A program of tightly regulated gene expression is at the heart of development for every living organism. Recent years have seen an increased appreciation for the complexity of transcriptional control by gene Transcription Factors (TFs) as well as post-transcriptional control by small RNAs known as microRNAs (miRNAs). The interaction between TFs and miRNAs has been hypothesized to enable established cell types to maintain their identify by silencing leaky transcription, to induce rapid developmental phase transitions via direct negative feedback loops, and many other life-critical tasks. This opens a new challenge to build models that integrate these two mechanisms in order to understand their relative contributions to gene circuit function. The Arabidopsis thaliana model plant system is uniquely amenable for the prediction, validation, and manipulation of functional miRNA and TF interactions within a large eukaryotic gene system. The simplicity of miRNA:target gene base pairing, spatio-temporal organization of cells within the root system, and ease of transgenic line creation make plants an ideal starting point for studying the interplay between TFs and miRNAs in specific gene circuits. The overall goal of the proposed research is to understand how transcription and small RNA-based gene regulation work together in living cells by identifying small TF-miRNA circuits and querying their biological function. A multi-disciplinary team of mentors (Philip Benfey, Uwe Ohler) and collaborators at Duke University will guide the transition to independence through this research. A team of experts in experimental plant biology, systems biology, statistical analysis, and large-scale computing methods will provide training and monitor development during the mentored phase of the research.
The specific aims of the research project are: (1) To experimentally map transcriptional control regions in Arabidopsis (2) To identify TF-miRNA gene circuits using computational analysis (3) To characterize the functions encoded by these gene circuits using a combination of experimental and computational methods. The expected impact of the proposed research will be to provide much-needed data and computational methods for the analysis of regulatory networks involving both transcription factors and miRNAs.

Public Health Relevance

Our current rudimentary understanding of the effects of changing even one single gene in the large complex network of a living organism presents a legitimate health concern on many levels. In fields of study ranging from dietary metabolism to drug development and genetic engineering, we must progress toward detailed comprehension of how genetic circuitry functions in our foods and in our bodies. Small RNAs have been implicated in numerous human diseases from diabetes to cancer, yet knowledge about their roles in isolation is not sufficient for a clear understanding of genetic pathways;the proposed research seeks to form solid scientific scaffold for large and small-scale gene network studies by understanding the connections between transcription and small RNA-based gene regulation.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Career Transition Award (K99)
Project #
1K99GM097188-01
Application #
8095511
Study Section
Special Emphasis Panel (ZGM1-BRT-9 (KR))
Program Officer
Hagan, Ann A
Project Start
2011-04-01
Project End
2013-03-31
Budget Start
2011-04-01
Budget End
2012-03-31
Support Year
1
Fiscal Year
2011
Total Cost
$85,266
Indirect Cost
Name
Duke University
Department
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Ansariola, Mitra; Megraw, Molly; Koslicki, David (2018) IndeCut evaluates performance of network motif discovery algorithms. Bioinformatics 34:1514-1521
Sparks, Erin E; Drapek, Colleen; Gaudinier, Allison et al. (2016) Establishment of Expression in the SHORTROOT-SCARECROW Transcriptional Cascade through Opposing Activities of Both Activators and Repressors. Dev Cell 39:585-596
Megraw, Molly; Cumbie, Jason S; Ivanchenko, Maria G et al. (2016) Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants. Plant Cell 28:286-303
Cumbie, Jason S; Filichkin, Sergei A; Megraw, Molly (2015) Improved DNase-seq protocol facilitates high resolution mapping of DNase I hypersensitive sites in roots in Arabidopsis thaliana. Plant Methods 11:42
Cumbie, Jason S; Ivanchenko, Maria G; Megraw, Molly (2015) NanoCAGE-XL and CapFilter: an approach to genome wide identification of high confidence transcription start sites. BMC Genomics 16:597
Filichkin, Sergei A; Cumbie, Jason S; Dharmawardhana, Palitha et al. (2015) Environmental stresses modulate abundance and timing of alternatively spliced circadian transcripts in Arabidopsis. Mol Plant 8:207-27