Literature DB >> 24795650

Recent advances in the involvement of long non-coding RNAs in neural stem cell biology and brain pathophysiology.

Daphne Antoniou1, Athanasios Stergiopoulos1, Panagiotis K Politis1.   

Abstract

Exploration of non-coding genome has recently uncovered a growing list of formerly unknown regulatory long non-coding RNAs (lncRNAs) with important functions in stem cell pluripotency, development and homeostasis of several tissues. Although thousands of lncRNAs are expressed in mammalian brain in a highly patterned manner, their roles in brain development have just begun to emerge. Recent data suggest key roles for these molecules in gene regulatory networks controlling neuronal and glial cell differentiation. Analysis of the genomic distribution of genes encoding for lncRNAs indicates a physical association of these regulatory RNAs with transcription factors (TFs) with well-established roles in neural differentiation, suggesting that lncRNAs and TFs may form coherent regulatory networks with important functions in neural stem cells (NSCs). Additionally, many studies show that lncRNAs are involved in the pathophysiology of brain-related diseases/disorders. Here we discuss these observations and investigate the links between lncRNAs, brain development and brain-related diseases. Understanding the functions of lncRNAs in NSCs and brain organogenesis could revolutionize the basic principles of developmental biology and neuroscience.

Entities:  

Keywords:  brain-related diseases; gene regulatory networks; gliogenesis; neural differentiation; neurogenesis; non-coding genome; regulatory RNAs

Year:  2014        PMID: 24795650      PMCID: PMC4001054          DOI: 10.3389/fphys.2014.00155

Source DB:  PubMed          Journal:  Front Physiol        ISSN: 1664-042X            Impact factor:   4.566


Introduction

A long standing question in biological sciences is how cell diversity, specification patterns, and tissue complexity are generated during organ development. The mammalian brain is the most complex organ of any living organism. The question of how this enormous complexity is generated is still open. Such complexity is the result of millions of years of evolution that have equipped neural stem/progenitor cells (NSCs/NPCs) in the embryo with the ability to generate every neuron and glial cell in the brain via a combined action of extrinsic morphogenetic cues and intrinsic gene regulatory networks. For long time, it was thought that these networks are mainly based on cross-regulatory interactions between transcription factors (TFs) (Jessell, 2000; Politis et al., 2008; Kaltezioti et al., 2010; Martynoga et al., 2012; Stergiopoulos and Politis, 2013). However, the recent advent of sequencing methodologies and experimental data from large-scale consortia focused on characterizing functional genomic elements such as ENCODE and FANTOM, have revolutionized our view for organization, activity, and regulation of the mammalian genome (Carninci et al., 2005; Katayama et al., 2005; Birney et al., 2007). Surprisingly, the vast majority of the genome is transcribed producing not only protein-coding RNAs but also a vast number of different kinds of newly-identified classes of non-coding RNAs, including microRNAs (miRNAs-small non-coding RNAs) and long non-coding RNAs (lncRNAs). miRNAs have been extensively studied while the role of lncRNAs in cell biology together with novel roles of miRNAs in directly regulating lncRNAs have just begun to emerge (Amodio et al., 2012a,b; Rossi et al., 2013; Tay et al., 2014). LncRNAs are transcribed by RNA polymerase II, defined as endogenous cellular RNAs longer than 200 nt in length that lack an ORF, can be post-transcriptional processed by 5′ capping, polyadenylation, splicing, RNA editing, and exhibit specific sub-cellular localization (Qureshi and Mehler, 2012). Most importantly, it was recently shown that lncRNAs participate in the gene regulatory networks controlling embryonic stem cell (ESC) pluripotency and metastasis of cancer cells, as well as development and function of various tissues (Guttman et al., 2011; Gutschner and Diederichs, 2012; Qureshi and Mehler, 2012; Yang et al., 2013). Although lncRNAs are the most abundant classes of RNAs (Katayama et al., 2005; Birney et al., 2007; Kapranov et al., 2007b; Kapranov and St Laurent, 2012), they remain poorly characterized and their roles in brain development have just begun to arise. Notably, it has been proposed that the number of lncRNAs far exceeds the number of protein-coding mRNAs in the mammalian transcriptome (Carninci et al., 2005; Kapranov et al., 2010) and the vast majority of them appears to be expressed in adult brain in a highly specific manner (Qureshi and Mehler, 2012). In the last few years, many groups have focused their efforts toward understanding the actions of lncRNAs in brain function and evolution. In this mini-review, we highlight the emerging evidence of the involvement of this new class of RNA molecules in NSC biology during development and adulthood, in health and disease. In particular, we summarize recent progress regarding the participation of lncRNAs in the regulatory networks that control the fine balance between proliferation and differentiation decisions of NSCs. The ability of lncRNAs to interact with both genomic loci and protein products of TF genes appears to endow them with a remarkable capacity to control NSC maintenance and differentiation, suggesting an undoubtedly important influence on the pathophysiology of several neurodegenerative disorders (Kapranov et al., 2007a,b; Guttman et al., 2009; Khalil et al., 2009; Orom et al., 2010; Bian and Sun, 2011; Qureshi and Mehler, 2012; Spadaro and Bredy, 2012; Ng et al., 2013).

LncRNAs: new players in cell biology

LncRNAs can be classified as bidirectional, intronic, intergenic, sense, antisense or 3′-UTR (untranslated region) transcripts with respect to nearby protein-coding genes (Mercer et al., 2009; Derrien et al., 2012). Some lncRNAs are exported from nucleus and perform important functions in the cytoplasm, but more often they are found in nucleus, particularly associated with chromatin (Saxena and Carninci, 2011). In more detail, these transcripts may be bound by proteins, other RNA molecules or even fulfil intrinsic catalytic functions (Fedor and Williamson, 2005; Ye, 2007; Guttman and Rinn, 2012). The vast majority of these transcripts are not translated, supporting a role as non-coding RNAs rather than protein precursors (Banfai et al., 2012; Derrien et al., 2012). Furthermore, lncRNAs are developmentally regulated, expressed in specific cell types, associated with chromatin signatures indicating transcriptional regulation, are under evolutionary constraint and associated with carcinogenesis and other diseases; all of which support meaningful roles of lncRNAs (Qureshi and Mehler, 2012; Fatica and Bozzoni, 2014). LncRNAs also participate in a striking diversity of cellular processes including transcriptional regulation, genomic imprinting, alternative splicing, mRNA stability, translational control, DNA damage response, cell cycle regulation and organelle biogenesis (Rinn and Chang, 2012). Interestingly, it seems that knock-down or over-expression of many of these lncRNAs produce phenotypes that are very well correlated with their aberrant expression in disease states (Qureshi et al., 2010; Gutschner and Diederichs, 2012; Qureshi and Mehler, 2012). Therefore, we believe that lncRNA transcripts would eventually occupy a central place in our understanding of the molecular mechanisms underlying human diseases. Systematical profiling and comprehensive annotation of lncRNAs in various cell types can shed light on the functionalities of these novel regulators. LncRNA-protein interactions can be currently predicted, approached and analyzed by various research advanced tools and strategies apart from bioinformatics, including high-throughput analysis of lncRNA expression [microarrays, RNA sequencing [RNA-Seq] (Mortazavi et al., 2008; Wang et al., 2009; Ilott and Ponting, 2013), RNA CaptureSeq, iSeeRNA [support vector machine (SVM)-based classifier] (Sun et al., 2013), BRIC-Seq [50-bromo-uridine (BrU) immunoprecipitation chase-deep sequencing analysis] (Imamachi et al., 2013)], RIP [RNA-binding protein (RBP) immunoprecipitation] coupled with microarray and high-throughput sequencing (RIP-Chip/Seq respectively) (Zhao et al., 2010; Jain et al., 2011), ChIRP (chromatin isolation by RNA purification) and CHART (capture hybridization analysis of RNA targets—High-throughput finding of RBPs and DNAs) as well as CLIP (crosslinking-immunopurification)-Seq, which provides transcriptome-wide coverage for mapping RBP-binding sites (Khalil et al., 2009; Wu et al., 2010; Chu et al., 2011; Zhu et al., 2013).

LncRNAs in neural stem cells

These technologies have greatly helped the efforts to elucidate the role of lncRNAs in NSCs, neural differentiation, migration and maturation. Toward this goal, Ramos and colleagues identified and predicted regulatory roles for more than 12,000 novel lncRNAs (2,265 lncRNAs had proximal protein-coding gene neighbors) in the subventricular zone (SVZ) of adult mice. In FACS-sorted NSCs, they found a unique lncRNA expression pattern for each of the three stages of neurogenesis analyzed. Moreover, by using ChIP-Seq (chromatin immunoprecipitation-sequencing), lncRNAs were shown to be transcriptionally regulated in a manner analogous to mRNAs, enabling the prediction of lncRNAs that may function in the glial-neuronal lineage specification of multipotent adult NSCs (Ramos et al., 2013; Wang et al., 2013). Further transcriptome-next-generation-sequencing revealed that lncRNA-mediated alternative splicing of cell fate determinants controls stem-cell commitment during neurogenesis. Specifically, Aprea and co-workers identified several genic and intergenic lncRNAs that are functionally involved in neurogenic commitment, including Cosl1, Btg2-AS1, Gm17566, Miat (Myocardial infarction associated transcript-Gomafu), Rmst (Rhabdomyosarcoma 2 associated transcript), Gm17566, Gm14207, Gm16758, 2610307P16Rik, AC102815.1, C230034O21Rik and 9930014A18Rik (Aprea et al., 2013). Accordingly, subsequent studies using high-throughput transcriptomic data (microarray platform) to examine lncRNA differential expression in NSCs, GABAergic neurons and oligodendrocytes, led to the identification of lncRNAs that are dynamically regulated during neural lineage specification, neuronal-glia fate switching and oligodendrocyte maturation [i.e., Dlx1AS (Distal-less homeobox 1 antisense), Evf2 (Embryonic ventral forebrain 2), Rmst, utNgn1 (untranslated Neurogenin1), MALAT1 (metastasis-associated lung adenocarcinoma transcript 1; also named NEAT2)] (Mercer et al., 2010; Qureshi and Mehler, 2012; Ng et al., 2013). ChIP-Seq approaches were also developed to generate and investigate genome-wide chromatin-state maps. These functional analyses predicted hypothetical roles for 150 mammalian lincRNAs (long intergenic non-coding RNAs) in a “guilt-by-association” manner in NSCs. In particular, specific lincRNAs appeared to localize near genes encoding key TFs (such as Sox2, Klf4, Myc, p53, NFkB and Brn1) that are involved in processes ranging from hippocampal development to neuronal and oligodendrocyte maturation (Guttman et al., 2009; Qureshi and Mehler, 2012). More concisely, Ramos et al. have also performed in vitro knock-down studies and observed that Dlx1AS, a lncRNA encoded from a bigene Dlx1/2 cluster, is associated with fate determination of adult SVZ NSCs via positive regulation of Dlx1 and Dlx2 gene expression. Mechanistically, enhanced transcription of Dlx1AS occurs during neurogenesis when H3K27me3 (trimethylation of histone H3 Lys-27) repression is decreased. The H3K27me3-specific demethylase JMJD3 was also found to be enriched at the Dlx1AS locus (Figure 1A) (Gonzales-Roybal and Lim, 2013; Ramos et al., 2013). Recently, a comprehensive study came up with the finding that UtNgn1 is a non-coding RNA transcribed from an enhancer region of the Neurogenin1 (Neurog1) locus. This non-coding transcript seems to positively regulate Neurog1 transcription during neuronal differentiation of NSCs. In detail, during the late stage of neocortical NSC development, utNgn1 expression is up-regulated via involvement of Wnt signaling whereas it is down-regulated by PcG (polycomb group) proteins (Figure 1B) (Onoguchi et al., 2012). Additionally, two lncRNAs, nuclear enriched abundant transcripts NEAT1 and NEAT2 (MALAT1) are up-regulated in neuronal and glial progeny, and are associated with neuronal activity, growth and branching (Mercer et al., 2010; Ng et al., 2013). Miat (also called Gomafu) is one of the known non-coding RNAs that participates in neuronal subtype- specific determination and is also highly expressed in oligodendrocyte lineage specification (Aprea et al., 2013). In the same lineage, another lncRNA, Nkx2.2AS, an antisense RNA of the known homeobox TF Nkx2.2, appears to lead NSCs into oligodendrocytic fate through modest induction of Nkx2.2 gene. By using deletion mutants, Tochitani and Hayashizaki showed that the overlapping regions of Nkx2.2AS and Nkx2.2 isoforms are required for promoting Nkx2.2 mRNA levels and the subsequent oligodendrocytic differentiation of NSCs (Figure 1C) (Tochitani and Hayashizaki, 2008). Evf2 is predominantly detected in the developing forebrain, both in human and mouse, and is critical for GABAergic-interneuron formation. Like other lncRNAs, Evf2 seems to control the expression of specific genes that are necessary during brain development, such as Dlx5, Dlx6 and Gad1, through distinct trans- and cis-acting mechanisms (Figure 1D) (Bond et al., 2009). Interestingly, Rmst is presented to be a novel marker for dopaminergic neurons during NSC differentiation, where it is co-expressed with the midbrain-specific TF Lmx1a (Uhde et al., 2010).
Figure 1

Proposed schematic models for the role of different lncRNAs (green) in neural development. (A) LncRNA Dlx1AS consists of two exons that are spliced and the mature transcript is polyadenylated. During neuronal differentiation of adult SVZ NSCs, Dlx1AS is required for the induction of Dlx1 and Dlx2 (red) gene expression (Gonzales-Roybal and Lim, 2013; Ramos et al., 2013). (B) During neocortical neurogenesis, utNgn1 receive Wnt signals (i.e., Wnt3a) to induce the expression of Neurog1 (red). PcG protein-mediated mechanisms (i.e., Ring1B, H3K27me3, H3K4me3, H3K9/K14ac) lead to the suppression of utNgn1 (Onoguchi et al., 2012). (C) The overlapping regions of Nkx2.2AS and Nkx2.2 isoforms (I and II-red) are necessary to promote Nkx2.2 mRNA levels and the subsequent oligodendrocytic differentiation of NSCs (Tochitani and Hayashizaki, 2008). (D) Mechanistic pathway for Evf2-dependent interactions crucial for forebrain development. Secreted Shh (Sonic hedgehog) promotes expression of Dlx1 and Dlx2 (red), which sequentially suppress Neuropilin2 and Notch signaling. Activation of Evf2 leads to the formation of a regulatory network together with Dlx's (red) and MECP2 (methyl CpG binding protein 2) that controls GAD67 and GABAergic-interneuron formation (Bond et al., 2009). NSC, neural stem cell; Evf1 (lncRNA) (blue), Embryonic ventral forebrain-1, Dlx6 antisense RNA 1 (Dlx6AS1).

Proposed schematic models for the role of different lncRNAs (green) in neural development. (A) LncRNA Dlx1AS consists of two exons that are spliced and the mature transcript is polyadenylated. During neuronal differentiation of adult SVZ NSCs, Dlx1AS is required for the induction of Dlx1 and Dlx2 (red) gene expression (Gonzales-Roybal and Lim, 2013; Ramos et al., 2013). (B) During neocortical neurogenesis, utNgn1 receive Wnt signals (i.e., Wnt3a) to induce the expression of Neurog1 (red). PcG protein-mediated mechanisms (i.e., Ring1B, H3K27me3, H3K4me3, H3K9/K14ac) lead to the suppression of utNgn1 (Onoguchi et al., 2012). (C) The overlapping regions of Nkx2.2AS and Nkx2.2 isoforms (I and II-red) are necessary to promote Nkx2.2 mRNA levels and the subsequent oligodendrocytic differentiation of NSCs (Tochitani and Hayashizaki, 2008). (D) Mechanistic pathway for Evf2-dependent interactions crucial for forebrain development. Secreted Shh (Sonic hedgehog) promotes expression of Dlx1 and Dlx2 (red), which sequentially suppress Neuropilin2 and Notch signaling. Activation of Evf2 leads to the formation of a regulatory network together with Dlx's (red) and MECP2 (methyl CpG binding protein 2) that controls GAD67 and GABAergic-interneuron formation (Bond et al., 2009). NSC, neural stem cell; Evf1 (lncRNA) (blue), Embryonic ventral forebrain-1, Dlx6 antisense RNA 1 (Dlx6AS1). Considering the tight connection between pluripotency of human ESCs and their differentiation into NSCs (ESC-derived NSCs) and subsequently into neurons, Ng and co-workers extensively showed that diverse lncRNAs are essential for ESC proliferation and neurogenesis through physical interaction with master TFs (e.g., Sox2). In detail, microarray data analysis led to the identification of 35 neuronal lncRNAs with important roles in neuronal differentiation, e.g., Rmst (AK056164, AF429305 and AF429306), lncRNA_N1 (AK124684), lncRNA_N2 (AK091713), lncRNA_N3 (AK055040, etc.). They also suggested that these lncRNAs are required for generation of neurons and suppression of gliogenesis by association with chromatin modifiers and nuclear proteins (Ng et al., 2012). In agreement, another study that aimed at identifying functional features of lncRNAs during ESC differentiation to adult cerebellum by utilizing RNA-Seq and ChIP-Seq technologies, demonstrated that filtered novel lncRNAs are located close to protein-coding genes involved in functions such as neuronal differentiation and transcriptional regulation (Guttman et al., 2009; Lv et al., 2013). Particular studies have been successful in identifying anti-NOS2A as an antisense transcript of the NOS2A (Nitric oxide synthase 2 enzyme) gene, an isoform of the NOS protein which induces hESC differentiation into neurogenic precursors (Korneev et al., 2008). Specific expression pattern was also detected for Otx2c (Orthodenticle homeobox 2 c), an alternative splicing variant of the pre-mRNA Otx2 with a possible role in neural differentiation of hESCs (Liu et al., 2013). Another lncRNA that is correlated with the proliferation state of ESCs is lincRNA-Sox2, which is located at the promoter of Sox2 locus and is regulated by Sox2 and Oct4 (Guttman et al., 2009). Finally, a thorough targeted RNA-Seq analysis carried out using neurons derived from patient-specific induced pluripotent stem cells (iPSCs) showed that more than 1,500 lncRNAs are dynamically regulated during differentiation of iPSCs toward glutamatergic neurons. Particularly, the expression of 1,622 non-coding genes (lncRNAs/lincRNAs) was dramatically affected during conversion from iPSCs to differentiating neurons, while alternative splicing occurred. Significant alterations were also observed in the expression patterns of non-coding genes involved in neuropsychiatric disorders (Lin et al., 2011; Qureshi and Mehler, 2012; Akula et al., 2014).

LncRNAs in brain function, evolution and neurological diseases

The importance of lncRNAs in the brain is explicitly highlighted by the observation that most of them are expressed in the adult mammalian brain in highly regional-, cellular- and sub-cellular compartment-specific and neuronal activity dependent profiles (Mercer et al., 2008; Ponjavic et al., 2009; Qureshi and Mehler, 2012). In fact, it seems that lncRNAs have played important roles in the evolution of the form and function of human brain, since the fastest evolving regions of the primate genome are non-coding sequences that generate lncRNAs implicated in the modulation of neuro-developmental genes (Pollard et al., 2006; Qureshi and Mehler, 2012). The most dramatic of these regions, called HAR1 (human accelerated region 1), is part of a novel lncRNA gene (HAR1F) that is expressed specifically in Cajal–Retzius neurons in the developing human neocortex from 7 to 19 gestational weeks, a crucial period for cortical neuron-specification and migration. Additionally, analysis of highly conserved lncRNAs in birds, marsupials and eutherian mammals revealed a remarkable similarity in spatiotemporal expression profiles of orthologous lncRNAs, suggesting ancient roles during brain development (Chodroff et al., 2010). Moreover, lncRNAs directly modulate synaptic processes (MALAT1), protein synthesis (BC1), learning and memory (Tsx), and are associated with neuronal activity in mouse cortex (Qureshi and Mehler, 2012). In agreement with these effects on neurons, lncRNAs have also been implicated in the pathophysiology of neuro-developmental, neurodegenerative, neuro-immunological and neuro-oncological diseases/disorders. For instance, high levels of BC1/BC200 and BACE1-AS have been implicated in Alzheimer's disease (AD) while NEAT1's in Huntington's disease (HD). BC1/BC200 normally seems to selectively regulate local protein synthesis in post-synaptic dendritic compartments, by repressing translation via an elF4-A-dependent mechanism (Qureshi et al., 2010; Niland et al., 2012). De-regulation of BACE1-AS has been shown to be responsible for feed-forward induction of BACE1 (β-secretase); thus leading to amyloid β (Aβ) increased production and possible AD pathogenesis (Qureshi et al., 2010). Additionally, NEAT1 is a lncRNA known to be involved in cell death mechanisms. In particular, NEAT1 controls target gene transcription by protein sequestration into paraspeckles (stress-responsive sub-nuclear structures), a potentially dysfunctional pathway in HD progression. In accordance, Hirose and co-workers have very recently shown that NEAT1 transcriptional up-regulation leads to the enlargement of these structures after proteasome inhibition (Johnson, 2012; Hirose et al., 2014). Various lncRNAs have also been correlated with Parkinson's disease (PINK-AS1, UCHL1-AS1), amyotrophic lateral sclerosis (MSUR1), Down's syndrome (NRON) as well as with tumor progression (ANRIL, MALAT1, HOTAIR, NOS3AS) (Gutschner and Diederichs, 2012). A common theme emerging from all these cases is that lncRNAs control the expression of nearby protein-coding genes in cis and de-regulation of this relationship could lead to nervous system-related diseases. In agreement, brain-expressed lncRNAs are preferentially located adjacent to protein-coding genes that are also expressed in the brain and involved in transcriptional regulation and/or nervous system development (Mercer et al., 2008; Ponjavic et al., 2009). Many of these pairs often exhibited coordinated expression during developmental transitions. Therefore, it was suggested that these lncRNAs may influence the expression of the associated protein-coding genes similarly to previously characterized examples such as Nkx2.2AS, HOTAIR, p15AS, p21AS and Evf2.

Perspective links between lncRNAs and brain development

Over recent years, it has become more and more evident that lncRNAs play key roles in gene regulatory networks controlling nervous system development. To initially investigate this link, we bioinformatically screened numerous mouse genes encoding TFs with well-established roles in CNS (central nervous system) development for close proximity with lncRNA genes (based on publicly available data from UCSC genome-browser). Accordingly, we managed to identify 79 such TF genes encompassing 91 transcriptional units for lncRNA genes in close proximity (<3,000 base pairs-bp) (Table 1). In particular, 40.65% of these lncRNAs are bidirectional, 16.48% intronic, 9.89% intergenic, 12.08% sense, 15.38% antisense and 5.49% 3′-UTR. The majority of these lncRNAs have only been identified in genome-wide expression screens, are expressed in nervous system, and intriguingly, their functions are totally unknown. Some of them have been reported to interact with TFs or chromatin-associated complexes (Wang and Chang, 2011; Guttman and Rinn, 2012; Rinn and Chang, 2012), indicating potential contribution to the combinatorial transcriptional codes involved in NSC maintenance, sub-type/lineage specification and terminal differentiation. Based on these preliminary evidence, we postulate that lncRNAs and TFs with regulatory role in neurogenesis are inter-connected and may form coherent cross-regulatory networks that are associated with CNS development. However, this hypothesis needs to be extensively interrogated in NSCs. Moreover, considering the fact that some TFs are used as reprogramming tools for the production of iPSCs, induced neurons, induced NSCs, cardiomyocytes, etc. (Yang et al., 2011), these lncRNAs may be utilized for the production of clinically useful cell types in the near feature, revolutionizing the basic principles of developmental/cell biology as well as neuroscience.
Table 1

List of genes encoding TFs with critical roles in brain development that also contain lncRNA genes in close proximity to their genomic loci (<3,000 bp).

Genes encoding for TFsLncRNAsPosition
Ascl4AK018959Sense
Atoh7AK005214Sense
Crebbp4930455F16RikIntergenic
CrxCrxOSBidirectional
Ctnnb14930593C16RikBidirectional
Cux2AK006762Sense
Cux2AK187608Bidirectional
Dlx1Dlx1ASAntisense
Dlx4A730090H04RikBidirectional
Dlx6Dlx6AS1Antisense
Dlx6Dlx6AS2Intronic
Emx2Emx2OSBidirectional
Evx15730457N03RikBidirectional
FezF1FezF1-AS1Bidirectional
FezF1AK086573Intergenic
FoxA2AK156045Antisense
FoxG1AK158887Intergenic
FoxG13110039M20RikSense
Gata1S57880Sense
Gata2AK137172Sense
Gata34930412013RBidirectional
Gata4AK031341Intronic
Gata6AK033147Bidirectional
Gata6AK003136Bidirectional
Gbx2D130058E05RikBidirectional
Gli1AK157048Sense
Gli2AK054469Intronic
Gli3AK135998Intergenic
Hmx1E130018O15RikBidirectional
Irx2Gm20554Bidirectional
Lef1Lef1-AS1Bidirectional
Lhx1Lhx1OSBidirectional
Lhx3AK035055Bidirectional
Lhx8AI606473Bidirectional
Lmx1bC130021I20Bidirectional
Lxrb (NR1H2)AK1846033 ′-UTR
Meis1AK144295Antisense
Meis2AK012325Sense
Meis2AK144367Bidirectional
Meis2AK144485Bidirectional
Msx1Msx1ASAntisense
MycNMYCNOSBidirectional
Myt1LAK138505Antisense
NFATc1AK1550683 ′-UTR
NFATc4AK014164Sense
NFIAE130114P18RikBidirectional
NFIBAK081607Intronic
NFIxAK168184Antisense
NFkB2AK029443Bidirectional
Ngn1AK016084Intergenic
Nkx2.2Nkx2.2ASAntisense
Notch1AK075572Antisense
NR2F1AK051417Intergenic
NR2F1A830082K12RikBidirectional
NR2F2AK135306Intronic
NR3C2Gm10649Bidirectional
NR4A2BB557941Intergenic
NR5A2 (lrh-1)AK178198Antisense
NR5A2 (lrh-1)AK145521Intronic
Otx2Otx2OSBidirectional
Pax2AK006641Antisense
Pax6AK044354Antisense
Pbx3AK138624Intronic
Pou4F1AK084042Intergenic
PPARdAK033897Intronic
PPARdAK007468Intronic
Prox1AK142161Bidirectional
Ptf1aAK053418Antisense
RARaAK031732Intronic
RARbAK0523063 ′-UTR
RBPjKAK164362Intronic
Runx1AK131747Intergenic
SATB29130024F11RikBidirectional
Six1AK0350853 ′-UTR
Six3Six3OS1Bidirectional
Six64930447C04RikBidirectional
Sox1Gm5607Sense
Sox10GM10863Bidirectional
Sox2Sox2OTSense
Sox21AK039417Bidirectional
Sox8AK079380Bidirectional
Sox9BC006965Bidirectional
STAT5bAK088966Intronic
Tgif25430405H02Rik3 ′-UTR
THRAAK165172Intronic
THRBAK088911Antisense
WT1AK033304Intronic
WT1AI314831Bidirectional
Zeb1AK041408Intronic
Zeb1Gm10125Bidirectional
Zeb2Zeb2OSBidirectional

Some of these TFs contain more than one lncRNA near to their genes (duplicates). The position of each lncRNA relatively to its nearby protein-coding gene is indicated at the third column of the table.

List of genes encoding TFs with critical roles in brain development that also contain lncRNA genes in close proximity to their genomic loci (<3,000 bp). Some of these TFs contain more than one lncRNA near to their genes (duplicates). The position of each lncRNA relatively to its nearby protein-coding gene is indicated at the third column of the table. To further examine the links between lncRNAs, brain development and neurological disorders, we tested whether lncRNAs, associated with nervous system-related diseases in humans, are expressed in embryonic mouse brain (E15.5) or ex vivo cultured NSCs (isolated from mouse telencephalon, E15.5). The rational for these experiments was based on observations showing many neurological diseases to be initiated very early during brain maturation and development (Bian and Sun, 2011; Qureshi and Mehler, 2012). Specifically, we first identified in silico and then tested for expression 20 such lncRNAs with clear conservation in mouse genome. Interestingly, RT-PCR (reverse transcription-PCR) analysis revealed that most lncRNAs are expressed in both brain and NSCs (Figure 2), suggesting potential involvement in brain development. Moreover, a possible function of these lncRNAs in NSCs may contribute to their roles in neurological diseases. Nevertheless, further investigation and initiation of new experimental studies are needed to uncover the exact function of lncRNAs in NSCs and nervous system in general.
Figure 2

RT-PCR-based detection of various lncRNAs associated with CNS-related diseases or disorders. Experiments were performed using cDNA samples derived from embryonic mouse brain (E15.5) or NSCs isolated from embryonic mouse telencephalon and cultured ex vivo, as indicated. In some cases alternative splicing isoforms are also evident. RT-PCR primer sequences are available upon request.

RT-PCR-based detection of various lncRNAs associated with CNS-related diseases or disorders. Experiments were performed using cDNA samples derived from embryonic mouse brain (E15.5) or NSCs isolated from embryonic mouse telencephalon and cultured ex vivo, as indicated. In some cases alternative splicing isoforms are also evident. RT-PCR primer sequences are available upon request.

Conclusions

LncRNAs represent a new exciting frontier in molecular biology with major roles in NSC fate decisions, specification and commitment. Full understanding of how these non-coding transcripts regulate the expression of protein-coding genes and participate in gene regulatory circuitries could lead to the discovery of novel cellular/molecular mechanisms and signaling pathways involved in neural development; thus having potential implications for the treatment of nervous system-related diseases and traumas.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  70 in total

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Review 2.  Molecular mechanisms of long noncoding RNAs.

Authors:  Kevin C Wang; Howard Y Chang
Journal:  Mol Cell       Date:  2011-09-16       Impact factor: 17.970

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4.  RNA-sequencing of the brain transcriptome implicates dysregulation of neuroplasticity, circadian rhythms and GTPase binding in bipolar disorder.

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Journal:  Mol Psychiatry       Date:  2014-01-07       Impact factor: 15.992

5.  Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project.

Authors:  Ewan Birney; John A Stamatoyannopoulos; Anindya Dutta; Roderic Guigó; Thomas R Gingeras; Elliott H Margulies; Zhiping Weng; Michael Snyder; Emmanouil T Dermitzakis; Robert E Thurman; Michael S Kuehn; Christopher M Taylor; Shane Neph; Christoph M Koch; Saurabh Asthana; Ankit Malhotra; Ivan Adzhubei; Jason A Greenbaum; Robert M Andrews; Paul Flicek; Patrick J Boyle; Hua Cao; Nigel P Carter; Gayle K Clelland; Sean Davis; Nathan Day; Pawandeep Dhami; Shane C Dillon; Michael O Dorschner; Heike Fiegler; Paul G Giresi; Jeff Goldy; Michael Hawrylycz; Andrew Haydock; Richard Humbert; Keith D James; Brett E Johnson; Ericka M Johnson; Tristan T Frum; Elizabeth R Rosenzweig; Neerja Karnani; Kirsten Lee; Gregory C Lefebvre; Patrick A Navas; Fidencio Neri; Stephen C J Parker; Peter J Sabo; Richard Sandstrom; Anthony Shafer; David Vetrie; Molly Weaver; Sarah Wilcox; Man Yu; Francis S Collins; Job Dekker; Jason D Lieb; Thomas D Tullius; Gregory E Crawford; Shamil Sunyaev; William S Noble; Ian Dunham; France Denoeud; Alexandre Reymond; Philipp Kapranov; Joel Rozowsky; Deyou Zheng; Robert Castelo; Adam Frankish; Jennifer Harrow; Srinka Ghosh; Albin Sandelin; Ivo L Hofacker; Robert Baertsch; Damian Keefe; Sujit Dike; Jill Cheng; Heather A Hirsch; Edward A Sekinger; Julien Lagarde; Josep F Abril; Atif Shahab; Christoph Flamm; Claudia Fried; Jörg Hackermüller; Jana Hertel; Manja Lindemeyer; Kristin Missal; Andrea Tanzer; Stefan Washietl; Jan Korbel; Olof Emanuelsson; Jakob S Pedersen; Nancy Holroyd; Ruth Taylor; David Swarbreck; Nicholas Matthews; Mark C Dickson; Daryl J Thomas; Matthew T Weirauch; James Gilbert; Jorg Drenkow; Ian Bell; XiaoDong Zhao; K G Srinivasan; Wing-Kin Sung; Hong Sain Ooi; Kuo Ping Chiu; Sylvain Foissac; Tyler Alioto; Michael Brent; Lior Pachter; Michael L Tress; Alfonso Valencia; Siew Woh Choo; Chiou Yu Choo; Catherine Ucla; Caroline Manzano; Carine Wyss; Evelyn Cheung; Taane G Clark; James B Brown; Madhavan Ganesh; Sandeep Patel; Hari Tammana; Jacqueline Chrast; Charlotte N Henrichsen; Chikatoshi Kai; Jun Kawai; Ugrappa Nagalakshmi; Jiaqian Wu; Zheng Lian; Jin Lian; Peter Newburger; Xueqing Zhang; Peter Bickel; John S Mattick; Piero Carninci; Yoshihide Hayashizaki; Sherman Weissman; Tim Hubbard; Richard M Myers; Jane Rogers; Peter F Stadler; Todd M Lowe; Chia-Lin Wei; Yijun Ruan; Kevin Struhl; Mark Gerstein; Stylianos E Antonarakis; Yutao Fu; Eric D Green; Ulaş Karaöz; Adam Siepel; James Taylor; Laura A Liefer; Kris A Wetterstrand; Peter J Good; Elise A Feingold; Mark S Guyer; Gregory M Cooper; George Asimenos; Colin N Dewey; Minmei Hou; Sergey Nikolaev; Juan I Montoya-Burgos; Ari Löytynoja; Simon Whelan; Fabio Pardi; Tim Massingham; Haiyan Huang; Nancy R Zhang; Ian Holmes; James C Mullikin; Abel Ureta-Vidal; Benedict Paten; Michael Seringhaus; Deanna Church; Kate Rosenbloom; W James Kent; Eric A Stone; Serafim Batzoglou; Nick Goldman; Ross C Hardison; David Haussler; Webb Miller; Arend Sidow; Nathan D Trinklein; Zhengdong D Zhang; Leah Barrera; Rhona Stuart; David C King; Adam Ameur; Stefan Enroth; Mark C Bieda; Jonghwan Kim; Akshay A Bhinge; Nan Jiang; Jun Liu; Fei Yao; Vinsensius B Vega; Charlie W H Lee; Patrick Ng; Atif Shahab; Annie Yang; Zarmik Moqtaderi; Zhou Zhu; Xiaoqin Xu; Sharon Squazzo; Matthew J Oberley; David Inman; Michael A Singer; Todd A Richmond; Kyle J Munn; Alvaro Rada-Iglesias; Ola Wallerman; Jan Komorowski; Joanna C Fowler; Phillippe Couttet; Alexander W Bruce; Oliver M Dovey; Peter D Ellis; Cordelia F Langford; David A Nix; Ghia Euskirchen; Stephen Hartman; Alexander E Urban; Peter Kraus; Sara Van Calcar; Nate Heintzman; Tae Hoon Kim; Kun Wang; Chunxu Qu; Gary Hon; Rosa Luna; Christopher K Glass; M Geoff Rosenfeld; Shelley Force Aldred; Sara J Cooper; Anason Halees; Jane M Lin; Hennady P Shulha; Xiaoling Zhang; Mousheng Xu; Jaafar N S Haidar; Yong Yu; Yijun Ruan; Vishwanath R Iyer; Roland D Green; Claes Wadelius; Peggy J Farnham; Bing Ren; Rachel A Harte; Angie S Hinrichs; Heather Trumbower; Hiram Clawson; Jennifer Hillman-Jackson; Ann S Zweig; Kayla Smith; Archana Thakkapallayil; Galt Barber; Robert M Kuhn; Donna Karolchik; Lluis Armengol; Christine P Bird; Paul I W de Bakker; Andrew D Kern; Nuria Lopez-Bigas; Joel D Martin; Barbara E Stranger; Abigail Woodroffe; Eugene Davydov; Antigone Dimas; Eduardo Eyras; Ingileif B Hallgrímsdóttir; Julian Huppert; Michael C Zody; Gonçalo R Abecasis; Xavier Estivill; Gerard G Bouffard; Xiaobin Guan; Nancy F Hansen; Jacquelyn R Idol; Valerie V B Maduro; Baishali Maskeri; Jennifer C McDowell; Morgan Park; Pamela J Thomas; Alice C Young; Robert W Blakesley; Donna M Muzny; Erica Sodergren; David A Wheeler; Kim C Worley; Huaiyang Jiang; George M Weinstock; Richard A Gibbs; Tina Graves; Robert Fulton; Elaine R Mardis; Richard K Wilson; Michele Clamp; James Cuff; Sante Gnerre; David B Jaffe; Jean L Chang; Kerstin Lindblad-Toh; Eric S Lander; Maxim Koriabine; Mikhail Nefedov; Kazutoyo Osoegawa; Yuko Yoshinaga; Baoli Zhu; Pieter J de Jong
Journal:  Nature       Date:  2007-06-14       Impact factor: 49.962

Review 6.  The multilayered complexity of ceRNA crosstalk and competition.

Authors:  Yvonne Tay; John Rinn; Pier Paolo Pandolfi
Journal:  Nature       Date:  2014-01-16       Impact factor: 49.962

Review 7.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

8.  The transcriptional landscape of the mammalian genome.

Authors:  P Carninci; T Kasukawa; S Katayama; J Gough; M C Frith; N Maeda; R Oyama; T Ravasi; B Lenhard; C Wells; R Kodzius; K Shimokawa; V B Bajic; S E Brenner; S Batalov; A R R Forrest; M Zavolan; M J Davis; L G Wilming; V Aidinis; J E Allen; A Ambesi-Impiombato; R Apweiler; R N Aturaliya; T L Bailey; M Bansal; L Baxter; K W Beisel; T Bersano; H Bono; A M Chalk; K P Chiu; V Choudhary; A Christoffels; D R Clutterbuck; M L Crowe; E Dalla; B P Dalrymple; B de Bono; G Della Gatta; D di Bernardo; T Down; P Engstrom; M Fagiolini; G Faulkner; C F Fletcher; T Fukushima; M Furuno; S Futaki; M Gariboldi; P Georgii-Hemming; T R Gingeras; T Gojobori; R E Green; S Gustincich; M Harbers; Y Hayashi; T K Hensch; N Hirokawa; D Hill; L Huminiecki; M Iacono; K Ikeo; A Iwama; T Ishikawa; M Jakt; A Kanapin; M Katoh; Y Kawasawa; J Kelso; H Kitamura; H Kitano; G Kollias; S P T Krishnan; A Kruger; S K Kummerfeld; I V Kurochkin; L F Lareau; D Lazarevic; L Lipovich; J Liu; S Liuni; S McWilliam; M Madan Babu; M Madera; L Marchionni; H Matsuda; S Matsuzawa; H Miki; F Mignone; S Miyake; K Morris; S Mottagui-Tabar; N Mulder; N Nakano; H Nakauchi; P Ng; R Nilsson; S Nishiguchi; S Nishikawa; F Nori; O Ohara; Y Okazaki; V Orlando; K C Pang; W J Pavan; G Pavesi; G Pesole; N Petrovsky; S Piazza; J Reed; J F Reid; B Z Ring; M Ringwald; B Rost; Y Ruan; S L Salzberg; A Sandelin; C Schneider; C Schönbach; K Sekiguchi; C A M Semple; S Seno; L Sessa; Y Sheng; Y Shibata; H Shimada; K Shimada; D Silva; B Sinclair; S Sperling; E Stupka; K Sugiura; R Sultana; Y Takenaka; K Taki; K Tammoja; S L Tan; S Tang; M S Taylor; J Tegner; S A Teichmann; H R Ueda; E van Nimwegen; R Verardo; C L Wei; K Yagi; H Yamanishi; E Zabarovsky; S Zhu; A Zimmer; W Hide; C Bult; S M Grimmond; R D Teasdale; E T Liu; V Brusic; J Quackenbush; C Wahlestedt; J S Mattick; D A Hume; C Kai; D Sasaki; Y Tomaru; S Fukuda; M Kanamori-Katayama; M Suzuki; J Aoki; T Arakawa; J Iida; K Imamura; M Itoh; T Kato; H Kawaji; N Kawagashira; T Kawashima; M Kojima; S Kondo; H Konno; K Nakano; N Ninomiya; T Nishio; M Okada; C Plessy; K Shibata; T Shiraki; S Suzuki; M Tagami; K Waki; A Watahiki; Y Okamura-Oho; H Suzuki; J Kawai; Y Hayashizaki
Journal:  Science       Date:  2005-09-02       Impact factor: 47.728

9.  The majority of total nuclear-encoded non-ribosomal RNA in a human cell is 'dark matter' un-annotated RNA.

Authors:  Philipp Kapranov; Georges St Laurent; Tal Raz; Fatih Ozsolak; C Patrick Reynolds; Poul H B Sorensen; Gregory Reaman; Patrice Milos; Robert J Arceci; John F Thompson; Timothy J Triche
Journal:  BMC Biol       Date:  2010-12-21       Impact factor: 7.431

10.  Emerging role of non-coding RNA in neural plasticity, cognitive function, and neuropsychiatric disorders.

Authors:  Paola A Spadaro; Timothy W Bredy
Journal:  Front Genet       Date:  2012-07-13       Impact factor: 4.599

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  14 in total

Review 1.  Lingering Questions about Enhancer RNA and Enhancer Transcription-Coupled Genomic Instability.

Authors:  Gerson Rothschild; Uttiya Basu
Journal:  Trends Genet       Date:  2017-01-10       Impact factor: 11.639

Review 2.  LncRNAs: macromolecules with big roles in neurobiology and neurological diseases.

Authors:  Ye Chen; Jun Zhou
Journal:  Metab Brain Dis       Date:  2017-02-04       Impact factor: 3.584

3.  Identification of a Novel Mucin Gene HCG22 Associated With Steroid-Induced Ocular Hypertension.

Authors:  Shinwu Jeong; Nitin Patel; Christopher K Edlund; Jaana Hartiala; Dennis J Hazelett; Tatsuo Itakura; Pei-Chang Wu; Robert L Avery; Janet L Davis; Harry W Flynn; Geeta Lalwani; Carmen A Puliafito; Hussein Wafapoor; Minako Hijikata; Naoto Keicho; Xiaoyi Gao; Pablo Argüeso; Hooman Allayee; Gerhard A Coetzee; Mathew T Pletcher; David V Conti; Stephen G Schwartz; Alexander M Eaton; M Elizabeth Fini
Journal:  Invest Ophthalmol Vis Sci       Date:  2015-04       Impact factor: 4.799

4.  Emerging Role of Long Noncoding RNAs in Perioperative Neurocognitive Disorders and Anesthetic-Induced Developmental Neurotoxicity.

Authors:  Tarun Pant; Johanna K DiStefano; Sara Logan; Zeljko J Bosnjak
Journal:  Anesth Analg       Date:  2021-06-01       Impact factor: 6.627

Review 5.  Prospero-related homeobox 1 (Prox1) at the crossroads of diverse pathways during adult neural fate specification.

Authors:  Athanasios Stergiopoulos; Maximilianos Elkouris; Panagiotis K Politis
Journal:  Front Cell Neurosci       Date:  2015-01-26       Impact factor: 5.505

6.  Identification of Differentially Expressed Genes through Integrated Study of Alzheimer's Disease Affected Brain Regions.

Authors:  Nisha Puthiyedth; Carlos Riveros; Regina Berretta; Pablo Moscato
Journal:  PLoS One       Date:  2016-04-06       Impact factor: 3.240

7.  Expression profiles of long noncoding RNAs and mRNAs in post-cardiac arrest rat brains.

Authors:  Rong Liu; Xiaoxing Liao; Xin Li; Hongyan Wei; Qing Liang; Zuopeng Zhang; Meixian Yin; Xiaoyun Zeng; Zijing Liang; Chunlin Hu
Journal:  Mol Med Rep       Date:  2018-03-07       Impact factor: 2.952

Review 8.  The Role of Long Noncoding RNAs in Central Nervous System and Neurodegenerative Diseases.

Authors:  Chang-Wei Wei; Ting Luo; Shan-Shan Zou; An-Shi Wu
Journal:  Front Behav Neurosci       Date:  2018-09-28       Impact factor: 3.558

9.  Long Non-coding RNAs Associated With Neurodegeneration-Linked Genes Are Reduced in Parkinson's Disease Patients.

Authors:  Maximilianos Elkouris; Georgia Kouroupi; Alexios Vourvoukelis; Nikolaos Papagiannakis; Valeria Kaltezioti; Rebecca Matsas; Leonidas Stefanis; Maria Xilouri; Panagiotis K Politis
Journal:  Front Cell Neurosci       Date:  2019-02-22       Impact factor: 5.505

Review 10.  Current status and potential challenges of mesenchymal stem cell-based therapy for malignant gliomas.

Authors:  Qing Zhang; Wei Xiang; Dong-Ye Yi; Bing-Zhou Xue; Wan-Wan Wen; Ahmed Abdelmaksoud; Nan-Xiang Xiong; Xiao-Bing Jiang; Hong-Yang Zhao; Peng Fu
Journal:  Stem Cell Res Ther       Date:  2018-08-24       Impact factor: 6.832

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