INRA, Nancy Université, UMR1137 Ecologie et Ecophysiologie Forestières, IFR 110 EFABA, F-54280 Champenoux, France.
BMC Biol. 2010 Mar 4;8:18. doi: 10.1186/1741-7007-8-18.
Technological advances have enabled the accurate quantification of gene expression, even within single cell types. While transcriptome analyses are routinely performed, most experimental designs only provide snapshots of gene expression. Molecular mechanisms underlying cell fate or positional signalling have been revealed through these discontinuous datasets. However, in developing multicellular structures, temporal and spatial cues, known to directly influence transcriptional networks, get entangled as the cells are displaced and expand. Access to an unbiased view of the spatiotemporal regulation of gene expression occurring during development requires a specific framework that properly quantifies the rate of change of a property in a moving and expanding element, such as a cell or an organ segment.
We show how the rate of change in gene expression can be quantified by combining kinematics and real-time polymerase chain reaction data in a mechanistic model which considers any organ as a continuum. This framework was applied in order to assess the developmental regulation of the two reference genes Actin11 and Elongation Factor 1-beta in the apex of poplar root. The growth field was determined by time-lapse photography and transcript density was obtained at high spatial resolution. The net accumulation rates of the transcripts of the two genes were found to display highly contrasted developmental profiles. Actin11 showed pulses of up and down regulation in the accelerating and decelerating parts of the growth zone while the dynamic of EF1beta were much slower. This framework provides key information about gene regulation in a developing organ, such as the location, the duration and the intensity of gene induction/repression.
We demonstrated that gene expression patterns can be monitored using the continuity equation without using mutants or reporter constructions. Given the rise of imaging technologies, this framework in our view opens a new way to dissect the molecular basis of growth regulation, even in non-model species or complex structures.
技术进步使得即使在单个细胞类型中也能够准确地定量基因表达。虽然经常进行转录组分析,但大多数实验设计仅提供基因表达的快照。通过这些不连续的数据集,揭示了细胞命运或位置信号的分子机制。然而,在发育中的多细胞结构中,已知直接影响转录网络的时空线索随着细胞的位移和扩展而变得混乱。要获得在发育过程中发生的基因表达的时空调节的无偏视图,需要一个特定的框架,该框架可以正确地量化在移动和扩展元件(例如细胞或器官段)中发生的属性变化率。
我们展示了如何通过将运动学和实时聚合酶链反应数据结合在一个机械模型中,该模型考虑了任何器官作为一个连续体,从而定量基因表达的变化率。该框架用于评估杨树根尖中两个参考基因 Actin11 和延伸因子 1-β的发育调节。通过延时摄影确定生长场,并且以高空间分辨率获得转录密度。发现两个基因的转录物的净积累率显示出高度对比的发育曲线。Actin11 在生长区的加速和减速部分显示出上调和下调的脉冲,而 EF1beta 的动态则要慢得多。该框架提供了有关发育器官中基因调节的关键信息,例如基因诱导/抑制的位置、持续时间和强度。
我们证明可以使用连续性方程来监测基因表达模式,而无需使用突变体或报告基因构建体。考虑到成像技术的兴起,我们认为这种框架为剖析生长调节的分子基础开辟了一条新途径,即使在非模式物种或复杂结构中也是如此。