Emily Beck
University of Kansas, KS·Genetics
Mitochondria, the cell's power plants, carry their own small genome of 13 protein-coding genes. They rely on roughly 2,000 proteins encoded by the cell's nuclear genome to function.
- Fields
Genetics
Ecology & Evolution
Biology
- Topics
mitochondria
mitogenome
mito-nuclear interactions
- Grants
- 1 known grant, through Dec 2026
What they work on
- Identify how the nuclear genome compensates for fast-evolving, highly divergent mitochondrial genomes in admixed threespine stickleback populations, using publicly available sequencing data.
- Compare marine and freshwater stickleback populations with mixed mitochondrial types to find nuclear compensations that depend on environment.
- Pinpoint nuclear compensations to mitochondrial variation that hold across environments, as candidates that could guide new genetic therapies, using sequencing data and preserved specimens.
More about the research
The two genomes are inherited largely separately, and the mitochondrial genome evolves 5–10 times faster. This can leave the two genomes poorly matched, and the resulting mitochondrial dysfunction underlies many neuromuscular, metabolic and cancer-related diseases. Even relatives with the same disease mutation can have different symptoms because of other genetic and environmental differences.
Why it matters
Mitochondrial dysfunction underlies neuromuscular degenerative disorders, metabolic diseases and cancers, and patients with the same mutation can respond differently to treatment. Identifying nuclear genetic changes that offset mitochondrial problems regardless of environment could point toward new genetic therapies for these conditions.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Diana Rennison
University of California-San Diego, CA·Ecology & Evolution
Survey replicate freshwater threespine stickleback populations with population genomics to measure how genetic parallelism, the repeated use of the same genes, translates across biological levels from genes to traits.
Xinjun Zhang
University of Michigan, MI·Genetics
Develop machine learning methods to detect archaic introgression from unknown 'ghost' archaic humans in East Asian genomes.
Michael Gruenstaeudl
Fort Hays State University, KS·Genetics
Build a tool that automatically links organelle genome records on GenBank to their original short-read sequencing data in the Sequence Read Archive (SRA), making the raw evidence behind each genome available for checking.
The school
University of Kansas: 26 labs on PI Pages, $546M a year on research, 351 research doctorates a year.
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