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Genome-wide Analysis of RARβ Transcriptional Targets in Mouse Striatum Links Retinoic Acid Signaling with Huntington’s Disease and Other Neurodegenerative Disorders

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Abstract

Retinoic acid (RA) signaling through retinoic acid receptors (RARs), known for its multiple developmental functions, emerged more recently as an important regulator of adult brain physiology. How RAR-mediated regulation is achieved is poorly known, partly due to the paucity of information on critical target genes in the brain. Also, it is not clear how reduced RA signaling may contribute to pathophysiology of diverse neuropsychiatric disorders. We report the first genome-wide analysis of RAR transcriptional targets in the brain. Using chromatin immunoprecipitation followed by high-throughput sequencing and transcriptomic analysis of RARβ-null mutant mice, we identified genomic targets of RARβ in the striatum. Characterization of RARβ transcriptional targets in the mouse striatum points to mechanisms through which RAR may control brain functions and display neuroprotective activity. Namely, our data indicate with statistical significance (FDR 0.1) a strong contribution of RARβ in controlling neurotransmission, energy metabolism, and transcription, with a particular involvement of G-protein coupled receptor (p = 5.0e−5), cAMP (p = 4.5e−4), and calcium signaling (p = 3.4e−3). Many identified RARβ target genes related to these pathways have been implicated in Alzheimer’s, Parkinson’s, and Huntington’s disease (HD), raising the possibility that compromised RA signaling in the striatum may be a mechanistic link explaining the similar affective and cognitive symptoms in these diseases. The RARβ transcriptional targets were particularly enriched for transcripts affected in HD. Using the R6/2 transgenic mouse model of HD, we show that partial sequestration of RARβ in huntingtin protein aggregates may account for reduced RA signaling reported in HD.

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Acknowledgments

This work was supported by a grant from the Agence Nationale de la Recherche (ANR grant ReSiNEs, ANR-11-BSV2-0003) to P.D. and by an institutional grant (LabEx ANR-10-LABX-0030-INRT) under the frame program Investissements d’Avenir labeled ANR-10-IDEX-0002-02. A.N-C was supported by ReSiNEs and by LabEx INRT funds, and A.P-D. by a PhD fellowship from INRT funds. A.K. was supported by fellowships from the French government (cotutelle), financement relais du Collège Doctoral Européen, and ANR (grant Neuroprotect; ANR-07-PNRA-022-04 to W.K.). We thank C. Thibault-Carpentier, B. Jost, I. Martianov, A. Oravecz, and K. Merienne, for helpful discussions concerning ChIP and transcriptomic analyses; V. Alunni and S. Vicaire from the IGBMC Microarray and High-Throughput Sequencing Platform for processing Affymetrix chips and Illumina libraries, respectively. The Platform is supported by the France Génomique National infrastructure, funded as part of the Investissements d’Avenir program ANR-10-INBS-09. We thank also Y. Trottier and C. Weber for advice on R6/2 line maintenance, P. Kessler from the IGBMC Imaging Platform for assistance in image acquisition and analyses, and V. Fraulob, B. Schuhbaur and J. Sikora for technical assistance.

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  1. Agnieszka Krzyżosiak

    Present address: MRC Laboratory of Molecular Biology, Francis Crick Avenue, CB2 0QH, Cambridge, UK

Authors and Affiliations

  1. Institut de Génétique et de Biologie Moléculaire et Cellulaire, 1 rue Laurent Fries, 67404, Illkirch Cedex, France

    Anna Niewiadomska-Cimicka, Agnieszka Krzyżosiak, Tao Ye, Anna Podleśny-Drabiniok, Doulaye Dembélé, Pascal Dollé & Wojciech Krężel

  2. Centre National de la Recherche Scientifique, UMR 7104, Illkirch, France

    Anna Niewiadomska-Cimicka, Agnieszka Krzyżosiak, Tao Ye, Anna Podleśny-Drabiniok, Doulaye Dembélé, Pascal Dollé & Wojciech Krężel

  3. Institut National de la Santé et de la Recherche Médicale, U 964, Illkirch, France

    Anna Niewiadomska-Cimicka, Agnieszka Krzyżosiak, Tao Ye, Anna Podleśny-Drabiniok, Doulaye Dembélé, Pascal Dollé & Wojciech Krężel

  4. Université de Strasbourg, Illkirch, France

    Anna Niewiadomska-Cimicka, Agnieszka Krzyżosiak, Tao Ye, Anna Podleśny-Drabiniok, Doulaye Dembélé, Pascal Dollé & Wojciech Krężel

  5. Fédération de Médecine Translationnelle de Strasbourg (FMTS), Strasbourg, France

    Anna Niewiadomska-Cimicka, Agnieszka Krzyżosiak, Anna Podleśny-Drabiniok, Pascal Dollé & Wojciech Krężel

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  1. Anna Niewiadomska-Cimicka
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Correspondence to Wojciech Krężel.

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ESM 1

Table S1. Genes with RARβ binding sites, which have been reported to be affected in their expression in Huntington’s disease (HD), Alzheimer’s disease (AD), Parkinson’s disease (PD), or schizophrenia (IPA and David analysis). (XLSX 29 kb)

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Table S2. Transcriptional regulators bearing RARβ binding site(s) and which expression was reported to be impaired in HD. (DOCX 16 kb)

ESM 3

Table S3. Genes with RARβ binding sites, which expression was reported to be affected in transcriptomic analyses of human post-mortem HD caudate nucleus samples (Hodges et al., [20]). (XLSX 34 kb)

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Table S4. Functional annotations of transcriptional changes in the NAcSh of RARβ−/− mice. (XLSX 13 kb)

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Table S5. Genes associated with G-protein signaling and altered in their expression in the NAcSh of RARβ−/− mice (IPA analysis). (DOCX 15 kb)

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Table S6. Genes which expression was reported to be affected in transcriptomic analyses of human post-mortem HD caudate nucleus samples (Hodges et al. [20]) as well as in NAcSh of RARβ−/− mice (this study). The following criteria were applied for both transcriptomes: 0.80 ≥ fold change (FC) ≥1.20, p value ≤0.05. (XLSX 17 kb)

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Table S7. Genes bearing RARβ binding sites and which expression was significantly altered in transcriptomic analyses of the RARβ−/− NAcSh. The following criteria were applied: 0.80 ≥ fold change (FC) ≥1.20, p value ≤0.05. (DOCX 29 kb)

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Fig. S1. Validation of specificity of the anti-RARβ antibody. RARβ (red) can be visualized by immunofluorescence detection in coronal sections of WT (A), but not RARβ−/− (B) CPu. Nuclei are counterstained with DAPI (blue). Scale bar, 10 μm. (JPG 90 kb)

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Fig. S2. Analysis of RARβ expression in the striatum of R6/2 mice embryos at stage E16.5. Immunofluorescent detection of RARβ (red) and HTT (green) in coronal sections of the CPu in E16.5 WT (upper panels) and R6/2 transgenic mice (lower panels). DAPI stained nuclei are shown in blue. Scale bar, 10 μm. (JPG 498 kb)

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Fig. S3. The statistical significance of cluster 1, cluster 2, and cluster 3-bound gene groups from comparative clustering of RARβ and H3K4me3 read densities (see Fig. 4d). Bootstrap statistical analyses (see Materials and Methods) were carried out with a random selection of 6273 genes (IDs) out of a total pool of 26,460 ENSEMBL IDs. Histograms represent the average numbers of observed IDs in the three random sets. The average numbers and SDs are: cluster 1, 245 ± 16 (A); cluster 2, 610 ± 21 (B); and cluster 3, 483 ± 21 (C). These averages are significantly far from the experimentally determined numbers (p value < 1.0e−32) shown with an arrow in bold. The z-cores are 51.26 (cluster 1), 93.01 (cluster 2), and 104.01 (cluster 3). (JPG 194 kb)

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Table S8. List of primers used for qPCR analyses. (DOCX 17 kb)

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Niewiadomska-Cimicka, A., Krzyżosiak, A., Ye, T. et al. Genome-wide Analysis of RARβ Transcriptional Targets in Mouse Striatum Links Retinoic Acid Signaling with Huntington’s Disease and Other Neurodegenerative Disorders. Mol Neurobiol 54, 3859–3878 (2017). https://doi.org/10.1007/s12035-016-0010-4

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  • DOI: https://doi.org/10.1007/s12035-016-0010-4

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