Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila
| Autor: | Luís A. Nunes Amaral, Nicolás Peláez, Neda Bagheri, Richard W. Carthew, Sebastian Michal Bernasek |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Cell Mutant Protein expression law.invention 0302 clinical medicine Software law Loss of Function Mutation Gene expression Medicine and Health Sciences Morphogenesis Drosophila Proteins Wings Animal Cell Cycle and Cell Division Biology (General) Data Curation 0303 health sciences Microscopy Confocal biology Ecology Mosaicism Drosophila Melanogaster Eukaryota Gene Expression Regulation Developmental Animal Models Fluorescence Insects Imaginal disc medicine.anatomical_structure Computational Theory and Mathematics Imaginal Discs Experimental Organism Systems Cell Processes Modeling and Simulation Larva Quantitative Microscopy Drosophila Gene Cloning Drosophila melanogaster Anatomy Research Article Arthropoda QH301-705.5 Imaging Techniques Software ecosystem Computational biology Research and Analysis Methods Ecosystems 03 medical and health sciences Cellular and Molecular Neuroscience Annotation Model Organisms Confocal microscopy Ocular System Fluorescence Imaging medicine Genetics Animals Molecular Biology Techniques Gene Molecular Biology Ecology Evolution Behavior and Systematics 030304 developmental biology Spatial contextual awareness business.industry Ecology and Environmental Sciences Wild type Organisms RNA Biology and Life Sciences Computational Biology Cell Biology biology.organism_classification Invertebrates Animal Studies Eyes business Head 030217 neurology & neurosurgery Cloning Developmental Biology |
| Zdroj: | PLoS Computational Biology PLoS Computational Biology, Vol 16, Iss 3, p e1007406 (2020) |
| ISSN: | 1553-7358 1553-734X |
| Popis: | Mosaic analysis provides a means to probe developmental processes in situ by generating loss-of-function mutants within otherwise wildtype tissues. Combining these techniques with quantitative microscopy enables researchers to rigorously compare RNA or protein expression across the resultant clones. However, visual inspection of mosaic tissues remains common in the literature because quantification demands considerable labor and computational expertise. Practitioners must segment cell membranes or cell nuclei from a tissue and annotate the clones before their data are suitable for analysis. Here, we introduce Fly-QMA, a computational framework that automates each of these tasks for confocal microscopy images of Drosophila imaginal discs. The framework includes an unsupervised annotation algorithm that incorporates spatial context to inform the genetic identity of each cell. We use a combination of real and synthetic validation data to survey the performance of the annotation algorithm across a broad range of conditions. By contributing our framework to the open-source software ecosystem, we aim to contribute to the current move toward automated quantitative analysis among developmental biologists. Author summary Biologists use mosaic tissues to compare the behavior of genetically distinct cells within an otherwise equivalent context. The ensuing analysis is often limited to qualitative insight. However, it is becoming clear that quantitative models are needed to unravel the complexities of many biological systems. In this manuscript we introduce a computational framework that automates the quantification of mosaic analysis for Drosophila imaginal discs, a common setting for studies of developmental processes. The software extracts quantitative measurements from confocal images of mosaic tissues, rectifies any cross-talk between fluorescent reporters, and identifies clonally-related subpopulations of cells. Together, these functions allow users to rigorously ascribe changes in gene expression to the presence or absence of particular genes. We validate the performance of our framework using both real and synthetic data. We invite interested readers to apply these methods using our freely available software. |
| Databáze: | OpenAIRE |
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