Review: Harnessing the power of gene regulatory networks for crop improvement

The number of large molecular plant datasets seems to be growing exponentially. With this growth comes an urgent need for researchers to understand how these datasets should be analyzed and integrated to get accurate understandings of what they represent. This fine article by Leong et al. is a good place to start. Trying to build a model of gene regulatory networks is challenging when the data available are limited and inconsistent. For example, many studies look at transcriptional time courses following a stimulus, but a course time series can miss critical short-lived events. Furthermore, mRNA levels are not tightly correlated with protein levels or even protein function, yet we often interpret them in this way. Another challenge lies in integrating datasets across species boundaries. The authors describe several considerations and strategies for identifying and analyzing gene regulatory networks, including a discussion on how these findings can be applied to improve crops through genome editing and synthetic biology approaches. (Summary by Mary Williams @PlantTeaching.bsky.social) Nature Biotechnol. 10.1038/s41587-025-02727-4