Open Access

In silico analysis of regulatory networks underlines the role of miR-10b-5p and its target BDNF in huntington’s disease

Translational Neurodegeneration20143:17

https://doi.org/10.1186/2047-9158-3-17

Received: 29 June 2014

Accepted: 13 August 2014

Published: 18 August 2014

Abstract

Non-coding RNAs (ncRNAs) play various roles during central nervous system development. MicroRNAs (miRNAs) are a class of ncRNAs that exert their function together with argonaute proteins by post-transcriptional gene silencing of messenger RNAs (mRNAs). Several studies provide evidence for alterations in miRNA expression in patients with neurodegenerative diseases. Among these is huntington‘s disease (HD), a dominantly inherited fatal disorder characterized by deregulation of neuronal-specific mRNAs as well as miRNAs. Recently, next-generation sequencing (NGS) miRNA profiles from human HD and neurologically normal control brain tissues were reported. Five consistently upregulated miRNAs affect the expression of genes involved in neuronal differentiation, neurite outgrowth, cell death and survival. We re-analyzed the NGS data publicly available in array express and detected nineteen additional differentially expressed miRNAs. Subsequently, we connected these miRNAs to genes implicated in HD development and network analysis pointed to miRNA-mediated downregulation of twenty-two genes with roles in the pathogenesis as well as treatment of the disease. In silico prediction and reporter systems prove that levels of BDNF, a central node in the miRNA-mRNA regulatory network, can be post-transcriptionally controlled by upregulated miR-10b-5p and miR-30a-5p. Reduced BDNF expression is associated with neuronal dysfunction and death in HD. Moreover, the 3’UTR of CREB1 harbors a predicted binding site for these two miRNAs. CREB1 is similarly downregulated in HD and overexpression decreased susceptibility to 3-nitropropionic-induced toxicity in a cell model. In contradiction to these observations, it is presumed that miR-10b-5p upregulation in HD exerts a neuroprotective role in response to the mutation in the huntingtin gene. Therefore, the function of miR-10b-5p and especially its effect on BDNF expression in HD requires further academic research.

Keywords

Huntington miRNA Sequencing Post-transcriptional regulation

Introduction

Huntington’s disease (HD) is a fatal hereditary neurodegenerative disorder characterized by unwanted choreatic movements, behavioral manifestations and dementia [1]. In the caucasian population HD appears with an incidence of one per 10,000-20,000 per year in middle age (30-50 years) [2]. The disease is caused by a genetic disorder. An elongation of the CAG trinucleotide repeat (36 repeats or more) is observed within the coding region of the huntingtin (HTT) gene [3]. This mutation yields a protein with deleterious functions for brain cells and even impairs the ability of normal HTT to exert fundamental molecular activities in the neurons [4]. As a consequence, neurons predominantly degenerate in the brains of affected patients [4]. While the altered biological processes finally leading to neurodegeneration remain poorly understood, changes in messenger RNA (mRNA) expression point to transcriptional dysregulation as a central mechanism [5]. Beside deregulation of mRNAs, also differential expression of microRNAs (miRNAs) has been linked to HD [6]. MiRNAs are a class of small non-coding RNAs (sncRNAs) that can repress gene expression through translational repression or mRNA deadenylation and decay by base pairing to partially complementary sites [7]. Recent research has examined the role of miRNAs in HD using next generation sequencing (NGS) and identified between five and 85 deregulated miRNAs [8, 9]. Hoss and colleagues [9] related five upregulated miRNAs (miR-10b-5p, miR-196a-5p, miR-196b-5p, miR-615-3p and miR-1247-5p) located in the HOX gene cluster to HD pathogenesis. Nevertheless, target and differential expression analysis with strict parameters revealed only one validated, downregulated target gene (KRT5) of these miRNAs. Therefore, their function in HD pathogenesis mostly remains unclear.

In order to shed light on the consequences of miRNA deregulation in HD we used omiRas [10] to re-analyze the dataset of Hoss and co-workers consisting of small RNA-Sequencing (sRNA-Seq) libraries derived from twelve HD and nine unaffected control brain tissue samples in FASTQ format. In extension to the five miRNAs identified by Hoss and colleagues we detected nineteen additional miRNAs as differentially expressed. Furthermore, we assigned functions to differentially expressed miRNAs via the interaction tool of omiRas. Analysis revealed BDNF as a validated target of two upregulated miRNAs (miR-10b and miR-30a), CREB1 is predicted to be post-transcriptionally controled by the same two miRNAs. The potential miRNA-mediated downregulation of several major player genes in HD pathogenesis underlines the feasibility of miRNAs as therapeutic targets in HD.

Materials and methods

Dataset collection and preprocessing

A publicly available sRNA-Seq expression dataset of twelve HD and nine control brain samples from the prefrontal cortex was downloaded from Array Express (E-MTAB-2206) in FASTQ format. The 3’ sequencing adapter (TCGTATGCCGTCTTCTGCTTGAAA) was removed from the reads with cutadapt [11]. Subsequently, low quality stretches below a SANGER quality score of 20 were additionally trimmed from each end of the reads (-q 20). Only reads with a minimum length of fifteen base pairs after clipping were used for further analysis(-m 15). A list of differentially regulated genes identified in Microarray data of sixteen HD patients’ prefrontal cortex and fifteen controls cases published by Hodges and co-workers [5] was retrieved in XLS format and intersected with a list of genes with implication in HD, as defined by the HD crossroads database [12].

MiRNA quantification, differential expression and target analysis

Samples were uploaded to omiRas and analyzed as described previously [10]. In contrast to Hoss and colleagues we tested for differential expression in “gene-est-only” mode of DESeq [13], which is recommended if more than seven replicates per condition are available. MRNA targets with involvement in HD pathogenesis (see dataset collection) of differentially expressed miRNAs were identified with the “interactive network tool” of omiRas. An interaction between a miRNA and a coding-gene is assumed to be valid if the following two criteria apply: (a) Three or more of seven miRNA-mRNA interaction databases support the interaction. (b) The expression of the miRNA/mRNA pair is inverse. The miRNA is significantly downregulated and the mRNA is upregulated or vice versa. Interactions between gene products of deregulated genes were detected via STRING database.

Results

The results for the comparison of twelve HD and nine control brain samples is available from omiRas (http://tools.genxpro.net/omiras/10eea4eb58d1/results/). Our analysis confirms the upregulation of miR-10b-5p, miR-196a-5p, miR-196b-5p, miR-615-3p and miR-1247-5p in HD. In addition, we detect nineteen other differentially expressed miRNAs, of which four are down- and fifteen upregulated. The expression values in both conditions as well as the corrected p-value for each miRNA are given in Table 1. The lower number of differentially expressed miRNAs in comparison to previous studies [8, 14] can be explained by the elimination of false positive candidates due to a reliable estimation of biological variance. The interaction network in Figure 1 comprises 65 protein products of downregulated genes with 121 protein-protein interactions. Hubs in the network represented by nodes with the most protein-protein interactions are Calmodulin 1 (CALM1) with twelve interactions and brain-derived neurotrophic factor (BDNF) with nine interactions. The downregulation of mRNAs coding for the proteins in the network is potentially caused by eight miRNAs with predicted binding sites in their 3’UTR. Approximately one third (22) of all mRNAs are predicted targets of miRNAs, four genes can be post-transcriptionally controlled by more than one miRNA (BDNF, CALM1, CNR1, CREB1). The hub genes BDNF and CALM1 harbor a binding site for miR-10b-5p, 196a-5p, 196b-5p and 30a-5p in their 3’UTR. CREB1 and BDNF are predicted targets of miR-10b and miR-30a, whereas the regulation of BDNF has recently been experimentally verified in the prefrontal cortex [15, 16].
Table 1

Deregulated miRNAs in HD

miRNA

NEV Control

NEV HD

foldChange

FDR

Other studies

miR-196a-5p

0.00

19.01

Inf

1.4E-010

[9, 14]

miR-891a

48.39

101.39

2.10

0.00001

-

miR-10b-5p

1011.52

30689.38

30.34

0.00003

[9]

miR-4645-3p

3.66

9.44

2.58

0.0001

-

miR-1247-5p

135.61

309.04

2.28

0.0004

[9]

miR-10b-3p

0.00

5.28

Inf

0.0026

-

miR-363-3p

2239.63

3274.71

1.46

0.0033

[8]

miR-30a-3p

5223.90

6943.31

1.33

0.0048

[8]

miR-125b-2-3p

17177.77

20740.93

1.21

0.0052

-

miR-615-3p

0.00

5.45

Inf

0.0065

[9]

miR-196b-5p

1.09

10.17

9.33

0.0134

[9]

miR-127-3p

175251.70

224611.39

1.28

0.0194

-

miR-208b

75.76

112.90

1.49

0.0217

-

miR-302a-5p

2.67

6.93

2.60

0.0451

-

miR-2682-5p

212.76

299.86

1.41

0.0451

-

miR-30a-5p

171969.53

228298.92

1.33

0.0451

[8]

miR-770-5p

333.36

445.55

1.34

0.0451

-

miR-130a-3p

4740.57

6385.28

1.35

0.0451

-

miR-92b-5p

40.62

57.17

1.41

0.0451

-

miR-449a

20.31

32.65

1.61

0.0451

-

miR-3139

8.59

2.27

0.26

0.0031

-

miR-4449

10.95

2.75

0.25

0.0163

-

miR-4521

335.51

168.04

0.50

0.0194

-

miR-138-2-3p

94.11

74.60

0.79

0.0194

-

MiRNAs upregulated in HD brains are indicated by a fold-change > 1, downregulated miRNAs by a fold-change < 1. NEV corresponds to the normalized expression value and FDR is the corrected p-value. Other studies indicates if any study different from this has likewise reported the miRNA deregulation in HD.

Figure 1

MiRNA-mRNA interaction network in HD. Downregulated genes/gene products with implication in HD pathogenesis are represented by red circles. Interactions between proteins are visualized with blue lines, predicted post-transcriptional regulation of mRNAs by miRNAs is indicated by a dotted grey line.

Discussion

We extend the report of Hoss and co-workers based on NGS miRNA expression profiles of twelve HD and nine healthy control brain samples. Re-analysis of the dataset reveals 24 differentially expressed miRNAs in HD, 20 of these up- and four downregulated. Regulatory network analysis comprising genes involved in HD pathogenesis with decreased expression underlines the role of the most significantly upregulated miRNA, miR-10b-5p, that targets BDNF and CREB1.

BDNF is a secreted neurotrophic factor, which represent a class of molecules that contribute essentially to the survival of the peripheral and central nervous system, and reduced level of BDNF mRNA as well as protein have been found in HD cerebral cortex and striatum [17]. BDNF is required in striatal neurons for survival and activity. The largest proportion of striatal BDNF is initially produced in the frontal cortex and subsequently transported to the striatum [18]. YAC 128 mice that were transplanted with BDNF overexpressing MSCs in the striatum show a significantly reduced amount of neuronal loss [19]. Downregulation of BDNF has been directly associated with the mutation of wild-type HTT[17]. Our analysis extends the regulatory mechanism leading to BDNF downregulation in HD to miR-10b-5p and 30a-5p which are significantly upregulated in HD and have been shown to target the 3’UTR of the BDNF transcript [15, 16]. Upregulation of BDNF levels in the striatum/cortex are a potential therapeutic strategy in HD treatment [18] and our analysis points to an inhibition of miRNAs by antagomiRs to achieve this goal. Mir-10b antagomirs have inter alias been used for therapeutic silencing of miR-10b to inhibit metastasis in a mouse mammary tumor model [20]. In contradiction to these observations, miR-10b-5p expression enhanced the survival of PC12 Q73 cells and its upregulation in HD may be a neuroprotective response to the HTT mutation [9]. Therefore, the role of miR-10b-5p and especially its effect on BDNF expression in HD requires further academic research.

CREB1 encodes a transcription factor that is a member of the leucine zipper family of DNA binding proteins. CREB1 induces transcription of genes in response to hormonal stimulation of the cAMP pathway. Members of the CREB family are essential for the maintenance of cell viability in various tissues and stages of development [21]. Reduced CREB1 expression has been reported in HD and mutant Htt represses CREB1 expression by a direct interaction with the CREB-binding protein [22]. Lack of CREB1 expression during development of the central nervous system leads to substantial apoptosis of postmitotic neurons [21]. The CREB signaling pathway has been suggested for pharmacological intervention in neurodegenerative disorders like HD [21]. The 3’UTR of CREB1 harbors predicted binding sites of miR-10b-5p, 30a-5p and 196a-5p, which makes antagomiRs a potential approach for intervention in CREB signalling. Nevertheless, these interactions lack experimental validation and form a basis for further research.

Taken together our analysis underlines the role of miRNAs in HD pathogenesis. The regulatory network of deregulated genes and miRNAs may now spur further research in the field of HD. We provide a set of miRNA-mRNA interactions that currently lack experimental validation and point to miRNAs that are potential targets for treatment with antagomiRs. The validity of the predicted interactions between downregulated genes and upregulated miRNAs is underlined by the recent validation of four interactions in the network (miR-10b-5p-BDNF, miR-30a-5p-BDNF, miR-30a-5p-AP2A1, miR-30a-5p-PPP3CA[23]).

Declarations

Acknowledgements

This work was supported by the Bundesministerium für Bildung und Forschung (BMBF) (Grant nos. FKZ0316043 and FKZ031A104A). The author thanks Professor Günter Kahl and Professor Ina Koch as well as Dr. Börn Rotter and Dr. Peter Winter for their advice and assistance.

Authors’ Affiliations

(1)
Molecular BioSciences, University of Frankfurt

References

  1. Pringsheim T, Wiltshire K, Day L, Dykeman J, Steeves T, Jette N: The incidence and prevalence of Huntington’s disease: A systematic review and meta-analysis. Mov Disord 2012, 27(9):1083-1091.View ArticlePubMedGoogle Scholar
  2. Roos RA: Hu ntingtonLs disease: a clinical review. Orphanet J Rare Dis 2010, 5: 40.PubMed CentralView ArticlePubMedGoogle Scholar
  3. MacDonald ME, Ambrose CM, Duyao MP, Myers RH, Lin C, Srinidhi L, Barnes G, Taylor SA, James M, Groot N, MacFarlane H, Jenkins B, Anderson MA, Wexler NS, Gusella JF, Bates GP, Baxendale S, Hummerich H, Kirby S, North M, Youngman S, Mott R, Zehetner G, Sedlacek Z, Poustka A, Frischauf A-M, Lehrach H: A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington’s disease chromosomes. Cell 1993, 72(6):971-983.View ArticleGoogle Scholar
  4. Graham RK, Deng Y, Slow EJ, Haigh B, Bissada N, Lu G, Pearson J, Shehadeh J, Bertram L, Murphy Z, Warby SC, Doty CN, Roy S, Wellington CL, Leavitt BR, Raymond LA, Nicholson DW, Hayden MR: Cleavage at the caspase-6 site is required for neuronal dysfunction and degeneration due to mutant huntingtin. Cell 2006, 125(6):1179-1191.View ArticlePubMedGoogle Scholar
  5. Hodges A, Strand AD, Aragaki AK, Kuhn A, Sengstag T, Hughes G, Elliston LA, Hartog C, Goldstein DR, Thu D, Hollingsworth ZR, Collin F, Synek B, Holmans PA, Young AB, Wexler NS, Delorenzi M, Kooperberg C, Augood SJ, Faull RLM, Olson JM, Jones L, Luthi-Carter R: Regional and cellular gene expression changes in human Huntington’s disease brain. Hum Mol Genet 2006, 15(6):965-977.View ArticlePubMedGoogle Scholar
  6. Junn E, Mouradian MM: MicroRNAs in neurodegenerative diseases and their therapeutic potential. Pharmacol Ther 2012, 133(2):142-150.PubMed CentralView ArticlePubMedGoogle Scholar
  7. Wu L, Fan J, Belasco JG: MicroRNAs direct rapid deadenylation of mRNA. Proc Natl Acad Sci U S A 2006, 103(11):4034-4039.PubMed CentralView ArticlePubMedGoogle Scholar
  8. Martí E, Pantano L, Bañez-Coronel M, Llorens F, Miñones-Moyano E, Porta S, Sumoy L, Ferrer I, Estivill X: A myriad of miRNA variants in control and Huntington’s disease brain regions detected by massively parallel sequencing. Nucleic Acids Res 2010, 38(20):7219-7235.PubMed CentralView ArticlePubMedGoogle Scholar
  9. Hoss AG, Kartha VK, Dong X, Latourelle JC, Dumitriu A, Hadzi TC, MacDonald ME, Gusella JF, Akbarian S, Chen J-F, Weng Z, Myers RH: MicroRNAs located in the Hox gene clusters are implicated in huntington’s disease pathogenesis. PLoS Genet 2014, 10(2):e1004188.PubMed CentralView ArticlePubMedGoogle Scholar
  10. Müller S, Rycak L, Winter P, Kahl G, Koch I, Rotter B: omiRas: a Web server for differential expression analysis of miRNAs derived from small RNA-Seq data. Bioinformatics 2013, 29(20):2651-2652.View ArticlePubMedGoogle Scholar
  11. Martin M: Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 2011, 17: 10.View ArticleGoogle Scholar
  12. Kalathur RKR, Hernández-Prieto MA, Futschik ME: Huntington’s disease and its therapeutic target genes: a global functional profile based on the HD research crossroads database. BMC Neurol 2012, 12: 47.PubMed CentralView ArticlePubMedGoogle Scholar
  13. Anders S, Huber W: Differential expression analysis for sequence count data. Genome Biol 2010, 11(10):R106.PubMed CentralView ArticlePubMedGoogle Scholar
  14. Packer AN, Xing Y, Harper SQ, Jones L, Davidson BL: The bifunctional microRNA miR-9/miR-9* regulates REST and CoREST and is downregulated in Huntington’s disease. J Neurosci 2008, 28(53):14341-14346.PubMed CentralView ArticlePubMedGoogle Scholar
  15. Varendi K, Kumar A, Härma MA, Andressoo JO: miR-1, miR-10b, miR-155, and miR-191 are novel regulators of BDNF. Cell Mol Life Sci 2014, 2014: 1-14.Google Scholar
  16. Mellios N, Huang HS, Grigorenko A, Rogaev E, Akbarian S: A set of differentially expressed miRNAs, including miR-30a-5p, act as post-transcriptional inhibitors of BDNF in prefrontal cortex. Hum Mol Genet 2008, 17(19):3030-3042.PubMed CentralView ArticlePubMedGoogle Scholar
  17. Zuccato C, Ciammola A, Rigamonti D, Leavitt BR, Goffredo D, Conti L, MacDonald ME, Friedlander RM, Silani V, Hayden MR, Timmusk T, Sipione S, Cattaneo E: Loss of huntingtin-mediated BDNF gene transcription in Huntington’s disease. Science 2001, 293(5529):493-498.View ArticlePubMedGoogle Scholar
  18. Xie Y, Hayden MR, Xu B: BDNF overexpression in the forebrain rescues Huntington’s disease phenotypes in YAC128 mice. J Neurosci 2010, 30(44):14708-14718.PubMed CentralView ArticlePubMedGoogle Scholar
  19. Dey ND, Bombard MC, Roland BP, Davidson S, Lu M, Rossignol J, Sandstrom MI, Skeel RL, Lescaudron L, Dunbar GL: Genetically engineered mesenchymal stem cells reduce behavioral deficits in the YAC 128 mouse model of Huntington’s disease. Behav Brain Res 2010, 214(2):193-200.View ArticlePubMedGoogle Scholar
  20. Ma L, Reinhardt F, Pan E, Soutschek J, Bhat B, Marcusson EG, Teruya-Feldstein J, Bell GW, Weinberg RA: Therapeutic silencing of miR-10b inhibits metastasis in a mouse mammary tumor model. Nat Biotechnol 2010, 28(4):341-347.PubMed CentralView ArticlePubMedGoogle Scholar
  21. Mantamadiotis T, Lemberger T, Bleckmann SC, Kern H, Kretz O, Villalba AM, Tronche F, Kellendonk C, Gau D, Kapfhammer J, Otto C, Schmid W, Schütz G: Disruption of CREB function in brain leads to neurodegeneration. Nat Genet 2002, 31: 47-54.View ArticlePubMedGoogle Scholar
  22. Chaturvedi RK, Hennessey T, Johri A, Tiwari SK, Mishra D, Agarwal S, Kim YS, Beal MF: Transducer of regulated CREB-binding proteins (TORCs) transcription and function is impaired in Huntington’s disease. Hum Mol Genet 2012, 21(15):3474-3488.PubMed CentralView ArticlePubMedGoogle Scholar
  23. Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G, Maragkakis M, Reczko M, Gerangelos S, Koziris N, Dalamagas T, Hatzigeorgiou AG: TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 2012, 40(D1):D222—D229.PubMed CentralView ArticlePubMedGoogle Scholar

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© Müller; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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