FOX family of transcription factor genes have expanded to over 40 members in mammals, and are involved in a variety of key developmental processes and human diseases. However, several key question concerning their evolutionary expansion, functional elaboration, transcriptional regulation, and selection are not completely understood. Gene duplication is a major driver of evolutionary innovation, as it allows an organism to elaborate existing biological function with specialization or diversification, while at the same time potentially avoiding negative fitness effects. Elaboration of new or specialized gene functions can involve at least two distinct pathways: (1) alteration of the spatial and temporal expression pattern of the gene, (2) alteration of the interaction partners, both DNA and protein. Alteration of expression patterns is likely to involve evolutionary divergence of the upstream cis regulatory elements while the alteration of interaction partners may involve sequence changes in functional domains of the protein. Previous comparative and evolutionary studies have focused on conserved aspects of gene sequence, structure and networks. Part of the challenge in studying divergence is that it is difficult to distinguish functionally relevant divergence from neutral drift. We propose to develop computational algorithms and statistical analysis methods that key in on correlated patterns of evolutionary divergence to identify novel regulatory elements and help elucidate the evolution of gene family members and their relation to disease phenotypes.
In specific aim 1 we will develop a novel method - Intra-genomic Phylogenetic Footprinting - to identify cis elements by exploiting correlated patterns of divergence in the regulatory-sequence and the expression of paralogs.
In specific aim 2, we will investigate additional pathways by which gene paralogs diversify in function and characterize the relationships between these pathways.
In specific aim 3, we will develop methods to quantify selective pressure and epistatic interactions among human cis regulatory polymorphisms. The methods will be comprehensively applied to gene families in multiple species. Application to specific gene families will provide insights into their functional expansion. Selected predictions will be experimentally validated. Besides providing a broader evolutionary understanding of gene family expansion, transcriptional regulation, and intraspecific variability in human populations, specific applications of the proposed research will be of direct biomedical relevance.

Public Health Relevance

FOX family of transcription factor genes have expanded to over 40 members in mammals, and are involved in a variety of key developmental processes and human diseases. However, several key question concerning their evolutionary expansion, functional elaboration, transcriptional regulation, and selection are not completely understood. We proposed to develop computational algorithms and statistical analysis methods to address some of these questions concerning the evolution of gene families and transcriptional regulation.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM085226-04S1
Application #
8208368
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Eckstrand, Irene A
Project Start
2009-09-18
Project End
2011-08-31
Budget Start
2010-11-01
Budget End
2011-08-31
Support Year
4
Fiscal Year
2009
Total Cost
$137,493
Indirect Cost
Name
University of Maryland College Park
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
790934285
City
College Park
State
MD
Country
United States
Zip Code
20742
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