Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2019 Apr 10;476(7):1083-1104.
doi: 10.1042/BCJ20180440.

lncRedibly versatile: biochemical and biological functions of long noncoding RNAs

Emily J Shields  1   2 , Ana F Petracovici  1   3 , Roberto Bonasio  4   5
Affiliations
Review

lncRedibly versatile: biochemical and biological functions of long noncoding RNAs

Emily J Shields et al. Biochem J. .

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.

Keywords: RNA-binding proteins; chromatin; epigenetics; gene expression and regulation; large intervening noncoding RNA.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.. Biochemical functions of lncRNAs.
(A) Some lncRNAs form RNA/DNA 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) A number of 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 distribution of these proteins. NEAT1 acts as a scaffold to bring together members of the RNA production and processing machinery in paraspeckles.
Figure 2.
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 crosslinking and biotinylated probes to capture a candidate lncRNA crosslinked 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 a E. coli adenine methyltransferase (Dam) fused to the MS2 coat protein. 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, GRIDseq, and CHARseq (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 crosslinked 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 crosslink RNA to protein, use biotinylated probes to capture target lncRNA-protein complexes, and digest with RNase to release bound proteins for mass spectrometry; 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 crosslink RNA to protein in live cells in the presence of 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 crosslinked peptides that can be analyzed by MS (bottom).
Figure 3.
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 to 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 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.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Cech TR and Steitz JA (2014) The Noncoding RNA Revolution-Trashing Old Rules to Forge New Ones. Cell. 157, 77–94 - PubMed
    1. Consortium EP (2012) An integrated encyclopedia of DNA elements in the human genome. Nature. 489, 57–74 - PMC - PubMed
    1. Kapranov P, Cawley SE, Drenkow J, Bekiranov S, Strausberg RL, Fodor SP and Gingeras TR (2002) Large-scale transcriptional activity in chromosomes 21 and 22. Science. 296, 916–919 - PubMed
    1. Okazaki Y, Furuno M, Kasukawa T, Adachi J, Bono H, Kondo S, Nikaido I, Osato N, Saito R, Suzuki H, Yamanaka I, Kiyosawa H, Yagi K, Tomaru Y, Hasegawa Y, Nogami A, Schonbach C, Gojobori T, Baldarelli R, Hill DP, Bult C, Hume DA, Quackenbush J, Schriml LM, Kanapin A, Matsuda H, Batalov S, Beisel KW, Blake JA, Bradt D, Brusic V, Chothia C, Corbani LE, Cousins S, Dalla E, Dragani TA, Fletcher CF, Forrest A, Frazer KS, Gaasterland T, Gariboldi M, Gissi C, Godzik A, Gough J, Grimmond S, Gustincich S, Hirokawa N, Jackson IJ, Jarvis ED, Kanai A, Kawaji H, Kawasawa Y, Kedzierski RM, King BL, Konagaya A, Kurochkin IV, Lee Y, Lenhard B, Lyons PA, Maglott DR, Maltais L, Marchionni L, McKenzie L, Miki H, Nagashima T, Numata K, Okido T, Pavan WJ, Pertea G, Pesole G, Petrovsky N, Pillai R, Pontius JU, Qi D, Ramachandran S, Ravasi T, Reed JC, Reed DJ, Reid J, Ring BZ, Ringwald M, Sandelin A, Schneider C, Semple CA, Setou M, Shimada K, Sultana R, Takenaka Y, Taylor MS, Teasdale RD, Tomita M, Verardo R, Wagner L, Wahlestedt C, Wang Y, Watanabe Y, Wells C, Wilming LG, Wynshaw-Boris A, Yanagisawa M, Yang I, Yang L, Yuan Z, Zavolan M, Zhu Y, Zimmer A, Carninci P, Hayatsu N, Hirozane-Kishikawa T, Konno H, Nakamura M, Sakazume N, Sato K, Shiraki T, Waki K, Kawai J, Aizawa K, Arakawa T, Fukuda S, Hara A, Hashizume W, Imotani K, Ishii Y, Itoh M, Kagawa I, Miyazaki A, Sakai K, Sasaki D, Shibata K, Shinagawa A, Yasunishi A, Yoshino M, Waterston R, Lander ES, Rogers J, Birney E, Hayashizaki Y, Consortium, F., I, R. G. E. R. G. P. and Team, I. I. (2002) Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature. 420, 563–573 - PubMed
    1. Bertone P, Stolc V, Royce TE, Rozowsky JS, Urban AE, Zhu X, Rinn JL, Tongprasit W, Samanta M, Weissman S, Gerstein M and Snyder M (2004) Global identification of human transcribed sequences with genome tiling arrays. Science. 306, 2242–2246 - PubMed

Publication types