Systematic identification of human mitochondrial disease genes through integrative genomics


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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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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Corresponding author

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).

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