
,
P.V.
,
West
,
J.A.
,
Chapman
,
B.A.
,
Alekseyenko
,
A.A.
et al.  (
2011
)
The genomic binding sites of a noncoding RNA
.
Proc. Natl Acad. Sci. U.S.A.
108
,
20497
20502
160
Chu
,
C.
,
Qu
,
K.
,
Zhong
,
F.L.
,
Artandi
,
S.E.
and
Chang
,
H.Y.
(
2011
)
Genomic maps of long noncoding RNA occupancy reveal principles of RNA-chromatin interactions
.
Mol. Cell
44
,
667
678
161
Simon
,
M.D.
(
2016
)
Insight into lncRNA biology using hybridization capture analyses
.
Biochim. Biophys. Acta
1859
,
121
127
162
Quinn
,
J.J.
,
Ilik
,
I.A.
,
Qu
,
K.
,
Georgiev
,
P.
,
Chu
,
C.
,
Akhtar
,
A.
et al.  (
2014
)
Revealing long noncoding RNA architecture and functions using domain-specific chromatin isolation by RNA purification
.
Nat. Biotechnol.
32
,
933
940
163
Simon
,
M.D.
,
Pinter
,
S.F.
,
Fang
,
R.
,
Sarma
,
K.
,
Rutenberg-Schoenberg
,
M.
,
Bowman
,
S.K.
et al.  (
2013
)
High-resolution Xist binding maps reveal two-step spreading during X-chromosome inactivation
.
Nature
504
,
465
469
164
Cheetham
,
S.W.
and
Brand
,
A.H.
(
2018
)
RNA-DamID reveals cell-type-specific binding of roX RNAs at chromatin-entry sites
.
Nat. Struct. Mol. Biol.
25
,
109
114
165
van Steensel
,
B.
and
Henikoff
,
S.
(
2000
)
Identification of in vivo DNA targets of chromatin proteins using tethered dam methyltransferase
.
Nat. Biotechnol.
18
,
424
428
166
Bell
,
J.C.
,
Jukam
,
D.
,
Teran
,
N.A.
,
Risca
,
V.I.
,
Smith
,
O.K.
,
Johnson
,
W.L.
et al.  (
2018
)
Chromatin-associated RNA sequencing (ChAR-seq) maps genome-wide RNA-to-DNA contacts
.
eLife
7
,
e27024
167
Li
,
X.
,
Zhou
,
B.
,
Chen
,
L.
,
Gou
,
L.T.
,
Li
,
H.
and
Fu
,
X.D.
(
2017
)
GRID-seq reveals the global RNA-chromatin interactome
.
Nat. Biotechnol.
35
,
940
950
168
Quinodoz
,
S.A.
,
Ollikainen
,
N.
,
Tabak
,
B.
,
Palla
,
A.
,
Schmidt
,
J.M.
,
Detmar
,
E.
et al.  (
2018
)
Higher-order inter-chromosomal hubs shape 3D genome organization in the nucleus
.
Cell
174
,
744
757 e724
169
Sridhar
,
B.
,
Rivas-Astroza
,
M.
,
Nguyen
,
T.C.
,
Chen
,
W.
,
Yan
,
Z.
,
Cao
,
X.
et al.  (
2017
)
Systematic mapping of RNA-chromatin interactions in vivo
.
Curr. Biol.
27
,
602
609
170
Gilbert
,
C.
,
Kristjuhan
,
A.
,
Winkler
,
G.S.
and
Svejstrup
,
J.Q.
(
2004
)
Elongator interactions with nascent mRNA revealed by RNA immunoprecipitation
.
Mol. Cell
14
,
457
464
171
Keene
,
J.D.
,
Komisarow
,
J.M.
and
Friedersdorf
,
M.B.
(
2006
)
RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts
.
Nat. Protoc.
1
,
302
307
172
Tenenbaum
,
S.A.
,
Carson
,
C.C.
,
Lager
,
P.J.
and
Keene
,
J.D.
(
2000
)
Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays
.
Proc. Natl Acad. Sci. U.S.A.
97
,
14085
14090
173
Zhao
,
J.
,
Ohsumi
,
T.K.
,
Kung
,
J.T.
,
Ogawa
,
Y.
,
Grau
,
D.J.
,
Sarma
,
K.
et al.  (
2010
)
Genome-wide identification of polycomb-associated RNAs by RIP-seq
.
Mol. Cell
40
,
939
953
174
Mili
,
S.
and
Steitz
,
J.A.
(
2004
)
Evidence for reassociation of RNA-binding proteins after cell lysis: implications for the interpretation of immunoprecipitation analyses
.
RNA
10
,
1692
1694
175
Licatalosi
,
D.D.
,
Mele
,
A.
,
Fak
,
J.J.
,
Ule
,
J.
,
Kayikci
,
M.
,
Chi
,
S.W.
et al.  (
2008
)
HITS-CLIP yields genome-wide insights into brain alternative RNA processing
.
Nature
456
,
464
469
176
Ule
,
J.
,
Jensen
,
K.B.
,
Ruggiu
,
M.
,
Mele
,
A.
,
Ule
,
A.
and
Darnell
,
R.B.
(
2003
)
CLIP identifies nova-regulated RNA networks in the brain
.
Science
302
,
1212
1215
177
Friedersdorf
,
M.B.
and
Keene
,
J.D.
(
2014
)
Advancing the functional utility of PAR-CLIP by quantifying background binding to mRNAs and lncRNAs
.
Genome Biol.
15
,
R2
178
König
,
J.
,
Zarnack
,
K.
,
Rot
,
G.
,
Curk
,
T.
,
Kayikci
,
M.
,
Zupan
,
B.
et al.  (
2010
)
iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution
.
Nat. Struct. Mol. Biol.
17
,
909
915
179
Van Nostrand
,
E.L.
,
Pratt
,
G.A.
,
Shishkin
,
A.A.
,
Gelboin-Burkhart
,
C.
,
Fang
,
M.Y.
,
Sundararaman
,
B.
et al.  (
2016
)
Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP)
.
Nat. Methods
13
,
508
514
180
Gu
,
J.
,
Wang
,
M.
,
Yang
,
Y.
,
Qiu
,
D.
,
Zhang
,
Y.
,
Ma
,
J.
et al.  (
2018
)
GoldCLIP: gel-omitted ligation-dependent CLIP
.
Genomics Proteomics Bioinformatics
16
,
136
143
181
Maticzka
,
D.
,
Ilik
,
I.A.
,
Aktas
,
T.
,
Backofen
,
R.
and
Akhtar
,
A.
(
2018
)
uvCLAP is a fast and non-radioactive method to identify in vivo targets of RNA-binding proteins
.
Nat. Commun.
9
,
1142
182
Aktaş
,
T.
,
Avşar Ilik
,
I.
,
Maticzka
,
D.
,
Bhardwaj
,
V.
,
Pessoa Rodrigues
,
C.
,
Mittler
,
G.
et al.  (
2017
)
DHX9 suppresses RNA processing defects originating from the Alu invasion of the human genome
.
Nature
544
,
115
119
183
Kim
,
D.I.
and
Roux
,
K.J.
(
2016
)
Filling the void: proximity-based labeling of proteins in living cells
.
Trends Cell Biol.
26
,
804
817
184
Beck
,
D.B.
,
Narendra
,
V.
,
Drury
, III,
W.J.
,
Casey
,
R.
,
Jansen
,
P.W.
,
Yuan
,
Z.F.
et al.  (
2014
)
In vivo proximity labeling for the detection of protein-protein and protein-RNA interactions
.
J Proteome Res.
13
,
6135
6143
185
Rhee
,
H.W.
,
Zou
,
P.
,
Udeshi
,
N.D.
,
Martell
,
J.D.
,
Mootha
,
V.K.
,
Carr
,
S.A.
et al.  (
2013
)
Proteomic mapping of mitochondria in living cells via spatially restricted enzymatic tagging
.
Science
339
,
1328
1331
186
Fazal
,
F.M.
,
Han
,
S.
,
Kaewsapsak
,
P.
,
Parker
,
K.R.
,
Xu
,
J.
,
Boettiger
,
A.N.
et al.  (
2018
)
Atlas of subcellular RNA localization revealed by APEX-seq
.
bioRxiv
,
454470
187
Padron
,
A.
,
Iwasaki
,
S.
and
Ingolia
,
N.
(
2018
)
Proximity RNA labeling by APEX-seq reveals the organization of translation initiation complexes and repressive RNA granules
.
bioRxiv
,
454066
188
Roux
,
K.J.
,
Kim
,
D.I.
,
Raida
,
M.
and
Burke
,
B.
(
2012
)
A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells
.
J. Cell Biol.
196
,
801
810
189
Ramanathan
,
M.
,
Majzoub
,
K.
,
Rao
,
D.S.
,
Neela
,
P.H.
,
Zarnegar
,
B.J.
,
Mondal
,
S.
et al.  (
2018
)
RNA-protein interaction detection in living cells
.
Nat. Methods
15
,
207
212
190
Chu
,
C.
,
Zhang
,
Q.C.
,
da Rocha
,
S.T.
,
Flynn
,
R.A.
,
Bharadwaj
,
M.
,
Calabrese
,
J.M.
et al.  (
2015
)
Systematic discovery of Xist RNA binding proteins
.
Cell
161
,
404
416
191
Baltz
,
A.G.
,
Munschauer
,
M.
,
Schwanhäusser
,
B.
,
Vasile
,
A.
,
Murakawa
,
Y.
,
Schueler
,
M.
et al.  (
2012
)
The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts
.
Mol. Cell
46
,
674
690
192
Beckmann
,
B.M.
,
Horos
,
R.
,
Fischer
,
B.
,
Castello
,
A.
,
Eichelbaum
,
K.
,
Alleaume
,
A.M.
et al.  (
2015
)
The RNA-binding proteomes from yeast to man harbour conserved enigmRBPs
.
Nat. Commun.
6
,
10127
193
Conrad
,
T.
,
Albrecht
,
A.S.
,
de Melo Costa
,
V.R.
,
Sauer
,
S.
,
Meierhofer
,
D.
and
Ørom
,
U.A.
(
2016
)
Serial interactome capture of the human cell nucleus
.
Nat. Commun.
7
,
11212
194
Bao
,
X.
,
Guo
,
X.
,
Yin
,
M.
,
Tariq
,
M.
,
Lai
,
Y.
,
Kanwal
,
S.
et al.  (
2018
)
Capturing the interactome of newly transcribed RNA
.
Nat. Methods
15
,
213
220
195
Huang
,
R.
,
Han
,
M.
,
Meng
,
L.
and
Chen
,
X.
(
2018
)
Transcriptome-wide discovery of coding and noncoding RNA-binding proteins
.
Proc. Natl Acad. Sci. U.S.A.
115
,
E3879
E3887
196
Trendel
,
J.
,
Schwarzl
,
T.
,
Horos
,
R.
,
Prakash
,
A.
,
Bateman
,
A.
,
Hentze
,
M.W.
et al.  (
2019
)
The human RNA-binding proteome and its dynamics during translational arrest
.
Cell
176
,
391
403 e19
197
Lunde
,
B.M.
,
Moore
,
C.
and
Varani
,
G.
(
2007
)
RNA-binding proteins: modular design for efficient function
.
Nat. Rev. Mol. Cell Biol.
8
,
479
490
198
Zhang
,
Q.
,
McKenzie
,
N.J.
,
Warneford-Thomson
,
R.
,
Gail
,
E.H.
,
Flanigan
,
S.F.
,
Owen
,
B.M.
et al.  (
2019
)
RNA exploits an exposed regulatory site to inhibit the enzymatic activity of PRC2
.
Nat. Struct. Mol. Biol.
26
,
237
247
199
Engreitz
,
J.M.
,
Sirokman
,
K.
,
McDonel
,
P.
,
Shishkin
,
A.A.
,
Surka
,
C.
,
Russell
,
P.
et al.  (
2014
)
RNA–RNA interactions enable specific targeting of noncoding RNAs to nascent pre-mRNAs and chromatin sites
.
Cell
159
,
188
199
200
Helwak
,
A.
,
Kudla
,
G.
,
Dudnakova
,
T.
and
Tollervey
,
D.
(
2013
)
Mapping the human miRNA interactome by CLASH reveals frequent noncanonical binding
.
Cell
153
,
654
665
201
Lu
,
Z.
,
Zhang
,
Q.C.
,
Lee
,
B.
,
Flynn
,
R.A.
,
Smith
,
M.A.
,
Robinson
,
J.T.
et al.  (
2016
)
RNA duplex map in living cells reveals higher-order transcriptome structure
.
Cell
165
,
1267
1279
202
Sharma
,
E.
,
Sterne-Weiler
,
T.
,
O'Hanlon
,
D.
and
Blencowe
,
B.J.
(
2016
)
Global mapping of human RNA-RNA interactions
.
Mol. Cell
62
,
618
626
203
Ziv
,
O.
,
Gabryelska
,
M.M.
,
Lun
,
A.T.L.
,
Gebert
,
L.F.R.
,
Sheu-Gruttadauria
,
J.
,
Meredith
,
L.W.
et al.  (
2018
)
COMRADES determines in vivo RNA structures and interactions
.
Nat. Methods
15
,
785
788
204
Engreitz
,
J.M.
,
Haines
,
J.E.
,
Perez
,
E.M.
,
Munson
,
G.
,
Chen
,
J.
,
Kane
,
M.
et al.  (
2016
)
Local regulation of gene expression by lncRNA promoters, transcription and splicing
.
Nature
539
,
452
455
205
Shalem
,
O.
,
Sanjana
,
N.E.
and
Zhang
,
F.
(
2015
)
High-throughput functional genomics using CRISPR-Cas9
.
Nat. Rev. Genet.
16
,
299
311
206
Qi
,
L.S.
,
Larson
,
M.H.
,
Gilbert
,
L.A.
,
Doudna
,
J.A.
,
Weissman
,
J.S.
,
Arkin
,
A.P.
et al.  (
2013
)
Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression
.
Cell
152
,
1173
1183
207
Liu
,
S.J.
,
Horlbeck
,
M.A.
,
Cho
,
S.W.
,
Birk
,
H.S.
,
Malatesta
,
M.
,
He
,
D.
et al.  (
2017
)
CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells
.
Science
355
,
aah7111
208
Zhu
,
S.
,
Li
,
W.
,
Liu
,
J.
,
Chen
,
C.H.
,
Liao
,
Q.
,
Xu
,
P.
et al.  (
2016
)
Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR-Cas9 library
.
Nat. Biotechnol.
34
,
1279
1286
209
Koirala
,
P.
,
Huang
,
J.
,
Ho
,
T.T.
,
Wu
,
F.
,
Ding
,
X.
and
Mo
,
Y.Y.
(
2017
)
LncRNA AK023948 is a positive regulator of AKT
.
Nat. Commun.
8
,
14422
210
Bester
,
A.C.
,
Lee
,
J.D.
,
Chavez
,
A.
,
Lee
,
Y.R.
,
Nachmani
,
D.
,
Vora
,
S.
et al.  (
2018
)
An integrated genome-wide CRISPRa approach to functionalize lncRNAs in drug resistance
.
Cell
173
,
649
664 e620
211
Hezroni
,
H.
,
Koppstein
,
D.
,
Schwartz
,
M.G.
,
Avrutin
,
A.
,
Bartel
,
D.P.
and
Ulitsky
,
I.
(
2015
)
Principles of long noncoding RNA evolution derived from direct comparison of transcriptomes in 17 species
.
Cell Rep.
11
,
1110
1122
212
Kirk
,
J.M.
,
Kim
,
S.O.
,
Inoue
,
K.
,
Smola
,
M.J.
,
Lee
,
D.M.
,
Schertzer
,
M.D.
et al.  (
2018
)
Functional classification of long non-coding RNAs by k-mer content
.
Nat. Genet.
50
,
1474
1482
213
Mukherjee
,
N.
,
Calviello
,
L.
,
Hirsekorn
,
A.
,
de Pretis
,
S.
,
Pelizzola
,
M.
and
Ohler
,
U.
(
2017
)
Integrative classification of human coding and noncoding genes through RNA metabolism profiles
.
Nat. Struct. Mol. Biol.
24
,
86
96
214
Kim
,
D.H.
,
Marinov
,
G.K.
,
Pepke
,
S.
,
Singer
,
Z.S.
,
He
,
P.
,
Williams
,
B.
et al.  (
2015
)
Single-cell transcriptome analysis reveals dynamic changes in lncRNA expression during reprogramming
.
Cell Stem Cell
16
,
88
101
215
Xie
,
T.
,
Wang
,
Y.
,
Deng
,
N.
,
Huang
,
G.
,
Taghavifar
,
F.
,
Geng
,
Y.
et al.  (
2018
)
Single-cell deconvolution of fibroblast heterogeneity in mouse pulmonary fibrosis
.
Cell Rep.
22
,
3625
3640
216
Davie
,
K.
,
Janssens
,
J.
,
Koldere
,
D.
,
De Waegeneer
,
M.
,
Pech
,
U.
,
Kreft
,
L.
et al.  (
2018
)
A single-cell transcriptome atlas of the aging Drosophila brain
.
Cell
174
,
982
998.e20
217
Forouzmand
,
E.
,
Owens
,
N.D.L.
,
Blitz
,
I.L.
,
Paraiso
,
K.D.
,
Khokha
,
M.K.
,
Gilchrist
,
M.J.
et al.  (
2017
)
Developmentally regulated long non-coding RNAs in Xenopus tropicalis
.
Dev. Biol.
426
,
401
408
218
Bonasio
,
R.
,
Zhang
,
G.
,
Ye
,
C.
,
Mutti
,
N.S.
,
Fang
,
X.
,
Qin
,
N.
et al.  (
2010
)
Genomic comparison of the ants Camponotus floridanus and Harpegnathos saltator
.
Science
329
,
1068
1071
219
Gospocic
,
J.
,
Shields
,
E.J.
,
Glastad
,
K.M.
,
Lin
,
Y.
,
Penick
,
C.A.
,
Yan
,
H.
et al.  (
2017
)
The neuropeptide corazonin controls social behavior and caste identity in ants
.
Cell
170
,
748
759 e712
220
Yan
,
H.
,
Opachaloemphan
,
C.
,
Mancini
,
G.
,
Yang
,
H.
,
Gallitto
,
M.
,
Mlejnek
,
J.
et al.  (
2017
)
An engineered orco mutation produces aberrant social behavior and defective neural development in ants
.
Cell
170
,
736
747 e739
221
Roundtree
,
I.A.
,
Evans
,
M.E.
,
Pan
,
T.
and
He
,
C.
(
2017
)
Dynamic RNA modifications in gene expression regulation
.
Cell
169
,
1187
1200
222
Patil
,
D.P.
,
Chen
,
C.K.
,
Pickering
,
B.F.
,
Chow
,
A.
,
Jackson
,
C.
,
Guttman
,
M.
et al.  (
2016
)
m6A RNA methylation promotes XIST-mediated transcriptional repression
.
Nature
537
,
369
373
223
Huarte
,
M.
(
2015
)
The emerging role of lncRNAs in cancer
.
Nat. Med.
21
,
1253
1261
224
Meng
,
L.
,
Ward
,
A.J.
,
Chun
,
S.
,
Bennett
,
C.F.
,
Beaudet
,
A.L.
and
Rigo
,
F.
(
2015
)
Towards a therapy for angelman syndrome by targeting a long non-coding RNA
.
Nature
518
,
409
412
225
Broadbent
,
K.M.
,
Park
,
D.
,
Wolf
,
A.R.
,
Van Tyne
,
D.
,
Sims
,
J.S.
,
Ribacke
,
U.
et al.  (
2011
)
A global transcriptional analysis of plasmodium falciparum malaria reveals a novel family of telomere-associated lncRNAs
.
Genome Biol.
12
,
R56
226
Calderwood
,
M.S.
,
Gannoun-Zaki
,
L.
,
Wellems
,
T.E.
and
Deitsch
,
K.W.
(
2003
)
Plasmodium falciparum var genes are regulated by two regions with separate promoters, one upstream of the coding region and a second within the intron
.
J. Biol. Chem.
278
,
34125
34132
227
Epp
,
C.
,
Li
,
F.
,
Howitt
,
C.A.
,
Chookajorn
,
T.
and
Deitsch
,
K.W.
(
2009
)
Chromatin associated sense and antisense noncoding RNAs are transcribed from the var gene family of virulence genes of the malaria parasite Plasmodium falciparum
.
RNA
15
,
116
127
228
Jenkins
,
A.M.
,
Waterhouse
,
R.M.
and
Muskavitch
,
M.A.
(
2015
)
Long non-coding RNA discovery across the genus anopheles reveals conserved secondary structures within and beyond the Gambiae complex
.
BMC Genomics
16
,
337
229
Menard
,
K.L.
,
Haskins
,
B.E.
,
Colombo
,
A.P.
and
Denkers
,
E.Y.
(
2018
)
Toxoplasma gondii manipulates expression of host long noncoding RNA during intracellular infection
.
Sci. Rep.
8
,
15017