MitoTrack, a user-friendly semi-automatic software for lineage tracking in living embryos

Abstract Motivation During development, progenitor cells undergo multiple rounds of cellular divisions during which transcriptional programs must be faithfully propagated. Investigating the timing of transcriptional activation, which is a highly stochastic phenomenon, requires the analysis of large amounts of data. In order to perform automatic image analysis of transcriptional activation, we developed a software that segments and tracks both small and large objects, leading the user from raw data up to the results in their final form. Results MitoTrack is a user-friendly open-access integrated software that performs the specific dual task of reporting the precise timing of transcriptional activation while keeping lineage tree history for each nucleus of a living developing embryo. The software works automatically but provides the possibility to easily supervise, correct and validate each step. Availability and implementation MitoTrack is an open source Python software, embedded within a graphical user interface (download here). Supplementary information Supplementary data are available at Bioinformatics online.

[1]  Edouard Bertrand,et al.  A Growing Toolbox to Image Gene Expression in Single Cells: Sensitive Approaches for Demanding Challenges. , 2018, Molecular cell.

[2]  Léo Guignard,et al.  Multi-view light-sheet imaging and tracking with the MaMuT software reveals the cell lineage of a direct developing arthropod limb , 2018, eLife.

[3]  Emmanuelle Gouillart,et al.  scikit-image: image processing in Python , 2014, PeerJ.

[4]  Ovidiu Radulescu,et al.  Transcriptional Memory in the Drosophila Embryo , 2017, Mechanisms of Development.

[5]  Johannes Schindelin,et al.  TrackMate: An open and extensible platform for single-particle tracking. , 2017, Methods.

[6]  Hernan G. Garcia,et al.  Quantitative Imaging of Transcription in Living Drosophila Embryos Links Polymerase Activity to Patterning , 2013, Current Biology.

[7]  C. Fradin,et al.  LiveFly: A Toolbox for the Analysis of Transcription Dynamics in Live Drosophila Embryos. , 2018, Methods in molecular biology.

[8]  Melissa M. Harrison,et al.  Temporal control of gene expression by the pioneer factor Zelda through transient interactions in hubs , 2018, Nature Communications.

[9]  Philipp J. Keller,et al.  Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data , 2014, Nature Methods.

[10]  Aleksandra M. Walczak,et al.  Live Imaging of Bicoid-Dependent Transcription in Drosophila Embryos , 2013, Current Biology.

[11]  Julia Zeitlinger,et al.  Paused Pol II Coordinates Tissue Morphogenesis in the Drosophila Embryo , 2013, Cell.

[12]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[13]  M. Lagha,et al.  Lighting Up Gene Activation in Living Drosophila Embryos. , 2019, Methods in molecular biology.