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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 compu...

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Autores principales: Estrada, Beatriz, Choe, Sung E, Gisselbrecht, Stephen S, Michaud, Sebastien, Raj, Lakshmi, Busser, Brian W, Halfon, Marc S, Church, George M, Michelson, Alan M
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1366495/
https://www.ncbi.nlm.nih.gov/pubmed/16482229
http://dx.doi.org/10.1371/journal.pgen.0020016
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author Estrada, Beatriz
Choe, Sung E
Gisselbrecht, Stephen S
Michaud, Sebastien
Raj, Lakshmi
Busser, Brian W
Halfon, Marc S
Church, George M
Michelson, Alan M
author_facet Estrada, Beatriz
Choe, Sung E
Gisselbrecht, Stephen S
Michaud, Sebastien
Raj, Lakshmi
Busser, Brian W
Halfon, Marc S
Church, George M
Michelson, Alan M
author_sort Estrada, Beatriz
collection PubMed
description 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.
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spelling pubmed-13664952006-02-21 An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes Estrada, Beatriz Choe, Sung E Gisselbrecht, Stephen S Michaud, Sebastien Raj, Lakshmi Busser, Brian W Halfon, Marc S Church, George M Michelson, Alan M PLoS Genet Research Article 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. Public Library of Science 2006-02 2006-02-17 /pmc/articles/PMC1366495/ /pubmed/16482229 http://dx.doi.org/10.1371/journal.pgen.0020016 Text en © 2006 Estrada et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Estrada, Beatriz
Choe, Sung E
Gisselbrecht, Stephen S
Michaud, Sebastien
Raj, Lakshmi
Busser, Brian W
Halfon, Marc S
Church, George M
Michelson, Alan M
An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes
title An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes
title_full An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes
title_fullStr An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes
title_full_unstemmed An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes
title_short An Integrated Strategy for Analyzing the Unique Developmental Programs of Different Myoblast Subtypes
title_sort integrated strategy for analyzing the unique developmental programs of different myoblast subtypes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1366495/
https://www.ncbi.nlm.nih.gov/pubmed/16482229
http://dx.doi.org/10.1371/journal.pgen.0020016
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