EASI-ORC: A Pipeline for the Efficient Analysis and Segmentation of smFISH Images for Organelle-RNA Colocalization Measurements in Yeast

Abstract

Analysis of single-molecule fluorescent in situ hybridization (smFISH) images is an arduous and time-consuming task that is important to perform accurately in order to translate image data into a quantifiable format. This task becomes increasingly more difficult greater the experimental scope and number of images captured. Although smFISH is the gold standard for RNA localization measurements, there are no freely available, user-friendly applications for assaying messenger RNA localization to sub-cellular structures, like the endoplasmic reticulum (ER) or mitochondria). We have developed a pipeline that allows for the automated analysis of multiple smFISH images in yeast cells: EASI-ORC (Efficient Analysis and Segmentation of smFISH Images for Organelle-RNA Colocalization). The EASI-ORC pipeline automates the segmentation of cells and sub-cellular structures (e.g. organelles), identifies bona fide smFISH signals, and measures the level of colocalization between an organelle and mRNA signals. Importantly, EASI-ORC works in a fast, accurate, and unbiased manner that is difficult to replicate manually. It also allows for the visualization of data filtering and outputs graphical representations of the colocalization data along with statistical analysis. EASI-ORC is based on existing ImageJ plugins and original scripts, thus, allowing free access and a relative ease of use. To circumvent any technical literacy issues, a step-by-step user guide is provided. EASI-ORC offers a robust solution for smFISH image analysis for both new and experienced researchers - one that saves time and effort, as well as providing more consistent overall measurements of RNA-organelle colocalization in yeast.