A mechanistic understanding of eukaryotic gene transcription is an important long-term goal in biology as it pertains to human health. Biotechnological advances have revealed heretofore unknown complexity of transcriptional regulation, challenging current models and raising new questions. The proposed projects address three such questions via novel methods and analysis, and promise to enhance our understanding of transcriptional control. (1) There are now a several known examples of "network rewiring" where a group of genes have conserved expression over long evolutionary distances but the transcriptional mechanisms underlying the expression of the genes has diverged. Understanding the mechanisms for such rewiring has implications for our understanding of evolvability and robustness of organisms. In the specific aim 1, we will develop computational methods to identify instances of transcriptional network rewiring and characterize the conditions facilitating the rewiring. (2) While traditionally, a particular transcription facto (TF) was believed to bind to a specific DNA motif, now it is becoming apparent that many TFs may recognize distinct motifs that modulate functionally distinct outcomes. In the specific aim 2, we will develop computational methods to discover and characterize functional subclasses of transcription factor binding sites. (3) Many important developmental enhancers act from a distance, up to a million nucleotides away from the target gene. How the enhancers accomplish their action-at-a-distance is not entirely clear and has implications for our understanding of developmental and tissue-specific gene regulation. In the specific aim 3 we will develop methods to map enhancers to their distal target genes. 1

Public Health Relevance

To address several questions pertaining to the mechanisms and evolution of transcriptional control, in the specific aim 1, we will develop computational methods to identify and characterize transcriptional network rewiring in yeast and in fly. In the specific aim 2, we will develop computational methods to discover and characterize functional subclasses of transcription factor binding sites. In the specific aim 3 we will develop methods to map enhancers to their distal target genes. 1

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM100335-02
Application #
8548377
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Brazhnik, Paul
Project Start
2012-09-20
Project End
2016-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
2
Fiscal Year
2013
Total Cost
$318,415
Indirect Cost
$105,243
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
Alemu, Elfalem Y; Carl Jr, Joseph W; Corrada Bravo, H├ęctor et al. (2014) Determinants of expression variability. Nucleic Acids Res 42:3503-14
Park, Seung Gu; Hannenhalli, Sridhar; Choi, Sun Shim (2014) Conservation in first introns is positively associated with the number of exons within genes and the presence of regulatory epigenetic signals. BMC Genomics 15:526
Kim, Robert; Kulkarni, Prakash; Hannenhalli, Sridhar (2013) Derepression of Cancer/testis antigens in cancer is associated with distinct patterns of DNA hypomethylation. BMC Cancer 13:144
Sahu, Avinash Das; Aniba, Radhouane; Chang, Yen-Pei Christy et al. (2013) Epigenomic model of cardiac enhancers with application to genome wide association studies. Pac Symp Biocomput :92-102
Malin, Justin; Aniba, Mohamed Radhouane; Hannenhalli, Sridhar (2013) Enhancer networks revealed by correlated DNAse hypersensitivity states of enhancers. Nucleic Acids Res 41:6828-38