Image processing challenges in the creation of spatiotemporal gene expression atlases of developing embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

[1]  Carlos Castro-Gonzalez,et al.  Towards a digital model of zebrafish embryogenesis. Integration of cell tracking and gene expression quantification , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[2]  James F Amatruda,et al.  Zebrafish as a cancer model system. , 2002, Cancer cell.

[3]  Alexander F Schier,et al.  Molecular genetics of axis formation in zebrafish. , 2005, Annual review of genetics.

[4]  Alison Abbott.  Microscopic marvels: Seeing the system , 2009, Nature.

[5]  F. Del Bene,et al.  Optical Sectioning Deep Inside Live Embryos by Selective Plane Illumination Microscopy , 2004, Science.

[6]  Allan R. Jones,et al.  Genome-wide atlas of gene expression in the adult mouse brain , 2007, Nature.

[7]  Le A. Trinh,et al.  Programmable in situ amplification for multiplexed imaging of mRNA expression , 2010, Nature Biotechnology.

[8]  L. Ramakrishnan,et al.  Multiplex fluorescent in situ hybridization in zebrafish embryos using tyramide signal amplification. , 2005, Zebrafish.

[9]  R. Tsien,et al.  The Fluorescent Toolbox for Assessing Protein Location and Function , 2006, Science.

[10]  John Reinitz,et al.  FlyEx, the quantitative atlas on segmentation gene expression at cellular resolution , 2008, Nucleic Acids Res..

[11]  Alessandro Sarti,et al.  Cells Segmentation From 3-D Confocal Images of Early Zebrafish Embryogenesis , 2010, IEEE Transactions on Image Processing.

[12]  M. Unser,et al.  The colored revolution of bioimaging , 2006, IEEE Signal Processing Magazine.

[13]  Luc Vincent,et al.  Morphological Area Openings and Closings for Grey-scale Images , 1994 .

[14]  P. Bourgine,et al.  Cell Lineage Reconstruction of Early Zebrafish Embryos Using Label-Free Nonlinear Microscopy , 2010, Science.

[15]  M. J. Ledesma-Carbayo,et al.  An automatic quantification and registration strategy to create a gene expression atlas of zebrafish embryogenesis , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[16]  Karl Rohr,et al.  Spline-based elastic image registration: integration of landmark errors and orientation attributes , 2003, Comput. Vis. Image Underst..

[17]  Markus Reischl,et al.  Zebrafish embryos as models for embryotoxic and teratological effects of chemicals. , 2009, Reproductive toxicology.

[18]  O. Rubel,et al.  Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data , 2010, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[19]  Konstantin A Lukyanov,et al.  Fluorescent proteins as a toolkit for in vivo imaging. , 2005, Trends in biotechnology.

[20]  Thomas D Pollard,et al.  Counting Cytokinesis Proteins Globally and Locally in Fission Yeast , 2005, Science.

[21]  Miguel A. Luengo-Oroz,et al.  Can voronoi diagram model cell geometries in early sea-urchin embryogenesis? , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[22]  Charless C. Fowlkes,et al.  A Quantitative Spatiotemporal Atlas of Gene Expression in the Drosophila Blastoderm , 2008, Cell.

[23]  Scott E. Fraser,et al.  Digitizing life at the level of the cell: high-performance laser-scanning microscopy and image analysis for in toto imaging of development , 2003, Mechanisms of Development.

[24]  S. Pauls,et al.  - Ortega A zebrafish histone variant H 2 A . F / Z and a transgenic H 2 A . F / Z : GFP fusion protein for in vivo studies of embryonic development , 2022 .

[25]  Philipp J. Keller,et al.  Quantitative in vivo imaging of entire embryos with Digital Scanned Laser Light Sheet Fluorescence Microscopy , 2008, Current Opinion in Neurobiology.

[26]  J. Campos-Ortega,et al.  A zebrafish histone variant H2A.F/Z and a transgenic H2A.F/Z:GFP fusion protein for in vivo studies of embryonic development , 2001, Development Genes and Evolution.

[27]  Scott E. Fraser,et al.  Imaging in Systems Biology , 2007, Cell.

[28]  F. Veronesi,et al.  Cells tracking in a live zebrafish embryo , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[29]  B. Hamann,et al.  Visual Exploration of Three-Dimensional Gene Expression Using Physical Views and Linked Abstract Views , 2007, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[30]  Philipp J. Keller,et al.  Reconstruction of Zebrafish Early Embryonic Development by Scanned Light Sheet Microscopy , 2008, Science.

[31]  E. Myers,et al.  A 3D Digital Atlas of C. elegans and Its Application To Single-Cell Analyses , 2009, Nature Methods.

[32]  Andrew C. Oates,et al.  Quantitative approaches in developmental biology , 2009, Nature Reviews Genetics.

[33]  E. Davidson,et al.  Gene Regulatory Networks and the Evolution of Animal Body Plans , 2006, Science.

[34]  Hanchuan Peng,et al.  Bioimage informatics: a new area of engineering biology , 2008, Bioinform..

[35]  P. Bourgine,et al.  Cell tracking in fluorescence images of embryogenesis processes with morphological reconstruction by 4D-tubular structuring elements , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[36]  Eric H Davidson,et al.  Confocal quantification of cis-regulatory reporter gene expression in living sea urchin. , 2006, Developmental biology.