Noncoding RNA Expression During Viral Infection: The Long and the Short of It

  • Laurence JossetEmail author
  • Jennifer Tisoncik-Go
  • Michael G. Katze
Part of the Progress in Inflammation Research book series (PIR)


New technologies have expanded our view of viral–host interactions with the growing identification of non-coding RNAs (ncRNAs) that act as key regulators of viral infection. In this chapter, we explore novel genomics-based approaches used to characterize ncRNAs involved in viral infection, focusing mainly on microRNAs and long noncoding RNAs. We present recent evidence implicating virally encoded and host-derived ncRNAs in viral replication and pathogenesis regulation, focusing on four different viral diseases (IAV, KHSV, HIV, and HBV). Finally, we discuss the current knowledge of ncRNAs modulation of innate and adaptive immune responses to viral infection. These findings highlight the complexity of host–pathogen networks determining the outcome of viral disease. Understanding the role of ncRNAs in these networks may offer novel antiviral therapy and diagnostic tools.


miRNA Expression West Nile Virus Japanese Encephalitis Virus Simian Immunodeficiency Virus Lock Nucleic Acid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

1 Introduction

Less than 2 % of the mammalian genome encodes protein-coding genes, while the majority of the genome is pervasively transcribed. This suggests that most of the mammalian transcriptome consists of noncoding transcripts. Noncoding RNAs (ncRNAs) comprised of microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and Piwi-interacting RNA (piRNA), to name a few, regulate a variety of diverse cellular and organismal processes. Since the discovery of RNA interference in nematodes 20 years ago [1, 2, 3], ncRNAs have garnered a great deal of attention, in particular for their role in pathogen–host interactions. To date, there are over 24,000 miRNA loci from 206 species registered with miRBase, a primary miRNA sequence repository that has grown tremendously with small RNA deep sequencing [4]. LncRNAs have been emerging more recently as key regulators of diverse cellular processes, including viral infection. In general, they are defined as transcripts that have at least 200 nucleotides and which lack any positive-strand open-reading frames longer than 30 amino acids. The number of lncRNAs is still a matter of debate, with, in humans, between 9,277 manually annotated lncRNA genes producing 14,880 transcripts present in GENCODE [5], to 56,018 lncRNA genes producing 95,135 transcripts in NONCODEv4 [6]. The nomenclature of lncRNAs is constantly evolving and they have been classified according to their location with respect to protein-coding genes: intergenic (lincRNA), antisense, sense exonic, and sense nonexonic [6]. In contrast to miRNAs that have a well-defined function in the cytoplasmic compartment by translational inhibition and/or degradation of target mRNAs, lncRNAs have a wide range of functions through diverse molecular mechanisms (reviewed in [7]). This chapter aims to summarize our current knowledge of miRNA and lncRNA roles in the context of viral infection in mammals, with a specific focus on ncRNA regulation of viral replication and immune responses.

2 Virus-Encoded ncRNAs

Mammalian viruses are highly diverse etiologic agents that can cause an array of human disease. Virus replication and the cellular responses activated to combat infection coordinately determine virus-induced pathogenesis. Similar to what is found in the host genome, viruses can encode small noncoding transcripts, or virally encoded miRNAs, that are more prevalent in DNA viruses due to their much larger genomes and their ability to replicate in the nucleus and cause persistent infection.

Virus miRNA expression was first reported in the context of Epstein–Barr virus (EBV) infection. Small RNAs cloned from a Burkitt’s lymphoma cell line latently infected with EBV were found to originate from the virus including two miRNAs from the introns of the BARTS (BAMHI A rightward transcripts) [8]. Since then, more than 200 viral miRNAs have been identified from large DNA viruses of the Herpesviridae family. Similar to host-derived miRNAs, virally encoded miRNAs are approximately 22 nucleotides in length and primarily regulate gene expression by binding to sequences located in the 3′ untranslated region (UTR) of target mRNAs through their “seed” region. Viral lncRNAs, on the other hand, are often smaller than 200 nucleotides that have been described for host lncRNAs. There are several novel classes of viral ncRNAs, including influenza A virus small viral RNAs (svRNA) [9], West Nile virus subgenomic flavivirus RNA (sfRNA) [10], Herpesvirus saimiri small nuclear RNAs [11], and the chimeric HBx-LINE1 viral-human gene fusion transcript, that functions as a hybrid RNA [12]. Retroviral antisense ncRNAs, such as HIV antisense lncRNA, regulate viral transcription by directing epigenetic silencing complexes to the LTR [13]. The HBZ antisense transcript of human T-lymphotrophic virus 1 (HTLV-1) is consistently expressed in adult T-cell leukemia/lymphoma (ATL) cells and codes for a multifunctional protein that positively correlates with proviral load and disease severity associated with HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) [14]. The roles of these ncRNAs in viral replication and pathogenesis remain poorly understood; however, HBZ antisense transcript, for example, could be a predictive biomarker of disease.

Viral ncRNAs are capable of regulating a variety of viral and cellular processes, including viral latency, apoptosis, and immunity. For instance, Kaposi’s sarcoma-associated herpesvirus (KSHV) encodes over 90 genes and has an abundant number of miRNAs, 12 of which are expressed from two latency-specific promoters that regulate the expression of latent viral proteins ORF71, ORF72, ORF73, and KapB controlling KSHV latency [15]. KSHV-encoded miRNAs can regulate cellular transformation and tumorigenesis [16] and target TLR-responsive genes, IRAK1 and MYD88, to reduce herpesvirus-induced inflammation [17]. Virally encoded miRNA mimics of cellular miRNAs have also been discovered. For example, KSHV miR-K12-11 is highly homologous to cellular miRNA-155, known to function as an oncogene, with both miRNAs containing identical seed regions critical for target recognition and downregulating a common set of mRNA targets [18]. The viral miR-155 analog is thought to contribute toward KSHV-associated malignancies in infected patients, a viral mimic strategy similar to herpes simplex virus 1 (HSV-1) γ134.5 protein with homology to cellular GADD34 controlling host protein synthesis [19]. In addition to human gammaherpesviruses, DNA virus families with members known to encode miRNAs include Polyomaviridae, Adenoviridae, Ascoviridae, and Baculoviridae (reviewed in [20]). The current knowledge of virally encoded ncRNAs and their cellular targets is summarized in Table 1.
Table 1

Viral-encoded ncRNAs and their cellular target genes and pathways

Virus family or subfamily


ncRNA type

ncRNA name

Functional role and cellular targets





Antisense transcript

Epigenetic regulation of gene expression



U3 antisense transcripts

Insertional activation of cellular proto-oncogenes Jdp2 and Bach2



HBZ transcript

Promotes T-cell lymphoma; CREB-mediated inhibition of cyclin D1; regulates hTERT transcriptional activity

[22, 23, 24]








Modulator of apoptosis PUMA



Pro-apoptotic protein BIM



Promotes cell cycle progression and proliferation; inhibits apoptosis






EBER-1 (166 nt) and EBER-2 (172 nt)

Promotes cellular proliferation and transformation; inhibits apoptosis







miR-K12-1, 3 and 4-3p

Targets CASP3 to regualte apoptosis


miR-K12-9-5p and miRK12-7-5p


[33, 34]


targets IKKε to modulate IFN signaling





miR-K12-1, miR-K12-6-5p, miR-K12-11




Targets Rbl2 to regualte global epigenetic reprogramming


miR-K12-9 (miR-K9) and miR-K5

IRAK1 and MYD88


miR-K1, miR-K3-3p, miR-K6-3p, miR-K11







miR-K12-3, miR-K12-7

C/EBPbeta p20 (LIP)




[18, 42]



Multifunctional transcript regulating viral replication and host response

[43, 44]













miR-UL112, miR-K12-7, miR-BART2-5p


[47, 48]

miR-K5; miR-K9; miR-K10a/b


[49, 50, 51]



H. saimiri U-rich nuclear RNAs (HSURs)

HSUR 1 and 2 bind specific host miRNAs in virally transformed T cells. HSUR 1 downregulates cellualr miR-27a









PU.1, GPM6B, RREB1, c-Myb, MAP3K7I, P2 PU.1, C/EBP








Noncoding subgenomic flavivirus RNA (sfRNA)

Required for viral pathogenicity and evasion of the type I interferon response





Influenza A virus-derived small viral RNAs (svRNAs)

Interacts with the viral RdRNP to initiate the switch from viral transcription to replication


3 Genomics-Based Approach to Identify and Characterize Host-Encoded ncRNAs Involved in Host-Response to Viral Infection

Initial studies of ncRNAs were based on conventional molecular biology techniques including RT-PCR and northern blot, characterizing the expression of single ncRNAs. The landscape of ncRNAs has widely expanded with recent advancements in sequencing technologies and computational biology.

3.1 Methods for Genome-Wide Characterization of ncRNA Expression

Large scale gene expression analysis has been dominated by DNA microarray since its development in the 1990s. Array technologies provide simultaneous quantification of tens of thousands of transcripts and have been widely used to characterize transcriptomic responses of cells, animal models, and human patients to virus infection (reviewed in [55]). Accurate detection and quantification of miRNAs poses several challenges that include the lack of common sequences for their purification, the high sequence similarity among miRNA within the same family, and the presence of natural variants of miRNAs, called isomiRs, which result from post-transcriptional nucleotide additions or deletions to 3′ and 5′ ends of mature miRNAs (reviewed in [56]). Various microarray-based strategies for profiling miRNA expression have been developed, including different approaches for fluorescent labeling of the miRNA for subsequent hybridization to classical DNA-based probes or locked nucleic acid (LNA)-modified capture probes (reviewed in [56]). LncRNA-specific microarrays offer less technical variations and they mainly differ by the number of lncRNAs targeted by DNA probes present on the chip. At the time of writing, lncRNA microarrays include Agilent® custom arrays by GENECODE targeting 11,880 human lncRNA transcripts [5] (22,001 lncRNAs transcripts in the newest version), Arraystar® LncRNA human and mouse arrays targeting ~30,600 and ~31,423 lncRNA transcripts, respectively, and Affymetrix® Human Gene ST Array covering 11,000 lncRNA RefSeq transcripts. The main limitations of microarray-based characterization of ncRNA are a restricted linear range of quantification and their dependence on the prior knowledge of annotated transcripts for probe design. In addition, microarrays can have imperfect specificity in some cases for miRNAs that are closely related in sequence.

The recent development of next-generation sequencing (NGS) platforms has enabled a novel approach for ncRNA expression profiling by RNA-Seq. RNA-Seq relies on the preparation of a cDNA library from the RNA sample of interest, followed by the “massively parallel” sequencing of millions of individual cDNA molecules from the library. The method of cDNA library construction used determines the type of transcripts to be sequenced: small RNA-Seq for sequencing of miRNAs, small nuclear (sn), small nucleolar (sno), and piwi-associated (pi)RNAs; mRNA-Seq for sequencing various types of polyadenylated transcripts; and total RNA-Seq for sequencing whole transcriptomes (all transcripts after ribosomal RNA (rRNA) removal). Remarkably, as many lncRNA transcripts may not be polyadenylated [57, 58], it is important to use total RNA-Seq approaches for the comprehensive detection of lncRNAs. Compared to microarray, RNA-Seq has a wider dynamic range, higher precision, and reproducibility [59, 60, 61], and is able to distinguish ncRNA that differ by as few as one nucleotide. Importantly, because RNA-Seq does not require prior transcript annotation for probes, novel transcripts can be detected, including both protein-coding and ncRNA transcripts, as well as RNA with somatic mutations and alternative splicing forms [62, 63]. The main limitations of RNA-Seq are the computational infrastructure required for data analysis, interpretation, and storage. The cost associated with sequencing can also be a limiting factor, though newer technologies, such as Illumnina NextSeq, are enabling quicker run times to generate up to 400 million clusters with a more cost-effective system that is used to store, analyze, and share genomic data.

3.2 Methods to Computationally Infer ncRNA Function

3.2.1 miRNA Annotation, Analysis, and Target Prediction

A number of tools are available for miRNA annotation, analysis, and target prediction (reviewed in [64]). The miRBase database is the primary online repository for miRNA sequences and annotation [4]. Several software packages predict novel miRNAs from RNA-Seq data, including miRDeep [65] and mirTools [66]. Finally, many miRNA target prediction tools have been published. These tools indirectly predict miRNA function, as miRNAs binding to the 3′ UTR of their mRNA target lead to the degradation or the translational repression of the target mRNA. Target prediction tools are based on sequence comparisons between mature miRNA and 3′ UTRs in candidate mRNA targets. Three widely used algorithms that have enhanced mRNA target prediction include TargetScan [67], miRanda [68], and DIANA-microT [69]. The best algorithms currently identify 60 % of all available targets and provide one valid target in approximately every three predicted targets [64], highlighting the importance of experimental validation.

3.2.2 lncRNA Annotation and Function Prediction

Many online databases are available for lncRNA annotation, some of which include predicted or experimentally validated lncRNA functions [6, 70, 71, 72, 73, 74, 75]. Identifying lncRNA functions is especially challenging because of the large number of lncRNAs and the variety of mechanisms driving their functions. With the large amount of transcriptome data created by microarray and RNA-Seq technologies, predicting gene function on the basis of expression has been proposed as an attractive strategy [76]. One approach for predicting function of both coding and noncoding genes is the “guilt by association” approach, which relies on finding which RNAs have similar expression profiles to protein-coding genes of known function. Several methods have been used to infer co-expression networks with the objective of predicting gene function: algorithms using the concept of mutual information (MI) [77, 78]; random matrix theory (RMT) [79]; and correlation analysis such as weighted gene co-expression network analysis (WGCNA) [80, 81]. This strategy was applied to mouse lncRNAs after re-annotation of the Affymetrix Mouse Array using 34 datasets derived from diverse mouse tissues and allowed the functional annotation of 340 lncRNAs mainly involved in development, cellular transport, and metabolic processes [81]. A similar method was also applied for lncRNA function annotation based on RNA-Seq data [82]. Many intergenic long noncoding RNAs (lincRNAs) that were co-expressed with genes in the p53 pathway were further validated as p53 transcriptional targets, including lincRNA-p21 which serves as a repressor in p53-dependent transcriptional responses [83]. Similarly, Hu et al. inferred potential functions of lincRNAs in T cells by analyzing their co-expression with coding genes and showed that the expression of LincR-Ccr2-5′AS was correlated with the expression of genes within a chemokine-mediated signaling pathway [84]. The knockdown of LincR-Ccr2-5′AS decreased the expression of its neighboring chemokine receptor-encoding genes.

Recently, we predicted the function of 5,329 lncRNAs involved in pulmonary responses to influenza A virus or SARS-CoV infection by using WGCNA and two levels of annotation: (1) a coarse annotation based on lncRNA membership within a co-expression module and (2) a finer rank-based annotation method [85]. This analysis identified many lncRNAs induced after viral infection and that were closely associated with interferon (IFN) response genes (Fig. 1).
Fig. 1

Example of six lncRNAs induced in mouse lung after respiratory virus infection and co-expressed with interferon response genes. These lncRNAs: n280936, n280698, n281722, n276967, n295716, and n287176, depicted in bold in the figure, also have binding motifs for IRF9 in their promoters. The network shows the co-expression associations between each lncRNA and top 15 most correlated genes. Nodes in the graph represent the coding or lncRNA genes while edges represent the significant co-expression associations. Based on whole network topology, n280936, n280698, and n295716 were classified as hubs of the interferon response module. The lncRNA-coding genes co-expression network was visualized using the Mouse NOnCode Lung database (MONOCLdb) at The MONOCLdb contains annotations, expression profiles, and functional enrichment results of lncRNA expressed in Collaborative Cross founder mice in response to respiratory infection caused by influenza and SARS-CoV [52]

3.3 Genome-Wide Characterization of ncRNA Expression During Viral Infection

Microarrays have been widely used to characterize miRNA expression in response to viral infections, with more than 100 publications referenced in PubMed to date. Among them, analysis of miRNAs expressed in the lung of mice following infection with influenza A virus found 130 cellular miRNAs were differentially regulated, with distinct expression patterns in response to highly pathogenic 1918 H1N1 virus compared to a nonlethal seasonal H1N1 influenza virus [86]. Some of these miRNAs had predicted mRNAs targets with anti-correlated expression levels, such as miR-200a and sip1, that were enriched in immune response and cell death pathways, suggesting that type I IFN singaling and CREB activity linked with the high virulence of 1918 pandemic influenza virus may be regulated by miRNAs.

RNA-Seq analysis has also been used to study the ncRNA response to respiratory virus infection. Peng et al. identified over 1,500 lncRNAs and 200 small RNAs, such as snRNAs and piRNA, expressed in mouse lung in response to SARS-CoV or influenza A virus [87, 88]. Using a large RNA-Seq dataset consisting of a wide-range of pulmonary transcriptional responses during SARS-CoV and influenza infection, we have expanded upon this analysis and identified 5,329 lncRNAs differentially expressed after infection in the lungs of 8 genetically diverse mouse strains [85]. These lncRNAs accounted for about 40 % of total genes differentially expressed upon viral infection. Most of the upregulated lncRNAs were related to the innate immune response and were co-expressed with genes specific to immune cells, suggesting they might be associated with immune cell infiltration of the lung following infection (Fig. 1). Some of these lncRNAs were highly connected (hubs) in the interferon-response co-expression module and could therefore have a role in controlling type I IFN signaling during viral infection [85].

Finally, RNA-Seq analysis of ncRNA expression in a CD4+ T cell line identified over 1,000 lncRNAs and 531 miRNAs differentially expressed upon HIV-1 infection [88, 89]. Integration of mRNA-Seq and small RNA-Seq data identified 5,023 anticorrelated interactions involving 46 differentially expressed miRNAs predicted to target as many as 518 mRNAs, including target genes with transcription regulatory activity, such as P/CAF (P300/CBP-associated factor), and genes within T cell activation-related pathways. The downregulation of miRNAs may have contributed to increased T cell receptor signaling.

4 Role of Host and Viral ncRNA in Regulating Viral Replication and Pathogenesis

Host and viral ncRNAs can impact viral replication and pathogenesis. For example, ncRNAs can influence poliovirus tissue tropism [90], Coxsackie A21 virus-induced myositis [91], hepatotoxicity associated with oncolytic adenoviruses [92], and HIV control of HLA-C expression [93]. Here, we focus on how host and viral ncRNAs impact the replication or pathogenesis of influenza A virus, KSHV, HIV, and HBV infection associated with hepatocellular carcinoma.

4.1 Influenza A Virus

Influenza virus is a respiratory pathogen that causes significant morbidity and mortality, with over 200,000 people hospitalized from infection each year in the United States alone. Influenza H1N1 and H3N2 viruses circulate within the human population and on occasion new viruses emerge as a result of gene reassortment, the shuffling of viral gene segments from different influenza A viruses. This in turn can give rise to a worldwide pandemic, as demonstrated by the recent 2009 pandemic H1N1 influenza virus that originated in swine due to a reassortment event between swine H1N1 and human H3N2 viruses.

4.1.1 Influenza svRNA

It has been generally accepted that RNA viruses do not transcribe ncRNAs; however, this notion is beginning to change with NGS technologies. For influenza A virus (IAV), a segmented negative-strand RNA virus, deep sequencing has captured small viral RNAs (svRNA) varying between 22 and 27 nucleotides in length originating from all eight genomic segments of the virus. The production of svRNAs is dependent on the IAV RNA-dependent RNA polymerase (RdRp), comprised of polymerase subunits, PB1, PB2, and PA, and corresponds to the shift from IAV transcription to replication. Unlike other virally encoded small ncRNAs, IAV svRNAs do not induce host antiviral defenses (e.g., IRF3 activation or IFNβ induction), but they were found to be important for viral replication. For instance, the use of LNA complementary to segment 4 svRNA (HA svRNA) significantly reduced HA vRNA synthesis resulting in decreased HA protein levels and reduced influenza H1N1 virus replication in cell culture [9].

4.1.2 Host lncRNA Regulation of Influenza Replication

VIN is a nuclear lncRNA, the expression of which is strongly increased 10–60-fold in human lung epithelial cells in response to H1N1, H3N2, or H7N7 IAV infection [94]. Interestingly, this lncRNA is not increased following infection with influenza B virus, IFNβ treatment, or TLR3 stimulation by polyI:C. Silencing of VIN decreases influenza virus replication suggesting that VIN could be a proviral factor, but its mechanism of action has not yet been determined. Silencing of another lncRNA named NRAV was found to decrease influenza virus replication in vivo and in vitro. However, NRAV was downregulated following viral infection, which increasing ISG induction and thereby inhibiting influenza virus replication [95].

4.2 Human Immunodeficiency Virus

There are more than 35 million people living with HIV in the world today. The retrovirus targets CD4+ T cells and their depletion facilitates a patient’s progression toward acquired immunodeficiency syndrome (AIDS) if left untreated. Mucosal transmission is one of the primary routes of HIV transmission and mucosal immune responses have been suggested to control systemic infection after virus exposure. Deep sequencing is revealing new insight into mucosal immunity against HIV and in particular, changes in ncRNA expression and their potential role in viral pathogenesis and HIV-associated disease.

4.2.1 Host ncRNAs Involved in Mucosal Immunity Against HIV

MiRNAs regulate intestinal epithelial differentiation, architecture, and barrier function [96], which are disrupted during HIV infection in part due to the rapid depletion of CD4+ T cells in the gastrointestinal tract [97]. In a nonhuman primate model of AIDS, simian immunodeficiency virus (SIV) infection decreased the expression of mucosal miRNAs (e.g., miR-16, -194, and -200c) involved in epithelial homeostasis of the gut and coincided with increased 5′–3′-exoribonuclease 2 (XRN2) protein expression and altered levels of miRNA biogenesis machinery components, DICER1 and Argonaute 2 (AGO2) [98]. In this same study, miRNA profiled from total RNA extracted from jejunal biopsy specimens from HIV-infected and HIV-negative patients also found reduced intestinal miRNA expression in patients chronically infected with HIV. These findings suggest that the gut mucosal response to viral infection involves decreased miRNA expression likely impairing epithelial cell growth and development during SIV and HIV infections. In a separate study, co-expression analysis between differentially expressed lncRNAs and coding genes revealed the downregulation of transcripts in rectal mucosa of rhesus macaques infected with SIV that were associated with wound healing, cell–cell adhesion, and tissue formation during acute SIV infection [99]. Taken together, alteration of the local microenvironment in the small intestine through ncRNA downregulation could lead to the dissemination of virus and intestinal enteropathy.

4.2.2 Viral Antisense lncRNA Involved in HIV Latency

After entering a cell, retroviruses integrate into the host genome where viral genes can be transcribed or remain latent. In addition to viral genomic sense RNA and mRNA, several retroviruses, including HIV, encode antisense RNAs (asRNAs) that are transcribed during infection (Table 1). Kobayashi-Ishihara et al. report the transcription of an apparent major form of HIV asRNAs, ASP-L, in HIV-1-infected cells. This transcript is localized in the nucleus and inhibits HIV-1 replication [100]. The molecular mechanism of HIV asRNA action was recently elucidated [13]. It is involved in the epigenetic regulation of viral transcription through its recruitment of DNMT3a and possibly other chromatin-remodeling proteins, such as enhancer of Zeste 2 (EZH2) and histone deacetylase 1 (HDAC-1), to the viral promoter (5′LTR). This complex induces a repressive chromatin state, which epigenetically silences the transcription of viral genes. Together with viral asRNAs, cellular lncRNAs may also be involved in regulating proviral HIV latency, as many lncRNAs function as epigenetic regulators [101, 102].

4.2.3 Host lncRNA Controlling HIV Replication

A host lncRNA named NEAT1 was shown to directly control HIV replication. NEAT1 is an essential structural component of paraspeckles, which are nuclear bodies rich in RNA-binding proteins and splicing factors. Recently, NEAT1 was found upregulated in human cell lines infected with HIV-1 [103]. Silencing of NEAT1 decreased nuclear paraspeckle bodies and was associated with enhanced HIV expression and increased levels of unspliced HIV transcripts in the cytoplasm. Zhang et al. hypothesized that NEAT1 modulates HIV-I replication by promoting HIV mRNA nuclear sequestration in paraspeckles; however, Imamura et al. recently described that silencing of NEAT1 impairs the induction of numerous genes including antiviral factors following TLR3 stimulation [104]. Therefore, the effect of NEAT1 on HIV replication may also be indirect and mediated by dysregulation of the antiviral host response.

4.3 Kaposi’s Sarcoma-Associated Herpesvirus

Kaposi’s sarcoma-associated herpesvirus KHSV is a gammaherpesvirus causing several human cancers and lymphoproliferative disorders, including Kaposi’s sarcoma (KS), primary effusion lymphoma (PEL), and a subset of multicentric Castleman’s disease (reviewed in [105]). Like other herpesviruses, KSHV infection is characterized by two states: viral latency and lytic growth. During latency, very few viral genes are expressed, reducing the number of viral epitopes available to trigger a host immune response. KSHV latent genomes are bound to host histones and can form either minichromosomes or episomes, which are epigenetically regulated [106]. Upon stimulation by various stress responses, KSHV activates the lytic program of its replication cycle to produce new infectious viral particles. Disruption of the repressive viral chromatin state is essential for KSHV reactivation, and it is mediated by viral proteins and ncRNAs [106].

4.3.1 miRNA Regulation of KSHV Replication

Early and late miRNA expression in primary lymphatic endothelial cells (LECs) infected with KSHV regulates the antiviral response by facilitating viral gene expression. Early-response miR-132 is highly upregulated after infection, which affects viral gene expression by suppressing transcriptional co-activator p300. Silencing of p300 in LECs impairs antiviral responses to KSHV by decreasing IFNβ, ISG15, IL-1β, and IL-6 mRNA expression. Conversely, the inhibition of miR-132 induction suppresses KSHV replication in LECs, resulting in increased IFNβ mRNA levels. A similar phenomena is observed with herpes simplex virus-1 (HSV-1)- and human cytomegalovirus (HCMV)-infected monocytes where virus-induced host miR-132 inhibits p300 expression [107].

4.3.2 lncRNA Control of KSHV Replication

KSHV encodes a viral lncRNA known as polyadenylated nuclear RNA (PAN RNA), which was discovered 18 years ago as the most abundant transcript produced during the lytic phase [108]. Several reports suggest that PAN RNA is a multifunctional regulatory transcript and plays an important role in KSHV replication [43, 44, 109, 110, 111]. PAN RNA interacts with several host factors, including histones H1 and H2A and chromatin modifiers, such as lysine demethylases UTX and JMJD3, and the histone methyltransferase MLL2 [109]. These interactions remove H3K27me3, a repressive chromatin marker within the KSHV genome [109]. PAN RNA also mediates changes in histone modifications by binding the Polycomb repressive complex 2 (PRC2) [110]. In addition, PAN RNA interacts with the viral latency-associated nuclear antigen (LANA), which is a transcriptional repressor associated with latent viral episomes. Upon reactivation, PAN RNA sequesters LANA away from the viral episome [44]. Finally, PAN RNA interacts with the host poly(A)-binding protein C1 PABPC1, which allows late viral mRNA exportation and translation. In addition to its role in regulating viral replication, PAN RNA also acts on cellular gene expression, modulating the expression of genes involved in cell cycle, immune response, and production of inflammatory cytokines [43, 110]. To date, there are no known host lncRNAs reported to directly regulate KSHV replication. However, similar to HIV, host lncRNAs that regulate chromatin state could also potentially control KSHV episomal latency [101, 102].

4.4 Hepatocarcinoma Associated with Hepatitis B Infection

Hepatitis B virus (HBV) is an oncogenic virus belonging to the Hepadnaviridae family of DNA viruses. HBV infection is the leading cause of acute and chronic hepatitis B, liver cirrhosis, and it is a major risk factor of hepatocellular carcinoma (HCC). Nearly 2 billion people are infected with HBV worldwide and more than 350 million are reported to be chronic HBV carriers. Many host cellular ncRNAs are involved in HCC (reviewed in [112]) in addition to specific viral ncRNA that can facilitate oncogenesis.

4.4.1 Viral-Human Chimeric lncRNA

After infection, HBV not only replicates as an episome, but HBV DNA can also integrate into the host genome, leading to chromosomal rearrangements and deletions. In most integrated subviral DNAs, X-ORF is maintained and the HBx gene transcribed at low levels during acute and chronic hepatitis (V. Schluter et al., Oncogene 1994). Such integration has been linked to liver cancer formation, with 85–90 % of HBV-associated HCC tumors having at least one HBV insertion [113]. Recently, Lau et al. detected a specific integration site of HBV into a transposable LINE1 element in chromosome 8 for about 23 % of HBV-HCC cases in a cohort of 90 patients [12]. [114] This integration leads to a chimeric viral-human transcript, HBx-LINE1. Silencing of HBx-LINE1 inhibits cell motility and Wnt/β-catenin signaling. The HBx-LINE1 fusion transcript encodes for a fusion protein; but unexpectedly, its oncogenic effect is dependent on the HBx-LINE1 mRNA and not protein expression. It was therefore concluded that HBx-LINE1 functions as a lncRNA. Moreover, HBx-LINE1 transgenic mice had increased risk of HCC development proving the oncogenic role of the HBx-LINE1 transcript.

4.4.2 Host lncRNA Regulating HBV- and HCV-HCC

Several cellular lncRNAs are differentially expressed in HCCs, including MALAT1, HULC, H19, HEIH, HOTAIR, MEG3, uc002mbe.2, lncRNA-LET, MVIH, and Dreh (reviewed in [115]). Interestingly, these lncRNA could provide prognostic and diagnostic markers of HCC [112]. Most of these lncRNAs have general oncogene-like effects and only two of them, HULC and Dreh, have been directly linked to HBV infection. Highly Upregulated in Liver Cancer (HULC) is upregulated in HBV-HCC and correlated with HBx levels [116]. HBx activates the HULC promoter through its interactions with the transcription factor cAMP-responsive element-binding protein (CREB) [117]. Interestingly, a genetic variation in HULC (rs7763881) is associated with a low-risk susceptibility to HCC in HBV-persistent carriers [118]. Another lncRNA found to be regulated by HBx is Dreh, which is downregulated in HBx transgenic mice and in human HBV-related HCC tissues [119]. Dreh acts as a tumor suppressor by changing the normal cytoskeleton structure to inhibit tumor metastasis [119].

5 Role of ncRNA in Immune Responses to Virus Infection

Innate immune sensing is a host’s first line of defense against invading pathogens. Cellular membrane-bound Toll-like receptors (TLRs) and cytosolic pathogen recognition receptors (PRRs), such as RIG-I and MDA-5, recognize pathogen-associated molecular patterns (PAMPs) present in genomic viral RNA. These viral molecular motifs initiate signaling cascades that culminate in interferon regulatory factor (IRF)-mediated transcription of IFNβ gene expression. IFNβ is then secreted from the cell and in an autocrine and paracrine manner binds to type I IFN receptor (IFNAR) expressed on the plasma membrane to induce hundreds of interferon-stimulated genes (ISGs), many with well-known antiviral effector functions. A host must be able to withstand physiological and oxidative stresses triggered by viral infection, such as the effects of NFκB-regulated pro-inflammatory cytokines, including TNF, IL-1, IL-6, and IL-8. Interferon, while the hallmark of innate immunity, is no longer the only major player in initiating and modulating antiviral defenses. As we have discussed, ncRNAs have widespread functions in a variety of cellular processes and the relationship between ncRNA regulation, innate immunity, and inflammatory responses is becoming increasingly clear. Here, we will discuss the current knowledge of ncRNA induction and modulation of innate and adaptive immunity in the context of pathogen–host interactions (Fig. 2).
Fig. 2

miRNAs and lncRNAs modulate innate immune response to viral infection. The innate immune-sensing pathway diagram was generated through the use of IPA (Ingenuity® Systems, MiRNAs are shown in blue and lncRNAs are shown in red. The cellular targets regulated by these ncRNAs are indicated

5.1 Activation of Innate Immune Responses by miRNAs

David Baltimore was among the first to study TLR-induced miRNA expression in response to a variety of microbial stimuli. Lipopolysaccharide (LPS), a component of the outer membrane of Gram-negative bacteria, is a strong stimulant of innate immune responses and a TLR4 agonist. When used to treat human monocytic THP-1 cells, LPS induces significant differences in miRNA expression [120]. Widespread and transient changes in miRNA expression have also been observed in the lung of mice exposed to LPS, further emphasizing ncRNA changes among transcriptional responses to microbial products. Among the miRNAs profiled in LPS-stimulated THP-1 cells, miR-146a/b, in particular, was significantly induced by pro-inflammatory mediators NFκB, TNF, and IL-1β [120]. Computational analyses identified TRAF6 and IRAK1, downstream kinases of TLR4, as targets for posttranscriptional repression by miR-146a/b based on near perfect complementarity to the miR-146a/b seed sequences (Fig. 2). This early evidence indicated that TLR could induce a potential new class of signaling regulators in response to pathogens and under pro-inflammatory conditions. Indeed, TRL4-responsive miR-146a was largely increased in human airway epithelial cells infected with human H3N2 influenza virus [121]. In a separate study, Cryptosporidium parvum, a protozoal species that causes cryptosporidiosis, was found to upregulate TLR4 in infected human biliary epithelial cells, which was concomitant with changes in ncRNA expression, such as decreased let-7i expression [122]. While enhancing innate immune signaling, miRNA expression can have the opposite effect on pro-inflammatory mediator production. For example, increases in miRNA expression was accompanied by decreased TNF, KC, a mouse cytokine involved in neutrophil chemotaxis and cell activation, and macrophage inflammatory protein (MIP)-2 expression in vivo, suggesting dual miRNA function in the modulation of host inflammatory responses [123].

In addition to miR-146, changes in the expression levels of several other miRNAs, including miR-155, miR-132, and miR-125b, have been associated with the activation of the innate immune response [124]. Cellular miR-155 is considered a lymphoma-associated oncomir and was recently found to modulate pro-inflammatory activities of different immune cell types, including macrophages [125], monocytes, and dendritic cells (DCs) [126, 127]. In human plasmacytoid DCs, miR-155 expression is increased in an NFκB- and Jnk-dependent manner that resulted in negative regulation of IFNα production [128]. While miR-155 was shown to negatively regulate IFNα expression, a separate study argued that miR-155 promotes type I IFN signaling in antiviral immunity by targeting SOCS1 [129]. Cellular mechanisms aimed at attenuating pro-inflammatory responses also target miR-155-mediated activity, including IL-10, which inhibits miR-155 and acts as a negative regulator of miR-155-mediated pro-inflammatory responses [126]. Taken together, miR-155 not only acts as a regulator of interferon responses but also serves as a target of anti-inflammatory factors that help balance miR-155-mediated enhancement of innate immunity.

Japanese encephalitis virus (JEV) is a mosquito-borne virus and a member of the Flaviviridae family that enhances neuroinflammation of the central nervous system. MiR-155 is found to regulate JEV-induced inflammatory responses by targeting Src homology 2-containing inositol phosphatase 1 (SHIP1) 3′ UTR [130]. For example, anti-miR-155 treatment of mice infected with JEV decreases the expression of pro-inflammatory cytokines TNF, MCP-1, and IL-6 in the brain. This in turn improves survival and JEV-associated disease, alleviating behavioral symptoms related to body stiffening and hind limb paralysis [130]. Microglial cell activation is a hallmark of neuroinflammation. MiR-29b was found to be significantly upregulated in JEV-infected mouse microglia (BV-2) and primary microglia cells, regulating microglia activation by targeting TNFα-induced protein 3 (TNFAIP3, also known as A20), a negative regulator of NFκB (Fig. 2) [131]. In response to a separate flavivirus, HCV patients with liver fibrosis have downregulated miR-107 and miR-449a expression, with upregulated CCL2 expression. Both miR-449a and miR-107 were found to regulate IL-6-mediated CCL2 expression and STAT3 phosphorylation by targeting IL-6R and JAK1 in HCV-infected hepatocytes [132]. Taken together, these studies demonstrate a role for miRNA in regulating inflammation in neurologic and liver diseases caused by flaviviruses.

Inflammatory responses are critical for controlling viral infection. One such mechanism is the inflammasome, an intracellular signaling complex that increases IL-1β when activated. Recently, two miRNAs encoded by EBV with sequence homology to miR-223 were shown to target the miR-223 binding site in the NLRP3 3′ UTR and inhibit inflammasome activity [133]. This demonstrates the diverse strategies of virally encoded miRNAs in mimicking cellular miRNA function regulating inflammatory pathways. Endogenous inflammatory mediators called damage-associated molecular patterns (DAMPs) have been suggested to modulate immune responses and inflammation, though their role in the context of viral infection is poorly understood. DAMP molecule, S100A9 (also known as Calgranulin B or MRP-14), enhances inflammation during acute influenza infection by acting as a non-PAMP activator via the TLR4-MyD88 pathway [134]. Interestingly, a new miRNA class known as damage-associated molecular pattern molecule-induced miRNAs (DAMPmiRs) was recently identified in human peripheral blood mononuclear cells [135]. Future studies will likely unveil the role of DAMPmiRs in virus-induced inflammatory responses.

5.2 Regulation of Inflammatory and Innate Immune Responses by lncRNA

Many studies have shown that lncRNAs have central roles in the control of gene expression during cellullar differentiation in the development of diverse organs and tissue types (reviewed in [136]). In addition to their roles in hematopoiesis and leukemogenesis [137, 138, 139], many lncRNAs are involved in immune cell activation (reviewed in [140]). Moreover, some lncRNAs modulate inflammatory and innate immune gene expression following the activation of some TLRs.

Similar to miRNAs, lncRNAs are expressed in response to TLR agonists. In mouse dendritic cells, 20 lncRNAs showed marked upregulation after stimulation with LPS including lincRNA-Cox2, which was not upregulated in TLR3-stimulated cells [82]. LincRNA-Cox2 was also upregulated in mouse macrophages stimulated with TLR2 ligand and following Listeria monocytogenes infection [141]. Silencing and overexpression of lincRNA-Cox2 revealed that the lncRNA regulates distinct classes of immune genes both basally and after TLR stimulation [141]. Using a custom microarray, 159 lncRNAs were found to be differentially expressed following TLR2-stimulation of human macrophages, including THRIL (also known as linc1992), which was found to be downregulated [142]. THRIL and lincRNA-Cox2 both interact with different heterogeneous nuclear ribonucleoproteins (hnRNPs) to bind immune gene promoters. LincRNA-Cox2 forms a complex with hnRNP-A/B and hnRNP-A2/B13 to repress the transcription of some immune genes including chemokine CCL5 gene [141], while THRIL binds hnRNPL to stimulate TNFα gene transcription (Fig. 2) [142].

Aside from these TLR2/TLR4-mediated lncRNA regulations, the lncRNA NEAT1 is induced after TLR3 stimulation and in response to influenza virus, herpes simplex virus 1 (HSV-1) [104], and HIV [103]. Upon infection, viruses detected through TLR3 activate p38 MAPK pathway which leads to NEAT1 induction (Fig. 2). This relocates the transcriptional repressor, SFPQ, from the promoter region of antiviral genes into paraspeckles, leading to the transcriptional activation of antiviral genes such as IL-8 (Fig. 2) [104]. Finally, numerous lncRNAs can be induced in response to cytokine stimulation, such as IFNβ [85, 88] and TNFα [143]. Among the 166 mouse lncRNAs induced by TNFα, a pseudogene transcribed into lncRNA named Lethe is also expressed in response to IL-1β or glucocorticoid receptor agonist, but it is unresponsive to TLR1-7 agonists. Lethe is directly induced by NFκB signaling and acts as a negative feedback inhibitor of NFκB by binding to RelA.

5.3 Regulation of Adaptive Responses by miRNA During Viral Infection

The inflammatory response has been linked to aberrant allergen-specific CD4+ T-helper 2 (TH2) cell function and the recruitment and activation of eosinophils and mast cells in the airways. TH2 cell-induced eosinophilia and airway hyperresponsiveness (AHR), as well as the secretion of a range of cytokines, including IL-4, IL-5, IL-9, IL-10, and IL-13, are hallmark features of allergic asthma, of which the TLR4 signaling pathway is central to the progression of allergic airway disease, as mice deficient in TLR4 signaling have been shown to have an attenuated allergic phenotype [144]. Single miRNAs can have profound effects on the development of pulmonary inflammation. For example, antagonism of miR-126 suppresses the effector function of TH2 cells, including the recruitment of eosinophils and neutrophils into the airways and the overproduction of airway mucus [145].

MiR-155 is upregulated in primary effector and effector memory CD8+ T cells and it is required for lymphocyte responses and effector T cell memory against influenza virus and Listeria monocytogenes. Antiviral CD8+ T cell responses and viral clearance were impaired in miR-155 knockout (KO) mice that exhibited reduced primary and memory responses, whereas CD8+ T cell responses were much more robust when miR-155 was overexpressed in infected mice [146]. MiR-155 has also been investigated for its role in cytotoxic T cell function in response to lymphocytic choriomeningitis virus (LCMV). Mice lacking miR-155 are deficient in primary CD8+ T cell responses following LCMV infection due to impaired Akt signaling that impacts cell survival. After infection, there were reduced numbers of IFNγ-producing T cells found in miR-155 KO spleens compared to wild-type (WT) spleens, as well as differential CD8+ T cell responses in the spleen between WT and KO mice [147].

5.4 Regulation of Adaptive Responses by lncRNA During Viral Infection

Expression of ncRNAs during T cell development was observed almost 30 years ago, with the transcription of the T early alpha (TEA) noncoding transcript in the T-cell receptor alpha chain locus [148] required for V(D)J recombination assembling the variable regions of T cell receptors [149]. Several lncRNAs were also found expressed in activated CD4+ T cells, including NTT [150], and the proto-oncogene, BIC [151].

More recently, systematic characterization of lncRNAs identified over 1,000 lncRNAs dynamically expressed during CD8+ T cell differentiation and activation after exposure to viral antigens [152]. Further exploring lncRNAs involved in T cell function, Hu et al. identified 1,524 regions encoding for lncRNA that were expressed at various developmental and differentiation stages of T cells [84]. The expression of most of them is controlled by T cell-specific transcription factors. Among these lncRNAs, LincR-Ccr2-5′AS was specifically expressed in TH2 cells and its expression was positively correlated with genes involved in chemokine signaling. Silencing of lincR-Ccr2-5′AS by shRNA led to deregulation of many genes, including lower expression of the neighboring Ccr1, Ccr2, Ccr3, and Ccr5 genes. This resulted in reduced migration of TH2 cells to the lung. While the mechanism of gene regulation by lincR-Ccr2-5′AS is still being elucidated, it is known to be distinct from the modulation of chromatin accessibility or recruitment of RNA polymerase II, a common mechanism for lncRNAs to regulate gene expression [153].

One of the most studied lncRNA in viral infection, Tmevpg1 (also named NeST), was initially discovered for its role in Theiler’s virus persistence [154, 155]. Theiler’s murine encephalomyelitis virus (TMEV or Theiler’s virus) is a picornavirus that causes acute infections in mice. In some mouse strains, such as SJL/J, TMEV causes persistent infection of the spinal cord followed by a late chronic demyelinating disease similar to multiple sclerosis in humans. TMEV infection is mainly controlled by the H2D class I gene; however, two other susceptibility loci were mapped on chromosome 10 close to the IFNγ locus and named Tmevp2 and Tmevp3 [156]. The lncRNA Tmevpg1 was identified in the Tmevp3 locus [154] and was expressed in unstimulated T cells and in CNS-infiltrating immune cells of resistant B10.S mice after TMEV infection [155]. While Vigneau et al. initially hypothesized that Tmevpg1 may downregulate the expression of IFNγ, Tmevpg1 was later found to positively regulate the transcription of IFNγ in cooperation with the transcription factor T-bet in CD4+ TH1 T cells [157]. Recently, Gomez et al. showed that transgenic expression of SJL/J-derived Tmevpg1 allele in B10. S mice prevents the clearance of TMEV, yet confers resistance to lethal infection with Salmonella enterica serotype Typhimurium [158]. Therefore, they renamed Tmevpg1 as NeST for “Nettoie Salmonella not TMEV” (clear Salmonella not TMEV). The SJL/J-derived NeST allele also conferred increased resistance to the lethal inflammatory disease caused by LPS injection. In contrast to the previous report of Vigneau et al. [155], NeST RNA was undetectable in T cells from B10.S, but it was expressed in SJL/J mice and its RNA level positively correlated with IFNγ transcription. NeST was shown to interact with the subunit WDR5 of the H3K4 methyltransferase complex that catalyzes the trimethylation of histone H3 at lysine 4, a mark of active gene expression [158]. Increased NeST RNA abundance in CD8+ T cells was associated with increased H3K4 trimethylation at the IFNγ locus and increased IFNγ synthesis in splenic tissue. A proposed mechanism is that NeST recruits histone H3 lysine 4 methyltransferases to the IFNγ gene locus, enhancing IFNγ expression in key T cell subsets. However, the link between NeST-mediated IFN regulation and its opposite effects on TMEV and Salmonella control remains unclear. In particular, whether NeST may regulate the chromatin state of other genes with key roles in the immune response to pathogens was not tested. It would be interesting to systematically characterize NeST functions using systems biology approaches [159].

6 Conclusion

The noncoding transcriptome has been increasingly implicated in regulating human development and disease over the past decade, with several reports suggesting that ncRNAs have enormous clinical potential. MiRNAs are being developed as serum biomarkers in cancer detection and diagnosis, and their usefulness toward a variety of clinical diseases is being explored. Cell-free miRNAs have been detected in the blood of patients with diffuse large B-cell lymphoma [160], Duchenne muscular dystrophy [161], pediatric Crohn disease [162], cardiovascular diseases (reviewed in [163]), and HBV-positive HCC cases [164]. For example, circulating miR-146a and miR-223 were significantly decreased in patients with sepsis compared to normal control patients. These candidate biomarkers could be used in conjunction with well-known biomarkers of acute systemic inflammation, such as C-reactive protein (CRP) [165]. MiR-122 is highly expressed in the liver, and serum miR-122 has been found to correlate with virologic responses to pegylated IFN therapy in chronic HCV [166], liver injury in patients with chronic HBV [167, 168], and HCC [169]. Therapeutic silencing of miR-122 in nonhuman primates with chronic HCV has been assessed and shown to suppress viremia [170]. In clinical settings, this would be a vast improvement to the current standard of care that combines pegylated IFNα with ribavirin, which is effective in only 50 % of patients and associated with serious side effects. Considering the therapeutic potential of miR-122, Regulus Therapeutics Inc. and GlaxoSmithKline are currently developing miRNA drugs linked to inflammatory diseases for commercialization. LncRNAs, such as HBx-LINE1, may also hold great promise as potential biomarkers for diagnosis and prognosis of viral infection [12]. Other host lncRNAs, such as MALAT1, could also be used as prognosis biomarkers for several cancers, independently of viral infection. Finally, long noncoding mitochondrial RNAs (ncmtRNAs) were recently reported as deregulated following human papillomavirus (HPV) infection [171]. The expression profile of these transcripts allows researchers to distinguish between normal, pre-tumoral, and cancer cells. One of these transcripts, SncmtRNA-1, has been characterized as a regulator of cell cycle progression, while two others, ASncmtRNA-1 and 2, have been suggested to act as three tumor suppressors. Expression of SncmtRNA-2 might contribute to the screening of early cervical intraepithelial lesions [172].

To conclude, novel sequencing technologies and computational methods have widely expanded the landscape of the mammalian transcriptome. NcRNAs have emerged as key players regulating various biological processes, including viral infection. Among ncRNAs, many miRNAs and lncRNAs have been identified as deregulated following viral infection. Only a few lncRNAs have been functionally characterized, but it is clear this class of ncRNAs is involved in a large variety of biological processes, similar to the ubiquitous importance of miRNAs. Virally encoded and host-derived miRNAs and lncRNAs have been linked to the virulence and pathogenesis of several different DNA and RNA viruses. They regulate viral replication and pathogenesis and modulate innate and adaptive immune responses to viral infection. Research on ncRNAs opens new avenues toward novel therapy and diagnostic tools, as well as development of novel paradigms about transcriptome regulation of biological systems. Most recent advances include the characterization of circular RNAs [173], RNAs acting as competing endogenous RNAs (ceRNAs) or natural microRNA sponges [174], and mRNA with noncoding functions such as HBx-LINE [12]. Now, the challenge is to understand their functions and how these diverse RNAs interact together to form a large interconnected transcriptional network that can shape the outcome of viral infection.



The authors thank Marcus Korth for his valuable feedback on the manuscript. Research in the Katze laboratory is supported by Public Health Service grants R24OD011172, R24OD010445, P51OD010425, U19AI100625, and U19AI109761 from the National Institutes of Health and by contracts HHSN272201400005C and HHSN272201300010C from the National Institute of Allergy and Infectious Diseases.


  1. 1.
    Lau NC, Lim LP, Weinstein EG, Bartel DP (2001) An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294:858–862PubMedCrossRefGoogle Scholar
  2. 2.
    Lee RC, Ambros V (2001) An extensive class of small RNAs in Caenorhabditis elegans. Science 294:862–864PubMedCrossRefGoogle Scholar
  3. 3.
    Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–854PubMedCrossRefGoogle Scholar
  4. 4.
    Kozomara A, Griffiths-Jones S (2014) miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 42:D68–D73PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    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 22:1775–1789PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Xie C, Yuan J, Li H, Li M, Zhao G, Bu D et al (2014) NONCODEv4: exploring the world of long non-coding RNA genes. Nucleic Acids Res 42:D98–D103PubMedCentralPubMedCrossRefGoogle Scholar
  7. 7.
    Moran VA, Perera RJ, Khalil AM (2012) Emerging functional and mechanistic paradigms of mammalian long non-coding RNAs. Nucleic Acids Res 40:6391–6400PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Pfeffer S, Zavolan M, Grasser FA, Chien M, Russo JJ, Ju J et al (2004) Identification of virus-encoded microRNAs. Science 304:734–746PubMedCrossRefGoogle Scholar
  9. 9.
    Perez JT, Varble A, Sachidanandam R, Zlatev I, Manoharan M, Garcia-Sastre A et al (2010) Influenza A virus-generated small RNAs regulate the switch from transcription to replication. Proc Natl Acad Sci USA 107:11525–11530PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Schuessler A, Funk A, Lazear HM, Cooper DA, Torres S, Daffis S et al (2012) West Nile virus noncoding subgenomic RNA contributes to viral evasion of the type I interferon-mediated antiviral response. J Virol 86:5708–5718PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Cazalla D, Yario T, Steitz JA (2010) Down-regulation of a host microRNA by a Herpesvirus saimiri noncoding RNA. Science 328:1563–1566PubMedCentralPubMedCrossRefGoogle Scholar
  12. 12.
    Lau CC, Sun T, Ching AK, He M, Li JW, Wong AM et al (2014) Viral-human chimeric transcript predisposes risk to liver cancer development and progression. Cancer Cell 25:335–349PubMedCrossRefGoogle Scholar
  13. 13.
    Saayman S, Ackley A, Turner AM, Famiglietti M, Bosque A, Clemson M et al (2014) An HIV-encoded antisense long noncoding RNA epigenetically regulates viral transcription. Mol Ther 22:1164–11675PubMedCentralPubMedCrossRefGoogle Scholar
  14. 14.
    Saito M, Matsuzaki T, Satou Y, Yasunaga J, Saito K, Arimura K et al (2009) In vivo expression of the HBZ gene of HTLV-1 correlates with proviral load, inflammatory markers and disease severity in HTLV-1 associated myelopathy/tropical spastic paraparesis (HAM/TSP). Retrovirology 6:19PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Cai X, Cullen BR (2006) Transcriptional origin of Kaposi’s sarcoma-associated herpesvirus microRNAs. J Virol 80:2234–2242PubMedCentralPubMedCrossRefGoogle Scholar
  16. 16.
    Moody R, Zhu Y, Huang Y, Cui X, Jones T, Bedolla R et al (2013) KSHV microRNAs mediate cellular transformation and tumorigenesis by redundantly targeting cell growth and survival pathways. PLoS Pathog 9:e1003857PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Abend JR, Ramalingam D, Kieffer-Kwon P, Uldrick TS, Yarchoan R, Ziegelbauer JM (2012) Kaposi’s sarcoma-associated herpesvirus microRNAs target IRAK1 and MYD88, two components of the toll-like receptor/interleukin-1R signaling cascade, to reduce inflammatory-cytokine expression. J Virol 86:11663–11674PubMedCentralPubMedCrossRefGoogle Scholar
  18. 18.
    Gottwein E, Mukherjee N, Sachse C, Frenzel C, Majoros WH, Chi JT et al (2007) A viral microRNA functions as an orthologue of cellular miR-155. Nature 450:1096–1099PubMedCentralPubMedCrossRefGoogle Scholar
  19. 19.
    He B, Gross M, Roizman B (1997) The gamma(1)34.5 protein of herpes simplex virus 1 complexes with protein phosphatase 1alpha to dephosphorylate the alpha subunit of the eukaryotic translation initiation factor 2 and preclude the shutoff of protein synthesis by double-stranded RNA-activated protein kinase. Proc Natl Acad Sci USA 94:843–848PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Grundhoff A, Sullivan CS (2011) Virus-encoded microRNAs. Virology 411:325–343PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Rasmussen MH, Ballarin-Gonzalez B, Liu J, Lassen LB, Fuchtbauer A, Fuchtbauer EM et al (2010) Antisense transcription in gammaretroviruses as a mechanism of insertional activation of host genes. J Virol 84:3780–3788PubMedCentralPubMedCrossRefGoogle Scholar
  22. 22.
    Zhao T, Matsuoka M (2012) HBZ and its roles in HTLV-1 oncogenesis. Front Microbiol 3:247. doi: 10.3389/fmicb.2012.00247. eCollection 2012 PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Ma Y, Zheng S, Wang Y, Zang W, Li M, Wang N, Li P, Jin J, Dong Z, Zhao G (2013) The HTLV-1 HBZ protein inhibits cyclin D1 expression through interacting with the cellular transcription factor CREB. Mol Biol Rep 40(10):5967–5975PubMedCrossRefGoogle Scholar
  24. 24.
    Kuhlmann AS, Villaudy J, Gazzolo L, Castellazzi M, Mesnard JM, Duc DM (2007) HTLV-1 HBZ cooperates with JunD to enhance transcription of the human telomerase reverse transcriptase gene (hTERT). Retrovirology 4:92PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Iizasa H, Wulff BE, Alla NR, Maragkakis M, Megraw M, Hatzigeorgiou A, Iwakiri D, Takada K, Wiedmer A, Showe L, Lieberman P, Nishikura K (2010) Editing of Epstein-Barr virus-encoded BART6 microRNAs controls their dicer targeting and consequently affects viral latency. J Biol Chem 285(43):33358–33370PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Choy EY, Siu KL, Kok KH, Lung RW, Tsang CM, To KF, Kwong DL, Tsao SW, Jin DY (2008) An Epstein-Barr virus-encoded microRNA targets PUMA to promote host cell survival. J Exp Med 205(11):2551–2560PubMedCentralPubMedCrossRefGoogle Scholar
  27. 27.
    Marquitz AR, Mathur A, Nam CS, Raab-Traub N (2011) The Epstein-Barr Virus BART microRNAs target the pro-apoptotic protein Bim. Virology 412(2):392–400PubMedCentralPubMedCrossRefGoogle Scholar
  28. 28.
    Seto E, Moosmann A, Grömminger S, Walz N, Grundhoff A, Hammerschmidt W (2010) Micro RNAs of Epstein-Barr virus promote cell cycle progression and prevent apoptosis of primary human B cells. PLoS Pathog 6(8):e1001063PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    Xia T, O'Hara A, Araujo I, Barreto J, Carvalho E, Sapucaia JB, Ramos JC, Luz E, Pedroso C, Manrique M, Toomey NL, Brites C, Dittmer DP, Harrington WJ Jr (2008) EBV microRNAs in primary lymphomas and targeting of CXCL-11 by ebv-mir-BHRF1-3. Cancer Res 68(5):1436–1442PubMedCentralPubMedCrossRefGoogle Scholar
  30. 30.
    Ahmed W, Khan G (2014) The labyrinth of interactions of Epstein-Barr virus-encoded small RNAs. Rev Med Virol 24(1):3–14. doi: 10.1002/rmv.1763, Epub 2013 Sep 18. ReviewPubMedCrossRefGoogle Scholar
  31. 31.
    Abend JR, Uldrick T, Ziegelbauer JM (2010) Regulation of tumor necrosis factor-like weak inducer of apoptosis receptor protein (TWEAKR) expression by Kaposi’s sarcoma-associated herpesvirus microRNA prevents TWEAK-induced apoptosis and inflammatory cytokine expression. J Virol 84(23):12139–12151PubMedCentralPubMedCrossRefGoogle Scholar
  32. 32.
    Suffert G, Malterer G, Hausser J, Viiliäinen J, Fender A, Contrant M, Ivacevic T, Benes V, Gros F, Voinnet O, Zavolan M, Ojala PM, Haas JG, Pfeffer S (2011) Kaposi's sarcoma herpesvirus microRNAs target caspase 3 and regulate apoptosis. PLoS Pathog 7(12):e1002405PubMedCentralPubMedCrossRefGoogle Scholar
  33. 33.
    Bellare P, Ganem D (2009) Regulation of KSHV lytic switch protein expression by a virus-encoded microRNA: an evolutionary adaptation that fine-tunes lytic reactivation. Cell Host Microbe 6(6):570–575PubMedCentralPubMedCrossRefGoogle Scholar
  34. 34.
    Lin X, Liang D, He Z, Deng Q, Robertson ES, Lan K (2011) miR-K12-7-5p encoded by Kaposi’s sarcoma-associated herpesvirus stabilizes the latent state by targeting viral ORF50/RTA. PLoS One 6(1):e16224Google Scholar
  35. 35.
    Liang D, Gao Y, Lin X, He Z, Zhao Q, Deng Q, Lan K (2011) A human herpesvirus miRNA attenuates interferon signaling and contributes to maintenance of viral latency by targeting IKKε. Cell Res 21(5):793–806. doi: 10.1038/cr.2011.5 PubMedCentralPubMedCrossRefGoogle Scholar
  36. 36.
    Lei X, Bai Z, Ye F, Xie J, Kim CG, Huang Y, Gao SJ (2010) Regulation of NF-kappaB inhibitor IkappaBalpha and viral replication by a KSHV microRNA. Nat Cell Biol 12(2):193–199. doi:10.1038/ncb2019. Epub 2010 Jan 17. Erratum in: Nat Cell Biol 2010;12(6):625Google Scholar
  37. 37.
    Hansen A, Henderson S, Lagos D, Nikitenko L, Coulter E, Roberts S, Gratrix F, Plaisance K, Renne R, Bower M, Kellam P, Boshoff C (2010) KSHV-encoded miRNAs target MAF to induce endothelial cell reprogramming. Genes Dev 24(2):195–205PubMedCentralPubMedCrossRefGoogle Scholar
  38. 38.
    Lu F, Stedman W, Yousef M, Renne R, Lieberman PM (2010) Epigenetic regulation of Kaposi’s sarcoma-associated herpesvirus latency by virus-encoded microRNAs that target Rta and the cellular Rbl2-DNMT pathway. J Virol 84(6):2697–2706PubMedCentralPubMedCrossRefGoogle Scholar
  39. 39.
    Samols MA, Skalsky RL, Maldonado AM, Riva A, Lopez MC, Baker HV, Renne R (2007) Identification of cellular genes targeted by KSHV-encoded microRNAs. PLoS Pathog 3(5):e65PubMedCentralPubMedCrossRefGoogle Scholar
  40. 40.
    Gottwein E, Cullen BR (2010) A human herpesvirus microRNA inhibits p21 expression and attenuates p21-mediated cell cycle arrest. J Virol 84(10):5229–5237PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Qin Z, Kearney P, Plaisance K, Parsons CH (2010) Pivotal advance: Kaposi’s sarcoma-associated herpesvirus (KSHV)-encoded microRNA specifically induce IL-6 and IL-10 secretion by macrophages and monocytes. J Leukoc Biol 87(1):25–34PubMedCentralPubMedCrossRefGoogle Scholar
  42. 42.
    Skalsky RL, Samols MA, Plaisance KB, Boss IW, Riva A, Lopez MC, Baker HV, Renne R (2007) Kaposi’s sarcoma-associated herpesvirus encodes an ortholog of miR-155. J Virol 81(23):12836–12845PubMedCentralPubMedCrossRefGoogle Scholar
  43. 43.
    Rossetto CC, Pari GS (2011) Kaposi’s sarcoma-associated herpesvirus noncoding polyadenylated nuclear RNA interacts with virus- and host cell-encoded proteins and suppresses expression of genes involved in immune modulation. J Virol 85:13290–13297PubMedCentralPubMedCrossRefGoogle Scholar
  44. 44.
    Campbell M, Kim KY, Chang PC, Huerta S, Shevchenko B, Wang DH et al (2014) A lytic viral long noncoding RNA modulates the function of a latent protein. J Virol 88:1843–1848PubMedCentralPubMedCrossRefGoogle Scholar
  45. 45.
    Dölken L, Krmpotic A, Kothe S, Tuddenham L, Tanguy M, Marcinowski L, Ruzsics Z, Elefant N, Altuvia Y, Margalit H, Koszinowski UH, Jonjic S, Pfeffer S (2010) Cytomegalovirus microRNAs facilitate persistent virus infection in salivary glands. PLoS Pathog 6(10):e1001150PubMedCentralPubMedCrossRefGoogle Scholar
  46. 46.
    Grey F, Tirabassi R, Meyers H, Wu G, McWeeney S, Hook L, Nelson JA (2010) A viral microRNA down-regulates multiple cell cycle genes through mRNA 5′UTRs. PLoS Pathog 6(6):e1000967PubMedCentralPubMedCrossRefGoogle Scholar
  47. 47.
    Stern-Ginossar N, Elefant N, Zimmermann A, Wolf DG, Saleh N, Biton M, Horwitz E, Prokocimer Z, Prichard M, Hahn G, Goldman-Wohl D, Greenfield C, Yagel S, Hengel H, Altuvia Y, Margalit H, Mandelboim O (2007) Host immune system gene targeting by a viral miRNA. Science 317(5836):376–381PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Nachmani D, Stern-Ginossar N, Sarid R, Mandelboim O (2009) Diverse herpesvirus microRNAs target the stress-induced immune ligand MICB to escape recognition by natural killer cells. Cell Host Microbe 5(4):376–385PubMedCrossRefGoogle Scholar
  49. 49.
    Ziegelbauer JM, Sullivan CS, Ganem D (2009) Tandem array-based expression screens identify host mRNA targets of virus-encoded microRNAs. Nat Genet 41(1):130–134. doi: 10.1038/ng.266, Epub 2008 Dec 21PubMedCentralPubMedCrossRefGoogle Scholar
  50. 50.
    Lee SH, Kalejta RF, Kerry J, Semmes OJ, O’Connor CM, Khan Z, Garcia BA, Shenk T, Murphy E (2012) BclAF1 restriction factor is neutralized by proteasomal degradation and microRNA repression during human cytomegalovirus infection. Proc Natl Acad Sci USA 109(24):9575–9580PubMedCentralPubMedCrossRefGoogle Scholar
  51. 51.
    Riley KJ, Rabinowitz GS, Yario TA, Luna JM, Darnell RB, Steitz JA (2012) EBV and human microRNAs co-target oncogenic and apoptotic viral and human genes during latency. EMBO J 31(9):2207–2221PubMedCentralPubMedCrossRefGoogle Scholar
  52. 52.
    Zhao Y, Yao Y, Xu H, Lambeth L, Smith LP, Kgosana L, Wang X, Nair V (2009) A functional MicroRNA-155 ortholog encoded by the oncogenic Marek’s disease virus. J Virol 83(1):489–492PubMedCentralPubMedCrossRefGoogle Scholar
  53. 53.
    Muylkens B, Coupeau D, Dambrine G, Trapp S, Rasschaert D (2010) Marek’s disease virus microRNA designated Mdv1-pre-miR-M4 targets both cellular and viral genes. Arch Virol 155(11):1823–1837. doi: 10.1007/s00705-010-0777-y PubMedCrossRefGoogle Scholar
  54. 54.
    Xu S, Xue C, Li J, Bi Y, Cao Y (2011) Marek’s disease virus type 1 microRNA miR-M3 suppresses cisplatin-induced apoptosis by targeting Smad2 of the transforming growth factor beta signal pathway. J Virol 85(1):276–285PubMedCentralPubMedCrossRefGoogle Scholar
  55. 55.
    Law GL, Korth MJ, Benecke AG, Katze MG (2013) Systems virology: host-directed approaches to viral pathogenesis and drug targeting. Nat Rev Microbiol 11:455–466PubMedCentralPubMedCrossRefGoogle Scholar
  56. 56.
    Pritchard CC, Cheng HH, Tewari M (2012) MicroRNA profiling: approaches and considerations. Nat Rev Genet 13:358–369PubMedCentralPubMedCrossRefGoogle Scholar
  57. 57.
    Carninci P, Kasukawa T, Katayama S, Gough J, Frith MC, Maeda N et al (2005) The transcriptional landscape of the mammalian genome. Science 309:1559–1563PubMedCrossRefGoogle Scholar
  58. 58.
    Cheng J, Kapranov P, Drenkow J, Dike S, Brubaker S, Patel S et al (2005) Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution. Science 2005(308):1149–1154CrossRefGoogle Scholar
  59. 59.
    Zhao S, Fung-Leung WP, Bittner A, Ngo K, Liu X (2014) Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells. PLoS One 9:e78644PubMedCentralPubMedCrossRefGoogle Scholar
  60. 60.
    Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y (2008) RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res 18:1509–1517PubMedCentralPubMedCrossRefGoogle Scholar
  61. 61.
    Bradford JR, Hey Y, Yates T, Li Y, Pepper SD, Miller CJ (2010) A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling. BMC Genomics 11:282PubMedCentralPubMedCrossRefGoogle Scholar
  62. 62.
    Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ et al (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28:511–515PubMedCentralPubMedCrossRefGoogle Scholar
  63. 63.
    Griffith M, Griffith OL, Mwenifumbo J, Goya R, Morrissy AS, Morin RD et al (2010) Alternative expression analysis by RNA sequencing. Nat Methods 7:843–847PubMedCrossRefGoogle Scholar
  64. 64.
    Vlachos IS, Hatzigeorgiou AG (2013) Online resources for miRNA analysis. Clin Biochem 46:879–900PubMedCrossRefGoogle Scholar
  65. 65.
    Friedlander MR, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S et al (2008) Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol 26:407–415PubMedCrossRefGoogle Scholar
  66. 66.
    Zhu E, Zhao F, Xu G, Hou H, Zhou L, Li X et al (2010) mirTools: microRNA profiling and discovery based on high-throughput sequencing. Nucleic Acids Res 38:W392–W397PubMedCentralPubMedCrossRefGoogle Scholar
  67. 67.
    Garcia DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP (2011) Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs. Nat Struct Mol Biol 18:1139–1146PubMedCentralPubMedCrossRefGoogle Scholar
  68. 68.
    John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS (2004) Human MicroRNA targets. PLoS Biol 2:e363PubMedCentralPubMedCrossRefGoogle Scholar
  69. 69.
    Paraskevopoulou MD, Georgakilas G, Kostoulas N, Vlachos IS, Vergoulis T, Reczko M et al (2013) DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows. Nucleic Acids Res 41:W169–W173PubMedCentralPubMedCrossRefGoogle Scholar
  70. 70.
    Yuan J, Wu W, Xie C, Zhao G, Zhao Y, Chen R (2014) NPInter v2.0: an updated database of ncRNA interactions. Nucleic Acids Res 42:D104–D108PubMedCentralPubMedCrossRefGoogle Scholar
  71. 71.
    Volders PJ, Helsens K, Wang X, Menten B, Martens L, Gevaert K et al (2013) LNCipedia: a database for annotated human lncRNA transcript sequences and structures. Nucleic Acids Res 41:D246–D251PubMedCentralPubMedCrossRefGoogle Scholar
  72. 72.
    Liao Q, Xiao H, Bu D, Xie C, Miao R, Luo H et al (2011) ncFANs: a web server for functional annotation of long non-coding RNAs. Nucleic Acids Res 39:W118–W124PubMedCentralPubMedCrossRefGoogle Scholar
  73. 73.
    Dinger ME, Pang KC, Mercer TR, Crowe ML, Grimmond SM, Mattick JS (2009) NRED: a database of long noncoding RNA expression. Nucleic Acids Res 37(Database issue):D122–D126PubMedCentralPubMedCrossRefGoogle Scholar
  74. 74.
    Amaral PP, Clark MB, Gascoigne DK, Dinger ME, Mattick JS (2011) lncRNAdb: a reference database for long noncoding RNAs. Nucleic Acids Res 39:D146–D151PubMedCentralPubMedCrossRefGoogle Scholar
  75. 75.
    Chen G, Wang Z, Wang D, Qiu C, Liu M, Chen X et al (2013) LncRNADisease: a database for long-non-coding RNA-associated diseases. Nucleic Acids Res 41:D983–D986PubMedCentralPubMedCrossRefGoogle Scholar
  76. 76.
    Wu LF, Hughes TR, Davierwala AP, Robinson MD, Stoughton R, Altschuler SJ (2002) Large-scale prediction of Saccharomyces cerevisiae gene function using overlapping transcriptional clusters. Nat Genet 31:255–265PubMedCrossRefGoogle Scholar
  77. 77.
    Taylor RC, Acquaah-Mensah G, Singhal M, Malhotra D, Biswal S (2008) Network inference algorithms elucidate Nrf2 regulation of mouse lung oxidative stress. PLoS Comput Biol 4:e1000166PubMedCentralPubMedCrossRefGoogle Scholar
  78. 78.
    Belcastro V, Siciliano V, Gregoretti F, Mithbaokar P, Dharmalingam G, Berlingieri S et al (2011) Transcriptional gene network inference from a massive dataset elucidates transcriptome organization and gene function. Nucleic Acids Res 39:8677–8688PubMedCentralPubMedCrossRefGoogle Scholar
  79. 79.
    Luo F, Yang Y, Zhong J, Gao H, Khan L, Thompson DK et al (2007) Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory. BMC Bioinformatics 8:299PubMedCentralPubMedCrossRefGoogle Scholar
  80. 80.
    Childs KL, Davidson RM, Buell CR (2011) Gene coexpression network analysis as a source of functional annotation for rice genes. PLoS One 6:e22196PubMedCentralPubMedCrossRefGoogle Scholar
  81. 81.
    Liao Q, Liu C, Yuan X, Kang S, Miao R, Xiao H et al (2011) Large-scale prediction of long non-coding RNA functions in a coding-non-coding gene co-expression network. Nucleic Acids Res 39:3864–3878PubMedCentralPubMedCrossRefGoogle Scholar
  82. 82.
    Guttman M, Amit I, Garber M, French C, Lin MF, Feldser D et al (2009) Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature 458:223–227PubMedCentralPubMedCrossRefGoogle Scholar
  83. 83.
    Huarte M, Guttman M, Feldser D, Garber M, Koziol MJ, Kenzelmann-Broz D et al (2010) A large intergenic noncoding RNA induced by p53 mediates global gene repression in the p53 response. Cell 142:409–419PubMedCentralPubMedCrossRefGoogle Scholar
  84. 84.
    Hu G, Tang Q, Sharma S, Yu F, Escobar TM, Muljo SA et al (2013) Expression and regulation of intergenic long noncoding RNAs during T cell development and differentiation. Nat Immunol 14:1190–1198PubMedCentralPubMedCrossRefGoogle Scholar
  85. 85.
    Josset L, Tchitchek N, Gralinski LE, Ferris MT, Eisfeld AJ, Green RR et al (2014) Annotation of long non-coding RNAs expressed in Collaborative Cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts. RNA Biol 11(7):875–890PubMedCentralPubMedCrossRefGoogle Scholar
  86. 86.
    Li Y, Chan EY, Li J, Ni C, Peng X, Rosenzweig E et al (2010) MicroRNA expression and virulence in pandemic influenza virus-infected mice. J Virol 84:3023–3032PubMedCentralPubMedCrossRefGoogle Scholar
  87. 87.
    Peng X, Gralinski L, Ferris MT, Frieman MB, Thomas MJ, Proll S et al (2011) Integrative deep sequencing of the mouse lung transcriptome reveals differential expression of diverse classes of small RNAs in response to respiratory virus infection. MBio 2:e00198–e00211PubMedCentralPubMedCrossRefGoogle Scholar
  88. 88.
    Peng X, Gralinski L, Armour CD, Ferris MT, Thomas MJ, Proll S et al (2010) Unique signatures of long noncoding RNA expression in response to virus infection and altered innate immune signaling. MBio 1:e00206–e00210PubMedCentralPubMedCrossRefGoogle Scholar
  89. 89.
    Chang ST, Thomas MJ, Sova P, Green RR, Palermo RE, Katze MG (2013) Next-generation sequencing of small RNAs from HIV-infected cells identifies phased microRNA expression patterns and candidate novel microRNAs differentially expressed upon infection. MBio 4(1):e00549PubMedCentralPubMedCrossRefGoogle Scholar
  90. 90.
    Barnes D, Kunitomi M, Vignuzzi M, Saksela K, Andino R (2008) Harnessing endogenous miRNAs to control virus tissue tropism as a strategy for developing attenuated virus vaccines. Cell Host Microbe 4:239–248PubMedCentralPubMedCrossRefGoogle Scholar
  91. 91.
    Kelly EJ, Hadac EM, Cullen BR, Russell SJ (2010) MicroRNA antagonism of the picornaviral life cycle: alternative mechanisms of interference. PLoS Pathog 6:e1000820PubMedCentralPubMedCrossRefGoogle Scholar
  92. 92.
    Ylosmaki E, Lavilla-Alonso S, Jaamaa S, Vaha-Koskela M, af Hallstrom T, Hemminki A et al (2013) MicroRNA-mediated suppression of oncolytic adenovirus replication in human liver. PLoS One 8:e54506PubMedCentralPubMedCrossRefGoogle Scholar
  93. 93.
    Kulkarni S, Savan R, Qi Y, Gao X, Yuki Y, Bass SE et al (2011) Differential microRNA regulation of HLA-C expression and its association with HIV control. Nature 472:495–498PubMedCentralPubMedCrossRefGoogle Scholar
  94. 94.
    Winterling C, Koch M, Koeppel M, Garcia-Alcalde F, Karlas A, Meyer TF (2014) Evidence for a crucial role of a host non-coding RNA in influenza A virus replication. RNA Biol 11:66–75PubMedCentralPubMedCrossRefGoogle Scholar
  95. 95.
    Ouyang J, Zhu X, Chen Y, Wei H, Chen Q, Chi X, Qi B, Zhang L, Zhao Y, Gao GF et al (2014) NRAV, a long noncoding RNA, modulates antiviral responses through suppression of interferon-stimulated gene transcription. Cell Host Microbe 16:616–626Google Scholar
  96. 96.
    McKenna LB, Schug J, Vourekas A, McKenna JB, Bramswig NC, Friedman JR et al (2010) MicroRNAs control intestinal epithelial differentiation, architecture, and barrier function. Gastroenterology 139:1654–1664PubMedCentralPubMedCrossRefGoogle Scholar
  97. 97.
    Guadalupe M, Reay E, Sankaran S, Prindiville T, Flamm J, McNeil A et al (2003) Severe CD4+ T-cell depletion in gut lymphoid tissue during primary human immunodeficiency virus type 1 infection and substantial delay in restoration following highly active antiretroviral therapy. J Virol 77:11708–11717PubMedCentralPubMedCrossRefGoogle Scholar
  98. 98.
    Gaulke CA, Porter M, Han YH, Sankaran-Walters S, Grishina I, George MD et al (2014) Intestinal epithelial barrier disruption through altered mucosal microRNA expression in human immunodeficiency virus and simian immunodeficiency virus infections. J Virol 88:6268–6280PubMedCentralPubMedCrossRefGoogle Scholar
  99. 99.
    Barrenas F, Palermo RE, Agricola B, Agy MB, Aicher L, Carter V et al (2014) Deep transcriptional sequencing of mucosal challenge compartment from rhesus macaques acutely infected with simian immunodeficiency virus implicates loss of cell adhesion preceding immune activation. J Virol 88:7962–7972PubMedCentralPubMedCrossRefGoogle Scholar
  100. 100.
    Kobayashi-Ishihara M, Yamagishi M, Hara T, Matsuda Y, Takahashi R, Miyake A et al (2012) HIV-1-encoded antisense RNA suppresses viral replication for a prolonged period. Retrovirology 9:38PubMedCentralPubMedCrossRefGoogle Scholar
  101. 101.
    Eilebrecht S, Schwartz C, Rohr O (2013) Non-coding RNAs: novel players in chromatin-regulation during viral latency. Curr Opin Virol 3:387–393PubMedCrossRefGoogle Scholar
  102. 102.
    Groen JN, Morris KV (2013) Chromatin, non-coding RNAs, and the expression of HIV. Viruses 5:1633–1645PubMedCentralPubMedCrossRefGoogle Scholar
  103. 103.
    Zhang Q, Chen CY, Yedavalli VS, Jeang KT (2013) NEAT1 long noncoding RNA and paraspeckle bodies modulate HIV-1 posttranscriptional expression. MBio 4:e00596PubMedCentralPubMedCrossRefGoogle Scholar
  104. 104.
    Imamura K, Imamachi N, Akizuki G, Kumakura M, Kawaguchi A, Nagata K et al (2014) Long noncoding RNA NEAT1-dependent SFPQ relocation from promoter region to paraspeckle mediates IL8 expression upon immune stimuli. Mol Cell 53:393–406PubMedCrossRefGoogle Scholar
  105. 105.
    Ganem D (2010) KSHV and the pathogenesis of Kaposi sarcoma: listening to human biology and medicine. J Clin Invest 120:939–949PubMedCentralPubMedCrossRefGoogle Scholar
  106. 106.
    Lieberman PM (2013) Keeping it quiet: chromatin control of gammaherpesvirus latency. Nat Rev Microbiol 11:863–875PubMedCentralPubMedCrossRefGoogle Scholar
  107. 107.
    Lagos D, Pollara G, Henderson S, Gratrix F, Fabani M, Milne RS et al (2010) miR-132 regulates antiviral innate immunity through suppression of the p300 transcriptional co-activator. Nat Cell Biol 12:513–519PubMedCrossRefGoogle Scholar
  108. 108.
    Sun R, Lin SF, Gradoville L, Miller G (1996) Polyadenylylated nuclear RNA encoded by Kaposi sarcoma-associated herpesvirus. Proc Natl Acad Sci USA 93:11883–11888PubMedCentralPubMedCrossRefGoogle Scholar
  109. 109.
    Rossetto CC, Pari G (2012) KSHV PAN RNA associates with demethylases UTX and JMJD3 to activate lytic replication through a physical interaction with the virus genome. PLoS Pathog 8:e1002680PubMedCentralPubMedCrossRefGoogle Scholar
  110. 110.
    Rossetto CC, Tarrant-Elorza M, Verma S, Purushothaman P, Pari GS (2013) Regulation of viral and cellular gene expression by Kaposi’s sarcoma-associated herpesvirus polyadenylated nuclear RNA. J Virol 87:5540–5553PubMedCentralPubMedCrossRefGoogle Scholar
  111. 111.
    Borah S, Darricarrere N, Darnell A, Myoung J, Steitz JA (2011) A viral nuclear noncoding RNA binds re-localized poly(A) binding protein and is required for late KSHV gene expression. PLoS Pathog 7:e1002300PubMedCentralPubMedCrossRefGoogle Scholar
  112. 112.
    Zhang Q, Pu R, Du Y, Han Y, Su T, Wang H et al (2012) Non-coding RNAs in hepatitis B or C-associated hepatocellular carcinoma: potential diagnostic and prognostic markers and therapeutic targets. Cancer Lett 321:1–12PubMedCrossRefGoogle Scholar
  113. 113.
    Brechot C, Gozuacik D, Murakami Y, Paterlini-Brechot P (2000) Molecular bases for the development of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Semin Cancer Biol 10:211–231PubMedCrossRefGoogle Scholar
  114. 114.
    Murakami S (1999) Hepatitis B virus X protein: structure, function and biology. Intervirology 42:81–99PubMedCrossRefGoogle Scholar
  115. 115.
    He Y, Meng XM, Huang C, Wu BM, Zhang L, Lv XW et al (2014) Long noncoding RNAs: novel insights into hepatocelluar carcinoma. Cancer Lett 344:20–27PubMedCrossRefGoogle Scholar
  116. 116.
    Panzitt K, Tschernatsch MM, Guelly C, Moustafa T, Stradner M et al (2007) Characterization of HULC, a novel gene with striking up-regulation in hepatocellular carcinoma, as noncoding RNA. Gastroenterology 132:330–342PubMedCrossRefGoogle Scholar
  117. 117.
    Du Y, Kong G, You X, Zhang S, Zhang T, Gao Y et al (2012) Elevation of highly up-regulated in liver cancer (HULC) by hepatitis B virus X protein promotes hepatoma cell proliferation via down-regulating p18. J Biol Chem 287:26302–26311PubMedCentralPubMedCrossRefGoogle Scholar
  118. 118.
    Liu Y, Pan S, Liu L, Zhai X, Liu J, Wen J et al (2012) A genetic variant in long non-coding RNA HULC contributes to risk of HBV-related hepatocellular carcinoma in a Chinese population. PLoS One 7:e35145PubMedCentralPubMedCrossRefGoogle Scholar
  119. 119.
    Huang JF, Guo YJ, Zhao CX, Yuan SX, Wang Y, Tang GN et al (2013) Hepatitis B virus X protein (HBx)-related long noncoding RNA (lncRNA) down-regulated expression by HBx (Dreh) inhibits hepatocellular carcinoma metastasis by targeting the intermediate filament protein vimentin. Hepatology 57:1882–1892PubMedCrossRefGoogle Scholar
  120. 120.
    Taganov KD, Boldin MP, Chang KJ, Baltimore D (2006) NF-kappaB-dependent induction of microRNA miR-146, an inhibitor targeted to signaling proteins of innate immune responses. Proc Natl Acad Sci USA 103:12481–12486PubMedCentralPubMedCrossRefGoogle Scholar
  121. 121.
    Buggele WA, Johnson KE, Horvath CM (2012) Influenza A virus infection of human respiratory cells induces primary microRNA expression. J Biol Chem 287:31027–31040PubMedCentralPubMedCrossRefGoogle Scholar
  122. 122.
    Chen XM, Splinter PL, O’Hara SP, LaRusso NF (2007) A cellular micro-RNA, let-7i, regulates Toll-like receptor 4 expression and contributes to cholangiocyte immune responses against Cryptosporidium parvum infection. J Biol Chem 282:28929–28938PubMedCentralPubMedCrossRefGoogle Scholar
  123. 123.
    Moschos SA, Williams AE, Perry MM, Birrell MA, Belvisi MG, Lindsay MA (2007) Expression profiling in vivo demonstrates rapid changes in lung microRNA levels following lipopolysaccharide-induced inflammation but not in the anti-inflammatory action of glucocorticoids. BMC Genomics 8:240PubMedCentralPubMedCrossRefGoogle Scholar
  124. 124.
    Tili E, Michaille JJ, Cimino A, Costinean S, Dumitru CD, Adair B et al (2007) Modulation of miR-155 and miR-125b levels following lipopolysaccharide/TNF-alpha stimulation and their possible roles in regulating the response to endotoxin shock. J Immunol 179:5082–5089PubMedCrossRefGoogle Scholar
  125. 125.
    O’Connell RM, Taganov KD, Boldin MP, Cheng G, Baltimore D (2007) MicroRNA-155 is induced during the macrophage inflammatory response. Proc Natl Acad Sci USA 104:1604–1609PubMedCentralPubMedCrossRefGoogle Scholar
  126. 126.
    McCoy CE, Sheedy FJ, Qualls JE, Doyle SL, Quinn SR, Murray PJ et al (2010) IL-10 inhibits miR-155 induction by toll-like receptors. J Biol Chem 285:20492–20498PubMedCentralPubMedCrossRefGoogle Scholar
  127. 127.
    Martinez-Nunez RT, Louafi F, Sanchez-Elsner T (2011) The interleukin 13 (IL-13) pathway in human macrophages is modulated by microRNA-155 via direct targeting of interleukin 13 receptor alpha1 (IL13Ralpha1). J Biol Chem 286:1786–1794PubMedCentralPubMedCrossRefGoogle Scholar
  128. 128.
    Zhou H, Huang X, Cui H, Luo X, Tang Y, Chen S et al (2010) miR-155 and its star-form partner miR-155* cooperatively regulate type I interferon production by human plasmacytoid dendritic cells. Blood 116:5885–5894PubMedCrossRefGoogle Scholar
  129. 129.
    Wang P, Hou J, Lin L, Wang C, Liu X, Li D et al (2010) Inducible microRNA-155 feedback promotes type I IFN signaling in antiviral innate immunity by targeting suppressor of cytokine signaling 1. J Immunol 185:6226–6233PubMedCrossRefGoogle Scholar
  130. 130.
    Thounaojam MC, Kundu K, Kaushik DK, Swaroop S, Mahadevan A, Shankar SK et al (2014) MicroRNA 155 regulates Japanese encephalitis virus-induced inflammatory response by targeting Src homology 2-containing inositol phosphatase 1. J Virol 88:4798–4810PubMedCentralPubMedCrossRefGoogle Scholar
  131. 131.
    Thounaojam MC, Kaushik DK, Kundu K, Basu A (2014) MicroRNA-29b modulates Japanese encephalitis virus-induced microglia activation by targeting tumor necrosis factor alpha-induced protein 3. J Neurochem 129:143–154PubMedCrossRefGoogle Scholar
  132. 132.
    Sarma NJ, Tiriveedhi V, Crippin JS, Chapman WC, Mohanakumar T (2014) Hepatitis C virus-induced changes in microRNA 107 (miRNA-107) and miRNA-449a modulate CCL2 by targeting the interleukin-6 receptor complex in hepatitis. J Virol 88:3733–3743PubMedCentralPubMedCrossRefGoogle Scholar
  133. 133.
    Haneklaus M, Gerlic M, Kurowska-Stolarska M, Rainey AA, Pich D, McInnes IB et al (2012) Cutting edge: miR-223 and EBV miR-BART15 regulate the NLRP3 inflammasome and IL-1beta production. J Immunol 189:3795–3799PubMedCrossRefGoogle Scholar
  134. 134.
    Tsai SY, Segovia JA, Chang TH, Morris IR, Berton MT, Tessier PA et al (2014) DAMP molecule S100A9 acts as a molecular pattern to enhance inflammation during influenza A virus infection: role of DDX21-TRIF-TLR4-MyD88 pathway. PLoS Pathog 10:e1003848PubMedCentralPubMedCrossRefGoogle Scholar
  135. 135.
    Unlu S, Tang S, Wang E, Martinez I, Tang D, Bianchi ME et al (2012) Damage associated molecular pattern molecule-induced microRNAs (DAMPmiRs) in human peripheral blood mononuclear cells. PLoS One 7:e38899PubMedCentralPubMedCrossRefGoogle Scholar
  136. 136.
    Fatica A, Bozzoni I (2014) Long non-coding RNAs: new players in cell differentiation and development. Nat Rev Genet 15:7–21PubMedCrossRefGoogle Scholar
  137. 137.
    Zhang X, Lian Z, Padden C, Gerstein MB, Rozowsky J, Snyder M et al (2009) A myelopoiesis-associated regulatory intergenic noncoding RNA transcript within the human HOXA cluster. Blood 113:2526–2534PubMedCentralPubMedCrossRefGoogle Scholar
  138. 138.
    Wagner LA, Christensen CJ, Dunn DM, Spangrude GJ, Georgelas A, Kelley L et al (2007) EGO, a novel, noncoding RNA gene, regulates eosinophil granule protein transcript expression. Blood 109:5191–5198PubMedCentralPubMedCrossRefGoogle Scholar
  139. 139.
    Hu W, Yuan B, Flygare J, Lodish HF (2014) Long noncoding RNA-mediated anti-apoptotic activity in murine erythroid terminal differentiation. Genes Dev 25:2573–2578CrossRefGoogle Scholar
  140. 140.
    Fitzgerald KA, Caffrey DR (2014) Long noncoding RNAs in innate and adaptive immunity. Curr Opin Immunol 26:140–146PubMedCrossRefGoogle Scholar
  141. 141.
    Carpenter S, Aiello D, Atianand MK, Ricci EP, Gandhi P, Hall LL et al (2013) A long noncoding RNA mediates both activation and repression of immune response genes. Science 341:789–792PubMedCentralPubMedCrossRefGoogle Scholar
  142. 142.
    Li Z, Chao TC, Chang KY, Lin N, Patil VS, Shimizu C et al (2014) The long noncoding RNA THRIL regulates TNFalpha expression through its interaction with hnRNPL. Proc Natl Acad Sci USA 111:1002–1007PubMedCentralPubMedCrossRefGoogle Scholar
  143. 143.
    Rapicavoli NA, Qu K, Zhang J, Mikhail M, Laberge RM, Chang HY (2013) A mammalian pseudogene lncRNA at the interface of inflammation and anti-inflammatory therapeutics. Elife 2:e00762PubMedCentralPubMedCrossRefGoogle Scholar
  144. 144.
    Phipps S, Lam CE, Kaiko GE, Foo SY, Collison A, Mattes J et al (2009) Toll/IL-1 signaling is critical for house dust mite-specific helper T cell type 2 and type 17 [corrected] responses. Am J Respir Crit Care Med 179:883–893PubMedCrossRefGoogle Scholar
  145. 145.
    Mattes J, Collison A, Plank M, Phipps S, Foster PS (2009) Antagonism of microRNA-126 suppresses the effector function of TH2 cells and the development of allergic airways disease. Proc Natl Acad Sci USA 106:18704–18709PubMedCentralPubMedCrossRefGoogle Scholar
  146. 146.
    Gracias DT, Stelekati E, Hope JL, Boesteanu AC, Doering TA, Norton J et al (2013) The microRNA miR-155 controls CD8(+) T cell responses by regulating interferon signaling. Nat Immunol 14:593–602PubMedCentralPubMedCrossRefGoogle Scholar
  147. 147.
    Lind EF, Elford AR, Ohashi PS (2013) Micro-RNA 155 is required for optimal CD8+ T cell responses to acute viral and intracellular bacterial challenges. J Immunol 190:1210–1216PubMedCrossRefGoogle Scholar
  148. 148.
    de Villartay JP, Lewis D, Hockett R, Waldmann TA, Korsmeyer SJ, Cohen DI (1987) Deletional rearrangement in the human T-cell receptor alpha-chain locus. Proc Natl Acad Sci USA 84:8608–8612PubMedCentralPubMedCrossRefGoogle Scholar
  149. 149.
    Abarrategui I, Krangel MS (2007) Noncoding transcription controls downstream promoters to regulate T-cell receptor alpha recombination. EMBO J 26:4380–4390PubMedCentralPubMedCrossRefGoogle Scholar
  150. 150.
    Liu AY, Torchia BS, Migeon BR, Siliciano RF (1997) The human NTT gene: identification of a novel 17-kb noncoding nuclear RNA expressed in activated CD4+ T cells. Genomics 39:171–184PubMedCrossRefGoogle Scholar
  151. 151.
    Haasch D, Chen YW, Reilly RM, Chiou XG, Koterski S, Smith ML et al (2002) T cell activation induces a noncoding RNA transcript sensitive to inhibition by immunosuppressant drugs and encoded by the proto-oncogene, BIC. Cell Immunol 217:78–86PubMedCrossRefGoogle Scholar
  152. 152.
    Pang KC, Dinger ME, Mercer TR, Malquori L, Grimmond SM, Chen W et al (2009) Genome-wide identification of long noncoding RNAs in CD8+ T cells. J Immunol 182:7738–7748PubMedCrossRefGoogle Scholar
  153. 153.
    Rinn JL, Chang HY (2012) Genome regulation by long noncoding RNAs. Annu Rev Biochem 81:145–166PubMedCrossRefGoogle Scholar
  154. 154.
    Vigneau S, Levillayer F, Crespeau H, Cattolico L, Caudron B, Bihl F et al (2001) Homology between a 173-kb region from mouse chromosome 10, telomeric to the Ifng locus, and human chromosome 12q15. Genomics 78:206–213PubMedCrossRefGoogle Scholar
  155. 155.
    Vigneau S, Rohrlich PS, Brahic M, Bureau JF (2003) Tmevpg1, a candidate gene for the control of Theiler’s virus persistence, could be implicated in the regulation of gamma interferon. J Virol 77:5632–5638PubMedCentralPubMedCrossRefGoogle Scholar
  156. 156.
    Bihl F, Brahic M, Bureau JF (1999) Two loci, Tmevp2 and Tmevp3, located on the telomeric region of chromosome 10, control the persistence of Theiler’s virus in the central nervous system of mice. Genetics 152:385–392PubMedCentralPubMedGoogle Scholar
  157. 157.
    Collier SP, Collins PL, Williams CL, Boothby MR, Aune TM (2012) Cutting edge: influence of Tmevpg1, a long intergenic noncoding RNA, on the expression of Ifng by Th1 cells. J Immunol 189:2084–2088PubMedCentralPubMedCrossRefGoogle Scholar
  158. 158.
    Gomez JA, Wapinski OL, Yang YW, Bureau JF, Gopinath S, Monack DM et al (2013) The NeST long ncRNA controls microbial susceptibility and epigenetic activation of the interferon-gamma locus. Cell 152:743–754PubMedCentralPubMedCrossRefGoogle Scholar
  159. 159.
    Novikoff AB (1945) The concept of integrative levels and biology. Science 101(2618):209–215Google Scholar
  160. 160.
    Lawrie CH, Gal S, Dunlop HM, Pushkaran B, Liggins AP, Pulford K et al (2008) Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. Br J Haematol 141:672–675PubMedCrossRefGoogle Scholar
  161. 161.
    Cacchiarelli D, Legnini I, Martone J, Cazzella V, D’Amico A, Bertini E et al (2011) miRNAs as serum biomarkers for Duchenne muscular dystrophy. EMBO Mol Med 3:258–265PubMedCentralPubMedCrossRefGoogle Scholar
  162. 162.
    Zahm AM, Thayu M, Hand NJ, Horner A, Leonard MB, Friedman JR (2011) Circulating microRNA is a biomarker of pediatric Crohn disease. J Pediatr Gastroenterol Nutr 53:26–33PubMedCrossRefGoogle Scholar
  163. 163.
    Di Stefano V, Zaccagnini G, Capogrossi MC, Martelli F (2011) microRNAs as peripheral blood biomarkers of cardiovascular disease. Vascul Pharmacol 55:111–118PubMedCrossRefGoogle Scholar
  164. 164.
    Li LM, Hu ZB, Zhou ZX, Chen X, Liu FY, Zhang JF et al (2010) Serum microRNA profiles serve as novel biomarkers for HBV infection and diagnosis of HBV-positive hepatocarcinoma. Cancer Res 70:9798–9807PubMedCrossRefGoogle Scholar
  165. 165.
    Wang JF, Yu ML, Yu G, Bian JJ, Deng XM, Wan XJ et al (2010) Serum miR-146a and miR-223 as potential new biomarkers for sepsis. Biochem Biophys Res Commun 394:184–188PubMedCrossRefGoogle Scholar
  166. 166.
    Su TH, Liu CH, Liu CJ, Chen CL, Ting TT, Tseng TC et al (2013) Serum microRNA-122 level correlates with virologic responses to pegylated interferon therapy in chronic hepatitis C. Proc Natl Acad Sci USA 110:7844–7849PubMedCentralPubMedCrossRefGoogle Scholar
  167. 167.
    Arataki K, Hayes CN, Akamatsu S, Akiyama R, Abe H, Tsuge M et al (2013) Circulating microRNA-22 correlates with microRNA-122 and represents viral replication and liver injury in patients with chronic hepatitis B. J Med Virol 85:789–798PubMedCrossRefGoogle Scholar
  168. 168.
    Xu J, Wu C, Che X, Wang L, Yu D, Zhang T et al (2011) Circulating microRNAs, miR-21, miR-122, and miR-223, in patients with hepatocellular carcinoma or chronic hepatitis. Mol Carcinog 50:136–142PubMedCrossRefGoogle Scholar
  169. 169.
    Kojima K, Takata A, Vadnais C, Otsuka M, Yoshikawa T, Akanuma M et al (2011) MicroRNA122 is a key regulator of alpha-fetoprotein expression and influences the aggressiveness of hepatocellular carcinoma. Nat Commun 2:338PubMedCrossRefGoogle Scholar
  170. 170.
    Lanford RE, Hildebrandt-Eriksen ES, Petri A, Persson R, Lindow M, Munk ME et al (2010) Therapeutic silencing of microRNA-122 in primates with chronic hepatitis C virus infection. Science 327:198–201PubMedCentralPubMedCrossRefGoogle Scholar
  171. 171.
    Villota C, Campos A, Vidaurre S, Oliveira-Cruz L, Boccardo E, Burzio VA et al (2012) Expression of mitochondrial non-coding RNAs (ncRNAs) is modulated by high risk human papillomavirus (HPV) oncogenes. J Biol Chem 287:21303–21315PubMedCentralPubMedCrossRefGoogle Scholar
  172. 172.
    Rivas A, Burzio V, Landerer E, Borgna V, Gatica S, Avila R et al (2012) Determination of the differential expression of mitochondrial long non-coding RNAs as a noninvasive diagnosis of bladder cancer. BMC Urol 12:37PubMedCentralPubMedCrossRefGoogle Scholar
  173. 173.
    Hansen TB, Jensen TI, Clausen BH, Bramsen JB, Finsen B, Damgaard CK et al (2013) Natural RNA circles function as efficient microRNA sponges. Nature 495:384–388PubMedCrossRefGoogle Scholar
  174. 174.
    Tay Y, Rinn J, Pandolfi PP (2014) The multilayered complexity of ceRNA crosstalk and competition. Nature 505:344–352PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Laurence Josset
    • 1
    Email author
  • Jennifer Tisoncik-Go
    • 2
  • Michael G. Katze
    • 2
  1. 1.Department of Microbiology, Laboratoire de Virologie et Centre National de Référence virus influenzae Laboratoire VirPatH EA4610, Faculté de Médecine Lyon EstUniversité Claude Bernard Lyon 1LyonFrance
  2. 2.Department of Microbiology, School of MedicineUniversity of WashingtonSeattleUSA

Personalised recommendations