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Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila

Bernasek, Sebastian M. and Peláez, Nicolás and Carthew, Richard W. and Bagheri, Neda and Amaral, Luís A. N. (2020) Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila. PLoS Computational Biology, 16 (3). Art. No. e1007406. ISSN 1553-734X. PMCID PMC7100978. https://resolver.caltech.edu/CaltechAUTHORS:20190920-100650519

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[img] Image (TIFF) (S1 Fig. Example clones in the larval fly eye) - Supplemental Material
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[img] Image (TIFF) (S2 Fig. Using background pixels to characterize bleedthrough contributions in the foreground) - Supplemental Material
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[img] Image (TIFF) (S3 Fig. Training a clone annotation model) - Supplemental Material
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[img] Image (TIFF) (S4 Fig. Label assignment using a trained clone annotation model) - Supplemental Material
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[img] Image (TIFF) (S5 Fig. Comparison of automated annotation with manually assigned labels) - Supplemental Material
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[img] Image (TIFF) (S6 Fig. Simulated growth of a synthetic cell culture) - Supplemental Material
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[img] Image (TIFF) (S7 Fig. Tunable generation of synthetic microscopy data) - Supplemental Material
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[img] Image (TIFF) (S9 Fig. Spatial context is most informative for large clones with ambiguous fluorescence) - Supplemental Material
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Abstract

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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1371/journal.pcbi.1007406DOIArticle
https://doi.org/10.1101/775783DOIDiscussion Paper
https://doi.org/10.21985/N2F207DOIData
https://doi.org/10.1371/journal.pcbi.1007406.s001DOIS1 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s002DOIS2 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s003DOIS3 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s004DOIS4 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s005DOIS5 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s006DOIS6 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s007DOIS7 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s008DOIS8 Fig.
https://doi.org/10.1371/journal.pcbi.1007406.s009DOIS9 Fig.
http://www.ncbi.nlm.nih.gov/pmc/articles/pmc7100978/PubMed CentralArticle
ORCID:
AuthorORCID
Bernasek, Sebastian M.0000-0002-1410-6178
Peláez, Nicolás0000-0001-9098-088X
Bagheri, Neda0000-0003-0146-4627
Amaral, Luís A. N.0000-0002-3762-789X
Additional Information:© 2020 Bernasek et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received: September 14, 2019; Accepted: January 27, 2020; Published: March 3, 2020. SMB and LANA were supported by the John and Leslie McQuown Gift. RWC was supported by NIH R35GM118144 (https://www.nih.gov). LANA, NB, and RWC were supported by NSF 1764421 (https://www.nsf.gov). LANA, NB, and RWC were supported by Simons Foundation 597491 (https://www.simonsfoundation.org). NP was supported by the HHMI Hanna H. Gray Fellowship (https://www.hhmi.org/programs/hanna-h-gray-fellows-program). In all cases, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data and software availability: We have distributed the automated mosaic analysis framework as an open-source python package available at https://sebastianbernasek.github.io/flyqma. The associated code repository contains resources designed to help users analyze their own microscope images. These include code documentation, a guide to getting started with Fly-QMA, and an interactive tutorial that uses example data to demonstrate the core features of the software. We also intend to incorporate Fly-QMA into future versions of FlyEye Silhouette, our open-source desktop application for quantitative analysis of the larval eye. The code used to generate synthetic microscopy data is also freely available at https://github.com/sebastianbernasek/growth. All segmented and annotated eye discs are accessible via our data repository (https://doi.org/10.21985/N2F207). Author Contributions Conceptualization: Sebastian M. Bernasek, Luı´s A. N. Amaral. Data curation: Sebastian M. Bernasek, Nicola´s Pela´ez. Formal analysis: Sebastian M. Bernasek. Funding acquisition: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Investigation: Nicola´s Pela´ez. Methodology: Sebastian M. Bernasek, Nicola´s Pela´ez, Luı´s A. N. Amaral. Project administration: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Resources: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Software: Sebastian M. Bernasek. Supervision: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Validation: Sebastian M. Bernasek. Visualization: Sebastian M. Bernasek. Writing – original draft: Sebastian M. Bernasek. Writing – review & editing: Sebastian M. Bernasek, Nicola´s Pela´ez, Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. The authors have declared that no competing interests exist. Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pcbi.1007406
Funders:
Funding AgencyGrant Number
John and Leslie McQuown GiftUNSPECIFIED
NIHR35GM118144
NSFDMS-1764421
Simons Foundation597491
Howard Hughes Medical Institute (HHMI)UNSPECIFIED
Issue or Number:3
PubMed Central ID:PMC7100978
Record Number:CaltechAUTHORS:20190920-100650519
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190920-100650519
Official Citation:Bernasek SM, Peláez N, Carthew RW, Bagheri N, Amaral LAN (2020) Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila. PLoS Comput Biol 16(3): e1007406. https://doi.org/10.1371/journal.pcbi.1007406
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:98774
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:20 Sep 2019 17:26
Last Modified:23 Apr 2020 18:39

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