A spatial and temporal map of C. elegans gene expression
A spatial and temporal map of C. elegans gene expression
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DOI：
10.1101/gr.114595.110
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发表时间：
2011-02-01
期刊：
影响因子：
7
通讯作者：
Miller, David M., III
中科院分区：
文献类型：
--
作者：
Spencer, W. Clay;Zeller, Georg;Miller, David M., III
线虫的基因组已经完全测序，这种模式生物的发育解剖是在单细胞分辨率上描述的。在这里，我们利用这种精确定义的体系结构来将基因表达与细胞类型联系起来。我们从特定细胞和每个发育阶段获得RNA，使用组织特异性启动子标记细胞，用于FACS分离或通过mRNA标签方法提取mRNA。然后，我们使用平铺阵列生成了30多个不同细胞和发育阶段的基因表达谱。基于机器学习的分析检测到与已建立的基因模型相对应的转录本，并在非编码区发现了新的转录活性区域(TAR)，这些区域至少占线虫总基因组的10%。我们的结果表明，大约75%的可检测到表达的转录本在不同发育阶段和不同细胞类型之间存在差异表达。对已知的组织和细胞特异性转录本的检查证实了这些数据集，并表明新发现的TAR可能行使细胞特异性功能。此外，我们使用自组织映射图来定义共调控转录组，并应用调控元件分析来确定已知的转录因子和miRNA结合位点，以及可能控制这些基因亚组的新基序。通过使用细胞特异性的全基因组图谱策略，我们已经检测到了大量新的转录本，并制作了高分辨率的基因表达图谱，为建立单个基因在细胞分化中的作用提供了基础。
The C. elegans genome has been completely sequenced, and the developmental anatomy of this model organism is described at single-cell resolution. Here we utilize strategies that exploit this precisely defined architecture to link gene expression to cell type. We obtained RNAs from specific cells and from each developmental stage using tissue-specific promoters to mark cells for isolation by FACS or for mRNA extraction by the mRNA-tagging method. We then generated gene expression profiles of more than 30 different cells and developmental stages using tiling arrays. Machine-learning-based analysis detected transcripts corresponding to established gene models and revealed novel transcriptionally active regions ( TARs) in noncoding domains that comprise at least 10% of the total C. elegans genome. Our results show that about 75% of transcripts with detectable expression are differentially expressed among developmental stages and across cell types. Examination of known tissue-and cell-specific transcripts validates these data sets and suggests that newly identified TARs may exercise cell-specific functions. Additionally, we used self-organizing maps to define groups of coregulated transcripts and applied regulatory element analysis to identify known transcription factor-and miRNA-binding sites, as well as novel motifs that likely function to control subsets of these genes. By using cell-specific, whole-genome profiling strategies, we have detected a large number of novel transcripts and produced high-resolution gene expression maps that provide a basis for establishing the roles of individual genes in cellular differentiation.