Systematic identification of human mitochondrial disease genes through integrative genomics

Abstract

The majority of inherited mitochondrial disorders are due to mutations not in the mitochondrial genome (mtDNA) but rather in the nuclear genes encoding proteins targeted to this organelle. Elucidation of the molecular basis for these disorders is limited because only half1,2 of the estimated 1,500 mitochondrial proteins3 have been identified. To systematically expand this catalog, we experimentally and computationally generated eight genome-scale data sets, each designed to provide clues as to mitochondrial localization: targeting sequence prediction, protein domain enrichment, presence of cis-regulatory motifs, yeast homology, ancestry, tandem-mass spectrometry, coexpression and transcriptional induction during mitochondrial biogenesis. Through an integrated analysis we expand the collection to 1,080 genes, which includes 368 novel predictions with a 10% estimated false prediction rate. By combining this expanded inventory with genetic intervals linked to disease, we have identified candidate genes for eight mitochondrial disorders, leading to the discovery of mutations in MPV17 that result in hepatic mtDNA depletion syndrome4. The integrative approach promises to better define the role of mitochondria in both rare and common human diseases.

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Figure 1: Sensitivity and specificity of mitochondrial prediction methods.
Figure 2: Integration of eight genome-scale approaches.
Figure 3: Experimental validation of novel mitochondrial predictions.

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GenBank/EMBL/DDBJ

Gene Expression Omnibus

References

  1. 1

    Andreoli, C. et al. MitoP2, an integrated database on mitochondrial proteins in yeast and man. Nucleic Acids Res. 32, D459–D462 (2004).

    CAS  Article  Google Scholar 

  2. 2

    Cotter, D., Guda, P., Fahy, E. & Subramaniam, S. MitoProteome: mitochondrial protein sequence database and annotation system. Nucleic Acids Res. 32, D463–D467 (2004).

    CAS  Article  Google Scholar 

  3. 3

    Lopez, M.F. et al. High-throughput profiling of the mitochondrial proteome using affinity fractionation and automation. Electrophoresis 21, 3427–3440 (2000).

    CAS  Article  Google Scholar 

  4. 4

    Spinazzola, A. et al. MPV17 encodes an inner mitochondrial membrane protein and is mutated in infantile hepatic mitochondrial DNA depletion. Nat. Genet., advance online publication 2 April 2006 (doi: 10.1038/ng1765).

  5. 5

    Emanuelsson, O., Nielsen, H., Brunak, S. & von Heijne, G. Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol. 300, 1005–1016 (2000).

    CAS  Article  Google Scholar 

  6. 6

    Mootha, V.K. et al. Integrated analysis of protein composition, tissue diversity, and gene regulation in mouse mitochondria. Cell 115, 629–640 (2003).

    CAS  Article  Google Scholar 

  7. 7

    Taylor, S.W. et al. Characterization of the human heart mitochondrial proteome. Nat. Biotechnol. 21, 281–286 (2003).

    CAS  Article  Google Scholar 

  8. 8

    Jansen, R. et al. A Bayesian networks approach for predicting protein-protein interactions from genomic data. Science 302, 449–453 (2003).

    CAS  Article  Google Scholar 

  9. 9

    Prokisch, H. et al. Integrative analysis of the mitochondrial proteome in yeast. PLoS Biol. 2, e160 (2004).

    Article  Google Scholar 

  10. 10

    Mootha, V.K. et al. Erralpha and Gabpa/b specify PGC-1alpha-dependent oxidative phosphorylation gene expression that is altered in diabetic muscle. Proc. Natl. Acad. Sci. USA 101, 6570–6575 (2004).

    CAS  Article  Google Scholar 

  11. 11

    Andersson, S.G. et al. The genome sequence of Rickettsia prowazekii and the origin of mitochondria. Nature 396, 133–140 (1998).

    CAS  Article  Google Scholar 

  12. 12

    Su, A.I. et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc. Natl. Acad. Sci. USA 101, 6062–6067 (2004).

    CAS  Article  Google Scholar 

  13. 13

    Lin, J. et al. Transcriptional co-activator PGC-1 alpha drives the formation of slow-twitch muscle fibres. Nature 418, 797–801 (2002).

    CAS  Article  Google Scholar 

  14. 14

    Guda, C., Fahy, E. & Subramaniam, S. MITOPRED: a genome-scale method for prediction of nucleus-encoded mitochondrial proteins. Bioinformatics 20, 1785–1794 (2004).

    CAS  Article  Google Scholar 

  15. 15

    Kopp, E. et al. ECSIT is an evolutionarily conserved intermediate in the Toll/IL-1 signal transduction pathway. Genes Dev. 13, 2059–2071 (1999).

    CAS  Article  Google Scholar 

  16. 16

    Finsterer, J. Mitochondriopathies. Eur. J. Neurol. 11, 163–186 (2004).

    CAS  Article  Google Scholar 

  17. 17

    Zeviani, M. Mitochondrial disorders. Suppl. Clin. Neurophysiol. 57, 304–312 (2004).

    Article  Google Scholar 

  18. 18

    Rotig, A. & Munnich, A. Genetic features of mitochondrial respiratory chain disorders. J. Am. Soc. Nephrol. 14, 2995–3007 (2003).

    Article  Google Scholar 

  19. 19

    Scaglia, F. et al. Clinical spectrum, morbidity, and mortality in 113 pediatric patients with mitochondrial disease. Pediatrics 114, 925–931 (2004).

    Article  Google Scholar 

  20. 20

    Shoubridge, E.A. Nuclear gene defects in respiratory chain disorders. Semin. Neurol. 21, 261–267 (2001).

    CAS  Article  Google Scholar 

  21. 21

    Thorburn, D.R. Mitochondrial disorders: prevalence, myths and advances. J. Inherit. Metab. Dis. 27, 349–362 (2004).

    CAS  Article  Google Scholar 

  22. 22

    Zwacka, R.M. et al. The glomerulosclerosis gene Mpv17 encodes a peroxisomal protein producing reactive oxygen species. EMBO J. 13, 5129–5134 (1994).

    CAS  Article  Google Scholar 

  23. 23

    Mootha, V.K. et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).

    CAS  Article  Google Scholar 

  24. 24

    Steinmuller, R., Steinberger, D. & Muller, U. MEHMO (mental retardation, epileptic seizures, hypogonadism and -genitalism, microcephaly, obesity), a novel syndrome: assignment of disease locus to xp21.1-p22.13. Eur. J. Hum. Genet. 6, 201–206 (1998).

    CAS  Article  Google Scholar 

  25. 25

    Christodoulou, K. et al. Mapping of the second Friedreich's ataxia (FRDA2) locus to chromosome 9p23-p11: evidence for further locus heterogeneity. Neurogenetics 3, 127–132 (2001).

    CAS  Article  Google Scholar 

  26. 26

    Mariman, E.C., van Beersum, S.E., Cremers, C.W., Struycken, P.M. & Ropers, H.H. Fine mapping of a putatively imprinted gene for familial non-chromaffin paragangliomas to chromosome 11q13.1: evidence for genetic heterogeneity. Hum. Genet. 95, 56–62 (1995).

    CAS  Article  Google Scholar 

  27. 27

    Seyda, A. et al. A novel syndrome affecting multiple mitochondrial functions, located by microcell-mediated transfer to chromosome 2p14–2p13. Am. J. Hum. Genet. 68, 386–396 (2001).

    CAS  Article  Google Scholar 

  28. 28

    Basel-Vanagaite, L. et al. Infantile bilateral striatal necrosis maps to chromosome 19q. Neurology 62, 87–90 (2004).

    CAS  Article  Google Scholar 

  29. 29

    Kerrison, J.B. et al. Genetic heterogeneity of dominant optic atrophy, Kjer type: Identification of a second locus on chromosome 18q12.2–12.3. Arch. Ophthalmol. 117, 805–810 (1999).

    CAS  Article  Google Scholar 

  30. 30

    El-Shanti, H., Lidral, A.C., Jarrah, N., Druhan, L. & Ajlouni, K. Homozygosity mapping identifies an additional locus for Wolfram syndrome on chromosome 4q. Am. J. Hum. Genet. 66, 1229–1236 (2000).

    CAS  Article  Google Scholar 

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Acknowledgements

We thank C. Guda for performing MitoPred analysis, J. Bunkenborg for performing Mascot searches using previously published mass spectrometry data, J. Evans of the Massachusetts Institute of Technology for assistance with microscopy and L. Gaffney for assistance with illustrations. We thank N. Patterson, L. Peshkin, B. Gewurz and E. Lander for valuable discussions and review of the manuscript. This work is funded by a grant from the United Mitochondrial Disease Foundation, a Burroughs Wellcome Fund Career Award in the Biomedical Sciences and a grant from the American Diabetes Association/Smith Family Foundation awarded to V.K.M.

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Correspondence to Vamsi K Mootha.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Maestro and MitoPred prediction overlap. (PDF 648 kb)

Supplementary Fig. 2

Mouse-to-human orthology mapping. (PDF 653 kb)

Supplementary Fig. 3

Correlation between eight data sets. (PDF 760 kb)

Supplementary Table 1

Computation of gold-standard nonmitochondrial protein Tmito. (PDF 755 kb)

Supplementary Table 2

MS/MS validation. (XLS 20 kb)

Supplementary Table 3

Previously known nuclear genes underlying mitochondrial diseases. (XLS 22 kb)

Supplementary Table 4

Human protein predictions. (XLS 8766 kb)

Supplementary Table 5

Mouse protein predictions. (XLS 7817 kb)

Supplementary Methods (PDF 119 kb)

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Calvo, S., Jain, M., Xie, X. et al. Systematic identification of human mitochondrial disease genes through integrative genomics. Nat Genet 38, 576–582 (2006). https://doi.org/10.1038/ng1776

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