RNA, Action through Interactions

Nguyen, Tri C.; Zaleta-Rivera, Kathia; Huang, Xuerui; Dai, Xiaofeng; Zhong, Sheng

doi:10.1016/j.tig.2018.08.001

Cited by 36 publications

(35 citation statements)

References 91 publications

(145 reference statements)

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“…We anticipate that more biologically relevant RNA dimers and multimers will be discovered with the advent of novel crosslinking and RNA-seq-based methods to map RNA-RNA interactions genome wide in vivo [ 17 , 213 , 214 , 215 ]. For instance, transfer RNA fragments (tRFs) were recently shown to form homodimers that increase their stability against nucleases [ 216 ], while other G-rich tRFs form tetramers by forming G-quadruplexes [ 217 ].…”

Section: Discussionmentioning

confidence: 99%

“…For instance, many unmodified tRNAs exhibit strong tendencies to dimerize and oligomerize and require a “snap-cool” procedure to refold into monomers [ 14 ]. However, the view that RNA oligomers are largely refolding artifacts is rapidly changing due to the recent recognition that multivalent, intermolecular RNA-RNA contacts can induce functional RNA oligomerization, condensation, phase separation or formation of ribonucleoprotein (RNP) granules that critically regulate cellular metabolism and cell fate [ 8 , 15 , 16 , 17 , 18 , 19 ]. These recent findings accentuate the importance and previously underappreciated role of RNA multimerization in biology.…”

Section: Introductionmentioning

confidence: 99%

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Structural Insights into RNA Dimerization: Motifs, Interfaces and Functions

Bou‐Nader

Zhang

2020

Molecules

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In comparison with the pervasive use of protein dimers and multimers in all domains of life, functional RNA oligomers have so far rarely been observed in nature. Their diminished occurrence contrasts starkly with the robust intrinsic potential of RNA to multimerize through long-range base-pairing (“kissing”) interactions, self-annealing of palindromic or complementary sequences, and stable tertiary contact motifs, such as the GNRA tetraloop-receptors. To explore the general mechanics of RNA dimerization, we performed a meta-analysis of a collection of exemplary RNA homodimer structures consisting of viral genomic elements, ribozymes, riboswitches, etc., encompassing both functional and fortuitous dimers. Globally, we found that domain-swapped dimers and antiparallel, head-to-tail arrangements are predominant architectural themes. Locally, we observed that the same structural motifs, interfaces and forces that enable tertiary RNA folding also drive their higher-order assemblies. These feature prominently long-range kissing loops, pseudoknots, reciprocal base intercalations and A-minor interactions. We postulate that the scarcity of functional RNA multimers and limited diversity in multimerization motifs may reflect evolutionary constraints imposed by host antiviral immune surveillance and stress sensing. A deepening mechanistic understanding of RNA multimerization is expected to facilitate investigations into RNA and RNP assemblies, condensates, and granules and enable their potential therapeutical targeting.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structural Insights into RNA Dimerization: Motifs, Interfaces and Functions

Bou‐Nader

Zhang

2020

Molecules

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“…In addition, our method can be further modified to identify other types of potentially interesting HIMs in heterogeneous networks by replacing the 4-node motif M with relevant motifs, especially when additional types of interactomes are included. For example, in addition to considering chromatin interactions and protein-DNA interactions as we did in this work, it would be of interest to incorporate other types of relevant interactomes in the nucleus, such as the RNA-chromatin interactome (Nguyen et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome

Tian

Zhang

et al. 2019

Preprint

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The composition of the cell nucleus is highly heterogeneous, with different constituents forming complex interactomes. However, the global patterns of these interwoven heterogeneous interactomes remain poorly understood. Here we focus on two different interactomes, chromatin interaction network and gene regulatory network, as a proof-of-principle, to identify heterogeneous interactome modules (HIMs) in the nucleus. Each HIM represents a cluster of gene loci that are in spatial contact more frequently than expected and that are regulated by the same group of transcription factor proteins. We develop a new algorithm MOCHI to facilitate the discovery of HIMs based on network motif clustering in heterogeneous interactomes. By applying MOCHI to five different cell types, we found that HIMs have strong spatial preference within the nucleus and exhibit distinct functional properties. Through integrative analysis, this work demonstrates the utility of MOCHI to identify HIMs, which may provide new perspectives on 3D genome organization and function. co-regulated genes in GRN can be facilitated by long-range chromosomal interactions (Fanucchi et al., 2013) and chromatin interactome has been shown to exhibit strong correlations with GRN (Kosak et al., 2007;Neems et al., 2016). Indeed, network-based representation of both chromatin interactome and GRN has been suggested to consider different subnuclear components holistically (Rajapakse et al., 2010;Chen et al., 2015). The paradigm of viewing the nucleus as a collection of interacting networks among various constituents can potentially be extended to account for other types of related interactomes in the nucleus. However, whether these interactomes, in particular chromatin interactome and GRN, are organized to form functionally relevant, global patterns remains unknown.In this work, as a proof-of-principle, we specifically consider two different types of interactomes in the nucleus: (1) chromatin interactome -a network of chromosomal interactions between different genomic loci -and (2) a GRN where TF proteins bind to the genomic loci to regulate target genes' transcription. Many studies in the past have analyzed the structure and dynamics of chromatin interactomes and GRNs as well as the coordinated binding of transcription factors on folded chromatin (Rao et al., 2014;Tang et al., 2015;Marbach et al., 2016;Ma et al., 2018;Cortini and Filion, 2018). However, the global network level patterns between chromatin interactome and GRN are still unclear, and algorithms that can simultaneously analyze these heterogeneous networks in the nucleus to discover important network structures have not been developed.Here we aim to identify mesoscale network structures where nodes of TFs (from GRN) and gene loci (from both chromatin interactome and GRN) cooperatively form distinct types of modules (i.e., clusters). We develop a new algorithm, MOCHI (MOtif Clustering in Heterogeneous Interactomes), that can effectively uncover such network modules, which we call heterogeneous interactome mod...

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“…Chromatin-associated RNAs (caRNAs) are proposed to be a layer of the epigenome 1 . Interactions of caRNA with chromatin are essential for diverse molecular and cellular functions, including X chromosome silencing 2 , anchoring nucleolus-chromosome interactions 3 , homology-directed repair of telomeres 4 , and RNA-mediated epigenetic inheritance 5 .…”

Section: Introductionmentioning

confidence: 99%

Mapping RNA–chromatin interactions by sequencing with iMARGI

Yan

Nguyen

et al. 2019

Nat Protoc

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RNA-chromatin interactions represent an important aspect of transcriptional regulation of genes and transposable elements. However, analyses of chromatin-associated RNAs (caRNA) are often limited to one caRNA at a time. Here, we describe the iMARGI (in situ Mapping of RNA-Genome jnteractome) technique used to discover caRNAs and reveal their respective genomic interaction loci. iMARGI starts with in situ crosslinking and genome fragmentation, followed by converting each proximal RNA-DNA pair into an RNA-linker-DNA chimeric sequence. These chimeric sequences are subsequently converted into a sequencing library suitable for paired-end sequencing. A standardized bioinformatic software package called iMARGI-Docker is provided to decode the paired-end sequencing data into caRNA-DNA interactions (https://sysbio.ucsd.edu/ imargi_pipeline). Compared to its predecessor MARGI, in iMARGI the number of input cells is 3-5 million, which is reduced by 100-fold, experimental time is reduced, and clear checkpoints have been established. It takes a few hours a day and a total of 8 days to complete the construction of an iMARGI sequencing library and one day to carry out data processing with iMARGI-Docker.

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RNA, Action through Interactions

Cited by 36 publications

References 91 publications

Structural Insights into RNA Dimerization: Motifs, Interfaces and Functions

Structural Insights into RNA Dimerization: Motifs, Interfaces and Functions

MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome

Mapping RNA–chromatin interactions by sequencing with iMARGI

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