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Identification of Polycomb Response Elements in Mammalian Embryonic Stem Cells and Cancer Cells Kit J. Menlove Mentored by Jianpeng Ma, Timothy Palzkill,

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Presentation on theme: "Identification of Polycomb Response Elements in Mammalian Embryonic Stem Cells and Cancer Cells Kit J. Menlove Mentored by Jianpeng Ma, Timothy Palzkill,"— Presentation transcript:

1 Identification of Polycomb Response Elements in Mammalian Embryonic Stem Cells and Cancer Cells Kit J. Menlove Mentored by Jianpeng Ma, Timothy Palzkill, and Qinghua Wang

2 Polycomb Repressive Complexes silencers –interact with Polycomb Response Elements epigenetic memory –posttranscriptionally modify histones –initiate modifications in chromatin structure –involved in long-term silencing events Cedar & Bergman, 2009

3 Polycomb Response Elements In flies, PREs have been found in the regulatory regions of genes involved in: –differentiation/pluripotency –development –cell fate decisions –stem cell self-renewal –tissue regeneration –cancer progression The first mammalian PRE was published on September 4 th (Sing et al., 2009)

4 Specific Aims 1 Identify mammalian PREs using data from chromatin immunoprecipitation (ChIP) experiments from human cancer and stem cell lines –established motif searching algorithms –linear support vector machine kernels –stochastic local alignment using population of Markov Chains

5 Specific Aims 2 and 3 Experimentally verify predicted PREs and their corresponding transcription factors –Test several PREs using a reporter system –Use ChIP-chip to detect enrichment for PRC binding –Compare verified segments to Transcription Factor databases Characterize binding energy –Build a Position-specific Energy Matrix for verified PREs and use for further searching

6 Mentoring Plan Dr. Jianpeng Ma, Rice/BCM –combinatorial statistics, simulation Dr. Timothy Palzkill, BCM –binding energy characterization Dr. Qinghua Wang, BCM –screening and validation techniques

7 Motif Searching Algorithms Projection Weeder MEME jPREdictor

8 cis-regulatory module detection Loo & Marynen, 2009

9 percentage-of-binding strategy start with a known 60-mer TF anneal SNP permutations to a chip hybridize and gather intensity data build Position-specific Energy Matrix search the genome using PEM


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