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 #
5R01GM100335-03
Application #
8689106
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
2014-07-01
Budget End
2015-06-30
Support Year
3
Fiscal Year
2014
Total Cost
$198,093
Indirect Cost
$61,030
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
Karathia, Hiren; Kingsford, Carl; Girvan, Michelle et al. (2016) A pathway-centric view of spatial proximity in the 3D nucleome across cell lines. Sci Rep 6:39279
Sharmin, Mahfuza; Bravo, Héctor Corrada; Hannenhalli, Sridhar (2016) Heterogeneity of transcription factor binding specificity models within and across cell lines. Genome Res 26:1110-23
Kumar, M Senthil; Plotkin, Joshua B; Hannenhalli, Sridhar (2015) Regulated CRISPR Modules Exploit a Dual Defense Strategy of Restriction and Abortive Infection in a Model of Prokaryote-Phage Coevolution. PLoS Comput Biol 11:e1004603
Wang, Kun; Das, Avinash; Xiong, Zheng-Mei et al. (2015) Phenotype-Dependent Coexpression Gene Clusters: Application to Normal and Premature Ageing. IEEE/ACM Trans Comput Biol Bioinform 12:30-9
Das, Avinash; Morley, Michael; Moravec, Christine S et al. (2015) Bayesian integration of genetics and epigenetics detects causal regulatory SNPs underlying expression variability. Nat Commun 6:8555
Sharmin, Mahfuza; Bravo, Héctor Corrada; Hannenhalli, Sridhar (2015) Distinct genomic and epigenomic features demarcate hypomethylated blocks in colon cancer. BMC Cancer 16:88
Rangarajan, Nivedita; Kulkarni, Prakash; Hannenhalli, Sridhar (2015) Evolutionarily conserved network properties of intrinsically disordered proteins. PLoS One 10:e0126729
Sarda, Shrutii; Hannenhalli, Sridhar (2015) High-Throughput Identification of Cis-Regulatory Rewiring Events in Yeast. Mol Biol Evol 32:3047-63
Sarda, Shrutii; Hannenhalli, Sridhar (2014) Next-generation sequencing and epigenomics research: a hammer in search of nails. Genomics Inform 12:2-11
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

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