# Genomic approaches for dissecting regulatory variation

> **NIH NIH R35** · UNIVERSITY OF MINNESOTA · 2020 · $385,000

## Abstract

Project Summary / Abstract
Much of the risk for common human disease arises from genetic variation among individuals. Research in my
laboratory is focused on regulatory genetic variation. This type of variation causes differences in gene
expression among individuals and contributes a substantial portion of the genetic risk for human diseases
including cardiovascular, autoimmune, and neurological disease. In spite of its critical importance for human
disease genetics, fundamental questions about regulatory variation remain unanswered.
 Because of low statistical power due to the small sample sizes commonly used when mapping
regulatory variation in the genome, the source of most regulatory variation remains unknown. The regulatory
loci that have been mapped typically span dozens of sequence variants, and we neither know the identity of
the actual causal variants, nor the molecular mechanisms through which they alter expression. Nearly all work
on regulatory variation is focused on mRNA levels, and it is unclear to what extent it translates to protein levels
and cell biology. Finally, our knowledge of how the environment can modulate the effects of regulatory
variation remains severely limited.
 This proposal outlines a research strategy to tackle these critical questions. We plan to combine
methods from quantitative and statistical genetics with experimental approaches that leverage emerging
techniques for reading, writing, and editing genomes. We will use powerful methods in the yeast
Saccharomyces cerevisiae to reveal principles of regulatory variation that are shared among eukaryotes, and
that are challenging to address in other species including humans.
 Our goals for the next five years are to dissect the influence of regulatory variation on the molecular
cascade from DNA to mRNA, proteins and cellular fitness. We plan to comprehensively identify causal
regulatory variants, understand genetic influences on mRNA and protein levels with high statistical power and
across different environments, and evaluate the effects of regulatory variation on cellular fitness. Our long term
vision is to turn yeast into the first eukaryotic species in which we can accurately predict the consequences of
natural genetic variation. The lessons to emerge from this work are expected to be highly valuable for
interpreting the role of regulatory variation in human health.

## Key facts

- **NIH application ID:** 9989865
- **Project number:** 5R35GM124676-04
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Frank Wolfgang Albert
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $385,000
- **Award type:** 5
- **Project period:** 2017-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9989865

## Citation

> US National Institutes of Health, RePORTER application 9989865, Genomic approaches for dissecting regulatory variation (5R35GM124676-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9989865. Licensed CC0.

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