Mol Genet Genomics DOI 10.1007/s00438-013-0734-z

REVIEW

miRNA–transcription factor interactions: a combinatorial regulation of gene expression S. Arora • R. Rana • A. Chhabra • A. Jaiswal V. Rani

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Received: 28 July 2012 / Accepted: 9 January 2013 Ó Springer-Verlag Berlin Heidelberg 2013

Abstract Developmental processes require a precise spatio-temporal regulation of gene expression wherein a diverse set of transcription factors control the signalling pathways. MicroRNAs (miRNAs), a class of small noncoding RNA molecules have recently drawn attention for their prominent role in development and disease. These tiny sequences are essential for regulation of processes, including cell signalling, cell development, cell death, cell proliferation, patterning and differentiation. The consequence of gene regulation by miRNAs is similar to that by transcription factors (TFs). A regulatory cascade essential for appropriate execution of several biological events is triggered through a combinatorial action of miRNAs and TFs. These two important regulators share similar regulatory logics and bring about a cooperative action in the gene regulatory network, dependent on the binding sites present on the target gene. The review addresses the biogenesis and nomenclature of miRNAs, outlines the mechanism of action and regulation of their expression, and focuses on the combinatorial action of miRNAs and TFs for the expression of genes in various regulatory cascades. Keywords miRNA  Transcription factor  Gene expression  miRNA nomenclature  Combinatorial regulation

Communicated by J. Graw. All authors have contributed equally. S. Arora  R. Rana  A. Chhabra  A. Jaiswal  V. Rani (&) Department of Biotechnology, Jaypee Institute of Information Technology, A-10, Sector-62, Noida 201307, Uttar Pradesh, India e-mail: [email protected]

Abbreviations CRM Cis-regulatory modules FFL Feed-forward loop HDAC Histone-deacetylase miRNA MicroRNA miRNPs miRNA-containing ribonucleoprotein complexes RISC RNA-induced silencing complex RNAi RNA interference siRNA Small interfering RNA TF Transcription factor TSS Transcription start site TUs Transcription units

Introduction MicroRNAs (miRNAs), a class of regulatory molecules are small, non-coding RNAs functioning as gene expression regulators which downregulate the expression of target mRNAs or cause their degradation (Wu and Belasco 2008; Lee et al. 1993). miRNA genes, mostly intronic, have also been reported to be present in the intergenic regions (Winter and Diederichs 2011; Nelson et al. 2003). The biogenesis and expression of miRNAs is under the regulation of a number of mediators including DNA methylases and transcription factors (TFs) (Han et al. 2007; Guo et al. 2010). In recent years, the potential of miRNAs to regulate the gene expression has emerged as a tool for diagnosis of a number of diseased conditions, such as cardiovascular diseases, cancer, neurodegenerative disorders and infectious diseases (Li et al. 2009). The review discusses the biogenesis followed by the nomenclature of miRNA, mode of miRNA action and the

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regulation of miRNA expression. It majorily focuses on the miRNA-TF interactions along with their role in coordination and control of cell growth, differentiation and development. In addition, the significance of this combined activity during embryonic development, haematopoiesis, skeletal and cardiac muscle development and macrophage differentiation has been addressed primarily due to the importance of these processes during the early developmental stages.

miRNA biogenesis miRNA genes are transcribed from their own promoters either as independent units or clusters. The independent units include protein coding transcription units (TUs), in the case of intronic miRNA and non-coding TUs, in the case of both, the intronic as well as exonic miRNA. In contrast, the clusters are transcribed as polycistronic primary transcripts (Kim and Nam 2006; Lee et al. 2002; Altuvia et al. 2005). The transcription of miRNA genes by RNA Pol II or RNA Pol III generates pri-miRNA, a large stem-loop structure with a 50 cap and a poly(A) tail (Cai et al. 2004; Fazi and Nervi 2008). This stem-loop structure is asymmetrically cleaved by a microprocessor complex, comprising of an RNase III endonuclease (Drosha) and a double-stranded RNA-binding protein (DiGeorge syndrome critical region gene; DGCR8) to release the precursor of miRNA (pre-miRNA). Pri-miRNA has *70 nucleotide hairpin loop structures (4–5 loops in case of polycistronic units) with flanking RNA sequences necessary for its efficient processing (Lee et al. 2003; Tomari and Zamore 2005). The cleavage of pri-miRNA results in the formation of staggered cuts on both the strands rendering two nucleotide overhangs on the 30 end and a phosphate group on the 50 end of each strand. Alternatively, pre-miRNAs called mirtrons are produced directly through spliceosomal excision from the introns (Denli et al. 2004). These pre-miRNAs are subsequently exported from the nucleus to the cytoplasm by Exportin 5/RanGTP complex, which recognizes the overhangs of pre-miRNAs, thereby, preventing the nuclear degradation of pre-miRNAs (Kim 2004, 2005). This is followed by their incorporation into a processing complex, comprising of RNase III endonuclease (Dicer), the human immunodeficiency virus transactivating response RNA-binding protein and protein kinase R-activating protein (PACT). This complex cleaves the single strand in the pre-miRNA opposite to the strand previously cleaved by Drosha, to generate a double-stranded miRNA duplex with 30 overhang ends (Perron and Provost 2010). Alternatively, there exists an Argonaute 2 (Ago2)dependent processing pathway in which Ago2, the catalytic

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component of the RNA-induced silencing complex (RISC), cleaves a single strand of the pre-miRNA to generate a nicked hairpin structure referred as ‘Ago2-cleaved precursor miRNA’ which is then cleaved by Dicer to generate an miRNA duplex. Unwinding of the duplex occurs with processes dependent on Dicer, the human immunodeficiency virus transactivating response RNA-binding protein, Ago2, helicases, nucleases and RNA-binding proteins. The strand with thermodynamically unstable base, pairs at the 50 end and is incorporated into RISC, also known as microRNA ribonucleoprotein complex (miRNP). The complex is then activated and it regulates the gene expression either by mRNA translational repression or degradation (Macfarlane and Murphy 2010). The different steps involved in miRNA biogenesis have been briefly illustrated in Fig. 1.

Nomenclature of miRNAs Research in the field of miRNA has indicated its potential to serve as a promising clinical therapy which necessitates the standardization of a universally accepted nomenclature system. miRBase (http://www.mirbase.org/) plays an important role in miRNA nomenclature. All novel miRNAs are first submitted to this database for assignment of names prior to their final publication (Griffiths-Jones 2010). The official name is incorporated in the final version of the manuscript. The miRNA nomenclature employs a set of guidelines that have been put forward by eminent miRNA researchers. Furthermore, Rfam, the database of RNA families, provides an online clearing house (http:// www.sanger.ac.uk/Software/Rfam/mirna/) for miRNA naming and aims to assign unique gene names while maintaining the confidentiality of unpublished data (Gardner et al. 2009). miRNAs are designated unique numerical identifiers indicative of the series of their discovery. The initials of the species are borne as a prefix to mir, while the numerical identifier is written as the suffix (Ambros et al. 2003). For instance, a novel miRNA discovered to be non-identical to any earlier identified sequence will be named as dme-mir-319, the previously discovered miRNA being dme-mir-318 in D. melanogaster (Griffiths-Jones 2004). Mature miRNAs are denoted by ‘miR’ while ‘mir’ is allocated to precursors or genes. The genes encoding the miRNA are named using the same three letter prefixes, with capitalization, hyphenation and italicization (e.g. mir-1 in D. melanogaster). Although miRBase offers extensive information regarding miRNA nomenclature, some of the key specifications have been summarized in Table 1. Also, there are few exceptions in the miRNA nomenclature system including lin-4 and let-7 which do not follow the conventional naming process for historic reasons.

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Fig. 1 Steps involved in miRNA biogenesis. In the nucleus, the long primary transcripts (pri-miRNA) transcribed by RNA Pol II or RNA Pol III are processed by the Microprocessor complex/RNase III-type enzyme, Drosha. Hairpin precursors (pre-miRNA) are generated and exported into the cytoplasm by Exportin 5/Ran GTP complex. The

pre-miRNAs are further processed by Dicer to form an unstable miRNA duplex. The two strands unwind and the less stable of the two is incorporated into RISC. This complex binds at a suitable miRNA binding site on mRNA and thus, causes mRNA degradation or translational repression

Table 1 Criteria for miRNA nomenclature Criteria

Nomenclature

Example

Reference

Nearly identical orthologs

Assigned the same number, irrespective of the species

miR-1 of D. melanogaster and C. elegans

GriffithsJones et al. (2006)

Very similar sequences within a species

Same number with only a differing additional letter

dme-mir-13a and dme-mir-13b in D. melanogaster

LagosQuintana et al. (2001)

Sequences when retrieved from discrete loci or separate precursor in an organism

Assigned an additional numerical suffix

dme-mir-6-1 and dme-mir-6-2 in D. melanogaster

LagosQuintana et al. (2001)

Sequences originating from opposite arms of the same hairpin precursor

Differentiated by ‘*’ or written with suffixes 5p and 3p for the 50 and 30 arm, respectively

miR-56 and miR56*/miR-17-5p and miR-17-3p

Lau et al. (2001)

Distinct miRNA species resulting from over-lapping or sequential processing

Distinguished by numerical suffixes

miR161.1 and miR161.2

Meyers et al. (2008)

Plant miRNA

MIR is sufficed by numerals and letters (lettered suffixes describe distinct loci expressing all related mature miRNAs, while no numeric suffixes are used for the plant system)

ath-MIR166a in A. thaliana

Meyers et al. (2008)

Viral miRNA

Inconsistent but always includes the locus from which the miRNA was derived

ebv-mir-BART1 from the Epstein Barr virus BART locus

GriffithsJones et al. (2008)

Animal genome

Additional points (other than animals)

Despite uniformity in the nomenclature system, it must be noted that miRNA names are not a suitable means to confer complex sequence relationships as they provide limited

information. Therefore, other sequence-related and evolutionary information-based approaches must definitely be used to describe these relations.

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Mechanism of miRNA action miRNA binds to the target mRNA at the 30 UTR usually, resulting in the regulation of the expression of the target gene (Hofacker 2007; Place et al. 2008; Orom et al. 2008; Henke et al. 2008). Interaction of miRNA with the 50 UTR region of target sequence has also been witnessed. Liver specific miR-122 has been found to show position-dependent function where its binding site, either 30 UTR or 50 UTR, on target sequence dictates the effect on gene regulation (Jopling et al. 2008). miRNA binding sites have also been reported to reside in the coding region. However, their impact on regulation is much less than binding at sites present in 30 UTR (Fang and Rajewsky 2011). Subsequent to the synthesis and processing, miRNA interacts with the argonaute proteins and results in the formation of RISC, particularly known as miRNP (Bartel 2004). The fate of the target mRNA is determined by the complementarity of the binding site to the miRNA seed sequence (Nilsen 2007). This seed sequence encompasses nucleotides 2–8 at the 50 end of the miRNA. A complete binding of the seed sequence with the target mRNA causes degradation of the target mRNA while an incomplete binding leads to its translational repression (Olsen and Ambros 1999; Shruti et al. 2011). This translational repression or inhibition by miRNAs has been anticipated to occur during the initiation of protein synthesis (Humphreys et al. 2005). Supporting this theory, recent studies on Drosophila S2 cells have shown early translational inhibition as the first step in the decay process of the target mRNA (Djuranovic et al. 2012). Further, action of miRNA-430 in zebrafish embryos occurs through reduction in ribosome density on the target mRNA, decreasing the rate of initiation of translation followed by deadenylation and hence translational repression (Bazzini et al. 2012). A repression through an early termination of translation has been reported in case of an association with the polysomes (Petersen et al. 2006). It has also been observed that it is only the expression of protein which is inhibited while the abundance of mRNA remains unaffected (Pillai et al. 2005; Filipowicz et al. 2008). The miRNA action may follow a slicer dependent pathway or a slicer independent pathway. The former involves endonucleases (Dicer), which first cleave the target mRNA followed by its deadenylation. Alternatively, the latter pathway mediated by Argonaute 2 can lead to translational repression or degradation of the target mRNA in an endonuclease-independent fashion (Macfarlane and Murphy 2010). The action of miRNA is also strongly associated with processing bodies (P-bodies) (Liu et al. 2005a). These cytoplasmic foci, containing a large number of biocatalysts, including nucleases and those like Dcp1/2 as well as 50 –30 exonuclease Xrn1, are involved in the decapping and deadenylation of mRNA (Bashkirov et al. 1997). Studies demonstrate the localization

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of argonaute proteins and targeted mRNAs to P-bodies on phosphorylation of argonaute proteins at ser-387 (Liu et al. 2005b; Zhao and Srivastava 2007). The P-bodies have been proposed to sequester the miRNA targets either by causing their degradation or by serving as a storehouse of the untranslated mRNAs (Pillai 2005).

Regulation of miRNA expression In the developmental context, the transcription factormediated regulation performs an ON or OFF switch function for the consequent gene expression (Flynt and Lai 2008). In addition, miRNAs form an exceptional regulatory circuit that is responsible for the regulation of gene expression and mediation of the cellular developmental processes. This necessitates their own regulation to prevent any diseased condition, as prevalent in tumour-like conditions owing to the over expression of miRNAs and variation in miRNA expression profiles during pathologies (Di Leva et al. 2006). In addition, a study reports the potential use of miRNA expression profiles over mRNA expression profiles in cancer diagnosis for the classification of tumour state (Lu et al. 2005). The expression of miRNAs has been attributed to be tissue and developmental stage-specific in nature due to various factors including transcriptional regulators, complex signalling networks, regulatory sequences present in promoters and the chromatin modifiers (Obernosterer et al. 2006; Neilson et al. 2007). miRNA-mediated expression pattern is regulated by TFs through cell-specific pathways (Hobert 2004). Regulatory elements controlling the transcription and sequential processing of miRNAs are preferentially located upstream of pre-miRNA genes within a 1-kb region (Lee et al. 2007). The TF binding sites have been found to cluster in this region and show overlaps with the predicted transcription start site (TSS) (Saini et al. 2007, 2008; O’Connell and Baltimore 2012). TFs interact with the cis-regulatory motifs, present upstream of TSS, to activate or repress miRNA gene expression. CpG islands in the TSS region, formed as a consequence of DNA hypermethylation and histone modification of miRNA genomic regions in the presence of histone-deacetylases (HDACs), are also the potential regions of regulation (Fazi and Nervi 2008).

Combinatorial action of miRNAs and transcription factors miRNAs and TFs are the principal classes of gene regulators that co-regulate the expression of genes as well as control the expression of each other. It has been observed that the complexity of the transcriptional regulation of a

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gene is positively correlated with the probability that the same gene is regulated by a miRNA (Cui et al. 2007). Henceforth, it can be elucidated that a direct relationship exists between the gene regulation networks controlled by TFs at the transcriptional level and those controlled by miRNAs at the post-transcriptional level. It is believed that miRNAs co-evolve with TFs, and the rapidly evolving TFs preferentially activate miRNAs (Qiu et al. 2010; Chen and Rajewsky 2007). miRNAs can regulate a number of target genes by cleaving or silencing the target mRNAs; whereas TFs direct the transcriptional progression by controlling gene expression for cell growth and differentiation. Recent studies have suggested that miRNAs may provide genetic switch mechanisms to essentially inactivate the target genes by regulation of TF functioning and TF-mediated events (Chen et al. 2011). Genome-wide target predictions have previously shown that TFs are susceptible to regulation by miRNAs (Enright et al. 2003). The active concert of these regulators in association to the regulatory feedback loops orchestrates various cellular mechanisms. The coordinated activity of miRNAs and TFs describes the mechanism of gene expression control. Moreover, to drive or repress the expression of particular miRNAs or TFs, these two elements coordinate to form autoregulatory feedback loops. Such a loop is the one in which the expression of one particular component is directly affected by the presence or absence of another. These loops consist of unilateral or reciprocal negative feedback loops and double-negative feedback loops (Krol et al. 2010) (Fig. 2). In a unilateral feedback loop, the expression of TF is negatively regulated by miRNA while the miRNA is positively regulated by TF. Thus, forming a single loop wherein the expression level of one is entirely dependent on the other. For instance, miR-133b has been found to function through a unilateral feedback loop in the midbrain dopamine neurons, where transcription factor, PITX3 specifically induces the transcription of miR-133b, while its own activity is downregulated post-transcriptionally by miR-133b (Kim et al. 2007). In reciprocal negative feedback loops, the miRNA represses TF expression, directly, by binding to complementary sequences within mRNA UTR of the TF while the miRNA is itself repressed by the TF. For instance, such a double loop is observed between miR-7 and Yan, an ETSdomain transcription factor, during differentiation of cells to photoreceptors in Drosophila wherein the transcription of miR-7 is downregulated by Yan in the cells while miR-7 represses the expression of Yan in the photoreceptors (Li and Carthew 2005). In addition to this, double-negative feedback loop has been observed in ASE chemosensory neurons of C. elegans where TF-regulated miRNA is directly responsible for transcriptional activation and inactivation, whereas the miRNA is itself regulated by TF. miR-273 expression is stimulated by the COG-1 TF while

miR-273 itself targets the DIE-1 transcription factor in right ASE (ASER). In left ASE (ASEL), DIE-1 activates lys-6 expression and promotes the ASEL-specific cell fate, while lys-6 blocks COG-1 (Johnston et al. 2005). TFs interact with each other to regulate the expression patterns by binding at DNA fragments with multiple sites for TFs, called cis-regulatory modules (CRMs). Similar to TFs, miRNAs hybridize to cis-regulatory RNA elements which are mostly located in the 30 UTR of their target mRNAs (Martinez and Walhout 2009). The co-regulation of TFs and miRNAs involves the formation of modules of CRMs and miRNAs, where the trans-acting factors specific for the cell type bind to the CRM in proximity to the gene. It has also been reported that genes jointly regulated by a specific CRM-miRNA module have different expression patterns in terms of the regulation of the corresponding CRM or miRNA (Su et al. 2010). However, the superiority of combinatorial action of these ‘trans’ regulators over individual action remains unestablished, although, it has been proposed that a co-regulation mechanism between the two may play an important role in many biological processes (Chen et al. 2011). The gene regulatory network of CRM-miRNA module includes regulatory loops and multilayered networks, of which, feed forward loops (FFLs) are most likely to be formed. A FFL is composed of input transcription factors and miRNAs, one of which regulates the other, both jointly regulating a target gene. FFLs can be miRNA-mediated where the miRNA may simultaneously repress the TF and its target genes (Fig. 3a). Hence, the target genes will only express on downregulation of the miRNA. This causes buffering of noise as the leaky expression is minimized (Shalgi et al. 2007; Collins 2011). Such a FFL has been observed between miR-208, GATA-4 and the target gene, a-myosin heavy chain (a-MHC) in the cardiac muscle wherein GATA-4 stimulates the cardiac muscle-specific expression of a-MHC, while miR-208 represses GATA-4 transcriptional activity and a-MHC expression, thus, acting as an important regulator of cardiac hypertrophy (Molkentin et al. 1994; Callis et al. 2009; Zhou et al. 2012). Conversely, in TF-mediated FFLs, the miRNA and target genes are activated or repressed simultaneously by a TF, thereby causing an incoherent effect on the expression of target genes, since the two pathways have opposite effects resulting in co-expression of miRNA and its target (Fig. 3b1, b2). The target gene gets suppressed on an event of the downregulation of TF or when there is a delay in the activation by the TF (Stark et al. 2005). An incoherent loop where the transcription factor, c-Myc, a regulator of cell proliferation, growth and apoptosis, activates miR-17-5p and miR-20a and the target gene E2F1 simultaneously, has been identified in the biological system. Such a network ensures a tightly controlled signal where c-Myc not only activates E2F1 transcription directly, but also limits its

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Mol Genet Genomics Fig. 2 miRNA-TF feedback loops. a Unilateral feedback loop, b reciprocal negative feedback loop, and c doublenegative feedback loop ); inhibition (activation ( ( ))

Fig. 3 miRNA-TF feedforward loops. a miRNAmediated FFL: miRNA simultaneously represses a TF and target gene. Target gene expresses upon downregulation of miRNA. b TF mediated FFL: 1 simultaneous activation of miRNA and target gene causes an incoherent effect on the expression of target gene, 2 simultaneous repression of miRNA and target gene causes an incoherent effect on the expression of target gene, 3 activation of target gene and inhibition of miRNA by TF leads to a coherent effect on the expression of target gene, 4 activation of miRNA and inhibition of target gene by TF leads to a coherent effect on the expression of target gene. c Composite FFL: miRNA represses TF and target gene, while the TF activates miRNA and the target gene. (activation ); inhibition ( )) (

translation indirectly (O’Donnell et al. 2005). Furthermore, a coherent effect occurs when the TF activates the target gene and inhibits the miRNA simultaneously (Fig. 3b3) or activates the miRNA and inhibits the target gene (Fig. 3b4), since both pathways from the mediator to the target have the same effect (either repressing or activating

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the target gene expression). The first type of coherent loop has been found between TGF-b, miR-29 and the cardiac fibrotic genes like elastin, collagen, fibrillin in the heart where TGF-b negatively regulates miR-29 expression but is an agonist for the synthesis of fibrotic genes in cardiac fibroblasts and miR-29 regulates cardiac fibrosis by

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silencing the cardiac fibrotic genes. The other type of loop can be observed between Pnt-P1, miR-7 and target gene, Yan in the imaginal disc of D. melanogaster eye. This coherent FFL ensures inhibition of the expression of Yan by causing activation of miR-7 as well as direct inhibition of the target gene (van Rooij et al. 2008; Inui et al. 2010). In addition to this, these FFLs facilitate avoidance of expression of the targets in the same tissue or at the same developmental stage, known as a spatio-temporal avoidance (Shalgi et al. 2009). Another type of FFL is the composite FFL which shows bi-directional relationship, where the miRNA represses the TF and the target gene, while the TF, in turn, activates the other two (Martinez and Walhout 2009) (Fig. 3c). Such a network can be witnessed between Myc, miR-17-92 cluster and target gene, E2F during cell cycle regulation in cancer where members of miR-17-92 cluster have been found to negatively regulate Myc and E2F while Myc induces the transcription of the cluster (Aguda et al. 2008). Studies on different FFL architectures have proposed that besides, fine-tuning the expression level of single genes by repressing the translation, miRNA-TF pairs act as an alternative mechanism to dampen excessive fluctuations in the mRNA level with a ‘quick-OFF-slow-ON’ switching device (Sevignani et al. 2006; Yiming et al. 2007). This combinatorial action of miRNAs and TFs to control the ON/OFF switch is an important mechanism that plays significant role during cell growth, differentiation and development. Moreover, this miRNA-TF correlation acts to maintain the genomic integrity and is also capable of altering cell fate by genetic manipulations. A disruption in this co-regulation has been associated with cancer metastasis (Guohua et al. 2008; Chang et al. 2008; Bueno et al. 2008; Calin et al. 2002, 2004). A feedback loop regulated by transcription factor ZEB1 and miR-200 during epithelial-mesenchymal transformation was identified (Reshmi et al. 2011). The mechanism of miRNA-TF combinatorial action has been elaborated further through powerful models of specific early development, cellular and lineage specification as well as differentiation pathways for a deeper insight into the biological functioning of miRNA-TF complexes.

Coordinated activity of miRNA and transcription factor in embryonic development Embryonic development is a precisely integrated process that requires several molecular coordinators for an appropriate cell proliferation, fate determination and differentiation (Mammoto and Ingber 2010). miRNAs have been found to display regulatory effects at various stages of embryonic development. Studies on zebra fish and mice have elucidated that repression or activation of certain

miRNAs present in the embryos may lead to unusual development (Zhao and Srivastava 2007). However, miRNAs are not the solitary regulators of embryonic development, while it is their combined action along with TFs that is crucial for a typical regulation of embryonic development. Oct4, Sox2 and Nanog are few of the earliest genes encoding TFs to regulate the development of human embryonic stem cells, and are related to the gene loci of 14 miRNAs (Boyer et al. 2005; Cole and Young 2008). A double-negative feedback loop connecting miR-145 and OCT4, SOX2 and KLF4 has been observed in the human embryonic stem cells wherein miR-145 expression downregulates OCT4, SOX2 and KLF4, while OCT4 represses miR-145 by binding to its promoter (Na et al. 2009). Furthermore, the binding sites of miR-21 have been located on Sox2 and Nanog mRNAs and are believed to affect the expression of Oct4, Sox2 and Nanog (Wang et al. 2009; Marson et al. 2008). Also, it appears that a class of Zn-finger FLYWCH transcription factors, that includes FLH-1, FLH2, and FLH-3, are particularly involved in inhibiting miRNA expression in embryos, and other regulatory mechanisms in C. elegans (Ow et al. 2008). The study of miRNAs, along with TFs and other regulatory factors, can give new insights on the understanding of embryonic development and may assist in the advancement of therapeutics.

Coordinated activity of miRNA and transcription factor in haematopoiesis The hematopoietic system is one of the first complex tissues to form in the developing mammalian embryo (Dzierzak and Speck 2008). Haematopoiesis, a highly regulated life-long process, generates differentiated blood cells in the bone marrow and lymphatic tissue (Shivdasani and Orkin 1996). The differentiation is strongly regulated by various factors including TFs, miRNAs and their concerted combinatorial action. miR-223, associated with granulocytic differentiation, is regulated by two transcription factors, namely, NFI-A and C/EBPa. NFI-A downregulates miR-223 and C/EBPa induces the expression of miR-223 leading to granulocytic differentiation (Gronostajski 2000; Radomska et al. 1998). However, NFI-A is repressed by miR-223 through a feedback loop formation (Fazi et al. 2005). In addition, another such example is observed during monocyte-macrophage maturation where transcription factor AML1 has been found to regulate expression of many haematopoietic genes by downregulating the expression of miR 17-5p-92 and 106a-92 cluster, and in turn serving as a target to these miRNAs (Fontana et al. 2007). During maturation, the miRNAs are downregulated causing an increased expression of AML1, which further downregulates the miRNAs. Hence, the regulatory

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loops maintain the cycle of differentiation and generation of different blood cells.

Coordinated activity of miRNA and transcription factor in cardiac and skeletal muscles Cardiac function is required during early embryogenesis for survival and subsequent growth of other cell types. miRNAs have been found to play regulatory functions in muscle development. miR-1, miR-133 and miR-206 have been reported to be highly expressed during cardiac development. miR-1 and miR-206 possess an identical seed sequence and are related to each other in their function and expression. However, since both miRNAs are present in different genomic loci, their expression and regulation differ. miR-1 is predominantly enriched in cardiac and skeletal muscle tissues, but miR-206 is a skeletal musclespecific miRNA (Liu et al. 2007). Moreover, these are coexpressed along with miR-133 as a bicistronic unit from three different genomic loci. miR-133 is also involved in cardiac muscle development, even though it is not abundant. Although miR-1 and miR-133 are important regulators in cardiac development, they have antagonistic functions. While miR-1 promotes and regulates cell-differentiation, miR-133 is responsible for cell proliferation and maintenance of the progenitor cell pool (Chen et al. 2006). The expression of these miRNAs is controlled by myogenic transcriptional factors including serum response factor (SRF), MyoD and Mef2 (Wang et al. 2001). SRF regulates miR-1 and miR-133a expression in the cardiac muscles. In addition to this, these miRNAs are expressed in skeletal muscles under the control of MyoD and Mef2. Also, MyoD activates the expression of miR-206, present only in the skeletal muscles (Kim et al. 2006). On the other hand, these TFs are under the control of the same miRNAs, hence crafting a feedback regulatory loop, as in case of SRF and miR-133, wherein SRF activates miR-133 expression in cardiac cells, which further leads to its own inhibition since SRF is itself a target for repression by miR-133, specifically miR-133a (Nilsen 2007; Liu et al. 2008). This combinatorial action regulates the differentiation and proliferation of cells. Furthermore, miR-208 has been found to express specifically in cardiac tissue and is known to target GATA-4, an early cardiac differentiation marker (Callis et al. 2009). A similar negative regulatory loop has been observed in skeletal muscle cells where miR-133 and miR-1 along with SRF and HDAC4, linked ultimately to MyoD, control the specific pathways collectively (Chen et al. 2006; Rao et al. 2006). Transcription factor, Pax7, supports the proliferation of the skeletal muscle satellite cells (Zammit et al. 2006). For differentiation of satellite cells to myogenic progenitor, miR-1

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and miR-206, bind to the target sites present at the 30 UTR, hence, downregulating the expression of Pax7. An absence of this regulation inhibits the myoblast differentiation (Jian-Fu et al. 2010). Thus, similar to the regulation of all other biological processes, the muscle system is under the combinatorial regulation of both miRNAs and transcription factors.

Coordinated activity of miRNA and transcription factor in macrophage differentiation Macrophages, the large phagocytic cells derived from monocytes, are a heterogenous population of cells present in various organs and tissues of humans and animals. These short lived and non-dividing terminal cells belong to the mononuclear phagocyte system (Pospisil et al. 2011). They are differentiated from their progenitor cells through different routes and the involvement of miRNAs during macrophage differentiation has been observed. One of such novel gene circuitry for normal macrophage differentiation contains transcription factor PU.1 and Egr2 associated to the polycistronic miR-17-92 microRNA cluster. This cluster carries six miRNAs (miR-17, miR-18a, miR-19a, miR-20a, miR-19b-1 and miR-92a) and a mutual regulatory relationship exists between miR-17-92 cluster and Egr2 induced by PU.1 (Ghani et al. 2011). In addition, PU.1 also controls the expression of miR-146a, miR-342, miR-338 and miR-155. Studies have indicated a selective differentiation of haematopoietic stem cells (HSCs) into functional macrophages in mouse transplantation studies as well as an inhibition of macrophage formation in early zebrafish (Danio rerio) on interruption of miR-146a function (Takahashi 2001). Also, a decrease in expression of miR-223, miR-15a and miR-16 during human monocytemacrophage differentiation has been reported. This decrease elevates the expression of IKKa, stabilizes kinase NIK and enhances expression of p52 which further modulates the noncanonical NF-jB pathway (Li et al. 2010).

Conclusion The discovery of miRNAs and their regulatory functions in various biological events has revealed new insights into the complexities involved in the gene regulatory networks. Transcription factor aided co-action of the miRNA molecules provides another regulatory check on the gene expression. The degree of expression of miRNAs has been correlated to normal and diseased conditions. The understanding of miRNA-TF interactions shall be of great relevance and can provide a novel therapeutic approach of modulating specific transcription factors for the treatment of various diseases using miRNA mimics or antagomers.

Mol Genet Genomics Acknowledgments We acknowledge Jaypee Institute of Information Technology (Deemed to be University), Noida, India for the support. The work is supported by the grant received by Dr. Vibha Rani from Department of Biotechnology, Ministry of Science and Technology, India.

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