Iterative subtraction facilitates automated, quantitative analysis of multiple pollen tube growth features.

In flowering plants, successful reproduction and generation of seed depends on the delivery of immotile sperm to female gametes via the pollen tube. As reproduction in flowering plants is the cornerstone of our agricultural industry, there is a need to uncover the genes, small molecules, and environmental conditions that affect pollen tube growth dynamics. However, methods for measuring pollen tube phenotypes are labor intensive, and suffer from a tradeoff between workload and resolution. To approach these problems, we use an image analysis technique called Automated Stack Iterative Subtraction (ASIST). Our tool converts growing pollen tube tips into closed particles, making the automated simultaneous extraction of multiple pollen tube phenotypes from hundreds of individual cells tractable via existing particle identification technology. Here we use our tool to analyze growth dynamics of pollen tubes in vitro, and semi in vivo. We show that ASIST provides a framework for robust, high throughput analysis of pollen tube growth behaviors in populations of cells, thus facilitating pollen tube phenomics.