The aim of this Program Project is to discover the function of most genes in the Dictyostelium genome. In Project II we utilize concepts and methods that are centered on gene expression analysis to serve this goal. In previous years we have discovered that transcriptional profiling is a robust method for phenotypic analysis of Dictyostelium mutants and a useful means of assigning function to genes. Here we propose to study the networks that regulate gene expression during development while applying Next Generation sequencing technologies to the task. First, we will establish a 'reference transcriptome'for direct analysis of transcript abundance in the developing wild type, examining both mRNAs and non-coding RNAs. This analysis of the transcriptome will also serve as a reference for comparison with mutant strains in this project and for the entire community. Next, we will test which regulators are responsible for the dramatic transcriptional changes that accompany Dictyostelium development. We hypothesize that evolutionarily conserved transcription factors are likely to be master regulators of developmental gene expression. We will test that hypothesis by mutating the most conserved transcription factor genes and analyzing the resulting developmental phenotypes. Once we identify the transcription factors necessary for developmental progression we will use RNA sequencing (RNA-seq) and Chromatin Immunoprecipitation (ChlP-seq) to identify genes that are directly regulated by these transcription factors. Finally, we will analyze many mutants from Project 1 by transcriptional profiling, with an emphasis on mutants in genes that participate in bacterial recognition. We will intersect the transcriptional data with the fitness and the physiological data provided by Project 1 to find links between gene function and patterns of gene expression. The data we produce will also be used by Project 111 for extracting information about the genetic networks that coordinate the functions of individual genes in Dictyostelium development.
The lessons we learn can be applied to other systems, improving our ability to predict gene function from gene expression in development and in disease. Another aspect is the transcriptional response of eukaryotic cells to bacteria. This response to infection is important due of its obvious relation to human health and because our work will reveal conserved pathways used by eukaryotes in their interactions with bacteria.
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|Zitnik, Marinka; Zupan, Blaž (2014) Gene network inference by probabilistic scoring of relationships from a factorized model of interactions. Bioinformatics 30:i246-i254|
|Zitnik, Marinka; Zupan, Blaz (2014) Matrix factorization-based data fusion for gene function prediction in baker's yeast and slime mold. Pac Symp Biocomput :400-11|
|Weirauch, Matthew T; Yang, Ally; Albu, Mihai et al. (2014) Determination and inference of eukaryotic transcription factor sequence specificity. Cell 158:1431-43|
|Miranda, Edward Roshan; Rot, Gregor; Toplak, Marko et al. (2013) Transcriptional profiling of Dictyostelium with RNA sequencing. Methods Mol Biol 983:139-71|
|Miranda, Edward Roshan; Zhuchenko, Olga; Toplak, Marko et al. (2013) ABC transporters in Dictyostelium discoideum development. PLoS One 8:e70040|
|Nasser, Waleed; Santhanam, Balaji; Miranda, Edward Roshan et al. (2013) Bacterial discrimination by dictyostelid amoebae reveals the complexity of ancient interspecies interactions. Curr Biol 23:862-72|
|Huang, Eryong; Talukder, Shaheynoor; Hughes, Timothy R et al. (2011) BzpF is a CREB-like transcription factor that regulates spore maturation and stability in Dictyostelium. Dev Biol 358:137-46|
|Sucgang, Richard; Kuo, Alan; Tian, Xiangjun et al. (2011) Comparative genomics of the social amoebae Dictyostelium discoideum and Dictyostelium purpureum. Genome Biol 12:R20|
|Loomis, William F; Shaulsky, Gad (2011) Developmental changes in transcriptional profiles. Dev Growth Differ 53:567-75|
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