Showing 2 ideas for tag "transcription"

Goal 2: Reduce Human Disease

Develop and apply single-cell-based assays to verify/modify existing biological theories

Many biological models developed to date are based on studies using heterogeneous cell populations. For example, ChIP-Seq studies have shown that RNA Pol II is frequently paused near promotes and that in stem cells, developmentally poised genes are controlled by bivalent enhancers. These studies are largely based on statistical analyses of average ChIP-Seq reads from millions of cells. Earlier biochemical analysis of... more »

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It will also be helpful to develop bioinformatic methods for quantitative analysis of the single-cell-derived results. Using these assays, it will be possible to reveal time-dependent kinetic regulation of transcription in normal and diseased cells. The outcome may revolutionize our current understanding of transcriptional regulation occurring in healthy and diseased cells, thereby benefiting the treatment of human diseases.

Name of idea submitter and other team members who worked on this idea Jinsong Zhang

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Goal 2: Reduce Human Disease

Kinetic analysis of transcriptional regulation by aberrant transcription factors in vivo

Aberrant transcription factors, such as leukemia fusion proteins, promote diseases by deregulating transcription of target genes. Recent genome-wide studies have provided new insight into transcriptional deregulation by aberrant transcription factors. Most of these studies have not used cells with synchronized transcriptional activities at specific repression/activation steps and, therefore, may have limited value in... more »

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These studies are feasible. Transcriptional regulation of a population of cells may be synchronized by epigenetic drugs, or by using inducible expression/knockdown approaches. Alternatively, it may be possible to overcome the heterogeneity issue by single-cell-based analysis. Next, time-dependent genome-wide studies may be applied to the cells to reconstruct dynamic transcriptional pathways associated with aberrant transcription factors. These approaches may be generally applicable to the study of other disease-related transcriptional and signaling molecules.

Name of idea submitter and other team members who worked on this idea Jinsong Zhang

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