AutoClone: automatic analysis of genetic labelling data and clonality assessment

The clonality assessment is a technique used to evaluate the similarity of cells/fibers based on their color profiles. It is taking advantage of multi-color systems generally used for fate mapping and lineage tracing strategies upon biological processes such as development and regeneration. Among those systems, the "Brainbow" mouse consists of the stochastic multi-color labeling of neuronal cells [1]. This technique relies on the Cre-Lox recombination system that allows the combination of multiple fluorophores within the cell of interest. Subsequently, this technique has been adapted to several other tissues and model organisms such as the Rainbow (for a variety of mice/mammalian tissues) [2], Flybow (for neural circuit analysis in Drosophila melanogaster) [3], CLoNe (for different tissues and species of mouse and chick) [4], and Zebrabow (for different zebrafish organs and tissues) [5]. Importantly, the Zebrabow system has been key in uncovering muscle stem cell dynamics upon growth and regeneration, through the concept of clonality. Tissue-resident stem cells have the capacity to self-renew and give rise to progenies committed to terminal differentiation. Upon their expansion, these cells will generate clones that are believed to share some genetic features, such as the initial color they have been attributed. In order to identify cells coming from a common progenitor, one has to be able to distinguish them from the randomly distributed ones. One of the important aspects of multi-colored lineage tracing systems is the quantification and statistical evaluation of the results (i.e. converting visual colors to interpretable statistics). In this regard, several methods have been proposed so far for color quantification and clonality assessment [6, 7]. Nguyen and Currie in a Methods paper [8] proposed a novel approach for quantifying the clonality and assessing multiple color profiles of clones, which enables the simultaneous comparison of the clonality of several clusters of cells/fibers. This approach works based on the translation of color values, such as Hue and Saturation, to trigonometric points with X and Y coordinates. Accordingly, to statistically evaluate the color similarity between individual clones, distances between two points (equivalent to cell or fiber) are calculated. While a high distance value between two points indicates a stochastic profile, a low mean distance corresponds to a clonal profile. In this approach, the three-channel (HSL) profile of the clones is converted to a 2D space color wheel. However, it is possible to maintain all three channels and convert the HSL to a 3D space color profile (i.e. converting Hue, Saturation, and Lightness values, to obtain X, Y, and Z coordinates). The following figures [9] illustrate how colors could be transformed into coordinates in a 2D or 3D space. The AutoClone web app implements both of these approaches, namely 2D and 3D color space-based coordinate measurement, to perform clonality assessment in three different modes which are illustrated in the right-hand side figure and are explained in the following three boxes.