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accession-icon SRP041313
Mismatch between mtDNA and nuclear DNA determines metabolism and healthy aging
  • organism-icon Mus musculus
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

We postulate here that the two singular characteristics of the mitochondrial oxidative phosphorylation system—the integration of three potentially antagonistic functions in the same structure and the double genetic origin of the components that assemble together in these molecular machines—make the evolution of an optimal system impossible. As a consequence the system is intrinsically mismatched and has to be continuously monitored, Adjusted and regulated in order to achieve the necessary and variable performance. Systematic transcriptomic, Metabolomic and biochemical evaluation of animals with identical nuclear DNA but different mtDNA haplotype strongly support the existence of intrinsic mismatch and reveals profound lifelong metabolic consequences on reactive oxygen species generation, Insulin signaling, Tendency towards obesity, And healthy ageing parameters, Including telomere atresia Overall design: Transcriptome analysis of conplastic mice versus WT mice in Liver and Heart tissues Conplastic strains were obtained after 10 generations of backcrossing to create a new line harboring the nuclear genome of one strain and the mtDNA of another (C57BL/6 and NZB were purchased from Harlan Laboratories).

Publication Title

Mitochondrial and nuclear DNA matching shapes metabolism and healthy ageing.

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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