36 results on '"Ann S. Hammonds"'
Search Results
2. OpenHiCAMM: High-Content Screening Software for Complex Microscope Imaging Workflows
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Benjamin W. Booth, Charles McParland, Keith Beattie, William W. Fisher, Ann S. Hammonds, Susan E. Celniker, and Erwin Frise
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Science - Abstract
Summary: High-content image acquisition is generally limited to cells grown in culture, requiring complex hardware and preset imaging modalities. Here we report an open source software package, OpenHiCAMM (Open Hi Content Acquisition for μManager), that provides a flexible framework for integration of generic microscope-associated robotics and image processing with sequential workflows. As an example, we imaged Drosophila embryos, detecting the embryos at low resolution, followed by re-imaging the detected embryos at high resolution, suitable for computational analysis and screening. The OpenHiCAMM package is easy to use and adapt for automating complex microscope image tasks. It expands our abilities for high-throughput image-based screens to a new range of biological samples, such as organoids, and will provide a foundation for bioimaging systems biology. : Optical Imaging; Technical Aspects of Cell Biology; Bioinformatics Subject Areas: Optical Imaging, Technical Aspects of Cell Biology, Bioinformatics
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- 2018
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3. Correction: Quantitative Analysis of the Segmentation Regulatory Network Using Pattern Generating Potentials.
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Majid Kazemian, Charles Blatti, Adam Richards, Michael McCutchan, Noriko Wakabayashi-Ito, Ann S. Hammonds, Susan E. Celniker, Sudhir Kumar, Scot A. Wolfe, Michael H. Brodsky, and Saurabh Sinha
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Biology (General) ,QH301-705.5 - Published
- 2013
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4. Systematic image‐driven analysis of the spatial Drosophila embryonic expression landscape
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Erwin Frise, Ann S Hammonds, and Susan E Celniker
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biological function ,embryo ,gene expression ,in situ hybridization ,Markov Random Field ,Biology (General) ,QH301-705.5 ,Medicine (General) ,R5-920 - Abstract
Abstract Discovery of temporal and spatial patterns of gene expression is essential for understanding the regulatory networks and development in multicellular organisms. We analyzed the images from our large‐scale spatial expression data set of early Drosophila embryonic development and present a comprehensive computational image analysis of the expression landscape. For this study, we created an innovative virtual representation of embryonic expression patterns using an elliptically shaped mesh grid that allows us to make quantitative comparisons of gene expression using a common frame of reference. Demonstrating the power of our approach, we used gene co‐expression to identify distinct expression domains in the early embryo; the result is surprisingly similar to the fate map determined using laser ablation. We also used a clustering strategy to find genes with similar patterns and developed new analysis tools to detect variation within consensus patterns, adjacent non‐overlapping patterns, and anti‐correlated patterns. Of the 1800 genes investigated, only half had previously assigned functions. The known genes suggest developmental roles for the clusters, and identification of related patterns predicts requirements for co‐occurring biological functions.
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- 2010
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5. An integrated host-microbiome response to atrazine exposure mediates toxicity in Drosophila
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Jian-Hua Mao, Siti Nur Sarah Morris, Susan E. Celniker, James B. Brown, William W. Fisher, Kenneth H. Wan, Richard Weiszmann, Mark R. Viant, Benjamin W. Booth, Charles Yu, Soo Park, Ann S. Hammonds, Jennifer A. Kirwan, Sasha A. Langley, Antoine M. Snijders, and Ralf J. M. Weber
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Male ,Insecticides ,QH301-705.5 ,Phenotypic screening ,Medicine (miscellaneous) ,Biology ,General Biochemistry, Genetics and Molecular Biology ,Article ,Inactivation ,chemistry.chemical_compound ,Immune system ,Detoxification ,Genetics ,Metabolomics ,Animals ,Acetobacter ,2.1 Biological and endogenous factors ,2.2 Factors relating to the physical environment ,Microbiome ,Atrazine ,Biology (General) ,Aetiology ,Transcriptomics ,Drosophila ,Nutrition ,Host Microbial Interactions ,Host (biology) ,biology.organism_classification ,Gastrointestinal Microbiome ,Drosophila melanogaster ,chemistry ,Inactivation, Metabolic ,Female ,Metabolic ,General Agricultural and Biological Sciences - Abstract
The gut microbiome produces vitamins, nutrients, and neurotransmitters, and helps to modulate the host immune system—and also plays a major role in the metabolism of many exogenous compounds, including drugs and chemical toxicants. However, the extent to which specific microbial species or communities modulate hazard upon exposure to chemicals remains largely opaque. Focusing on the effects of collateral dietary exposure to the widely used herbicide atrazine, we applied integrated omics and phenotypic screening to assess the role of the gut microbiome in modulating host resilience in Drosophila melanogaster. Transcriptional and metabolic responses to these compounds are sex-specific and depend strongly on the presence of the commensal microbiome. Sequencing the genomes of all abundant microbes in the fly gut revealed an enzymatic pathway responsible for atrazine detoxification unique to Acetobacter tropicalis. We find that Acetobacter tropicalis alone, in gnotobiotic animals, is sufficient to rescue increased atrazine toxicity to wild-type, conventionally reared levels. This work points toward the derivation of biotic strategies to improve host resilience to environmental chemical exposures, and illustrates the power of integrative omics to identify pathways responsible for adverse health outcomes., Brown et al. apply integrated omics and phenotypic screening to assess the role of the gut microbiome in modulating host resilience in Drosophila melanogaster. They find that Acetobacter tropicalis in gnotobiotic animals, is sufficient to rescue increased atrazine toxicity, which could pave the way for biotic strategies to improve host resilience to environmental chemical exposure.
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- 2021
6. Toll mediated infection response is altered by gravity and spaceflight in Drosophila.
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Katherine Taylor, Kurt Kleinhesselink, Michael D George, Rachel Morgan, Tangi Smallwood, Ann S Hammonds, Patrick M Fuller, Perot Saelao, Jeff Alley, Allen G Gibbs, Deborah K Hoshizaki, Laurence von Kalm, Charles A Fuller, Kathleen M Beckingham, and Deborah A Kimbrell
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Medicine ,Science - Abstract
Space travel presents unlimited opportunities for exploration and discovery, but requires better understanding of the biological consequences of long-term exposure to spaceflight. Immune function in particular is relevant for space travel. Human immune responses are weakened in space, with increased vulnerability to opportunistic infections and immune-related conditions. In addition, microorganisms can become more virulent in space, causing further challenges to health. To understand these issues better and to contribute to design of effective countermeasures, we used the Drosophila model of innate immunity to study immune responses in both hypergravity and spaceflight. Focusing on infections mediated through the conserved Toll and Imd signaling pathways, we found that hypergravity improves resistance to Toll-mediated fungal infections except in a known gravitaxis mutant of the yuri gagarin gene. These results led to the first spaceflight project on Drosophila immunity, in which flies that developed to adulthood in microgravity were assessed for immune responses by transcription profiling on return to Earth. Spaceflight alone altered transcription, producing activation of the heat shock stress system. Space flies subsequently infected by fungus failed to activate the Toll pathway. In contrast, bacterial infection produced normal activation of the Imd pathway. We speculate on possible linkage between functional Toll signaling and the heat shock chaperone system. Our major findings are that hypergravity and spaceflight have opposing effects, and that spaceflight produces stress-related transcriptional responses and results in a specific inability to mount a Toll-mediated infection response.
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- 2014
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7. Chromosomal Sequence of Lactobacillus brevis Oregon-R-modENCODE Strain BDGP6, a Lactic Acid Bacterium Isolated from the Gut of Drosophila melanogaster
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Benjamin W. Booth, Kenneth H. Wan, Soo Park, Susan E. Celniker, Charles Yu, Ann S. Hammonds, and Newton, Irene LG
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Proteome ,Information Storage and Retrieval ,Documentation ,Vocabulary ,Automation ,03 medical and health sciences ,0302 clinical medicine ,Immunology and Microbiology (miscellaneous) ,Artificial Intelligence ,Genetics ,Animals ,Humans ,Molecular Biology ,030304 developmental biology ,Sequence (medicine) ,Internet ,0303 health sciences ,Genome ,biology ,Strain (chemistry) ,Lactobacillus brevis ,Circular bacterial chromosome ,Human Genome ,Genome Sequences ,Chromosome Mapping ,Computational Biology ,food and beverages ,biology.organism_classification ,Molecular biology ,C content ,Interaction studies ,Lactic acid bacterium ,Database Management Systems ,Drosophila melanogaster ,Controlled ,Sequence Analysis ,030217 neurology & neurosurgery ,Signal Transduction ,Biotechnology - Abstract
Lactobacillus brevis Oregon-R-modENCODE strain BDGP6 was isolated from the gut of Drosophila melanogaster for functional host-microbial interaction studies. The bacterial chromosome is a single circular DNA molecule of 2,785,111 bp with a G+C content of 46%.
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- 2020
8. The ModERN Resource: Genome-Wide Binding Profiles for Hundreds of Drosophila and Caenorhabditis elegans Transcription Factors
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LaDeana W. Hillier, Mitch Corson, Martha Wall, D. Vafeados, Alec Victorsen, Robert H. Waterston, Robert Terrell, William W. Fisher, Susan E. Celniker, David Steffen, Matt Kirkey, Ann S. Hammonds, Koon-Kiu Yan, Mark Gerstein, Haneen N. Ammouri, Swapna Samanta, Samantha Seabrook-Sturgis, Madhura Kadaba, Lijia Ma, Soo Park, Jeffery Gersch, Matt Szynkarek, Michelle M. Kudron, Mei Han, Valerie Reinke, Kevin P. White, Jennifer L. Moran, Timothy Durham, Louis Gevirtzman, Jinrui Xu, Jaeda Patton, and Nader Jameel
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0301 basic medicine ,Genetics ,ved/biology ,fungi ,ved/biology.organism_classification_rank.species ,Computational biology ,Biology ,ENCODE ,biology.organism_classification ,Genome ,03 medical and health sciences ,chemistry.chemical_compound ,030104 developmental biology ,0302 clinical medicine ,chemistry ,Drosophila melanogaster ,Model organism ,Gene ,Transcription factor ,030217 neurology & neurosurgery ,DNA ,Caenorhabditis elegans - Abstract
The model organism Encylopedia of Regulatory Elements (modERN) project was designed to generate genome-wide binding profiles for the majority of transcription... To develop a catalog of regulatory sites in two major model organisms, Drosophila melanogaster and Caenorhabditis elegans, the modERN (model organism Encyclopedia of Regulatory Networks) consortium has systematically assayed the binding sites of transcription factors (TFs). Combined with data produced by our predecessor, modENCODE (Model Organism ENCyclopedia Of DNA Elements), we now have data for 262 TFs identifying 1.23 M sites in the fly genome and 217 TFs identifying 0.67 M sites in the worm genome. Because sites from different TFs are often overlapping and tightly clustered, they fall into 91,011 and 59,150 regions in the fly and worm, respectively, and these binding sites span as little as 8.7 and 5.8 Mb in the two organisms. Clusters with large numbers of sites (so-called high occupancy target, or HOT regions) predominantly associate with broadly expressed genes, whereas clusters containing sites from just a few factors are associated with genes expressed in tissue-specific patterns. All of the strains expressing GFP-tagged TFs are available at the stock centers, and the chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center and also through a simple interface (http://epic.gs.washington.edu/modERN/) that facilitates rapid accessibility of processed data sets. These data will facilitate a vast number of scientific inquiries into the function of individual TFs in key developmental, metabolic, and defense and homeostatic regulatory pathways, as well as provide a broader perspective on how individual TFs work together in local networks and globally across the life spans of these two key model organisms.
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- 2018
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9. Quantitative analysis of the Drosophila segmentation regulatory network using pattern generating potentials.
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Majid Kazemian, Charles Blatti, Adam Richards, Michael McCutchan, Noriko Wakabayashi-Ito, Ann S Hammonds, Susan E Celniker, Sudhir Kumar, Scot A Wolfe, Michael H Brodsky, and Saurabh Sinha
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Biology (General) ,QH301-705.5 - Abstract
Cis-regulatory modules that drive precise spatial-temporal patterns of gene expression are central to the process of metazoan development. We describe a new computational strategy to annotate genomic sequences based on their "pattern generating potential" and to produce quantitative descriptions of transcriptional regulatory networks at the level of individual protein-module interactions. We use this approach to convert the qualitative understanding of interactions that regulate Drosophila segmentation into a network model in which a confidence value is associated with each transcription factor-module interaction. Sequence information from multiple Drosophila species is integrated with transcription factor binding specificities to determine conserved binding site frequencies across the genome. These binding site profiles are combined with transcription factor expression information to create a model to predict module activity patterns. This model is used to scan genomic sequences for the potential to generate all or part of the expression pattern of a nearby gene, obtained from available gene expression databases. Interactions between individual transcription factors and modules are inferred by a statistical method to quantify a factor's contribution to the module's pattern generating potential. We use these pattern generating potentials to systematically describe the location and function of known and novel cis-regulatory modules in the segmentation network, identifying many examples of modules predicted to have overlapping expression activities. Surprisingly, conserved transcription factor binding site frequencies were as effective as experimental measurements of occupancy in predicting module expression patterns or factor-module interactions. Thus, unlike previous module prediction methods, this method predicts not only the location of modules but also their spatial activity pattern and the factors that directly determine this pattern. As databases of transcription factor specificities and in vivo gene expression patterns grow, analysis of pattern generating potentials provides a general method to decode transcriptional regulatory sequences and networks.
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- 2010
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10. Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy
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Clara Henriquez, Hamutal Arbel, Mark D. Biggin, Susan E. Celniker, Kenneth H. Wan, James B. Brown, Sumanta Basu, Soo Park, Peter J. Bickel, Richard Weiszmann, Benjamin W. Booth, Ann S. Hammonds, Omid Shams Solari, William W. Fisher, and Soile V.E. Keranen
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random forests ,Embryo, Nonmammalian ,Enhancer Elements ,Computer science ,1.1 Normal biological development and functioning ,Embryonic Development ,Computational biology ,ENCODE ,03 medical and health sciences ,Naive Bayes classifier ,0302 clinical medicine ,Genetic ,MD Multidisciplinary ,Genetics ,Animals ,Drosophila Proteins ,Segmentation ,Enhancer ,030304 developmental biology ,0303 health sciences ,Multidisciplinary ,Nonmammalian ,Human Genome ,Drosophila embryogenesis ,embryo development ,Sequence Analysis, DNA ,DNA ,Biological Sciences ,Expression (mathematics) ,Random forest ,Enhancer Elements, Genetic ,Drosophila melanogaster ,machine learning ,PNAS Plus ,Embryo ,Generic Health Relevance ,Test set ,Drosophila ,enhancers ,Sequence Analysis ,030217 neurology & neurosurgery ,Developmental Biology ,Transcription Factors ,Genome-Wide Association Study - Abstract
Significance We demonstrate a high-accuracy method for predicting enhancers genome-wide with >85% precision as validated by transgenic reporter assays in Drosophila embryos. This accuracy in a metazoan system enables us to predict with high confidence 1,640 enhancers genome-wide that participate in body segmentation during early development. The predicted enhancers are demarcated by heterogeneous collections of epigenetic marks; many strong enhancers are free from classic indicators of activity, including H3K27ac, but are bound by key transcription factors., Identifying functional enhancer elements in metazoan systems is a major challenge. Large-scale validation of enhancers predicted by ENCODE reveal false-positive rates of at least 70%. We used the pregrastrula-patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held-out data results from heterogeneity of functional signatures in enhancer elements. We show that at least two classes of enhancers are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, greater than 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well-predicted elements is composed predominantly of enhancers driving multistage segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naïve Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome. An analysis of 32 SDEs using whole-mount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.
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- 2019
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11. Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy
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Richard Weiszmann, Soo Park, Clara Henriquez, Hamutal Arbel, Peter J. Bickel, Omid Shams Solari, Susan E. Celniker, Kenneth H. Wan, Mark D. Biggin, James B. Brown, Soile V.E. Keranen, William W. Fisher, and Ann S. Hammonds
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Enhancer Elements ,biology ,Computer science ,Drosophila embryogenesis ,Genomics ,Computational biology ,biology.organism_classification ,ENCODE ,Genome ,Embryonic stem cell ,Expression (mathematics) ,Naive Bayes classifier ,chemistry.chemical_compound ,Histone ,chemistry ,Test set ,biology.protein ,Drosophila melanogaster ,Enhancer ,Transcription factor ,DNA - Abstract
Identifying functional enhancers elements in metazoan systems is a major challenge. For example, large-scale validation of enhancers predicted by ENCODE reveal false positive rates of at least 70%. Here we use the pregrastrula patterning network ofDrosophila melanogasterto demonstrate that loss in accuracy in held out data results from heterogeneity of functional signatures in enhancer elements. We show that two classes of enhancer are active during earlyDrosophilaembryogenesis and that by focusing on a single, relatively homogeneous class of elements, over 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well predicted elements is composed predominantly of enhancers driving multi-stage, segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naïve Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome, 916 of which are novel. An analysis of 32 novel SDEs using wholemount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.Significance StatementWe demonstrate a high accuracy method for predicting enhancers genome wide with > 85% precision as validated by transgenic reporter assays inDrosophilaembryos. This is the first time such accuracy has been achieved in a metazoan system, allowing us to predict with high-confidence 1640 enhancers, 916 of which are novel. The predicted enhancers are demarcated by heterogeneous collections of epigenetic marks; many strong enhancers are free from classical indicators of activity, including H3K27ac, but are bound by key transcription factors. H3K27ac, often used as a one-dimensional predictor of enhancer activity, is an uninformative parameter in our data.
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- 2018
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12. Complete Genome Sequence of Acetobacter tropicalis Oregon-R-modENCODE Strain BDGP1, an Acetic Acid Bacterium Found in the Drosophila melanogaster Gut
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Ann S. Hammonds, Kenneth H. Wan, Soo Park, Charles Yu, Susan E. Celniker, and Benjamin W. Booth
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0301 basic medicine ,Genetics ,Whole genome sequencing ,Strain (chemistry) ,Human Genome ,Biology ,biology.organism_classification ,Microbiology ,Acetobacter tropicalis ,Genome ,03 medical and health sciences ,Acetic acid ,chemistry.chemical_compound ,030104 developmental biology ,Plasmid ,chemistry ,Biochemistry and Cell Biology ,Drosophila melanogaster ,Molecular Biology ,Bacteria - Abstract
Acetobacter tropicalis Oregon-R-modENCODE strain BDGP1 was isolated from Drosophila melanogaster for functional host-microbe interaction studies. The complete genome comprises a single chromosomal circle of 3,988,649 bp with a G+C content of 56% and a conjugative plasmid of 151,013 bp.
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- 2017
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13. Complete Genome Sequence of
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Kenneth H, Wan, Charles, Yu, Soo, Park, Ann S, Hammonds, Benjamin W, Booth, and Susan E, Celniker
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Prokaryotes - Abstract
Enterococcus durans Oregon-R-modENCODE strain BDGP3 was isolated from the Drosophila melanogaster gut for functional host-microbe interaction studies. The complete genome is composed of a single circular genome of 2,983,334 bp, with a G+C content of 38%, and a single plasmid of 5,594 bp.
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- 2017
14. Complete Genome Sequence of Enterococcus durans Oregon-R-modENCODE Strain BDGP3, a Lactic Acid Bacterium Found in the Drosophila melanogaster Gut
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Benjamin W. Booth, Ann S. Hammonds, Soo Park, Susan E. Celniker, Kenneth H. Wan, and Charles Yu
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0301 basic medicine ,Genetics ,Whole genome sequencing ,biology ,Strain (chemistry) ,Human Genome ,biology.organism_classification ,Microbiology ,Genome ,Enterococcus durans ,Interaction studies ,03 medical and health sciences ,030104 developmental biology ,Plasmid ,Lactic acid bacterium ,Biochemistry and Cell Biology ,Drosophila melanogaster ,Molecular Biology ,Biotechnology - Abstract
Enterococcus durans Oregon-R-modENCODE strain BDGP3 was isolated from the Drosophila melanogaster gut for functional host-microbe interaction studies. The complete genome is composed of a single circular genome of 2,983,334 bp, with a G+C content of 38%, and a single plasmid of 5,594 bp.
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- 2017
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15. Complete Genome Sequence of Bacillus kochii Oregon-R-modENCODE Strain BDGP4, Isolated from Drosophila melanogaster Gut
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Soo Park, Ann S. Hammonds, Kenneth H. Wan, Susan E. Celniker, Benjamin W. Booth, and Charles Yu
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0301 basic medicine ,Genetics ,Whole genome sequencing ,biology ,Strain (chemistry) ,Host (biology) ,Human Genome ,biology.organism_classification ,C content ,Genome ,Microbiology ,03 medical and health sciences ,030104 developmental biology ,Plasmid ,Bacillus kochii ,Biochemistry and Cell Biology ,Drosophila melanogaster ,Molecular Biology ,Biotechnology - Abstract
Bacillus kochii Oregon-R-modENCODE strain BDGP4 was isolated from the gut of Drosophila melanogaster for functional host microbial interaction studies. The complete genome comprised a single chromosomal circle of 4,557,232 bp with a G+C content of 37% and a single plasmid of 137,143 bp.
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- 2017
16. Complete Genome Sequence of Lactobacillus plantarum Oregon-R-modENCODE Strain BDGP2 Isolated from Drosophila melanogaster Gut
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Charles Yu, Soo Park, Susan E. Celniker, Ann S. Hammonds, Kenneth H. Wan, and Benjamin W. Booth
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0301 basic medicine ,Whole genome sequencing ,Genetics ,biology ,Strain (chemistry) ,Host (biology) ,Microbial interaction ,Human Genome ,030106 microbiology ,food and beverages ,biology.organism_classification ,Microbiology ,Genome ,03 medical and health sciences ,030104 developmental biology ,Plasmid ,Biochemistry and Cell Biology ,Prokaryotes ,Drosophila melanogaster ,Molecular Biology ,Lactobacillus plantarum - Abstract
Lactobacillus plantarum Oregon-R-modENCODE strain BDGP2 was isolated from the gut of Drosophila melanogaster for functional host microbial interaction studies. The complete genome comprised a single circular genome of 3,407,160 bp, with a G+C content of 44%, and four plasmids.
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- 2017
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17. The ModERN Resource: Genome-Wide Binding Profiles for Hundreds of
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Michelle M, Kudron, Alec, Victorsen, Louis, Gevirtzman, LaDeana W, Hillier, William W, Fisher, Dionne, Vafeados, Matt, Kirkey, Ann S, Hammonds, Jeffery, Gersch, Haneen, Ammouri, Martha L, Wall, Jennifer, Moran, David, Steffen, Matt, Szynkarek, Samantha, Seabrook-Sturgis, Nader, Jameel, Madhura, Kadaba, Jaeda, Patton, Robert, Terrell, Mitch, Corson, Timothy J, Durham, Soo, Park, Swapna, Samanta, Mei, Han, Jinrui, Xu, Koon-Kiu, Yan, Susan E, Celniker, Kevin P, White, Lijia, Ma, Mark, Gerstein, Valerie, Reinke, and Robert H, Waterston
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Chromatin Immunoprecipitation ,Binding Sites ,fungi ,Models, Biological ,Communications ,Databases, Genetic ,Animals ,natural sciences ,Drosophila ,Nucleotide Motifs ,Caenorhabditis elegans ,Genome-Wide Association Study ,Protein Binding ,Transcription Factors - Abstract
To develop a catalog of regulatory sites in two major model organisms, Drosophila melanogaster and Caenorhabditis elegans, the modERN (model organism Encyclopedia of Regulatory Networks) consortium has systematically assayed the binding sites of transcription factors (TFs). Combined with data produced by our predecessor, modENCODE (Model Organism ENCyclopedia Of DNA Elements), we now have data for 262 TFs identifying 1.23 M sites in the fly genome and 217 TFs identifying 0.67 M sites in the worm genome. Because sites from different TFs are often overlapping and tightly clustered, they fall into 91,011 and 59,150 regions in the fly and worm, respectively, and these binding sites span as little as 8.7 and 5.8 Mb in the two organisms. Clusters with large numbers of sites (so-called high occupancy target, or HOT regions) predominantly associate with broadly expressed genes, whereas clusters containing sites from just a few factors are associated with genes expressed in tissue-specific patterns. All of the strains expressing GFP-tagged TFs are available at the stock centers, and the chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center and also through a simple interface (http://epic.gs.washington.edu/modERN/) that facilitates rapid accessibility of processed data sets. These data will facilitate a vast number of scientific inquiries into the function of individual TFs in key developmental, metabolic, and defense and homeostatic regulatory pathways, as well as provide a broader perspective on how individual TFs work together in local networks and globally across the life spans of these two key model organisms.
- Published
- 2017
18. Comparative Analysis of the Transcriptome across Distant Species
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Gang Fang, LaDeana W. Hillier, Brenton R. Graveley, Ali Mortazavi, Norbert Perrimon, Nathan Boley, Jingyi Jessica Li, William C. Spencer, James B. Brown, Chau Huynh, Roger A. Hoskins, Mark Gerstein, Ann S. Hammonds, Sarah Djebali, Sonali Jha, Kenneth H. Wan, Cédric Howald, Raymond K. Auerbach, Chenghai Xue, Haiyan Huang, Jorg Drenkow, Elise A. Feingold, Julien Lagarde, Daifeng Wang, Dmitri D. Pervouchine, Thomas R. Gingeras, Guilin Wang, Peter Cherbas, Brent Ewing, Chao Di, Gary Saunders, Benjamin W. Booth, Joel Rozowsky, Yan Zhang, Anastasia Samsonova, Dionna M. Kasper, Cristina Sisu, Marcus H. Stoiber, Jiayu Wen, Michael O. Duff, Felix Schlesinger, Gennifer E. Merrihew, Sara Olson, Susan E. Celniker, Burak H. Alver, Chao Cheng, Gemma E. May, Alexandre Reymond, Carrie A. Davis, Alexander Dobin, Max E. Boeck, Roger P. Alexander, Michael J. Pazin, Peter J. Park, Adam Frankish, Lucy Cherbas, Zhi Lu, Kevin Y. Yip, Henry Zheng, Owen Thompson, Jing Leng, Kathie L. Watkins, Andrea Tanzer, Valerie Reinke, Rebecca McWhirter, Eric C. Lai, Steven E. Brenner, Robert H. Waterston, Koon-Kiu Yan, Masaomi Kato, Roderic Guigó, Huaien Wang, Kimberly Bell, Pnina Strasbourger, Baikang Pei, Jen Harrow, Long Hu, Chris Zaleski, Rabi Murad, Thomas C. Kaufman, Erik Ladewig, Robert R. Kitchen, Anurag Sethi, Kejia Wen, Guanjun Gao, Arif Harmanci, Megan Fastuca, Brian Oliver, Frank J. Slack, David M. Miller, Tim Hubbard, Garrett Robinson, Peter J. Good, Peter J. Bickel, Michael J. MacCoss, and Li Yang
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RNA, Untranslated ,Caenorhabditis elegans -- Embriologia ,Genome ,Transcriptome ,Histones ,0302 clinical medicine ,Models ,Cluster Analysis ,Developmental ,Drosòfila -- Genètica ,Promoter Regions, Genetic ,Genetics ,0303 health sciences ,Multidisciplinary ,biology ,Pupa ,Untranslated ,Gene Expression Regulation, Developmental ,Chromatin ,Molecular Sequence Annotation ,Drosophila melanogaster ,Larva ,Sequence Analysis ,Biotechnology ,animal structures ,General Science & Technology ,Computational biology ,ENCODE ,Article ,Promoter Regions ,03 medical and health sciences ,Genetic ,Regulació genètica ,Animals ,Humans ,Transcriptomics ,Caenorhabditis elegans ,030304 developmental biology ,Comparative genomics ,Models, Genetic ,Phylum ,Sequence Analysis, RNA ,Gene Expression Profiling ,fungi ,Human Genome ,biology.organism_classification ,Gene expression profiling ,Gene Expression Regulation ,RNA ,Generic health relevance ,030217 neurology & neurosurgery - Abstract
The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features1, 2, 3, 4, 5, 6. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a ‘universal model’ based on a single set of organism-independent parameters. In particular, this work was funded by a contract from the National Human Genome Research Institute modENCODE Project, contract U01 HG004271 and U54 HG006944, to S.E.C. (principal investigator) and P.C., T.R.G., R.A.H. and B.R.G. (co-principal investigators) with additional support from R01 GM076655 (S.E.C.) both under Department of Energy contract no. DE-AC02-05CH11231, and U54 HG007005 to B.R.G. J.B.B.’s work was supported by NHGRI K99 HG006698 and DOE DE-AC02-05CH11231. Work in P.J.B.’s group was supported by the modENCODE DAC sub award 5710003102, 1U01HG007031-01 and the ENCODE DAC 5U01HG004695-04. Work in M.B.G.’s group was supported by NIH grants HG007000 and HG007355. Work in Bloomington was supported in part by the Indiana METACyt Initiative of Indiana University, funded by an award from the Lilly Endowment, Inc. Work in E.C.L.’s group was supported by U01-HG004261 and RC2-HG005639. P.J.P. acknowledges support from the National Institutes of Health (grant no. U01HG004258). We thank the HAVANA team for providing annotation of the human reference genome, whose work is supported by National Institutes of Health (grant no. 5U54HG004555), the Wellcome Trust (grant no. WT098051). R.G. acknowledges support from the Spanish Ministry of Education (grant BIO2011-26205). We also acknowledge use of the Yale University Biomedical High Performance Computing Center. R.W.'s lab was supported by grant no. U01 HG 004263.
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- 2014
19. Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks
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Siqi Wu, Ann S. Hammonds, Susan E. Celniker, Antony Joseph, Erwin Frise, and Bin Yu
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0301 basic medicine ,Computer science ,Stability (learning theory) ,Gene regulatory network ,sparse decomposition ,Computational biology ,computer.software_genre ,Non-negative matrix factorization ,Set (abstract data type) ,03 medical and health sciences ,Databases ,Genetic ,Models ,Databases, Genetic ,Genetics ,Animals ,Gene Regulatory Networks ,Representation (mathematics) ,Gap gene ,principal patterns ,Multidisciplinary ,Models, Genetic ,Model selection ,spatially local networks ,stability selection ,030104 developmental biology ,Drosophila melanogaster ,Gene Expression Regulation ,Scalability ,Physical Sciences ,Data mining ,spatial gene expression ,Generic health relevance ,computer - Abstract
Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. The performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.
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- 2016
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20. The developmental transcriptome of Drosophila melanogaster
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Roger A. Hoskins, Peter Cherbas, Brian B. Tuch, Lucy Cherbas, Michael R. Brent, Wei Lin, Laura Langton, Dayu Zhang, James B. Brown, Thomas R. Gingeras, Aarron T. Willingham, Alexander Dobin, Brenton R. Graveley, Susan E. Celniker, Nathan Boley, Carlo G. Artieri, Steven E. Brenner, Nicolas R. Mattiuzzo, Carrie A. Davis, Marco Blanchette, Jeremy E. Sandler, David Sturgill, Sandrine Dudoit, Brian Oliver, Benjamin W. Booth, Peter J. Bickel, Renhua Li, Yu Zhang, Norbert Perrimon, Phil Kapranov, David Scott Miller, Ann S. Hammonds, Marijke J. van Baren, Yi Zou, Richard E. Green, Joseph W. Carlson, Lichun Jiang, Jane M. Landolin, Chris Zaleski, Li Yang, Kenneth H. Wan, Thomas C. Kaufman, Brian D. Eads, John H. Malone, Angela N. Brooks, Michael O. Duff, and Justen Andrews
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Genetics ,0303 health sciences ,Multidisciplinary ,biology ,Computational biology ,biology.organism_classification ,Genome ,Article ,Transcriptome ,03 medical and health sciences ,Exon ,0302 clinical medicine ,RNA editing ,Genetic model ,RNA splicing ,Drosophila melanogaster ,Gene ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
Drosophila melanogaster is one of the most well studied genetic model organisms, nonetheless its genome still contains unannotated coding and non-coding genes, transcripts, exons, and RNA editing sites. Full discovery and annotation are prerequisites for understanding how the regulation of transcription, splicing, and RNA editing directs development of this complex organism. We used RNA-Seq, tiling microarrays, and cDNA sequencing to explore the transcriptome in 30 distinct developmental stages. We identified 111,195 new elements, including thousands of genes, coding and non-coding transcripts, exons, splicing and editing events and inferred protein isoforms that previously eluded discovery using established experimental, prediction and conservation-based approaches. Together, these data substantially expand the number of known transcribed elements in the Drosophila genome and provide a high-resolution view of transcriptome dynamics throughout development.
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- 2010
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21. Determination of gene expression patterns using high-throughput RNA in situ hybridization to whole-mount Drosophila embryos
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Richard Weiszmann, Ann S. Hammonds, and Susan E. Celniker
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Embryo, Nonmammalian ,animal structures ,Embryonic Development ,Dot blot ,In situ hybridization ,Biology ,Polymerase Chain Reaction ,Article ,General Biochemistry, Genetics and Molecular Biology ,Embryo Culture Techniques ,Transcription (biology) ,Gene expression ,Animals ,Cloning, Molecular ,In Situ Hybridization ,Gene Expression Profiling ,Hybridization probe ,Gene Expression Regulation, Developmental ,RNA ,RNA Probes ,Molecular biology ,Antisense RNA ,genomic DNA ,embryonic structures ,Drosophila - Abstract
We describe a high-throughput protocol for RNA in situ hybridization (ISH) to Drosophila embryos in 96-well format. cDNA or genomic DNA templates are amplified by PCR and then digoxigenin-labeled ribonucleotides are incorporated into anti-sense RNA probes by in vitro transcription. The quality of each probe is evaluated prior to in situ hybridization using a RNA Probe Quantification (dot blot) assay. RNA probes are hybridized to fixed, mixed-staged Drosophila embryos in 96-well plates. The resulting stained embryos can be examined and photographed immediately or stored at 4°C for later analysis. Starting with fixed, staged embryos, the protocol takes 6 days from probe template production through hybridization. Preparation of fixed embryos requires a minimum of two weeks to collect embryos representing all stages. The method has been used to determine the expression patterns of over 6000 genes throughout embryogenesis.
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- 2009
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22. Tools for neuroanatomy and neurogenetics in Drosophila
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Christopher J. Mungall, Todd R. Laverty, Barret D. Pfeiffer, James T. Kadonaga, Ann S. Hammonds, Michael B. Eisen, Chris Q. Doe, Gerald M. Rubin, Arnim Jenett, Susan E. Celniker, Audra Scully, Rob Svirskas, Sima Misra, Christine Murphy, Teri T.B. Ngo, Kenneth H. Wan, and Joseph W. Carlson
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Biomedical Research ,Transgene ,Genes, Insect ,Computational biology ,Biology ,Animals, Genetically Modified ,Transcription (biology) ,Gene expression ,medicine ,Animals ,Enhancer ,Gene ,Neurons ,Recombination, Genetic ,Genetics ,Multidisciplinary ,Neurosciences ,Brain ,Gene Expression Regulation, Developmental ,Promoter ,Biological Sciences ,biology.organism_classification ,Drosophila melanogaster ,Enhancer Elements, Genetic ,medicine.anatomical_structure ,Neuroanatomy - Abstract
We demonstrate the feasibility of generating thousands of transgenic Drosophila melanogaster lines in which the expression of an exogenous gene is reproducibly directed to distinct small subsets of cells in the adult brain. We expect the expression patterns produced by the collection of 5,000 lines that we are currently generating to encompass all neurons in the brain in a variety of intersecting patterns. Overlapping 3-kb DNA fragments from the flanking noncoding and intronic regions of genes thought to have patterned expression in the adult brain were inserted into a defined genomic location by site-specific recombination. These fragments were then assayed for their ability to function as transcriptional enhancers in conjunction with a synthetic core promoter designed to work with a wide variety of enhancer types. An analysis of 44 fragments from four genes found that >80% drive expression patterns in the brain; the observed patterns were, on average, comprised of D. melanogaster genome contains >50,000 enhancers and that multiple enhancers drive distinct subsets of expression of a gene in each tissue and developmental stage. We expect that these lines will be valuable tools for neuroanatomy as well as for the elucidation of neuronal circuits and information flow in the fly brain.
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- 2008
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23. Mutational Analysis of Stubble-stubbloid Gene Structure and Function in Drosophila Leg and Bristle Morphogenesis
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James W. Fristrom and Ann S. Hammonds
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DNA Mutational Analysis ,Morphogenesis ,Investigations ,Biology ,medicine.disease_cause ,Bristle ,Animals, Genetically Modified ,Structure-Activity Relationship ,Genetics ,medicine ,Animals ,Drosophila Proteins ,Transgenes ,Cytoskeleton ,Actin ,Genes, Dominant ,Mutation ,Polymorphism, Genetic ,Hydrolysis ,Serine Endopeptidases ,Membrane Proteins ,Extremities ,Transmembrane protein ,Extracellular Matrix ,Imaginal disc ,Phenotype ,Drosophila ,Drosophila Protein - Abstract
The Stubble-stubbloid (Sb-sbd) gene is required for ecdysone-regulated epithelial morphogenesis of imaginal tissues during Drosophila metamorphosis. Mutations in Sb-sbd are associated with defects in apical cell shape changes critical for the evagination of the leg imaginal disc and with defects in assembly and extension of parallel actin bundles in growing mechanosensory bristles. The Sb-sbd gene encodes a type II transmembrane serine protease (TTSP). Here we use a Sb-sbd transgenic construct to rescue both bristle and leg morphogenesis defects in Sb-sbd mutations. Molecular characterization of Sb-sbd mutations and rescue experiments with wild-type and modified Sb-sbd transgenic constructs show that the protease domain is required for both leg and bristle functions. Truncated proteins that express the noncatalytic domains without the protease have dominant effects in bristles but not in legs. Leg morphogenesis, but not bristle growth, is sensitive to Sb-sbd overexpression. Antibody localization of the Sb-sbd protein shows apical expression in elongating legs. Sb-sbd protein is found in the base and shaft in budding bristles and then concentrates at the growing tip when bristles are elongating rapidly. We propose a model whereby Sb-sbd helps coordinate proteolytic modification of extracellular matrix attachments with cytoskeletal changes in both legs and bristles.
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- 2006
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24. Toll mediated infection response is altered by gravity and spaceflight in Drosophila
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Jeff Alley, Perot Saelao, Deborah K. Hoshizaki, Rachel Morgan, Katherine Taylor, Tangi Smallwood, Ann S. Hammonds, Kurt Kleinhesselink, Laurence von Kalm, Kathleen M. Beckingham, Allen G. Gibbs, Patrick M. Fuller, Michael D. George, Deborah A. Kimbrell, Charles A. Fuller, and Söderhäll, Kenneth
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Male ,lcsh:Medicine ,Astronomical Sciences ,law.invention ,Molecular cell biology ,law ,Drosophila Proteins ,Innate ,lcsh:Science ,Immune Response ,Heat-Shock Proteins ,Cellular Stress Responses ,Multidisciplinary ,Weightlessness ,Drosophila Melanogaster ,Toll-Like Receptors ,Animal Models ,Space Exploration ,Signaling in Selected Disciplines ,Innate Immunity ,Drosophila melanogaster ,Infectious Diseases ,Botrytis ,Infection ,Research Article ,Signal Transduction ,General Science & Technology ,Immunology ,DNA transcription ,Gravitaxis ,Hypergravity ,Space Missions ,Biology ,Immunological Signaling ,Spaceflight ,Immunocompromised Host ,Model Organisms ,Immune system ,Heat shock protein ,Escherichia coli ,Genetics ,Animals ,Heat shock ,Innate immune system ,Inflammatory and immune system ,lcsh:R ,Immunity ,Space Flight ,Immunity, Innate ,Gene Expression Regulation ,lcsh:Q ,Gene expression ,Antimicrobial Cationic Peptides - Abstract
Space travel presents unlimited opportunities for exploration and discovery, but requires better understanding of the biological consequences of long-term exposure to spaceflight. Immune function in particular is relevant for space travel. Human immune responses are weakened in space, with increased vulnerability to opportunistic infections and immune-related conditions. In addition, microorganisms can become more virulent in space, causing further challenges to health. To understand these issues better and to contribute to design of effective countermeasures, we used the Drosophila model of innate immunity to study immune responses in both hypergravity and spaceflight. Focusing on infections mediated through the conserved Toll and Imd signaling pathways, we found that hypergravity improves resistance to Toll-mediated fungal infections except in a known gravitaxis mutant of the yuri gagarin gene. These results led to the first spaceflight project on Drosophila immunity, in which flies that developed to adulthood in microgravity were assessed for immune responses by transcription profiling on return to Earth. Spaceflight alone altered transcription, producing activation of the heat shock stress system. Space flies subsequently infected by fungus failed to activate the Toll pathway. In contrast, bacterial infection produced normal activation of the Imd pathway. We speculate on possible linkage between functional Toll signaling and the heat shock chaperone system. Our major findings are that hypergravity and spaceflight have opposing effects, and that spaceflight produces stress-related transcriptional responses and results in a specific inability to mount a Toll-mediated infection response.
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- 2014
25. Spatial expression of transcription factors in Drosophila embryonic organ development
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Christopher A. Bristow, Manolis Kellis, Richard Weiszmann, Susan E. Celniker, William W. Fisher, Siqi Wu, Volker Hartenstein, Erwin Frise, Ann S. Hammonds, Bin Yu, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Bristow, Christopher A., and Kellis, Manolis
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Central Nervous System ,Bioinformatics ,Response element ,genetic processes ,Gene regulatory network ,Context (language use) ,Computational biology ,Biology ,03 medical and health sciences ,0302 clinical medicine ,Information and Computing Sciences ,Genetics ,Animals ,Drosophila Proteins ,natural sciences ,Developmental ,Gene Regulatory Networks ,Gene ,Transcription factor ,In Situ Hybridization ,030304 developmental biology ,0303 health sciences ,Research ,Gene Expression Profiling ,fungi ,Gene Expression Regulation, Developmental ,Biological Sciences ,Gene expression profiling ,Drosophila melanogaster ,Spatiotemporal gene expression ,Gene Expression Regulation ,Organ Specificity ,030217 neurology & neurosurgery ,Environmental Sciences ,Transcription Factors ,Biotechnology - Abstract
Background: Site-specific transcription factors (TFs) bind DNA regulatory elements to control expression of target genes, forming the core of gene regulatory networks. Despite decades of research, most studies focus on only a small number of TFs and the roles of many remain unknown. Results: We present a systematic characterization of spatiotemporal gene expression patterns for all known or predicted Drosophila TFs throughout embryogenesis, the first such comprehensive study for any metazoan animal. We generated RNA expression patterns for all 708 TFs by in situ hybridization, annotated the patterns using an anatomical controlled vocabulary, and analyzed TF expression in the context of organ system development. Nearly all TFs are expressed during embryogenesis and more than half are specifically expressed in the central nervous system. Compared to other genes, TFs are enriched early in the development of most organ systems, and throughout the development of the nervous system. Of the 535 TFs with spatially restricted expression, 79% are dynamically expressed in multiple organ systems while 21% show single-organ specificity. Of those expressed in multiple organ systems, 77 TFs are restricted to a single organ system either early or late in development. Expression patterns for 354 TFs are characterized for the first time in this study. Conclusions: We produced a reference TF dataset for the investigation of gene regulatory networks in embryogenesis, and gained insight into the expression dynamics of the full complement of TFs controlling the development of each organ system., National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award
- Published
- 2013
26. Quantitative Analysis of the Drosophila Segmentation Regulatory Network Using Pattern Generating Potentials
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Majid Kazemian, Charles Blatti, Adam Richards, Michael McCutchan, Noriko Wakabayashi-Ito, Ann S. Hammonds, Susan E. Celniker, Sudhir Kumar, Scot A. Wolfe, Michael H. Brodsky, and Saurabh Sinha
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0303 health sciences ,03 medical and health sciences ,0302 clinical medicine ,General Immunology and Microbiology ,QH301-705.5 ,General Neuroscience ,Correction ,Biology (General) ,General Agricultural and Biological Sciences ,030217 neurology & neurosurgery ,General Biochemistry, Genetics and Molecular Biology ,030304 developmental biology - Published
- 2013
27. DNA regions bound at low occupancy by transcription factors do not drive patterned reporter gene expression in Drosophila
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Barret D. Pfeiffer, Peter J. Bickel, Stewart MacArthur, Jingyi Jessica Li, Ann S. Hammonds, William W. Fisher, Michael B. Eisen, Susan E. Celniker, James B. Brown, Sean Thomas, Mark D. Biggin, Richard Weiszmann, and John A. Stamatoyannopoulos
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Male ,Embryo, Nonmammalian ,Response element ,Genome, Insect ,Kruppel-Like Transcription Factors ,E-box ,Biology ,Animals, Genetically Modified ,Genes, Reporter ,Animals ,Drosophila Proteins ,Enhancer ,Genetics ,Multidisciplinary ,General transcription factor ,Gene Expression Regulation, Developmental ,Promoter ,TCF4 ,DNA ,Biological Sciences ,Drosophila melanogaster ,TAF2 ,GATA transcription factor ,Female ,Protein Binding ,Transcription Factors - Abstract
In animals, each sequence-specific transcription factor typically binds to thousands of genomic regions in vivo. Our previous studies of 20 transcription factors show that most genomic regions bound at high levels in Drosophila blastoderm embryos are known or probable functional targets, but genomic regions occupied only at low levels have characteristics suggesting that most are not involved in the cis -regulation of transcription. Here we use transgenic reporter gene assays to directly test the transcriptional activity of 104 genomic regions bound at different levels by the 20 transcription factors. Fifteen genomic regions were selected based solely on the DNA occupancy level of the transcription factor Kruppel. Five of the six most highly bound regions drive blastoderm patterns of reporter transcription. In contrast, only one of the nine lowly bound regions drives transcription at this stage and four of them are not detectably active at any stage of embryogenesis. A larger set of 89 genomic regions chosen using criteria designed to identify functional cis -regulatory regions supports the same trend: genomic regions occupied at high levels by transcription factors in vivo drive patterned gene expression, whereas those occupied only at lower levels mostly do not. These results support studies that indicate that the high cellular concentrations of sequence-specific transcription factors drive extensive, low-occupancy, nonfunctional interactions within the accessible portions of the genome.
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- 2012
28. Development of expression-ready constructs for generation of proteomic libraries
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Charles, Yu, Kenneth H, Wan, Ann S, Hammonds, Mark, Stapleton, Joseph W, Carlson, and Susan E, Celniker
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Cell Extracts ,Electrophoresis, Agar Gel ,Proteomics ,Bacteria ,Genetic Vectors ,Cell Culture Techniques ,Computational Biology ,Gene Expression ,Polymerase Chain Reaction ,Open Reading Frames ,Drug Resistance, Bacterial ,Chromatography, Gel ,Ampicillin ,Transformation, Bacterial ,Cloning, Molecular ,Deoxyribonucleases, Type II Site-Specific ,DNA Primers ,Gene Library - Abstract
We describe a method for high-throughput production of protein expression-ready clones. Open-reading frames (ORFs) are amplified by PCR from sequence-verified cDNA clones and subcloned into an appropriate loxP-containing donor vector. Each ORF is represented by two types of clones, one containing the native stop codon for expression of the native protein or amino-terminal fusion constructs and the other made without the stop codon to allow for carboxy-terminal fusion constructs. The expression-ready clone is sequenced to verify that no PCR errors have been introduced. We have made over 11,000 clones ranging in size from 78-6,699 bp with a median of 1,056 bp. This is the largest set of fully sequence-verified-"movable ORFs" of any model organism genome project. The donor clone facilitates rapid and simple transfer of the ORF into any expression vector of choice. Vectors are available for expressing these ORFs in bacteria, cell lines, or transgenic animals. The flexibility of this ORF clone collection makes possible a variety of proteomic applications, including protein interaction mapping, high-throughput cell-based expression screens, and functional studies. We have transferred 5,800 ORFs to a vector that allows production of a FLAG-HA tagged protein in Drosophila tissue culture cells with a metallothionein-inducible promoter. These clones are being used to produce a protein complex map of Drosophila from Schneider cells.
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- 2011
29. Development of Expression-Ready Constructs for Generation of Proteomic Libraries
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Mark Stapleton, Joseph W. Carlson, Charles Yu, Kenneth H. Wan, Susan E. Celniker, and Ann S. Hammonds
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clone (Java method) ,Open reading frame ,Expression vector ,Complementary DNA ,Genomic library ,Genome project ,Computational biology ,ORFS ,Biology ,Stop codon - Abstract
We describe a method for high-throughput production of protein expression-ready clones. Open-reading frames (ORFs) are amplified by PCR from sequence-verified cDNA clones and subcloned into an appropriate loxP-containing donor vector. Each ORF is represented by two types of clones, one containing the native stop codon for expression of the native protein or amino-terminal fusion constructs and the other made without the stop codon to allow for carboxy-terminal fusion constructs. The expression-ready clone is sequenced to verify that no PCR errors have been introduced. We have made over 11,000 clones ranging in size from 78-6,699 bp with a median of 1,056 bp. This is the largest set of fully sequence-verified-"movable ORFs" of any model organism genome project. The donor clone facilitates rapid and simple transfer of the ORF into any expression vector of choice. Vectors are available for expressing these ORFs in bacteria, cell lines, or transgenic animals. The flexibility of this ORF clone collection makes possible a variety of proteomic applications, including protein interaction mapping, high-throughput cell-based expression screens, and functional studies. We have transferred 5,800 ORFs to a vector that allows production of a FLAG-HA tagged protein in Drosophila tissue culture cells with a metallothionein-inducible promoter. These clones are being used to produce a protein complex map of Drosophila from Schneider cells.
- Published
- 2011
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30. Quantitative analysis of the Drosophila segmentation regulatory network using pattern generating potentials
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Michael H. Brodsky, Majid Kazemian, Scot A. Wolfe, Saurabh Sinha, Sudhir Kumar, Michael McCutchan, Noriko Wakabayashi-Ito, Ann S. Hammonds, Adam Richards, Susan E. Celniker, and Charles Blatti
- Subjects
Genome evolution ,QH301-705.5 ,Gene regulatory network ,Computational Biology/Transcriptional Regulation ,Computational biology ,Biology ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,0302 clinical medicine ,Animals ,Segmentation ,Gene Regulatory Networks ,Biology (General) ,Transcription factor ,030304 developmental biology ,Cis-regulatory module ,Body Patterning ,Regulation of gene expression ,0303 health sciences ,Binding Sites ,General Immunology and Microbiology ,Models, Genetic ,General Neuroscience ,Computational Biology ,Gene Expression Regulation, Developmental ,DNA binding site ,Enhancer Elements, Genetic ,Regulatory sequence ,Insect Proteins ,Drosophila ,General Agricultural and Biological Sciences ,030217 neurology & neurosurgery ,Software ,Research Article ,Developmental Biology ,Protein Binding ,Transcription Factors - Abstract
A new computational method uses gene expression databases and transcription factor binding specificities to describe regulatory elements in the Drosophila A/P patterning network in unprecedented detail., Cis-regulatory modules that drive precise spatial-temporal patterns of gene expression are central to the process of metazoan development. We describe a new computational strategy to annotate genomic sequences based on their “pattern generating potential” and to produce quantitative descriptions of transcriptional regulatory networks at the level of individual protein-module interactions. We use this approach to convert the qualitative understanding of interactions that regulate Drosophila segmentation into a network model in which a confidence value is associated with each transcription factor-module interaction. Sequence information from multiple Drosophila species is integrated with transcription factor binding specificities to determine conserved binding site frequencies across the genome. These binding site profiles are combined with transcription factor expression information to create a model to predict module activity patterns. This model is used to scan genomic sequences for the potential to generate all or part of the expression pattern of a nearby gene, obtained from available gene expression databases. Interactions between individual transcription factors and modules are inferred by a statistical method to quantify a factor's contribution to the module's pattern generating potential. We use these pattern generating potentials to systematically describe the location and function of known and novel cis-regulatory modules in the segmentation network, identifying many examples of modules predicted to have overlapping expression activities. Surprisingly, conserved transcription factor binding site frequencies were as effective as experimental measurements of occupancy in predicting module expression patterns or factor-module interactions. Thus, unlike previous module prediction methods, this method predicts not only the location of modules but also their spatial activity pattern and the factors that directly determine this pattern. As databases of transcription factor specificities and in vivo gene expression patterns grow, analysis of pattern generating potentials provides a general method to decode transcriptional regulatory sequences and networks., Author Summary The developmental program specifying segmentation along the anterior-posterior axis of the Drosophila embryo is one of the best studied examples of transcriptional regulatory networks. Previous work has identified the location and function of dozens of DNA segments called cis-regulatory “modules” that regulate several genes in precise spatial patterns in the early embryo. In many cases, transcription factors that interact with such modules have also been identified. We present a novel computational framework that turns a qualitative and fragmented understanding of modules and factor-module interactions into a quantitative, systems-level view. The formalism utilizes experimentally characterized binding specificities of transcription factors and gene expression patterns to describe how multiple transcription factors (working as activators or repressors) act together in a module to determine its regulatory activity. This formalism can explain the expression patterns of known modules, infer factor-module interactions and quantify the potential of an arbitrary DNA segment to drive a gene's expression. We have also employed databases of gene expression patterns to find novel modules of the regulatory network. As databases of binding motifs and gene expression patterns grow, this new approach provides a general method to decode transcriptional regulatory sequences and networks.
- Published
- 2010
31. Characterization ofIMP-E3, A gene active during imaginal disc morphogenesis inDrosophila melanogaster
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John T. Moore, James W. Fristrom, Dianne Fristrom, and Ann S. Hammonds
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Signal peptide ,Transcription, Genetic ,Molecular Sequence Data ,Restriction Mapping ,Morphogenesis ,chemistry.chemical_compound ,Drosophilidae ,Genetics ,Animals ,Drosophila Proteins ,Amino Acid Sequence ,Regulation of gene expression ,Base Sequence ,biology ,Imaginal disc morphogenesis ,Cell Biology ,biology.organism_classification ,Molecular biology ,Imaginal disc ,Drosophila melanogaster ,Ecdysterone ,Gene Expression Regulation ,Genes ,chemistry ,Insect Hormones ,Poly A ,Ecdysone ,Developmental Biology - Abstract
The steroid hormone 20-hydroxyecdysone (20-HE) induces imaginal discs to form adult appendages in Drosophila. We have isolated a set of six ecdysone-responsive genes that apparently encode disc cell-surface or secreted proteins. Transcripts from one of these genes, IMP-E3, accumulate rapidly within 1-2 h in response to hormone. Developmentally, IMP-E3 transcripts reach maximum levels during the first stages of metamorphosis (white prepupae, WPP) and are primarily limited to imaginal tissues. Transcripts are also present during embryogenesis (0-3 h and 12-18 h). Two different-sized transcripts (1.2 and 1.4 kb) result from differential polyadenylation, with the larger transcript predominating in WPP. The conceptual IMP-E3 protein contains a signal peptide, an RGD sequence, and a potential glycosylphosphatidylinositol anchor. We speculate that the protein provides a transient cue important for imaginal disc morphogenesis.
- Published
- 1990
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32. Comparative Analysis of Spatial Patterns of Gene Expression in Drosophila melanogaster Imaginal Discs
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Parvez Ahammad, Susan E. Celniker, Richard Weiszmann, S. Shankar Sastry, Gerald M. Rubin, Cyrus L. Harmon, and Ann S. Hammonds
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Genetics ,Imaginal disc ,Microarray analysis techniques ,Gene expression ,Pair-rule gene ,Spatial ecology ,Computational biology ,Biology ,Drosophila melanogaster ,biology.organism_classification ,Gene ,Expression (mathematics) - Abstract
Determining the precise spatial extent of expression of genes across different tissues, along with knowledge of the biochemical function of the genes is critical for understanding the roles of various genes in the development of metazoan organisms. To address this problem, we have developed high-throughput methods for generating images of gene expression in Drosophila melanogaster imaginal discs and for the automated analysis of these images. Our method automatically learns tissue shapes from a small number of manually segmented training examples and automatically aligns, extracts and scores new images, which are analyzed to generate gene expression maps for each gene. We have developed a reverse lookup procedure that enables us to identify genes that have spatial expression patterns most similar to a given gene of interest. Our methods enable us to cluster both the genes and the pixels that of the maps, thereby identifying sets of genes that have similar patterns, and regions of the tissues of interest that have similar gene expression profiles across a large number of genes.
- Published
- 2007
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33. Joint Nonparametric Alignment for Analyzing Spatial Gene Expression Patterns in Drosophila Imaginal Discs
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Cyrus L. Harmon, Gerald M. Rubin, Ann S. Hammonds, S. Shankar Sastry, and Parvez Ahammad
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Computer science ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Image noise ,Nonparametric statistics ,Unsupervised learning ,Pattern recognition ,Segmentation ,Computer vision ,Image segmentation ,Artificial intelligence ,business ,Measure (mathematics) - Abstract
To compare spatial patterns of gene expression, one must analyze a large number of images as current methods are only able to measure a small number of genes at a time. Bringing images of corresponding tissues into alignment is a critical first step in making a meaningful comparative analysis of these spatial patterns. Significant image noise and variability in the shapes make it hard to pick a canonical shape model. In this paper, we address these problems by combining segmentation and unsupervised shape learning algorithms. We first segment images to acquire structures of interest, then jointly align the shapes of these acquired structures using an unsupervised nonparametric maximum likelihood algorithm along the lines of 'congealing' (E. G. Miller et al., 2000), while simultaneously learning the underlying shape model and associated transformations. The learned transformations are applied to corresponding images to bring them into alignment in one step. We demonstrate the results for images of various classes of Drosophila imaginal discs and discuss the methodology used for a quantitative analysis of spatial gene expression patterns.
- Published
- 2005
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34. The Drosophila Stubble-stubbloid gene encodes an apparent transmembrane serine protease required for epithelial morphogenesis
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Dianne Fristrom, James C. Garbe, James W. Fristrom, Mary Prout, Ann S. Hammonds, Robin Abu-Shumays, and Laurel F. Appel
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Embryo, Nonmammalian ,Transcription, Genetic ,medicine.medical_treatment ,Molecular Sequence Data ,Morphogenesis ,Genes, Recessive ,Biology ,Protein Sorting Signals ,Cell membrane ,Chromosome Walking ,medicine ,Extracellular ,Animals ,Drosophila Proteins ,Amino Acid Sequence ,Cloning, Molecular ,Genes, Dominant ,Serine protease ,Multidisciplinary ,Protease ,Base Sequence ,Sequence Homology, Amino Acid ,C-terminus ,Cell Membrane ,Serine Endopeptidases ,Pupa ,Membrane Proteins ,Epithelial Cells ,DNA ,Blotting, Northern ,Molecular biology ,Transmembrane protein ,Cell biology ,Imaginal disc ,medicine.anatomical_structure ,Drosophila melanogaster ,Larva ,biology.protein ,RNA ,Research Article - Abstract
The Stubble-stubbloid (Sb-sbd) gene is required for hormone-dependent epithelial morphogenesis of imaginal discs of Drosophila, including the formation of bristles, legs, and wings. The gene has been cloned by using Sb-sbd-associated DNA lesions in a 20-kilobase (kb) region of a 263-kb genomic walk. The region specifies an approximately 3.8-kb transcript that is induced by the steroid hormone 20-hydroxyecdysone in imaginal discs cultured in vitro. The conceptually translated protein is an apparent 786-residue type II transmembrane protein (N terminus in, C terminus out), including an intracellular N-terminal domain of at least 35 residues and an extracellular C-terminal trypsin-like serine protease domain of 244 residues. Sequence analyses indicate that the Sb-sbd-encoded protease could activate itself by proteolytic cleavage. Consistent with the cell-autonomous nature of the Sb-sbd bristle phenotype, a disulfide bond between cysteine residues in the noncatalytic N-terminal fragment and the C-terminal catalytic fragment could tether the protease to the membrane after activation. Both dominant Sb and recessive sbd mutations affect the organization of microfilament bundles during bristle morphogenesis. We propose that the Sb-sbd product has a dual function. (i) It acts through its proteolytic extracellular domain to detach imaginal disc cells from extracellular matrices, and (ii) it transmits an outside-to-inside signal to its intracellular domain to modify the cytoskeleton and facilitate cell shape changes underlying morphogenesis.
- Published
- 1993
35. Systematic image-driven analysis of the spatial Drosophila embryonic expression landscape
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Ann S. Hammonds, Susan E. Celniker, and Erwin Frise
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Time Factors ,Systems biology ,Gene regulatory network ,embryo ,Computational biology ,Biology ,General Biochemistry, Genetics and Molecular Biology ,Article ,03 medical and health sciences ,0302 clinical medicine ,Fate mapping ,Databases, Genetic ,Computer Graphics ,Animals ,Cluster Analysis ,Drosophila Proteins ,Gene Regulatory Networks ,biological function ,030304 developmental biology ,Regulation of gene expression ,Genetics ,0303 health sciences ,General Immunology and Microbiology ,Applied Mathematics ,Systems Biology ,Gene Expression Regulation, Developmental ,Signal Processing, Computer-Assisted ,Markov Random Field ,Expression (mathematics) ,Multicellular organism ,Computational Theory and Mathematics ,Spatial ecology ,gene expression ,Drosophila ,in situ hybridization ,General Agricultural and Biological Sciences ,030217 neurology & neurosurgery ,Drosophila Protein ,Information Systems - Abstract
We created innovative virtual representation for our large scale Drosophila insitu expression dataset. We aligned an elliptically shaped mesh comprised of small triangular regions to the outline of each embryo. Each triangle defines a unique location in the embryo and comparing corresponding triangles allows easy identification of similar expression patterns. The virtual representation was used to organize the expression landscape at stage 4-6. We identified regions with similar expression in the embryo and clustered genes with similar expression patterns. We created algorithms to mine the dataset for adjacent non-overlapping patterns and anti-correlated patterns. We were able to mine the dataset to identify co-expressed and putative interacting genes. Using co-expression we were able to assign putative functions to unknown genes., Analyzing both temporal and spatial gene expression is essential for understanding development and regulatory networks of multicellular organisms. Interacting genes are commonly expressed in overlapping or adjacent domains. Thus, gene expression patterns can be used to assign putative gene functions and mined to infer candidates for networks. We have generated a systematic two-dimensional mRNA expression atlas profiling embryonic development of Drosophila melanogaster (Tomancak et al, 2002, 2007). To date, we have collected over 70 000 images for over 6000 genes. To explore spatial relationships between gene expression patterns, we used a novel computational image-processing approach by converting expression patterns from the images into virtual representations (Figure 1). Using a custom-designed automated pipeline, for each image, we segmented and aligned the outline of the embryo to an elliptically shaped mesh, comprised of 311 small triangular regions each defining a unique location within the embryo. By comparing corresponding triangles, we produced a distance score to identify similar patterns. We generated those triangulated images (TIs) for our entire data set at all developmental stages and demonstrated that this representation can be used as for objective computationally defined description for expression in in situ hybridization images from various sources, including images from the literature. We used the TIs to conduct a comprehensive analysis of the expression landscape. To this end, we created a novel approach to temporally sort and compact TIs to a non-redundant data set suitable for further computational processing. Although generally applicable for all developmental stages, for this study, we focused on developmental stages 4–6. For this stage range, we reduced the initial set of about 5800 TIs to 553 TIs containing 364 genes. Using this filtered data set, to discover how expression subdivides the embryo into regions, we clustered areas with similar expression and demonstrated that expression patterns divide the early embryo into distinct spatial regions resembling a fate map (Figure 3). To discover the range of unique expression patterns, we used affinity propagation clustering (Frey and Dueck, 2007) to group TIs with similar patterns and identified 39 clusters each representing a distinct pattern class. We integrated the remaining genes into the 39 clusters and studied the distribution of expression patterns and the relationships between the clusters. The clustered expression patterns were used to identify putative positive and negative regulatory interactions. The similar TIs in each cluster not only grouped already known genes with related functions, but previously undescribed genes. A comparative analysis identified subtle differences between the genes within each expression cluster. To investigate these differences, we developed a novel Markov Random Field (MRF) segmentation algorithm to extract patterns. We then extended the MRF algorithm to detect shared expression boundaries, generate similarity measurements, and discriminate even faint/uncertain patterns between two TIs. This enabled us to identify more subtle partial expression pattern overlaps and adjacent non-overlapping patterns. For example, by conducting this analysis on the cluster containing the gene snail, we identified the previously known huckebein, which restricts snail expression (Reuter and Leptin, 1994), and zfh1, which interacts with tinman (Broihier et al, 1998; Su et al, 1999). By studying the functions of known genes, we assigned putative developmental roles to each of the 39 clusters. Of the 1800 genes investigated, only half of them had previously assigned functions. Representing expression patterns with geometric meshes facilitates the analysis of a complex process involving thousands of genes. This approach is complementary to the cellular resolution 3D atlas for the Drosophila embryo (Fowlkes et al, 2008). Our method can be used as a rapid, fully automated, high-throughput approach to obtain a map of co-expression, which will serve to select specific genes for detailed multiplex in-situ hybridization and confocal analysis for a fine-grain atlas. Our data are similar to the data in the literature, and research groups studying reporter constructs, mutant animals, or orthologs can easily produce in situ hybridizations. TIs can be readily created and provide representations that are both comparable to each other and our data set. We have demonstrated that our approach can be used for predicting relationships in regulatory and developmental pathways., Discovery of temporal and spatial patterns of gene expression is essential for understanding the regulatory networks and development in multicellular organisms. We analyzed the images from our large-scale spatial expression data set of early Drosophila embryonic development and present a comprehensive computational image analysis of the expression landscape. For this study, we created an innovative virtual representation of embryonic expression patterns using an elliptically shaped mesh grid that allows us to make quantitative comparisons of gene expression using a common frame of reference. Demonstrating the power of our approach, we used gene co-expression to identify distinct expression domains in the early embryo; the result is surprisingly similar to the fate map determined using laser ablation. We also used a clustering strategy to find genes with similar patterns and developed new analysis tools to detect variation within consensus patterns, adjacent non-overlapping patterns, and anti-correlated patterns. Of the 1800 genes investigated, only half had previously assigned functions. The known genes suggest developmental roles for the clusters, and identification of related patterns predicts requirements for co-occurring biological functions.
- Published
- 2010
36. Dynamic reprogramming of chromatin accessibility during Drosophila embryo development
- Author
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Ann S. Hammonds, Mark D. Biggin, William W. Fisher, Xiao Yong Li, John A. Stamatoyannopoulos, Sean Thomas, Theresa K. Canfield, Erika Giste, Richard Sandstrom, Susan E. Celniker, Peter J. Sabo, and Robert E. Thurman
- Subjects
Chromatin Immunoprecipitation ,Genome, Insect ,Embryonic Development ,Biology ,Chromatin remodeling ,03 medical and health sciences ,0302 clinical medicine ,Animals ,Deoxyribonuclease I ,Drosophila Proteins ,Blastoderm ,Scaffold/matrix attachment region ,Promoter Regions, Genetic ,ChIA-PET ,030304 developmental biology ,Body Patterning ,Genetics ,0303 health sciences ,Research ,Gene Expression Regulation, Developmental ,Promoter ,Genomics ,Chromatin ,Cell biology ,Drosophila melanogaster ,Genetic Loci ,Female ,Developmental biology ,Chromatin immunoprecipitation ,030217 neurology & neurosurgery ,Developmental Biology ,Transcription Factors - Abstract
Background The development of complex organisms is believed to involve progressive restrictions in cellular fate. Understanding the scope and features of chromatin dynamics during embryogenesis, and identifying regulatory elements important for directing developmental processes remain key goals of developmental biology. Results We used in vivo DNaseI sensitivity to map the locations of regulatory elements, and explore the changing chromatin landscape during the first 11 hours of Drosophila embryonic development. We identified thousands of conserved, developmentally dynamic, distal DNaseI hypersensitive sites associated with spatial and temporal expression patterning of linked genes and with large regions of chromatin plasticity. We observed a nearly uniform balance between developmentally up- and down-regulated DNaseI hypersensitive sites. Analysis of promoter chromatin architecture revealed a novel role for classical core promoter sequence elements in directing temporally regulated chromatin remodeling. Another unexpected feature of the chromatin landscape was the presence of localized accessibility over many protein-coding regions, subsets of which were developmentally regulated or associated with the transcription of genes with prominent maternal RNA contributions in the blastoderm. Conclusions Our results provide a global view of the rich and dynamic chromatin landscape of early animal development, as well as novel insights into the organization of developmentally regulated chromatin features.
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