资源环境科技发展态势分析平台

The stem cell niche and the size of the root meristem in plants are maintained by intercellular interactions and signalling networks involving a peptide hormone, root meristem growth factor 1 (RGF1)(1). Understanding how RGF1 regulates the development of the root meristem is essential for understanding stem cell function. Although five receptors for RGF1 have been identified(2-4), the downstream signalling mechanism remains unknown. Here we report a series of signalling events that follow RGF1 activity. We find that the RGF1-receptor pathway controls the distribution of reactive oxygen species (ROS) along the developmental zones of the Arabidopsis root. We identify a previously uncharacterized transcription factor, RGF1-INDUCIBLE TRANSCRIPTION FACTOR 1 (RITF1), that has a central role in mediating RGF1 signalling. Manipulating RITF1 expression leads to the redistribution of ROS along the root developmental zones. Changes in ROS distribution in turn enhance the stability of the PLETHORA2 protein, a master regulator of root stem cells. Our results thus clearly depict a signalling cascade that is initiated by RGF1, linking this peptide to mechanisms that regulate ROS.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.