Estrada Beatriz, Choe Sung E, Gisselbrecht Stephen S, Michaud Sebastien, Raj Lakshmi, Busser Brian W, Halfon Marc S, Church George M, Michelson Alan M
Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
PLoS Genet. 2006 Feb;2(2):e16. doi: 10.1371/journal.pgen.0020016. Epub 2006 Feb 17.
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.
在理解调控特定器官形成的机制方面，一个重要但在很大程度上尚未解决的挑战是破译目标组织内多种细胞类型所展现的复杂且动态的遗传程序。在此，我们运用综合的遗传学、基因组学和计算策略，全面确定果蝇胚胎中胚层内不同成肌细胞亚群在细胞命运最初确定时的分子特征。我们针对通过流式细胞术从适当发育阶段的野生型胚胎以及12种成肌作用被选择性且可预测地干扰的基因型中纯化出的原代中胚层细胞，生成了基因表达谱汇编。基于基因表达的预期趋势以及每种基因型对已知肌肉基因检测的相对贡献，对这些汇总数据集进行统计元分析，初步将数百个差异表达基因分配到特定的成肌细胞亚型。随后使用全胚胎原位杂交来验证这些预测中的大部分，从而能够估计微阵列数据的真阳性检测率。这种综合分析表明，成肌细胞表现出比之前认识到的更大的基因表达异质性和整体复杂性。此外，它表明大量未表征且差异表达的基因参与了成肌细胞特化及随后的形态发生。这些发现还强调了产生多样成肌细胞特征需要相当大的调控特异性。最后，为了说明如何能够有效地研究新鉴定的成肌细胞基因的发育功能，我们开发了一种可在活体胚胎中评分的快速RNA干扰检测方法，并将其应用于选定的基因。这种用于检查胚胎基因表达和功能的综合策略为进一步研究这个模型发育系统提供了一个大幅扩展的框架。
