Author
Listed:
- Beatriz Estrada
- Sung E Choe
- Stephen S Gisselbrecht
- Sebastien Michaud
- Lakshmi Raj
- Brian W Busser
- Marc S Halfon
- George M Church
- Alan M Michelson
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.Synopsis: Animal development requires cells in complex organs to acquire distinct identities. During the development of the body wall musculature of the fruit fly, a pool of apparently identical cells gives rise to two types of muscle precursors, both of which are required for the appearance of functioning muscles. These identities depend on broad programs of gene expression. The authors attempt to dissect the complements of expressed genes that define these two different cell types by integrating modern methods in genetics, genomics, and informatics. By purifying informative cells from normal embryos and mutants that perturb muscle development, assaying their genomewide gene expression programs, and combining experiments statistically, they have identified fivefold more founder-specific genes than were previously suspected to characterize this cell type. The expression patterns of hundreds of genes were examined in whole embryos to test the statistical predictions, permitting the authors to estimate how many more cell type–specific genes remain to be discovered. Finally, dozens of the genes highlighted by these methods were tested for direct involvement in muscle development, and several new players in this process are reported. The integrated strategy used here can be generalized for studying genetic programs in other complex tissues.
Suggested Citation
Beatriz Estrada & Sung E Choe & Stephen S Gisselbrecht & Sebastien Michaud & Lakshmi Raj & Brian W Busser & Marc S Halfon & George M Church & Alan M Michelson, 2006.
"An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes,"
PLOS Genetics, Public Library of Science, vol. 2(2), pages 1-12, February.
Handle:
RePEc:plo:pgen00:0020016
DOI: 10.1371/journal.pgen.0020016
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Citations
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Cited by:
- Clive H Glover & Michael Marin & Connie J Eaves & Cheryl D Helgason & James M Piret & Jennifer Bryan, 2006.
"Meta-Analysis of Differentiating Mouse Embryonic Stem Cell Gene Expression Kinetics Reveals Early Change of a Small Gene Set,"
PLOS Computational Biology, Public Library of Science, vol. 2(11), pages 1-12, November.
- Anastasia A Samsonova & Mahesan Niranjan & Steven Russell & Alvis Brazma, 2007.
"Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster,"
PLOS Computational Biology, Public Library of Science, vol. 3(7), pages 1-13, July.
- Han Yan & Kavitha Venkatesan & John E Beaver & Niels Klitgord & Muhammed A Yildirim & Tong Hao & David E Hill & Michael E Cusick & Norbert Perrimon & Frederick P Roth & Marc Vidal, 2010.
"A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster,"
PLOS ONE, Public Library of Science, vol. 5(8), pages 1-11, August.
- Jen-Tsan Chi & Edwin H Rodriguez & Zhen Wang & Dimitry S A Nuyten & Sayan Mukherjee & Matt van de Rijn & Marc J van de Vijver & Trevor Hastie & Patrick O Brown, 2007.
"Gene Expression Programs of Human Smooth Muscle Cells: Tissue-Specific Differentiation and Prognostic Significance in Breast Cancers,"
PLOS Genetics, Public Library of Science, vol. 3(9), pages 1-15, September.
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