bioRxivPathology
Molecular signature of RV cardiac remodeling associated with Polymerase Gamma mutation
M. W. Gorr, A. Francois, L. M. Marcho, T. Saldana, E. McGrail, N. Sun, M. Stratton
Abstract
Aging is associated with metabolic dysfunction and metabolic dysfunction accelerates the course of aging. This is well illustrated by aging-like phenotypes displayed in the Polymerase Gamma mutant mouse. Here, a key residue of the mitochondrial DNA polymerase is mutated (D257A) which hinders proof reading capacity, resulting in mitochondrial DNA mutation and instability. Given known cardiac phenotypes in the POLG mutant mouse, we sought to characterize the course of cardiac dysfunction in the POLG mutant to guide future intervention studies. Including both male and female animals allowed interrogation of sex-specific responses to severe metabolic dysfunction. We also conducted RNA-seq analysis on cardiac right ventricles to broadly identify mechanisms engaged by severe metabolic dysfunction that are associated with RV pathology. Several interesting sex differences were noted. Specifically, female POLG mutants died earlier than male POLG mutants and LV chamber diameters were impacted earlier in females than males. Moreover, male POLG mutants showed LV wall thinning while female POLG mutant LV walls were thicker. Both males and females displayed significant RV hypertrophy. Finally, RNA-seq analysis of the RV tissue indicated that POLG mutation significantly impacted canonical pathways associated with inflammation, fibrosis, and heart failure. Comparison of this RNA-seq dataset with other publically available datasets highlight 1) strong conservation among downregulated genes in models of accelerated cardiac aging, 2) the potential involvement of the mitochondrial unfolded protein response in the POLG mutant, and 3) the ability of zinc dependent HDAC inhibition to rescue the expression of genes downregulated in accelerated cardiac aging.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
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