Literature DB >> 20494971

CORSEN, a new software dedicated to microscope-based 3D distance measurements: mRNA-mitochondria distance, from single-cell to population analyses.

Laurent Jourdren1, Thierry Delaveau, Emelie Marquenet, Claude Jacq, Mathilde Garcia.   

Abstract

Recent improvements in microscopy technology allow detection of single molecules of RNA, but tools for large-scale automatic analyses of particle distributions are lacking. An increasing number of imaging studies emphasize the importance of mRNA localization in the definition of cell territory or the biogenesis of cell compartments. CORSEN is a new tool dedicated to three-dimensional (3D) distance measurements from imaging experiments especially developed to access the minimal distance between RNA molecules and cellular compartment markers. CORSEN includes a 3D segmentation algorithm allowing the extraction and the characterization of the cellular objects to be processed--surface determination, aggregate decomposition--for minimal distance calculations. CORSEN's main contribution lies in exploratory statistical analysis, cell population characterization, and high-throughput assays that are made possible by the implementation of a batch process analysis. We highlighted CORSEN's utility for the study of relative positions of mRNA molecules and mitochondria: CORSEN clearly discriminates mRNA localized to the vicinity of mitochondria from those that are translated on free cytoplasmic polysomes. Moreover, it quantifies the cell-to-cell variations of mRNA localization and emphasizes the necessity for statistical approaches. This method can be extended to assess the evolution of the distance between specific mRNAs and other cellular structures in different cellular contexts. CORSEN was designed for the biologist community with the concern to provide an easy-to-use and highly flexible tool that can be applied for diverse distance quantification issues.

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Year:  2010        PMID: 20494971      PMCID: PMC2885679          DOI: 10.1261/rna.1996810

Source DB:  PubMed          Journal:  RNA        ISSN: 1355-8382            Impact factor:   4.942


  18 in total

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