Abstract
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.
Highlights
Transcriptional regulation plays a central role in metazoan development by establishing cell-specific patterns of gene expression that represent coordinate responses to extrinsic signals and intrinsic programming [1,2]
When 123 of the predicted 276 fusion-complement myoblast (FCM) genes were examined by in situ hybridization, 18 (15%) were found to have FCM-specific expression patterns, while an additional 40 (33%) were found to be expressed in both founder cell (FC) and FCMs. These findings suggest that, while FC gene predictions derived from the present experimental design are very accurate, the hypothesized specificity of the genetic manipulations for FCM genes is confounded by genes that are expressed in both myoblast types
We have used an integrated strategy for systematically studying the development of a complex tissue by combining genetic perturbations of a particular biological process, computational analysis of a compendium of gene expression profiles that is targeted to the tissue by fluorescence activated cell sorting (FACS) purification of the cells of interest, large-scale validation of predicted gene expression patterns by whole embryo in situ hybridization, and RNA interference (RNAi)-based functional studies of newly discovered genes
Summary
Transcriptional regulation plays a central role in metazoan development by establishing cell-specific patterns of gene expression that represent coordinate responses to extrinsic signals and intrinsic programming [1,2]. Given the cellular diversity present in most tissues, it would be ideal to derive the entire genetic program of each individual cell type and to determine the response of each differentially expressed gene to perturbations of the pathways that regulate formation of that organ. Defining such cell-specific gene expression signatures and mapping the sequential steps involved in their generation are both essential to achieving a systemslevel view of development [3,4].
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