Project description:Dam identification (DamID) is a powerful technique to generate genome-wide maps of chromatin protein binding. Due to its high sensitivity, it is particularly suited to study the genome interactions of chromatin proteins in small tissue samples in model organisms such as Drosophila Here, we report an intein-based approach to tune the expression level of Dam and Dam-fusion proteins in Drosophila by addition of a ligand to fly food. This helps to suppress possible toxic effects of Dam. In addition, we describe a strategy for genetically controlled expression of Dam in a specific cell type in complex tissues. We demonstrate the utility of the latter by generating a glia-specific map of Polycomb in small samples of brain tissue. These new DamID tools will be valuable for the mapping of binding patterns of chromatin proteins in Drosophila tissues and especially in cell lineages.
Project description:Dam identification (DamID) is a powerful technique to generate genome-wide maps of chromatin protein binding. Due to its high sensitivity it is particularly suited to study the genome interactions of chromatin proteins in small tissue samples in model organisms such as Drosophila. Here we report an intein-based approach to tune the expression level of Dam and Dam-fusion proteins in Drosophila by addition of a ligand to fly food. This helps to suppress toxic effects of Dam. In addition we describe a strategy for genetically controlled expression of Dam in a specific cell type in complex tissues. We demonstrate the utility of the latter by generating a glia-specific map of Polycomb in small samples of brain tissue.
Project description:Dam identification (DamID) is a powerful technique to generate genome-wide maps of chromatin protein binding. Due to its high sensitivity it is particularly suited to study the genome interactions of chromatin proteins in small tissue samples in model organisms such as Drosophila. Here we report an intein-based approach to tune the expression level of Dam and Dam-fusion proteins in Drosophila by addition of a ligand to fly food. This helps to suppress toxic effects of Dam. In addition we describe a strategy for genetically controlled expression of Dam in a specific cell type in complex tissues. We demonstrate the utility of the latter by generating a glia-specific map of Polycomb in small samples of brain tissue. We determined DamID scores for Polycomb, normalized by Dam only control, for Drosophila larval central brain, larval fat bodies and repo+ glial cells of larval central brain. All samples were performed with 2 biological replicates. In case of Dam only control for larval central brain, each biological replicate was performed with 3 technical replicates.
Project description:Dam identification (DamID) is a powerful technique to generate genome-wide maps of chromatin protein binding. Due to its high sensitivity it is particularly suited to study the genome interactions of chromatin proteins in small tissue samples in model organisms such as Drosophila. Here we report an intein-based approach to tune the expression level of Dam and Dam-fusion proteins in Drosophila by addition of a ligand to fly food. This helps to suppress toxic effects of Dam. In addition we describe a strategy for genetically controlled expression of Dam in a specific cell type in complex tissues. We demonstrate the utility of the latter by generating a glia-specific map of Polycomb in small samples of brain tissue.
Project description:Dam identification (DamID) is a powerful technique to generate genome-wide maps of chromatin protein binding. Due to its high sensitivity it is particularly suited to study the genome interactions of chromatin proteins in small tissue samples in model organisms such as Drosophila. Here we report an intein-based approach to tune the expression level of Dam and Dam-fusion proteins in Drosophila by addition of a ligand to fly food. This helps to suppress toxic effects of Dam. In addition we describe a strategy for genetically controlled expression of Dam in a specific cell type in complex tissues. We demonstrate the utility of the latter by generating a glia-specific map of Polycomb in small samples of brain tissue. RNA sequencing of 3 samples, each using 2 biological replicates.
Project description:Since their inception, tetracycline (Tet)-inducible systems have become the method of choice for transgenic research. The Tet-Off systems have a number of advantages, including robust target induction using a relatively benign effector molecule. However, use of the Tet-On system has been fraught with difficulties, including high background expression in the absence of effector molecules and inconsistent gene induction. Recently, second generation Tet-On transactivators (TAs) have been described. In HeLa cells, they are far more efficient than the original reverse TA protein, and they exhibit lower background activity in the absence of effectors. Here we examine the most promising TA in transgenic Drosophila and characterize its in vivo properties. We report that low levels of doxycycline, when added to normal fly food, efficiently and rapidly induce target transgenes in adults, larvae, and embryos. This TA is superior to all other Tet-On proteins, and its performance is comparable to that of the widely used Tet-Off TA. In addition, combining the improved Tet-On TA with the Gal4-UAS (upstream-activating sequence) system produces robust, spatially restricted, temporally controlled transgene induction. Because this Tet-On TA is significantly more efficient than previous ones used in Drosophila, it is also possible to modulate gene induction by controlling the dosage of the antibiotic in the food.
Project description:Analysis of gene expression regulation typically requires identification of genomic sites where regulatory proteins bind. For this purpose, ChIP and DamID methods applied to cell lines or model organisms are now routinely used, even in selected cell types. In this work, we present modifications to experimental DamID protocol, as well as a custom data processing algorithm that allows to confidently identify genomic sites enriched with the proteins of interest. This algorithm is implemented in Perl and is also available as executable files thereby making DamID analysis relatively straightforward. Finally, we demonstrate how this pipeline performs when fed with real experimental data.