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Alan M Michelson

Publications and source records attributed to Alan M Michelson.

10 recordsLinked to original sources
PubMed2006

Expression-guided in silico evaluation of candidate cis regulatory codes for Drosophila muscle founder cells.

While combinatorial models of transcriptional regulation can be inferred for metazoan systems from a priori biological knowledge, validation requires extensive and time-consuming experimental work. Thus, there is a need for computational methods that can evaluate hypothesized cis regulatory codes before the difficult task of experimental verification is undertaken. We have developed a novel computational framework (termed "CodeFinder") that integrates transcription factor binding site and gene expression information to evaluate whether a hypothesized transcriptional regulatory model (TRM; i.e., a set of co-regulating transcription factors) is likely to target a given set of co-expressed genes. Our basic approach is to simultaneously predict cis regulatory modules (CRMs) associated with a given gene set and quantify the enrichment for combinatorial subsets of transcription factor binding site motifs comprising the hypothesized TRM within these predicted CRMs. As a model system, we have examined a TRM experimentally demonstrated to drive the expression of two genes in a sub-population of cells in the developing Drosophila mesoderm, the somatic muscle founder cells. This TRM was previously hypothesized to be a general mode of regulation for genes expressed in this cell population. In contrast, the present analyses suggest that a modified form of this cis regulatory code applies to only a subset of founder cell genes, those whose gene expression responds to specific genetic perturbations in a similar manner to the gene on which the original model was based. We have confirmed this hypothesis by experimentally discovering six (out of 12 tested) new CRMs driving expression in the embryonic mesoderm, four of which drive expression in founder cells.

Amino Acid Motifs↗
PubMed2006

An integrated strategy for analyzing the unique developmental programs of different myoblast subtypes.

An important but largely unmet challenge in understanding the mechanisms that govern the formation of specific organs is to decipher the complex and dynamic genetic programs exhibited by the diversity of cell types within the tissue of interest. Here, we use an integrated genetic, genomic, and computational strategy to comprehensively determine the molecular identities of distinct myoblast subpopulations within the Drosophila embryonic mesoderm at the time that cell fates are initially specified. A compendium of gene expression profiles was generated for primary mesodermal cells purified by flow cytometry from appropriately staged wild-type embryos and from 12 genotypes in which myogenesis was selectively and predictably perturbed. A statistical meta-analysis of these pooled datasets--based on expected trends in gene expression and on the relative contribution of each genotype to the detection of known muscle genes--provisionally assigned hundreds of differentially expressed genes to particular myoblast subtypes. Whole embryo in situ hybridizations were then used to validate the majority of these predictions, thereby enabling true-positive detection rates to be estimated for the microarray data. This combined analysis reveals that myoblasts exhibit much greater gene expression heterogeneity and overall complexity than was previously appreciated. Moreover, it implicates the involvement of large numbers of uncharacterized, differentially expressed genes in myogenic specification and subsequent morphogenesis. These findings also underscore a requirement for considerable regulatory specificity for generating diverse myoblast identities. Finally, to illustrate how the developmental functions of newly identified myoblast genes can be efficiently surveyed, a rapid RNA interference assay that can be scored in living embryos was developed and applied to selected genes. This integrated strategy for examining embryonic gene expression and function provides a substantially expanded framework for further studies of this model developmental system.

Animals↗
PubMed2005

Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset.

BACKGROUND: As more methods are developed to analyze RNA-profiling data, assessing their performance using control datasets becomes increasingly important. RESULTS: We present a 'spike-in' experiment for Affymetrix GeneChips that provides a defined dataset of 3,860 RNA species, which we use to evaluate analysis options for identifying differentially expressed genes. The experimental design incorporates two novel features. First, to obtain accurate estimates of false-positive and false-negative rates, 100-200 RNAs are spiked in at each fold-change level of interest, ranging from 1.2 to 4-fold. Second, instead of using an uncharacterized background RNA sample, a set of 2,551 RNA species is used as the constant (1x) set, allowing us to know whether any given probe set is truly present or absent. Application of a large number of analysis methods to this dataset reveals clear variation in their ability to identify differentially expressed genes. False-negative and false-positive rates are minimized when the following options are chosen: subtracting nonspecific signal from the PM probe intensities; performing an intensity-dependent normalization at the probe set level; and incorporating a signal intensity-dependent standard deviation in the test statistic. CONCLUSIONS: A best-route combination of analysis methods is presented that allows detection of approximately 70% of true positives before reaching a 10% false-discovery rate. We highlight areas in need of improvement, including better estimate of false-discovery rates and decreased false-negative rates.

Algorithms↗
PubMed2003

Running interference for hedgehog signaling.

The new technology of RNA interference (RNAi) is allowing high-throughput screening of cells to examine many biological processes. Michelson discusses one such system in which the Drosophila Hedgehog (Hh) pathway was analyzed by systematic genome-wide RNAi analysis. The results not only suggest unexpected overlap in the Hh and Wingless (Wg) pathways, but also provide proof of principle for the development of high-throughput assays using RNAi techniques.

Animals↗
PubMed2002

Exploring genetic regulatory networks in metazoan development: methods and models.

One of the foremost challenges of 21st century biological research will be to decipher the complex genetic regulatory networks responsible for embryonic development. The recent explosion of whole genome sequence data and of genome-wide transcriptional profiling methods, such as microarrays, coupled with the development of sophisticated computational tools for exploiting and analyzing genomic data, provide a significant starting point for regulatory network analysis. In this article we review some of the main methodological issues surrounding genome annotation, transcriptional profiling, and computational prediction of cis-regulatory elements and discuss how the power of model genetic organisms can be used to experimentally verify and extend the results of genomic research.

Animals↗
PubMed2002

Reciprocal regulatory interactions between the Notch and Ras signaling pathways in the Drosophila embryonic mesoderm.

Convergent intercellular signals must be precisely integrated in order to elicit specific biological responses. During specification of muscle and cardiac progenitors from clusters of equivalent cells in the Drosophila embryonic mesoderm, the Ras/MAPK pathway--activated by both epidermal and fibroblast growth factor receptors--functions as an inductive cellular determination signal, while lateral inhibition mediated by Notch antagonizes this activity. A critical balance between these signals must be achieved to enable one cell of an equivalence group to segregate as a progenitor while its neighbors assume a nonprogenitor identity. We have investigated whether these opposing signals directly interact with each other, and we have examined how they are integrated by the responding cells to specify their unique fates. Our findings reveal that Ras and Notch do not function independently; rather, we have uncovered several modes of cross-talk between these pathways. Ras induces Notch, its ligand Delta, and the epidermal growth factor receptor antagonist, Argos. We show that Delta and Argos then synergize to nonautonomously block a positive autoregulatory feedback loop that amplifies a fate-inducing Ras signal. This feedback loop is characterized by Ras-mediated upregulation of proximal components of both the epidermal and fibroblast growth factor receptor pathways. In turn, Notch activation in nonprogenitors induces its own expression and simultaneously suppresses both Delta and Argos levels, thereby reinforcing a unidirectional inhibitory response. These reciprocal interactions combine to generate the signal thresholds that are essential for proper specification of progenitors and nonprogenitors from groups of initially equivalent cells.

Animals↗
PubMed2002

Identification of a novel cis-regulatory element involved in the heat shock response in Caenorhabditis elegans using microarray gene expression and computational methods.

We report here the identification of a previously unknown transcription regulatory element for heat shock (HS) genes in Caenorhabditis elegans. We monitored the expression pattern of 11,917 genes from C. elegans to determine the genes that were up-regulated on HS. Twenty eight genes were observed to be consistently up-regulated in several different repetitions of the experiments. We analyzed the upstream regions of these genes using computational DNA pattern recognition methods. Two potential cis-regulatory motifs were identified in this way. One of these motifs (TTCTAGAA) was the DNA binding motif for the heat shock factor (HSF), whereas the other (GGGTGTC) was previously unreported in the literature. We determined the significance of these motifs for the HS genes using different statistical tests and parameters. Comparative sequence analysis of orthologous HS genes from C. elegans and Caenorhabditis briggsae indicated that the identified DNA regulatory motifs are conserved across related species. The role of the identified DNA sites in regulation of HS genes was tested by in vitro mutagenesis of a green fluorescent protein (GFP) reporter transgene driven by the C. elegans hsp-16-2 promoter. DNA sites corresponding to both motifs are shown to play a significant role in up-regulation of the hsp-16-2 gene on HS. This is one of the rare instances in which a novel regulatory element, identified using computational methods, is shown to be biologically active. The contributions of individual sites toward induction of transcription on HS are nonadditive, which indicates interaction and cross-talk between the sites, possibly through the transcription factors (TFs) binding to these sites.

Animals↗