Most complex disorders are influenced by a mix genetic and environmental factors. Environmental factors can cause changes to gene expression in the body through epigenetic mechanisms that control gene activity. The Gregg lab has discovered novel epigenetic effects in the brain and in other tissues of the body that differentially impact the expression of maternally versus paternally inherited gene copies (or alleles). We have uncovered many different forms of these effects. Canonical genomic imprinting involves complete silencing of the maternal or paternal allele. Noncanonical imprinting involves partial or cell-type specific silencing of one parent’s allele. These two mechanisms constitute heritable maternal and paternal influences on gene expression in offspring. Recently, we further discovered allele co-expression effects, differential allele expression effects and antagonistic allele expression effects in the brain. Our research reveals that diverse epigenetic effects shape the expression of maternal and paternal alleles in the brain.

Since most genetic mutations are heterozygous, meaning only one gene copy is impacted, a potential implication of our findings is that epigenetic mechanisms may silence one gene copy such that some cells in the body only express a mutated copy and the healthy backup copy is silent. We are testing the hypothesis that human brain disorders and other diseases arise, in part, because of the existence of cells that preferentially express a mutated maternal or paternal gene copy. Further, we are investigating the normal biological function of the these epigenetic effects and applications for disease diagnostics and therapy.

Mechanisms Regulating the Development of Complex Patterns of Behavior

Weaning is an amazing stage in mammalian life that involves the transition from maternal care to independence. This transition requires profound changes to brain function, metabolism and behavior. The Gregg lab is studying the epigenetic and genetic mechanisms in the brain that regulate the emergence of complex patterns of independent behavior that emerge in offspring during the weaning period. To achieve this, we have developed new approaches to study behavioral development in mouse models. Our approaches involve deep behavioral phenotyping methods that work by deconstructing complex ethological behaviors into hundreds of component features using automated video-tracking and machine learning-based methods. This work is contributing to a new field of computational developmental ethology, and it is allowing us to discover new genetic and epigenetic mechanisms that shape the development of complex patterns of behavior in offspring. In one study, we have discovered “prodigy” mouse lines that rapidly develop behavioral independence and a complex behavioral repertoire. We are working to uncover the molecular mechanisms involved.

Big Data Analysis To Uncover Master Regulatory Elements and Pathways for Disease Resistance

Breakthroughs in the biological and biomedical sciences arise in large part due to the emergence of new technologies.  One of the most transformative aspects of modern science is the ability to gather, store and analyze massive amounts of data.  The Gregg lab is actively developing novel software and other technologies to analyze and visualize large scale datasets.  One of our major interests is in the development of new approaches to study complex datasets associated with gene expression data, genome data and animal behavior data.  In addition to the computer scientists working in the Gregg Lab on these projects, we collaborate with exceptional scientists at the Scientific Computing and Imaging Institute (SCI) and Center for High Performance Computing (CHPC) at the University of Utah.  Our projects have lead to the discovery of  novel “master” regulatory elements and pathways in the mammalian genome for autism-related social behaviors, cancer resistance, insulin resistance and other disease-relevant phenotypes.




Huang* WC., Ferris* E., Cheng T, Stacher Horndli C., Tamminga C., Wagner J.D., Christian J., Gregg C. (2017) Diverse non-genetic, allele-specific expression effects shape genetic architecture at the cellular level in the mammalian brain. Neuron, 93(5), 1094-1109.

Bonthuis P, Huang WC, Statcher Horndli C, Ferris E, Cheng T, Gregg C (2015). Noncanonical genomic imprinting effects in offspring. Cell Reports, 12(6), 979-91.

Gregg C, Zhang J, Weissbourd B, Luo S, Schroth GP, Haig D, Dulac C (2010). High-resolution analysis of parent-of- origin allelic expression in the mouse brain. Science, 329(5992), 643-8.

Gregg C, Zhang J, Butler JE, Haig D, Dulac C (2010). Sex-specific parent-of-origin allelic expression in the mouse brain. Science, 329(5992), 682-5.

Gregg C.  (2010) Eppendorf winner. Parental Control Over The Brain. Science. 330(6005):770-1.


Stacher Horndli CN, Wong E, Rhodes AN, Ferris E, Fletcher PT, Gregg C. An Ethomics Approach to Study Behavioral Development and Foraging Reveals Age-Dependent Parental and Genetic Effects. (under review)

Stacher Horndli CN, Wong E, Palande S, Fletcher T, Wang B, Gregg C. Parental and Genetic Influences on Offspring Personality Architecture and Economic Strategies Revealed by a Computational Approach to Ethology. (In Preparation)


McKenna S, Meyer M, Gregg C, Gerber S (2015). s-CorrPlot: An Interactive Scatterplot for Exploring Correlation. J Comput Graph Stat, 25(2,2016).

...four other papers in preparation that will be posted here soon!