Skip to main content
Log in

Evidence of TAF1 dysfunction in peripheral models of X-linked dystonia-parkinsonism

Cellular and Molecular Life Sciences Aims and scope Submit manuscript

Cite this article

Abstract

The molecular dysfunction in X-linked dystonia-parkinsonism is not completely understood. Thus far, only noncoding alterations have been found in genetic analyses, located in or nearby the TATA-box binding protein-associated factor 1 (TAF1) gene. Given that this gene is ubiquitously expressed and is a critical component of the cellular transcription machinery, we sought to study differential gene expression in peripheral models by performing microarray-based expression profiling in blood and fibroblasts, and comparing gene expression in affected individuals vs. ethnically matched controls. Validation was performed via quantitative polymerase chain reaction in discovery and independent replication sets. We observed consistent downregulation of common TAF1 transcripts in samples from affected individuals in gene-level and high-throughput experiments. This signal was accompanied by a downstream effect in the microarray, reflected by the dysregulation of 307 genes in the disease group. Gene Ontology and network analyses revealed enrichment of genes involved in RNA polymerase II-dependent transcription, a pathway relevant to TAF1 function. Thus, the results converge on TAF1 dysfunction in peripheral models of X-linked dystonia-parkinsonism, and provide evidence of altered expression of a canonical gene in this disease. Furthermore, our study illustrates a link between the previously described genetic alterations and TAF1 dysfunction at the transcriptome level.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

ACRC :

Acid repeat-containing gene

ATP6V0E2 :

ATPase, H+ transporting, lysosomal, 9-kD, V0 subunit E2

BHLHE40 :

Basic helix-loop-helix family, member E40

CXCR3 :

Chemokine, CXC motif, receptor 3

DBN1 :

Drebrin E

DUSP1 :

Dual-specificity phosphatase 1

EFNB1 :

Ephrin B1

ETV3 :

ETS variant gene 3

GRIN2D :

Glutamate receptor, ionotropic, N-methyl-d-aspartate, subunit 2D

GZF1 :

GDNF-inducible zinc finger protein 1

KCND2 :

Potassium voltage-gated channel, Shal-related subfamily, member 2

MRPS6 :

Mitochondrial ribosomal protein S6

OGT :

O-linked N-acetylglucosamine transferase

PRDM1 :

PR-domain containing protein 1

SLC5A3 :

Solute carrier family 5 (inositol transporter), member 3

SRF :

Serum response factor

SYTL2 :

Synaptotagmin-like 2

TAF1 :

TATA-box binding protein-associated factor 1

TBP :

TATA-box binding protein

ZADH2 :

Zinc alcohol dehydrogenase

ZC3H12A :

Zinc finger CCCH domain-containing protein 12A

DEG:

Differentially expressed gene

DSC:

Disease-specific single-nucleotide change

GO:

Gene ontology

HD:

Huntington’s disease

MTS:

Multiple transcript system

SAM:

Significance analysis of microarrays

XDP:

X-linked dystonia-parkinsonism

References

  1. Lee LV, Rivera C, Teleg R et al (2011) The unique phenomenology of X-linked dystonia-parkinsonism (XDP, DYT3, “Lubag”). Int J Neurosci 121(Suppl):3–11. doi:10.3109/00207454.2010.526727

    Article  PubMed  Google Scholar 

  2. Domingo A, Westenberger A, Lee LV et al (2015) New insights into the genetics of X-linked dystonia-parkinsonism (XDP, DYT3). Eur J Hum Genet 23:1334–1340. doi:10.1038/ejhg.2014.292

    Article  CAS  PubMed  Google Scholar 

  3. Rosales RL (2010) X-linked dystonia parkinsonism: clinical phenotype, genetics and therapeutics. J Mov Disord 3:32–38. doi:10.14802/jmd.10009

    Article  PubMed  PubMed Central  Google Scholar 

  4. Goto S, Lee LV, Munoz EL et al (2005) Functional anatomy of the basal ganglia in X-linked recessive dystonia-parkinsonism. Ann Neurol 58:7–17. doi:10.1002/ana.20513

    Article  PubMed  Google Scholar 

  5. Pasco PMD, Ison CV, Munoz EL et al (2011) Understanding XDP through imaging, pathology, and genetics. Int J Neurosci 121:12–17. doi:10.3109/00207454.2010.526729

    Article  CAS  PubMed  Google Scholar 

  6. Nolte D, Niemann S, Müller U (2003) Specific sequence changes in multiple transcript system DYT3 are associated with X-linked dystonia parkinsonism. Proc Natl Acad Sci USA 100:10347–10352. doi:10.1073/pnas.1831949100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Makino S, Kaji R, Ando S et al (2007) Reduced neuron-specific expression of the TAF1 gene is associated with X-linked dystonia-parkinsonism. Am J Hum Genet 80:393–406. doi:10.1086/512129

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Herzfeld T, Nolte D, Grznarova M et al (2013) X-linked dystonia parkinsonism syndrome (XDP, lubag): disease-specific sequence change DSC3 in TAF1/DYT3 affects genes in vesicular transport and dopamine metabolism. Hum Mol Genet 22:941–951. doi:10.1093/hmg/dds499

    Article  CAS  PubMed  Google Scholar 

  9. Thomas MC, Chiang C-M (2006) The general transcription machinery and general cofactors. Crit Rev Biochem Mol Biol 41:105–178. doi:10.1080/10409230600648736

    Article  CAS  PubMed  Google Scholar 

  10. Herzfeld T, Nolte D, Müller U (2007) Structural and functional analysis of the human TAF1/DYT3 multiple transcript system. Mamm Genome 18:787–795. doi:10.1007/s00335-007-9063-z

    Article  CAS  PubMed  Google Scholar 

  11. Müller U, Herzfeld T, Nolte D et al (2007) Letters to the editor. Am J Hum Genet 81:414–421. doi:10.1086/521416

    Article  Google Scholar 

  12. Borovecki F, Lovrecic L, Zhou J et al (2005) Genome-wide expression profiling of human blood reveals biomarkers for Huntington’s disease. Proc Natl Acad Sci USA 102:11023–11028. doi:10.1073/pnas.0504921102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Tang Y, Schapiro MB, Franz DN et al (2004) Blood expression profiles for tuberous sclerosis complex 2, neurofibromatosis type 1, and Down’s syndrome. Ann Neurol 56:808–814. doi:10.1002/ana.20291

    Article  CAS  PubMed  Google Scholar 

  14. Strand AD, Aragaki AK, Shaw D et al (2005) Gene expression in Huntington’s disease skeletal muscle: a potential biomarker. Hum Mol Genet 14:1863–1876. doi:10.1093/hmg/ddi192

    Article  CAS  PubMed  Google Scholar 

  15. Leek JT, Scharpf RB, Bravo HC et al (2010) Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet 11:733–739

    Article  CAS  PubMed  Google Scholar 

  16. Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 98:5116–5121. doi:10.1073/pnas.091062498

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25:402–408. doi:10.1006/meth.2001.1262

    Article  CAS  PubMed  Google Scholar 

  18. Marullo M, Zuccato C, Mariotti C et al (2010) Expressed Alu repeats as a novel, reliable tool for normalization of real-time quantitative RT-PCR data. Genome Biol 11:R9. doi:10.1186/gb-2010-11-1-r9

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hruz T, Wyss M, Docquier M et al (2011) RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization. BMC Genom 12:156. doi:10.1186/1471-2164-12-156

    Article  CAS  Google Scholar 

  20. Stamova BS, Apperson M, Walker WL et al (2009) Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood. BMC Med Genom 2:49. doi:10.1186/1755-8794-2-49

    Article  Google Scholar 

  21. Shamir R, Maron-Katz A, Tanay A et al (2005) EXPANDER–an integrative program suite for microarray data analysis. BMC Bioinform 6:232. doi:10.1186/1471-2105-6-232

    Article  Google Scholar 

  22. Ulitsky I, Maron-Katz A, Shavit S et al (2010) Expander: from expression microarrays to networks and functions. Nat Protoc 5:303–322

    Article  CAS  PubMed  Google Scholar 

  23. Ulitsky I, Shamir R (2007) Identification of functional modules using network topology and high-throughput data. BMC Syst Biol 1:8. doi:10.1186/1752-0509-1-8

    Article  PubMed  PubMed Central  Google Scholar 

  24. Ulitsky I, Laurent LC, Shamir R (2010) Towards computational prediction of microRNA function and activity. Nucleic Acids Res 38:e160-e160. doi:10.1093/nar/gkq570

    Article  Google Scholar 

  25. Elkon R, Linhart C, Sharan R et al (2003) Genome-wide in silico identification of transcriptional regulators controlling the cell cycle in human cells. Genome Res 13:773–780. doi:10.1101/gr.947203.5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Subramanian A, Subramanian A, Tamayo P et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102:15545–15550. doi:10.1073/pnas.0506580102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Warde-Farley D, Donaldson SL, Comes O et al (2010) The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res 38:214–220. doi:10.1093/nar/gkq537

    Article  Google Scholar 

  28. Kim TH, Barrera LO, Zheng M et al (2005) A high-resolution map of active promoters in the human genome. Nature 436:876–880. doi:10.1038/nature03877

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Dalman MR, Deeter A, Nimishakavi G, Duan Z-H (2012) Fold change and p value cutoffs significantly alter microarray interpretations. BMC Bioinformatics 13:S11. doi:10.1186/1471-2105-13-S2-S11

    Article  PubMed  PubMed Central  Google Scholar 

  30. Allison DB, Cui X, Page GP, Sabripour M (2006) Microarray data analysis: from disarray to consolidation and consensus. Nat Rev Genet 7:55–65. doi:10.1038/nrg1869

    Article  CAS  PubMed  Google Scholar 

  31. White MP, Rufaihah AJ, Liu L et al (2013) Limited gene expression variation in human embryonic stem cell and induced pluripotent stem cell-derived endothelial cells. Stem Cells 31:92–103. doi:10.1002/stem.1267

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Bithell A, Johnson R, Buckley NJ (2009) Transcriptional dysregulation of coding and non-coding genes in cellular models of Huntington’s disease. Biochem Soc Trans 37:1270–1275. doi:10.1042/BST0371270

    Article  CAS  PubMed  Google Scholar 

  33. Bhattacharya S, Lou X, Hwang P et al (2014) Structural and functional insight into TAF1-TAF7, a subcomplex of transcription factor II D. Proc Natl Acad Sci USA 111:9103–9108. doi:10.1073/pnas.1408293111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Dunah AW, Jeong H, Griffin A et al (2002) Sp1 and TAFII130 transcriptional activity disrupted in early Huntington’s disease. Science 296:2238–2243. doi:10.1126/science.1072613

    Article  CAS  PubMed  Google Scholar 

  35. Friedman MJ, Shah AG, Fang Z-H et al (2007) Polyglutamine domain modulates the TBP-TFIIB interaction: implications for its normal function and neurodegeneration. Nat Neurosci 10:1519–1528. doi:10.1038/nn2011

    Article  CAS  PubMed  Google Scholar 

  36. Shah AG, Friedman MJ, Huang S et al (2009) Transcriptional dysregulation of TrkA associates with neurodegeneration in spinocerebellar ataxia type 17. Hum Mol Genet 18:4141–4152. doi:10.1093/hmg/ddp363

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kuroda TS, Fukuda M, Ariga H, Mikoshiba K (2002) The Slp homology domain of synaptotagmin-like proteins 1–4 and Slac2 functions as a novel Rab27A binding domain. J Biol Chem 277:9212–9218. doi:10.1074/jbc.M112414200

    Article  CAS  PubMed  Google Scholar 

  38. Fukuda M (2005) Versatile role of Rab27 in membrane trafficking: focus on the Rab27 effector families. J Biochem 137:9–16. doi:10.1093/jb/mvi002

    Article  PubMed  Google Scholar 

  39. Schreij AMA, Fon EA, McPherson PS (2015) Endocytic membrane trafficking and neurodegenerative disease. Cell Mol Life Sci. doi:10.1007/s00018-015-2105-x

    PubMed  Google Scholar 

  40. Perrett RM, Alexopoulou Z, Tofaris GK (2015) The endosomal pathway in Parkinson’s disease. Mol Cell Neurosci 66:21–28. doi:10.1016/j.mcn.2015.02.009

    Article  CAS  PubMed  Google Scholar 

  41. Munsie LN, Milnerwood AJ, Seibler P et al (2015) Retromer-dependent neurotransmitter receptor trafficking to synapses is altered by the Parkinson’s disease VPS35 mutation p. D620N. Hum Mol Genet 24:1691–1703. doi:10.1093/hmg/ddu582

    Article  CAS  PubMed  Google Scholar 

  42. Fenili D, Weng Y-Q, Aubert I et al (2011) Sodium/myo-Inositol transporters: substrate transport requirements and regional brain expression in the TgCRND8 mouse model of amyloid pathology. PLoS ONE 6:e24032. doi:10.1371/journal.pone.0024032

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Ahmed I, Sbodio JI, Harraz MM et al (2015) Huntington’s disease: neural dysfunction linked to inositol polyphosphate multikinase. Proc Natl Acad Sci USA 112:9751–9756. doi:10.1073/pnas.1511810112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Wieland I, Jakubiczka S, Muschke P et al (2004) Mutations of the ephrin-B1 gene cause craniofrontonasal syndrome. Am J Hum Genet 74:1209–1215. doi:10.1086/421532

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. O’Rawe JA, Wu Y, Dörfel MJ et al (2015) TAF1 variants are associated with dysmorphic features, intellectual disability, and neurological manifestations. Am J Hum Genet 97:922–932. doi:10.1016/j.ajhg.2015.11.005

    Article  PubMed  PubMed Central  Google Scholar 

  46. Bartkuhn M, Renkawitz R (2008) Long range chromatin interactions involved in gene regulation. Biochim Biophys Acta 1783:2161–2166. doi:10.1016/j.bbamcr.2008.07.011

    Article  CAS  PubMed  Google Scholar 

  47. Edvardson S, Cinnamon Y, Ta-Shma A et al (2012) A deleterious mutation in DNAJC6 encoding the neuronal-specific clathrin-uncoating Co-chaperone auxilin, is associated with juvenile parkinsonism. PLoS ONE 7:4–8. doi:10.1371/journal.pone.0036458

    Article  Google Scholar 

  48. Koroglu C, Baysal L, Cetinkaya M et al (2013) DNAJC6 is responsible for juvenile parkinsonism with phenotypic variability. Parkinsonism Relat Disord 19:320–324. doi:10.1016/j.parkreldis.2012.11.006

    Article  PubMed  Google Scholar 

  49. Liu S, Zhang Y, Bian H, Li X (2016) Gene expression profiling predicts pathways and genes associated with Parkinson’s disease. Neurol Sci Off J Ital Neurol Soc Ital Soc Clin Neurophysiol 37:73–79. doi:10.1007/s10072-015-2360-5

    Google Scholar 

  50. Coppede F, Migliore L (2015) DNA damage in neurodegenerative diseases. Mutat Res 776:84–97. doi:10.1016/j.mrfmmm.2014.11.010

    Article  CAS  PubMed  Google Scholar 

  51. Schapira AHV, Olanow CW, Greenamyre JT, Bezard E (2014) Slowing of neurodegeneration in Parkinson’s disease and Huntington’s disease: future therapeutic perspectives. Lancet (London, England) 384:545–555. doi:10.1016/S0140-6736(14)61010-2

    Article  CAS  Google Scholar 

  52. Shen M (2002) Basic helix-loop-helix protein DEC1 promotes chondrocyte differentiation at the early and terminal stages. J Biol Chem 277:50112–50120. doi:10.1074/jbc.M206771200

    Article  CAS  PubMed  Google Scholar 

  53. Qian Y, Zhang J, Yan B, Chen X (2008) DEC1, a basic helix-loop-helix transcription factor and a novel target gene of the p53 family, mediates p53-dependent premature senescence. J Biol Chem 283:2896–2905. doi:10.1074/jbc.M708624200

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This research was funded by a Thyssen Foundation research grant, and by a Jake’s Ride for Dystonia research grant (through the Bachmann-Strauss Dystonia and Parkinson Foundation) to Ana Westenberger. Aloysius Domingo is supported by the German Academic Exchange Service (DAAD). David Amar is supported by the Azrieli Foundation and the Edmond J. Safra Center for Bioinformatics at Tel Aviv University. Ron Shamir is supported by the Raymond and Beverly Sackler Chair in Bioinformatics. Christine Klein is supported by the Hermann and Lilly Schilling Foundation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christine Klein.

Ethics declarations

Conflict of interest

Authors report no potential conflicts of interest.

Electronic supplementary material

Below is the link to the electronic supplementary material.

18_2016_2159_MOESM1_ESM.pdf

Supplementary Fig. 1. Study workflow showing the high-throughput (microarray-based, left-side) and gene-level (qPCR-based, right-side) experiments and analyses. One lane on the microarray had a defect that was undetected during hybridization but was later made obvious by quality control assessments. The blood-derived sample from an affected individual was not included in further analyses. (PDF 98 kb)

18_2016_2159_MOESM2_ESM.pdf

Supplementary Fig. 2. Expression in various parts of the brain of the different genes chosen for follow-up. Data is derived from the UK Brain Expression Consortium (http://www.braineac.org/). From top left, clockwise: transcript-level expression of SYTL2, SLC5A3, EFNB1, MRPS6, BHLHE40, KCND2, ATP6V0E2, TAF1. (PDF 296 kb)

Supplementary material 3 (XLSX 55 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Domingo, A., Amar, D., Grütz, K. et al. Evidence of TAF1 dysfunction in peripheral models of X-linked dystonia-parkinsonism. Cell. Mol. Life Sci. 73, 3205–3215 (2016). https://doi.org/10.1007/s00018-016-2159-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00018-016-2159-4

Keywords

Navigation