Towards the genesis of neuronal regulatory catalogs and their vocabularies
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Date
2015-01-28
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Johns Hopkins University
Abstract
My research has focused on the identification and characterization of the transcriptional enhancers required for the development and specification of neuronal populations that are impacted in human health and disease. The enhancer field has evolved quickly and as a result I have used multiple methods to identify cell-type restricted enhancers. I started by using sequence conservation to identify sequences flanking LMX1A and LMX1B that drive expression in the central nervous system. We identified 47/71 constructs driving reporter expression in the CNS of mosaic zebrafish embryos. I then identified multiple founders driving consistent expression overlapping with endogenous expression patterns in 22/47 stable lines. This is a good method for locus specific analysis but is not easily scalable to genome-wide enhancer identification. In order to identify enhancers in a broader context we applied machine learning to create a classifier that identifies hindbrain enhancers genome-wide. Using a set of experimentally proven enhancers that drive expression in the hindbrain as a training set for a machine learning algorithm that searches for over representation of known transcription factor binding sites and de novo motifs, we predicted 40,000 hindbrain enhancers. The in vivo validation rate for tested elements reached 88% for expression in the hindbrain, displaying high sensitivity but low specificity. We attribute the lack of specificity to the heterogeneity of the training set and determined to employ a new approach to acquire a more homogenous cell population. Previous work has established that the joint analysis of transcriptional co-activator EP300 with histone modification H3K4me1 by ChIP-seq in cultured cells yields a highly accurate catalog of putative enhancers. However, my specific neuronal subtypes of interest are not obtainable in the large numbers necessary for EP300 ChIP-seq. Instead, I examined public data from human substantia nigra and worked to optimize a small-cell number ChIP-seq protocol for the analysis of ex vivo sorted neurons. I have completed histone ChIP-seq in sorted neurons from a transgenic mouse line driving EGFP in DA neurons. This work identifies a catalog of putative enhancers that may play important roles in the expression of genes required for the development and maintenance of DA neurons.
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Keywords
Genetics, Genomics, Enhancers, neurons, dopamine, Parkinson's disease, zebrafish, Molecular biology, Transcriptional regulation