Faithin Omaha eBook Collection

Download or read book Exploring Cis-regulation in C. Elegans Gut Development with Single Molecule Resolution and Deep Learning Techniques written by Lawrence Du and published by . This book was released on 2017 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: A long-term goal of biology has been to understand how DNA sequences specify complex multicellular living organisms. Understanding this mapping of sequence to form requires identification of cis-regulatory elements and parsing their roles in gene regulatory networks (GRNs). We have tackled this problem experimentally through the study of the C. elegans gut GRN, and by developing machine learning tools for predicting and visualizing cis-regulatory sites. For the C. elegans GRN, we examined the function of \textit{cis}-regulatory GATA motifs upstream of the gut master regulator elt-2. We found that despite similar conservation and binding capability to upstream activators, different GATA cis-regulatory motifs within the promoter of the C. elegans endoderm regulator elt-2 play distinctive roles in activating and modulating gene expression throughout development. By using single copy insertion promoter-reporter constructs and high resolution single-molecule RNA FISH, we determined that a single primary dominant GATA motif located -527 bp upstream of the elt-2 start codon was necessary for both embryonic activation and later maintenance of transcription, while nearby secondary GATA motifs played largely subtle roles in modulating postembryonic levels of elt-2. Mutation of the primary activating site increased low-level spatiotemporally ectopic stochastic transcription, indicating that this site acts repressively in non-endoderm cells. Our results reveal that CREs with similar GATA factor binding affinities in close proximity can play very divergent context-dependent roles in regulating the expression of a developmentally critical gene in vivo. In order to better understand CREs in a context dependent manner, we developed a convolutional neural network (CNN) based tool, DeepNuc, to explore how deep learning techniques can be used to examine cis-regulation. We have used DeepNuc to demonstrate that much of the information needed to define a worm promoter sequence is present in the primary DNA sequence, and we have also applied our tool for exploring miRNAs.