We describe the comprehensive characterization of homeodomain DNA-binding specificities from a metazoan genome. The analysis of all 84 independent homeodomains from D. melanogaster reveals the breadth of DNA sequences that can be specified by this recognition motif. The majority of these factors can be organized into 11 different specificity groups, where the preferred recognition sequence between these groups can differ at up to four of the six core recognition positions. Analysis of the recognition motifs within these groups led to a catalog of common specificity determinants that may cooperate or compete to define the binding site preference. With these recognition principles, a homeodomain can be reengineered to create factors where its specificity is altered at the majority of recognition positions. This resource also allows prediction of homeodomain specificities from other organisms, which is demonstrated by the prediction and analysis of human homeodomain specificities.
FlyFactorSurvey (http://pgfe.umassmed.edu/TFDBS/) is a database of DNA binding specificities for Drosophila transcription factors (TFs) primarily determined using the bacterial one-hybrid system. The database provides community access to over 400 recognition motifs and position weight matrices for over 200 TFs, including many unpublished motifs. Search tools and flat file downloads are provided to retrieve binding site information (as sequences, matrices and sequence logos) for individual TFs, groups of TFs or for all TFs with characterized binding specificities. Linked analysis tools allow users to identify motifs within our database that share similarity to a query matrix or to view the distribution of occurrences of an individual motif throughout the Drosophila genome. Together, this database and its associated tools provide computational and experimental biologists with resources to predict interactions between Drosophila TFs and target cis-regulatory sequences.
Cetaceans have most likely experienced metabolic shifts since evolutionarily diverging from their terrestrial ancestors, shifts that may be reflected in the proteins such as cytochrome b that are responsible for metabolic efficiency. However, accepted statistical methods for detecting molecular adaptation are largely biased against even moderately conservative proteins because the primary criterion involves a comparison of nonsynonymous and synonymous substitution rates (dN/dS); they do not allow for the possibility that adaptation may come in the form of very few amino acid changes. We apply the MM01 model to the possible molecular adaptation of cytochrome b among cetaceans because it does not rely on a dN/dS ratio, instead evaluating positive selection in terms of the amino acid properties that comprise protein phenotypes that selection at the molecular level may act upon. We also apply the codon-degeneracy model (CDM), which focuses on evaluating overall patterns of nucleotide substitution in terms of base exchange, codon position, and synonymy to estimate the overall effect of selection. Using these relatively new models, we characterize the molecular adaptation that has occurred in the cetacean cytochrome b protein by comparing revealed amino acid replacement patterns to those found among artiodactyls, the modern terrestrial mammals found to be most closely related to cetaceans. Our findings suggest that several regions of the cetacean cytochrome b protein have experienced molecular adaptation. Also, these adaptations are spatially associated with domain structure, protein function, and the structure and function of the cytochrome bc(1) complex and its constituents. We also have found a general correlation between the results of the analytical software programs TreeSAAP (which implements the MM01 model) and CDM (which implements the codon-degeneracy model).
The widespread use of zinc finger nucleases (ZFNs) for genome engineering is hampered by the fact that only a subset of sequences can be efficiently recognized using published finger archives. We describe a set of validated two-finger modules that complement existing finger archives and expand the range of ZFN-accessible sequences by three-fold. Using this archive, we successfully introduce lesions at 9 of 11 target sites in the zebrafish genome.
Cys 2 -His 2 zinc finger proteins (ZFPs) are the largest group of transcription factors in higher metazoans. A complete characterization of these ZFPs and their associated target sequences is pivotal to fully annotate transcriptional regulatory networks in metazoan genomes. As a first step in this process, we have characterized the DNA-binding specificities of 129 zinc finger sets from Drosophila using a bacterial one-hybrid system. This data set contains the DNA-binding specificities for at least one encoded ZFP from 70 unique genes and 23 alternate splice isoforms representing the largest set of characterized ZFPs from any organism described to date. These recognition motifs can be used to predict genomic binding sites for these factors within the fruit fly genome. Subsets of fingers from these ZFPs were characterized to define their orientation and register on their recognition sequences, thereby allowing us to define the recognition diversity within this finger set. We find that the characterized fingers can specify 47 of the 64 possible DNA triplets. To confirm the utility of our finger recognition models, we employed subsets of Drosophila fingers in combination with an existing archive of artificial zinc finger modules to create ZFPs with novel DNA-binding specificity. These hybrids of natural and artificial fingers can be used to create functional zinc finger nucleases for editing vertebrate genomes.
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