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KMID : 1144120140040040338
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Biomedical Engineering Letters
2014 Volume.4 No. 4 p.338 ~ p.346
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Constructing 5D developing gene expression patterns without live animal imaging
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Peng Hanchuan
Myers Eugene W.
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Abstract
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Purpose: There are five intrinsic dimensions for spatiotemporally developing patterns of gene expression, i.e. three spatial dimensions X, Y, and Z, the time, and the co-localized developing expression of multiple genes. Observing the formation of these patterns shed new light in understanding basic cellular processes and the genetic regulatory/signaling network. Ideally one would like to image this five-dimensional process in vivo, but most of current live animal imaging studies limit one to narrow time windows or small volumes or a small number of co-stained genes of interest.
Methods: Here we demonstrate reconstructing this developing pattern computationally without live imaging. For Drosophila embryos with labeled mRNA gene expression, we have reconstructed developmental time series of co-localized gene expression patterns by automatically sorting three-dimensional in situ images of late blastoderm Drosophila embryos sampled randomly from the desired time interval.
Results: Specifically, we have developed a computational method to reconstruct such a developmental time series of the expression of a gene using 3D in situ images of a large number of Drosophila embryos sampled randomly from the desired time interval. Each sampled embryo in a data series has its nuclei labeled and two or more selected mRNA targets labeled via hybridization with probes of a different color. The multi-color images in such a series are automatically sorted into their temporal order by our new computational approach. We formulate this problem as that of learning a manifold, and solve it by first registering or aligning the images and then sorting them temporally by minimizing the alignment differences between adjacent images in a putative order. We present two approaches for ordering the data, the first based on minimum spanning trees and the second based on finding a principal curve through the data.
Conclusions: We have applied this computational approach to reconstruct the developmental time series of the expression of several genes in late blastoderm fly embryos.
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KEYWORD
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Gene expression, Manifold, Image analysis, Drosophila, Live imaging, Registration
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