Abstract
Many facets of transcriptional and translational regulation contribute to the proper functioning of the nervous system. Dysfunctional control of mRNA and protein expression can lead to neurodegenerative conditions. Recently, a new regulatory control element—small noncoding RNAs—has been found to play a significant role in many physiologic systems. Here, we review the microRNA (miRNA) field as it pertains to discovery-based and mechanistic studies on the brain and specifically in neurodegenerative disorders. Understanding the role of miRNAs in the brain will aid to open new avenues to the field of neuroscience and, importantly, neurodegenerative disease research.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
To date (06/01/09), there are 9,539 microRNA (miRNA) entries in the online repository miRBase (version 13.0, http://miRNA.sanger.ac.uk) and many more new sequences are being added on a regular basis. The fundamental understanding of miRNA biogenesis and its function has tremendously increased over the past 5 years. Almost all fields in biology have been transformed with the discovery of small noncoding RNAs, leading to novel discoveries on how these molecules affect biological functions.
miRNA biogenesis
As the name “micro” suggests, miRNAs are tiny ∼20–22 nucleotide (nt) regulatory RNA molecules, which are encoded by the genome but are not translated into protein. Instead, they play a potential role to control the gene expression by associating with the 3′ untranslated region (UTR) of nascent messenger RNA (mRNA) molecules thereby repressing their expression. These miRNAs have been identified in a broad scale of genomes ranging from viruses to humans (Lagos-Quintana et al. 2001; Lau et al. 2001; Lee and Ambros 2001; Reinhart and Ruvkun 2001; Bentwich et al. 2005; Berezikov et al. 2005).
The biogenesis of miRNAs has been extensively studied and reported. The early steps in biogenesis begin in the nucleus where the miRNA genes are predominantly transcribed by RNA polymerase II (with some by RNA polymerase III) into primary miRNA transcripts also called as pri-miRNAs (Cai et al. 2004; Lee et al. 2004; Borchert et al. 2006). The pri-miRNA is cleaved by a nuclear microprocessor complex, which includes an endonuclease RNA III enzyme named Drosha; and a protein component termed Di George critical region 8 (DGCR8), which also goes by the name Pasha in Drosophila melanogaster and Caenorhabditis elegans (Denli et al. 2004). This latter co-factor, DGCR8/Pasha, interacts with the ∼33-bp stem of the pri-miRNA thereby aligning and anchoring it for subsequent Drosha cleavage (Han et al. 2006). The pri-miRNAs are then cleaved by Drosha in the nucleus to produce ∼70-nt precursor miRNAs (pre-miRNAs) with a hairpin structure (Lee et al. 2003). The pre-miRNA is then shuttled to the cytoplasm where it is cleaved by another RNase III enzyme, Dicer, thereby generating a mature ∼20–22-nt double-stranded RNA molecule (Hutvagner et al. 2001). The double-stranded molecule is unwound first, and the stable strand is chosen to be recruited by a RNA-induced silencing complex (RISC) comprising of Argonaute and related proteins (Peters and Meister 2007). RISC binds to the 3′ UTR of the mRNA molecules with an imperfect complementary to the miRNA, leading to mRNA degradation and/or translational inhibition, resulting in decreased protein expression (Pillai 2005; Nilsen 2007). While sites of miRNA action in the 3′-UTR are the most common, the protein-coding region can also contain functional miRNA targets (Rigoutsos 2009).
Tools and techniques to isolate and identify miRNAs
For the past decade, substantial work has been done on identifying new miRNAs in the mammalian genome, and new techniques have been developed to monitor their function. The major challenge in miRNA biology is the enrichment of small species from the complex pool of abundant species that include rRNA, tRNA, and mRNA. Moreover, the miRNA itself exists in three forms: short mature form, hairpin pre-miRNA, and long pri-miRNA. The isolation of short mature forms (the functional form) is often a tricky process. Several techniques have been used to purify small RNA species from the pool and have made researchers’ jobs more straightforward. Techniques such as forward genetics were extensively used in the past to study and identify miRNAs in C. elegans and D. melanogaster; and in fact, the first miRNAs, lin-4 and let-7, were discovered by this method (Lee et al. 1993; Reinhart et al. 2000).
However, due to several limitations (Berezikov et al. 2006) forward genetics has proven to be relatively inefficient. cDNA cloning and sequencing methods have proven to be very useful tools to identify many miRNAs (Lagos-Quintana et al. 2001; Lau et al. 2001; Lee and Ambros 2001). This technique has been employed to samples expressing low amounts of RNA or to rare cell types (Berezikov et al. 2006). A variation in sequencing techniques called “deep sequencing” was introduced as a technological breakthrough using advanced sequencing platforms. Although this technique invariably helped to profile known and novel miRNAs at exceptional sensitivity, the main drawback was the need of good algorithms for eliminating the false-positive data. Recently, an ingenious publicly available software called “miRDeep” was developed to help estimate the false-positive rate and sensitivity of the runs (Friedlander et al. 2008).
Currently, the most widely used method for characterization of miRNAs expression has been the microarray method. The first probing was done as dot blotting on nylon membranes (Krichevsky et al. 2003), which proved to be very inexpensive but required larger amounts of RNA. Later, researchers developed a much more sensitive method to screen miRNAs from smaller samples by hybridizing the probes to glass slides (Liu et al. 2004). The microarray has a more preferable platform as it can conveniently screen a larger number of miRNAs and is flexible for probe design. The main limitation that is encountered in the microarray is the specificity of probe binding that is mainly caused by the short length of the probe. Several nucleic acid analogs have been introduced lately to the market such as the LNA (locked nucleic acid) and PNA (peptide nucleic acid) that result in more favorable hybridizations than the conventional array platforms. High-throughput microarray profiling is now used for detecting miRNAs and other small RNAs in complex tissues of higher mammals (Maroney et al. 2007). Arrays to assess miRNAs can be made by researchers and are also available from a number of commercial sources. However the true sensitivity, specificity, and reproducibility of these arrays remain to be determined.
Modified probes also have been designed to improve sensitivity and specificity for Northern blotting techniques, a technique which is also widely used for detection of miRNAs (Valoczi et al. 2004). Several other technologies have been developed to study miRNAs from diseased tissues and limited tissues, such as biopsy samples or brain sections. One of the widely used technologies for such small samples, as well as to validate array-based findings, is quantitative real-time polymerase chain reaction. Both the Taqman and LNA technology have been used to improve the sensitivity in detecting and quantifying low abundant miRNAs. Bead-based methods for analysis by flow cytometry, RNA-primed-array-based Klenow enzyme assay and nanotechnology are a few of the many technologies being developed for increasing the sensitivity of miRNAs (Kong et al. 2009).
miRNAs, the mammalian brain, and neurodegenerative disorders
The mammalian brain is the most complicated organ to study, not only from the gross functional, structural, and evolutionary distinctiveness but also due to its complexity at the molecular level. Though the human genome has been fully deciphered, the human brain transcriptome still remains to be solved. Progress is continuing on assessing mRNA expression patterns in the brain; for example, the Allen brain atlas (http://www.brain-map.org) is due to be completed in 2012. However, another level of complexity arises as one starts to screen for miRNAs that can regulate these genes in the human brain. The unprecedented role of miRNAs in regulating mRNA levels and protein has led to intense interest in studying miRNA expression and function in the central nervous system (CNS).
While discovery-based and profiling studies continue in addition to the crucial follow-up mechanistic studies, one aspect that has received less attention is the necessity to provide a regional and cell-type specific examination of miRNA expression in the normal and diseased brain. The brain not only is quite heterogeneous in structure and function, but also is made up of a number of cell types of which only a minority are neurons. While the effects of non-neuronal cell types on neurons and CNS function are profound, it is important to delineate whether changes in miRNAs that are found in the brain occur in neurons, glia, or other cell types. The only way to definitively show this is through in situ hybridization, which remains a difficult technique in miRNA assessment. While a number of new protocols have been described recently (Nuovo 2008; Nelson and Wilfred 2009; Nuovo et al. 2009a, b; Pena et al. 2009), optimized protocols, especially to include double labeling to allow cell-type identification, remain a distinct goal.
The importance of miRNAs in the nervous system was first described in Danio rerio (zebrafish) where a mutation in dicer led to failure to produce mature miRNAs and resulted in gross morphological defects in the nervous system (Wienholds et al. 2003). Effects of specific miRNAs on neurons have been found in a number of organisms including mammals. For example, during neurogenesis, the levels of both miR-124 and miR-9 are greatly increased, and in vitro experiments have linked both to neuronal differentiation (Conaco et al. 2006; Krichevsky et al. 2006). Deep sequencing of miRNAs derived from tissues and cell lines have revealed these and other miRNAs to be restricted to the CNS (Landgraf et al. 2007). Definitive proof of the role of miR-124 in neurogenesis has now been achieved in vivo, revealing its critical role in the differentiation of neurons from neural precursors (Cheng et al. 2009).
In addition to differentiation of neurons, miRNAs have been shown to affect crucial aspects of neurons. For example, neurite outgrowth is regulated by miR-132 (Vo et al. 2005). Furthermore, one crucial functional aspect of neurons, the synapse, is under miRNA control. In the hippocampus, miR-134 regulates the size of dendritic spines, sites of synaptic transmission (Schratt et al. 2006). Further linking of miRNAs to synaptic changes and the implications of such in brain development and plasticity was the recent demonstration that miR-138 controls dendritic spine morphogenesis (Siegel et al. 2009).
Recognizing the role of miRNA in neuronal development and control of neuronal functional elements, it is not surprising that many researchers have sought to link miRNAs to neurodegenerative diseases. Many studies have been done in Alzheimer’s disease (AD), profiling miRNAs as well as linking miRNAs to expression of putative pathogenic molecules such as beta-site amyloid precursor protein-cleaving enzyme 1 (beta-secretase, BACE1). Two studies have linked different miRNAs (miR-29a/b-1 and miR-107) to modulation of expression of BACE1 in AD (Hebert et al. 2008; Wang et al. 2008); regulation of BACE1 by miR-298 and miR-328 has also been reported (Boissonneault et al. 2009). Notably, for miR-107, its expression was found decreased in the brains of those with AD even at the early stages of pathology (Wang et al. 2008). In addition to BACE1, studies have revealed that the related miRNAs miR-20a, miR-17-5p, and miR-106b can regulate the level of amyloid precursor protein in vitro, and it was found that the levels of miR-106b were decreased in the brains of AD patients (Hebert et al. 2009). Furthermore, miR-146a is increased in AD and linked to inflammatory and/or stress responses (Lukiw et al. 2008). Others have also reported differences in miRNA profiles in AD (Cogswell et al. 2008; Sethi and Lukiw 2009). Given the complexity of AD, it is likely that additional studies will add to our understanding of miRNA perturbations in this disorder.
Huntington’s disease (HD), which results from polyglutamine- mutant huntingtin (Htt) protein, is characterized by neuronal mRNA dysregulation. One function of the Htt protein is to sequester the transcription factor REST in the cytoplasm. Mutant Htt is unable to perform this function and REST translocates to the nucleus, where it decreases neuronal gene expression. A number of miRNAs are targets for REST, and in a mouse model for HD (the R6/2 transgenic line), four of these: mir-29a, mir-124a, mir-132, and mir-135b show decreased expression in the cortex (Johnson et al. 2008). Examination of human HD brains revealed that mir-132 was also downregulated; however, in human samples, mir-29a and mir-330 (another REST-targeted miRNA) were upregulated (Johnson et al. 2008). The genes encoding miR-9/miR-9* are also targets for REST, and another study found that these miRNAs are also decreased in HD brain, and interestingly themselves regulate components of the REST complex (Packer et al. 2008). In keeping with such findings, there are a number of perturbations in miRNAs in both human and mouse models of HD (Johnson et al. 2008). Intriguingly, in addition to sequestering REST, wild-type Htt protein stabilizes interactions within the RISC, but the mutant Htt inhibits the formation of such complexes (Savas et al. 2008). Thus, in HD, the expression as well as function of miRNA may be altered, both leading to changes in neuronal protein composition.
Whereas HD results from polyglutamine-mutant Htt, spinocerebellar ataxia type I (SCAI) results from polyglutamine-mutant ataxin 1 (ATX1). The level of the mutant protein affects disease severity, and three miRNAs (miR-19, miR-101, and miR-130) can alter the level of ATX1 (Lee et al. 2008). Interestingly, this study found that these miRNAs act cooperatively in reducing ATX1 levels, and are indeed expressed in infected neurons, and that in a cell culture model, their inhibition (leading to increased mutant ATX1) resulting in increased cytotoxicity, linking this miRNA regulation to disease mechanisms.
TDP-43-positive frontal temporal dementia with ubiquitin positive, tau-negative inclusions (FTLD-U) results from a number of different loss of function mutations in the progranulin (GRN) gene. Interestingly, a common genetic variant in the 3′-UTR of the GRN gene increases the risk for FTLD-U, and this variant leads to creation of an efficient binding site for miR-659, which was shown to reduce expression of GRN carrying this variant (Rademakers et al. 2008). Individuals with this variant had reduced levels of GRN in their brains, revealing another mechanism in FTLD-U through post-transcriptional decreased GRN expression.
Parkinson’s disease (PD) results from the loss of dopaminergic neurons in the midbrain. Downregulation of miR-133b is found in the midbrain of humans with PD (Kim et al. 2007). Interestingly, this study demonstrated that miR-133b participates in a feedback loop with the transcription factor Pitx3 controlling the development and function of dopaminergic neurons. In autosomal-dominant PD as well as transgenic mouse models of PD, increased α-synuclein is causative for disease, and accumulation of α-synuclein is characteristic of spontaneous PD. α-synuclein has been found to be regulated by miR-7, and in the MPTP neurotoxin model of PD, miR-7 levels decrease (Junn et al. 2009).
While these disorders are sporadic and/or genetic in nature, neurodegeneration also occurs from infectious etiologies. Prion diseases (also known as transmissible spongiform encephalopathies) result from the abnormal conversion of a normal host protein into an infectious neuropathogenic form. In mice, dysregulation of miRNA expression was found in prion-infected brains, with both up- and downregulation of specific miRNAs (Saba et al. 2008). Human immunodeficiency virus (HIV)-associated neurocognitive disorder (HAND) develops in a subset of individuals infected with HIV-1 and results from an indirect neurotoxicity, since HIV only infects macrophages and microglia in the brain. While mRNA dysregulation has been demonstrated in humans with HAND as well as monkeys with simian immunodeficiency virus (SIV)-induced CNS disease (Roberts et al. 2003; Masliah et al. 2004; Roberts et al. 2006), miRNA alterations have not yet been reported. Given the findings in the other neurodegenerative disorders above, it will be of interest to assess whether the mRNA changes and the neuronal dysfunction are linked to miRNA alterations in people with HAND and in the monkey/SIV model.
Perspectives
There remains much needed discovery-based work on miRNA. New miRNAs are still being identified, and obtaining knowledge of the expression pattern of known and new miRNAs during neuronal development, plasticity, normal functioning, and disease is a significant challenge. This is compounded in the brain by the intermixture of different cell types within the brain, as well as the numerous different anatomic and functional regions within the brain. Although difficult with these small RNAs, there is no substitute for in situ hybridization studies to follow up various experimental findings in order to assess the regions and cell types (often necessitating combination with immunohistochemistry for cell type identification) responsible for miRNA expression patterns.
Regarding the cell types, it is notable that to date the focus of research has been on neuronal expressed miRNAs. While this is understandable, it ignores the very real possibility that glia or other cells within the CNS cells contribute to or are themselves responsible for the neuronal changes, as non-cell autonomous neurodegeneration is likely not uncommon (Lobsiger and Cleveland 2007). All cell types express miRNAs, and miRNA alterations likely have a role in tumors of the CNS, such as medulloblastomas and astrocytomas (Pang et al. 2009). In addition, neurons themselves have structurally and functionally distinct domains, and distinct miRNAs have been found in the dendrites and at the synapse (Schratt et al. 2006; Kye et al. 2007; Lugli et al. 2008); in concert mRNAs as well as protein synthetic machinery exists there as well (Schuman et al. 2006). Furthermore, astrocytes are integral components of the tripartite synapse, at the synpase, emphasizing the need to assess non-neuronal cell types that can affect neuronal function. Finally, while model organisms will continue to be of great utility, there is no substitute for studies performed on human brains, due to human specific functionality as well as true disease manifestations.
Many studies have identified an miRNA that is altered in expression, and then search for potential targets, using bioinformatic approaches followed by experimental validation. While this approach has been fruitful, there is a high chance we are losing important findings. First, the bioinformatic techniques to identify targets are imperfect and often have little overlap between different algorithms. Although false positives will be identified in the validation experiments, false negatives will be lost, and still other potential candidates will never be chosen for validation. Second, miRNAs each regulate multiple transcripts. While a focus on individual candidate genes is more accessible experimentally, the overall effect of altered miRNA expression is to change the level of hundreds of proteins (Baek et al. 2008; Selbach et al. 2008). Understanding how these changes work in concert to affect function requires a broader approach in investigations. Third, as exemplified nicely in the SCAI study described above (Lee et al. 2008), a given miRNA species does not exist alone, and is expressed in the context of other miRNAs with which it may work cooperatively. A focus on a single miRNA, similar to focusing on a single target, may confound discovery of the true biological effect resulting from altered miRNA expression. In this regard, it has been recently shown that the common method of transfection to experimentally induce high levels of an miRNA under study can lead to competition with endogenous miRNA for the cellular processing machinery, leading to artifactual increases in their targets (Khan et al. 2009).
While there is no simple solution to these issues, investigation of miRNA function in neurodegenerative diseases has benefited from several approaches. For discovery-based approaches, transcripts for candidate disease-specific protein-coding genes can be examined bioinformatically for potential miRNA binding sites, and then tested for regulation by those miRNAs. Altered expression of identified miRNAs can be then assessed in models of disease or diseased tissue itself. A complementary strategy is to assess miRNA profiles in disease models or diseased tissue, verify altered expression of specific miRNAs, and perform bioinformatic analysis for transcripts that may be regulated by these miRNAs, followed by verification. Instead of bioinformatics, other approaches such as gene array or proteomic analysis of appropriate cell lines or primary cells engineered to over- or under-express these miRNAs, are likely to lead to novel avenues of research and understanding. (Baek et al. 2008; Selbach et al. 2008; Barbato et al. 2009). Investigation and understanding of the cell-type specific regulation is critical, as many of the discovery-based studies first examine miRNA in homogenates of mixed cell types from the brain. Studies in disease models, both in cell culture and in model organisms, will not only provide the needed proof of relevance of molecular studies to mechanistic systems, but enable the better understanding of the complex interactions that occur in cells, tissues, and organisms. In this regard, better computational tools will be essential, and a holistic systems biology would complement well the reductionist nature of study of single miRNAs and single target transcripts.
Conclusion
Brain research has taken a major turn towards translational medicine. The basic understanding of the nervous system in the fields of neuroanatomy, neurophysiology, and neurochemistry has been extensively studied; but, as of yet, the cure for neurodegenerative disorders is still a daunting task for neuroscientists. The technological breakthroughs in neuroscience research, such as genomics and proteomics, have already led to great understandings about the genes and proteins involved that cause several neurological diseases. However, a deeper understanding on the regulation of these genes and proteins is needed. The discovery of miRNAs has opened new avenues of research in neuroscience to understand neurodegenerative disorders. Contributions of miRNA study to the areas of brain development, neurogenesis, neural differentiation, and synaptogenesis have been striking. Recent work on miRNAs in neurodegenerative diseases is quite promising. The study on disease-associated miRNAs, their mRNA targets, and resulting changes in protein products will continue to be an exciting field of research, leading to a greater understanding of the regulatory effects of the miRNA, and how their dysregulation leads to neurodegenerative diseases.
References
Baek D, Villen J, Shin C, Camargo FD, Gygi SP, Bartel DP (2008) The impact of microRNAs on protein output. Nature 455:64–71
Barbato C, Arisi I, Frizzo ME, Brandi R, Da Sacco L, Masotti A (2009) Computational challenges in miRNA target predictions: to be or not to be a true target? J Biomed Biotechnol 2009:803069
Bentwich I, Avniel A, Karov Y, Aharonov R, Gilad S, Barad O, Barzilai A, Einat P, Einav U, Meiri E, Sharon E, Spector Y, Bentwich Z (2005) Identification of hundreds of conserved and nonconserved human microRNAs. Nat Genet 37:766–770
Berezikov E, Guryev V, van de Belt J, Wienholds E, Plasterk RH, Cuppen E (2005) Phylogenetic shadowing and computational identification of human microRNA genes. Cell 120:21–24
Berezikov E, Cuppen E, Plasterk RH (2006) Approaches to microRNA discovery. Nat Genet 38(Suppl):S2–S7
Boissonneault V, Plante I, Rivest S, Provost P (2009) MicroRNA-298 and microRNA-328 regulate expression of mouse beta-amyloid precursor protein-converting enzyme 1. J Biol Chem 284:1971–1981
Borchert GM, Lanier W, Davidson BL (2006) RNA polymerase III transcribes human microRNAs. Nat Struct Mol Biol 13:1097–1101
Cai X, Hagedorn CH, Cullen BR (2004) Human microRNAs are processed from capped, polyadenylated transcripts that can also function as mRNAs. RNA 10:1957–1966
Cheng LC, Pastrana E, Tavazoie M, Doetsch F (2009) miR-124 regulates adult neurogenesis in the subventricular zone stem cell niche. Nat Neurosci 12:399–408
Cogswell JP, Ward J, Taylor IA, Waters M, Shi Y, Cannon B, Kelnar K, Kemppainen J, Brown D, Chen C, Prinjha RK, Richardson JC, Saunders AM, Roses AD, Richards CA (2008) Identification of miRNA changes in Alzheimer’s disease brain and CSF yields putative biomarkers and insights into disease pathways. J Alzheimers Dis 14:27–41
Conaco C, Otto S, Han JJ, Mandel G (2006) Reciprocal actions of REST and a microRNA promote neuronal identity. Proc Natl Acad Sci USA 103:2422–2427
Denli AM, Tops BB, Plasterk RH, Ketting RF, Hannon GJ (2004) Processing of primary microRNAs by the microprocessor complex. Nature 432:231–235
Friedlander MR, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S, Rajewsky N (2008) Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol 26:407–415
Han J, Lee Y, Yeom KH, Nam JW, Heo I, Rhee JK, Sohn SY, Cho Y, Zhang BT, Kim VN (2006) Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell 125:887–901
Hebert SS, Horre K, Nicolai L, Papadopoulou AS, Mandemakers W, Silahtaroglu AN, Kauppinen S, Delacourte A, De Strooper B (2008) Loss of microRNA cluster miR-29a/b-1 in sporadic Alzheimer’s disease correlates with increased BACE1/beta-secretase expression. Proc Natl Acad Sci USA 105:6415–6420
Hebert SS, Horre K, Nicolai L, Bergmans B, Papadopoulou AS, Delacourte A, De Strooper B (2009) MicroRNA regulation of Alzheimer’s amyloid precursor protein expression. Neurobiol Dis 33:422–428
Hutvagner G, McLachlan J, Pasquinelli AE, Balint E, Tuschl T, Zamore PD (2001) A cellular function for the RNA-interference enzyme Dicer in the maturation of the let-7 small temporal RNA. Science 293:834–838
Johnson R, Zuccato C, Belyaev ND, Guest DJ, Cattaneo E, Buckley NJ (2008) A microRNA-based gene dysregulation pathway in Huntington’s disease. Neurobiol Dis 29:438–445
Junn E, Lee KW, Jeong BS, Chan TW, Im JY, Mouradian MM (2009) Repression of alpha-synuclein expression and toxicity by microRNA-7. Proc Natl Acad Sci USA 106:13052–13057
Khan AA, Betel D, Miller ML, Sander C, Leslie CS, Marks DS (2009) Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs. Nat Biotechnol 27:549–555
Kim J, Inoue K, Ishii J, Vanti WB, Voronov SV, Murchison E, Hannon G, Abeliovich A (2007) A MicroRNA feedback circuit in midbrain dopamine neurons. Science 317:1220–1224
Kong W, Zhao JJ, He L, Cheng JQ (2009) Strategies for profiling microRNA expression. J Cell Physiol 218:22–25
Krichevsky AM, King KS, Donahue CP, Khrapko K, Kosik KS (2003) A microRNA array reveals extensive regulation of microRNAs during brain development. RNA 9:1274–1281
Krichevsky AM, Sonntag KC, Isacson O, Kosik KS (2006) Specific microRNAs modulate embryonic stem cell-derived neurogenesis. Stem Cells 24:857–864
Kye MJ, Liu T, Levy SF, Xu NL, Groves BB, Bonneau R, Lao K, Kosik KS (2007) Somatodendritic microRNAs identified by laser capture and multiplex RT-PCR. RNA 13:1224–1234
Lagos-Quintana M, Rauhut R, Lendeckel W, Tuschl T (2001) Identification of novel genes coding for small expressed RNAs. Science 294:853–858
Landgraf P et al (2007) A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129:1401–1414
Lau NC, Lim LP, Weinstein EG, Bartel DP (2001) An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294:858–862
Lee RC, Ambros V (2001) An extensive class of small RNAs in Caenorhabditis elegans. Science 294:862–864
Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–854
Lee Y, Ahn C, Han J, Choi H, Kim J, Yim J, Lee J, Provost P, Radmark O, Kim S, Kim VN (2003) The nuclear RNase III Drosha initiates microRNA processing. Nature 425:415–419
Lee Y, Kim M, Han J, Yeom KH, Lee S, Baek SH, Kim VN (2004) MicroRNA genes are transcribed by RNA polymerase II. EMBO J 23:4051–4060
Lee Y, Samaco RC, Gatchel JR, Thaller C, Orr HT, Zoghbi HY (2008) miR-19, miR-101 and miR-130 co-regulate ATXN1 levels to potentially modulate SCA1 pathogenesis. Nat Neurosci 11:1137–1139
Liu CG, Calin GA, Meloon B, Gamliel N, Sevignani C, Ferracin M, Dumitru CD, Shimizu M, Zupo S, Dono M, Alder H, Bullrich F, Negrini M, Croce CM (2004) An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues. Proc Natl Acad Sci USA 101:9740–9744
Lobsiger CS, Cleveland DW (2007) Glial cells as intrinsic components of non-cell-autonomous neurodegenerative disease. Nat Neurosci 10:1355–1360
Lugli G, Torvik VI, Larson J, Smalheiser NR (2008) Expression of microRNAs and their precursors in synaptic fractions of adult mouse forebrain. J Neurochem 106:650–661
Lukiw WJ, Zhao Y, Cui JG (2008) An NF-kappaB-sensitive micro RNA-146a-mediated inflammatory circuit in Alzheimer disease and in stressed human brain cells. J Biol Chem 283:31315–31322
Maroney PA, Chamnongpol S, Souret F, Nilsen TW (2007) A rapid, quantitative assay for direct detection of microRNAs and other small RNAs using splinted ligation. RNA 13:930–936
Masliah E, Roberts ES, Langford D, Everall I, Crews L, Adame A, Rockenstein E, Fox HS (2004) Patterns of gene dysregulation in the frontal cortex of patients with HIV encephalitis. J Neuroimmunol 157:163–175
Nelson PT, Wilfred BR (2009) In situ hybridization is a necessary experimental complement to microRNA (miRNA) expression profiling in the human brain. Neurosci Lett
Nilsen TW (2007) Mechanisms of microRNA-mediated gene regulation in animal cells. Trends Genet 23:243–249
Nuovo GJ (2008) In situ detection of precursor and mature microRNAs in paraffin embedded, formalin fixed tissues and cell preparations. Methods 44:39–46
Nuovo G, Lee EJ, Lawler S, Godlewski J, Schmittgen T (2009a) In situ detection of mature microRNAs by labeled extension on ultramer templates. Biotechniques 46:115–126
Nuovo GJ, Elton TS, Nana-Sinkam P, Volinia S, Croce CM, Schmittgen TD (2009b) A methodology for the combined in situ analyses of the precursor and mature forms of microRNAs and correlation with their putative targets. Nat Protoc 4:107–115
Packer AN, Xing Y, Harper SQ, Jones L, Davidson BL (2008) The bifunctional microRNA miR-9/miR-9* regulates REST and CoREST and is downregulated in Huntington’s disease. J Neurosci 28:14341–14346
Pang JC, Kwok WK, Chen Z, Ng HK (2009) Oncogenic role of microRNAs in brain tumors. Acta neuropathologica 117:599–611
Pena JT, Sohn-Lee C, Rouhanifard SH, Ludwig J, Hafner M, Mihailovic A, Lim C, Holoch D, Berninger P, Zavolan M, Tuschl T (2009) miRNA in situ hybridization in formaldehyde and EDC-fixed tissues. Nat Methods 6:139–141
Peters L, Meister G (2007) Argonaute proteins: mediators of RNA silencing. Mol Cell 26:611–623
Pillai RS (2005) MicroRNA function: multiple mechanisms for a tiny RNA? RNA 11:1753–1761
Rademakers R et al (2008) Common variation in the miR-659 binding-site of GRN is a major risk factor for TDP43-positive frontotemporal dementia. Hum Mol Genet 17:3631–3642
Reinhart BJ, Ruvkun G (2001) Isoform-specific mutations in the Caenorhabditis elegans heterochronic gene lin-14 affect stage-specific patterning. Genetics 157:199–209
Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, Horvitz HR, Ruvkun G (2000) The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403:901–906
Rigoutsos I (2009) New tricks for animal microRNAS: targeting of amino acid coding regions at conserved and nonconserved sites. Cancer Res 69:3245–3248
Roberts ES, Zandonatti MA, Watry DD, Madden LJ, Henriksen SJ, Taffe MA, Fox HS (2003) Induction of pathogenic sets of genes in macrophages and neurons in NeuroAIDS. Am J Pathol 162:2041–2057
Roberts ES, Huitron-Resendiz S, Taffe MA, Marcondes MC, Flynn CT, Lanigan CM, Hammond JA, Head SR, Henriksen SJ, Fox HS (2006) Host response and dysfunction in the CNS during chronic simian immunodeficiency virus infection. J Neurosci 26:4577–4585
Saba R, Goodman CD, Huzarewich RL, Robertson C, Booth SA (2008) A miRNA signature of prion induced neurodegeneration. PLoS ONE 3:e3652
Savas JN, Makusky A, Ottosen S, Baillat D, Then F, Krainc D, Shiekhattar R, Markey SP, Tanese N (2008) Huntington’s disease protein contributes to RNA-mediated gene silencing through association with Argonaute and P bodies. Proc Natl Acad Sci USA 105:10820–10825
Schratt GM, Tuebing F, Nigh EA, Kane CG, Sabatini ME, Kiebler M, Greenberg ME (2006) A brain-specific microRNA regulates dendritic spine development. Nature 439:283–289
Schuman EM, Dynes JL, Steward O (2006) Synaptic regulation of translation of dendritic mRNAs. J Neurosci 26:7143–7146
Selbach M, Schwanhausser B, Thierfelder N, Fang Z, Khanin R, Rajewsky N (2008) Widespread changes in protein synthesis induced by microRNAs. Nature 455:58–63
Sethi P, Lukiw WJ (2009) Micro-RNA abundance and stability in human brain: specific alterations in Alzheimer’s disease temporal lobe neocortex. Neurosci Lett 459:100–104
Siegel G et al (2009) A functional screen implicates microRNA-138-dependent regulation of the depalmitoylation enzyme APT1 in dendritic spine morphogenesis. Nat Cell Biol 11:705–716
Valoczi A, Hornyik C, Varga N, Burgyan J, Kauppinen S, Havelda Z (2004) Sensitive and specific detection of microRNAs by northern blot analysis using LNA-modified oligonucleotide probes. Nucleic Acids Res 32:e175
Vo N, Klein ME, Varlamova O, Keller DM, Yamamoto T, Goodman RH, Impey S (2005) A cAMP-response element binding protein-induced microRNA regulates neuronal morphogenesis. Proc Natl Acad Sci USA 102:16426–16431
Wang WX, Rajeev BW, Stromberg AJ, Ren N, Tang G, Huang Q, Rigoutsos I, Nelson PT (2008) The expression of microRNA miR-107 decreases early in Alzheimer’s disease and may accelerate disease progression through regulation of beta-site amyloid precursor protein-cleaving enzyme 1. J Neurosci 28:1213–1223
Wienholds E, Koudijs MJ, van Eeden FJ, Cuppen E, Plasterk RH (2003) The microRNA-producing enzyme Dicer1 is essential for zebrafish development. Nat Genet 35:217–218
Acknowledgments
This is manuscript #05 from the UNMC Center for Integrative and Translational Neuroscience. The work of the authors is supported by NIH grants P30 MH062261, R01 MH073490, and P01 DA026146.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yelamanchili, S.V., Fox, H.S. Defining Larger Roles for “Tiny” RNA Molecules: Role of miRNAs in Neurodegeneration Research. J Neuroimmune Pharmacol 5, 63–69 (2010). https://doi.org/10.1007/s11481-009-9172-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11481-009-9172-4