Letter

Systematic identification of human mitochondrial disease genes through integrative genomics

Received:
Accepted:
Published online:

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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Accessions

GenBank/EMBL/DDBJ

Gene Expression Omnibus

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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.

Author information

Affiliations

  1. Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

    • Sarah Calvo
    • , Mohit Jain
    • , Xiaohui Xie
    • , Sunil A Sheth
    • , Betty Chang
    • , Olga A Goldberger
    • , Steven A Carr
    •  & Vamsi K Mootha
  2. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.

    • Sarah Calvo
    • , Mohit Jain
    • , Sunil A Sheth
    • , Olga A Goldberger
    •  & Vamsi K Mootha
  3. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02446, USA.

    • Sarah Calvo
    • , Mohit Jain
    • , Sunil A Sheth
    • , Olga A Goldberger
    •  & Vamsi K Mootha
  4. Unit of Molecular Neurogenetics, National Neurological Institute 'C. Besta', 20126 Milan, Italy.

    • Antonella Spinazzola
    •  & Massimo Zeviani

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Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Vamsi K Mootha.

Supplementary information

PDF files

  1. 1.

    Supplementary Fig. 1

    Maestro and MitoPred prediction overlap.

  2. 2.

    Supplementary Fig. 2

    Mouse-to-human orthology mapping.

  3. 3.

    Supplementary Fig. 3

    Correlation between eight data sets.

  4. 4.

    Supplementary Table 1

    Computation of gold-standard nonmitochondrial protein Tmito.

  5. 5.

    Supplementary Methods

Excel files

  1. 1.

    Supplementary Table 2

    MS/MS validation.

  2. 2.

    Supplementary Table 3

    Previously known nuclear genes underlying mitochondrial diseases.

  3. 3.

    Supplementary Table 4

    Human protein predictions.

  4. 4.

    Supplementary Table 5

    Mouse protein predictions.