Skip to main content
  • Letter to the Editor
  • Open access
  • Published:

Gene co-expression analysis unravels a link between C9orf72 and RNA metabolism in myeloid cells

GGGGCC hexanucleotide repeat expansion in the promoter or intronic regions of C9orf72 is responsible for the most common familial forms of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) [4]. Gain-of-function of C9orf72, at the mRNA and/or protein level, is currently considered as a major mechanism of neurodegeneration in these patients [2, 5, 7]. To further elucidate the genomic impact of a C9orf72 gain-of-function, we performed a gene co-expression analysis using the open source bioinformatics tool Multi Experiment Matrix (MEM) [1] that covers a large set of human transcriptomic data (n = 1794) on the same expression array platform (Affymetrix HG-U133_Plus_2). This approach allowed us to identify the 100 mRNA species that are overall the most positively correlated with C9orf72 mRNA levels and, conversely, the 100 mRNA species that are the most inversely correlated with C9orf72 mRNA levels. We then used “EnrichR” [3] to assess these two gene lists with regard to their enrichment in subsets of genes sharing the same Gene Ontology (GO) annotations i.e. belonging to the same functional family. While we did not find any significant enrichment in the list of genes whose expression levels were positively correlated with C9orf72, the list of mRNA species that were inversely correlated with C9orf72 was highly significantly enriched in genes annotated with RNA metabolism-related GO terms. These included notably the terms “ncRNA metabolism” (adjusted p-value = 6.57E-6), “tRNA aminoacylation” (adjusted p-value = 6.57E-6) and “tRNA metabolic process” (1.90E-5). Table 1 shows the full list of GO terms for which a significant enrichment with an adjusted p-value < 0.001 was found. This data shows that an increase of C9orf72 mRNA levels associates with a concomitant downregulation of genes that exert key functions in RNA metabolism. Altered RNA metabolism is considered as a key pathological feature in not only C9orf72 mutation carriers but also patients bearing mutations in FUS or TDP43 genes as well as sporadic ALS patients [8]. Our observation suggests that an increased expression of non-mutated C9orf72 may similarly trigger RNA metabolism alterations. However, the relevance of such a finding in the context of C9orf72 mutation remains to be determined.

Table 1 Enrichment analysis of genes inversely correlated with C9orf72 mRNA levels

Interestingly, among the 1794 microarray expression studies from which C9orf72 inverse correlations were calculated, data sets analyzing the transcriptomic profile of myeloid cells, in particular acute myeloid leukemia cells, were by far the most informative i.e. giving rise to the most significant inverse correlations. In addition, it is worth noting that in the BioGPS Affymetrix expression atlas [9], C9orf72 probes are reported to detect much higher C9orf72 mRNA levels in monocytes than in neurons or astrocytes. Monocytes belong to the myeloid lineage and share many phenotypic and functional properties with microglia, although both cell types derive from distinct progenitors [6]. Therefore, one may consider that a link between C9orf72 and RNA metabolism could similarly occur in microglia. This deserves further investigation. Finally, our observation suggests that C9orf72 is possibly a key regulator of RNA metabolism in acute myeloid leukemia cells.

References

  1. Adler P, Kolde R, Kull M, Tkachenko A, Peterson H, Reimand J et al (2009) Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods. Genome Biol 10:R139. doi:10.1186/gb-2009-10-12-r139

    Article  PubMed Central  PubMed  Google Scholar 

  2. Chan HYE (2014) RNA-mediated pathogenic mechanisms in polyglutamine diseases and amyotrophic lateral sclerosis. Front Cell Neurosci 8:1–12. doi:10.3389/fncel.2014.00431

    Article  CAS  Google Scholar 

  3. Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV et al (2013) Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14:128. doi:10.1186/1471-2105-14-128

    Article  PubMed Central  PubMed  Google Scholar 

  4. DeJesus-Hernandez M, Mackenzie IR, Boeve BF, Boxer AL, Baker M, Rutherford NJ et al (2011) Expanded GGGGCC hexanucleotide repeat in noncoding region of C9ORF72 causes chromosome 9p-linked FTD and ALS. Neuron 72:245–56. doi:10.1016/j.neuron.2011.09.011

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  5. Gendron TF, Belzil VV, Zhang Y-J, Petrucelli L (2014) Mechanisms of toxicity in C9FTLD/ALS. Acta Neuropathol 127:359–76. doi:10.1007/s00401-013-1237-z

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  6. Prinz M, Mildner A (2011) Microglia in the CNS: immigrants from another world. Glia 59:177–87. doi:10.1002/glia.21104

    Article  PubMed  Google Scholar 

  7. Rohrer JD, Isaacs AM, Mizlienska S, Mead S, Lashley T, Wray S et al (2015) C9orf72 expansions in frontotemporal dementia and amyotrophic lateral sclerosis. Lancet Neurol 14:291–301. doi:10.1016/S1474-4422(14)70233-9

    Article  CAS  PubMed  Google Scholar 

  8. Sreedharan J, Brown RH (2013) Amyotrophic lateral sclerosis: problems and prospects. Ann Neurol 74:309–16. doi:10.1002/ana.24012

    Article  CAS  PubMed  Google Scholar 

  9. Wu C, Macleod I, Su AI (2013) BioGPS and MyGene.info: organizing online, gene-centric information. Nucleic Acids Res 41:D561–5. doi:10.1093/nar/gks1114

    Article  PubMed Central  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Serge Nataf.

Additional information

Competing interests

The authors declare that they have no conflict of interest.

Authors’ contribution

SN and LP carried out the bioinformatics analyses and wrote thepaper. All authors read and approved the final manuscript.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nataf, S., Pays, L. Gene co-expression analysis unravels a link between C9orf72 and RNA metabolism in myeloid cells. acta neuropathol commun 3, 64 (2015). https://doi.org/10.1186/s40478-015-0242-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40478-015-0242-y

Keywords